00578nas a2200193 4500000000100000000000100001008004100002260003100043100001600074700002300090700002100113700002300134700001900157700002500176700001700201700001700218245013500235300001400370 2012 d bSpringer Berlin Heidelberg1 aM. Blachnik1 aPrzemysław Głomb1 aLeszek Rutkowski1 aMarcin Korytkowski1 aRafał Scherer1 aRyszard Tadeusiewicz1 aZadeh Lotfia1 aJacek Zurada00aDo we need complex models for gestures? A comparison of data representation and preprocessing methods for hand gesture recognition a477–48500355nas a2200109 4500000000100000000000100001008004100002100002000043700002300063245014500086022001400231 2012 d1 aMichał Cholewa1 aPrzemysław Głomb00aEstimation of the number of states for gesture recognition with Hidden Markov Models based on the number of critical points in time sequence a0167-865500313nas a2200121 4500000000100000000000100001008004100002100002000043700002300063245008400086300001400170490000700184 2011 d1 aMichał Cholewa1 aPrzemysław Głomb00aGesture data modeling and classification based on critical points approximation a365–3730 v9500607nas a2200241 4500000000100000000000100001008004100002260002600043100002000069700002300089700002100112700002400133700002100157700001900178700001800197700001400215700001500229700001800244700002400262700001800286245003900304020002200343 2013 d bOficyna Wydawnicza PW1 aMichał Cholewa1 aPrzemysław Głomb1 aSebastian Opozda1 aMichał Romaszewski1 aArkadiusz Sochan1 aM. Kosiedowski1 aE. Kuśmierek1 aA. Bęben1 aP. Krawiec1 aA. Stroiński1 aWojciech Burakowski1 aPiotr Krawiec00aAplikacje Sieci Świadomej Treści a978-83-7814-099-300479nas a2200157 4500000000100000000000100001008004100002260002000043100002100063700002300084700002500107700002000132245006300152490000700215520009900222 2009 d bSpringer Verlag1 aJoanna Domańska1 aPrzemysław Głomb1 aPrzemysław Kowalski1 aSławomir Nowak00aModeling of Internet 3D Traffic Using Hidden Markov Models0 v643 a

Artykuł podejmuje temat modelowania złożoności przesyłu siatek progresywnych 3D.

00938nas a2200205 4500000000100000000000100001008004100002260003400043100001700077700002300094700002200117700002200139700002400161700002500185700002200210245005500232300001200287520041100299020002200710 2011 d bSpringeraBerlin / Heidelberg1 aPiotr Gawron1 aPrzemysław Głomb1 aJaroslaw Miszczak1 aZbigniew Puchała1 aTadeusz Czachórski1 aStanisław Kozielski1 aUrszula Stańczyk00aEigengestures for natural human computer interface a49–563 aWe 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. a978-3-642-23168-100422nas a2200145 4500000000100000000000100001008004100002260004500043100002200088700002400110700002300134700002100157700002000178245007800198 2004 d bWydawnictwa Naukowo-TechniczneaWarszawa1 aKrzysztof Grochla1 aTadeusz Czachórski1 aPrzemysław Głomb1 aArkadiusz Sochan1 aAndrzej Grzywak00aInternet w społeczeństwie informacyjnym - Podstawowe problemy Internetu00285nas a2200121 4500000000100000000000100001000000100002008004100003100002200044700002300066245006700089490000700156 2002 d1 aKrzysztof Grochla1 aPrzemysław Głomb00aKształtowanie ruchu w routerach pracujących w systemie Linux0 v2300741nas a2200145 4500000000100000000000100001008004100002260004500043100002200088700002300110700002100133700002000154245006600174520035500240 2004 d bWydawnictwa Naukowo-TechniczneaWarszawa1 aKrzysztof Grochla1 aPrzemysław Głomb1 aArkadiusz Sochan1 aAndrzej Grzywak00aWspółczesne problemy sieci komputerowych - Nowe technologie3 aRozdział 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.00307nas a2200133 4500000000100000000000100001008004100002260000600043100002200049700002100071700002300092700001500115245004300130 2008 d c41 aKrzysztof Grochla1 aArkadiusz Sochan1 aPrzemysław Głomb1 a- Borcochi00aTransmission of scalable video streams00747nas a2200145 4500000000100000000000100001008004100002260004500043100002200088700002100110700002300131700002000154245008000174520034700254 2004 d bWydawnictwa Naukowo-TechniczneaWarszawa1 aKrzysztof Grochla1 aArkadiusz Sochan1 aPrzemysław Głomb1 aAndrzej Grzywak00aWspółczesne problemy sieci komputerowych - Zastosowanie i bezpieczeństwo3 aRozdział 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.00245nas a2200109 4500000000100000000000100001008004100002260001300043100002300056700002100079245003500100 2007 d bSpringer1 aPrzemysław Głomb1 aMarek Kurzyński00aComputer Recognition Systems 200375nas a2200145 4500000000100000000000100001008004100002260003500043100002300078700001800101700002100119700002500140700001700165245004700182 2006 d bAcademic Publishing House EXIT1 aPrzemysław Głomb1 aAndrzej Cader1 aLeszek Rutkowski1 aRyszard Tadeusiewicz1 aJacek Zurada00aArtificial Intelligence and Soft Computing00227nas a2200085 4500000000100000000000100001008004100002100002300043245007500066 2009 d1 aPrzemysław Głomb00aDetection of interest points on 3D data: extending the Harris operator00210nas a2200085 4500000000100000000000100001008004100002100002300043245005800066 2007 d1 aPrzemysław Głomb00aImage Language Terminal Symbols from Feature Analysis00247nas a2200085 4500000000100000000000100001008004100002100002300043245009500066 2005 d1 aPrzemysław Głomb00aAnalysis of fGn and http requests traces using localized multiscale H parameter estimation00310nas a2200109 4500000000100000000000100001008004100002260005100043100002300094700002200117245006100139 2006 d bInstytut Informatyki Teoretycznej i Stosowanej1 aPrzemysław Głomb1 aKrzysztof Grochla00aRepresenting single-link traffic quality with kernel PCA00232nas a2200097 4500000000100000000000100001008004100002100002300043700002200066245004600088 2005 d1 aPrzemysław Głomb1 aKrzysztof Grochla00aModeling Connection State with Kernel PCA00295nas a2200121 4500000000100000000000100001000000100002008004100003100002300044700002200067245007700089490000700166 2002 d1 aPrzemysław Głomb1 aKrzysztof Grochla00aModelowanie stacji roboczych w sieci ATM przy użyciu symulatora OMNeT++0 v2300893nas a2200145 4500000000100000000000100001008004100002260004500043100002300088700002200111700002100133700002000154245007800174520049500252 2004 d bWydawnictwa Naukowo-TechniczneaWarszawa1 aPrzemysław Głomb1 aKrzysztof Grochla1 aArkadiusz Sochan1 aAndrzej Grzywak00aInternet w społeczeństwie informacyjnym - Podstawowe problemy Internetu3 aArtykuł 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.00287nas a2200097 4500000000100000000000100001008004100002100002300043700002000066245010300086 2008 d1 aPrzemysław Głomb1 aSławomir Nowak00aExperimental rate distortion analysis of image coder with contourlet transform and SPIHT algorithm01225nas a2200169 4500000000100000000000100001000000100002008004100003100002300044700002200067700002100089245008600110300001400196490000700210520081700217022002101034 2007 d1 aPrzemysław Głomb1 aZbigniew Puchała1 aArkadiusz Sochan00aContext selection for efficient bit modeling of contourlet transform coefficients a135–1460 v193 aContourlet 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 aISSN 1896–533400435nas a2200145 4500000000100000000000100001008004100002260003100043100002300074700002400097700002100121700002100142245008100163250004500244 2012 d bSpringer Berlin Heidelberg1 aPrzemysław Głomb1 aMichał Romaszewski1 aSebastian Opozda1 aArkadiusz Sochan00aChoosing and Modeling the Hand Gesture Database for a Natural User Interface aLecture Notes in Artificial Intelligence00329nas a2200121 4500000000100000000000100001008004100002100002300043700002400066700002100090700002100111245007500132 2011 d1 aPrzemysław Głomb1 aMichał Romaszewski1 aSebastian Opozda1 aArkadiusz Sochan00aChoosing and modeling hand gesture database for natural user interface00386nas a2200133 4500000000100000000000100001008004100002100002300043700002400066700002100090700002100111245011100132490000900243 2011 d1 aPrzemysław Głomb1 aMichał Romaszewski1 aArkadiusz Sochan1 aSebastian Opozda00aUnsupervised Parameter Selection for Gesture Recognition with Vector Quantization and Hidden Markov Models0 v694900297nas a2200121 4500000000100000000000100001008004100002100002300043700002100066245006200087300001200149022001400161 2009 d1 aPrzemysław Głomb1 aKrzysztof Skabek00aLaboratory for the exploration of virtual 3D environments a57–59 a1640-375400520nas a2200193 4500000000100000000000100001008004100002100002300043700002100066700002100087700002300108700001900131700002500150700001600175700001700191245008200208300001400290020002200304 2014 d1 aPrzemysław Głomb1 aArkadiusz Sochan1 aLeszek Rutkowski1 aMarcin Korytkowski1 aRafał Scherer1 aRyszard Tadeusiewicz1 aLotfi Zadeh1 aJacek Zurada00aSurface Mixture Models for the Optimization of Object Boundary Representation a703–714 a978-3-319-07172-501429nas a2200241 4500000000100000000000100001000000100002008004100003100001900044700001800063700001800081700002000099700002300119700002100142700002400163700002100187700001400208700001500222245003900237300001600276520088100292022001401173 2012 d1 aM. Kosiedowski1 aE. Kuśmierek1 aA. Stroiński1 aMichał Cholewa1 aPrzemysław Głomb1 aSebastian Opozda1 aMichał Romaszewski1 aArkadiusz Sochan1 aA. Bęben1 aP. Krawiec00aAplikacje sieci świadomej treści a1491–15023 aArtykuł 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. a1230-349601032nas a2200193 4500000000100000000000100001000000100002008004100003260000700044100002000051700002100071700001800092700002300110245008500133300001400218490000700232520058500239022001400824 2010 d c111 aSławomir Nowak1 aJoanna Domańska1 aMateusz Nowak1 aPrzemysław Głomb00aProgressive 3D meshes transmission: traffic generating and simulation evaluation a247–2590 v223 aThe 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. a1896-533400389nas a2200109 4500000000100000000000100001008004100002100002000043700002300063245010600086520008700192 2010 d1 aSławomir Nowak1 aPrzemysław Głomb00aREMOTE VIRTUAL REALITY: EXPERIMENTAL INVESTIGATIONSOF PROGRESSIVE 3D MESH TRANSMISSION IN IP NETWORKS3 aPerformance Modelling and Evaluation of Heterogeneous Networks, proc. HETNET 2010.00337nas a2200121 4500000000100000000000100001008004100002100002400043700001700067700002300084245007200107856003600179 2011 d1 aMichał Romaszewski1 aPiotr Gawron1 aPrzemysław Głomb00aTowards a natural gesture interface: LDA-based gesture separability uhttps://arxiv.org/abs/1109.503400362nas a2200133 4500000000100000000000100001008004100002260001900043100002400062700002300086245009900109300001400208490000600222 2011 d c2011bSpringer1 aMichał Romaszewski1 aPrzemysław Głomb00aThe Effect of Multiple Training Sequences on HMM Classification of Motion Capture Gesture Data a365–3730 v400332nas a2200145 4500000000100000000000100001008004100002260000600043100002400049700002300073245005200096300001200148490001200160022001400172 2009 d cV1 aMichał Romaszewski1 aPrzemysław Głomb00a3D Mesh Approximation Using Vector Quantization a71–780 v57/2009 a1615-387100380nas a2200145 4500000000100000000000100001008004100002260001300043100002400056700002300080700001700103700001900120245008100139300001400220 2014 d c10bIEEE1 aMichał Romaszewski1 aPrzemysław Głomb1 aPiotr Gawron1 aKhalifa Djemal00aNatural hand gestures for human identification in a Human-Computer Interface a404–40900432nas a2200157 4500000000100000000000100001008004100002260003400043100002400077700002100101700002300122700002000145700002400165245007100189300001400260 2009 d bAcademy Publishing House EXIT1 aMichał Romaszewski1 aSebastian Opozda1 aPrzemysław Głomb1 aRyszard Choraś1 aAntoni Zabłudowski00a3D Mesh Identification Using Random Walks and Hidden Markov Models a302–30800771nas a2200145 4500000000100000000000100001008004100002260004500043100002100088700002200109700002300131700002000154245007800174520037300252 2004 d bWydawnictwa Naukowo-TechniczneaWarszawa1 aArkadiusz Sochan1 aKrzysztof Grochla1 aPrzemysław Głomb1 aAndrzej Grzywak00aInternet w społeczeństwie informacyjnym - Podstawowe problemy Internetu3 aW rozdziale zarysowano koncepcję usług katalogowych i metody dostępu do nich. Przedstawiono architekturę aplikacji WWW i różne rozwiązania stosowane do tworzenia takich aplikacji. Zaprezentowano wyniki badań porównawczych przeprowadzonych dla tych rozwiązań. Na koniec scharakteryzowano opracowaną aplikację WWW korzystającą z usług katalogowych i XML.00774nas a2200145 4500000000100000000000100001008004100002260004500043100002100088700002300109700002200132700002000154245006600174520038800240 2004 d bWydawnictwa Naukowo-TechniczneaWarszawa1 aArkadiusz Sochan1 aPrzemysław Głomb1 aKrzysztof Grochla1 aAndrzej Grzywak00aWspółczesne problemy sieci komputerowych - Nowe technologie3 aW rozdziale opisano prace badawcze dotyczące transmisji strumieni MPEG-2 poprzez kanał o zmiennej przepływności bitowej w sieci ATM. Prace miały charakter zarówno doświadczalno-pomiarowy, jak i analityczny. Określono zależność funkcyjną pomiędzy parametrami ruchu sieci ATM, natężeniem strumienia wideo a jakością transmisji multimedialnej. Zależność powiązano z00499nas a2200181 4500000000100000000000100001008004100002100002100043700002300064700002100087700002400108700002100132700002200153700001400175700001300189245010100202300001400303 2011 d1 aArkadiusz Sochan1 aPrzemysław Głomb1 aKrzysztof Skabek1 aMichał Romaszewski1 aSebastian Opozda1 aAndrzej Kwiecień1 aPiotr Gaj1 aP. Stera00aVirtual Museum as an Example of 3D Content Distribution in the Architecture of a Future Internet a459–46400402nas a2200169 4500000000100000000000100001008004100002100001700043700001800060700001200078700001600090700001900106700001500125700002300140245005500163300001400218 2009 d1 aE. Switonski1 aD. Tejszerska1 aM. Gzik1 aW. Wolanski1 aB. Gzik-Zroska1 aM. Mandera1 aPrzemysław Głomb00aInteraktywna kinezyterapia dzieci z płaskostopiem a211–21400280nas a2200097 4500000000100000000000100001008004100002100002300043700002000066245009600086 2009 d1 aPrzemysław Głomb1 aSławomir Nowak00aIMAGE CODING WITH CONTOURLET / WAVELET TRANSFORMS AND SPIHT ALGORITHM:AN EXPERIMENTAL STUDY01043nas a2200169 4500000000100000000000100001008004100002260004300043100001700086700002300103700002100126700002200147700002000169245006900189520059700258020001800855 2005 d bWydawnictwa Komunikacji i Łączności1 aT. Białecki1 aPrzemysław Głomb1 aArkadiusz Sochan1 aAndrzej Kwiecień1 aAndrzej Grzywak00aWysokowydajne sieci komputerowe - Zastosowanie i bezpieczeństwo3 aW 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. a83-206-1573-900923nas a2200169 4500000000100000000000100001008004100002260008200043100001700125700002300142700002100165700002200186700002000208245006000228520044700288020001800735 2005 d bWydawnictwa Komunikacji i ŁącznościaWydawnictwa Komunikacji l Łaczności1 aT. Białecki1 aPrzemysław Głomb1 aArkadiusz Sochan1 aAndrzej Kwiecień1 aKazimiera Wódz00aTechniczne i społeczne problemy zastosowania Internetu3 aW 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. a83-206-1590-901428nas a2200181 4500000000100000000000100001008004100002260000900043100002100052700002300073700002700096245009000123856010300213300001200316490000700328520089500335022001601230 2015 d c20151 aKrzysztof Domino1 aPrzemysław Głomb1 aZbigniew Łaskarzewski00aClassification of LPG clients using the Hurst exponent and the correlation coeficient uhttp://yadda.icm.edu.pl/yadda/element/bwmeta1.element.baztech-1ba91297-f921-4524-927c-381996c36512 a13–240 v273 a

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

 a 1896-5334 00592nas a2200217 4500000000100000000000100001008004100002260003800043100002300081700002000104700002100124700002300145700001800168700002500186700001600211700001700227245008700244300001200331490000900343020002200352 2015 d bSpringer International Publishing1 aPrzemysław Głomb1 aMichał Cholewa1 aLeszek Rutkowski1 aMarcin Korytkowski1 aRafal Scherer1 aRyszard Tadeusiewicz1 aLotfi Zadeh1 aJacek Zurada00aExperimental Evaluation of Selected Approaches to Covariance Matrix Regularization a391-4010 v9120 a978-3-319-19368-700315nas a2200109 4500000000100000000000100001008004100002100002400043700002300067245009300090020002200183 2016 d1 aMichał Romaszewski1 aPrzemysław Głomb00aParameter Estimation for HOSVD-based Approximation of Temporally Coherent Mesh Sequences a978-989-758-175-500491nas a2200157 4500000000100000000000100001008004100002100002400043700002300067700002000090245011800110856007100228300001200299490000800311022001400319 2016 d1 aMichał Romaszewski1 aPrzemysław Głomb1 aMichał Cholewa00aSemi-supervised hyperspectral classification from a small number of training samples using a co-training approach uhttp://www.sciencedirect.com/science/article/pii/S0924271616303446 a60 - 760 v121 a0924-271600274nas a2200109 4500000000100000000000100001008004100002100002000043700002300063245005600086020002200142 2016 d1 aMichał Cholewa1 aPrzemysław Głomb00aTwo Stage SVM Classification for Hyperspectral Data a978-989-758-173-100288nas a2200109 4500000000100000000000100001008004100002100002300043700002000066245007000086020002200156 2016 d1 aPrzemysław Głomb1 aMichał Cholewa00aPerformance of Interest Point Descriptors on Hyperspectral Images a978-989-758-175-501088nas a2200181 4500000000100000000000100001008004100002100002000043700001700063700002300080700001900103245007200122856004800194300000800242490000700250520063500257022001400892 2017 d1 aMichał Cholewa1 aPiotr Gawron1 aPrzemysław Głomb1 aDariusz Kurzyk00aQuantum hidden Markov models based on transition operation matrices uhttp://dx.doi.org/10.1007/s11128-017-1544-8 a1010 v163 a

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.

 a1573-133200522nas a2200169 4500000000100000000000100001008004100002260001200043100002300055700002400078700002000102700002100122245011600143856007100259490000800330022001400338 2018 d c07/20181 aPrzemysław Głomb1 aMichał Romaszewski1 aMichał Cholewa1 aKrzysztof Domino00aApplication of hyperspectral imaging and Machine Learning methods for the detection of gunshot residue patterns uhttp://www.sciencedirect.com/science/article/pii/S03790738183036570 v290 a0379-073801191nas a2200145 4500000000100000000000100001008004100002260003800043100002400081700002300105700002000128245009700148520077800245020002201023 2018 d bSpringer International Publishing1 aMichał Romaszewski1 aPrzemysław Głomb1 aMichał Cholewa00aAdaptive, Hubness-Aware Nearest Neighbour Classifier with Application to Hyperspectral Data3 a

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.

 a978-3-030-00840-600427nas a2200157 4500000000100000000000100001008004100002260001000043100002000053700002300073700002400096245011600120300001200236490000700248022001400255 2019 d cMarch1 aMichał Cholewa1 aPrzemysław Głomb1 aMichał Romaszewski00aA Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification a467-4710 v16 a1545-598X02068nas a2200181 4500000000100000000000100001008004100002100002200043700002300065700002300088700001700111245006100128856007100189300001100260490000700271520159400278022001401872 2018 d1 aBartosz Grabowski1 aWojciech Masarczyk1 aPrzemysław Głomb1 aAgata Mendys00aAutomatic pigment identification from hyperspectral data uhttp://www.sciencedirect.com/science/article/pii/S1296207417306544 a1 - 120 v313 a

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.

 a1296-207402286nas a2200157 4500000000100000000000100001008004100002100002300043700002300066700002200089700002400111245012800135856003700263490000700300520182100307 2020 d1 aWojciech Masarczyk1 aPrzemysław Głomb1 aBartosz Grabowski1 aMateusz Ostaszewski00aEffective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling uhttps://arxiv.org/abs/1909.055070 v123 a

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.

00555nas a2200169 4500000000100000000000100001008004100002260007300043100002300116700002100139700002400160700002000184245011100204856003700315300001100352020002200363 2019 d c2019bWroclaw University of Science and TechnologyaWrocław, Poland1 aPrzemysław Głomb1 aKrzysztof Domino1 aMichał Romaszewski1 aMichał Cholewa00aBand selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images uhttps://arxiv.org/abs/1808.03513 ap. 121 a978-83-943803-2-800446nas a2200145 4500000000100000000000100001008004100002260006700043100002200110700002300132700002400155700002400179245007500203020002200278 2019 d bWroclaw University of Science and TechnologyaWrocław, Poland1 aBartosz Grabowski1 aPrzemysław Głomb1 aMichał Romaszewski1 aMateusz Ostaszewski00aUnsupervised deep learning approach to hyperspectral anomaly detection a978-83-943803-2-800409nas a2200133 4500000000100000000000100001008004100002260001300043100002300056700002400079245006100103856008900164020002200253 2020 d bElsevier1 aPrzemysław Głomb1 aMichał Romaszewski00aAnomaly detection in hyperspectral remote sensing images uhttps://www.elsevier.com/books/hyperspectral-remote-sensing/pandey/978-0-08-102894-0 a978-0-08-102894-003407nas a2200193 4500000000100000000000100001008004100002260001200043100002000055700002400075700002300099700002200122700002000144245008300164856004600247490000700293520289900300022001403199 2020 d c11/20201 aKamil Książek1 aMichał Romaszewski1 aPrzemysław Głomb1 aBartosz Grabowski1 aMichał Cholewa00aBlood Stain Classification with Hyperspectral Imaging and Deep Neural Networks uhttps://www.mdpi.com/1424-8220/20/22/66660 v203 a

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.

 a1424-822001424nas a2200145 4500000000100000000000100001008004100002100002400043700002300067700002100090700002000111245008000131856004300211520102400254 2020 d1 aMichał Romaszewski1 aPrzemysław Głomb1 aArkadiusz Sochan1 aMichał Cholewa00aA Dataset for Evaluating Blood Detection in Hyperspectral Images [Data set] uhttps://doi.org/10.5281/zenodo.39849053 a

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.

01436nas a2200169 4500000000100000000000100001008004100002100002400043700002300067700002100090700002000111245006900131856003700200490000800237520100700245022001401252 2021 d1 aMichał Romaszewski1 aPrzemysław Głomb1 aArkadiusz Sochan1 aMichał Cholewa00aA dataset for evaluating blood detection in hyperspectral images uhttps://arxiv.org/abs/2008.102540 v3203 a

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.

 a0379-073801481nas a2200205 4500000000100000000000100001008004100002260004200043100002000085700002300105700002400128700002000152700002200172700001900194245010400213856003700317490001000354520088900364022002201253 2022 d c05/2022bSpringer, ChamaLecce, Italy1 aKamil Książek1 aPrzemysław Głomb1 aMichał Romaszewski1 aMichał Cholewa1 aBartosz Grabowski1 aKrisztian Buza00aImproving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation uhttps://arxiv.org/abs/2109.137480 v132313 a

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.

 a978-3-031-06427-201607nas a2200193 4500000000100000000000100001008004100002260001200043100002200055700001700077700001900094700002300113700002000136700002700156245006100183856005900244490000700303520110300310 2022 d c11/20221 aKrzysztof Grochla1 aAnna Strzoda1 aRafał Marjasz1 aPrzemysław Głomb1 aKamil Książek1 aZbigniew Łaskarzewski00aEnergy-Aware Algorithm for Assignment of Relays in LPWAN uhttps://dl.acm.org/doi/10.1145/3544561?cid=996599133970 v183 a

The Low Power Wide Area Networks allow maintaining connectivity with devices over a distance of a few kilometres. However, due
to the presence of obstacles the communication range in an urban environment may be shorter, which creates multiple blind spots or
areas with limited coverage. The nodes acting as relays may solve this problem by forwarding the data from other devices with poor
connectivity. We propose and investigate a novel algorithm that assigns devices to the relay role while keeping the battery constraints.
We define the algorithm, describe the simulation testbed, and present performance evaluation in several scenarios, including real-life
topologies of IoT networks. The proposed relay selection scheme allows increasing the lifetime of the network by selecting the relay
taking into account the current battery capacity. Additionally, it outperforms a previously proposed relay selection algorithm for LP
WAN, showing an average 4% decrease in transmission time and an order of magnitude lower computation complexity.

02153nas a2200181 4500000000100000000000100001008004100002260004900043100002200092700002300114700002000137700001900157245008500176856006600261490000900327520161300336022002201949 2022 d c11/2022bSpringeraHo Chi Minh City, Vietnam1 aBartosz Grabowski1 aPrzemysław Głomb1 aKamil Książek1 aKrisztian Buza00a Improving Autoencoders Performance for Hyperspectral Unmixing Using Clustering uhttps://link.springer.com/chapter/10.1007/978-981-19-8234-7_90 v17163 a

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.

 a978-981-19-8233-000340nas a2200133 4500000000100000000000100001008004100002260003800043100001700081700002200098700002300120700001800143245004500161 2023 d c07/2023bIEEEaMarrakesh, Morocco1 aAnna Strzoda1 aKrzysztof Grochla1 aPrzemysław Głomb1 aAndrzej Madej00aLink failure prediction in LoRa networks01389nas a2200193 4500000000100000000000100001008004100002260001200043100002300055700002000078700001900098700001800117700002400135245006600159856004000225490000700265520090900272022001401181 2023 d c05/20231 aPrzemysław Głomb1 aMichał Cholewa1 aWojciech Koral1 aAndrzej Madej1 aMichał Romaszewski00aDetection of emergent leaks using machine learning approaches uhttps://doi.org/10.2166/ws.2023.1180 v233 a

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.

 a1606-974902406nas a2200241 4500000000100000000000100001008004100002260001200043100002000055700002200075700002300097700002400120700001800144700001900162700001900181700001700200700001900217700001900236700002100255245017800276856006600454520164400520 2023 d c08/20231 aKamil Książek1 aWilhelm Masarczyk1 aPrzemysław Głomb1 aMichał Romaszewski1 aIga Stokłosa1 aPiotr Ścisło1 aPaweł Dębski1 aRobert Pudlo1 aKrisztian Buza1 aPiotr Gorczyca1 aMagdalena Piegza00aThe 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 uhttps://www.medrxiv.org/content/10.1101/2023.08.04.23293640v13 a

Background and Objective: 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.
Methods: 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.
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.
Results and Conclusions: 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.

01717nas a2200217 4500000000100000000000100001008004100002100002000043700002200063700002300085700002400108700001800132700001900150700001900169700001700188700001900205700002100224245014000245856003800385520107600423 2023 d1 aKamil Książek1 aWilhelm Masarczyk1 aPrzemysław Głomb1 aMichał Romaszewski1 aIga Stokłosa1 aPiotr Ścisło1 aPaweł Dębski1 aRobert Pudlo1 aPiotr Gorczyca1 aMagdalena Piegza00aHRV-ACC: a dataset with R-R intervals and accelerometer data for the diagnosis of psychotic disorders using a Polar H10 wearable sensor uhttps://zenodo.org/record/81712663 a

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.

00488nas a2200157 4500000000100000000000100001008004100002100002400043700002100067700002400088700002300112700002600135700002000161245013500181022001400316 2023 d1 aAgnieszka Ciemięga1 aKatarzyna Maresz1 aMichał Romaszewski1 aPrzemysław Głomb1 aPaulina Krupska-Wolas1 aKrystian Prusik00aHyperspectral Imaging as a Facile and Non-Destructive Method for Size Analysis of Gold Nanoparticles Deposited on Porous Materials a0934-086601285nas a2200205 4500000000100000000000100001008004100002260015900043100001900202700002000221700002200241700002300263700001900286700002100305245012300326856004500449490000900494520055400503022002201057 2023 d c09/2023bKnižnicné a edicné centrum, Fakulta matematiky, fyziky a informatiky, Univerzita Komenského, Mlynská dolina, BratislavaaTatranské Matliare1 aKrisztian Buza1 aKamil Książek1 aWilhelm Masarczyk1 aPrzemysław Głomb1 aPiotr Gorczyca1 aMagdalena Piegza00aA Simple and Effective Classifier for the Detection of Psychotic Disorders based on Heart Rate Variability Time Series uhttps://ceur-ws.org/Vol-3498/paper28.pdf0 v34983 a

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.

 a978-80-8147-132-200633nas a2200229 4500000000100000000000100001008004100002100002300043700002300066700002500089700002200114700002300136700001900159700001800178700002400196700001700220700002500237700002200262700002100284700002200305245007600327 2023 d1 aBartłomiej Gardas1 aPrzemysław Głomb1 aPrzemysław Sadowski1 aZbigniew Puchała1 aKonrad Jałowiecki1 aŁukasz Pawela1 aOrphee Faucoz1 aPierre-Marie Brunet1 aPiotr Gawron1 aMatthijs Van Waveren1 aMickaël Savinaud1 aGuillaume Pasero1 aVeronique Defonte00aHyper-Spectral Image Classification Using Adiabatic Quantum Computation00491nas a2200169 4500000000100000000000100001008004100002260004000043100002300083700002400106700002000130700001900150700001800169700002000187700002500207245008900232 2023 d bWydawnictwo Politechniki Łódzkiej1 aPrzemysław Głomb1 aMichał Romaszewski1 aMichał Cholewa1 aWojciech Koral1 aAndrzej Madej1 aMaciej Skrabski1 aKatarzyna Kołodziej00aMachine Learning for Water Leak Detection and Localization in the WaterPrime Project00544nas a2200181 4500000000100000000000100001008004100002100002300043700002000066700001900086700001700105700001700122700002100139700002100160700001900181245012300200856003900323 2023 d1 aPrzemysław Głomb1 aMichał Cholewa1 aPaweł Foszner1 aJakub Bularz1 aMaria Ganzha1 aLeszek Maciaszek1 aMarcin Paprzycki1 aDominik Slezak00aContinual learning of a time series model using a mixture of HMMs with application to the IoT fuel sensor verification uhttps://doi.org/10.15439/2023F185600754nas a2200253 4500000000100000000000100001008004100002260001200043100002000055700002200075700002300097700002400120700001800144700001900162700001900181700001700200700001900217700001900236700002100255245013000276856007200406490000800478022001400486 2024 d c05/20241 aKamil Książek1 aWilhelm Masarczyk1 aPrzemysław Głomb1 aMichał Romaszewski1 aIga Stokłosa1 aPiotr Ścisło1 aPaweł Dębski1 aRobert Pudlo1 aKrisztian Buza1 aPiotr Gorczyca1 aMagdalena Piegza00aAssessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data uhttps://www.sciencedirect.com/science/article/pii/S00104825240062800 v176 a0010-482500457nas a2200157 4500000000100000000000100001008004100002260001200043100002400055700002400079700002300103700002000126700002500146245009100171856003700262 2024 d c06/20241 aMichał Romaszewski1 aPrzemysław Sekuła1 aPrzemysław Głomb1 aMichał Cholewa1 aKatarzyna Kołodziej00aThrough the Thicket: A Study of Number-Oriented LLMs derived from Random Forest Models uhttps://arxiv.org/abs/2406.0492600578nas a2200193 4500000000100000000000100001008004100002260001200043100002000055700002400075700002300099700002500122700002100147700001600168700001900184700001800203700002000221245014300241 2024 d c06/20241 aMichał Cholewa1 aMichał Romaszewski1 aPrzemysław Głomb1 aKatarzyna Kołodziej1 aMichał Gorawski1 aJakub Koral1 aWojciech Koral1 aAndrzej Madej1 aKryspin Musioł00a‘Just One More Sensor is Enough’ – Iterative Water Leak Localization with Physical Simulation and a Small Number of Pressure Sensors00456nas a2200157 4500000000100000000000100001008004100002260001200043100002500055700002000080700002300100700001900123700002400142245009500166856003700261 2024 d c09/20241 aKatarzyna Kołodziej1 aMichał Cholewa1 aPrzemysław Głomb1 aWojciech Koral1 aMichał Romaszewski00aEfficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials uhttps://arxiv.org/abs/2410.0277200605nas a2200217 4500000000100000000000100001008004100002100001700043700002500060700002300085700002300108700002500131700002000156700002100176700002200197700002400219700001800243700002200261700001900283245008500302 2024 d1 aPiotr Gawron1 aPrzemysław Sadowski1 aPrzemysław Głomb1 aBartłomiej Gardas1 aMatthijs Van Waveren1 aClément Forray1 aGuillaume Pasero1 aMickaël Savinaud1 aPierre-Marie Brunet1 aOrphee Faucoz1 aZbigniew Puchała1 aŁukasz Pawela00aWhat Could be Achieved with a Million Qubits Quantum Annealer in Remote Sensing?00409nas a2200145 4500000000100000000000100001008004100002100002500043700002000068700002400088700002300112700001900135700002400154245008500178 2024 d1 aKatarzyna Kołodziej1 aMichał Cholewa1 aMichał Romaszewski1 aPrzemysław Głomb1 aWojciech Koral1 aPrzemysław Sekuła00aCalibration of Water Demand Network Through a Machine Learned Digital Twin Model00427nas a2200157 4500000000100000000000100001008004100002260001200043100002400055700002400079700002300103700002000126700002500146245009100171490000700262 2025 d c03/20251 aMichał Romaszewski1 aPrzemysław Sekuła1 aPrzemysław Głomb1 aMichał Cholewa1 aKatarzyna Kołodziej00aThrough the Thicket: A Study of Number-Oriented LLMS Derived from Random Forest Models0 v1501940nas a2200157 4500000000100000000000100001008004100002100002400043700002400067700002300091700002000114700001900134245006100153856006700214520150100281 2025 d1 aPrzemysław Sekuła1 aMichał Romaszewski1 aPrzemysław Głomb1 aMichał Cholewa1 aŁukasz Pawela00aQuantum-aware Transformer model for state classification uhttps://link.springer.com/chapter/10.1007/978-3-031-97570-7_153 a

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.

02630nas a2200241 4500000000100000000000100001008004100002260001200043100002000055700002200075700002300097700002400120700001900144700002400163700002000187700002500207700001900232700002100251245012200272490000700394520197300401022001402374 2025 d c09/20251 aKamil Książek1 aWilhelm Masarczyk1 aPrzemysław Głomb1 aMichał Romaszewski1 aKrisztian Buza1 aPrzemysław Sekuła1 aMichał Cholewa1 aKatarzyna Kołodziej1 aPiotr Gorczyca1 aMagdalena Piegza00aDeep learning approach for automatic assessment of schizophrenia and bipolar disorder in patients using R-R intervals0 v213 a

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.

 a1553-735800311nas a2200109 4500000000100000000000100001008004100002100002500043700002300068700001800091245009200109 2025 d1 aKatarzyna Kołodziej1 aPrzemysław Głomb1 aAnna Zawadzka00aChallenges associated with the integration of Large Multimodal Models for waste sorting00317nas a2200109 4500000000100000000000100001008004100002100002000043700002400063700002300087245009700110 2025 d1 aMichał Cholewa1 aMichał Romaszewski1 aPrzemysław Głomb00aData structure better than labels? Unsupervised heuristics for SVM hyperparameter estimation00317nas a2200109 4500000000100000000000100001008004100002100002000043700002400063700002300087245009700110 2025 d1 aMichał Cholewa1 aMichał Romaszewski1 aPrzemysław Głomb00aData structure better than labels? Unsupervised heuristics for SVM hyperparameter estimation01850nas a2200121 4500000000100000000000100001008004100002100001800043700002300061700002000084245008900104520153500193 2025 d1 aAnna Zawadzka1 aPrzemysław Głomb1 aMateusz Żarski00aDevelopment of an effective method for detecting small buildings in satellite images3 a

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.

00485nas a2200169 4500000000100000000000100001008004100002260001200043100002500055700002000080700002300100700001900123700002400142245009500166856004600261490000800307 2026 d c02/20261 aKatarzyna Kołodziej1 aMichał Cholewa1 aPrzemysław Głomb1 aWojciech Koral1 aMichał Romaszewski00aEfficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials uhttps://doi.org/10.1061/JWRMD5.WRENG-68390 v15200365nas a2200145 4500000000100000000000100001008004100002100001800043700002000061700001700081700002300098700002400121700002000145245005400165 2026 d1 aAnna Zawadzka1 aMateusz Żarski1 aKamil Drejer1 aPrzemysław Głomb1 aMichał Romaszewski1 aMichał Cholewa00a Map-Guided Cross-Training for Building Detection01085nas a2200109 4500000000100000008004100001260001200042100001800054700002300072245007500095520080500170 2026 d c04/20261 aAnna Zawadzka1 aPrzemysław Głomb00aArchitecture Matters: Gender Disparities in Automated Image Moderation3 a

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,  we compute false positive rates overall and by gender. 
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. 
Reasoning-based models do not consistently mitigate bias but, in the proposed pipeline, they offer a transparency layer.

02216nas a2200169 4500000000100000008004100001100001700042700002500059700002000084700002400104700002300128700001800151700001600169700001900185245007600204520176600280 2026 d1 aAygün Varol1 aKatarzyna Kołodziej1 aŁukasz Sobczak1 aMichał Romaszewski1 aPrzemysław Głomb1 aNaser Motlagh1 aMirka Leino1 aJohanna Virkki00aEnabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing3 a

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.

02266nas a2200181 4500000000100000008004100001100001700042700002500059700002000084700002400104700002300128700001800151700001600169700001900185245007600204856003800280520176600318 2026 d1 aAygün Varol1 aKatarzyna Kołodziej1 aŁukasz Sobczak1 aMichał Romaszewski1 aPrzemysław Głomb1 aNaser Motlagh1 aMirka Leino1 aJohanna Virkki00aEnabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing uhttps://arxiv.org/abs/2606.22496 3 a

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.

03010nas a2200181 4500000000100000008004100001100001700042700002500059700002000084700002400104700002300128700001800151700001600169700001900185245011600204856005200320520245600372 2026 d1 aAygün Varol1 aKatarzyna Kołodziej1 aŁukasz Sobczak1 aMichał Romaszewski1 aPrzemysław Głomb1 aNaser Motlagh1 aMirka Leino1 aJohanna Virkki00aAIRWISE: Environmental Sensor and LLM Query Dataset for Edge AI-Based Air-Quality and Thermal-Comfort Analytics uhttps://zenodo.org/doi/10.5281/zenodo.20783874 3 a

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”: https://doi.org/10.48550/arXiv.2606.22496
AIRWISE provides three core resources:
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.
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.
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.
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.

00582nas a2200193 4500000000100000008004100001100002400042700001700066700002500083700001800108700002500126700002300151700002000174700002300194700002100217700002400238700001600262245011000278 2026 d1 aMichał Romaszewski1 aKamil Drejer1 aKatarzyna Kołodziej1 aAnna Zawadzka1 aStanisław Lewiński1 aPrzemysław Głomb1 aMarek Ruciński1 aMichał Krupiński1 aKrzysztof Gryguc1 aPrzemysław Sekuła1 aSzymon Sala00aToward Seasonal Guidelines for Robust Deep-Learning Sentinel-2 Building Detection in Different Area Types01668nas a2200109 4500000000100000000000100001008004100002260005500043100002000098245008900118520135100207 2013 d bInstytut Informatyki Teoretycznej i Stosowanej PAN1 aMichał Cholewa00aCzołowe funkcje kuliste jako baza do aproksymacji sygnałów o ograniczonym paśmie3 aTematem 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.01556nam a2200169 4500000000100000000000100001008004100002260002300043100001700066700002000083700001900103245007300122856004900195300000800244520111600252022001801368 2016 d bIITiS PANaGliwice1 aPiotr Gawron1 aMichał Cholewa1 aKatarzyna Kara00aRewolucja stanu - fantastyczne wprowadzenie do informatyki kwantowej uhttps://depot.ceon.pl/handle/123456789/16807 a1283 a

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.

Jednak wszechobecna cenzura rodzi bunt.

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...

 a978839260541600293nas a2200097 4500000000100000000000100001008004100002100002000043700002100063245011100084 2016 d1 aMichał Cholewa1 aArkadiusz Sochan00aMulti-sensor dataset for testing merge of Hyperspectral, HD and 3D cloud information for image recognition00474nas a2200169 4500000000100000000000100001008004100002100002400043700002100067700001600088700001800104700002100122700002000143245008900163856004500252490000700297 2025 d1 aPrzemysław Sekuła1 aNarjes Shayesteh1 aQinglian He1 aSara Zahedian1 aRodrigo Moscosso1 aMichał Cholewa00aMove Over Law Compliance Analysis Utilizing a Deep Learning Computer Vision Approach uhttps://www.mdpi.com/2076-3417/15/4/20110 v1501834nas a2200217 4500000000100000000000100001008004100002260001200043100002400055700001600079700001900095700002100114700001800135700001700153700001500170700002000185245007100205856004600276490000700322520128700329 2025 d c09/20251 aPrzemysław Sekuła1 aQinglian He1 aKaveh Sadabadi1 aRodrigo Moscosso1 aThomas Jacobs1 aZachary Laan1 aMark Franz1 aMichał Cholewa00aVehicle-to-Infrastructure System Prototype for Intersection Safety uhttps://www.mdpi.com/2076-3417/15/17/97540 v153 a

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.

00352nas a2200145 4500000000100000000000100001008004100002100002400043700001700067700002100084245006400105300001400169490000900183022001400192 2014 d1 aMichał Romaszewski1 aPiotr Gawron1 aSebastian Opozda00aDimensionality reduction of dynamic animations using HO-SVD a757–7680 v8467 a0302-974300266nas a2200109 4500000000100000000000100001008004100002100002400043700001700067700002100084245005100105 2013 d1 aMichał Romaszewski1 aPiotr Gawron1 aSebastian Opozda00aCompression of animated 3D models using HO-SVD00367nas a2200157 4500000000100000000000100001000000100002008004100003100002400044700001700068700002100085245006900106300001400175490000600189022001400195 2013 d1 aMichał Romaszewski1 aPiotr Gawron1 aSebastian Opozda00aDimensionality Reduction of Dynamic Mesh Animations Using HO-SVD a277–2890 v3 a2083-256700362nas a2200157 4500000000100000000000100001000000100002008004100003260000600044100002400050700002100074245007400095300001400169490000700183022001400190 2010 d c91 aMichał Romaszewski1 aSebastian Opozda00aOptimization of a Vector Quantizer's Quality for 3D Mesh Applications a131–1400 v22 a1896-533401416nas a2200145 4500000000100000000000100001008004100002260004400043100002400087700002100111700002100132245009200153520100300245020002201248 2018 d bSpringer International PublishingaCham1 aMichał Romaszewski1 aArkadiusz Sochan1 aKrzysztof Skabek00aMatrix and Tensor-Based Approximation of 3D Face Animations from Low-Cost Range Sensors3 a

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™ 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.

 a978-3-030-00840-600422nas a2200157 4500000000100000000000100001008004100002260001200043100002300055700002400078700002100102700002300123245010100146300001000247490000700257 2020 d c11/20201 aMałgorzata Domino1 aMichał Romaszewski1 aTomasz Jasiński1 aMałgorzata Maśko00aComparison of the Surface Thermal Patterns of Horses and Donkeys in Infrared Thermography Images a 22010 v1000772nas a2200145 4500000000100000000000100001008004100002100002300043700002400066700002100090700002300111245009000134856003800224520036400262 2020 d1 aMałgorzata Domino1 aMichał Romaszewski1 aTomasz Jasiński1 aMałgorzata Maśko00aComparison of surface thermal patterns of horses and donkeys in IRT images [Data set] uhttps://zenodo.org/record/40850753 a

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.

00567nas a2200181 4500000000100000000000100001008004100002260001200043100001700055700002300072700001800095700002400113700002000137245016200157856004500319490000700364022001400371 2021 d c03/20211 aFilip Pałka1 aWojciech Książek1 aPawel Plawiak1 aMichał Romaszewski1 aKamil Książek00aHyperspectral Classification of Blood-Like Substances Using Machine Learning Methods Combined with Genetic Algorithms in Transductive and Inductive Scenarios uhttps://www.mdpi.com/1424-8220/21/7/22930 v21 a1424-822000305nas a2200109 4500000000100000000000100001008004100002260002800043100002400071700002400095245007600119 2024 d c04/2024aWarsaw, Poland1 aMichał Romaszewski1 aPrzemysław Sekuła00aPoster: Explainable classification of multimodal time series using LLMs00357nas a2200121 4500000000100000000000100001008004100002100002000043700002400063700002000087245010700107856002100214 d1 aKatarzyna Filus1 aMichał Romaszewski1 aMateusz Żarski00aSemantic Depth Matters: Explaining Errors of Deep Vision Networks through Perceived Class Similarities uarXiv:2504.0995600463nas a2200157 4500000000100000000000100001008004100002260001200043100001700055700002400072700001700096245009400113856007700207490000700284022001400291 2025 d c08/20251 aManish Gupta1 aMichał Romaszewski1 aPiotr Gawron00aPotential of quantum machine learning for processing multispectral Earth observation data uhttps://journals.pan.pl/dlibra/publication/154279/edition/135180/content0 v73 a2300-191700394nas a2200145 4500000000100000000000100001008004100002260001200043100002200055700002400077700002000101700002100121700001900142245008700161 2025 d c04/20251 aKrzysztof Grochla1 aMichał Romaszewski1 aJarosław Sotor1 aPiotr Masłowski1 aBartosz Belter00aTowards AI-assisted Science with PLAI4SCIENCE - new Polish Research Infrastructure00415nas a2200169 4500000000100000000000100001008004100002100001200043700001300055700001000068700002600078700001500104245009400119300001100213490000700224022001400231 2014 d1 aL. Ding1 aL. Zhang1 aX. Wu1 aMirosław Skibniewski1 aY. Qunzhou00aSafety management in tunnel construction: Case study of Wuhan metro construction in China a8–150 v62 a0925-753500394nas a2200169 4500000000100000000000100001008004100002100001300043700002600056700001000082700001200092700001200104245007600116300001100192490000700203022001400210 2014 d1 aL. Zhang1 aMirosław Skibniewski1 aX. Wu1 aY. Chen1 aQ. Deng00aA probabilistic approach for safety risk analysis in metro construction a8–170 v63 a0925-753501606nas a2200181 4500000000100000000000100001008004100002260005600043100001300099700001000112700001200122700002600134700001300160700002600173245010500199300001400304520110600318 2013 d bSent Istvan University Ybl Miklos Faculty, Budapest1 aL. Zhang1 aX. Wu1 aL. Ding1 aMirosław Skibniewski1 aM. Hajdu1 aMirosław Skibniewski00aDecision support analysis for safety assurance in metro construction base on Fuzzy Bayesian Networks a896–9093 aThis 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.00383nas a2200157 4500000000100000000000100001008004100002100001300043700001000056700001200066700002600078245008600104300001400190490000700204022001400211 2013 d1 aL. Zhang1 aX. Wu1 aL. Ding1 aMirosław Skibniewski00aA novel model for risk assessment of adjacent buildings in tunneling environments a185–1940 v65 a0360-132302109nas a2200181 4500000000100000000000100001008004100002100001300043700001000056700001200066700002600078700001400104245011100118300001400229490000700243520166300250022001401913 2014 d1 aL. Zhang1 aX. Wu1 aQ. Chen1 aMirosław Skibniewski1 aS.-C. Hsu00aTowards a safety management approach for adjacent buildings in tunneling environments: Case study in China a222–2350 v753 aThis 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. a0360-132300391nas a2200169 4500000000100000000000100001008004100002100001300043700001000056700002600066700001300092700001000105245007200115300001200187490000800199022001400207 2014 d1 aL. Zhang1 aX. Wu1 aMirosław Skibniewski1 aJ. Zhong1 aY. Lu00aBayesian-network-based safety risk analysis in construction project a29–390 v131 a0951-832000417nas a2200181 4500000000100000000000100001000000100002008004100003100001300044700001400057700002600071700001100097700001400108245008100122300001100203490000700214022001400221 2014 d1 aS. Ghosh1 aB. Lauren1 aMirosław Skibniewski1 aN. Sam1 aK.J. Hoon00aOrganizational governance to integrate sustainability project: a case study. a1–240 v20 a2029-491301335nas a2200229 4500000000100000000000100001000000100002008004100003100002600044700001700070700001300087700001500100700001400115700001400129700001500143700001400158245008000172300001200252490000600264520082100270022001401091 2014 d1 aMirosław Skibniewski1 aH.-P. Tserng1 aS.-H. Ju1 aC.-W. Feng1 aC.-T. Lin1 aJ.-Y. Han1 aK.-W. Weng1 aS.-C. Hsu00aWeb-based real time bridge scour monitoring system for disaster management. a17–250 v93 aNatural 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. a1822-427x01574nas a2200181 4500000000100000000000100001008004100002100001200043700001300055700001500068700002600083700001500109245011000124300001600234490000700250520112100257022001401378 2015 d1 aX.G. Wu1 aZ. Jiang1 aL.M. Zhang1 aMirosław Skibniewski1 aJ.B. Zhong00aDynamic risk analysis for adjacent buildings in tunneling environments: a Bayesian network based approach a1447–14610 v293 aThis 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. a1436-324001762nas a2200193 4500000000100000000000100001008004100002100001500043700001500058700001600073700002600089700001600115700001700131245009600148300001400244490000800258520128800266022001401554 2015 d1 aWu Xianguo1 aLiu Huitao1 aZhang Limao1 aMirosław Skibniewski1 aDeng Qianli1 aTeng Jiaying00aA dynamic Bayesian network based approach to safety decision support in tunnel construction a157–1680 v1343 aThis 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. a0951-832001772nas a2200181 4500000000100000000000100001000000100002008004100003100001000044700001000054700002600064700001000090700001200100700001000112245013700122490000700259520132400266 2015 d1 aY. Lu1 aY. Li1 aMirosław Skibniewski1 aZ. Wu1 aR. Wang1 aY. Le00aInformation and communication technology applications in architecture, engineering, and construction organizations: a 15 year review0 v313 aInformation 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.00464nas a2200181 4500000000100000000000100001000000100002008004100003100001000044700001000054700002600064700001000090700001200100700001000112245013900122490000700261022001400268 2014 d1 aY. Lu1 aY. Li1 aMirosław Skibniewski1 aZ. Wu1 aR. Wang1 aY. Le00aInformation and communication technology applications in architecture, engineering, and construction organizations: A 15-years review.0 v31 a0742-597x00497nas a2200181 4500000000100000000000100001008004100002100001600043700001500059700001400074700002600088700001400114245011100128856004100239300001400280490000700294022001400301 2016 d1 aLimao Zhang1 aXianguo Wu1 aYawei Qin1 aMirosław Skibniewski1 aWenli Liu00aTowards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel-Induced Pipeline Damage uhttp://dx.doi.org/10.1111/risa.12448 a278–3010 v36 a1539-692401689nas a2200157 4500000000100000000000100001008004100002100001700043700001700060700002600077245012200103856005100225300001200276490000700288520123600295 2016 d1 aSun-Chan Bae1 aWon-Suk Jang1 aMirosław Skibniewski00aReliability performance of wireless sensor networks for civil infrastructure – Part II: prediction and verification uhttp://dx.doi.org/10.3846/13923730.2014.948909 a243-2530 v223 a

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.

01896nas a2200181 4500000000100000000000100001008004100002100001600043700001500059700001600074700002600090700001300116245006400129856005200193300001200245490000700257520145000264 2016 d1 aLimao Zhang1 aXianguo Wu1 aLieyun Ding1 aMirosław Skibniewski1 aYujie Lu00aBim-Based Risk Identification System in tunnel construction uhttp://dx.doi.org/10.3846/13923730.2015.1023348 a529-5390 v223 a

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.

00408nas a2200157 4500000000100000000000100001008004100002260001200043100001200055700001400067700002600081245011000107300001200217490000700229022001400236 2017 d c04/20171 aQ.Q. Ju1 aJ.Y. Ding1 aMirosław Skibniewski00aOptimization strategies to eliminate interface conflicts in complex study chains of construction projects a712-7260 v23 a1392-373000398nas a2200145 4500000000100000000000100001008004100002260001200043100001000055700002600065245013200091300000900223490000600232022001400238 2017 d c11/20171 aY Han1 aMirosław Skibniewski00aA Market Equilibrium Supply Chain Model for Supporting Self-Manufacturing or Outsourcin Decisions in Prefabricated Construction a1-180 v9 a2071-105000397nas a2200169 4500000000100000000000100001008004100002260001200043100001200055700001100067700000900078700002600087245008200113300001000195490000800205022001400213 2017 d c08/20171 aL Zhang1 aL Ding1 aX Wu1 aMirosław Skibniewski00aAn improved Dempster–Shafer approach to construction safety risk perception a30-460 v132 a0950-705100446nas a2200181 4500000000100000000000100001008004100002260001200043100001100055700001200066700002600078700001100104700001300115245010300128300001200231490000700243022001400250 2017 d c10/20171 aC Zhou1 aLY Ding1 aMirosław Skibniewski1 aHB Luo1 aSN Jiang00aCharacterizing time series of near-miss accidents in metro construction via complex network theory a145-1580 v98 a0925-753500409nas a2200169 4500000000100000000000100001008004100002260001200043100001400055700001300069700001000082700002600092245008600118300001400204490000700218022001400225 2017 d c05/20171 aL.M Zhang1 aY. Huang1 aX. Wu1 aMirosław Skibniewski00aRisk-based estimate for operational safety in complex projects under uncertainty, a108–1200 v54 a1568-494600433nas a2200169 4500000000100000000000100001008004100002260001200043100001200055700001300067700001000080700002600090245011800116300000900234490000600243022001400249 2017 d c03/20171 aJ. Yuan1 aX. Zheng1 aJ You1 aMirosław Skibniewski00aIdentifying Critical Factors Influencing the Rents of Public Rental Housing Delivery by PPPs: The Case of Nanjing a1-220 v9 a2071-105000457nas a2200181 4500000000100000000000100001008004100002260001200043100001300055700001000068700001300078700002600091700001300117245011200130300001200242490000700254022001400261 2015 d c02/20151 aLM Zhang1 aXG Wu1 aQQ. Chen1 aMirosław Skibniewski1 aJB Zhong00aDeveloping a cloud model based risk assessment methodology for tunnel- induced damage to existing pipelines a513-5260 v29 a1436-324000459nas a2200181 4500000000100000000000100001008004100002260001200043100001300055700001000068700002600078700001200104700001200116245011600128300001200244490000700256022001400263 2015 d c05/20151 aLM Zhang1 aXG Wu1 aMirosław Skibniewski1 aWL Fang1 aQL Deng00aConservation of historical buildings in tunneling environments: Case study of Wuhan Metro construction in China a310-3220 v82 a0950-061800414nas a2200169 4500000000100000000000100001008004100002260001200043100001200055700001000067700001300077700002600090245009500116300001200211490000700223022001400230 2015 d c12/20151 aLI Ding1 aXG Wu1 aLM Zhang1 aMirosław Skibniewski00aHow to protect historical buildings against tunnel-induced damage: A case study in China.  a904-9110 v16 a1296-207400406nas a2200181 4500000000100000000000100001008004100002260001200043100001000055700000900065700001200074700002600086700001200112245006900124300001000193490000700203022001400210 2015 d c05/20151 aXG Wu1 aQ Lu1 aL Zhang1 aMirosław Skibniewski1 aYH Wang00aProspective safety performance evaluation on construction sites a58-720 v78 a0001-457500438nas a2200193 4500000000100000000000100001008004100002260001200043100001000055700001200065700001300077700001200090700002600102700001300128245007000141300001200211490000700223022001400230 2015 d c08/20151 aXG Wu1 aYH Wang1 aLM Zhang1 aLY Ding1 aMirosław Skibniewski1 aJB Zhong00aA Dynamic Decision Approach for Risk Analysis in Complex Projects a591-6010 v79 a0921-029602140nas a2200217 4500000000100000000000100001008004100002100001500043700001300058700002000071700001400091700001600105700002600121700001600147245009700163856007100260300001100331490000800342520155800350022001401908 2019 d1 aCheng Zhou1 aRui Chen1 aShuangnan Jiang1 aYing Zhou1 aLieyun Ding1 aMirosław Skibniewski1 aXinggui Lin00aHuman dynamics in near-miss accidents resulting from unsafe behavior of construction workers uhttp://www.sciencedirect.com/science/article/pii/S037843711930888X a1214950 v5303 a

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.

 a0378-437102551nas a2200181 4500000000100000000000100001008004100002100001500043700001600058700002600074700001300100245011100113856007100224300001100295490000700306520204200313022001402355 2019 d1 aShiyao Cai1 aZhiliang Ma1 aMirosław Skibniewski1 aSong Bao00aConstruction automation and robotics for high-rise buildings over the past decades: A comprehensive review uhttp://www.sciencedirect.com/science/article/pii/S1474034619305622 a1009890 v423 a

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.

 a1474-034600448nas a2200157 4500000000100000000000100001008004100002100001500043700001500058700001000073700001500083700002600098245014500124300001400269490000700283 2020 d1 aLiang Wang1 aPing Zhang1 aLi Ma1 aXuhui Cong1 aMirosław Skibniewski00aDeveloping a corporate social responsibility framework for sustainable construction using partial least squares structural equation modeling a186–2120 v2602459nas a2200169 4500000000100000000000100001008004100002100001400043700001500057700002600072245010000098856007100198300001200269490000700281520198700288022001402275 2019 d1 aKaiman Li1 aHanbin Luo1 aMirosław Skibniewski00aA non-centralized adaptive method for dynamic planning of construction components storage areas uhttp://www.sciencedirect.com/science/article/pii/S1474034617305633 a80 - 940 v393 a

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.

 a1474-034600339nas a2200145 4500000000100000000000100001008004100002100001500043700001400058700002600072700001100098700001700109245005800126490000900184 2019 d1 aNuman Khan1 aAhmad Ali1 aMirosław Skibniewski1 aDo Lee1 aChansik Park00aExcavation Safety Modeling Approach Using BIM and VPL0 v201900373nas a2200133 4500000000100000000000100001008004100002100001900043700001800062700001500080700002600095245010900121490000900230 2019 d1 aChuanjun Zheng1 aJingfeng Yuan1 aLingzhi Li1 aMirosław Skibniewski00aProcess-Based Identification of Critical Factors for Residual Value Risk in China's Highway PPP Projects0 v201900392nas a2200145 4500000000100000000000100001008004100002100001800043700001500061700001600076700002600092245010600118300001400224490000800238 2019 d1 aJingfeng Yuan1 aLingzhi Li1 aEndong Wang1 aMirosław Skibniewski00aExamining sustainability indicators of space management in elderly Facilities—a case study in China a144–1590 v20800369nas a2200157 4500000000100000000000100001008004100002100001200043700001600055700001500071700001500086700002600101245006200127300001400189490000800203 2019 d1 aYue Pan1 aLimao Zhang1 aXianguo Wu1 aWenwei Qin1 aMirosław Skibniewski00aModeling face reliability in tunneling: A copula approach a272–2860 v10900418nas a2200157 4500000000100000000000100001008004100002100001600043700001600059700002000075700002600095700002000121245009800141300001300239490000800252 2019 d1 aShengyu Guo1 aLieyun Ding1 aYongcheng Zhang1 aMirosław Skibniewski1 aKongzheng Liang00aHybrid recommendation approach for behavior modification in the Chinese construction industry a040190350 v14500422nas a2200157 4500000000100000000000100001008004100002100001800043700001100061700001100072700001400083700002600097245012000123300001400243490000700257 2019 d1 aJingfeng Yuan1 aWei Li1 aBo Xia1 aYuan Chen1 aMirosław Skibniewski00aOperation performance measurement of public rental housing delivery by PPPS with fuzzy-AHP comprehensive evaluation a328–3530 v2300387nas a2200145 4500000000100000000000100001008004100002100001500043700001600058700001400074700002600088245010800114300001200222490000700234 2019 d1 aCheng Zhou1 aLieyun Ding1 aYing Zhou1 aMirosław Skibniewski00aVisibility graph analysis on time series of shield tunneling parameters based on complex network theory a10–240 v8900382nas a2200121 4500000000100000000000100001008004100002100001800043700001400061700001600075700002600091245014300117 2019 d1 aJingfeng Yuan1 aLei Zhang1 aYongtao Tan1 aMirosław Skibniewski00aEvaluating the regional social sustainability contribution of public-private partnerships in China: The development of an indicator system00420nas a2200145 4500000000100000000000100001008004100002100001800043700001500061700001400076700002600090245013500116300001600251490000700267 2019 d1 aJingfeng Yuan1 aWenying Ji1 aJiyue Guo1 aMirosław Skibniewski00aSimulation-based dynamic adjustments of prices and subsidies for transportation PPP projects based on stakeholders’ satisfaction a2309–23450 v4600374nas a2200145 4500000000100000000000100001008004100002100001600043700001500059700001400074700002600088245009400114300001300208490000700221 2019 d1 aLimao Zhang1 aXianguo Wu1 aWenli Liu1 aMirosław Skibniewski00aOptimal Strategy to Mitigate Tunnel-Induced Settlement in Soft Soils: Simulation Approach a040190580 v3300394nas a2200157 4500000000100000000000100001008004100002100001200043700001600055700001500071700001700086700002600103245008500129300001400214490000800228 2019 d1 aYue Pan1 aLimao Zhang1 aXianguo Wu1 aKainan Zhang1 aMirosław Skibniewski00aStructural health monitoring and assessment using wavelet packet energy spectrum a652–6650 v12002014nas a2200157 4500000000100000000000100001008004100002260000900043100001200052700001600064700002600080245007800106856006300184490000700247520160200254 2020 d c20201 aYue Pan1 aLimao Zhang1 aMirosław Skibniewski00aClustering of designers based on building information modeling event logs uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/mice.125510 v353 a

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.

02477nas a2200193 4500000000100000000000100001008004100002100001900043700001500062700001900077700001800096700002600114245010300140856007100243300001100314490000700325520193700332022001402269 2020 d1 aZhen-Song Chen1 aXuan Zhang1 aWitold Pedrycz1 aXian-Jia Wang1 aMirosław Skibniewski00aBid evaluation in civil construction under uncertainty: A two-stage LSP-ELECTRE III-based approach uhttp://www.sciencedirect.com/science/article/pii/S0952197620302025 a1038350 v943 a

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.

 a0952-197600361nas a2200133 4500000000100000000000100001008004100002100001200043700002600055700001600081700001400097700001900111245009700130 2020 d1 aHui Liu1 aMirosław Skibniewski1 aQianqian Ju1 aJunjie Li1 aHongbing Jiang00aBIM-enabled construction innovation through collaboration: a mixed-methods systematic review01848nas a2200157 4500000000100000000000100001008004100002100001700043700001800060700001300078700002600091700001400117245011300131300001100244520143500255 2020 d1 aXiaer Xiahou1 aJingfeng Yuan1 aHong Xie1 aMirosław Skibniewski1 aQiming Li00aExploring driving factors of smart city development under the physical-human society-cyber (PHC) space model a1–113 a

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.

01956nas a2200193 4500000000100000000000100001008004100002260000800043100001400051700001800065700001600083700002600099245010000125856004600225300000900271490000700280520146100287022001401748 2020 d coct1 aXijun Yao1 aHsi-Hsien Wei1 aIgal Shohet1 aMirosław Skibniewski00aAssessment of Terrorism Risk to Critical Infrastructures: The Case of a Power-Supply Substation uhttps://www.mdpi.com/2076-3417/10/20/7162 a71620 v103 a

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.

 a2076-341700431nas a2200169 4500000000100000000000100001008004100002100001400043700001800057700001300075700001300088700001400101700002600115245009900141300001400240490000700254 2020 d1 aLei Zhang1 aJingfeng Yuan1 aNini Xia1 aYan Ning1 aJunwei Ma1 aMirosław Skibniewski00aMeasuring value-added-oriented BIM climate in construction projects: dimensions and indicators a800–8180 v2601615nam a2200181 4500000000100000000000100001008004100002260001300043100001600056700001200072700001500084700002600099245007100125300001200196490000800208520119500216020002201411 2021 d bSpringer1 aLimao Zhang1 aYue Pan1 aXianguo Wu1 aMirosław Skibniewski00aArtificial Intelligence in Construction Engineering and Management aXI, 2630 v1633 a

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.

 a978-981-16-2842-900258nas a2200109 4500000000100000000000100001008004100002100001200043700002600055245006000081490000700141 2021 d1 aMing Hu1 aMirosław Skibniewski00aGreen Building Construction Cost Surcharge: An Overview0 v2700391nas a2200145 4500000000100000000000100001008004100002100001200043700001600055700001700071700001300088700002600101245011100127490000700238 2021 d1 aYue Pan1 aLimao Zhang1 aZhenzhen Yan1 aMay Lwin1 aMirosław Skibniewski00aDiscovering optimal strategies for mitigating COVID-19 spread using machine learning: Experience from Asia0 v7502424nas a2200193 4500000000100000000000100001008004100002100001900043700001700062700001900079700001200098700001900110700002000129700001900149700002600168245011200194490001600306520190800322 2021 d1 aZhen-Song Chen1 aLan-Lan Yang1 aKwai-Sang Chin1 aYi Yang1 aWitold Pedrycz1 aJian-Peng Chang1 aLuis Martínez1 aMirosław Skibniewski00aSustainable building material selection: An integrated multi-criteria large group decision making framework0 v113, Part A3 a

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.

00470nas a2200157 4500000000100000000000100001008004100002100001400043700001700057700001900074700002600093700001900119700001800138700001900156245013700175 2021 d1 aAli Khoso1 aAminah Yusof1 aZhen-Song Chen1 aMirosław Skibniewski1 aKwai-Sang Chin1 aShabir Khahro1 aSamiullah Sohu00aComprehensive analysis of state-of-the-art contractor selection models in construction environment-A critical review and future call00313nas a2200121 4500000000100000000000100001008004100002100002400043700002600067700001800093245007200111490000800183 2021 d1 aSvetlana Besklubova1 aMirosław Skibniewski1 aXueqing Zhang00aFactors Affecting 3D Printing Technology Adaptation in Construction0 v14700273nas a2200097 4500000000100000000000100001008004100002100001200043700002600055245009400081 2021 d1 aMing Hu1 aMirosław Skibniewski00aA Review of Building Construction Cost Research: Current Status, Gaps and Green Buildings00451nas a2200157 4500000000100000000000100001008004100002100001500043700001000058700001500068700002300083700002300106700002600129245013000155490000800285 2021 d1 aXuhui Cong1 aLi Ma1 aLiang Wang1 aJonas Šaparauskas1 aJarosław Górecki1 aMirosław Skibniewski00aThe early warning system for determining the “not in My Back Yard” of heavy pollution projects based on public perception0 v28200405nas a2200133 4500000000100000000000100001008004100002100001800043700001500061700002600076700001700102245014500119490000700264 2021 d1 aMuhammad Khan1 aNuman Khan1 aMirosław Skibniewski1 aChansik Park00aEnvironmental Particulate Matter (PM) Exposure Assessment of Construction Activities Using Low-Cost PM Sensor and Latin Hypercubic Technique0 v1300364nas a2200133 4500000000100000000000100001008004100002100001900043700001800062700001600080700002600096245010100122490000700223 2021 d1 aHan-Tang Huang1 aH Ping Tserng1 aRuei-Yu Hou1 aMirosław Skibniewski00aWireless Sensor Network-Based Monitoring of Bridge Pile Foundations for Detecting Scouring Depth0 v2902021nas a2200145 4500000000100000000000100001008004100002100001100043700001300054700001300067700002600080245011900106490000700225520164300232 2022 d1 aY. Pan1 aL. Zhang1 aJ. Unwin1 aMirosław Skibniewski00aDiscovering spatial-temporal patterns via complex networks in investigating COVID-19 pandemic in the United States0 v773 a

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.

00434nas a2200169 4500000000100000000000100001008004100002260000800043100001200051700001600063700001200079700001300091700002600104700001600130245010900146490000900255 2022 d cjan1 aHui Liu1 aQianqian Ju1 aNa Zhao1 aHujun Li1 aMirosław Skibniewski1 aHanliang Fu00aValue Proposition for Enabling Construction Project Innovation by Applying Building Information Modeling0 v202201829nas a2200205 4500000000100000000000100001008004100002260001500043100001300058700001800071700001900089700001600108700001800124700002000142700001600162700002600178245006400204520134100268022001401609 2023 d c01/08/20231 aYang Liu1 aXian-Jia Wang1 aZhen-Song Chen1 aYifei Zhang1 aShenghao Zhao1 aMuhammet Devici1 aLeSheng Jin1 aMirosław Skibniewski00aEvaluating Digital Health Services Quality via Social Media3 a

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.

 a0018-939100397nas a2200133 4500000000100000000000100001008004100002100002400043700001700067700001900084700002600103245012500129490000900254 2018 d1 aPrzemysław Sekuła1 aZachary Laan1 aKaveh Sadabadi1 aMirosław Skibniewski00aPredicting work zone collision probabilities via clustering: application in optimal deployment of highway response teams0 v201801523nas a2200181 4500000000100000000000100001008004100002260001200043100002000055700002000075700002000095700002200115700002600137245009200163856007700255490001200332520099700344 2023 d c10/20231 aBartosz Wójcik1 aMateusz Żarski1 aKamil Książek1 aJaroslaw Miszczak1 aMirosław Skibniewski00aA deep learning method for hard-hat-wearing detection based on head center localization uhttps://journals.pan.pl/dlibra/publication/147340/edition/128931/content0 v71 (EA)3 a

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.

02304nas a2200169 4500000000100000000000100001008004100002260001200043100001900055700001900074700001600093700001900109700002600128245012500154490000800279520184700287 2024 d c03/20241 aZhen-Song Chen1 aChong-Ze Liang1 aYa-Qiang Xu1 aWitold Pedrycz1 aMirosław Skibniewski00aDynamic collective opinion generation framework for digital transformation barrier analysis in the construction industry0 v1033 a

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.

02667nas a2200181 4500000000100000000000100001008004100002260001200043100001900055700001800074700002000092700001700112700001900129700002600148245014600174490000800320520215700328 2024 d c02/20241 aZhen-Song Chen1 aZhuo-Ran Wang1 aMuhammet Deveci1 aWeiping Ding1 aWitold Pedrycz1 aMirosław Skibniewski00aOptimization-based probabilistic decision support for assessing building information modelling (BIM) maturity considering multiple objectives0 v1023 a

The phase of operation and maintenance (O&M) is the most time-consuming and cost-intensive stage in the project life cycle. However, the potential benefits of Building Information Modeling (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&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 probabilistic context 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 Sewage Treatment Plant as a practical case to illustrate the effectiveness and feasibility of the proposed BIM MAM.

02077nas a2200169 4500000000100000000000100001008004100002260001200043100001900055700001700074700001600091700001900107700002600126245010200152490000700254520164600261 2024 d c01/20241 aZhen-Song Chen1 aKou-Dan Chen1 aYa-Qiang Xu1 aWitold Pedrycz1 aMirosław Skibniewski00aMultiobjective optimization-based decision support for building digital twin maturity measurement0 v593 a

The digital twin (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 multiobjective optimization 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.

02313nas a2200205 4500000000100000000000100001008004100002260001200043100001900055700001300074700001600087700001700103700002000120700002000140700001800160700002600178245013600204490000600340520176100346 2023 d c12/20231 aZhen-Song Chen1 aJia Zhou1 aChen-Ye Zhu1 aZhu-Jun Wang1 aSheng-Hua Xiong1 aRosa Rodríguez1 aLuis Martinez1 aMirosław Skibniewski00aPrioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework0 v93 a

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.

01595nas a2200193 4500000000100000000000100001008004100002260001200043100001600055700001300071700002600084700001500110700001500125700002300140700001400163245008000177490000800257520113600265 2023 d c11/20231 aHuanbao Liu1 aZihan Li1 aMirosław Skibniewski1 aLiang Wang1 aXuhui Cong1 aJarosław Górecki1 aWenyu Jin00aMolding quality control with nonlinear forming method in 3D cement printing0 v2353 a

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.

01984nas a2200169 4500000000100000000000100001008004100002260001200043100001200055700001900067700001200086700001800098700002600116245012600142490000800268520153800276 2023 d c11/20231 aLu Xiao1 aZhen-Song Chen1 aRui Hou1 aAbbas Mardani1 aMirosław Skibniewski00aGreenness-based subsidy and dual credit policy to promote new energy vehicles considering consumers' low-carbon awareness0 v1853 a

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.

02638nas a2200181 4500000000100000000000100001008004100002260001200043100001900055700001500074700001800089700001700107700002000124700002600144245011700170490000800287520216100295 2023 d c11/20231 aZhen-Song Chen1 aJing-Yi Lu1 aJiang-Tao Wen1 aXianjia Wang1 aMuhammet Deveci1 aMirosław Skibniewski00aBIM-enabled decision optimization analysis for architectural glass material selection considering sustainability0 v6473 a

The careful consideration and choice of Sustainable Architectural Glass Material (SAGM) is a crucial step towards reducing energy consumption 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 Building Information Modeling 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 thermal insulation 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 building materials.

02887nas a2200205 4500000000100000000000100001008004100002260001200043100001500055700001500070700001300085700001400098700001500112700002300127700002300150700002600173245017500199490001200374520229500386 2023 d c10/20231 aXuhui Cong1 aZhipeng Qi1 aSai Wang1 aPeikun Su1 aLiang Wang1 aJonas Šaparauskas1 aJarosław Górecki1 aMirosław Skibniewski00aEcological Welfare Performance Evaluation and Spatial–Temporal Difference Evolution of Blue Economic Zones: A Case Study of the Blue Economic Zone of Shandong Peninsula0 v12 (10)3 a

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 data envelopment analysis (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 autocorrelation 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 > response > impact > driving force > 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, sewage treatment 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.

02529nas a2200181 4500000000100000000000100001008004100002260001200043100001700055700001900072700001100091700001200102700002000114700002600134245010200160490000900262520207600271 2023 d c12/20231 aZhu-Jun Wang1 aZhen-Song Chen1 aQin Su1 aLu Xiao1 aKannan Govindan1 aMirosław Skibniewski00aBlockchain adoption in sustainable supply chains for Industry 5.0: A multistakeholder perspective0 v8(4)3 a

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 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 expertise-based group decision-making approach is used to quantify 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.

02025nas a2200205 4500000000100000000000100001008004100002260001200043100001500055700001400070700001500084700001300099700001500112700002300127700002300150700002600173245015400199490001000353520145600363 2023 d c10/20231 aXuhui Cong1 aPeikun Su1 aLiang Wang1 aSai Wang1 aZhipeng Qi1 aJonas Šaparauskas1 aJarosław Górecki1 aMirosław Skibniewski00aMeasuring the Construction Efficiency of Zero-Waste City Clusters Based on an Undesirable Super-Efficiency Model and Kernel Density Estimation Method0 v11(9)3 a

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.

02427nas a2200181 4500000000100000000000100001008004100002260001200043100001900055700001600074700001700090700002300107700002700130700002600157245009000183490001000273520196200283 2023 d c09/20231 aZhen-Song Chen1 aZhengze Zhu1 aXianjia Wang1 aFrancisco Chiclana1 aEnrique Herrera-Viedma1 aMirosław Skibniewski00aMultiobjective Optimization-Based Collective Opinion Generation With Fairness Concern0 v59(9)3 a

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.

02502nas a2200205 4500000000100000000000100001008004100002260001200043100001500055700001300070700001700083700001200100700001200112700001900124700001300143700002600156245013500182490000800317520197100325 2023 d c06/20231 aXianguo Wu1 aYuan Cao1 aWeicheng Liu1 aYabo He1 aGang Xu1 aZhen-Song Chen1 aYang Liu1 aMirosław Skibniewski00aBIM-driven building greenness evaluation system: An integrated perspective drawn from model data and collective experts' judgments0 v4063 a

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.

01940nas a2200181 4500000000100000000000100001008004100002260001200043100002000055700001600075700001900091700002000110700002300130700002600153245011800179490000800297520145300305 2023 d c03/20231 aSheng-Hua Xiong1 aChen-Ye Zhu1 aZhen-Song Chen1 aMuhammet Deveci1 aFrancisco Chiclana1 aMirosław Skibniewski00aOn extended power geometric operator for proportional hesitant fuzzy linguistic large-scale group decision-making0 v6323 a

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.

01827nas a2200205 4500000000100000000000100001008004100002260001200043100001600055700001300071700001700084700001300101700001400114700002600128700001900154700001300173245007100186490000800257520135600265 2023 d c06/20231 aHongyu Chen1 aXinyi Li1 aZongbao Feng1 aLei Wang1 aYawei Qin1 aMirosław Skibniewski1 aZhen-Song Chen1 aYang Liu00aShield attitude prediction based on Bayesian-LGBM machine learning0 v6323 a

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.

03199nas a2200169 4500000000100000000000100001008004100002260001200043100001300055700001200068700002600080700001300106700001500119245014700134490000800281520274000289 2023 d c05/20231 aPing Xie1 aKe Chen1 aMirosław Skibniewski1 aJun Wang1 aHanbin Luo00aParametric geological model update and probabilistic analysis of shield tunnel excavation: A borehole-based conditional random fields approach0 v1573 a

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 probabilistic safety assessment (PSA) frameworks that consider the uncertainties of soil properties have encountered limitations in engineering practice due to the complexity of conditional random field (CRF) theory and the operability of numerical modeling. Based on the digitization of the underground infrastructure, this study implements the object-oriented parametric modeling (PM) to address these limitations. A PM-CRF engine is first developed to automate the process of parametric geological modeling 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 tunnel design schemes by considering the uncertainties of soil properties.

01892nas a2200169 4500000000100000000000100001008004100002260001200043100001500055700001300070700001500083700001500098700002600113245011300139490001000252520146000262 2023 d c04/20231 aXuhui Cong1 aSai Wang1 aLiang Wang1 aZhipeng Qi1 aMirosław Skibniewski00aNew smart city clusters’ construction level evaluation under economic circles: the case of Shandong, China0 v29(3)3 a

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.

01925nas a2200181 4500000000100000000000100001008004100002260001200043100001600055700001500071700001400086700001900100700001700119700002600136245007900162490001000241520149200251 2023 d c05/20231 aOmar Daboun1 aNur Abidin1 aAli Khoso1 aZhen-Song Chen1 aAminah Yusof1 aMirosław Skibniewski00aEffect of relationship management on construction project success delivery0 v29(5)3 a

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.

01581nas a2200157 4500000000100000000000100001008004100002260001200043100001900055700001900074700001200093700002000105700002600125245009500151520117700246 2023 d c02/20231 aTong-Yuan Wang1 aZhen-Song Chen1 aPeng He1 aKannan Govindan1 aMirosław Skibniewski00aAlliance strategy in an online retailing supply chain: Motivation, choice, and equilibrium3 a

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.

02288nas a2200193 4500000000100000000000100001008004100002260001200043100002000055700001900075700001700094700001600111700001900127700001800146700002600164245014300190490001000333520175100343 2023 d c02/20231 aJian-Peng Chang1 aZhen-Song Chen1 aZhu-Jun Wang1 aLeSheng Jin1 aWitold Pedrycz1 aLuis Martinez1 aMirosław Skibniewski00aAssessing Spatial Synergy Between Integrated Urban Rail Transit System and Urban Form: A BULI-Based MCLSGA Model With the Wisdom of Crowds0 v31(2)3 a

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.

02504nas a2200169 4500000000100000000000100001008004100002260001200043100001700055700001500072700001300087700001600100700002600116245017900142490000800321520200500329 2023 d c11/20231 aZongbao Feng1 aWeiya Chen1 aYang Liu1 aHongyu Chen1 aMirosław Skibniewski00aLong-term equilibrium relationship analysis and energy-saving measures of metro energy consumption and its influencing factors based on cointegration theory and an ARDL model0 v2633 a

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.

01799nas a2200193 4500000000100000000000100001008004100002260001200043100001300055700001700068700001900085700001600104700001800120700002000138700001600158700002600174245006400200520134100264 2023 d c07/20231 aYang Liu1 aXianjia Wang1 aZhen-Song Chen1 aYifei Zhang1 aShenghao Zhao1 aMuhammet Deveci1 aLeSheng Jin1 aMirosław Skibniewski00aEvaluating Digital Health Services Quality via Social Media3 a

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.

03301nas a2200181 4500000000100000000000100001008004100002260001200043100002000055700001900075700001700094700001800111700001900129700002600148245015100174490000800325520278600333 2023 d c01/20231 aJian-Peng Chang1 aZhen-Song Chen1 aXianjia Wang1 aLuis Martinez1 aWitold Pedrycz1 aMirosław Skibniewski00aRequirement-driven sustainable supplier selection: Creating an integrated perspective with stakeholders' interests and the wisdom of expert crowds0 v1753 a

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.

01814nas a2200169 4500000000100000000000100001008004100002260001200043100002000055700001800075700001200093700002600105700001900131245009600150490000800246520139000254 2024 d c04.20241 aSheng-Hua Xiong1 aZhi-Peng Wang1 aGang Li1 aMirosław Skibniewski1 aZhen-Song Chen00aPrediction of airport runway settlement using an integrated SBAS-InSAR and BP-EnKF approach0 v6653 a

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%.

01983nas a2200133 4500000000100000008004100001653010900042100001500151700001700166700001100183700002600194245009000220520153900310 2026 d10aHuman–robot collaboration; Construction robots; Psychophysiological signals; Human–robot interaction1 aSaika Wong1 aZhentao Chen1 aMi Pan1 aMirosław Skibniewski00aExploring psychophysiological methods for human–robot collaboration in construction3 a

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.

01476nas a2200145 4500000000100000008004100001100002000042700001600062700001900078700001400097700001900111700002600130245008800156520108600244 2025 d1 aSheng-Hua Xiong1 aXi-Hang Wei1 aZhen-Song Chen1 aHao Zhang1 aWitold Pedrycz1 aMirosław Skibniewski00aIdentifying causes of aviation safety events using wW2V-tCNN with data augmentation3 a

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

01664nas a2200133 4500000000100000008004100001100001900042700001200061700001300073700001600086700002600102245014400128520125800272 2025 d1 aZhen-Song Chen1 aYue Tan1 aZheng Ma1 aZhengze Zhu1 aMirosław Skibniewski00aUnlocking the potential of quantum computing in prefabricated construction supply chains: Current trends, challenges, and future directions3 a

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.

02151nas a2200157 4500000000100000008004100001100001400042700001800056700001600074700001600090700001500106700001300121700002600134245011200160520172100272 2025 d1 aLei Zhang1 aJingfeng Yuan1 aXianfei Yin1 aTiantian Gu1 aYinghao Lu1 aPing Liu1 aMirosław Skibniewski00aThe emotional equation: how psychosocial support boosts safety practices in the context of construction 5.03 a

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.

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.

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.

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

02177nas a2200133 4500000000100000008004100001100001200042700001600054700001600070700002600086700001800112245014700130520176600277 2025 d1 aHui Liu1 aHanyu Zheng1 aQianqian Ju1 aMirosław Skibniewski1 aMengmeng Wang00aTemporal-Spatial Evolution of BIM-Based Collaborative Innovation Network: Evidence from Patents in China\textquoterights Construction Industry3 a

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.

01559nas a2200109 4500000000100000008004100001100001400042700001600056700002600072245011400098520123700212 2025 d1 aQiong Liu1 aLimao Zhang1 aMirosław Skibniewski00aNetwork extension planning towards resilient urban critical infrastructures using deep reinforcement learning3 a

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.

01492nas a2200157 4500000000100000008004100001100001500042700001500057700001700072700001400089700001800103700002600121700001800147245009800165520107100263 2025 d1 aYashuai Li1 aWubin Wang1 aJichang Zhao1 aYang Yang1 aZhaohui Zhang1 aMirosław Skibniewski1 aJingfeng Yuan00aEstimating demolition waste from residential interior photos: A Large Language Model solution3 a

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.

02449nas a2200133 4500000000100000008004100001100001600042700001600058700002600074700001300100700001300113245012600126520206300252 2025 d1 aHongyu Chen1 aQiping Shen1 aMirosław Skibniewski1 aYuan Cao1 aYang Liu00aDynamic prediction and optimization of tunneling parameters with high reliability based on a hybrid intelligent algorithm3 a

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.

01769nas a2200121 4500000000100000008004100001100002000042700001800062700001800080700002600098245007400124520144900198 2025 d1 aATaha Demirbağ1 aHande Aladağ1 aZeynep Işık1 aMirosław Skibniewski00aCircular Economy-Based Decision-Making Model for Contractor Selection3 a

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.

02473nas a2200157 4500000000100000008004100001100001500042700001700057700001400074700001700088700001600105700001800121700002600139245008600165520206400251 2025 d1 aXudong Fan1 aYishuo Jiang1 aRay Zhong1 aFabio Duarte1 aWaishan Qiu1 aJürgen Hackl1 aMirosław Skibniewski00aAdvancements and potential pitfalls for smart cities and sentient infrastructures3 a

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

00542nas a2200157 4500000000100000008004100001100001500042700001500057700001500072700001900087700001200106700002200118700002500140700002600165245019300191 2025 d1 aBocong Liu1 aXuhui Cong1 aLiang Wang1 aShenghui Zhang1 aHao Liu1 aJonas Saparauskas1 aLeonas Ustinovichius1 aMirosław Skibniewski00aSpatial-temporal evolution and influencing factors of the coupling coordination degree between new infrastructure construction and high-quality development in urban agglomerations in China01489nas a2200133 4500000000100000008004100001100001700042700001600059700001600075700001700091700002600108245013000134520109100264 2026 d1 aZhenzhao Xia1 aBotao Zhong1 aShuai Zhang1 aTonghui Zhao1 aMirosław Skibniewski00aGraph-driven embedding reinforcement and traceable LLM agent for reliable element alignment in construction report generation3 a

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.

02071nas a2200181 4500000000100000008004100001653002400042653001600066653001900082653000800101100001800109700001500127700001600142700001500158700002600173245010600199520158400305 2026 d10aSemantic enrichment10aMEP systems10aGraph matching10aBIM1 aZhuohao Zhang1 aWeiya Chen1 aJianhua Cai1 aHanbin Luo1 aMirosław Skibniewski00aHierarchical system decomposition and semantic enrichment of BIM for lifecycle support of MEP systems3 a

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.

00208nas a2200085 4500000000100000000000100001008004100002100002400043245005500067 2013 d1 aPrzemysław Sekuła00aKolejowe przewozy regionalne–wyzwania i problemy00237nas a2200097 4500000000100000000000100001008004100002100002400043245006500067490000700132 2014 d1 aPrzemysław Sekuła00aZarządzanie programami według Program Management Institute0 v1200252nas a2200097 4500000000100000000000100001008004100002100002400043700001100067245007600078 2015 d1 aPrzemysław Sekuła1 aothers00aBudżet zadaniowy jako skuteczne narzędzie zarządzania w samorządzie00382nas a2200121 4500000000100000000000100001008004100002100002300043700002900066700001800095700002400113245012300137 2016 d1 aHenryk Brandenburg1 aKatarzyna Ficek-Wojciuch1 aMarek Magdoń1 aPrzemysław Sekuła00aInteresariusze projektów publicznych–sukces projektu publicznego w ujęciu specjalistów od zarządzania projektami00395nas a2200121 4500000000100000000000100001008004100002100002300043700002900066700001800095700002400113245013600137 2016 d1 aHenryk Brandenburg1 aKatarzyna Ficek-Wojciuch1 aMarek Magdoń1 aPrzemysław Sekuła00aProjekt badawczy pt" Sukces projektu publicznego i jego uwarunkowania"-wyniki studiów literaturowych i program realizacji projektu00352nas a2200133 4500000000100000000000100001008004100002100002400043700002300067700001800090700002900108245007400137490000700211 2016 d1 aPrzemysław Sekuła1 aHenryk Brandenburg1 aMarek Magdoń1 aKatarzyna Ficek-Wojciuch00aMulticriteria evaluation methods in location of touristic investments0 v5000340nas a2200133 4500000000100000000000100001008004100002100001100043700001800054700001900072700002400091700001800115245007300133 2018 d1 aYi Hou1 aStanley Young1 aKaveh Sadabadi1 aPrzemysław Sekuła1 aDenise Markow00aEstimating highway volumes using vehicle probe data-proof of concept00381nas a2200133 4500000000100000000000100001008004100002100002400043700002100067700001700088700001900105245011600124490000700240 2018 d1 aPrzemysław Sekuła1 aNikola Marković1 aZachary Laan1 aKaveh Sadabadi00aEstimating historical hourly traffic volumes via machine learning and vehicle probe data: A Maryland case study0 v9700434nas a2200145 4500000000100000000000100001008004100002100002100043700002400064700001700088700002200105700002200127245013200149490000700281 2018 d1 aNikola Marković1 aPrzemysław Sekuła1 aZachary Laan1 aGennady Andrienko1 aNatalia Andrienko00aApplications of trajectory data from the perspective of a road transportation agency: Literature review and maryland case study0 v2000397nas a2200157 4500000000100000000000100001008004100002100001400043700001800057700001600075700002400091700001500115700001500130245008600145490000800231 2019 d1 aYing Zhou1 aChenshuang Li1 aLieyun Ding1 aPrzemysław Sekuła1 aPeter Love1 aCheng Zhou00aCombining association rules mining with complex networks to monitor coupled risks0 v18600337nas a2200121 4500000000100000000000100001008004100002100002400043700002100067700001700088700001900105245009100124 2018 d1 aPrzemysław Sekuła1 aNikola Marković1 aZachary Laan1 aKaveh Sadabadi00aApplication of Vehicle Probe Data in Estimating Traffic Volumes: a Maryland Case Study00389nas a2200133 4500000000100000000000100001008004100002100001800043700002400061700001800085700001700103245012600120490000900246 2020 d1 aSara Zahedian1 aPrzemysław Sekuła1 aAmir Nohekhan1 aZachary Laan00aEstimating hourly traffic volumes using artificial neural network with additional inputs from automatic traffic recorders0 v267400396nas a2200157 4500000000100000000000100001008004100002100001500043700001300058700001600071700002400087700001400111700001600125245008900141490000800230 2020 d1 aCheng Zhou1 aBin Tang1 aLieyun Ding1 aPrzemysław Sekuła1 aYing Zhou1 aZekun Zhang00aDesign and automated assembly of Planetary LEGO Brick for lunar in-situ construction0 v11800318nas a2200133 4500000000100000000000100001008004100002100001300043700001400056700002400070700001600094245006800110490000600178 2021 d1 aYayin Xu1 aYing Zhou1 aPrzemysław Sekuła1 aLieyun Ding00aMachine learning in construction: From shallow to deep learning0 v600425nas a2200145 4500000000100000000000100001008004100002100002400043700001700067700001900084700002000103700001800123245012900141490000900270 2021 d1 aPrzemysław Sekuła1 aZachary Laan1 aKaveh Sadabadi1 aKrzysztof Kania1 aSara Zahedian00aTransferability of a Machine Learning-Based Model of Hourly Traffic Volume Estimation—Florida and New Hampshire Case Study0 v202100401nas a2200157 4500000000100000000000100001008004100002260001000043100001500053700001800068700001900086700001700105700001900122700002400141245007800165 2019 d bITSWC1 aMark Franz1 aStanley Young1 aStephen Remias1 aMichael Pack1 aKaveh Sadabadi1 aPrzemysław Sekuła00aAutomated Traffic Signal Performance Measures Using Emerging Data Sources00231nas a2200085 4500000000100000000000100001008004100002100002400043245007800067 2022 d1 aPrzemysław Sekuła00aSzacowanie natężenia ruchu drogowego z wykorzystaniem sieci neuronowych00232nas a2200097 4500000000100000000000100001008004100002100002400043700001100067245005600078 2016 d1 aPrzemysław Sekuła1 aothers00aWpływ autostrad na rozwój lokalny–wyniki badań00340nas a2200133 4500000000100000000000100001008004100002100001100043700001800054700001900072700002400091700001800115245007300133 2018 d1 aYi Hou1 aStanley Young1 aKaveh Sadabadi1 aPrzemysław Sekuła1 aDenise Markow00aEstimating highway volumes using vehicle probe data-proof of concept00397nas a2200157 4500000000100000000000100001008004100002100001400043700001800057700001600075700002400091700001500115700001500130245008600145490000800231 2019 d1 aYing Zhou1 aChenshuang Li1 aLieyun Ding1 aPrzemysław Sekuła1 aPeter Love1 aCheng Zhou00aCombining association rules mining with complex networks to monitor coupled risks0 v18600337nas a2200121 4500000000100000000000100001008004100002100002400043700002100067700001700088700001900105245009100124 2018 d1 aPrzemysław Sekuła1 aNikola Marković1 aZachary Laan1 aKaveh Sadabadi00aApplication of Vehicle Probe Data in Estimating Traffic Volumes: a Maryland Case Study00396nas a2200157 4500000000100000000000100001008004100002100001500043700001300058700001600071700002400087700001400111700001600125245008900141490000800230 2020 d1 aCheng Zhou1 aBin Tang1 aLieyun Ding1 aPrzemysław Sekuła1 aYing Zhou1 aZekun Zhang00aDesign and automated assembly of Planetary LEGO Brick for lunar in-situ construction0 v11800318nas a2200133 4500000000100000000000100001008004100002100001300043700001400056700002400070700001600094245006800110490000600178 2021 d1 aYayin Xu1 aYing Zhou1 aPrzemysław Sekuła1 aLieyun Ding00aMachine learning in construction: From shallow to deep learning0 v600317nas a2200121 4500000000100000000000100001008004100002100001800043700002000061700001500081700002400096245007500120 2018 d1 aMasoud Hamedi1 aSepideh Eshragh1 aMark Franz1 aPrzemysław Sekuła00aAnalyzing impact of I-85 bridge collapse on regional travel in Atlanta00429nas a2200157 4500000000100000000000100001008004100002100001200043700001200055700002400067700001200091700001000103245011200113856004000225490000600265 2024 d1 aC. Zhou1 aR. Chen1 aPrzemysław Sekuła1 aB. Tang1 aY. Qu00aHuman–machine interaction controlling system for teleoperation of robotic arms in prefabrication assembly uhttps://doi.org/10.55092/sc202400050 v100416nas a2200157 4500000000100000000000100001008004100002260001200043100001800055700001500073700001800088700002400106700001700130700002100147245009000168 2025 d c11/20251 aSara Zahedian1 aMark Franz1 aDharia Parekh1 aPrzemysław Sekuła1 aMichael Pack1 aCharles Lattimer00aAssessment of the Impact of the Francis Scott Key Bridge Collapse on Regional Traffic00626nas a2200193 4500000000100000008004100001100001800042700002600060700002000086700002400106700002400130700002000154700001800174700002000192700002200212700002100234245017000255490000700425 2026 d1 aJarosław Bis1 aKinga Gościńska-Bis1 aŁukasz Mokrisz1 aMikołaj Jodłowski1 aPrzemysław Sekuła1 aMichał Cholewa1 aKrystian Wita1 aMarta Strugała1 aRyszard Bachowski1 aRadosław Gocoł00aArtificial Intelligence-Enhanced Remote Monitoring After Cardiac Surgery: A Prospective Single-Centre Feasibility Study with Retrospective Wound Image Classification0 v1500470nas a2200145 4500000000100000008004100001100001600042700001500058700001500073700002400088245011900112856007200231490000700303022001400310 2026 d1 aJiajing Liu1 aJianxin Wu1 aHanbin Luo1 aPrzemysław Sekuła00aA knowledge distillation framework for multi-signal-to-noise ratio speech enhancement in construction environments uhttps://www.sciencedirect.com/science/article/pii/S26661659260011580 v26 a2666-165900231nas a2200085 4500000000100000000000100001008004100002100002500043245007700068 2024 d1 aKatarzyna Kołodziej00aAI for the Rescue: Tackling Challenges in Polish Waste Management System01557nas a2200265 4500000000100000000000100001008004100002100001900043700002100062700002200083700002000105700002000125700002100145700002400166700002100190700001600211700002400227700002100251700001800272245007800290856004600368490000700414520085600421022001401277 2025 d1 aPiotr Zawadzki1 aGrzegorz Dziwoki1 aMarcin Kucharczyk1 aJan Machniewski1 aWojciech Sułek1 aJacek Izydorczyk1 aWeronika Izydorczyk1 aPiotr Kłosowski1 aAdam Dustor1 aWojciech Filipowski1 aKrzysztof Paszek1 aAnna Zawadzka00aQuantum Enabled Data Authentication Without Classical Control Interaction uhttps://www.mdpi.com/2079-9292/14/20/40370 v143 a

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.

 a2079-929201539nas a2200109 4500000000100000008004100001100001900042700001800061700002000079245006300099520126700162 2026 d1 aPiotr Zawadzki1 aAnna Zawadzka1 aAlicja Zawadzka00aPolar wiretap coding for practical quantum confidentiality3 a

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.