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<xml><records><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. Blachnik</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Leszek Rutkowski</style></author><author><style face="normal" font="default" size="100%">Marcin Korytkowski</style></author><author><style face="normal" font="default" size="100%">Rafał Scherer</style></author><author><style face="normal" font="default" size="100%">Ryszard Tadeusiewicz</style></author><author><style face="normal" font="default" size="100%">Zadeh Lotfia</style></author><author><style face="normal" font="default" size="100%">Jacek Zurada</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Do we need complex models for gestures? A comparison of data representation and preprocessing methods for hand gesture recognition</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2012</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Artificial Intelligence and Soft Computing Lecture Notes in Computer Science 7267</style></secondary-title><pages><style face="normal" font="default" size="100%">477–485</style></pages><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimation of the number of states for gesture recognition with Hidden Markov Models based on the number of critical points in time sequence</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2012</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Pattern Recognition Letters</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Gesture data modeling and classification based on critical points approximation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2011</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Advances in Intelligent and Soft Computing, 2011, Volume 95, Computer Recognition Systems 4,</style></secondary-title><pages><style face="normal" font="default" size="100%">365–373</style></pages><volume><style face="normal" font="default" size="100%">95</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Sebastian Opozda</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">M. Kosiedowski</style></author><author><style face="normal" font="default" size="100%">E. Kuśmierek</style></author><author><style face="normal" font="default" size="100%">A. Bęben</style></author><author><style face="normal" font="default" size="100%">P. Krawiec</style></author><author><style face="normal" font="default" size="100%">A. Stroiński</style></author><author><style face="normal" font="default" size="100%">Wojciech Burakowski</style></author><author><style face="normal" font="default" size="100%">Piotr Krawiec</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Aplikacje Sieci Świadomej Treści</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2013</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Inżynieria Internetu przyszłości część 2</style></secondary-title><section><style face="normal" font="default" size="100%">Aplikacje Sieci Świadomej Treści</style></section><isbn><style face="normal" font="default" size="100%">978-83-7814-099-3</style></isbn><publisher><style face="normal" font="default" size="100%">Oficyna Wydawnicza PW</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Joanna Domańska</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Przemysław Kowalski</style></author><author><style face="normal" font="default" size="100%">Sławomir Nowak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling of Internet 3D Traffic Using Hidden Markov Models</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2009</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Advances in Intelligent and Soft Computing</style></secondary-title><volume><style face="normal" font="default" size="100%">64</style></volume><section><style face="normal" font="default" size="100%">Modeling of Internet 3D Traffic Using Hidden Markov Models</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Artykuł podejmuje temat modelowania złożoności przesyłu siatek progresywnych 3D.&lt;/p&gt;&#13;
</style></abstract><publisher><style face="normal" font="default" size="100%">Springer Verlag</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Jaroslaw Miszczak</style></author><author><style face="normal" font="default" size="100%">Zbigniew Puchała</style></author><author><style face="normal" font="default" size="100%">Tadeusz Czachórski</style></author><author><style face="normal" font="default" size="100%">Stanisław Kozielski</style></author><author><style face="normal" font="default" size="100%">Urszula Stańczyk</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Eigengestures for natural human computer interface</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2011</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Man-Machine Interactions 2</style></secondary-title><pages><style face="normal" font="default" size="100%">49–56</style></pages><abstract><style face="normal" font="default" size="100%">We present the application of Principal Component Analysis for data acquired during the design of a natural gesture interface. We investigate the concept of an eigengesture for motion capture hand gesture data and present the visualisation of principal components obtained in the course of conducted experiments. We also show the influence of dimensionality reduction on reconstructed gesture data quality.</style></abstract><isbn><style face="normal" font="default" size="100%">978-3-642-23168-1</style></isbn><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin / Heidelberg</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">arXiv:1105.1293</style></notes></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author><author><style face="normal" font="default" size="100%">Tadeusz Czachórski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Andrzej Grzywak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Internet w społeczeństwie informacyjnym - Podstawowe problemy Internetu</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2004</style></year></dates><section><style face="normal" font="default" size="100%">Badania symulacyjne pakietowych sieci optycznych o dowolnych topologiach</style></section><publisher><style face="normal" font="default" size="100%">Wydawnictwa Naukowo-Techniczne</style></publisher><pub-location><style face="normal" font="default" size="100%">Warszawa</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Kształtowanie ruchu w routerach pracujących w systemie Linux</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2002</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Studia Informatica</style></secondary-title><volume><style face="normal" font="default" size="100%">23</style></volume><number><style face="normal" font="default" size="100%">2A</style></number><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Andrzej Grzywak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Współczesne problemy sieci komputerowych - Nowe technologie</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2004</style></year></dates><section><style face="normal" font="default" size="100%">Kształtowanie ruchu w transmisjach wideo wykorzystujących kompresję falkową</style></section><abstract><style face="normal" font="default" size="100%">Rozdział przedstawia budowę i wyniki badań symulacyjnych mechanizmu sterowania transmisją sieciową skalowalnego strumienia wideo. Skalowalność typu SNR otrzymywana jest z wykorzystaniem transformaty falkowej, a sterowanie zrealizowane jest z użyciem regulatora proporcjonalno-różniczkującego w oparciu o pomiar opóźnień kolejnych ramek.</style></abstract><publisher><style face="normal" font="default" size="100%">Wydawnictwa Naukowo-Techniczne</style></publisher><pub-location><style face="normal" font="default" size="100%">Warszawa</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">- Borcochi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transmission of scalable video streams</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style face="normal" font="default" size="100%">4</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Proceedings from the 4th Euro-NGI Workshop on New trends in network architectures and services</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Andrzej Grzywak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Współczesne problemy sieci komputerowych - Zastosowanie i bezpieczeństwo</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2004</style></year></dates><section><style face="normal" font="default" size="100%">Integracja systemów autoryzacji użytkowników w sieciowym środowisku heterogenicznym</style></section><abstract><style face="normal" font="default" size="100%">Rozdział prezentuje jednolity system autoryzacji użytkowników umożliwiający dostęp do wszytskich zasobów sieci za pomocą jednego hasła. Zaprezentowano rozwiązanie wdrożone w IITiS PAN. Autorzy wykorzystali oprogramowanie firmy Microsoft oraz pakiety dostępne na zasadach open source takie jak: Samba, Dovecot, Apache oraz smbpamd.</style></abstract><publisher><style face="normal" font="default" size="100%">Wydawnictwa Naukowo-Techniczne</style></publisher><pub-location><style face="normal" font="default" size="100%">Warszawa</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Marek Kurzyński</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computer Recognition Systems 2</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2007</style></year></dates><section><style face="normal" font="default" size="100%">Local analysis of stereo image pairs with polynomial series</style></section><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Andrzej Cader</style></author><author><style face="normal" font="default" size="100%">Leszek Rutkowski</style></author><author><style face="normal" font="default" size="100%">Ryszard Tadeusiewicz</style></author><author><style face="normal" font="default" size="100%">Jacek Zurada</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Artificial Intelligence and Soft Computing</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2006</style></year></dates><section><style face="normal" font="default" size="100%">Object recognition with kernel PCA</style></section><publisher><style face="normal" font="default" size="100%">Academic Publishing House EXIT</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Detection of interest points on 3D data: extending the Harris operator</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2009</style></year></dates><secondary-title><style face="normal" font="default" size="100%">6th International Conference on Computer Recognition Systems</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Image Language Terminal Symbols from Feature Analysis</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2007</style></year></dates><secondary-title><style face="normal" font="default" size="100%">IEEE International Workshop on Imaging Systems and Techniques – IST</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of fGn and http requests traces using localized multiscale H parameter estimation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2005</style></year></dates><secondary-title><style face="normal" font="default" size="100%"/></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Representing single-link traffic quality with kernel PCA</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2006</style></year></dates><publisher><style face="normal" font="default" size="100%">Instytut Informatyki Teoretycznej i Stosowanej</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling Connection State with Kernel PCA</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2005</style></year></dates><secondary-title><style face="normal" font="default" size="100%">2nd EuroNGI Workshop on New Trends in Modeling, Quantitative Methods and Measurements</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modelowanie stacji roboczych w sieci ATM przy użyciu symulatora OMNeT++</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2002</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Studia Informatica</style></secondary-title><volume><style face="normal" font="default" size="100%">23</style></volume><number><style face="normal" font="default" size="100%">2A</style></number><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Andrzej Grzywak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Internet w społeczeństwie informacyjnym - Podstawowe problemy Internetu</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2004</style></year></dates><section><style face="normal" font="default" size="100%">Skalowalna kompresja wideo na potrzeby transmisji sieciowych</style></section><abstract><style face="normal" font="default" size="100%">Artykuł prezentuje przegląd i badania zagadnienia skalowalności w stosowanych współcześnie technologiach kodowania sygnału wideo. W pierwszej części prezentowane są modele skalowalności przyjęte w stosowanych i opracowywanych standardach kompresji, w drugiej przedstawione są wyniki badań jakości transmisji skalowalnych strumieni w różnorodnych warunkach obciążenia. Całość zamknięta jest podsumowaniem możliwości sterowania transmisją sieciową takich strumieni.</style></abstract><publisher><style face="normal" font="default" size="100%">Wydawnictwa Naukowo-Techniczne</style></publisher><pub-location><style face="normal" font="default" size="100%">Warszawa</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Sławomir Nowak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Experimental rate distortion analysis of image coder with contourlet transform and SPIHT algorithm</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2008</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Theoretical and Applied Informatics</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Zbigniew Puchała</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Context selection for efficient bit modeling of contourlet transform coefficients</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2007</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Theoretical and Applied Informatics</style></secondary-title><pages><style face="normal" font="default" size="100%">135–146</style></pages><volume><style face="normal" font="default" size="100%">19</style></volume><number><style face="normal" font="default" size="100%">2</style></number><abstract><style face="normal" font="default" size="100%">Contourlet transform is named as one possible successor to the wavelet transform as a tool for representation of image information. It has better properties in representation of edge information, which make it suitable for designing image compression systems. It is not clear, however, how to exploit the statistical structure of the coefficients generated by this transform in effective compression algorithm. In this work, authors propose a general, nonparametric method to achieve context map, thus allowing for efficient application of EBCOT/JPEG 2000 bit modeling and encoding approach to contourlet transformed images. The article presents the derivation of the method and experiments performed on a publicly available image set. Keywords: contourlet transform, coefficient bit modeling, context estimation</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Sebastian Opozda</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Choosing and Modeling the Hand Gesture Database for a Natural User Interface</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2012</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Gesture and Sign Language in Human-Computer Interaction and Embodied Communication</style></secondary-title><edition><style face="normal" font="default" size="100%">Lecture Notes in Artificial Intelligence</style></edition><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Sebastian Opozda</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Choosing and modeling hand gesture database for natural user interface</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2011</style></year></dates><secondary-title><style face="normal" font="default" size="100%">GW 2011: the 9th International Gesture in Embodied Communication and Human-Computer InteractionWorkshop</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Sebastian Opozda</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Unsupervised Parameter Selection for Gesture Recognition with Vector Quantization and Hidden Markov Models</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2011</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science, Human-Computer Interaction – INTERACT</style></secondary-title><volume><style face="normal" font="default" size="100%">6949</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Krzysztof Skabek</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Laboratory for the exploration of virtual 3D environments</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2009</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Annual Report 2009</style></secondary-title><pages><style face="normal" font="default" size="100%">57–59</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Leszek Rutkowski</style></author><author><style face="normal" font="default" size="100%">Marcin Korytkowski</style></author><author><style face="normal" font="default" size="100%">Rafał Scherer</style></author><author><style face="normal" font="default" size="100%">Ryszard Tadeusiewicz</style></author><author><style face="normal" font="default" size="100%">Lotfi Zadeh</style></author><author><style face="normal" font="default" size="100%">Jacek Zurada</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Surface Mixture Models for the Optimization of Object Boundary Representation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science 8467</style></secondary-title><pages><style face="normal" font="default" size="100%">703–714</style></pages><isbn><style face="normal" font="default" size="100%">978-3-319-07172-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. Kosiedowski</style></author><author><style face="normal" font="default" size="100%">E. Kuśmierek</style></author><author><style face="normal" font="default" size="100%">A. Stroiński</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Sebastian Opozda</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">A. Bęben</style></author><author><style face="normal" font="default" size="100%">P. Krawiec</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Aplikacje sieci świadomej treści</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2012</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Przegląd telekomunikacyjny</style></secondary-title><pages><style face="normal" font="default" size="100%">1491–1502</style></pages><number><style face="normal" font="default" size="100%">8-9</style></number><abstract><style face="normal" font="default" size="100%">Artykuł przedstawia aplikacje korzystające z sieci świadomej treści PI CAN opracowanej w ramach projektu Inżynieria Internetu Przyszłości (IIP)1. Są to trzy aplikacje oferujące dostęp do treści multimedialnych: HomeNetMedia dla celów rozrywki, Rozproszone Wirtualne Muzeum dla edukacji oraz Biblioteka Cyfrowa Pacjenta dla przekazywania informacji medycznej. Scharakteryzowana została funkcjonalność sieci PI CAN z punktu widzenia aplikacji wraz z zasadami współpracy z użytkownikami, tj. dostawcami i konsumentami treści. Poszczególne aplikacje omówione zostały ze wskazaniem sposobu wykorzystania sieci świadomej treści oraz implementacji usług zewnętrznych powiązanych z siecią PI CAN specyficznych dla aplikacji. Przedstawione zostały również wyniki integracji poszczególnych aplikacji z siecią PI CAN oraz wyniki przeprowadzonych testów.</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sławomir Nowak</style></author><author><style face="normal" font="default" size="100%">Joanna Domańska</style></author><author><style face="normal" font="default" size="100%">Mateusz Nowak</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Progressive 3D meshes transmission: traffic generating and simulation evaluation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style face="normal" font="default" size="100%">11</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Theoretical and Applied Informatics</style></secondary-title><pages><style face="normal" font="default" size="100%">247–259</style></pages><volume><style face="normal" font="default" size="100%">22</style></volume><number><style face="normal" font="default" size="100%">4</style></number><abstract><style face="normal" font="default" size="100%">The paper presents issues related to the progressive transmission of 3D meshes in clientserver architecture. A tool generating network traffic for different 3D scenes and scenarios is presented. The objective was to evaluate the transmission dynamics and possible impact of 3D traffic on the amount of data available in VR browsing client, which relates to browsing QoE (Quality of Experience). Simulation studies were carried out and HMM model of traffic generated by 3D server was worked out, planned for use in modeling works on future internet protocols, servicing 3D traffic.</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">DOI: 10.2478/v10179-010-0012-2</style></notes></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sławomir Nowak</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">REMOTE VIRTUAL REALITY: EXPERIMENTAL INVESTIGATIONSOF PROGRESSIVE 3D MESH TRANSMISSION IN IP NETWORKS</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2010</style></year></dates><abstract><style face="normal" font="default" size="100%">Performance Modelling and Evaluation of Heterogeneous Networks, proc. HETNET 2010.</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards a natural gesture interface: LDA-based gesture separability</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2011</style></year></dates><urls><style face="normal" font="default" size="100%">https://arxiv.org/abs/1109.5034</style></urls><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" 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font="default" size="100%">Ryszard Choraś</style></author><author><style face="normal" font="default" size="100%">Antoni Zabłudowski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">3D Mesh Identification Using Random Walks and Hidden Markov Models</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2009</style></year></dates><secondary-title><style face="normal" font="default" size="100%"/></secondary-title><pages><style face="normal" font="default" size="100%">302–308</style></pages><publisher><style face="normal" font="default" size="100%">Academy Publishing House EXIT</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arkadiusz 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Przedstawiono architekturę aplikacji WWW i różne rozwiązania stosowane do tworzenia takich aplikacji. Zaprezentowano wyniki badań porównawczych przeprowadzonych dla tych rozwiązań. 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Prace miały charakter zarówno doświadczalno-pomiarowy, jak i analityczny. Określono zależność funkcyjną pomiędzy parametrami ruchu sieci ATM, natężeniem strumienia wideo a jakością transmisji multimedialnej. 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Stera</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Virtual Museum as an Example of 3D Content Distribution in the Architecture of a Future Internet</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2011</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Computer Networks 2011. Communications in Computer and Information Science 160.</style></secondary-title><pages><style face="normal" font="default" size="100%">459–464</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">E. Switonski</style></author><author><style face="normal" font="default" size="100%">D. Tejszerska</style></author><author><style face="normal" font="default" size="100%">M. Gzik</style></author><author><style face="normal" font="default" size="100%">W. Wolanski</style></author><author><style face="normal" font="default" size="100%">B. Gzik-Zroska</style></author><author><style face="normal" font="default" size="100%">M. Mandera</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interaktywna kinezyterapia dzieci z płaskostopiem</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2009</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Aktualne Problemy Biomechaniki</style></secondary-title><pages><style face="normal" font="default" size="100%">211–214</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Sławomir Nowak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">IMAGE CODING WITH CONTOURLET / WAVELET TRANSFORMS AND SPIHT ALGORITHM:AN EXPERIMENTAL STUDY</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2009</style></year></dates><secondary-title><style face="normal" font="default" size="100%">proc. of IMAGAPP 2009, International Conference on Imaging Theory and Applications, Lisboa, Portugal, 2009.</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">T. Białecki</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Andrzej Kwiecień</style></author><author><style face="normal" font="default" size="100%">Andrzej Grzywak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Wysokowydajne sieci komputerowe - Zastosowanie i bezpieczeństwo</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2005</style></year></dates><section><style face="normal" font="default" size="100%">Mechanizm skalowalnej kompresji wykorzystujący standard JPEG2000 w zastosowaniach sieciowych</style></section><abstract><style face="normal" font="default" size="100%">W rozdziale przedstawiono możliwości wykorzystania standardu JPEG-2000 do kodowania strumieni przesyłanych przez kanał transmisyjny o wysokim współczynniku błędu i start. Scharakteryzowano metodę kodowania i wynikające z niej cechy skalowalności. W dalszej części opisano zastosowany model i przeprowadzone badania dotyczące stabilizacji jakości prezentowanych sekwencji obrazów z wykorzystaniem informacji nadmiarowej. Pokazano, że kodowanie obrazów ruchomych oparte na warstwach i płaszczyznach bitowych w połączeniu z kodami nadmiarowymi poprawia jakość prezentacji.</style></abstract><isbn><style face="normal" font="default" size="100%">83-206-1573-9</style></isbn><publisher><style face="normal" font="default" size="100%">Wydawnictwa Komunikacji i Łączności</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">T. Białecki</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Andrzej Kwiecień</style></author><author><style face="normal" font="default" size="100%">Kazimiera Wódz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Techniczne i społeczne problemy zastosowania Internetu</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2005</style></year></dates><section><style face="normal" font="default" size="100%">JPEG 2000 w transmisjach sieciowych - wpływ współczynnika strat na jakość obrazu wideo</style></section><abstract><style face="normal" font="default" size="100%">W rozdziale przedstawiono analizę mechanizmu utrzymania jakości prezentacji strumienia obrazów JPEG 2000 w warunkach transmisji z utratą danych z wykorzystaniem dodatkowej informacji nadmiarowej. Kolejne podrozdziały przedstawiają: teoretyczną analizę zagadnienia skalowanej transmisji wideo w środowisku o wysokiej stopie błędu z wykorzystaniem informacji korekcyjnej, opracowane stanowisko badawcze, wyniki badań i podsumowanie.</style></abstract><isbn><style face="normal" font="default" size="100%">83-206-1590-9</style></isbn><publisher><style face="normal" font="default" size="100%">Wydawnictwa Komunikacji i Łączności</style></publisher><pub-location><style face="normal" font="default" size="100%">Wydawnictwa Komunikacji l Łaczności</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Domino</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Zbigniew Łaskarzewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Classification of LPG clients using the Hurst exponent and the correlation coeficient</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style face="normal" font="default" size="100%">2015</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Theoretical and Applied Informatics</style></secondary-title><urls><style face="normal" font="default" size="100%">http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.baztech-1ba91297-f921-4524-927c-381996c36512</style></urls><electronic-resource-num><style face="normal" font="default" size="100%"> 10.20904/271013</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">13–24</style></pages><volume><style face="normal" font="default" size="100%">27</style></volume><issue><style face="normal" font="default" size="100%">1</style></issue><section><style face="normal" font="default" size="100%">13</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper we present the analysis of the gas usage for different types of buildings. First, we introduce the classical theory of building heating. This allows the establishment of theoretical relations between gas consumption time series and the outside air temperature for different types of buildings, residential and industrial. These relations imply dierent auto-correlations of gas usage time series as well as different cross-correlations between gas consumption and temperature time series for different types of buildings. Therefore, the autocorrelation and the cross-correlation were used to classify the buildings into three classes: housing, housing with high thermal capacity, and industry. The Hurst exponent was calculated using the global DFA to investigate auto-correlation, while the Kendall's τ rank coeficient was calculated to investigate cross-correlation&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Leszek Rutkowski</style></author><author><style face="normal" font="default" size="100%">Marcin Korytkowski</style></author><author><style face="normal" font="default" size="100%">Rafal Scherer</style></author><author><style face="normal" font="default" size="100%">Ryszard Tadeusiewicz</style></author><author><style face="normal" font="default" size="100%">Lotfi Zadeh</style></author><author><style face="normal" font="default" size="100%">Jacek Zurada</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Experimental Evaluation of Selected Approaches to Covariance Matrix Regularization</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2015</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Artificial Intelligence and Soft Computing</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1007/978-3-319-19369-4_35</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">391-401</style></pages><volume><style face="normal" font="default" size="100%">9120</style></volume><isbn><style face="normal" font="default" size="100%">978-3-319-19368-7</style></isbn><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Parameter Estimation for HOSVD-based Approximation of Temporally Coherent Mesh Sequences</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.5220/0005723501380145</style></electronic-resource-num><isbn><style face="normal" font="default" size="100%">978-989-758-175-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Semi-supervised hyperspectral classification from a small number of training samples using a co-training approach</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">ISPRS Journal of Photogrammetry and Remote Sensing</style></secondary-title><urls><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S0924271616303446</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.isprsjprs.2016.08.011</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">60 - 76</style></pages><volume><style face="normal" font="default" size="100%">121</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Two Stage SVM Classification for Hyperspectral Data</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.5220/0005828103870391</style></electronic-resource-num><isbn><style face="normal" font="default" size="100%">978-989-758-173-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Performance of Interest Point Descriptors on Hyperspectral Images</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.5220/0005785001980203</style></electronic-resource-num><isbn><style face="normal" font="default" size="100%">978-989-758-175-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Dariusz Kurzyk</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Quantum hidden Markov models based on transition operation matrices</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2017</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Quantum Information Processing</style></secondary-title><urls><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/s11128-017-1544-8</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.1007/s11128-017-1544-8</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">101</style></pages><volume><style face="normal" font="default" size="100%">16</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this work, we extend the idea of quantum Markov chains (Gudder in J Math Phys 49(7):072105 [3]) in order to propose quantum hidden Markov models (QHMMs). For that, we use the notions of transition operation matrices and vector states, which are an extension of classical stochastic matrices and probability distributions. Our main result is the Mealy QHMM formulation and proofs of algorithms needed for application of this model: Forward for general case and Vitterbi for a restricted class of QHMMs. We show the relations of the proposed model to other quantum HMM propositions and present an example of application.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Krzysztof Domino</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of hyperspectral imaging and Machine Learning methods for the detection of gunshot residue patterns</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style face="normal" font="default" size="100%">07/2018</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Forensic Science International</style></secondary-title><urls><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S0379073818303657</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.forsciint.2018.06.040</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">290</style></volume><section><style face="normal" font="default" size="100%">227</style></section><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Adaptive, Hubness-Aware Nearest Neighbour Classifier with Application to Hyperspectral Data</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2018</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Computer and Information Sciences</style></secondary-title><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We present an extension of the Nearest Neighbour classifier that can adapt to sample imbalances in local regions of the dataset. Our approach uses the hubness statistic as a measure of a relation between new samples and the existing training set. This allows to estimate the upper limit of neighbours that vote for the label of the new instance. This estimation improves the classifier performance in situations where some classes are locally under-represented. The main focus of our method is to solve the problem of local undersampling that exists in hyperspectral data classification. Using several well-known Machine Learning and hyperspectral datasets, we show that our approach outperforms standard and distance-weighted kNN, especially for high values of k.&lt;/p&gt;&#13;
</style></abstract><isbn><style face="normal" font="default" size="100%">978-3-030-00840-6</style></isbn><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style face="normal" font="default" size="100%">March</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">IEEE Geoscience and Remote Sensing Letters</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1109/LGRS.2018.2868862</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">467-471</style></pages><volume><style face="normal" font="default" size="100%">16</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bartosz Grabowski</style></author><author><style face="normal" font="default" size="100%">Wojciech Masarczyk</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Agata Mendys</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automatic pigment identification from hyperspectral data</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2018</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Cultural Heritage</style></secondary-title><urls><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S1296207417306544</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.culher.2018.01.003</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">1 - 12</style></pages><volume><style face="normal" font="default" size="100%">31</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Art objects conservation or historical analysis necessitates a thorough knowledge of materials used by the artist and their subsequent changes. In the case of paintings this requires the ability to correctly identify the pigments that were used for creation or later restoration of the artwork. This is a challenging problem, as the applied method should be non-contact, robust for the wide variety of chemical substances used and straightforward in the interpretation. Recently, the hyperspectral imaging has emerged as a promising measuring methodology for this kind of the artwork analysis; the combination of acquiring spectral information and planar (photography-like) pixel arrangement provides a lot of potential for material characterization. While initial studies of hyperspectral imaging application to art objects analysis are encouraging, the difficulties of working with its multidimensional data are acknowledged; in many cases complex algorithms are required to fully utilize its potential. In this paper, we study the problem of algorithm design for pigment identification based on a hyperspectral image of a painting. We combine various processing steps to achieve a robust solution requiring minimal user intervention. Using a special set of paintings and a reference pigment database we demonstrate the viability of applying this method in the pigment recognition setting. Our results confirm the potential of using hyperspectral imaging in the art conservation setting, and based on them we discuss the potential construction and elements of such an algorithm.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wojciech Masarczyk</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Bartosz Grabowski</style></author><author><style face="normal" font="default" size="100%">Mateusz Ostaszewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Remote Sensing</style></secondary-title><urls><style face="normal" font="default" size="100%">https://arxiv.org/abs/1909.05507</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.3390/rs12162653</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">12</style></volume><issue><style face="normal" font="default" size="100%">16</style></issue><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Hyperspectral imaging is a rich source of data, allowing for a multitude of effective applications. However, such imaging remains challenging because of large data dimension and, typically, a small pool of available training examples. While deep learning approaches have been shown to be successful in providing effective classification solutions, especially for high dimensional problems, unfortunately they work best with a lot of labelled examples available. The transfer learning approach can be used to alleviate the second requirement for a particular dataset: first the network is pre-trained on some dataset with large amount of training labels available, then the actual dataset is used to fine-tune the network. This strategy is not straightforward to apply with hyperspectral images, as it is often the case that only one particular image of some type or characteristic is available. In this paper, we propose and investigate a simple and effective strategy of transfer learning that uses unsupervised pre-training step without label information. This approach can be applied to many of the hyperspectral classification problems. The performed experiments show that it is very effective at improving the classification accuracy without being restricted to a particular image type or neural network architecture. The experiments were carried out on several deep neural network architectures and various sizes of labeled training sets. The greatest improvement in overall accuracy on the Indian Pines and Pavia University datasets is over 21 and 13 percentage points, respectively. An additional advantage of the proposed approach is the unsupervised nature of the pre-training step, which can be done immediately after image acquisition, without the need of the potentially costly expert’s time.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Krzysztof Domino</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style face="normal" font="default" size="100%">2019</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">PP-RAI'2019</style></secondary-title><urls><style face="normal" font="default" size="100%">https://arxiv.org/abs/1808.03513</style></urls><pages><style face="normal" font="default" size="100%">p. 121</style></pages><isbn><style face="normal" font="default" size="100%">978-83-943803-2-8</style></isbn><publisher><style face="normal" font="default" size="100%">Wroclaw University of Science and Technology</style></publisher><pub-location><style face="normal" font="default" size="100%">Wrocław, Poland</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bartosz Grabowski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Mateusz Ostaszewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Unsupervised deep learning approach to hyperspectral anomaly detection</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">PP-RAI'2019</style></secondary-title><isbn><style face="normal" font="default" size="100%">978-83-943803-2-8</style></isbn><publisher><style face="normal" font="default" size="100%">Wroclaw University of Science and Technology</style></publisher><pub-location><style face="normal" font="default" size="100%">Wrocław, Poland</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Anomaly detection in hyperspectral remote sensing images</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><secondary-title><style face="normal" font="default" size="100%"/></secondary-title><urls><style face="normal" font="default" size="100%">https://www.elsevier.com/books/hyperspectral-remote-sensing/pandey/978-0-08-102894-0</style></urls><isbn><style face="normal" font="default" size="100%">978-0-08-102894-0</style></isbn><publisher><style face="normal" font="default" size="100%">Elsevier</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Bartosz Grabowski</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style face="normal" font="default" size="100%">11/2020</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Sensors</style></secondary-title><urls><style face="normal" font="default" size="100%">https://www.mdpi.com/1424-8220/20/22/6666</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.3390/s20226666</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">20</style></volume><issue><style face="normal" font="default" size="100%">Recent Advances in Multi- and Hyperspectral Image Analysis</style></issue><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In recent years, growing interest in deep learning neural networks has raised a question on how they can be used for effective processing of high-dimensional datasets produced by hyperspectral imaging (HSI). HSI, traditionally viewed as being within the scope of remote sensing, is used in non-invasive substance classification. One of the areas of potential application is forensic science, where substance classification on the scenes is important. An example problem from that area—blood stain classification—is a case study for the evaluation of methods that process hyperspectral data. To investigate the deep learning classification performance for this problem we have performed experiments on a dataset which has not been previously tested using this kind of model. This dataset consists of several images with blood and blood-like substances like ketchup, tomato concentrate, artificial blood, etc. To test both the classic approach to hyperspectral classification and a more realistic application-oriented scenario, we have prepared two different sets of experiments. In the first one, Hyperspectral Transductive Classification (HTC), both a training and a test set come from the same image. In the second one, Hyperspectral Inductive Classification (HIC), a test set is derived from a different image, which is more challenging for classifiers but more useful from the point of view of forensic investigators. We conducted the study using several architectures like 1D, 2D and 3D convolutional neural networks (CNN), a recurrent neural network (RNN) and a multilayer perceptron (MLP). The performance of the models was compared with baseline results of Support Vector Machine (SVM). We have also presented a model evaluation method based on t-SNE and confusion matrix analysis that allows us to detect and eliminate some cases of model undertraining. Our results show that in the transductive case, all models, including the MLP and the SVM, have comparative performance, with no clear advantage of deep learning models. The Overall Accuracy range across all models is 98–100% for the easier image set, and 74–94% for the more difficult one. However, in a more challenging inductive case, selected deep learning architectures offer a significant advantage; their best Overall Accuracy is in the range of 57–71%, improving the baseline set by the non-deep models by up to 9 percentage points. We have presented a detailed analysis of results and a discussion, including a summary of conclusions for each tested architecture. An analysis of per-class errors shows that the score for each class is highly model-dependent. Considering this and the fact that the best performing models come from two different architecture families (3D CNN and RNN), our results suggest that tailoring the deep neural network architecture to hyperspectral data is still an open problem.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Dataset for Evaluating Blood Detection in Hyperspectral Images [Data set]</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><urls><style face="normal" font="default" size="100%">https://doi.org/10.5281/zenodo.3984905</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.5281/zenodo.3984905</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The sensitivity of hyperspectral imaging (imaging spectroscopy) to haemoglobin derivatives makes it a promising tool for detection and classification of blood. However, due to complexity and high dimensionality of hyperspectral images, the development of hyperspectral blood detection algorithms is challenging. To facilitate their development, we present a new hyperspectral blood detection dataset. This dataset consists of 14 hyperspectral images (ENVI format) of a mock-up scene containing blood and visually similar substances (e.g. artificial blood or tomato concentrate). Images were taken over a period of three weeks and differ in terms of background composition and lighting intensity. To facilitate the use of data, the dataset includes an annotation of classes: pixels where blood and similar substances are visible have been marked by the authors. The main intention behind the dataset is to serve as testing data for Machine Learning methods for hyperspectral target detection and classification.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A dataset for evaluating blood detection in hyperspectral images</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Forensic Science International</style></secondary-title><urls><style face="normal" font="default" size="100%">https://arxiv.org/abs/2008.10254</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.forsciint.2021.110701</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">320</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The sensitivity of imaging spectroscopy to haemoglobin derivatives makes it a promising tool for detecting blood. However, due to complexity and high dimensionality of hyperspectral images, the development of hyperspectral blood detection algorithms is challenging. To facilitate their development, we present a new hyperspectral blood detection dataset. This dataset, published under an open access license, consists of multiple detection scenarios with varying levels of complexity. It allows to test the performance of Machine Learning methods in relation to different acquisition environments, types of background, age of blood and presence of other blood-like substances. We have explored the dataset with blood detection experiments, for which we have used a hyperspectral target detection algorithm based on the well-known Matched Filter detector. Our results and their discussion highlight the challenges of blood detection in hyperspectral data and form a reference for further works.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Bartosz Grabowski</style></author><author><style face="normal" font="default" size="100%">Krisztian Buza</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style face="normal" font="default" size="100%">05/2022</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">21st International Conference on Image Analysis and Processing</style></secondary-title><urls><style face="normal" font="default" size="100%">https://arxiv.org/abs/2109.13748</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.1007/978-3-031-06427-2_33</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">13231</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Neural networks, in particular autoencoders, are one of the most promising solutions for unmixing hyperspectral data, i.e. reconstructing the spectra of observed substances (endmembers) and their relative mixing fractions (abundances), which is needed for effective hyperspectral analysis and classification. However, as we show in this paper, the training of autoencoders for unmixing is highly dependent on weights initialisation; some sets of weights lead to degenerate or low-performance solutions, introducing negative bias in the expected performance. In this work, we experimentally investigate autoencoders stability as well as network reinitialisation methods based on coefficients of neurons’ dead activations. We demonstrate that the proposed techniques have a positive effect on autoencoder training in terms of reconstruction, abundances and endmembers errors.&lt;/p&gt;&#13;
</style></abstract><publisher><style face="normal" font="default" size="100%">Springer, Cham</style></publisher><pub-location><style face="normal" font="default" size="100%">Lecce, Italy</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author><author><style face="normal" font="default" size="100%">Anna Strzoda</style></author><author><style face="normal" font="default" size="100%">Rafał Marjasz</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Zbigniew Łaskarzewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Energy-Aware Algorithm for Assignment of Relays in LPWAN</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style face="normal" font="default" size="100%">11/2022</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Transactions on Sensor Networks</style></secondary-title><urls><style face="normal" font="default" size="100%">https://dl.acm.org/doi/10.1145/3544561?cid=99659913397</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.1145/3544561</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">18</style></volume><issue><style face="normal" font="default" size="100%">4</style></issue><section><style face="normal" font="default" size="100%">Article No. 60</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The Low Power Wide Area Networks allow maintaining connectivity with devices over a distance of a few kilometres. However, due&lt;br /&gt;&#13;
to the presence of obstacles the communication range in an urban environment may be shorter, which creates multiple blind spots or&lt;br /&gt;&#13;
areas with limited coverage. The nodes acting as relays may solve this problem by forwarding the data from other devices with poor&lt;br /&gt;&#13;
connectivity. We propose and investigate a novel algorithm that assigns devices to the relay role while keeping the battery constraints.&lt;br /&gt;&#13;
We define the algorithm, describe the simulation testbed, and present performance evaluation in several scenarios, including real-life&lt;br /&gt;&#13;
topologies of IoT networks. The proposed relay selection scheme allows increasing the lifetime of the network by selecting the relay&lt;br /&gt;&#13;
taking into account the current battery capacity. Additionally, it outperforms a previously proposed relay selection algorithm for LP&lt;br /&gt;&#13;
WAN, showing an average 4% decrease in transmission time and an order of magnitude lower computation complexity.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bartosz Grabowski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Krisztian Buza</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%"> Improving Autoencoders Performance for Hyperspectral Unmixing Using Clustering</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style face="normal" font="default" size="100%">11/2022</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Asian Conference on Intelligent Information and Database Systems</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Communications in Computer and Information Science</style></tertiary-title><urls><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007/978-981-19-8234-7_9</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.1007/978-981-19-8234-7_9</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">1716</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Hyperspectral cameras acquire images containing information across the electromagnetic spectrum, which convey useful information about the scene. To enable effective analysis of such data, spectral unmixing is often used. It is an important task in hyperspectral imaging, allowing one to obtain the information about spectral endmembers which make up each hyperspectral pixel. This task, traditionally solved with dedicated statistical methods, has recently been explored with deep learning methods. One of the methods well-suited to this task are autoencoders. These neural networks are initialized using multiple random weights, and their initialization often has a significant impact on their efficiency. Because of that, to improve the initialization of autoencoders for the spectral unmixing task, we propose to use the pre-training scheme consisting of clustering-based artificial labeling. We test the approach on two popular hyperspectral datasets, i.e. Samson and Jasper Ridge. Our experiment delivers promising results, improving autoencoders effectiveness in the case of Samson dataset, i.e. for 25-class labeling endmembers’ and abundances’ errors improve by 0.045 and 0.008, respectively. The worse results in the case of Jasper Ridge dataset (improvement of the endmembers’ error by 0.001, and worsening of the abundances’ error by 0.006 for 25-classes labeling) show that more research is required to understand when the proposed approach improves the results of the spectral unmixing. The auxiliary experiments that we also conduct allow us to partially answer that question.&lt;/p&gt;&#13;
</style></abstract><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Ho Chi Minh City, Vietnam</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Anna Strzoda</style></author><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Andrzej Madej</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Link failure prediction in LoRa networks</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">07/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%"> International Wireless Communications and Mobile Computing Conference, IWCMC</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1109/IWCMC58020.2023.10183185</style></electronic-resource-num><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Marrakesh, Morocco</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Wojciech Koral</style></author><author><style face="normal" font="default" size="100%">Andrzej Madej</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Detection of emergent leaks using machine learning approaches</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">05/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Water Supply</style></secondary-title><urls><style face="normal" font="default" size="100%">https://doi.org/10.2166/ws.2023.118</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.2166/ws.2023.118</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">23</style></volume><issue><style face="normal" font="default" size="100%">6</style></issue><section><style face="normal" font="default" size="100%">2370</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this work, we focus on the detection of leaks occurring in district metered areas (DMAs). Those leaks are observable as a number of time-related deviations from zone patterns over days or weeks. While they are detectable given enough time, due to the huge cost of water loss resulting from an undetected leak, the main challenge is to find them as soon as possible, when the deviation from the zone pattern is small. Using our collected observational data, we investigate the appearance of leaks and discuss the performance of several machine learning (ML) anomaly detectors in detecting them. We test a diverse set of six anomaly detectors, each based on a different ML algorithm, on nine scenarios containing leaks and anomalies of various kinds. The proposed approach is very effective at quickly (within hours) identifying the presence of a leak, with a limited number of false positives.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Wilhelm Masarczyk</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Iga Stokłosa</style></author><author><style face="normal" font="default" size="100%">Piotr Ścisło</style></author><author><style face="normal" font="default" size="100%">Paweł Dębski</style></author><author><style face="normal" font="default" size="100%">Robert Pudlo</style></author><author><style face="normal" font="default" size="100%">Krisztian Buza</style></author><author><style face="normal" font="default" size="100%">Piotr Gorczyca</style></author><author><style face="normal" font="default" size="100%">Magdalena Piegza</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The analysis of heart rate variability and accelerometer mobility data in the assessment of symptom severity in psychotic disorder patients using a wearable Polar H10 sensor</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">08/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">medXriv</style></secondary-title><urls><style face="normal" font="default" size="100%">https://www.medrxiv.org/content/10.1101/2023.08.04.23293640v1</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.1101/2023.08.04.23293640</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;em&gt;Background and Objective: &lt;/em&gt;Advancement in mental health care requires easily accessible diagnostic and treatment assessment tools. There is an ongoing search for biomarkers that would enable objectification and automatization of the diagnostic and treatment process dependent on a psychiatric interview. Current wearable technology and computational methods make it possible to incorporate heart rate variability (HRV), an indicator of autonomic nervous system functioning and a potential biomarker of disease severity in mental disorders, into accessible diagnostic and treatment assessment frameworks.&lt;br /&gt;&#13;
&lt;em&gt;Methods:&lt;/em&gt; We used a commercially available electrocardiography (ECG) chest strap with a built-in accelerometer, i.e. Polar H10, to record R-R intervals and activity of 30 hospitalized schizophrenia or bipolar disorder patients and 30 control participants for 1.5-2 hours time periods.&lt;br /&gt;&#13;
We performed an analysis to assess the relationship between HRV and the Positive and Negative Syndrome Scale (PANSS) test scores. The source code for the reproduction of all experiments is available on GitHub while the dataset is available in Zenodo.&lt;br /&gt;&#13;
&lt;em&gt;Results and Conclusions:&lt;/em&gt; Mean HRV values were lower in the patient group and negatively correlated with the results of the PANSS general subcategory. For the control group, we also discovered the inversely proportional dependency between the mobility coefficient based on accelerometer data and HRV. This relationship was less pronounced for the patient group. This indicates that HRV and mobility may be promising markers in disease diagnosis.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Wilhelm Masarczyk</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Iga Stokłosa</style></author><author><style face="normal" font="default" size="100%">Piotr Ścisło</style></author><author><style face="normal" font="default" size="100%">Paweł Dębski</style></author><author><style face="normal" font="default" size="100%">Robert Pudlo</style></author><author><style face="normal" font="default" size="100%">Piotr Gorczyca</style></author><author><style face="normal" font="default" size="100%">Magdalena Piegza</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">HRV-ACC: a dataset with R-R intervals and accelerometer data for the diagnosis of psychotic disorders using a Polar H10 wearable sensor</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year></dates><urls><style face="normal" font="default" size="100%">https://zenodo.org/record/8171266</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.5281/zenodo.8171266</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The issue of diagnosing psychotic diseases, including schizophrenia and bipolar disorder, in particular, the objectification of symptom severity assessment, is still a problem requiring the attention of researchers. Two measures that can be helpful in patient diagnosis are heart rate variability calculated based on electrocardiographic signal and accelerometer mobility data. The following dataset contains data from 30 psychiatric ward patients having schizophrenia or bipolar disorder and 30 healthy persons. The duration of the measurements for individuals was usually between 1.5 and 2 hours. R-R intervals necessary for heart rate variability calculation were collected simultaneously with accelerometer data using a wearable Polar H10 device. The Positive and Negative Syndrome Scale (PANSS) test was performed for each patient participating in the experiment, and its results were attached to the dataset. Furthermore, the code for loading and preprocessing data, as well as for statistical analysis, was included on the corresponding GitHub repository.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Agnieszka Ciemięga</style></author><author><style face="normal" font="default" size="100%">Katarzyna Maresz</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Paulina Krupska-Wolas</style></author><author><style face="normal" font="default" size="100%">Krystian Prusik</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Hyperspectral Imaging as a Facile and Non-Destructive Method for Size Analysis of Gold Nanoparticles Deposited on Porous Materials</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year></dates><secondary-title><style face="normal" font="default" size="100%"/></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1002/ppsc.202200204</style></electronic-resource-num><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krisztian Buza</style></author><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Wilhelm Masarczyk</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Piotr Gorczyca</style></author><author><style face="normal" font="default" size="100%">Magdalena Piegza</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Simple and Effective Classifier for the Detection of Psychotic Disorders based on Heart Rate Variability Time Series</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">09/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%"> Information Technologies – Applications and Theory 2023</style></secondary-title><urls><style face="normal" font="default" size="100%">https://ceur-ws.org/Vol-3498/paper28.pdf</style></urls><volume><style face="normal" font="default" size="100%">3498</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper, we focus on automated detection of schizophrenia and bipolar disorder. For this task, we describe a simple and effective classifier, i.e. convolutional nearest neighbor. It provides a data-driven and objective approach for the detection of schizophrenia and bipolar disorder based on heart rate variability time series. According to our results, our approach is able to distinguish whether the selected person belongs to the patient group with an accuracy of 85% and area under receiver-operator characteristic curve of 0.92.&lt;/p&gt;&#13;
</style></abstract><publisher><style face="normal" font="default" size="100%">Knižnicné a edicné centrum, Fakulta matematiky, fyziky a informatiky, Univerzita Komenského, Mlynská dolina, Bratislava</style></publisher><pub-location><style face="normal" font="default" size="100%">Tatranské Matliare</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bartłomiej Gardas</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Przemysław Sadowski</style></author><author><style face="normal" font="default" size="100%">Zbigniew Puchała</style></author><author><style face="normal" font="default" size="100%">Konrad Jałowiecki</style></author><author><style face="normal" font="default" size="100%">Łukasz Pawela</style></author><author><style face="normal" font="default" size="100%">Orphee Faucoz</style></author><author><style face="normal" font="default" size="100%">Pierre-Marie Brunet</style></author><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author><author><style face="normal" font="default" size="100%">Matthijs Van Waveren</style></author><author><style face="normal" font="default" size="100%">Mickaël Savinaud</style></author><author><style face="normal" font="default" size="100%">Guillaume Pasero</style></author><author><style face="normal" font="default" size="100%">Veronique Defonte</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Hyper-Spectral Image Classification Using Adiabatic Quantum Computation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year></dates><secondary-title><style face="normal" font="default" size="100%">IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1109/IGARSS52108.2023.10282125</style></electronic-resource-num><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Wojciech Koral</style></author><author><style face="normal" font="default" size="100%">Andrzej Madej</style></author><author><style face="normal" font="default" size="100%">Maciej Skrabski</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Machine Learning for Water Leak Detection and Localization in the WaterPrime Project</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Wojciechowski A.(Ed.), Lipiński P.(Ed.)., Progress in Polish Artificial Intelligence Research 4, Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.</style></secondary-title><publisher><style face="normal" font="default" size="100%">Wydawnictwo Politechniki Łódzkiej</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Paweł Foszner</style></author><author><style face="normal" font="default" size="100%">Jakub Bularz</style></author><author><style face="normal" font="default" size="100%">Maria Ganzha</style></author><author><style face="normal" font="default" size="100%">Leszek Maciaszek</style></author><author><style face="normal" font="default" size="100%">Marcin Paprzycki</style></author><author><style face="normal" font="default" size="100%">Dominik Slezak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Continual learning of a time series model using a mixture of HMMs with application to the IoT fuel sensor verification</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 18th Conference on Computer Science and Intelligence Systems, FedCSIS 2023, Warsaw, Poland, September 17-20, 2023</style></secondary-title><urls><style face="normal" font="default" size="100%">https://doi.org/10.15439/2023F1856</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.15439/2023F1856</style></electronic-resource-num><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Wilhelm Masarczyk</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Iga Stokłosa</style></author><author><style face="normal" font="default" size="100%">Piotr Ścisło</style></author><author><style face="normal" font="default" size="100%">Paweł Dębski</style></author><author><style face="normal" font="default" size="100%">Robert Pudlo</style></author><author><style face="normal" font="default" size="100%">Krisztian Buza</style></author><author><style face="normal" font="default" size="100%">Piotr Gorczyca</style></author><author><style face="normal" font="default" size="100%">Magdalena Piegza</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style face="normal" font="default" size="100%">05/2024</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Computers in Biology and Medicine</style></secondary-title><urls><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S0010482524006280</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.compbiomed.2024.108544</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">176</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Through the Thicket: A Study of Number-Oriented LLMs derived from Random Forest Models</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style face="normal" font="default" size="100%">06/2024</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">arXiv preprint arXiv:2406.04926</style></secondary-title><urls><style face="normal" font="default" size="100%">https://arxiv.org/abs/2406.04926</style></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Michał Gorawski</style></author><author><style face="normal" font="default" size="100%">Jakub Koral</style></author><author><style face="normal" font="default" size="100%">Wojciech Koral</style></author><author><style face="normal" font="default" size="100%">Andrzej Madej</style></author><author><style face="normal" font="default" size="100%">Kryspin Musioł</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">‘Just One More Sensor is Enough’ – Iterative Water Leak Localization with Physical Simulation and a Small Number of Pressure Sensors</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style face="normal" font="default" size="100%">06/2024</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">IEEE Sensors Journal</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1109/JSEN.2024.3413889</style></electronic-resource-num><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Wojciech Koral</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Efficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style face="normal" font="default" size="100%">09/2024</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">arXiv preprint 	arXiv:2410.02772</style></secondary-title><urls><style face="normal" font="default" size="100%">https://arxiv.org/abs/2410.02772</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.48550/arXiv.2410.02772</style></electronic-resource-num><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author><author><style face="normal" font="default" size="100%">Przemysław Sadowski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Bartłomiej Gardas</style></author><author><style face="normal" font="default" size="100%">Matthijs Van Waveren</style></author><author><style face="normal" font="default" size="100%">Clément Forray</style></author><author><style face="normal" font="default" size="100%">Guillaume Pasero</style></author><author><style face="normal" font="default" size="100%">Mickaël Savinaud</style></author><author><style face="normal" font="default" size="100%">Pierre-Marie Brunet</style></author><author><style face="normal" font="default" size="100%">Orphee Faucoz</style></author><author><style face="normal" font="default" size="100%">Zbigniew Puchała</style></author><author><style face="normal" font="default" size="100%">Łukasz Pawela</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">What Could be Achieved with a Million Qubits Quantum Annealer in Remote Sensing?</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year></dates><secondary-title><style face="normal" font="default" size="100%">IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Wojciech Koral</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Calibration of Water Demand Network Through a Machine Learned Digital Twin Model</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year></dates><secondary-title><style face="normal" font="default" size="100%">5th Polish Conference on Artificial Intelligence (PP-RAI 2024)</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Through the Thicket: A Study of Number-Oriented LLMS Derived from Random Forest Models</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style face="normal" font="default" size="100%">03/2025</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Artificial Intelligence and Soft Computing Research</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.2478/jaiscr-2025-0014</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">15</style></volume><issue><style face="normal" font="default" size="100%">3</style></issue><section><style face="normal" font="default" size="100%">279</style></section><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Łukasz Pawela</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Quantum-aware Transformer model for state classification</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">International Conference on Computational Science 2025</style></secondary-title><urls><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007/978-3-031-97570-7_15</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.48550/arXiv.2502.21055</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Entanglement is a fundamental feature of quantum mechanics, playing a crucial role in quantum information processing. However, classifying entangled states, particularly in the mixed-state regime, remains a challenging problem, especially as system dimensions increase. In this work, we focus on bipartite quantum states and present a data-driven approach to entanglement classification using transformer-based neural networks. Our dataset consists of a diverse set of bipartite states, including pure separable states, Werner entangled states, general entangled states, and maximally entangled states. We pretrain the transformer in an unsupervised fashion by masking elements of vectorized Hermitian matrix representations of quantum states, allowing the model to learn structural properties of quantum density matrices. This approach enables the model to generalize entanglement characteristics across different classes of states. Once trained, our method achieves near-perfect classification accuracy, effectively distinguishing between separable and entangled states. Compared to previous Machine Learning, our method successfully adapts transformers for quantum state analysis, demonstrating their ability to systematically identify entanglement in bipartite systems. These results highlight the potential of modern machine learning techniques in automating entanglement detection and classification, bridging the gap between quantum information theory and artificial intelligence.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Wilhelm Masarczyk</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Krisztian Buza</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Piotr Gorczyca</style></author><author><style face="normal" font="default" size="100%">Magdalena Piegza</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deep learning approach for automatic assessment of schizophrenia and bipolar disorder in patients using R-R intervals</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style face="normal" font="default" size="100%">09/2025</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">PLOS Computational Biology</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1371/journal.pcbi.1012983</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">21</style></volume><section><style face="normal" font="default" size="100%">1</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Schizophrenia and bipolar disorder are severe mental illnesses that significantly impact quality of life. These disorders are associated with autonomic nervous system dysfunction, which can be assessed through heart activity analysis. Heart rate variability (HRV) has shown promise as a potential biomarker for diagnostic support and early screening of those conditions. This study aims to develop and evaluate an automated classification method for schizophrenia and bipolar disorder using short-duration electrocardiogram (ECG) signals recorded with a low-cost wearable device. We conducted classification experiments using machine learning techniques to analyze R-R interval windows extracted from short ECG recordings. The study included 60 participants—30 individuals diagnosed with schizophrenia or bipolar disorder and 30 control subjects. We evaluated multiple machine learning models, including Support Vector Machines, XGBoost, multilayer perceptrons, Gated Recurrent Units, and ensemble methods. Two time window lengths (about 1 and 5 minutes) were evaluated. Performance was assessed using 5-fold cross-validation and leave-one-out cross-validation, with hyperparameter optimization and patient-level classification based on individual window decisions. Our method achieved classification accuracy of 83% for the 5-fold cross-validation and 80% for the leave-one-out scenario. Despite the complexity of our scenario, which mirrors real-world clinical settings, the proposed approach yielded performance comparable to advanced diagnostic methods reported in the literature. The results highlight the potential of short-duration HRV analysis as a cost-effective and accessible tool for aiding in the diagnosis of schizophrenia and bipolar disorder. Our findings support the feasibility of using wearable ECG devices and machine learning-based classification for psychiatric screening, paving the way for further research and clinical applications.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Anna Zawadzka</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Challenges associated with the integration of Large Multimodal Models for waste sorting</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">6th Polish Conference on Artificial Intelligence (PP-RAI 2025)</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data structure better than labels? Unsupervised heuristics for SVM hyperparameter estimation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Bulletin of the Polish Academy of Sciences Technical Sciences</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.24425/bpasts.2025.155891</style></electronic-resource-num><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data structure better than labels? Unsupervised heuristics for SVM hyperparameter estimation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Bulletin of the Polish Academy of Sciences Technical Sciences</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.24425/bpasts.2025.155891</style></electronic-resource-num><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Anna Zawadzka</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Mateusz Żarski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of an effective method for detecting small buildings in satellite images</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">PP-RAI 2025</style></secondary-title><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Detecting and monitoring small-scale buildings is a critical challenge in various sectors and can be crucial for various important tasks. Buildings considered small are those with a footprint smaller than 10 × 10 meters, a definition justified by the resolution of Sentinel-2 images, which is 10 meters at best. Examples of tasks for which small building detection is essential include assessment and monitoring of damage caused by natural disasters or war, identification of illegal settlements, detecting new buildings in key military areas, and identification of structures in protected areas. Regrettably, widely available satellite imagery, such as Sentinel-2, provides very limited spatial resolution, making it impossible to efficiently detect small structures. Despite its importance, this issue remains unexplored, with very limited research directly concerning building segmentation and detecting small structures. Traditional segmentation and classification methods exhibit severe limitations, particularly due to small buildings frequently being positioned at pixel boundaries, essentially occupying an insignificant fraction of the original pixel. Additionally, in the context of buildings in complex environments (e.g., surrounded by vegetation or shadows), popular methods such as U-Net with ResNet often fail to deliver reliable results. In this study, we propose a novel approach to this issue by integrating a state-of-the-art object detection model with a deep-learning-based super-resolution network.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Wojciech Koral</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Efficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2026</style></year><pub-dates><date><style face="normal" font="default" size="100%">02/2026</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Water Resources Planning and Management - ASCE</style></secondary-title><urls><style face="normal" font="default" size="100%">https://doi.org/10.1061/JWRMD5.WRENG-6839</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.1061/JWRMD5.WRENG-6839 </style></electronic-resource-num><volume><style face="normal" font="default" size="100%">152</style></volume><issue><style face="normal" font="default" size="100%">4</style></issue><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Anna Zawadzka</style></author><author><style face="normal" font="default" size="100%">Mateusz Żarski</style></author><author><style face="normal" font="default" size="100%">Kamil Drejer</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%"> Map-Guided Cross-Training for Building Detection</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2026</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Geoscience and Remote Sensing Letters</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Anna Zawadzka</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Architecture Matters: Gender Disparities in Automated Image Moderation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2026</style></year><pub-dates><date><style face="normal" font="default" size="100%">04/2026</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">PP-RAI'2026: 7th Polish Conference on Artificial Intelligence</style></secondary-title><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Automated image moderation systems shape online visibility and dataset curation, yet prior work has identified demographic disparities in similarity-based NSFW classifiers. We compare such systems with instruction-tuned vision-language models (VLMs) that generate structured moderation decisions with textual rationales. Using the PHASE-annotated subset of the GCC dataset, &#160;we compute false positive rates overall and by gender.&#160;&lt;br&gt;Results show substantial variation in moderation strictness and in bias direction: two models show more pronounced strictness in moderation of male images, while other two exhibit higher removal rates for female images.&#160;&lt;br&gt;Reasoning-based models do not consistently mitigate bias but, in the proposed pipeline, they offer a transparency layer.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aygün Varol</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Łukasz Sobczak</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Naser Motlagh</style></author><author><style face="normal" font="default" size="100%">Mirka Leino</style></author><author><style face="normal" font="default" size="100%">Johanna Virkki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2026</style></year></dates><secondary-title><style face="normal" font="default" size="100%">IEEE Internet of Things Journal</style></secondary-title><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Large language models (LLMs) offer a natural-language interface for interpreting Internet of Things (IoT) sensor data in smart environments; however, cloud deployment introduces latency, privacy, and connectivity concerns. Local LLMs can reduce these limitations, but compact edge-deployable models often show weaker numerical reasoning when raw sensor readings are provided directly. This paper investigates whether prompt-side preprocessing can improve the accuracy--latency trade-off of local LLMs for environmental monitoring. We propose a structured prompt construction framework that transforms raw air-quality and thermal-comfort measurements into progressively enriched textual representations: raw sensor values, threshold-aware descriptions, and compact environmental summary flags. The approach is evaluated using indoor Raspberry Pi/BME680 datasets from Tampere University and outdoor air-quality datasets from Helsinki, Katowice, and Warsaw. We construct a binary LLM query dataset covering air quality, thermal comfort, and joint environmental conditions, and evaluate five local and five cloud LLMs across three prompt variants and two inference modes, with and without chain-of-thought prompting. The results show that prompt enrichment substantially improves local-model accuracy. In No-CoT mode, local accuracy increases from 50.9\% to 81.7\% indoors and from 63.7\% to 89.3\% outdoors from the raw to the most enriched prompt. Local No-CoT inference is the fastest configuration, with mean latency close to 0.22 s, while CoT substantially increases inference time. These findings suggest that lightweight prompt-side preprocessing can narrow the local--cloud performance gap and support low-latency IoT analytics in smart environments.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aygün Varol</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Łukasz Sobczak</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Naser Motlagh</style></author><author><style face="normal" font="default" size="100%">Mirka Leino</style></author><author><style face="normal" font="default" size="100%">Johanna Virkki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2026</style></year></dates><secondary-title><style face="normal" font="default" size="100%">arXiv preprint arXiv </style></secondary-title><urls><style face="normal" font="default" size="100%">https://arxiv.org/abs/2606.22496 </style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.48550/ARXIV.2606.22496 </style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Large language models (LLMs) offer a natural-language interface for interpreting Internet of Things (IoT) sensor data in smart environments; however, cloud deployment introduces latency, privacy, and connectivity concerns. Local LLMs can reduce these limitations, but compact edge-deployable models often show weaker numerical reasoning when raw sensor readings are provided directly. This paper investigates whether prompt-side preprocessing can improve the accuracy--latency trade-off of local LLMs for environmental monitoring. We propose a structured prompt construction framework that transforms raw air-quality and thermal-comfort measurements into progressively enriched textual representations: raw sensor values, threshold-aware descriptions, and compact environmental summary flags. The approach is evaluated using indoor Raspberry Pi/BME680 datasets from Tampere University and outdoor air-quality datasets from Helsinki, Katowice, and Warsaw. We construct a binary LLM query dataset covering air quality, thermal comfort, and joint environmental conditions, and evaluate five local and five cloud LLMs across three prompt variants and two inference modes, with and without chain-of-thought prompting. The results show that prompt enrichment substantially improves local-model accuracy. In No-CoT mode, local accuracy increases from 50.9\% to 81.7\% indoors and from 63.7\% to 89.3\% outdoors from the raw to the most enriched prompt. Local No-CoT inference is the fastest configuration, with mean latency close to 0.22 s, while CoT substantially increases inference time. These findings suggest that lightweight prompt-side preprocessing can narrow the local--cloud performance gap and support low-latency IoT analytics in smart environments.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aygün Varol</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Łukasz Sobczak</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Naser Motlagh</style></author><author><style face="normal" font="default" size="100%">Mirka Leino</style></author><author><style face="normal" font="default" size="100%">Johanna Virkki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">AIRWISE: Environmental Sensor and LLM Query Dataset for Edge AI-Based Air-Quality and Thermal-Comfort Analytics</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2026</style></year></dates><urls><style face="normal" font="default" size="100%">https://zenodo.org/doi/10.5281/zenodo.20783874 </style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.5281/ZENODO.20783874 </style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;AIRWISE is an open benchmark dataset for edge AI, IoT environmental monitoring, and large language model (LLM) evaluation on real sensor data. It combines indoor air-quality and thermal-comfort measurements, outdoor air-quality and meteorological time series, and a labeled binary question-answering benchmark for threshold-aware reasoning and anomaly detection. The dataset supports the study “Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing”:&#160;https://doi.org/10.48550/arXiv.2606.22496&lt;br&gt;AIRWISE provides three core resources:&lt;br&gt;Indoor environmental sensor dataset (BME680, 1-minute resolution). 146,000+ minute-averaged readings from Raspberry Pi + Bosch BME680 nodes in three real micro-environments (office, kitchen, hallway) at Tampere, Finland (2025-11-14 to 2025-12-18): temperature, relative humidity, barometric pressure, gas resistance, indoor air quality (IAQ) proxy, z-score anomaly detectors, and limit-annotated long-format tables with ground-truth anomaly flags.&lt;br&gt;Outdoor air-quality and meteorological time series (hourly, full-year 2023). Helsinki (Finland), Katowice and Warsaw (Poland): NO₂, CO, O₃, PM₂.₅, temperature, and relative humidity assembled from national monitoring networks (FMI, GIOŚ, IMGW-PIB), as cleaned single-series city tables (≈8,760 hourly records per city) and limit-annotated long-format tables with anomaly flags.&lt;br&gt;Binary LLM query benchmark (1,440 labeled yes/no questions). 240 natural-language questions per site across six sites, balanced by task type (80 air quality, 80 thermal comfort, 80 joint environmental condition), each with ground-truth answer, violation label, offending factors, and rationale — ready for benchmarking local/edge and cloud LLMs on sensor-grounded reasoning.&lt;br&gt;Also included: reference air-quality and thermal-comfort limits (EU air-quality standards and Finnish/Polish national guidelines); the unmodified institutional source files for the outdoor component (FMI exports, GIOŚ archive workbooks and station metadata, IMGW-PIB synoptic tables); the complete dataset-generation scripts covering every pipeline step (raw sources → cleaned tables → limit-annotated data → LLM queries) with a requirements.txt for a verified minimal Python environment; SHA-256 checksums; and a dependency-free validation script. Schemas, exact row counts, coverage, and usage examples are documented in README.md and MANIFEST.md.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Kamil Drejer</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author><author><style face="normal" font="default" size="100%">Anna Zawadzka</style></author><author><style face="normal" font="default" size="100%">Stanisław Lewiński</style></author><author><style face="normal" font="default" size="100%">Przemysław Głomb</style></author><author><style face="normal" font="default" size="100%">Marek Ruciński</style></author><author><style face="normal" font="default" size="100%">Michał Krupiński</style></author><author><style face="normal" font="default" size="100%">Krzysztof Gryguc</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Szymon Sala</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Toward Seasonal Guidelines for Robust Deep-Learning Sentinel-2 Building Detection in Different Area Types</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2026</style></year></dates><electronic-resource-num><style face="normal" font="default" size="100%">10.1109/JSTARS.2026.3742586</style></electronic-resource-num></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>32</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Czołowe funkcje kuliste jako baza do aproksymacji sygnałów o ograniczonym paśmie</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2013</style></year></dates><abstract><style face="normal" font="default" size="100%">Tematem pracy jest analiza algorytmu aproksymującego sygnały o ograniczonym pasmie opartego na czołowych funkcjach kulistych. Obecny stan wiedzy zawiera analizę błędu pesymistycznego dla zawężonego przypadku funkcji o ograniczonej energii oraz oszacowanie błędu w przypadku średnim, jednakże bez uwzględnienia błędu wynikającego z błędu pomiaru i kwantyzacji oraz jittera. Ponieważ oba te czynniki występują w praktycznym zastosowaniu wszelkich algorytmów aproksymacyjnych, gruntowna analiza ich wpływu jest istotna z punktu badania efektywności algorytmu. Szczególnie jitter jest wielkością o znaczącym wpływie na wynik działania algorytmu, jako, że nawet niewielki jitter sprawia, że problem wymyka się spod założeń Lematu Smolyaka, który mówi o istnieniu optymalnego algorytmu liniowego. W pracy przedstawione jest oszacowanie błędu średniego dla rodziny zadanych miar Gaussa i wykazuje, że błąd średni algorytmu można dobrze ograniczyć. To prowadzi do wniosku, że algorytm aproksymacji sygnałów o ograniczonym pasmie oparty o czołowe funkcje kuliste jest algorytmem odpornym na działanie czynników zakłócających takich jak błąd pomiaru i kwantyzacji oraz jitter. Praca zawiera również implementację algorytmu numerycznego wyliczania wartości zadanych czołowych funkcji kulistych.</style></abstract><publisher><style face="normal" font="default" size="100%">Instytut Informatyki Teoretycznej i Stosowanej PAN</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>28</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Katarzyna Kara</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Rewolucja stanu - fantastyczne wprowadzenie do informatyki kwantowej</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><urls><style face="normal" font="default" size="100%">https://depot.ceon.pl/handle/123456789/16807</style></urls><pages><style face="normal" font="default" size="100%">128</style></pages><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Świat, jaki znamy – świat wolnych sieci informacyjnych, świat swobodnej wymiany wiedzy i doświadczeń – skończył się nieodwołalnie. Wolny dostęp do wiedzy okazał się szkodliwą ideą, a najbardziej skorzystali na nim zbrodniarze, twórcy broni biologicznej, która nieomal zmiotła cywilizację z powierzchni ziemi. Zdziesiątkowana przez terror, wojny i epidemię ludzkość powoli odradza się pod czujnym okiem Cerbera. Jego agenci mają jeden cel: nie dopuścić, aby wiedza stała się znów powszechnie dostępna.&lt;/p&gt;&#13;
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&lt;p&gt;Jednak wszechobecna cenzura rodzi bunt.&lt;/p&gt;&#13;
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&lt;p&gt;Niektórzy są nawet gotowi ginąć – i zabijać – za wolny dostęp do informacji. I najwyraźniej czują się dość pewnie, by rzucić Cerberowi wyzwanie – bo czym innym może być zamach na wysokiego dygnitarza organizacji w jej głównej kwaterze? Teraz Cerber musi użyć wszystkich dostępnych środków, by znaleźć zleceniodawców napastnika. Niestety, jego as atutowy, kwantowa hakerka Eve, właśnie zasiada na ławie oskarżonych pod zarzutem zdrady na rzecz grupy terrorystycznej ALICE...&lt;/p&gt;&#13;
</style></abstract><publisher><style face="normal" font="default" size="100%">IITiS PAN</style></publisher><pub-location><style face="normal" font="default" size="100%">Gliwice</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multi-sensor dataset for testing merge of Hyperspectral, HD and 3D cloud information for image recognition</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Narjes Shayesteh</style></author><author><style face="normal" font="default" size="100%">Qinglian He</style></author><author><style face="normal" font="default" size="100%">Sara Zahedian</style></author><author><style face="normal" font="default" size="100%">Rodrigo Moscosso</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Move Over Law Compliance Analysis Utilizing a Deep Learning Computer Vision Approach</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Applied Sciences</style></secondary-title><urls><style face="normal" font="default" size="100%">https://www.mdpi.com/2076-3417/15/4/2011</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.3390/app15042011</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">15</style></volume><issue><style face="normal" font="default" size="100%">4</style></issue><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Qinglian He</style></author><author><style face="normal" font="default" size="100%">Kaveh Sadabadi</style></author><author><style face="normal" font="default" size="100%">Rodrigo Moscosso</style></author><author><style face="normal" font="default" size="100%">Thomas Jacobs</style></author><author><style face="normal" font="default" size="100%">Zachary Laan</style></author><author><style face="normal" font="default" size="100%">Mark Franz</style></author><author><style face="normal" font="default" size="100%">Michał Cholewa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Vehicle-to-Infrastructure System Prototype for Intersection Safety</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style face="normal" font="default" size="100%">09/2025</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Applied Sciences</style></secondary-title><urls><style face="normal" font="default" size="100%">https://www.mdpi.com/2076-3417/15/17/9754</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.3390/app15179754</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">15</style></volume><issue><style face="normal" font="default" size="100%">17</style></issue><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This study investigates the use of Autonomous Sensing Infrastructure and Connected and Autonomous Vehicles (CAV) technologies to support infrastructure-to-vehicle (I2V) and infrastructure-to-everything (I2X) communications, including the alerting of drivers and pedestrians. It describes research findings in the following CAV functionalities: (1) Intersection-based object detection and tracking; (2) Basic Safety Message (BSM) generation and transmission; and (3) In-Vehicle BSM receipt and display, including handheld (smartphone) application BSM receipt and user presentation. The study summarizes the various software and hardware components used to create the I2V and I2X prototype solutions, which include open-source and commercial software as well as industry-standard transportation infrastructure hardware, e.g., Signal Controllers. Results from in-lab testing demonstrate effective object detection (e.g., pedestrians, bicycles) based on sample traffic camera video feeds as well as successful BSM message generation and receipt using the leveraged software and hardware components. The I2V and I2X solutions created as part of this research are scheduled to be deployed in a real-world intersection in coordination with state and local transportation agencies.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author><author><style face="normal" font="default" size="100%">Sebastian Opozda</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dimensionality reduction of dynamic animations using HO-SVD</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Lecture Notes in Artificial Intelligence</style></secondary-title><pages><style face="normal" font="default" size="100%">757–768</style></pages><volume><style face="normal" font="default" size="100%">8467</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author><author><style face="normal" font="default" size="100%">Sebastian Opozda</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Compression of animated 3D models using HO-SVD</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2013</style></year></dates><secondary-title><style face="normal" font="default" size="100%">arXiv:1310.1240</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">arXiv:1310.1240</style></notes></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author><author><style face="normal" font="default" size="100%">Sebastian Opozda</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2013</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Artificial Intelligence and Soft Computing Research</style></secondary-title><pages><style face="normal" font="default" size="100%">277–289</style></pages><volume><style face="normal" font="default" size="100%">3</style></volume><number><style face="normal" font="default" size="100%">4</style></number><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">DOI 10.2478/jaiscr-2014-0020</style></notes></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Sebastian Opozda</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimization of a Vector Quantizer's Quality for 3D Mesh Applications</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style face="normal" font="default" size="100%">9</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Theoretical and Applied Informatics</style></secondary-title><pages><style face="normal" font="default" size="100%">131–140</style></pages><volume><style face="normal" font="default" size="100%">22</style></volume><number><style face="normal" font="default" size="100%">2</style></number><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Arkadiusz Sochan</style></author><author><style face="normal" font="default" size="100%">Krzysztof Skabek</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Matrix and Tensor-Based Approximation of 3D Face Animations from Low-Cost Range Sensors</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2018</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Computer and Information Sciences</style></secondary-title><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Three-dimensional animation is often represented in the form of a sequence of 3D meshes, also called dynamic animation or Temporally Coherent Mesh Sequence (TCMS). Widespread availability of affordable range sensors makes capturing such data easy, however, its huge volume complicates both storage and further processing. One of the possible solutions is to approximate the data using matrix or tensor decomposition. However the quality the animation may have different impact on both approaches. In this work we use the Microsoft Kinect™&#160;to crate sequences of human face models and compare the approximation error obtained from modelling animations using Principal component analysis (PCA) and Higher Order Singular Value Decomposition (HOSVD). We focus on distortion introduced by reconstruction of data from its truncated factorization. We show that while HOSVD may outperform PCA in terms of approximation error, it may be significantly affected by distortion in animation data.&lt;/p&gt;&#13;
</style></abstract><isbn><style face="normal" font="default" size="100%">978-3-030-00840-6</style></isbn><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Małgorzata Domino</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Tomasz Jasiński</style></author><author><style face="normal" font="default" size="100%">Małgorzata Maśko</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of the Surface Thermal Patterns of Horses and Donkeys in Infrared Thermography Images</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style face="normal" font="default" size="100%">11/2020</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Animals</style></secondary-title><pages><style face="normal" font="default" size="100%"> 2201</style></pages><volume><style face="normal" font="default" size="100%">10</style></volume><issue><style face="normal" font="default" size="100%">12</style></issue><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Małgorzata Domino</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Tomasz Jasiński</style></author><author><style face="normal" font="default" size="100%">Małgorzata Maśko</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of surface thermal patterns of horses and donkeys in IRT images [Data set]</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><urls><style face="normal" font="default" size="100%">https://zenodo.org/record/4085075</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">http://doi.org/10.5281/zenodo.4085075</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The dataset contains infrared thermography (IRT) images of horses and donkeys along with annotations of 15 ROIs corresponding to areas with potential impact of large equine muscles. All animals were healthy and rested. Imaged animals: sixteen horses and eighteen donkeys. Measured animal features such as hair length, and skin thickness are included.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Filip Pałka</style></author><author><style face="normal" font="default" size="100%">Wojciech Książek</style></author><author><style face="normal" font="default" size="100%">Pawel Plawiak</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Kamil Książek</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Hyperspectral Classification of Blood-Like Substances Using Machine Learning Methods Combined with Genetic Algorithms in Transductive and Inductive Scenarios</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style face="normal" font="default" size="100%">03/2021</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Sensors</style></secondary-title><urls><style face="normal" font="default" size="100%">https://www.mdpi.com/1424-8220/21/7/2293</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.3390/s21072293</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">21</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Poster: Explainable classification of multimodal time series using LLMs</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style face="normal" font="default" size="100%">04/2024</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">5th Polish Conference on Artificial Intelligence (PP-RAI 2024)</style></secondary-title><pub-location><style face="normal" font="default" size="100%">Warsaw, Poland</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Katarzyna Filus</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Mateusz Żarski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Semantic Depth Matters: Explaining Errors of Deep Vision Networks through Perceived Class Similarities</style></title></titles><keywords/><dates/><secondary-title><style face="normal" font="default" size="100%">arXiv preprint</style></secondary-title><urls><style face="normal" font="default" size="100%">arXiv:2504.09956</style></urls><electronic-resource-num><style face="normal" font="default" size="100%"> https://doi.org/10.48550/arXiv.2504.09956</style></electronic-resource-num><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Manish Gupta</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Piotr Gawron</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Potential of quantum machine learning for processing multispectral Earth observation data</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style face="normal" font="default" size="100%">08/2025</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Bulletin of the Polish Academy of Sciences Technical Sciences</style></secondary-title><urls><style face="normal" font="default" size="100%">https://journals.pan.pl/dlibra/publication/154279/edition/135180/content</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.24425/bpasts.2025.154279</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">73</style></volume><issue><style face="normal" font="default" size="100%">5</style></issue><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Grochla</style></author><author><style face="normal" font="default" size="100%">Michał Romaszewski</style></author><author><style face="normal" font="default" size="100%">Jarosław Sotor</style></author><author><style face="normal" font="default" size="100%">Piotr Masłowski</style></author><author><style face="normal" font="default" size="100%">Bartosz Belter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards AI-assisted Science with PLAI4SCIENCE - new Polish Research Infrastructure</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style face="normal" font="default" size="100%">04/2025</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">6th Polish Conference on Artificial Intelligence (PP-RAI 2025)</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">L. Ding</style></author><author><style face="normal" font="default" size="100%">L. Zhang</style></author><author><style face="normal" font="default" size="100%">X. Wu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Y. Qunzhou</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Safety management in tunnel construction: Case study of Wuhan metro construction in China</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Safety Science</style></secondary-title><pages><style face="normal" font="default" size="100%">8–15</style></pages><volume><style face="normal" font="default" size="100%">62</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">L. Zhang</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">X. Wu</style></author><author><style face="normal" font="default" size="100%">Y. Chen</style></author><author><style face="normal" font="default" size="100%">Q. Deng</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A probabilistic approach for safety risk analysis in metro construction</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Safety Science</style></secondary-title><pages><style face="normal" font="default" size="100%">8–17</style></pages><volume><style face="normal" font="default" size="100%">63</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">L. Zhang</style></author><author><style face="normal" font="default" size="100%">X. Wu</style></author><author><style face="normal" font="default" size="100%">L. Ding</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">M. Hajdu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Decision support analysis for safety assurance in metro construction base on Fuzzy Bayesian Networks</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2013</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Creacive Construction 2013</style></secondary-title><pages><style face="normal" font="default" size="100%">896–909</style></pages><abstract><style face="normal" font="default" size="100%">This paper presents a novel and systemic decision support model based on Fuzzy Bayesian Networks (FBN) for safety assurance in metro construction. An expert confidence index is proposed for the fuzzification in probability assessment of basic risk factors, aiming to ensure the reliability of collected data during the expert investigation. A fuzzy-based decision approach, with the capacity of forward reasoning, sensitivity analysis and backward reasoning, is developed based on Bayesian inference. The safety assurance progress is extended to the entire life cycle of risk-prone events, including the pre-accident, during-construction continuous and post-accident control. A typical hazard concerning the tunnel leakage in the Wuhan Yangtze Metro Tunnel construction is presented in a case study. The results demonstrate the feasibility of the proposed method and its application potential. The proposed method can be used as a decision support tool to provide guidelines for safety assurance in metro construction, and thus increase the likelihood of a successful project in a complex environment.</style></abstract><publisher><style face="normal" font="default" size="100%">Sent Istvan University Ybl Miklos Faculty, Budapest</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">Creative Construction 2013 Conference, July 6-9, Budapest</style></notes></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">L. Zhang</style></author><author><style face="normal" font="default" size="100%">X. Wu</style></author><author><style face="normal" font="default" size="100%">L. Ding</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A novel model for risk assessment of adjacent buildings in tunneling environments</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2013</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Building and Environment</style></secondary-title><pages><style face="normal" font="default" size="100%">185–194</style></pages><volume><style face="normal" font="default" size="100%">65</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">L. Zhang</style></author><author><style face="normal" font="default" size="100%">X. Wu</style></author><author><style face="normal" font="default" size="100%">Q. Chen</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">S.-C. Hsu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards a safety management approach for adjacent buildings in tunneling environments: Case study in China</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Building and Environment</style></secondary-title><pages><style face="normal" font="default" size="100%">222–235</style></pages><volume><style face="normal" font="default" size="100%">75</style></volume><abstract><style face="normal" font="default" size="100%">This paper develops a systematic approach with detailed step-by-step procedures for safety management of existing buildings adjacent to tunneling excavation. The potential safety risk of a specific nearby building is assessed within four different risk levels, with the spatial neighbor relation (hazard parameter) and the building health condition (vulnerability component) taken into account. Compared with the traditional two-stage approach, a reasonable balance between the system safety and cost constrains is reached in the developed systematic approach, where the safety risk assessment is added in the first stage, and the assessed safety risk level acts as a decisive role in the depth of the subsequent two-stage numerical analyses. It is suggested that numerical simulation analyses should be employed in the situation where the existing building lies in a risk level of III (Medium risk) or IV (High risk). A case concerning the protection of a five-story framed building adjacent to a twin-tunnel in China is utilized to verify the applicability oh the proposed approach. The impact of both the tunnel excavation on the soil displacement and building foundation deformation is further analyzed in details. Results demonstrate the feasibility of the proposed approach, as well as its application potential. The proposed approach can be used by practitioners in the industry to provide guidelines on guaranteeing the system safety of adjacent buildings in tunneling environments. At the same time, the analysis cost can be greatly reduced, especially when a large number of existing buildings adjacent to tunneling excavation need to be protected.</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">L. Zhang</style></author><author><style face="normal" font="default" size="100%">X. Wu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">J. Zhong</style></author><author><style face="normal" font="default" size="100%">Y. Lu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bayesian-network-based safety risk analysis in construction project</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Reliability Engineering and System Safety</style></secondary-title><pages><style face="normal" font="default" size="100%">29–39</style></pages><volume><style face="normal" font="default" size="100%">131</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">S. Ghosh</style></author><author><style face="normal" font="default" size="100%">B. Lauren</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">N. Sam</style></author><author><style face="normal" font="default" size="100%">K.J. Hoon</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Organizational governance to integrate sustainability project: a case study.</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Technological and Economic Development of Economy</style></secondary-title><pages><style face="normal" font="default" size="100%">1–24</style></pages><volume><style face="normal" font="default" size="100%">20</style></volume><number><style face="normal" font="default" size="100%">1</style></number><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">H.-P. Tserng</style></author><author><style face="normal" font="default" size="100%">S.-H. Ju</style></author><author><style face="normal" font="default" size="100%">C.-W. Feng</style></author><author><style face="normal" font="default" size="100%">C.-T. Lin</style></author><author><style face="normal" font="default" size="100%">J.-Y. Han</style></author><author><style face="normal" font="default" size="100%">K.-W. Weng</style></author><author><style face="normal" font="default" size="100%">S.-C. Hsu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Web-based real time bridge scour monitoring system for disaster management.</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Baltic Journal of Road and Bridge Engineering</style></secondary-title><pages><style face="normal" font="default" size="100%">17–25</style></pages><volume><style face="normal" font="default" size="100%">9</style></volume><number><style face="normal" font="default" size="100%">1</style></number><abstract><style face="normal" font="default" size="100%">Natural disasters such as typhoous, earthquakes, and especially floods, often cause severe damage in Taiwan. Although bridge engineering technology has matured, the lack of an integrated bridge management system under sever disasters remains a challenge for the government. This research aims to develop a web-based system that displays the real time bridge scour information through combining Global Positioning System an Wirelles Sensor Networks technologies for bridges. The system also provides early warming for bridge safety based on a developed genetic model for estimating scour depth a round the bridge piers. The bridge safety monitoring agency utilizes the system as a decision support tool make the maintenance plan for bridges under severe weather conditions to prevent the damages from bridge collapse.</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">X.G. Wu</style></author><author><style face="normal" font="default" size="100%">Z. Jiang</style></author><author><style face="normal" font="default" size="100%">L.M. Zhang</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">J.B. Zhong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dynamic risk analysis for adjacent buildings in tunneling environments: a Bayesian network based approach</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2015</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Stochastic Enveronmental Research and Risk Assessment</style></secondary-title><pages><style face="normal" font="default" size="100%">1447–1461</style></pages><volume><style face="normal" font="default" size="100%">29</style></volume><abstract><style face="normal" font="default" size="100%">This paper presents a systemic Bayesian network (BN) based approach for dynamic risk analysis of adjacent buildings in tunneling environments, consisting of risk/hazard identification, BN learning and BN validation. Two validation indicators are proposed to evaluate the effectiveness of the established BN model, aiming to ensure that the model predictions are not significantly different from actual observations. In the dynamic risk analysis framework, the predictive, sensitivity and diagnostic techniques are used to conduct the feed-forward control in the pre-construction stage, intermediate control in the construction stage and back-forward control in the post-accident stage, respectively. A case regarding some existing buildings adjacent to construction of the Wuhan Yangtze metro tunnel in China is presented. The results demonstrate the feasibility of the proposed approach, as well as its application potential. The proposed approach can be used by practitioners in the industry as a decision support tool to provide guidelines on the conservation of adjacent buildings against tunnel-induced damages.</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wu Xianguo</style></author><author><style face="normal" font="default" size="100%">Liu Huitao</style></author><author><style face="normal" font="default" size="100%">Zhang Limao</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Deng Qianli</style></author><author><style face="normal" font="default" size="100%">Teng Jiaying</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A dynamic Bayesian network based approach to safety decision support in tunnel construction</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2015</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Reliability Engineering and System Safety</style></secondary-title><pages><style face="normal" font="default" size="100%">157–168</style></pages><volume><style face="normal" font="default" size="100%">134</style></volume><abstract><style face="normal" font="default" size="100%">This paper presents a systemic decision approach with step-by-step procedures based on dynamic Bayesian network (DBN), aiming to provide guidelines for dynamic safety analysis of the tunnel-induced road surface damage over time. The proposed DBN-based approach can accurately illustrate the dynamic and updated feature of geological, design and mechanical variables as the construction progress evolves,in order to overcome deficenciesof traditional fault analysis method. Adopting the predictive, sensitivity and diagnostic analysis techniques in the DBN inference, this this approach is able to perform feed-forward, concurrent and back-forward control respectively on a quantitative basis, and provide real-time support before and after an accident. A case study in relating to dynamic safety analysis in the construction of Wuhan Yangtze Metro Tunel in China is used to verify the feasibility of the proposed approach, as well as its application potential. The relationships between the DBN-based and BN-based approaches are further discussed according to analysis results. The proposed aproach can be used as a decision tool to provide support for safety analysis in tunnel construction, and thus increase the likelihood of a successful project in a dynamic project environment.</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Y. Lu</style></author><author><style face="normal" font="default" size="100%">Y. Li</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Z. Wu</style></author><author><style face="normal" font="default" size="100%">R. Wang</style></author><author><style face="normal" font="default" size="100%">Y. Le</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Information and communication technology applications in architecture, engineering, and construction organizations: a 15 year review</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2015</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Management in Engineering</style></secondary-title><volume><style face="normal" font="default" size="100%">31</style></volume><number><style face="normal" font="default" size="100%">1</style></number><abstract><style face="normal" font="default" size="100%">Information and communication technology (ICT) has had enormous effects on the development of architecture, engineering, and construction (AEC) organizations in past decades. The effects have resonated in various disciplines, such as organizational efficiency, communication approach, and employee behavior. However, a comprehensive and in-depth review of the ICT applied in the AEC organization is missing from the current literature. To fill this gap, this paper presents an in-depth review of mainstream studies of ICT-supported AEC organizations published in last 15years (1998-2012). A total of 145 articles from 12 construction and IT-related journals are identified and have been thoroughly reviewed. This review is divided into four parts: (1)synthesis and general trend of existing literature; (2)lessons learned from ICT practical implementation; (3)enabling technologies of ICT applications; and (4)ICT-induced organizational outcomes. Throughout this paper the authors summarize and categorize developments to date, discuss the advances and limitations of the use of ICT, and propose key areas for future research. This review can become a foundation for the classification and integration of the state of the art in ICT research on behalf of AEC organizations. (C) 2014 American Society of Civil Engineers.</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Y. Lu</style></author><author><style face="normal" font="default" size="100%">Y. Li</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Z. Wu</style></author><author><style face="normal" font="default" size="100%">R. Wang</style></author><author><style face="normal" font="default" size="100%">Y. Le</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Information and communication technology applications in architecture, engineering, and construction organizations: A 15-years review.</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Management in Engineering</style></secondary-title><volume><style face="normal" font="default" size="100%">31</style></volume><number><style face="normal" font="default" size="100%">special is</style></number><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Limao Zhang</style></author><author><style face="normal" font="default" size="100%">Xianguo Wu</style></author><author><style face="normal" font="default" size="100%">Yawei Qin</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Wenli Liu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel-Induced Pipeline Damage</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Risk Analysis</style></secondary-title><urls><style face="normal" font="default" size="100%">http://dx.doi.org/10.1111/risa.12448</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.1111/risa.12448</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">278–301</style></pages><volume><style face="normal" font="default" size="100%">36</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sun-Chan Bae</style></author><author><style face="normal" font="default" size="100%">Won-Suk Jang</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reliability performance of wireless sensor networks for civil infrastructure – Part II: prediction and verification</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Civil Engineering and Management</style></secondary-title><urls><style face="normal" font="default" size="100%">http://dx.doi.org/10.3846/13923730.2014.948909</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.3846/13923730.2014.948909</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">243-253</style></pages><volume><style face="normal" font="default" size="100%">22</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;AbstractApplication studies on wireless sensor networks (WSN) are actively conducted in the construction industry. However, there are several technical limitations including signal interference caused by the characteristics of wireless sensors, reliability degradation in wireless communication and uncertainty of configuring a network topology. This may lead to a decline in reliability and performance of real-time data acquisition methods. Thus, the paper developed a model capable of predicting reliability performance of wireless signals applied to civil infrastructures. The measured and predicted values of wireless signals are compared and analyzed through a field experiment carried out in an actual bridge to verify the prediction model suggested herein. As a result of the analysis, the prediction model demonstrated a variation up to 8.4% compared with actual measurements, proving the high accuracy of the prediction model. Furthermore, the reception rate at short distances within a 5 m radius is at least 90%, showing a highly reliable reception capacity. When this is applied to monitoring systems in the construction sector, it is believed that performance and reliability of such system can be secured.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Limao Zhang</style></author><author><style face="normal" font="default" size="100%">Xianguo Wu</style></author><author><style face="normal" font="default" size="100%">Lieyun Ding</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Yujie Lu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bim-Based Risk Identification System in tunnel construction</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Civil Engineering and Management</style></secondary-title><urls><style face="normal" font="default" size="100%">http://dx.doi.org/10.3846/13923730.2015.1023348</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.3846/13923730.2015.1023348</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">529-539</style></pages><volume><style face="normal" font="default" size="100%">22</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;AbstractThis paper presents an innovative approach of integrating Building Information Modeling (BIM) and expert systems to address deficiencies in traditional safety risk identification process in tunnel construction. A BIM-based Risk Identification Expert System (B-RIES) composed of three main built-in subsystems: BIM extraction, knowledge base management, and risk identification subsystems, is proposed. The engineering parameter information related to risk factors is first extracted from BIM of a specific project where the Industry Foundation Classes (IFC) standard plays a bridge role between the BIM data and tunnel construction safety risks. An integrated knowledge base, consisting of fact base, rule base and case base, is then established to systematize the fragmented explicit and tacit knowledge. Finally, a hybrid inference approach, with case-based reasoning and rule-based reasoning combined, is developed to improve the flexibility and comprehensiveness of the system reasoning capacity. B-RIES is used to overcome low-efficiency in traditional information extraction, reduce the dependence on domain experts, and facilitate knowledge sharing and communication among dispersed clients and domain experts. The identification of a safety hazard regarding the water gushing in one metro station of China is presented in a case study. The results demonstrate the feasibility of B-RIES and its application effectiveness.&lt;/p&gt;&#13;
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Wu</style></author><author><style face="normal" font="default" size="100%">YH Wang</style></author><author><style face="normal" font="default" size="100%">LM Zhang</style></author><author><style face="normal" font="default" size="100%">LY Ding</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">JB Zhong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Dynamic Decision Approach for Risk Analysis in Complex Projects</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style face="normal" font="default" size="100%">08/2015</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%"/></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1007/s10846-014-0153-3</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">591-601</style></pages><volume><style face="normal" font="default" size="100%">79</style></volume><issue><style face="normal" font="default" size="100%">3-4</style></issue><section><style face="normal" font="default" size="100%">591</style></section><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cheng Zhou</style></author><author><style face="normal" font="default" size="100%">Rui Chen</style></author><author><style face="normal" font="default" size="100%">Shuangnan Jiang</style></author><author><style face="normal" font="default" size="100%">Ying Zhou</style></author><author><style face="normal" font="default" size="100%">Lieyun Ding</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Xinggui Lin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Human dynamics in near-miss accidents resulting from unsafe behavior of construction workers</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Physica A: Statistical Mechanics and its Applications</style></secondary-title><urls><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S037843711930888X</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.physa.2019.121495</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">121495</style></pages><volume><style face="normal" font="default" size="100%">530</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Near misses, as a common result of unsafe behavior and/or unsafe conditions, are precursors of accidents in the construction industry. Given the complexity of near misses, seeking regularities in time series of near misses is almost impossible. We present a human dynamics model based on near-miss data to reveal common dynamic features of near-miss accidents that result from unsafe behavior of construction workers. To validate the model, we conducted an empirical case study based on unsafe behavior related to near misses from a database in the Early Warning System for Safety Risk Management in Wuhan Metro Construction, created by the Huazhong University of Science and Technology. Heavy-tailed distribution and approximate power-law distribution are observed in the inter-event time series of near misses, rather than being randomly distributed in time in current models. The strong burst and weak memory phenomena were observed in the whole, annual, and categorized inter-event time distributions of near misses. Moreover, the results showed a non-trivial, monotonous increase of the power-law exponent with the activity of different construction site in near misses, thus indicating that heterogeneity and complexity exist in general. We defined a new safety performance metric that is more reliable than the number of near misses and validated this performance metric by using expert assessment results of metro construction sites. Furthermore, we proposed further research prospects on human dynamics in construction safety behavior.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Shiyao Cai</style></author><author><style face="normal" font="default" size="100%">Zhiliang Ma</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Song Bao</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Construction automation and robotics for high-rise buildings over the past decades: A comprehensive review</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Advanced Engineering Informatics</style></secondary-title><urls><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S1474034619305622</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.aei.2019.100989</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">100989</style></pages><volume><style face="normal" font="default" size="100%">42</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Automation and robotics technology is expected to improve the productivity of the construction industry as well as to solve problems such as labor shortage and safety risks, especially for high-rise buildings. Substantial research efforts have been devoted to the field over the past decades, while the application rate at the construction sites is still limited. Although various reviews have summarized the research topics and future trends in this field, few research efforts have been made on a consideration of both academic research and practical application in the industry. Focusing on high-rise building construction, this study explores the development of both academic research and practical application of automation and robotics based on literature and market review. Scientometric and critical literature reviews were conducted to identify and analyze the development of key research areas based on academic publications from the 1980s to present. In the meantime, the development of basic technologies was summarized. The market review surveyed on existing products and developers of construction automation and robotics. By comparing the results of the literature review and market review, four development patterns of academic research and product application were identified, i.e., simultaneous development led by the same party, development at a similar pace with the two sides taking the lead in different aspects, academic research providing basic technologies for product development, and available technologies in academic research with no products found. Then three gaps in this field, i.e., the gap between academic research and products, the gap between products and application, and the gap between the construction industry and the robotics industry, were discussed with corresponding suggestions to narrow the gaps, followed by an outlook for future directions. This study contributes to the knowledge body by identifying and analyzing the key research areas and the development gaps systematically.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liang Wang</style></author><author><style face="normal" font="default" size="100%">Ping Zhang</style></author><author><style face="normal" font="default" size="100%">Li Ma</style></author><author><style face="normal" font="default" size="100%">Xuhui Cong</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Developing a corporate social responsibility framework for sustainable construction using partial least squares structural equation modeling</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Technological and Economic Development of Economy</style></secondary-title><pages><style face="normal" font="default" size="100%">186–212</style></pages><volume><style face="normal" font="default" size="100%">26</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kaiman Li</style></author><author><style face="normal" font="default" size="100%">Hanbin Luo</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A non-centralized adaptive method for dynamic planning of construction components storage areas</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Advanced Engineering Informatics</style></secondary-title><urls><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S1474034617305633</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.aei.2018.12.001</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">80 - 94</style></pages><volume><style face="normal" font="default" size="100%">39</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Rehandling of construction components, such as pipes, structural steel elements, and curtain walls, may increase the handling cost and reduce the construction efficiency, which is a critical issue for storage area plans of a project. Moreover, on some construction sites where space is limited, there are not adequate storage areas for centralized stacking of components and frequent changes in spatial state. Existing studies have investigated site layout planning for temporary facilities including arranging a storage area for the same type of material, which still have limitations in solving the above problems. This study proposes a novel and flexible arrangement method for incoming components in limited site space. This method is non-centralized and adaptive to the dynamic change of the actual component requirements based on construction activities and the real-time storage area availability. Therefore, a construction components storage areas planning (CCSAP) model is developed for dynamic allocation of construction components storage areas. Building information modeling (BIM) can be used to generate the material requirements planning before construction according to the actual construction activities. Real-time spatial recognition is a critical step for dynamic allocation of construction components storage areas because no such research has been done. This paper firstly presents an imaging technology with a low-rank matrix to identify on-site unoccupied locations automatically in real time. In addition, genetic algorithms (GA) consider two types of decision variables: actual components supply and real-time space availability. Finally, a dynamic visualization platform is built for planning construction components storage areas. An implementation example is demonstrated to validate principles and this model and shows a 21.9% reduction in the handling cost and a 19.4% increase in the construction efficiency compared with conventional methods.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Numan Khan</style></author><author><style face="normal" font="default" size="100%">Ahmad Ali</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Do Lee</style></author><author><style face="normal" font="default" size="100%">Chansik Park</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Excavation Safety Modeling Approach Using BIM and VPL</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Advances in Civil 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China</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of cleaner production</style></secondary-title><pages><style face="normal" font="default" size="100%">144–159</style></pages><volume><style face="normal" font="default" size="100%">208</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yue Pan</style></author><author><style face="normal" font="default" size="100%">Limao Zhang</style></author><author><style face="normal" font="default" size="100%">Xianguo Wu</style></author><author><style face="normal" font="default" size="100%">Wenwei Qin</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling face reliability in tunneling: A copula approach</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Computers and Geotechnics</style></secondary-title><pages><style face="normal" font="default" size="100%">272–286</style></pages><volume><style face="normal" font="default" size="100%">109</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Shengyu Guo</style></author><author><style face="normal" font="default" size="100%">Lieyun Ding</style></author><author><style face="normal" font="default" size="100%">Yongcheng Zhang</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Kongzheng Liang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Hybrid recommendation approach for behavior modification in the Chinese construction industry</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Construction Engineering and Management</style></secondary-title><pages><style face="normal" font="default" size="100%">04019035</style></pages><volume><style face="normal" font="default" size="100%">145</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jingfeng Yuan</style></author><author><style face="normal" font="default" size="100%">Wei Li</style></author><author><style face="normal" font="default" size="100%">Bo Xia</style></author><author><style face="normal" font="default" size="100%">Yuan Chen</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Operation performance measurement of public rental housing delivery by PPPS with fuzzy-AHP comprehensive evaluation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">International Journal of Strategic Property Management</style></secondary-title><pages><style face="normal" font="default" size="100%">328–353</style></pages><volume><style face="normal" font="default" size="100%">23</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cheng Zhou</style></author><author><style face="normal" font="default" size="100%">Lieyun Ding</style></author><author><style face="normal" font="default" size="100%">Ying Zhou</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Visibility graph analysis on time series of shield tunneling parameters based on complex network theory</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Tunnelling and Underground Space Technology</style></secondary-title><pages><style face="normal" font="default" size="100%">10–24</style></pages><volume><style face="normal" font="default" size="100%">89</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jingfeng Yuan</style></author><author><style face="normal" font="default" size="100%">Lei Zhang</style></author><author><style face="normal" font="default" size="100%">Yongtao Tan</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluating the regional social sustainability contribution of public-private partnerships in China: The development of an indicator system</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Sustainable Development</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jingfeng Yuan</style></author><author><style face="normal" font="default" size="100%">Wenying Ji</style></author><author><style face="normal" font="default" size="100%">Jiyue Guo</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Simulation-based dynamic adjustments of prices and subsidies for transportation PPP projects based on stakeholders’ satisfaction</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Transportation</style></secondary-title><pages><style face="normal" font="default" size="100%">2309–2345</style></pages><volume><style face="normal" font="default" size="100%">46</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Limao Zhang</style></author><author><style face="normal" font="default" size="100%">Xianguo Wu</style></author><author><style face="normal" font="default" size="100%">Wenli Liu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimal Strategy to Mitigate Tunnel-Induced Settlement in Soft Soils: Simulation Approach</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Performance of Constructed Facilities</style></secondary-title><pages><style face="normal" font="default" size="100%">04019058</style></pages><volume><style face="normal" font="default" size="100%">33</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yue Pan</style></author><author><style face="normal" font="default" size="100%">Limao Zhang</style></author><author><style face="normal" font="default" size="100%">Xianguo Wu</style></author><author><style face="normal" font="default" size="100%">Kainan Zhang</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Structural health monitoring and assessment using wavelet packet energy spectrum</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Safety Science</style></secondary-title><pages><style face="normal" font="default" size="100%">652–665</style></pages><volume><style face="normal" font="default" size="100%">120</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yue Pan</style></author><author><style face="normal" font="default" size="100%">Limao Zhang</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Clustering of designers based on building information modeling event logs</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style face="normal" font="default" size="100%">2020</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Computer-Aided Civil and Infrastructure Engineering</style></secondary-title><urls><style face="normal" font="default" size="100%">https://onlinelibrary.wiley.com/doi/abs/10.1111/mice.12551</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.1111/mice.12551</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">35</style></volume><issue><style face="normal" font="default" size="100%">7</style></issue><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A network-enabled event log mining approach is proposed for a deep understanding of the Building Information Modeling (BIM)-based collaborative design work. It proposes a novel algorithm termed node2vec-GMM combining a graph embedding algorithm named node2vec and a clustering method named Gaussian mixture model (GMM) to cluster designers within a network into several subgroups, and then makes cluster analysis. Its superiority lies in the efficient feature learning ability to preserve network structure and the powerful clustering ability to tackle uncertainty and visualize results, which can directly return the cluster embedding. As a case study, a directional network with 68 nodes (designers) and 436 ties (design task transmissions) is constructed based on retrieved data from 4GB real BIM event logs. The node2vec learns and projects the network feature representation into a 128-dimensional vector, which is learned by GMM to discover three possible clusters owning 15, 26, and 27 closely linked designers. Analysis of each cluster is performed from node importance measurement and link prediction to identify information spreading and designers’ roles within clusters. Our new algorithm node2vec-GMM is proven to better improve clustering quality than other state-of-the-art methods by at least 6.0% Adjusted Rand Index and 13.4% Adjusted Mutual Information. Overall, the designer clustering process provides managers with data-driven support in both monitoring the whole course of the BIM-based design and making reliable decisions to increase collaboration opportunities.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Xuan Zhang</style></author><author><style face="normal" font="default" size="100%">Witold Pedrycz</style></author><author><style face="normal" font="default" size="100%">Xian-Jia Wang</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bid evaluation in civil construction under uncertainty: A two-stage LSP-ELECTRE III-based approach</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Engineering Applications of Artificial Intelligence</style></secondary-title><urls><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S0952197620302025</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.engappai.2020.103835</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">103835</style></pages><volume><style face="normal" font="default" size="100%">94</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Increasing growth and development of building industry and civil engineering motivates enterprises to advance bid evaluation process in an effort to ameliorate building quality and diminish construction cost. The selection of qualified construction contractor has been generally formulated and addressed as a multi-attribute group decision-making problem. However, few existing studies have taken the reasoning logic pattern in human cognition process and the compensatory among attributes into account. Therefore, a two-stage logic scoring of preference-ELECTRE III-based approach is established for the management and manipulation of bidder selection. In a bid to facilitate expert evaluation articulation, alternative-attribute assessments in this approach take the form of generalized comparative linguistic expressions, which are subsequently converted into possibility-distribution-based hesitant fuzzy linguistic term set via the similarity measure-based generation approach to enhance information quality and reliability. Then, nonlinear optimization-based direction rules are introduced to advance the automatic minimum-distance-based consensus reaching model and based on which, the individual semantic-embedded assessments are algorithmically adjusted to reach acceptable consensus. Furthermore, the expert and attribute importance degrees are extracted from both semantic and formal logic aspects, and the modified individual assessments are gathered by integrating the two-stage logic scoring of preference aggregation structure and the ELECTRE III method. The present approach provides a solution to bid evaluation problems considering the reasoning logic pattern in human cognition process and the compensatory among attributes. A practical case study and a comparative analysis are performed to demonstrate the feasibility and effectiveness of the established multi-attribute group decision-making approach.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hui Liu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Qianqian Ju</style></author><author><style face="normal" font="default" size="100%">Junjie Li</style></author><author><style face="normal" font="default" size="100%">Hongbing Jiang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BIM-enabled construction innovation through collaboration: a mixed-methods systematic review</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Engineering, Construction and Architectural Management</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaer Xiahou</style></author><author><style face="normal" font="default" size="100%">Jingfeng Yuan</style></author><author><style face="normal" font="default" size="100%">Hong Xie</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Qiming Li</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploring driving factors of smart city development under the physical-human society-cyber (PHC) space model</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><secondary-title><style face="normal" font="default" size="100%">International Journal of Construction Management</style></secondary-title><pages><style face="normal" font="default" size="100%">1–11</style></pages><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The concept of Smart City (SC) with its ambitious scheme has successfully attracted the interests of different stakeholders (i.e., government, information and communication technologies vendors, as well as researchers). While great efforts have been concentrating on the interpretation and the implementation of the ‘smartness’, the incentives for SC development are ignored. Understanding the incentives would clarify the goals of SC development and thereby boost its development efficiency. By exploring existing researches and cases of Nanjing, China, 15 factors were identified using a proposed physical-human society-cyber (P-H-C) space model. A structured questionnaire survey was conducted among different stakeholders in Nanjing to investigate their attitudes towards these factors. In factor analysis, these factors are grouped into three dimensions: technology push, government pull, and user-driven. Results show that currently SC development is mainly pushed by the technical progress and innovations. Meanwhile, government plays a significant role in pulling SC development especially at the initial stage. In addition, requirements to enhance the experience of end-users including government, companies, citizens etc. are critical for SC development. This paper provides insight on the incentives of SC development, research findings could be used as guidelines for the SC development in cities worldwide.&lt;/p&gt;</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xijun Yao</style></author><author><style face="normal" font="default" size="100%">Hsi-Hsien Wei</style></author><author><style face="normal" font="default" size="100%">Igal Shohet</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessment of Terrorism Risk to Critical Infrastructures: The Case of a Power-Supply Substation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style face="normal" font="default" size="100%">oct</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Applied Sciences</style></secondary-title><urls><style face="normal" font="default" size="100%">https://www.mdpi.com/2076-3417/10/20/7162</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.3390/app10207162</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">7162</style></pages><volume><style face="normal" font="default" size="100%">10</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper presents a novel approach for estimating the vulnerability level of critical infrastructure confronting potential terrorist threats and assessing the usefulness of various protection strategies for critical infrastructure (CI). A methodology, utilizing a combination of topological network analysis and game theory, is presented to evaluate the effectiveness of protection strategies for certain components in the infrastructure under various attack scenarios. This paper focuses on protective strategies that are based on different attack scenarios as well as on the connectivity of the critical infrastructure components. The methodology proposed allows optimization of protection strategies in terms of investment in critical infrastructure protection in order to reduce expenditures on local infrastructure protection or on a single critical infrastructure for small projects. A case study of a power-supply substation is included to validate the analytical framework. The results indicate that the framework is highly applicable to other types of critical infrastructures facing similar threats. The results suggest that when only terrorist attacks are considered, improving the robustness of CI has a much higher effectiveness and efficiency than improving CI redundancy. The research methodology in this paper can be applied to a wide range of critical infrastructures and systems that may be at risk from manmade extreme events.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lei Zhang</style></author><author><style face="normal" font="default" size="100%">Jingfeng Yuan</style></author><author><style face="normal" font="default" size="100%">Nini Xia</style></author><author><style face="normal" font="default" size="100%">Yan Ning</style></author><author><style face="normal" font="default" size="100%">Junwei Ma</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Measuring value-added-oriented BIM climate in construction projects: dimensions and indicators</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Civil Engineering and Management</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.3846/jcem.2020.13893</style></electronic-resource-num><pages><style face="normal" font="default" size="100%">800–818</style></pages><volume><style face="normal" font="default" size="100%">26</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>28</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Limao Zhang</style></author><author><style face="normal" font="default" size="100%">Yue Pan</style></author><author><style face="normal" font="default" size="100%">Xianguo Wu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Artificial Intelligence in Construction Engineering and Management</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Lecture Notes in Civil Engineering</style></secondary-title><pages><style face="normal" font="default" size="100%">XI, 263</style></pages><volume><style face="normal" font="default" size="100%">163</style></volume><abstract><style face="normal" font="default" size="100%">&lt;div class="springer-html"&gt;&#13;
&lt;p&gt;This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally.&lt;/p&gt;&#13;
&lt;/div&gt;&#13;
</style></abstract><isbn><style face="normal" font="default" size="100%">978-981-16-2842-9</style></isbn><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ming Hu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Green Building Construction Cost Surcharge: An Overview</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Architectural Engineering</style></secondary-title><volume><style face="normal" font="default" size="100%">27</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yue Pan</style></author><author><style face="normal" font="default" size="100%">Limao Zhang</style></author><author><style face="normal" font="default" size="100%">Zhenzhen Yan</style></author><author><style face="normal" font="default" size="100%">May Lwin</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Discovering optimal strategies for mitigating COVID-19 spread using machine learning: Experience from Asia</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Sustainable cities and society</style></secondary-title><volume><style face="normal" font="default" size="100%">75</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Lan-Lan Yang</style></author><author><style face="normal" font="default" size="100%">Kwai-Sang Chin</style></author><author><style face="normal" font="default" size="100%">Yi Yang</style></author><author><style face="normal" font="default" size="100%">Witold Pedrycz</style></author><author><style face="normal" font="default" size="100%">Jian-Peng Chang</style></author><author><style face="normal" font="default" size="100%">Luis Martínez</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sustainable building material selection: An integrated multi-criteria large group decision making framework</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Applied Soft Computing</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.asoc.2021.107903</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">113, Part A</style></volume><section><style face="normal" font="default" size="100%">107903</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In the past decades, the rapid urbanisation has driven the prosperity of building industry, which, however, has led to the consumption of enormous amounts of energy and resources and the continued deterioration of the environment owing to its unsustainable development. These outcomes impact seriously the ecosystems and human health. In order to promote the sustainable performance of building sector, the widely adoption of sustainable building materials has been considered as one of the most promising ways toward this endeavor. This paper aims at addressing the problem of sustainable building material selection (SBMS) under uncertain context by developing an integrated multi-criteria large-group decision-making framework. In the proposed framework, the assessment information is characterised in the form of Improved Basic Uncertain Linguistic Information (IBULI), which incorporates reliable degrees of decision experts that can accurately quantify subjective assessment information provided under uncertainty. The weights of assessment criteria for SBMS are determined by the Quality Function Deployment-based method that is capable of accommodating the influences of multiple stakeholders and the fields of conflicts amongst them. Subsequently, the assessment information given by a large-group of decision experts are aggregated by IBULI-aggregation operators guided by an IBULI-based correlation- and consensus-driven clustering method, which achieves the classification of large-scale decision experts and the satisfied consensus level simultaneously. The selection of sustainable building materials is eventually accomplished by the IBULI-based Technique for Order Preference by Similarity to Ideal Solution method. Finally, an illustrative example accompanied by sensitivity and comparative analyses is performed to verify the rationality and feasibility of the proposed model.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ali Khoso</style></author><author><style face="normal" font="default" size="100%">Aminah Yusof</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Kwai-Sang Chin</style></author><author><style face="normal" font="default" size="100%">Shabir Khahro</style></author><author><style face="normal" font="default" size="100%">Samiullah Sohu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comprehensive analysis of state-of-the-art contractor selection models in construction environment-A critical review and future call</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Socio-Economic Planning Sciences</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Svetlana Besklubova</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Xueqing Zhang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Factors Affecting 3D Printing Technology Adaptation in Construction</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Construction Engineering and Management</style></secondary-title><volume><style face="normal" font="default" size="100%">147</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ming Hu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Review of Building Construction Cost Research: Current Status, Gaps and Green Buildings</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%"/></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xuhui Cong</style></author><author><style face="normal" font="default" size="100%">Li Ma</style></author><author><style face="normal" font="default" size="100%">Liang Wang</style></author><author><style face="normal" font="default" size="100%">Jonas Šaparauskas</style></author><author><style face="normal" font="default" size="100%">Jarosław Górecki</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The early warning system for determining the “not in My Back Yard” of heavy pollution projects based on public perception</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Cleaner Production</style></secondary-title><volume><style face="normal" font="default" size="100%">282</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Muhammad Khan</style></author><author><style face="normal" font="default" size="100%">Numan Khan</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Chansik Park</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Environmental Particulate Matter (PM) Exposure Assessment of Construction Activities Using Low-Cost PM Sensor and Latin Hypercubic Technique</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Sustainability</style></secondary-title><volume><style face="normal" font="default" size="100%">13</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Han-Tang Huang</style></author><author><style face="normal" font="default" size="100%">H Ping Tserng</style></author><author><style face="normal" font="default" size="100%">Ruei-Yu Hou</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Wireless Sensor Network-Based Monitoring of Bridge Pile Foundations for Detecting Scouring Depth</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Marine Science and Technology</style></secondary-title><volume><style face="normal" font="default" size="100%">29</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Y. Pan</style></author><author><style face="normal" font="default" size="100%">L. Zhang</style></author><author><style face="normal" font="default" size="100%">J. Unwin</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Discovering spatial-temporal patterns via complex networks in investigating COVID-19 pandemic in the United States</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2022</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Sustainable Cities and Society</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.scs.2021.103508</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">77</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A novel approach combining time series analysis and complex network theory is proposed to deeply explore characteristics of the COVID-19 pandemic in some parts of the United States (US). It merges as a new way to provide a systematic view and complementary information of COVID-19 progression in the US, enabling evidence-based responses towards pandemic intervention and prevention. To begin with, the Principal Component Analysis (PCA) varimax is adopted to fuse observed time-series data about the pandemic evolution in each state across the US. Then, relationships between the pandemic progress of two individual states are measured by different synchrony metrics, which can then be mapped into networks under unique topological characteristics. Lastly, the hidden knowledge in the established networks can be revealed from different perspectives by network structure measurement, community detection, and online random forest, which helps to inform data-driven decisions for battling the pandemic. It has been found that states gathered in the same community by diffusion entropy reducer (DER) are prone to be geographically close and share a similar pattern and tendency of COVID-19 evolution. Social factors regarding the political party, Gross Domestic Product (GDP), and population density are possible to be significantly associated with the two detected communities within a constructed network. Moreover, the cluster-specific predictor based on online random forest and sliding window is proven useful in dynamically capturing and predicting the epidemiological trends for each community, which can reach the highest.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hui Liu</style></author><author><style face="normal" font="default" size="100%">Qianqian Ju</style></author><author><style face="normal" font="default" size="100%">Na Zhao</style></author><author><style face="normal" font="default" size="100%">Hujun Li</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Hanliang Fu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Value Proposition for Enabling Construction Project Innovation by Applying Building Information Modeling</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style face="normal" font="default" size="100%">jan</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Computational Intelligence and Neuroscience</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1155/2022/2586307</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">2022</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yang Liu</style></author><author><style face="normal" font="default" size="100%">Xian-Jia Wang</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Yifei Zhang</style></author><author><style face="normal" font="default" size="100%">Shenghao Zhao</style></author><author><style face="normal" font="default" size="100%">Muhammet Devici</style></author><author><style face="normal" font="default" size="100%">LeSheng Jin</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluating Digital Health Services Quality via Social Media</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">01/08/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on Engineering Management</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1109/TEM.2023.3298906</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Given the widespread demand for digital health services, a systematic study on the quality of digital health services is essential. Based on the current situation of tertiary hospitals in central China providing digital health services via social media, we used the Cronbach and Bayesian Best and Worst methods to evaluate the quality of hospital digital health services and conduct an empirical study of several hospitals. Based on the results of the empirical study, we propose a path for constructing a digital health service platform, suggesting that hospitals focus on building business function services of social media and accelerate the development of Internet hospitals. Hospitals should also improve the operation and maintenance of social media, optimize the intelligence of online guidance, and simplify the design logic of function menus. In terms of content information services, hospitals need to design targeted content according to the characteristics of different social media, improve content quality, and ensure the appropriate proportion of various types of information. With such measures, hospitals can guide users to use social media through business function services and retain users through content information services to increase the influence of hospitals and the quality of social health welfare.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Zachary Laan</style></author><author><style face="normal" font="default" size="100%">Kaveh Sadabadi</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Predicting work zone collision probabilities via clustering: application in optimal deployment of highway response teams</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2018</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Advanced Transportation</style></secondary-title><volume><style face="normal" font="default" size="100%">2018</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bartosz Wójcik</style></author><author><style face="normal" font="default" size="100%">Mateusz Żarski</style></author><author><style face="normal" font="default" size="100%">Kamil Książek</style></author><author><style face="normal" font="default" size="100%">Jaroslaw Miszczak</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A deep learning method for hard-hat-wearing detection based on head center localization</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">10/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Bulletin of the Polish Academy of Sciences Technical Sciences</style></secondary-title><urls><style face="normal" font="default" size="100%">https://journals.pan.pl/dlibra/publication/147340/edition/128931/content</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.24425/bpasts.2023.147340</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">71 (EA)</style></volume><issue><style face="normal" font="default" size="100%">6</style></issue><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In recent years, a lot of attention is paid to deep learning methods in the context of vision-based construction site safety systems. However, there is still more to be done to establish the relationship between supervised construction workers and their essential personal protective equipment, like hard hats. A deep learning method combining object detection, head center localization, and simple rule-based reasoning is proposed in this article. In tests, this solution surpassed the previous methods based on the relative bounding box position of different instances and direct detection of hard hat wearers and non-wearers. Achieving MS COCO style overall AP of 67.5% compared to 66.4% and 66.3% achieved by the approaches mentioned above, with class-specific AP for hard hat non-wearers of 64.1% compared to 63.0% and 60.3%. The results show that using deep learning methods with a humanly interpretable rule-based algorithm is better suited for detecting hard hat non-wearers.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Chong-Ze Liang</style></author><author><style face="normal" font="default" size="100%">Ya-Qiang Xu</style></author><author><style face="normal" font="default" size="100%">Witold Pedrycz</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dynamic collective opinion generation framework for digital transformation barrier analysis in the construction industry</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style face="normal" font="default" size="100%">03/2024</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Information Fusion</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.inffus.2023.102096</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">103</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The absence of a reliable, dynamic evaluation system has impeded early-stage industrial research progress, particularly in the digital transformation of the construction industry. Moreover, existing research studies rarely explore the impact of digitalt transformation barriers considering the interplays among them. This paper aims to introduce an innovative framework to generate dynamic collective opinions for barrier analysis in such context. The proposed dynamic collective opinion generation framework comprises three key components: Collective Opinion Generation, Prediction with Expert Advice (PEA), and Social Network Analysis. Its goal is to provide dependable decision support when subjective evaluation data from experts is available. Initially, a bi-objective optimization model generates the initial barrier weight vector. The PEA incorporates a loss function to measure the deviation between aggregated probablity density function and actual observed data, updating the weight vector over time. Next, an influence network covering all barriers is established. Node significance is evaluated through metrics like degree centrality, closeness centrality, and eigenvector centrality. The gravity model based on three metrics is used to determine interrelationships among barriers, resulting in a weight vector capturing these interplays. The two weight vectors are combined with Nash equilibrium, yielding the ultimate weight vector for barriers. The effectiveness of the proposed dynamic collective opinion generation framework is showcased through a case study on China Construction Third Bureau. Results indicate that talent structure notably influences construction companies' digital transformation. Additionally, market structure and strategic position significantly impact digital transformation in this industry.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Zhuo-Ran Wang</style></author><author><style face="normal" font="default" size="100%">Muhammet Deveci</style></author><author><style face="normal" font="default" size="100%">Weiping Ding</style></author><author><style face="normal" font="default" size="100%">Witold Pedrycz</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimization-based probabilistic decision support for assessing building information modelling (BIM) maturity considering multiple objectives</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style face="normal" font="default" size="100%">02/2024</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Information Fusion</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.inffus.2023.102026</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">102</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The phase of&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/operation-and-maintenance" title="Learn more about operation and maintenance from ScienceDirect's AI-generated Topic Pages"&gt;operation and maintenance&lt;/a&gt;&#160;(O&amp;M) is the most time-consuming and cost-intensive stage in the&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/project-life-cycle" title="Learn more about project life cycle from ScienceDirect's AI-generated Topic Pages"&gt;project life cycle&lt;/a&gt;. However, the potential benefits of&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/building-information-modeling" title="Learn more about Building Information Modeling from ScienceDirect's AI-generated Topic Pages"&gt;Building Information Modeling&lt;/a&gt;&#160;(BIM) in this phase have not been fully explored, unlike in the design and construction phases. This is particularly evident in the absence of a comprehensive assessment of its application capabilities. In light of this setting, we develop a BIM maturity assessment model (BIM MAM) for the project’s O&amp;M phase. The proposed model comprises of an assessment indicator system that facilitates experts in providing individual assessment results, and a collective opinion aggregation method in a&#160;&lt;a href="https://www.sciencedirect.com/topics/computer-science/probabilistic-context" title="Learn more about probabilistic context from ScienceDirect's AI-generated Topic Pages"&gt;probabilistic context&lt;/a&gt;&#160;based on a multi-objective optimization model that is employed to generate the ultimate collective assessment results. The established multi-objective optimization model for BIM MAM incorporates the influence of human behavior factors on the final results by introducing the fairness concern utility level as an objective. Finally, we take Wuhan Jiangxia&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/sewage-treatment-plant" title="Learn more about Sewage Treatment Plant from ScienceDirect's AI-generated Topic Pages"&gt;Sewage Treatment Plant&lt;/a&gt;&#160;as a practical case to illustrate the effectiveness and feasibility of the proposed BIM MAM.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Kou-Dan Chen</style></author><author><style face="normal" font="default" size="100%">Ya-Qiang Xu</style></author><author><style face="normal" font="default" size="100%">Witold Pedrycz</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiobjective optimization-based decision support for building digital twin maturity measurement</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style face="normal" font="default" size="100%">01/2024</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Advanced Engineering Informatics</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.aei.2023.102245</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">59</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The&#160;&lt;a href="https://www.sciencedirect.com/topics/computer-science/digital-twin" title="Learn more about digital twin from ScienceDirect's AI-generated Topic Pages"&gt;digital twin&lt;/a&gt;&#160;(DT) represents a powerful tool for advancing construction industry to provide a cyber–physical integration that enables real-time monitoring of assets and activities and facilitates decision-making. Due to the inherent characteristics of the construction industry and the diverse possibilities with DT, proliferation of building digital twin (BDT) necessitates a comprehensive comprehension of its evolution and the creation of roadmaps. This paper aims to contribute to the formalization and standardization of BDT. It designs a novel assessment framework for the overall maturity measurement of existing BDT projects. The developed BDT maturity model incorporates a collective opinion generation paradigm based on a fairness-aware&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/multiobjective-optimization" title="Learn more about multiobjective optimization from ScienceDirect's AI-generated Topic Pages"&gt;multiobjective optimization&lt;/a&gt;&#160;model to provide an expert-based evaluation system for evaluating the maturity of BDT projects. The effectiveness and feasibility of the proposed framework have been validated through a case study of an experimental BDT initiative. This paper establishes a generalizable framework for BDT maturity assessment that can offer insights into BDT maturity standards to construction practitioners to create effective strategies for the diffusion, development, and maturation of BDT.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Jia Zhou</style></author><author><style face="normal" font="default" size="100%">Chen-Ye Zhu</style></author><author><style face="normal" font="default" size="100%">Zhu-Jun Wang</style></author><author><style face="normal" font="default" size="100%">Sheng-Hua Xiong</style></author><author><style face="normal" font="default" size="100%">Rosa Rodríguez</style></author><author><style face="normal" font="default" size="100%">Luis Martinez</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">12/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Financial Innovation</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1186/s40854-023-00517-y</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">9</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness. In the context of real estate enterprises, credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects. Additionally, it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry. However, Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns, making subjective evaluation approaches inevitable, occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks. To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises, this study proposes an integrated multi-criteria group decision-making approach. First, a credit risk assessment index for Chinese real estate enterprises is established. Then, the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods. This approach is suitable for processing large amounts of data with high uncertainty, which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjective evaluation information. Finally, the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility. This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huanbao Liu</style></author><author><style face="normal" font="default" size="100%">Zihan Li</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Liang Wang</style></author><author><style face="normal" font="default" size="100%">Xuhui Cong</style></author><author><style face="normal" font="default" size="100%">Jarosław Górecki</style></author><author><style face="normal" font="default" size="100%">Wenyu Jin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Molding quality control with nonlinear forming method in 3D cement printing</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">11/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Materials and Design</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.matdes.2023.112455</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">235</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;3D cement printing is an emerging technology that can construct building elements without formwork, which has broad application prospects in the field of constructing non-linear and complex building structures. However, the high-quality printing and molding of nonlinear structure has become one of the bottleneck technologies restricting the development of 3D building printing. In this paper, variable radian 3D printing nozzle is firstly developed to verify the controllability of extruded concrete material based on self-developed 3D building printer. Then, variable radian forming theory is presented and used to evaluate the mechanism material fracture and accumulation, and improve the molding quality of nonlinear structure. Finally, simulation analysis and experiments are designed to explore the controllable mechanism of variable radian molding and verify the consistency between the experimental results and the theoretical analysis. The research results can promote the application of 3D printing in the construction industry, and provide support for the utilization of building resources and green buildings.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lu Xiao</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Rui Hou</style></author><author><style face="normal" font="default" size="100%">Abbas Mardani</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Greenness-based subsidy and dual credit policy to promote new energy vehicles considering consumers' low-carbon awareness</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">11/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Computers and Industrial Engineering</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI:10.1016/j.cie.2023.109620</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">185</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Considering a market consisting of a new energy vehicle (NEV) manufacturer, a fuel vehicle (FV) manufacturer, the government, and consumers with low-carbon awareness, this paper constructs NEV-FV competitive models to study the effect of greenness-based subsidy policy and dual credit policy on prices, quantities, profits, consumer surplus and social welfare. Under the greenness-based subsidy policy, the government provides subsidies based on NEVs’ carbon emission reduction to consumers. Under the dual credit policy, the FV manufacturer has to purchase NEV credits from the NEV manufacturer before starting to manufacture. The government’s optimal subsidy strategy and the two manufacturers’ pricing and production strategies of two kinds of vehicles are studied. The impact of consumers’ low-carbon awareness, NEVs’ carbon emission reduction, unit production cost, and unit cost gap between two kinds of vehicles with respect to equilibrium decisions are analyzed. The results show that both the greenness-based subsidy policy and dual credit policy can improve NEVs’ market share when the manufacturing cost gap is relatively low, and enhance the NEV firm’s competitiveness when the investment cost of greenness-enhancement is relatively low. The subsidy policy can improve social welfare, whereas the dual credit policy is harmful to social welfare. In terms of promoting the sales and profits of NEVs, both the subsidy policy and dual credit policy can play a positive role under different conditions.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Jing-Yi Lu</style></author><author><style face="normal" font="default" size="100%">Jiang-Tao Wen</style></author><author><style face="normal" font="default" size="100%">Xianjia Wang</style></author><author><style face="normal" font="default" size="100%">Muhammet Deveci</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BIM-enabled decision optimization analysis for architectural glass material selection considering sustainability</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">11/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Information Sciences</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.ins.2023.119450</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">647</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The careful consideration and choice of Sustainable Architectural Glass Material (SAGM) is a crucial step towards&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/reducing-energy-consumption" title="Learn more about reducing energy consumption from ScienceDirect's AI-generated Topic Pages"&gt;reducing energy consumption&lt;/a&gt;&#160;and enhancing the overall sustainability of buildings. However, the current techniques employed for selecting architectural glass material do not take into account the aspect of sustainability in the ultimate adoption of material solutions, as perceived by the stakeholders. This study aims to develop a comprehensive evaluation criteria system and introduce a group decision support framework that utilizes&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/building-information-modeling" title="Learn more about Building Information Modeling from ScienceDirect's AI-generated Topic Pages"&gt;Building Information Modeling&lt;/a&gt;&#160;technology to facilitate the selection of SAGM in large-scale projects, in accordance with the demands of various stakeholders. The proposed framework is utilized to address a selection problem related to SAGM faced by a large construction corporation in Wuhan. The findings indicate that the criteria of daylighting and&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/thermal-insulation" title="Learn more about thermal insulation from ScienceDirect's AI-generated Topic Pages"&gt;thermal insulation&lt;/a&gt;&#160;performance hold significant importance, with insulating glass being a subtype of SAGM exhibiting superior performance. Ultimately, the proposed model is subjected to sensitivity and comparative analyses to validate its advantages over several existing methodologies. The proposed model in this study offers practitioners an optimized methodology for the selection of SAGM, while also providing a framework for the selection of other sustainable&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/building-material" title="Learn more about building materials from ScienceDirect's AI-generated Topic Pages"&gt;building materials&lt;/a&gt;.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xuhui Cong</style></author><author><style face="normal" font="default" size="100%">Zhipeng Qi</style></author><author><style face="normal" font="default" size="100%">Sai Wang</style></author><author><style face="normal" font="default" size="100%">Peikun Su</style></author><author><style face="normal" font="default" size="100%">Liang Wang</style></author><author><style face="normal" font="default" size="100%">Jonas Šaparauskas</style></author><author><style face="normal" font="default" size="100%">Jarosław Górecki</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Ecological Welfare Performance Evaluation and Spatial–Temporal Difference Evolution of Blue Economic Zones: A Case Study of the Blue Economic Zone of Shandong Peninsula</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">10/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Land</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI:10.3390/land12101886</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">12 (10)</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Ecological security (ES) is an important element in the construction of an ecological civilization and plays a vital role in ensuring the sustainable development of social economies. Further, ES is an important measure of regional sustainable development. Based on ecosystem theory, this study constructs a comprehensive evaluation framework using the driving force-pressure-state-impact-response (DPSIR) and slacks-based measure of&#160;&lt;a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/data-envelopment-analysis" title="Learn more about data envelopment analysis from ScienceDirect's AI-generated Topic Pages"&gt;data envelopment analysis&lt;/a&gt;&#160;(SBM-DEA) models. Taking the Three Gorges Reservoir Area as an example, the study develops an ES evaluation system and realizes a transformation from “efficiency” to “quality”.Gray correlation theory and spatial&#160;&lt;a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/autocorrelation" title="Learn more about autocorrelation from ScienceDirect's AI-generated Topic Pages"&gt;autocorrelation&lt;/a&gt;&#160;and are adopted to analyze the ecosystem's spatial–temporal evolution and driving factors. The results demonstrate that the overall level of ES in the Three Gorges Reservoir Area from 2010 to 2020 was good; however, the spatial distribution of ES revealed an unbalanced state. The influence of each subsystem on the result of the ES evaluation is state &gt; response &gt; impact &gt; driving force &gt; pressure. The spatial correlation analysis of ES in the Three Gorges Reservoir area exhibited a positive autocorrelation, and the agglomeration effect was significant; on this basis, the key factors affecting ES were identified. The ratio of environmental protection investment,&#160;&lt;a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/sewage-treatment" title="Learn more about sewage treatment from ScienceDirect's AI-generated Topic Pages"&gt;sewage treatment&lt;/a&gt;&#160;rate, green coverage rate of built-up areas, proportion of primary industry in GDP, and proportion of tertiary industry in GDP had notable effects on the ES of the study area. The research contributes to the theory of ES and provides guidance for ecologically sustainable development.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhu-Jun Wang</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Qin Su</style></author><author><style face="normal" font="default" size="100%">Lu Xiao</style></author><author><style face="normal" font="default" size="100%">Kannan Govindan</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Blockchain adoption in sustainable supply chains for Industry 5.0: A multistakeholder perspective</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">12/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Innovation and Knowledge</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.jik.2023.100425</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">8(4)</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Industry 5.0 has introduced a novel interpretation of sustainable supply chains (SSCs) that emphasizes the importance of building a transparent and trustworthy network that can be continuously monitored and controlled through stakeholder collaboration as well as the use of advanced, intelligent machinery. The ultimate goal of SSCs is to meet specific economic, social, and environmental standards. The implementation of blockchain technology can significantly improve the reliability, efficiency, and security of the information exchanged among stakeholders in SSCs. However, these stakeholders inevitably possess varying informational advantages and exhibit divergent perspectives regarding the adoption of blockchain technology. This paper thus aims to examine the impediments to the adoption of blockchain technology in the context of SSCs with the goal of promoting blockchain adoption. To achieve this objective, this study analyzes the barriers to blockchain adoption from the perspectives of various stakeholders in SSCs and&#160;constructs a barrier severity assessment model that utilizes group decision-making methods to integrate all stakeholders’ attitudes. This study employs the PEEST (political, economic, environmental, social, and technological) framework to identify 27 barriers to the adoption of blockchain technology. Subsequently, an&#160;expertise-based group decision-making approach is used to quantify&#160;the prominence of various barriers according to various types of stakeholders. The results indicate that the five most intense barriers are storage constraints, insufficient economic incentives, high integration costs, a lack of functional appeal, and ambiguity regarding data disclosure and public data management regulations. This research makes novel theoretical and practical contributions, as it takes an empirical and all-encompassing approach to identifying obstacles to the adoption of blockchain technology and provides valuable insights for policymakers and practitioners to reference in overcoming these obstacles.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xuhui Cong</style></author><author><style face="normal" font="default" size="100%">Peikun Su</style></author><author><style face="normal" font="default" size="100%">Liang Wang</style></author><author><style face="normal" font="default" size="100%">Sai Wang</style></author><author><style face="normal" font="default" size="100%">Zhipeng Qi</style></author><author><style face="normal" font="default" size="100%">Jonas Šaparauskas</style></author><author><style face="normal" font="default" size="100%">Jarosław Górecki</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Measuring the Construction Efficiency of Zero-Waste City Clusters Based on an Undesirable Super-Efficiency Model and Kernel Density Estimation Method</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">10/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Systems</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.3390/systems11090473</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">11(9)</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The global total amount of generated solid waste is currently on a rapid growth trend. China, as the largest developing country, promulgated its Pilot Work Plan for the Construction of Zero-Waste Cities led by the new development concept in 2018 after recognizing the inadequacy and urgency of solid waste management, and the lack of valuable experience and benchmark cities for the construction of zero-waste cities. This study uses the undesirable super-efficiency model and kernel density estimation method to measure the efficiency of zero-waste city construction in 16 prefecture-level cities in Shandong Province and analyze their spatial and temporal differences. Three major problems were found, namely, low regional coordination, the rigid policies of some local governments, and the unbalanced development of scale efficiency and pure technical efficiency. Results show that the zero-waste city construction efficiency as a whole shows a declining and then fluctuating growth trend, and that low-scale efficiency is the main reason behind the decrease in construction efficiency. Suggestions are then provided considering three aspects: improving regional synergy; improving government quality and capacity, and strengthening government supervision and revitalizing the market; and introducing social capital for environmental pollution treatment. These suggestions ultimately help improve the level of zero-waste city construction.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Zhengze Zhu</style></author><author><style face="normal" font="default" size="100%">Xianjia Wang</style></author><author><style face="normal" font="default" size="100%">Francisco Chiclana</style></author><author><style face="normal" font="default" size="100%">Enrique Herrera-Viedma</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiobjective Optimization-Based Collective Opinion Generation With Fairness Concern</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">09/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on Systems, Man, and Cybernetics: Systems</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1109/TSMC.2023.3273715</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">59(9)</style></volume><section><style face="normal" font="default" size="100%">5729-5741</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The generation of collective opinion based on probability distribution function (PDF) aggregation is gradually becoming a critical approach for tackling immense and delicate assessment and evaluation tasks in decision analysis. However, the existing collective opinion generation approaches fail to model the behavioral characteristics associated with individuals, and thus, cannot reflect the fairness concerns among them when they consciously or unconsciously incorporate their judgments on the fairness level of distribution into the formulations of individual opinions. In this study, we propose a multi-objective optimization-driven collective opinion generation approach that generalizes the bi-objective optimization-based PDF aggregation paradigm. In doing so, we adapt the notion of fairness concern utility function to characterize the influence of fairness inclusion and take its maximization as an additional objective, together with the criteria of consensus and confidence levels, to achieve in generating collective opinion. The formulation of fairness concern is then transformed into the congregation of individual fairness concern utilities in the use of aggregation functions. We regard the generalized extended Bonferroni mean as an elaborated framework for aggregating individual fairness concern utilities. In such way, we establish the concept of Bonferroni mean-type collective fairness concern utility to empower multi-objective optimization-driven collective opinion generation approach with the capacity of modeling different structures associated with the expert group with fairness concern. The application of the proposed fairness-aware framework in the maturity assessment of building information modelling demonstrates the effectiveness and efficiency of multi-objective optimization-driven approach for generating collective opinion when accomplishing complicated assessment and evaluation tasks with data scarcity.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xianguo Wu</style></author><author><style face="normal" font="default" size="100%">Yuan Cao</style></author><author><style face="normal" font="default" size="100%">Weicheng Liu</style></author><author><style face="normal" font="default" size="100%">Yabo He</style></author><author><style face="normal" font="default" size="100%">Gang Xu</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Yang Liu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BIM-driven building greenness evaluation system: An integrated perspective drawn from model data and collective experts' judgments</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">06/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Cleaner Production</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.jclepro.2023.136883</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">406</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Traditional buildings will lead to a series of problems such as high energy consumption, high pollution, and serious waste of resources and environmental damage. It is of great significance to construct a green building evaluation system based on the physical building framework to achieve energy saving and consumption reduction and to fit the sustainable development. In this study, a building greenness evaluation system combining BIM data model and prior knowledge of experts is constructed and the applicability of the method has been verified. IFC information is expressed and transmitted in terms of components, materials, equipment, environmental quality impact, etc., and BIM based building performance design data information conversion and greenness evaluation process is constructed; Based on the comparison and summary of the existing green building evaluation systems at home and abroad, the evaluation model of building greenness is determined; Based on the ideas and steps of establishing the index system proposed in the research, the index system of building greenness evaluation is established from the aspects of environmental quality (Q) and building load (L) on the basis of questionnaire, prior knowledge of experts and other methods; Combined with the mathematical model of greenness evaluation, the paper analyzes the indexes of different levels, determines the structural calculation methods of different indexes, and carries on the quantitative classification of the overall greenness evaluation. Finally, taking a citizen's house as an engineering case, the paper makes an empirical analysis on the greenness evaluation of green buildings. The results show that the green degree of the building is excellent(class A), which is consistent with the project positioning, and provides the basis for the efficient and accurate evaluation of green building. † Xianguo Wu and Yuan Cao and Weicheng Liu contributed equally to the work.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sheng-Hua Xiong</style></author><author><style face="normal" font="default" size="100%">Chen-Ye Zhu</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Muhammet Deveci</style></author><author><style face="normal" font="default" size="100%">Francisco Chiclana</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On extended power geometric operator for proportional hesitant fuzzy linguistic large-scale group decision-making</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">03/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Information Sciences</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.ins.2023.03.001</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">632</style></volume><section><style face="normal" font="default" size="100%">637-663</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The unduly low or high data are commonly regarded as outliers in the classical power geometric operator. However, in many cases, these types of data may be significantly important to the aggregated results. This study aims at expanding the practical application scope of the power geometric operator and then utilizing it to develop a proportional hesitant fuzzy linguistic large-scale group decision-making (LSGDM) model. The extended power geometric (EPG) operator is first introduced, in which these outliers can be distinguished as sufficiently important or "false/biased" data in accordance with the decision-making context. Several useful properties and application characteristics of the EPG operator are highlighted. Subsequently, the proportional hesitant fuzzy linguistic normalized Manhattan distance is proposed, which is a basic concept for the construction of the proportional hesitant fuzzy linguistic extended power geometry (PHFLEPG) operator. Combined with the clustering model for decision-makers, a PHFLEPG-operator-based consensus-reaching approach is provided to simplify and rationalize the decision-making process. Furthermore, the comprehensive LSGDM result is derived by utilizing the PHFLEPG operator. Eventually, a case study on regulatory capacity evaluation for the Civil Aviation Safety Regulatory Authority of China is performed to validate the feasibility and effectiveness of the established LSGDM method.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hongyu Chen</style></author><author><style face="normal" font="default" size="100%">Xinyi Li</style></author><author><style face="normal" font="default" size="100%">Zongbao Feng</style></author><author><style face="normal" font="default" size="100%">Lei Wang</style></author><author><style face="normal" font="default" size="100%">Yawei Qin</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Yang Liu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Shield attitude prediction based on Bayesian-LGBM machine learning</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">06/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Information Sciences</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.ins.2023.03.004</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">632</style></volume><section><style face="normal" font="default" size="100%">105-129</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Effective shield attitude control is essential for the quality and safety of shield construction. The traditional shield attitude control method is manual control based on a driver's experience, which has the defects of hysteresis and poor reliability. This research proposes an intelligent method to predict the shield attitude based on a Bayesian-light gradient boosting machine (LGBM) model. The constructed model includes 29 parameters that impact the shield attitude and 6 parameters that represent the shield attitude. The developed the Bayesian-LGBM model can predict the shield attitude and support shield attitude control by adjusting construction parameters and conducting iterative prediction. Guiyang rail transit line 3 is selected as a case study to verify the effectiveness of the proposed method. The results indicate: (1) The developed the Bayesian-LGBM model is able to effectively predict the shield attitude; (2) The importance ranking can clarify the key construction parameters that should be controlled; (3) The proposed method enables support the effective shield attitude control by continuously adjusting the shield construction parameters. the proposed attitude guidance control method based on the Bayesian-LGBM can be used to provide a reference for actual shield attitude applications and other similar problems.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ping Xie</style></author><author><style face="normal" font="default" size="100%">Ke Chen</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Jun Wang</style></author><author><style face="normal" font="default" size="100%">Hanbin Luo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Parametric geological model update and probabilistic analysis of shield tunnel excavation: A borehole-based conditional random fields approach</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">05/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Computers and Geotechnics</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.compgeo.2023.105349</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">157</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Shield tunnel construction has faced considerable challenges due to the uncertain geological conditions in real scenarios. The borehole data obtained from geological investigations are often too limited to effectively evaluate uncertainties at nonsampled points. Moreover, the existing&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/probabilistic-safety-assessment" title="Learn more about probabilistic safety assessment from ScienceDirect's AI-generated Topic Pages"&gt;probabilistic safety assessment&lt;/a&gt;&#160;(PSA) frameworks that consider the uncertainties of soil properties have encountered limitations in engineering practice due to the complexity of&#160;&lt;a href="https://www.sciencedirect.com/topics/computer-science/conditional-random-field" title="Learn more about conditional random field from ScienceDirect's AI-generated Topic Pages"&gt;conditional random field&lt;/a&gt;&#160;(CRF) theory and the operability of&#160;&lt;a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/numerical-modeling" title="Learn more about numerical modeling from ScienceDirect's AI-generated Topic Pages"&gt;numerical modeling&lt;/a&gt;. Based on the digitization of the underground infrastructure, this study implements the object-oriented&#160;&lt;a href="https://www.sciencedirect.com/topics/engineering/parametric-modeling" title="Learn more about parametric modeling from ScienceDirect's AI-generated Topic Pages"&gt;parametric modeling&lt;/a&gt;&#160;(PM) to address these limitations. A PM-CRF engine is first developed to automate the process of parametric&#160;&lt;a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/geological-modeling" title="Learn more about geological modeling from ScienceDirect's AI-generated Topic Pages"&gt;geological modeling&lt;/a&gt;&#160;using CRFs. Then, a PM-CRF-PSA interoperability framework is proposed to automatically generate a PSA model for comprehensive safety assessment considering the uncertainties of soil properties. Finally, a case study is conducted with the proposed framework to assess the whole process of parametric modeling from CRF characterization to PSA. The results of this study highlight the clear advantages of this framework compared to traditional deterministic safety assessment (DSA) methods in terms of characterization of the uncertainty of soil properties and the efficiency of PSA modeling. Thus, the proposed framework enables the efficient and comprehensive exploration of shield&#160;&lt;a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/tunnel-design" title="Learn more about tunnel design from ScienceDirect's AI-generated Topic Pages"&gt;tunnel design&lt;/a&gt;&#160;schemes by considering the uncertainties of soil properties.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xuhui Cong</style></author><author><style face="normal" font="default" size="100%">Sai Wang</style></author><author><style face="normal" font="default" size="100%">Liang Wang</style></author><author><style face="normal" font="default" size="100%">Zhipeng Qi</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">New smart city clusters’ construction level evaluation under economic circles: the case of Shandong, China</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">04/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Technological and Economic Development of Economy</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.3846/tede.2023.18792</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">29(3)</style></volume><section><style face="normal" font="default" size="100%">949-980</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;China’s Shandong Province plans to create a new smart city cluster that is developmentfocused, demand-led, people-oriented, and data-driven. This entails the scientific assessment of construction levels, analysis of potential hurdles, and formulation of upgraded strategies. However, existing research has mainly focused on measuring single or multiple traditional smart cities, therein overlooking the construction level of new smart city clusters. Thus, this study takes the new smart city clusters in Shandong Province and uses both entropy method and the Moran index to analyze the construction level and spatial differences in the four dimensions of social livelihood, economic production, innovation-driven development, and safeguard measures. Results show that the construction level of the provincial capital economic circle is uneven and has polarization issues. Meanwhile, the construction level of Jiaodong economic circle is relatively good, although the economic driving capacity needs further improvement. The low urbanization rate of the Lunan economic circle occupies a gathering zone with low construction levels, making the construction of digital villages necessary. Targeted suggestions in improving the radiationdriven capacity of core cities, improving digital infrastructure, and developing smart industries are then forwarded to promote the establishment of new smart city clusters and achieve top-notch economic growth.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Omar Daboun</style></author><author><style face="normal" font="default" size="100%">Nur Abidin</style></author><author><style face="normal" font="default" size="100%">Ali Khoso</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Aminah Yusof</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Effect of relationship management on construction project success delivery</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">05/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Civil Engineering and Management</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.3846/jcem.2023.18827</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">29(5)</style></volume><section><style face="normal" font="default" size="100%">372-397</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The dynamic, challenging, and complex nature of the construction projects environment often cause adversarial culture, disputed claims, and deteriorating relationships between project participants. This paper aims to study the correlation between Relationship Management (RM) and construction project success and to develop a framework that includes practical actions, tools, and strategies for managing relationships in construction projects. Literature review and interviews were used to explore and validate the RM’s relevant associated traits. Subsequently, a piloted questionnaire was used to collect the data from 264 construction experts and assess the effect of RM on the overall project success. The data were analyzed using Partial-Least Squares Structural Equation Modeling (PLS-SEM), where the structural and measurement models of the higher and lower order constructed were assessed. The study findings categorized the RM-associated traits into three main pillars: Contractual Measures, Team Interactions, and Top Management Actions. The findings also confirmed that RM has a significant positive effect on the overall success of construction projects. In addition, this paper proposed an integrated framework for managing relationships in construction projects, allowing construction firms to monitor the relationships in their projects and identify key areas for strengthening the relationships throughout their projects to foster their projects' success rates.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tong-Yuan Wang</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Peng He</style></author><author><style face="normal" font="default" size="100%">Kannan Govindan</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Alliance strategy in an online retailing supply chain: Motivation, choice, and equilibrium</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">02/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Omega (United Kingdom)</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.omega.2022.102791</style></electronic-resource-num><section><style face="normal" font="default" size="100%">115</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper, we investigate the alliance strategy in an Online Retailing Supply Chain (ORSC). Three alliance models in addition to one no alliance model are built and examined. The no alliance model as a benchmark is developed to characterize the alliance motivation for each supply chain member. Afterwards, we identify the optimal alliance strategy and the final alliance equilibrium. The results show that the manufacturer always has motivations to form an alliance with each of other two members, while the retailer and the platform may form an alliance only when the agency rate is relatively low. Moreover, under certain conditions, all supply chain members could achieve a win-win-win result in the manufacturer-retailer and manufacturer-platform alliance models, but fall into a lose-lose-lose situation in the retailer-platform alliance model. Additionally, it is interesting that a higher agency rate makes the retailer more profitable when the platform and manufacturer enter into an alliance. Finally, we find that each of the three alliance models may be the final equilibrium, which is largely dependent on channel competition and the agency rate.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jian-Peng Chang</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Zhu-Jun Wang</style></author><author><style face="normal" font="default" size="100%">LeSheng Jin</style></author><author><style face="normal" font="default" size="100%">Witold Pedrycz</style></author><author><style face="normal" font="default" size="100%">Luis Martinez</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessing Spatial Synergy Between Integrated Urban Rail Transit System and Urban Form: A BULI-Based MCLSGA Model With the Wisdom of Crowds</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">02/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on Fuzzy Systems</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1109/TFUZZ.2022.3185680</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">31(2)</style></volume><section><style face="normal" font="default" size="100%">434-448</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Spatially synergizing the urban rail transit (URT) network integrated with its feeder transit system and the urban form plays an important role in improving the effectiveness of URT in mitigating traffic congestion, reducing air pollution, optimizing urban spatial structure, etc. This article mainly focuses on assessing the spatial synergy between the two parts by specifying the assessment criteria that can effectively characterize the spatial synergic mechanism between the two parts and developing a novel multicriteria large-scale group assessment (MCLSGA) model, in which basic uncertain linguistic information (BULI), as an extended form of fuzzy linguistic approach, is used to model and process the subjective assessment information (Assess-Inf) elicited by experts. In order to alleviate the computing complexity, an agglomerative hierarchical clustering algorithm is introduced to cluster the Assess-Inf given by a huge number of experts as per the organizers’ expected discrimination level on reliability-related Assess-Inf. A method for weighting the clusters is then proposed to control the roles played by the items of the Assess-Inf, representing each cluster and having different reliability levels in their fusing process to tap into wisdom of crowds (WOC) while accommodating the organizers’ trust level in the reliability-related Assess-Inf given by experts. Afterward, the best–worst method is extended to the BULI-based large-scale group assessment context with the aim of accurately weighting the criteria by drawing on WOC. Finally, a case study on assessing the spatial synergy between Chongqing’s integrated URT system and urban form is conducted to validate the validity of the proposed MCLSGA model.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zongbao Feng</style></author><author><style face="normal" font="default" size="100%">Weiya Chen</style></author><author><style face="normal" font="default" size="100%">Yang Liu</style></author><author><style face="normal" font="default" size="100%">Hongyu Chen</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Long-term equilibrium relationship analysis and energy-saving measures of metro energy consumption and its influencing factors based on cointegration theory and an ARDL model</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">11/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Energy</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.energy.2022.125965</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">263</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The energy consumption of metros has widely been concerned with respect to their economy and environmental protection. To analyze the complex dynamic relationship between metro energy consumption and its influencing factors and provide a reference for metro energy conservation control, this paper uses the monthly energy consumption, passenger flow and operating distance statistical data for Wuhan Metro Line 2 from 2018 to 2019. First, metro energy consumption and its influencing factors are qualitatively analyzed and identified. Then, based on cointegration theory and an autoregressive distributed lag (ARDL) model, a correlation hypothesis between metro energy consumption and its influencing factors is constructed, and a method for analyzing the influencing factors of metro energy consumption is proposed. The total energy consumption of a metro (TEC), train traction energy consumption (TTEC), environmental control energy consumption (ECEC), station lighting energy consumption (SLEC), station equipment energy consumption (SEEC) and the operating distance (OD) and passenger flow (PF) variables are analyzed. Using cointegration and an impulse response function, the dynamic relationships between the various energy consumption factors and operating distance and passenger flow are evaluated. The results show that there are substantial differences in the effects of OD and PF and their degree of influence on metro energy consumption. (1) OD affects mainly TTEC and TEC. The degree of influence of OD on TTEC reaches 97.8%, and the degree of influence of OD on TEC reaches 65.9%. (2) PF affects mainly ECEC and SEEC, and the degrees of influence of PF on ECEC and SEEC are 32.2% and 41.3%, respectively. (3) Considering that OD is the key factor affecting TTEC and TEC, train marshaling schemes, train running intervals and train stopping scheme optimization countermeasures are proposed, which can provide decision support for metro energy consumption management and control.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yang Liu</style></author><author><style face="normal" font="default" size="100%">Xianjia Wang</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Yifei Zhang</style></author><author><style face="normal" font="default" size="100%">Shenghao Zhao</style></author><author><style face="normal" font="default" size="100%">Muhammet Deveci</style></author><author><style face="normal" font="default" size="100%">LeSheng Jin</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluating Digital Health Services Quality via Social Media</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">07/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on Engineering Management</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1109/TEM.2023.3298906</style></electronic-resource-num><section><style face="normal" font="default" size="100%">1-13</style></section><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Given the widespread demand for digital health services, a systematic study on the quality of digital health services is essential. Based on the current situation of tertiary hospitals in central China providing digital health services via social media, we used the Cronbach and Bayesian Best and Worst methods to evaluate the quality of hospital digital health services and conduct an empirical study of several hospitals. Based on the results of the empirical study, we propose a path for constructing a digital health service platform, suggesting that hospitals focus on building business function services of social media and accelerate the development of Internet hospitals. Hospitals should also improve the operation and maintenance of social media, optimize the intelligence of online guidance, and simplify the design logic of function menus. In terms of content information services, hospitals need to design targeted content according to the characteristics of different social media, improve content quality, and ensure the appropriate proportion of various types of information. With such measures, hospitals can guide users to use social media through business function services and retain users through content information services to increase the influence of hospitals and the quality of social health welfare.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jian-Peng Chang</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Xianjia Wang</style></author><author><style face="normal" font="default" size="100%">Luis Martinez</style></author><author><style face="normal" font="default" size="100%">Witold Pedrycz</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Requirement-driven sustainable supplier selection: Creating an integrated perspective with stakeholders' interests and the wisdom of expert crowds</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style face="normal" font="default" size="100%">01/2023</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Computers and Industrial Engineering</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">DOI: 10.1016/j.cie.2022.108903</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">175</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Driven by the pressure from various stakeholders to embrace sustainability and from the market to enhance competitiveness, more and more companies have been committed to conducting sustainable supplier selection (SSS). SSS is a requirement-driven multi-criteria decision-making (MCDM) problem and the existing pieces of literature have attempted to integrate quality function deployment (QFD) with various MCDM methods to model the problem. However, these models have not conducted SSS based on stakeholders’ satisfaction from alternatives and used the weights of criteria obtained from stakeholders’ preferences for requirements, which is used to model the compensation among satisfaction levels of different requirements, to guide the compensation among alternatives’ performances on different criteria. In order to address these deficiencies, this paper develops a novel generalized (QFD)-based MCDM structure for SSS, based on which we further design a QFD-based multi-stakeholders and multi-experts MCDM model considering stakeholders’ consensus of interest and wisdom of expert crowds. Firstly, multiple stakeholder groups with multiple participants in each one are asked to output their expectations and preferences for their own requirements; within each group, the algorithm for consensus reaching process (CRP) is designed to formulate the acceptable collective expectations, and the best-worst method (BWM) method integrated with an algorithm for consistency improving process (CIP) and an algorithm for CRP is developed to weight requirements. Secondly, multiple experts use basic uncertain linguistic information (BULI) to characterize performances of alternatives on criteria and the relationship between requirements and criteria, and a method of weighting individual judgments with the capability of drawing on the wisdom of crowds (WOC) while accommodating organizers’ trust level in reliability given by experts is used to facilitate formulating a collective judgment. Thirdly, for each alternative and each requirement of each stakeholder group, we can quantify the comprehensive performance of the alternative on the requirement with the help of QFD, based on which and the group’s expectation we can use the value function of prospect theory to quantify the group’s satisfaction of the requirement from the alternative; aggregating the weighted satisfaction levels of requirements gives rise to the comprehensive satisfaction level of each group from each alternative, and then the Maximin decision rule is introduced to rank alternatives because of its ability to accommodate the non-compensation among different stakeholder groups. Finally, a case study is conducted to investigate the validity and effectiveness of the proposed model.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sheng-Hua Xiong</style></author><author><style face="normal" font="default" size="100%">Zhi-Peng Wang</style></author><author><style face="normal" font="default" size="100%">Gang Li</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of airport runway settlement using an integrated SBAS-InSAR and BP-EnKF approach</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style face="normal" font="default" size="100%">04.2024</style></date></pub-dates></dates><secondary-title><style face="normal" font="default" size="100%">Elsevier</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.ins.2024.120376</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">665</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The prediction of surface settlement occupies a crucial role in achieving effective catastrophe prevention and mitigation, as well as facilitating the maintenance of airport runways. Given the challenges associated with the manual collection of settlement data and the suboptimal timeliness of the Back Propagation (BP) technique in neural networks, this study proposes an integrated prediction method that combines the Ensemble Kalman Filter (EnKF) with BP. This study focuses on the processing of Synthetic Aperture Radar (SAR) pictures obtained from the ascending orbit of the Sentinel-1A satellite. The Small Baseline Subset Interferometric synthetic aperture radar (SBAS-InSAR) technology is employed to derive the settlement time series on the runway of Kangding Airport. Moreover, three sites with high coherence within the primary settlement region are employed to assess the dependability of the model after the expansion of the data by cubic spline interpolation. The findings of the study indicate that both the BP-EnKF and BP models exhibit favorable outcomes in predicting airport runway settlement. However, following the alteration of data caused by external environmental influences, the BP-EnKF model has superior adaptability to variations in data. It has been shown that the BP-EnKF model exhibits a prediction accuracy that surpasses the BP model by 9.25%.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Saika Wong</style></author><author><style face="normal" font="default" size="100%">Zhentao Chen</style></author><author><style face="normal" font="default" size="100%">Mi Pan</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploring psychophysiological methods for human–robot collaboration in construction</style></title></titles><keywords><keyword><style face="normal" font="default" size="100%">Human–robot collaboration; Construction robots; Psychophysiological signals; Human–robot interaction</style></keyword></keywords><dates><year><style face="normal" font="default" size="100%">2026</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Advanced Engineering Informatics</style></secondary-title><keyword><style face="normal" font="default" size="100%"/></keyword><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.aei.2026.104692</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Psychophysiological methods present a promising approach to fostering enhanced mutual communication and collaboration between human workers and robots. Despite their potential, there is still limited understanding of how to effectively integrate psychophysiological methods to improve human–robot collaboration (HRC) in construction. This paper addresses this gap by critically reviewing the use of psychophysiological methods for HRC within construction environments, based on a concept-methodology-value philosophical framework. The review explores different interaction modalities of implementing psychophysiological measures to communicate or control robots in construction. The analysis reveals that measuring brain activity using electroencephalography is the most widely used psychophysiological method, while the majority of the works are still at the proof-of-concept stage in laboratory and virtual construction environments and lack empirical evidence. Four potential research directions are proposed: the fusion of multi-modal psychophysiological signals, enriching field experimental settings for better generalizability, leveraging advanced biocompatible or contactless technologies for effective signal detection in construction scenarios, and examining the practicality of psychophysiological methods to construction HRC. The findings should benefit subsequent exploration and practical applications of psychophysiological methods to enable the better implementation of robots and support HRC in construction.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sheng-Hua Xiong</style></author><author><style face="normal" font="default" size="100%">Xi-Hang Wei</style></author><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Hao Zhang</style></author><author><style face="normal" font="default" size="100%">Witold Pedrycz</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identifying causes of aviation safety events using wW2V-tCNN with data augmentation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">International Journal of General Systems</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1080/03081079.2025.2456960</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Identifying the causes of these safety events is crucial for safety agencies to create recommendations and for airlines to enhance procedures and mitigate hazards. This paper proposes a model to identify the causes of civil aviation safety events using a weighted Word2Vec-based Text-CNN (wW2V-tCNN) algorithm and data augmentation techniques. A corpus is built by matching narrative texts from investigation reports with cause labels from the Aviation Safety Network database. This corpus is transformed into Text-CNN inputs using a weighted sentence vector method based on word embeddings, considering word frequency and part-of-speech weighting. Additionally, a novel document balancing method is introduced for data augmentation. The proposed identification model achieves Macro-F1 and Macro-accuracy scores of 0.9803 and 0.9699, outperforming traditional methods and showing significant improvement over models like Doc2vec and SBERT. This model provides an accurate tool for safety agencies and airlines to analyze and effectively mitigate civil aviation safety events&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhen-Song Chen</style></author><author><style face="normal" font="default" size="100%">Yue Tan</style></author><author><style face="normal" font="default" size="100%">Zheng Ma</style></author><author><style face="normal" font="default" size="100%">Zhengze Zhu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Unlocking the potential of quantum computing in prefabricated construction supply chains: Current trends, challenges, and future directions</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Information Fusion</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.inffus.2025.103043</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The intricate nature of prefabricated construction supply chain management (PCSCM) presents ongoing challenges in production scheduling, inventory control, and logistics coordination. Recent advances in quantum computing (QC) offer compelling approaches to address these multifaceted issues by enabling significantly faster and more precise optimization. This paper systematically reviews and synthesizes existing QC research in the supply chain context, particularly focusing on quantum algorithms that target the PCSCM lifecycle. Our analysis identifies three key domains: production, inventory, and transportation, in which QC can outperform classical methods, as evidenced by enhanced scheduling flexibility and cost minimization. However, our findings also highlight crucial bottlenecks, including quantum hardware limitations, organizational readiness gaps, and a lack of specialized interdisciplinary talent. We propose a framework of strategies to guide QC adoption, such as specialized algorithm development, collaborative research partnerships, and standardized data protocols. These insights offer promising future directions for leveraging QC to streamline operations and boost sustainability in the prefabricated construction sector.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lei Zhang</style></author><author><style face="normal" font="default" size="100%">Jingfeng Yuan</style></author><author><style face="normal" font="default" size="100%">Xianfei Yin</style></author><author><style face="normal" font="default" size="100%">Tiantian Gu</style></author><author><style face="normal" font="default" size="100%">Yinghao Lu</style></author><author><style face="normal" font="default" size="100%">Ping Liu</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The emotional equation: how psychosocial support boosts safety practices in the context of construction 5.0</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Frontiers in Psychology</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.3389/fpsyg.2025.1632848</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Background: Construction 5.0, which emphasizes human-centric technologies and improved collaboration between humans and machines in intelligent construction ecosystems, introduces distinct safety management challenges that necessitate effective emotional resource allocation strategies. This study utilizes job demands-resources theory to investigate how emotional resources are allocated for safety management by examining the relationships among safety practice, psychosocial support, safety participation, and leadership safety behavior.&lt;/p&gt; &lt;p&gt;Methods: A face-to-face questionnaire survey was conducted with front-line construction workers involved in Construction 5.0 projects, yielding 118 valid responses. The data were analyzed using linear regression models and the bootstrap method.&lt;/p&gt; &lt;p&gt;Results: The findings reveal that: (1) psychosocial support positively influences both safety participation and safety practices; (2) safety participation enhances safety practices; (3) safety participation fully mediates the effect of psychosocial support on safety practices; and (4) leadership safety behavior positively moderates the relationship between safety participation and safety practices.&lt;/p&gt; &lt;p&gt;Conclusion: This study extends the job demands-resources framework by illustrating the flow of emotional resources in the context of Construction 5.0, thereby highlighting the principles of multi-level emotional resources in the relationship between emotion and safety. Practically, this framework allows for the evolution of human-centric safety measures in tandem with advanced technology-enabled work environments, while also maintaining psychosocial balance in intelligent construction ecosystems&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hui Liu</style></author><author><style face="normal" font="default" size="100%">Hanyu Zheng</style></author><author><style face="normal" font="default" size="100%">Qianqian Ju</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Mengmeng Wang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Temporal-Spatial Evolution of BIM-Based Collaborative Innovation Network: Evidence from Patents in China\textquoterights Construction Industry</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Management in Engineering - ASCE</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1061/jmenea.meeng-6805</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Nowadays, the efficiency and effectiveness of construction innovation is deemed urgent. Given the innovative potential of building information modeling (BIM), BIM-based collaborative innovation (BIM-CI) has been perceived as a promising approach to meet this requirement. However, the underlying mechanism that drives BIM-CI remains largely unexplored, which seriously hinders progress in designing and planning effective interventions to promote BIM-CI so as to accelerate the release of innovation capacity in the construction system. BIM-CI exhibits distinct network characteristics. Therefore, this study employed social network analysis to examine the temporal and spatial evolution process of the BIM-based collaborative innovation network (BIM-CIN) in China based on 1,677 BIM-CI-related patent data from 2011 to 2023. The results indicate that BIM-CIN has expanded across three phases, with its network structure becoming more decentralized and diversified. This shift provides innovators with enhanced collaboration opportunities, fostering a more dynamic and inclusive innovation process. Key innovators, such as the State Grid Corporation of China and China Construction First (Group) Company Limited, play a pivotal role in facilitating communication and strengthening collaboration within the BIM-CIN. Additionally, the spatial evolution analysis highlights that the increasing number of provinces participating signifies a positive trend toward more extensive collaboration and innovation within the BIM-CIN. The findings provide valuable references for relevant practitioners to better organize their managerial activities to promote the development of BIM-CI, thereby improving the efficiency and effectiveness of construction innovation.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Qiong Liu</style></author><author><style face="normal" font="default" size="100%">Limao Zhang</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Network extension planning towards resilient urban critical infrastructures using deep reinforcement learning</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">APPLIED SOFT COMPUTING</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.asoc.2025.113163</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;As cities continue to grow, expanding metro networks becomes essential for optimizing urban transportation efficiency. Therefore, scientific strategic planning of metro networks is indispensable. This study proposes a deep reinforcement learning (DRL) approach to discover the optimal planning strategy for metro network extension. The model integrates multi-source data into the reward function while customizing the state and action spaces to reflect the unique characteristics of metro networks. A policy network is developed using an Encoder-Decoder framework, with the parameters being updated by an Actor-Critic framework based on policy gradient. A comprehensive performance index is proposed to evaluate the vulnerability and service capacity of planned networks. The proposed method is validated through a case study on the Hangzhou metro system. The results demonstrate that the proposed DRL can result in optimal planned networks that outperform the actually implemented network with a maximum Performance Improvement Percentage of 19.87 \%. The DRL-based optimization framework proposed for metro network extension planning is anticipated to enhance adaptability towards urban development and increase resilience.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yashuai Li</style></author><author><style face="normal" font="default" size="100%">Wubin Wang</style></author><author><style face="normal" font="default" size="100%">Jichang Zhao</style></author><author><style face="normal" font="default" size="100%">Yang Yang</style></author><author><style face="normal" font="default" size="100%">Zhaohui Zhang</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Jingfeng Yuan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimating demolition waste from residential interior photos: A Large Language Model solution</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Automation in Construction</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.autcon.2025.106478</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Demolition waste management is a critical challenge during the final stages of construction projects, particularly concerning fine-grained waste at the room level. This paper investigates the predictive potential of visual elements for demolition waste estimation, with an emphasis on interior room design. A framework integrating deep learning models with Large Language Model (LLM) is proposed to automatically classify interior design types and predict demolition waste. By utilizing both residential interior photos and floor plans, the framework can identify design types, segment walls, match rooms, and estimate demolition volumes at the room level. The results show high accuracy in design classification and waste prediction, surpassing traditional methods based on waste generation rates. The framework also provides valuable insights into specific waste materials, enhancing waste management at a detailed level. This research advances micro-level demolition waste prediction, promoting the broader application of LLMs in the construction industry.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hongyu Chen</style></author><author><style face="normal" font="default" size="100%">Qiping Shen</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author><author><style face="normal" font="default" size="100%">Yuan Cao</style></author><author><style face="normal" font="default" size="100%">Yang Liu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dynamic prediction and optimization of tunneling parameters with high reliability based on a hybrid intelligent algorithm</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Information Fusion</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.inffus.2024.102705</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper, a hybrid intelligent framework comprising Bayesian optimization (BO), gradient boosting with categorical features (CatBoost) and the nondominated sorting genetic algorithm-III (NSGA-III) was proposed to support multiobjective optimization of shield construction parameters without large sample datasets, improve the shield performance, and ensure reliable and interpretable results. First, with the use of the specific tunneling energy, advancing speed and cutter wear as objective functions, a BO-CatBoost prediction model for shield construction parameters and various objectives was constructed, and the key influencing factors were identified via the SHapley Additive exPlanations (SHAP) method. Then, a BO-CatBoost-NSGA-III model was developed to obtain Pareto solutions under different scenarios involving the adjustment of the key influencing factors. Finally, adopting the Wuhan Metro as the background, the accuracy, stability, and generalizability of the constructed algorithm were verified. The results indicated that (1) the developed BO-CatBoost algorithm is superior to 9 other algorithms. The R2 values of the proposed approach were 0.976 and 0.901\textendash0.976 on the test set. (2) The developed BO-CatBoost-NSGA-III algorithm could be used to obtain Pareto solutions under different scenarios via the adjustment of the key influencing factors with the SHAP method, and the optimal solutions could facilitate improvements in the advancing speed, specific tunneling energy and cutter wear of 3.45 \%, 6.09 \%, and 0.52 \%, respectively, with an overall average reliability of 90.5 \%. (3) By comparing various prediction algorithms, optimization schemes of different objectives and geological conditions, the accuracy, stability, and generalizability of the constructed algorithm were verified. The developed BO-CatBoost-NSGA-III framework could enable dynamic adjustment of shield construction parameters for decision-making purposes in the event of conflicting shield construction objectives and exhibits generality.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">ATaha Demirbağ</style></author><author><style face="normal" font="default" size="100%">Hande Aladağ</style></author><author><style face="normal" font="default" size="100%">Zeynep Işık</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Circular Economy-Based Decision-Making Model for Contractor Selection</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Buildings</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.3390/buildings15101665</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Increasing environmental pollution has reinforced the necessity of implementing circular economy (CE) as a sustainable approach to reducing resource consumption, waste generation, and carbon emissions. Despite the construction industry\textquoterights significant environmental impact in terms of global carbon emissions, water consumption, and biodiversity loss, only 12\% of its materials exhibit circular characteristics, necessitating improvements in terms of circularity in construction projects. This study develops a CE-based decision-making model for contractor selection, focusing on off-site construction (OSC), which offers greater circularity potential than conventional construction methods. The decision-making model, established through literature analysis and expert discussions, utilizes the fuzzy analytic hierarchy process (AHP) to evaluate CE criteria and employ the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine contractor suitability. The findings indicate that Material Circularity, Energy Circularity, and Product Circularity are the most influential criteria, with green procurement emerging as the highest-priority factor. The model was validated through a hypothetical case study involving four contractors experienced in sustainable construction. The results demonstrate the model\textquoterights capacity to produce sensitive outcomes in terms of decision-making.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xudong Fan</style></author><author><style face="normal" font="default" size="100%">Yishuo Jiang</style></author><author><style face="normal" font="default" size="100%">Ray Zhong</style></author><author><style face="normal" font="default" size="100%">Fabio Duarte</style></author><author><style face="normal" font="default" size="100%">Waishan Qiu</style></author><author><style face="normal" font="default" size="100%">Jürgen Hackl</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Advancements and potential pitfalls for smart cities and sentient infrastructures</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Digital Engineering</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.dte.2025.100036</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;As urban areas struggle with increasing challenges related to population growth, climate change, the built environment, and public well-being, the concept of smart cities has emerged as a transformative solution. A smart city refers to the seamless integration of advanced information and communication technologies (ICT) with existing urban infrastructure to enhance efficiency, sustainability, and quality of life, thereby reshaping the future of urban living [2]. Originating in the early 2000s with a focus on \textquotedbllefttop-down\textquotedblright technology deployment [9], the practice has evolved owing to the rapid growth of digital infrastructure-such as broadband networks, smart sensors, and open data platforms, which has enabled cities to become dynamic environments that foster real-time decision-making and community participation [6]. Contemporary smart city initiatives increasingly recognize the importance of \textquotedblleftbottom-up\textquotedblright innovation, where residents actively contribute to the design and improvement of urban services [17]. This evolution reflects a shift towards emphasizing connectivity, citizen engagement, and a more human-centric approach to urban challenges. The collaborative, living-lab approach positions citizens as agents of change, making cities more adaptive and responsive to evolving needs. Despite these advancements, the development of smart cities still involves several challenges. Beyond technological deployments, ethical issues such as privacy, data security, and equitable access to technology are critical hurdles that must be addressed [1]. Moreover, the growing complexity of managing interconnected urban systems demands innovative governance frameworks that ensure interoperability while balancing technological progress with inclusiveness and sustainability. Ultimately, the success of smart cities will depend on the ability to create resilient, data-driven communities that empower their residents and prioritize both human well-being and environmental stewardship&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bocong Liu</style></author><author><style face="normal" font="default" size="100%">Xuhui Cong</style></author><author><style face="normal" font="default" size="100%">Liang Wang</style></author><author><style face="normal" font="default" size="100%">Shenghui Zhang</style></author><author><style face="normal" font="default" size="100%">Hao Liu</style></author><author><style face="normal" font="default" size="100%">Jonas Saparauskas</style></author><author><style face="normal" font="default" size="100%">Leonas Ustinovichius</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatial-temporal evolution and influencing factors of the coupling coordination degree between new infrastructure construction and high-quality development in urban agglomerations in China</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Engineering, Construction and Architectural Management</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1108/ecam-11-2024-1627</style></electronic-resource-num></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhenzhao Xia</style></author><author><style face="normal" font="default" size="100%">Botao Zhong</style></author><author><style face="normal" font="default" size="100%">Shuai Zhang</style></author><author><style face="normal" font="default" size="100%">Tonghui Zhao</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Graph-driven embedding reinforcement and traceable LLM agent for reliable element alignment in construction report generation</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2026</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Automation in Construction</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.autcon.2026.106816</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Engineering report generation from construction-site Internet of Things (IoT) data using large language models (LLMs) remains challenging due to hallucinations. Ensuring traceability and reliability in information retrieval and multi-step reasoning is essential within retrieval-augmented generation (RAG) for LLM. This paper formalizes the RAG-LLM pipeline and proposes a dual-stream enhancement combining knowledge graph (KG) construction with reinforcement learning (RL)-based retriever tuning. The graph-guided module extracts structured engineering elements, while RL improves semantic alignment and tokenization of critical terms. Leveraging this dual-stream RAG, a traceable reporting agent is developed, providing end-to-end traceability of retrieval and reasoning, along with inter-step similarity measures. When collaborating with existing on-site IoT systems, the agent can extend automated monitoring to decision-making support. This paper presents a reliable approach for construction report generation and advances human-AI collaboration in construction management.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhuohao Zhang</style></author><author><style face="normal" font="default" size="100%">Weiya Chen</style></author><author><style face="normal" font="default" size="100%">Jianhua Cai</style></author><author><style face="normal" font="default" size="100%">Hanbin Luo</style></author><author><style face="normal" font="default" size="100%">Mirosław Skibniewski</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Hierarchical system decomposition and semantic enrichment of BIM for lifecycle support of MEP systems</style></title></titles><keywords><keyword><style face="normal" font="default" size="100%">Semantic enrichment</style></keyword><keyword><style face="normal" font="default" size="100%">MEP systems</style></keyword><keyword><style face="normal" font="default" size="100%">Graph matching</style></keyword><keyword><style face="normal" font="default" size="100%">BIM</style></keyword></keywords><dates><year><style face="normal" font="default" size="100%">2026</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Advanced Engineering Informatics</style></secondary-title><keyword><style face="normal" font="default" size="100%"/></keyword><electronic-resource-num><style face="normal" font="default" size="100%">10.1016/j.aei.2026.104428</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The effective lifecycle management of modular Mechanical, Electrical, and Plumbing (MEP) systems is often compromised by a significant data gap between the digital design in Building Information Modeling (BIM) and the as-built conditions of prefabricated components. This paper specifically addresses the challenge of defining and structuring functionally independent component groups, or \textquoterightblocks,\textquoteright within complex BIM models that lack explicit system-level semantics and suffer from disorganized data. To solve this, a framework was proposed for hierarchical MEP system decomposition and semantic enrichment and implemented through a hybrid topological-geometric matching method that first identifies all structurally identical component assemblies via a topological search and then verifies these candidates by comparing their morphological signatures. Experimental validation demonstrates the method\textquoterights high accuracy and scalability, achieving an F1-score of 0.98, near-linear time complexity, and above 99\% precision in large-scale applications, as verified by domain experts. This research provides a robust, bottom-up approach to automatically populate a structured system hierarchy, bridging the critical data gap between the design model and physical, prefabricated modules. By creating semantically enriched and well-structured models, this work establishes a foundational data layer that enables future advancements in automated quantity take-off, modular maintenance, and end-of-life management, such as component reuse.&lt;/p&gt;</style></abstract></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Kolejowe przewozy regionalne–wyzwania i problemy</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2013</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Biblioteka Regionalisty</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Zarządzanie programami według Program Management Institute</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2014</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Barometr Regionalny. Analizy i prognozy</style></secondary-title><volume><style face="normal" font="default" size="100%">12</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">others</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Budżet zadaniowy jako skuteczne narzędzie zarządzania w samorządzie</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2015</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Henryk Brandenburg</style></author><author><style face="normal" font="default" size="100%">Katarzyna Ficek-Wojciuch</style></author><author><style face="normal" font="default" size="100%">Marek Magdoń</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interesariusze projektów publicznych–sukces projektu publicznego w ujęciu specjalistów od zarządzania projektami</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Henryk Brandenburg</style></author><author><style face="normal" font="default" size="100%">Katarzyna Ficek-Wojciuch</style></author><author><style face="normal" font="default" size="100%">Marek Magdoń</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Projekt badawczy pt" Sukces projektu publicznego i jego uwarunkowania"-wyniki studiów literaturowych i program realizacji projektu</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Prace Naukowe/Uniwersytet Ekonomiczny w Katowicach</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Henryk Brandenburg</style></author><author><style face="normal" font="default" size="100%">Marek Magdoń</style></author><author><style face="normal" font="default" size="100%">Katarzyna Ficek-Wojciuch</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multicriteria evaluation methods in location of touristic investments</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Галицький економічний вісник Тернопільського національного технічного університету</style></secondary-title><volume><style face="normal" font="default" size="100%">50</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yi Hou</style></author><author><style face="normal" font="default" size="100%">Stanley Young</style></author><author><style face="normal" font="default" size="100%">Kaveh Sadabadi</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Denise Markow</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimating highway volumes using vehicle probe data-proof of concept</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2018</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Nikola Marković</style></author><author><style face="normal" font="default" size="100%">Zachary Laan</style></author><author><style face="normal" font="default" size="100%">Kaveh Sadabadi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimating historical hourly traffic volumes via machine learning and vehicle probe data: A Maryland case study</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2018</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Transportation Research Part C: Emerging Technologies</style></secondary-title><volume><style face="normal" font="default" size="100%">97</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nikola Marković</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Zachary Laan</style></author><author><style face="normal" font="default" size="100%">Gennady Andrienko</style></author><author><style face="normal" font="default" size="100%">Natalia Andrienko</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Applications of trajectory data from the perspective of a road transportation agency: Literature review and maryland case study</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2018</style></year></dates><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on Intelligent Transportation Systems</style></secondary-title><volume><style face="normal" font="default" size="100%">20</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ying Zhou</style></author><author><style face="normal" font="default" size="100%">Chenshuang Li</style></author><author><style face="normal" font="default" size="100%">Lieyun Ding</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Peter Love</style></author><author><style face="normal" font="default" size="100%">Cheng Zhou</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Combining association rules mining with complex networks to monitor coupled risks</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2019</style></year></dates><secondary-title><style face="normal" font="default" size="100%"/></secondary-title><volume><style face="normal" font="default" size="100%">186</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Nikola Marković</style></author><author><style face="normal" font="default" size="100%">Zachary Laan</style></author><author><style face="normal" font="default" size="100%">Kaveh Sadabadi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of Vehicle Probe Data in Estimating Traffic Volumes: a Maryland Case Study</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2018</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sara Zahedian</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Amir Nohekhan</style></author><author><style face="normal" font="default" size="100%">Zachary Laan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimating hourly traffic volumes using artificial neural network with additional inputs from automatic traffic recorders</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Transportation Research Record</style></secondary-title><volume><style face="normal" font="default" size="100%">2674</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cheng Zhou</style></author><author><style face="normal" font="default" size="100%">Bin Tang</style></author><author><style face="normal" font="default" size="100%">Lieyun Ding</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Ying Zhou</style></author><author><style face="normal" font="default" size="100%">Zekun Zhang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Design and automated assembly of Planetary LEGO Brick for lunar in-situ construction</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2020</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Automation in Construction</style></secondary-title><volume><style face="normal" font="default" size="100%">118</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yayin Xu</style></author><author><style face="normal" font="default" size="100%">Ying Zhou</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Lieyun Ding</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Machine learning in construction: From shallow to deep learning</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Developments in the built environment</style></secondary-title><volume><style face="normal" font="default" size="100%">6</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">Zachary Laan</style></author><author><style face="normal" font="default" size="100%">Kaveh Sadabadi</style></author><author><style face="normal" font="default" size="100%">Krzysztof Kania</style></author><author><style face="normal" font="default" size="100%">Sara Zahedian</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transferability of a Machine Learning-Based Model of Hourly Traffic Volume Estimation—Florida and New Hampshire Case Study</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2021</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Journal of Advanced Transportation</style></secondary-title><volume><style face="normal" font="default" size="100%">2021</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mark Franz</style></author><author><style face="normal" font="default" size="100%">Stanley Young</style></author><author><style face="normal" font="default" size="100%">Stephen Remias</style></author><author><style face="normal" font="default" size="100%">Michael Pack</style></author><author><style face="normal" font="default" size="100%">Kaveh Sadabadi</style></author><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automated Traffic Signal 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font="default" size="100%">Transport Miejski i Regionalny</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Przemysław Sekuła</style></author><author><style face="normal" font="default" size="100%">others</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Wpływ autostrad na rozwój lokalny–wyniki badań</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2016</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" 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size="100%">https://www.sciencedirect.com/science/article/pii/S2666165926001158</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.dibe.2026.100957</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">26</style></volume></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Katarzyna Kołodziej</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">AI for the Rescue: Tackling Challenges in Polish Waste Management System</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2024</style></year></dates><secondary-title><style face="normal" font="default" size="100%">XII International Conference Environmental Protection and Energy (EPAE 2024)</style></secondary-title><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Piotr Zawadzki</style></author><author><style face="normal" font="default" size="100%">Grzegorz Dziwoki</style></author><author><style face="normal" font="default" size="100%">Marcin Kucharczyk</style></author><author><style face="normal" font="default" size="100%">Jan Machniewski</style></author><author><style face="normal" font="default" size="100%">Wojciech Sułek</style></author><author><style face="normal" font="default" size="100%">Jacek Izydorczyk</style></author><author><style face="normal" font="default" size="100%">Weronika Izydorczyk</style></author><author><style face="normal" font="default" size="100%">Piotr Kłosowski</style></author><author><style face="normal" font="default" size="100%">Adam Dustor</style></author><author><style face="normal" font="default" size="100%">Wojciech Filipowski</style></author><author><style face="normal" font="default" size="100%">Krzysztof Paszek</style></author><author><style face="normal" font="default" size="100%">Anna Zawadzka</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Quantum Enabled Data Authentication Without Classical Control Interaction</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2025</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Electronics</style></secondary-title><urls><style face="normal" font="default" size="100%">https://www.mdpi.com/2079-9292/14/20/4037</style></urls><electronic-resource-num><style face="normal" font="default" size="100%">10.3390/electronics14204037</style></electronic-resource-num><volume><style face="normal" font="default" size="100%">14</style></volume><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We present a quantum-assisted data authentication protocol that integrates classical information-theoretic security with quantum communication techniques. We assume only that the participants have access to open classical and quantum channels, and share a random static key material. Building on the Wegman–Carter paradigm, our scheme employs universal hashing for message authentication and leverages quantum channels to securely transmit random nonces, eliminating the need for key recycling. The protocol utilizes polar codes within Wyner’s wiretap channel model to ensure confidentiality and reliability, even in the presence of an all-powerful adversary. Security analysis demonstrates that the protocol inherits strong guarantees from both classical and quantum frameworks, provided the quantum channel maintains low loss and noise.&lt;/p&gt;&#13;
</style></abstract><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Piotr Zawadzki</style></author><author><style face="normal" font="default" size="100%">Anna Zawadzka</style></author><author><style face="normal" font="default" size="100%">Alicja Zawadzka</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Polar wiretap coding for practical quantum confidentiality</style></title></titles><keywords/><dates><year><style face="normal" font="default" size="100%">2026</style></year></dates><secondary-title><style face="normal" font="default" size="100%">Quantum Information Processing</style></secondary-title><electronic-resource-num><style face="normal" font="default" size="100%">https://doi.org/10.1007/s11128-026-05177-2</style></electronic-resource-num><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style="-webkit-text-stroke-width:0px;background-color:rgb(255, 255, 255);color:rgb(34, 34, 34);display:inline !important;float:none;font-family:Merriweather, serif;font-size:18px;font-style:normal;font-variant-caps:normal;font-variant-ligatures:normal;font-weight:400;letter-spacing:normal;orphans:2;text-align:start;text-decoration-color:initial;text-decoration-style:initial;text-decoration-thickness:initial;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;"&gt;We present a quantum-assisted protocol that provides a confidential data channel under the assumption of pre-shared keys. The pre-shared key can be reused across multiple sessions, reducing the cost of fresh key generation. The protocol does not require an authenticated classical feedback channel during execution. Confidentiality is ensured by the physical properties of quantum states and information-theoretic preprocessing using polar codes within the Wyner wiretap framework. The construction avoids entanglement and quantum memories, enabling deployment with current hardware. Due to the physics of quantum communication, the protocol is point-to-point with limited throughput, but is suitable for high-assurance, moderate-rate applications.&lt;/span&gt;&lt;/p&gt;</style></abstract></record></records></xml>
