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Enhancing Building Safety: A Brief Review of Agent-Based Modeling for Fire Evacuation Simulation

Procedia computer science 2025年 257卷 668-675页

作者： Selain K. Kasereka Ortega M. Kabwe Maria W.K. Kinyanta Audrey L. Kasongo Godwill W.K. Ilunga Katya Muhambya Tasho Tashev Kyandoghere Kyamakya Mathematics Statistics and Computer Science Department University of Kinshasa Kinshasa DR. Congo Faculty of English Engineering Studies Technical University of Sofia Sofia Bulgaria ABIL Research Center Kinshasa DR. Congo Faculty of Computer Science Université Nouveaux Horizons Lubumbashi DR Congo Ganpat University Faculty of Computer Application Gujarat India Université Libre des Pays des Grands Lacs Faculty of Sciences and Technology Goma DR Congo Institute of Smart Systems Technologies University of Klagenfurt Klagenfurt Austria Polytechnic Faculty University of Kinshasa Kinshasa Democratic Republic of the Congo

The issue of building evacuation in the event of a fire is a significant concern in urban planning and architecture. In the absence of appropriate measures, an emergency situation can potentially result in disastrous outcomes. In this review article, we explore the application of agent-based modeling (ABM) in the simulation of building evacuations in the event of a free breakout. To address this issue, we present a synthesis of findings from several studies, highlighting the advantages of ABM in modeling complex evacuation dynamics such as crowd behavior, consideration of multiple parameters, and decision-making processes. Additionally, we provide insight into the simulation tools and techniques used in studies that demonstrate the practical applications of ABM in enhancing evacuation strategies. Furthermore, we identify current challenges, research gaps, and propose future directions to enhance the accuracy and effectiveness of fire evacuation modeling and simulations. This study aims to contribute to the improvement of proposed solutions and models for the development of successful, effective, and reliable evacuation plans to enhance the safety of occupants in buildings.

关键词： Agent-based Modeling Evacuation Fire Breakout Building Safety Disaster Agent-Based Simulation

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Exploring an InGaN Micro-LED structure for optimum IQE operating on low current condition through simulation study

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International Journal of Modern Physics B 2025年第6期39卷

作者： Hung, Wen-Ching Chang, Sheng-Po Chang, Shoou-Jinn Kuo, Hao-Chung Chen, Jyh-Chen Department of Mechanical Engineering National Central University Jhongli City32001 Taiwan Department of Microelectronics Engineering National Kaohsiung University of Science and Technology Kaohsiung City88157 Taiwan Department of Electrical Engineering Institute of Microelectronics National Cheng Kung University No. 1 Ta Hseuh Road Tainan City70101 Taiwan Department of Photonics College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan

Light-emitting diodes (LEDs) are key components in display applications. The quantum efficiency of GaN/InGaN LEDs has been enhanced, leading to advancements in indoor and outdoor RGB LED display applications. White LED backlights are commonly used in displays due to the increased efficiency of InGaN LEDs. Despite efficiency, lifespan and image retention issues, OLED displays are utilized in high-end mobile phones to meet market expectations for screen response time and color saturation. Micro-LED RGB full-color displays have the potential to dominate the next-generation display market, driven by the increasing demands for resolution, power consumption and response time. Micro-LEDs are becoming smaller, reaching sizes of 50μm or even smaller, to meet the high-resolution requirements of displays. They offer higher contrast, brightness and faster response speeds. This research utilizes numerical simulations to develop a model for radiative and nonradiative recombination in InGaN semiconductor materials. The aim is to investigate the internal quantum efficiency (IQE) of various chip sizes, quantum well counts, well thicknesses and electron block layers under low current densities. The research reveals that the optimal structure is a single quantum well with an electron block layer (EBL), which can increase IQE from 53.85% to 80.9% at 0.01A/cm2 under low current density conditions, with a decrease in the number of quantum wells to one. The IQE efficiency improvement is 27.05%. © 2025 World Scientific Publishing Company.

关键词： Light emitting diodes

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Compression Mechanical Behaviour of 7075 Aluminium Matrix Composite Reinforced with Nano-sized SiC Particles in Semisolid State

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Journal of Materials science & technology 2016年第11期32卷 1197-1203页

作者： Jufu Jiang Gang Chen Ying Wang State Key Laboratory of Advanced Processing and Recycling of Non-ferrous Metals Lanzhou University of Technology School of Materials Science and Engineering Harbin Institute of Technology School of Materials Science and Engineering Harbin Institute of Technology at Weihai School of Mechatronics Engineering Harbin Institute of Technology

The 7075 aluminium matrix composite reinforced with nano-sized Si C particles was fabricated by ultrasonic assisted semisolid stirring method. The compression mechanical behaviour of the fabricated composite in semisolid state was investigated. The results show that the microstructure of the composite before semisolid compression consists of fine and spheroidal solid grains surrounded by liquid *** compression led to a nonuniform plastic deformation of solid grains. A slight plastic deformation occurred in the locations near the free surface due to the dependence of deformation on liquid flow and flow of liquid incorporating solid grains. However, obvious plastic deformation occurred in the central location and location contacting to die due to the contribution of plastic deformation of solid *** true stress–strain curve of the sample compressed at 500 °C consists of rapid increase of true stress and steady stage. However, rapid increase of true stress and decrease of true stress and steady stage are involved in the true stress–strain curves of the samples compressed at 550, 560, 570, 580 and 590 °*** true stress–strain curve at 600 °C is similar to that at 500 °C. Apparent viscosity decreases with an increase of shear rate, indicating a shear thinning occurrence. When soaking time increases from 5 min to 15 min, the peak stress and steady stress decrease significantly. A further increase of the soaking time led to a slight change. Peak stress and steady stress increase with increasing volume fraction of Si C particles. A sudden increase or decrease of compression velocity led to a significant increase or decrease of the steady stress. The destruction of the samples compressed at solid state temperature mainly depends on cracks parallel to compression direction. However, the destruction forms of the samples compressed at semisolid temperatures consist of cracks parallel to compression direction and partial collapse. Increasing soaking time led t

关键词： 7075 aluminium matrix composite Nano-sized SiC particles Semisolid compression True stress–strain curve

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Analysis of the mechanism of orientations evolution during hot rolling and mechanical properties of TiBw/TA15 composites based on crystal plasticity finite element model

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Journal of Materials science & technology 2023年第36期167卷 137-151页

作者： Zhenlun Li Qingxin Kang Xiaochong Sui Xunhu Xu Liqiang Zhan Guofeng Wang School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China National Key Laboratory for Precision Hot Processing of Metals Harbin Institute of TechnologyHarbin 150006China School of Architectural Engineering Harbin University of Science&TechnologyHarbin 150080China

An in-depth understanding of the crystal orientation evolution during hot rolling of TiB whisker(TiBw)/TA15 composites and the anisotropy of the as-rolled plates can help fully utilize the material *** this paper,the crystal plasticity finite element models of high-temperature(HT)β-phase and room-temperature(RT)α-phase were constructed from electron backscattering diffraction *** on this,the orientation evolution during hot rolling in the single-phase region and the effects of the matrix texture on the mechanical properties of the as-rolled plates were *** effect of TiBw on the anisotropy was studied by the composites finite element *** showed that theα-fiber texture of theβ-phase was formed during HT *** texture was converted to the T-texture of theα-phase at RT during cooling according to the Burgers orientation *** TiBw had little effect on the matrix texture *** TiBw and matrix texture caused the matrix to have higher strength along the rolling direction and the transverse direction,*** matrix texture dominated the difference in mechanical properties because its effect exceeded that of *** effect of the matrix on the mechanical properties was caused by the Schmid factors(SFs)and the critical resolved shear stress(CRSS)of the slip system *** slip mode was influenced by SFs determined by the angular rela-tionship between the crystal orientation and the loading *** CRSS of the activated slip system determined the yield strength.

关键词： TiBw/TA15 composites Crystal plasticity finite element model Orientation Anisotropic Slip mode

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Optimizing Supply Chain Security Using ACO and Blockchain: Integrating Root of Trust, Unclonable Functions, and SBOM for Cybersecurity

Optimizing Supply Chain Security Using ACO and Blockchain: I...

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Visual Analytics and Data Visualization (ICVADV), International Conference on

作者： L Sherin Beevi Ponsy R K Sathia Bhama J Albert Vijayan Joe Prathap P. M. W Vinil Dani J. Premalatha Department of Computer Science and Engineering R.M.D. Engineering College Kavaraipettai INDIA Department of Computer Technology Madras Institute of Technology Anna University Chromepet Amaala Utilities PPP Larsen & Toubro Limited Soudi Arabia Department of EEE St. Peter's College of Engg.and Tech. Chennai INDIA Department of Artificial Intelligence and Data Science Dhanalakshmi Srinivasan College of Engg. and Tech. Mamallapuram

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Proposed work describes an optimal framework for improving supply chain security and delivery efficiency by combining Ant Colony Optimization (ACO) and blockchain technology. Inconvenient path design is a primary trouble in last-mile delivery, causing delays and wasting resources. This study seeks to address the above issue by optimizing delivery schedules, guaranteeing that many purchasers in the same geographic area are handled by a single delivery person, hence eliminating redundant trips and delivery times. Proposed technique is driven by real-world inefficiencies seen in e-commerce systems, such as the case of two independent things bought to the same address but delivered at different times by different couriers on the same day. ACO is used to find the best delivery route, guaranteeing that all consumers in a particular area receive their items simultaneously. The framework incorporates blockchain technology to improve security, transparency, and traceability during the delivery process. Furthermore, advanced cybersecurity measures such as Root of Trust (RoT), Physically Unclonable Functions (PUFs), and Software Bill of Materials (SBOM) are used to secure data integrity and enable third-party monitoring. By combining ACO for route optimization with blockchain for safe transaction processing, this system not only improves shipping time as well as asset efficiency, but it also protects supply chain cybersecurity. The suggested approach provides a scalable and reliable framework for future smart logistics and e-commerce applications, assuring operational efficiency and security.

关键词： Ant colony optimization Visual analytics Supply chains Bills of materials Physical unclonable function Software Real-time systems Blockchains Electronic commerce Software measurement

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An efficient algorithm for approximate Voronoi diagram construction on triangulated surfaces

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Computational Visual Media 2023年第3期9卷 443-459页

作者： Wenlong Meng Pengbo Bo Xiaodong Zhang Jixiang Hong Shiqing Xin Changhe Tu School of Computer Science and Technology Harbin Institute of TechnologyWeihai 264209China School of Computer Science and Technology Shandong UniversityQingdao 266237China

Voronoi diagrams on triangulated surfaces based on the geodesic metric play a key role in many applications of computer *** methods of constructing such Voronoi diagrams generally depended on having an exact geodesic ***,exact geodesic computation is time-consuming and has high memory usage,limiting wider application of geodesic Voronoi diagrams(GVDs).In order to overcome this issue,instead of using exact methods,we reformulate a graph method based on Steiner point insertion,as an effective way to obtain geodesic ***,since a bisector comprises hyperbolic and line segments,we utilize Apollonius diagrams to encode complicated structures,enabling Voronoi diagrams to encode a medial-axis surface for a dense set of boundary *** on these strategies,we present an approximation algorithm for efficient Voronoi diagram construction on triangulated *** also suggest a measure for evaluating similarity of our results to the exact *** our GVD results are constructed using approximate geodesic distances,we can get GVD results similar to exact results by inserting Steiner points on triangle *** results on many 3D models indicate the improved speed and memory requirements compared to previous leading methods.

关键词： geodesic Voronoi diagrams(GVDs) triangular surfaces mesh surfaces approximate geodesics Apollonius diagrams

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TextAI 3.0 (Multimodal): multimodal sentiment analysis using attention-enabled ensemble-based deep learning in hyperbolic space

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International Journal of Information technology (Singapore) 2025年 1-16页

作者： Singh, Jaskaran Sanga, Prabhav Khanna, Narendra N. Laird, John R. Singh, Inder M. Kalra, Mannudeep K. Mantella, Laura E. Johri, Amer M. Faa, Gavino Tiwari, Ekta Singh, Rajesh Abbas, Mohamed Saba, Luca Suri, Jasjit S. Stroke Monitoring and Diagnostic Division AtheroPoint™ Roseville 95661 CA United States Bharati Vidyapeeth’s College of Engineering New Delhi India Department of Cardiology Indraprastha APOLLO Hospitals New Delhi 110001 India Department of Neurology and Stroke Program University of Maryland School of Medicine Baltimore United States Department of Radiology Harvard Medical School Boston 02115 MA United States Department of Biomedical and Molecular Sciences Queen’s University Kingston ON Canada Division of Cardiology Department of Medicine Queen’s University Kingston ON Canada Department of Pathology University of Cagliari Cagliari Italy Department of Computer Science Visvesvaraya National Institute of Technology (VNIT) Nagpur 440010 India Department of Research and Innovation Uttaranchal Institute of Technology Uttaranchal University Dehradun 248007 India Central Labs King Khalid University P.O. Box 960 AlQura’a Abha Saudi Arabia Electrical Engineering Department College of Engineering King Khalid University Abha 61421 Saudi Arabia Department of Neurology University of Cagliari Cagliari Italy Department of ECE Idaho State University Pocatello 83209 ID United States Department of CE Graphic Era Deemed to Be University Dehradun 248002 India University Center for Research and Development Chandigarh University Mohali India Symbiosis Institute of Technology Symbiosis International (Deemed University) Nagpur Campus Pune India Department of Innovation Global Biomedical Technologies Inc. Roseville 95661 CA United States

The rising prevalence of depression presents a significant global health challenge, underscoring the need for effective early detection through sentiment analysis. Traditional multimodal sentiment analysis methods, which rely on Euclidean space for data representation, often fail to capture the complex hierarchical relationships and non-linear structures inherent in multimodal data. To address this limitation, we propose a novel multimodal architecture that operates in hyperbolic space and incorporates attention-based ensemble learning to enhance feature representation and model performance. We developed and evaluated ten AI models—five utilizing Euclidean space and five leveraging hyperbolic space—on the Spoken Language Understanding Evaluation (SLUE) benchmark dataset. The models were assessed using cross-validation techniques to ensure robustness, and statistical analyses were conducted to validate the findings. Our results indicate that hyperbolic-based multimodal models achieve a 2.32% improvement in accuracy compared to their Euclidean counterparts, while the integration of self-attention mechanisms further contributes an average accuracy gain of 0.96%. Additionally, we observed a 3.76% decline in performance when reducing the training-to-test data ratio from 90:10 to 50:50, highlighting the importance of data distribution in model training. These findings confirm that attention-enhanced multimodal models in hyperbolic space offer superior representations for sentiment analysis. © Bharati Vidyapeeth's institute of computer Applications and Management 2025.

关键词： Attention-enabled Deep learning Euclidean space Hyperbolic space Multimodal Sentiment analysis

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Five-month real-ambient PM_2.5 exposure impairs learning in Brown Norway rats: Insights from multi omics-based analysis

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Ecotoxicology and Environmental Safety 2025年 294卷 118065页

作者： Song, Chenchen Zhou, Li Xiong, Yi Zhao, Lianlian Guo, Jindan Zhang, Ling Han, Yunlin Yang, Hu Xu, Yanfeng Zhao, Wenjie Shan, Shan Sun, Xiuping Zhang, Boxiang Guo, Jianguo State Key Laboratory of Respiratory Health and Multimorbidity NHC Key Laboratory of Human Disease Comparative Medicine Institute of Laboratory Animal Sciences CAMS&PUMC Key Laboratory of Human Diseases Animal Model State Administration of Traditional Chinese Medicine Beijing 100021 China Institute of Environmental Systems Biology Environment Science and Engineering College Dalian Maritime University 116026 China Department of Food Science and Engineering School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin 150001 China

PM2.5, recognized as a potential pathogenic factor for nervous system diseases, remains an area with many unknowns, particularly regarding its effects on human health. After five-month real-ambient PM2.5 exposure, we ... 详细信息

PM_2.5, recognized as a potential pathogenic factor for nervous system diseases, remains an area with many unknowns, particularly regarding its effects on human health. After five-month real-ambient PM_2.5 exposure, we observed no significant pathological damage to the lung, liver, spleen, or kidney tissues. However, PM_2.5 exposure led to neuronal degeneration in the hippocampal CA1 region of Brown Norway (BN) rats. The level of IL-6, IL-13, IL-1β, IL-12, IL-4, GRO/KC, MIP-1α, CM-CSF significantly increased in lung lavage fluid (P < 0.05 for all). Notably, we detected a slight impairment in spatial learning ability, as evidenced by the Barnes maze training outcomes. There were no significant changes in the bacterial community in lung lavage fluid (P = 0.621), but the bacterial community in the gut significantly changed (P < 0.001), with more species identified (P < 0.05). The metabolomic analysis revealed 147 and 149 significantly changed metabolites in the pulmonary system and serum, respectively (P < 0.05). PM_2.5 exposure caused a decrease in Nervonic acid (NA) in both the lung and serum, which likely contributed to spatial learning impairment (P < 0.01). The correlation between lung metabolites, gut bacterial species, and serum metabolites indicated that PM_2.5 exposure likely impaired spatial learning through the lung-gut-brain axis pathway. Lung and serum metabolic disorders and intestinal microbial imbalance occurred in BN rats post-five-month real-ambient PM_2.5 exposure. There were two potential ways that PM_2.5 exposure caused the decline of spatial learning ability in wild-type BN rats: (1) PM_2.5 exposure led to a significant decrease of neuroprotective Nervonic acid in lung and serum metabolites. (2) PM_2.5 exposure likely led to reduced spatial learning ability through the lung-gut-brain axis. © 2025 The Authors

关键词： Inflammation Lung-gut-brain axis microorganism Nervonic acid PM2.5 Spatial learning

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Giant magneto-impedance effect of two paralleled amorphous microwires

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Rare Metals 2016年第4期35卷 344-348页

作者： Shu-Ling Zhang Yue-Sheng Chai Da-Qing Fang Lu-Cai Wang Da-Wei Xing Jian-Fei Sun School of Materials Science and Engineering Taiyuan University of Science and Technology School of Materials Science and Engineering Harbin Institute of Technology

Giant magneto-impedance （GMI） is effectively enhanced by the mutual magnetic interaction between two amorphous microwires. A comparative study on GMI properties of a single wire and two wires arranged in par- allel mode was reported in this work. Two-peak （TP） of impedance characteristic is presented when the dc external field changed from 0 to 320 A,m-＇ in two-wire system, which is attributed to successive magnetization process in two wires induced by their magnetic interaction. And the evolution of single peak to TP phenomenon, when the distance between two wires is upto 8 ram, evidences a distance dependence of transformation from successive magnetization to simultaneous via a corresponding dis- tance dependence of magnetostatic interactions. It is pro- posed that the recombination of magnetic interaction and the shielding effect results in a distance dependency of GMI response. When the distance is 8 ram, the magneti- zation process is close to synchronous between two wires, which give rises to higher circular permeability and better GMI response. The impedance ratio AZ/Z increases from 74.5 % of single wire to 172.4 % at 10 MHz. However, when the distance is upto 12 mm, the magnetic interaction is weak and magnetization process is completely independent, and GMI response decreases, relatively. This indicates that the GMI response could be effectively improved in a two-wire connection with an optical distance, which is promising and useful for the application of high-performance GMI sensors.

关键词： Amorphous microwire Magnetic interaction Giant magneto-impedance Magnetization

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Interpretable inverse iteration mean shift networks for clustering tasks

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Neural Networks 2025年 189卷 107528页

作者： Zhang, Bingjie Yu, Zihan Wang, Jian Żelaszczyk, Maciej Zhang, Yaqian Mańdziuk, Jacek Zhang, Chao Pedrycz, Witold School of Mathematics and Statistics Weifang University Weifang261061 China College of Science Mathematics and Technology Wenzhou-Kean University Wenzhou325060 China Qingdao266580 China Faculty of Mathematics and Information Science Warsaw University of Technology Warsaw Poland Artificial Intelligence Institute University of Waikato Hamilton New Zealand Faculty of Computer Science AGH University of Krakow Cracow Poland School of Mathematical Sciences Dalian University of Technology Dalian116024 China Department of Electrical and Computer Engineering University of Alberta Edmonton ABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Sariyer/Istanbul Turkey

Neural networks have become the standard approach for tasks such as computer vision, machine translation and pattern recognition. While they exhibit significant feature representation capabilities, they often lack interpretability. This suggests that it might be beneficial to explore interpretable machine learning approaches in order to inform the neural network architectures. On the contrary, the mean shift algorithm (MS) has an unambiguous computational process, yet lacking in representation power. In order to draw on the advantages of both neural networks and the mean shift method, we propose the mean shift network (MS-Net) — a novel architecture, which is an inverse iteration fuzzy clustering network. Each layer of the proposed network possesses good interpretability, while the network as a whole is able to produce strong feature representations. To relax the limitations of the kernel function and ensure convergence, we design a continuously-differentiable Gaussian-inspired kernel as the activation function for the membership layer of MS-Net. Furthermore, we devise a weighted version of the architecture, called WMS-Net, to incorporate the importance of the training examples. We present theoretical results, with proofs of weak and strong convergence. We also consider two extensions to the proposed method, CB-MS-Net and CB-WMS-Net, which apply the curvature-based method to MS-Net and WMS-Net. Simulation results on 5 clustering tasks and 6 real-world datasets confirm the effectiveness of the proposed algorithms. © 2025

关键词： Fuzzy neural networks

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