Article
Geosciences, Multidisciplinary
Navid Hooshangi, Ali Asghar Alesheikh, Mahdi Panahi, Saro Lee
Summary: This paper investigates task allocation in urban search and rescue (USAR) operations using an agent-based simulation, proposing a method based on the contract net protocol (CNP) to manage uncertainty through the application of different allocation strategies. Simulations conducted in Tehran demonstrate that considering allocation strategies can significantly improve the efficiency of rescue operations.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2021)
Article
Computer Science, Information Systems
Anna Labetski, Stelios Vitalis, Filip Biljecki, Ken Arroyo Ohori, Jantien Stoter
Summary: Urban morphology plays a crucial role in various fields such as city planning, transportation, climate, energy, and urban data science. Most studies still simplify buildings to their 2D form, but we propose a comprehensive set of 3D metrics to better capture the detailed shape of buildings. We provide an open dataset and a use case to demonstrate the added value of 3D metrics in analyzing architectural patterns.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2023)
Article
Green & Sustainable Science & Technology
Y. Zhou, D. Wilmink, M. Zeman, O. Isabella, H. Ziar
Summary: This study develops a GIS-based large-scale visibility assessment tool to evaluate the visibility of roofs on monumental buildings in urban areas, providing decision-making support for photovoltaic planning. The results show that installing photovoltaic systems on the monumental buildings at TU Delft campus can yield significant electricity generation, depending on the visibility of the photovoltaic modules.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Thermodynamics
Ali Katal, Mohammad Mortezazadeh, Liangzhu (Leon) Wang, Haiyi Yu
Summary: This study presents a new approach for dynamic urban building energy and microclimate modeling using publicly available data sets and tools. By integrating OpenStreetMap, Microsoft, and Google Earth data, 3D city models are generated and building archetype library is created for dynamic integration. Weather station data is used for boundary conditions and validation, providing an effective modeling solution.
Article
Robotics
Gongcheng Wang, Weidong Wang, Pengchao Ding, Yueming Liu, Han Wang, Zhenquan Fan, Hua Bai, Zhu Hongbiao, Zhijiang Du
Summary: This paper proposes a dual-robot system solution for search and rescue in an underground building environment. The two robots focus on different tasks while sharing environmental perception information and location. The system integrates various technologies such as Lidar, inertial measurement unit, multiview cameras, depth camera, and wireless multinode networking to overcome challenges in underground rescue. Experimental results demonstrate the system's high reliability and applicability in over-the-horizon maneuvering, teleoperation, object searching, and environmental perception.
JOURNAL OF FIELD ROBOTICS
(2023)
Article
Management
Pierre Leone, Julia Buwaya, Steve Alpern
Summary: This study introduces a new type of asymmetric rendezvous search problem where one player must give the other a 'gift', which can be in the form of information or material. The research finds optimal agent paths and drop off times using families of linear programs. Applications of this work include solving other forms of rendezvous on a line and determining optimal strategies for different variations of the game.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Review
Construction & Building Technology
Cyrus Ho Hin Wong, Meng Cai, Chao Ren, Ying Huang, Cuiping Liao, Shi Yin
Summary: This paper reviews and compares major methods for simulating building energy use at the urban scale, highlighting differences in strengths, limitations, and applications. It suggests that future development in urban-scale building energy use should explore ways to incorporate spatial variation in weather and morphological conditions, especially in dense urban settings facing greater environmental challenges.
BUILDING AND ENVIRONMENT
(2021)
Article
Urban Studies
Wei Zhu, Chao Yuan
Summary: This study developed a systematic method to assess the urban heat health risk to the aging population in high-density tropical cities. The findings showed that the old HDB neighborhoods in the Central Region of Singapore are at the highest risk.
Article
Chemistry, Multidisciplinary
Athanasios Douklias, Aris Dadoukis, Spyros Athanasiadis, Angelos Amditis
Summary: Despite technological progress, disasters continue to challenge government organizations. Volunteer USAR organizations aim to provide help but face challenges due to limited funding and lack of resources. To address this need, a field deployable communication system leveraging existing infrastructure and wireless connectivity has been designed.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Multidisciplinary
Anastasia Yfantidou, Melpomeni Zoka, Nikolaos Stathopoulos, Martha Kokkalidou, Stella Girtsou, Michail-Christos Tsoutsos, Diofantos Hadjimitsis, Charalampos Kontoes
Summary: This study presents an integrated approach for assessing and managing forest fire risk in peri-urban areas. It combines fire hazard modeling, vulnerability and exposure assessment, and field observations to provide practical solutions for strategic planning and mitigation.
APPLIED SCIENCES-BASEL
(2023)
Article
Construction & Building Technology
Monica C. M. Parlato, Simona M. C. Porto, Francesca Valenti
Summary: Within the circular economy and green deal context, valorizing greasy wool into new resources for insulation building components is an important challenge. The sustainable and innovative alternative uses of this livestock waste can create new opportunities for the sheep farming sector and reduce environmental issues. By using Geographic Information Systems tools, a methodology has been carried out to evaluate the availability and geographical distribution of sheared sheep wool, and it was found that a significant amount of insulation materials can be produced from the re-utilization of sheep wool, taking the first step towards developing a new wool valorization chain.
BUILDING AND ENVIRONMENT
(2022)
Review
Environmental Sciences
Mingyang Lyu, Yibo Zhao, Chao Huang, Hailong Huang
Summary: This article aims to provide readers with an understanding of the latest progress and trends in the field of UAV search and rescue by synthesizing and organizing relevant papers. It discusses the various types and components of UAVs and their importance in SAR operations. The article also reviews the integration of sensors in UAVs for SAR purposes, highlighting their roles in target perception, localization, and identification. Furthermore, it explores the applications of UAVs in SAR, including on-site monitoring and modeling, target perception and localization, and SAR operations such as task assignment, path planning, and collision avoidance. Overall, it presents a comprehensive overview of the significant role of UAVs in enhancing SAR operations and discusses potential avenues for improving their performance.
Article
Computer Science, Artificial Intelligence
Ignacio Martinez-Alpiste, Gelayol Golcarenarenji, Qi Wang, Jose Maria Alcaraz-Calero
Summary: This paper presents a new system for Search and Rescue (SAR) missions using a combination of a UAV and machine-learning-based object detection system on a smartphone. The system achieved a high accuracy of 94.73% and is highly portable, cost-effective, and fast.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Green & Sustainable Science & Technology
Hariklia D. Skilodimou, George D. Bathrellos, Dimitrios E. Alexakis
Summary: This study proposes a simple method to produce a flood hazard assessment map in burned and urban areas with limited data. The study found that the areas with highest flood hazard are in the eastern and southern parts of the study area. The model predictions were robust, and the map was shown to be reliable and accurate, with potential applications in land use planning, disaster mitigation, and post-fire management.
Article
Geosciences, Multidisciplinary
Ziqian Kang, Shuo Wang, Ling Xu, Fenglin Yang, Shushen Zhang
Summary: The study adopted PNN coupled with GIS to assess land use suitability, revealing that the south is suitable for residential land, the north is suitable for ecological reserve, and the central area is suitable for industrial land.
Article
Computer Science, Interdisciplinary Applications
Albert Y. Chen, James C. Chu
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2016)
Article
Transportation Science & Technology
James-C. Chu, Albert Y. Chen, Yu-Fu Lin
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2017)
Article
Emergency Medicine
Wen-Chu Chiang, Ming-Ju Hsieh, Hsin-Lan Chu, Albert Y. Chen, Shin-Yi Wen, Wen-Shuo Yang, Yu-Chun Chien, Yao-Cheng Wang, Bin-Chou Lee, Huei-Chih Wang, Edward Pei-Chuan Huang, Chih-Wei Yang, Jen-Tang Sun, Kah-Meng Chong, Hao-Yang Lin, Shu-Hsien Hsu, Shey-Ying Chen, Matthew Huei-Ming
ANNALS OF EMERGENCY MEDICINE
(2018)
Article
Construction & Building Technology
Cheng-Ta Lee, Yu-Ching Lee, Albert Y. Chen
AUTOMATION IN CONSTRUCTION
(2019)
Article
Transportation Science & Technology
Albert Y. Chen, Yen-Lin Chiu, Meng-Hsiu Hsieh, Po-Wei Lin, Ohay Angah
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2020)
Article
Geosciences, Multidisciplinary
Chun-Chien Hsiao, Min-Ci Sun, Albert Y. Chen, Yu-Ting Hsu
Summary: This study proposes a Shelter-In-Place (SIP) strategy for large-scale evacuations during unpredictable disasters, using optimization models to determine SIP deployment and evacuee assignment. Factors such as spatial risk distribution and multi-class evacuees are considered in optimizing shelter locations.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Computer Science, Interdisciplinary Applications
Wen-Xin Qiu, Jen-Yu Han, Albert Y. Chen
Summary: This research estimated the spatial-temporal distribution of humans in buildings through image sensing, utilizing object detection and tracking models to discover humans in the images. Image depth estimation, clustering, and camera modeling were integrated to associate human and in-building space in image coordinates with real world coordinates, resulting in acquiring temporal human count for each in-building space. The proposed approach achieved results comparable to manual counting.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2021)
Article
Economics
Chang-Chi Chou, Wen-Chu Chiang, Albert Y. Chen
Summary: The study aims to improve the response efficiency of Emergency Medical Service (EMS) by addressing congestion in transportation networks and hospitals. A patient transportation and assignment model is proposed, combining a Cell Transmission Model (CTM) and a nonlinear treatment impedance function. The problem is decomposed into linear and nonlinear sub-problems, which are solved using the simplex algorithm and gradient projection algorithm respectively. The proposed methodology outperforms traditional approaches, as demonstrated in a case study and benchmark testing.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Economics
Yu-Ching Lee, Yu-Shih Chen, Albert Y. Chen
Summary: This study proposes a new stochastic programming model to minimize the Time to Arrive at Hospital (TAH) in pre-hospital emergency medical service. The model takes into account short-term demand estimation and dynamically generates scenarios to achieve near real-time ambulance relocation decisions. The results show that the proposed system has the potential to enhance the performance of pre-hospital EMS.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Health Care Sciences & Services
Kuan-Chen Chin, Yu-Chia Cheng, Jen-Tang Sun, Chih-Yen Ou, Chun-Hua Hu, Ming-Chi Tsai, Matthew Huei-Ming Ma, Wen-Chu Chiang, Albert Y. Chen
Summary: A machine learning-based model, called the PAMT model, was developed to predict severe road accident trauma. The study found that the accuracy of the PAMT model is similar to that of the participating dispatchers, but it may provide higher accuracy when the dispatchers lack confidence in their judgments.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Article
Construction & Building Technology
Ohay Angah, Albert Y. Chen
AUTOMATION IN CONSTRUCTION
(2020)
Article
Construction & Building Technology
Ohay Angah, Albert Y. Chen
AUTOMATION IN CONSTRUCTION
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Shin-Yi Wen, Yu Yen, Albert Y. Chen
ADVANCES IN COMPUTER VISION, VOL 2
(2020)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Chang-Chi Chou, Albert Y. Chen
COMPUTING IN CIVIL ENGINEERING 2017: INFORMATION MODELLING AND DATA ANALYTICS
(2017)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Chun-Hao Chen, Albert Y. Chen
COMPUTING IN CIVIL ENGINEERING 2017: INFORMATION MODELLING AND DATA ANALYTICS
(2017)
Article
Computer Science, Artificial Intelligence
Fangyu Chen, Yongchang Wei, Hongchang Ji, Gangyan Xu
Summary: This paper introduces a dual-layer network analytical framework for evaluating standard systems in construction safety management and validates its effectiveness through a case study. The research findings suggest that key standards often encompass a wider array of risks, providing suggestions for revising construction standards.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Minghao Li, Qiubing Ren, Mingchao Li, Ting Kong, Heng Li, Huijing Tian, Shiyuan Liu
Summary: This study proposes a method using digital twin technology to construct a collision early warning system for marine piling. The system utilizes a five-dimensional model and four independently maintainable development modules to maximize its effectiveness. The pile positioning algorithm and collision early warning algorithm are capable of providing warnings for complex pile groups.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Seokhyun Ryu, Sungjoo Lee
Summary: This study proposes the use of patent information to develop a robust technology tree and applies it to the furniture manufacturing process. Through methods such as clustering analysis, semantic analysis, and association-rule mining, technological attributes and their relationships are extracted and analyzed. This approach provides meaningful information to improve the understanding of a target technology and supports research and development planning.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Shuai Ma, Kechen Song, Menghui Niu, Hongkun Tian, Yanyan Wang, Yunhui Yan
Summary: This paper proposes a feature-based domain disentanglement and randomization (FDDR) framework to improve the generalization of deep models in unseen datasets. The framework successfully addresses the appearance difference issue between training and test images by decomposing the defect image into domain-invariant structural features and domain-specific style features. It also utilizes randomly generated samples for training to further expand the training sample.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Fang Xu, Tianyu Zhou, Hengxu You, Jing Du
Summary: This study explores the impact of AR-based egocentric perspectives on indoor wayfinding performance. The results reveal that participants using the egocentric perspective demonstrate improved efficiency, reduced cognitive load, and enhanced spatial awareness in indoor navigation tasks.
ADVANCED ENGINEERING INFORMATICS
(2024)
Review
Computer Science, Artificial Intelligence
Yujie Lu, Shuo Wang, Sensen Fan, Jiahui Lu, Peixian Li, Pingbo Tang
Summary: Image-based 3D reconstruction plays a crucial role in civil engineering by bridging the gap between physical objects and as-built models. This study provides a comprehensive summary of the field over the past decade, highlighting its interdisciplinary nature and integration of various technologies such as photogrammetry, 3D point cloud analysis, semantic segmentation, and deep learning. The proposed 3D reconstruction knowledge framework outlines the essential elements, use phases, and reconstruction scales, and identifies eight future research directions. This review is valuable for scholars interested in the current state and future trends of image-based 3D reconstruction in civil engineering, particularly in relation to deep learning methods.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hang Zhang, Wenhu Wang, Shusheng Zhang, Yajun Zhang, Jingtao Zhou, Zhen Wang, Bo Huang, Rui Huang
Summary: This paper presents a novel framework for segmenting intersecting machining features using deep reinforcement learning. The framework enhances the effectiveness of intersecting machining feature segmentation by leveraging the robust feature representation, decision-making, and automatic learning capabilities of deep reinforcement learning. Experimental results demonstrate that the proposed approach successfully addresses some existing challenges faced by several state-of-the-art methods in intersecting machining feature segmentation.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Chao Zhao, Weiming Shen
Summary: This paper proposes a semantic-discriminative augmentation-driven network for imbalanced domain generalization fault diagnosis, which enhances the model's generalization capabilities through synthesizing reliable samples and optimizing representations.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Ching-Chih Chang, Teng-Wen Chang, Hsin-Yi Huang, Shih-Ting Tsai
Summary: Ideation is the process of generating ideas through exploring visual and semantic stimuli for creative problem-solving. This process often requires changes in user goals and insights. Using pre-designed content and semantic-visual concepts for ideation can introduce uncertainty. An adaptive workflow is proposed in this study that involves extracting and summarizing semantic-visual features, using clusters of adapted information for multi-label classification, and constructing a design exploration model with visualization and exploration.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Zhen Wang, Shusheng Zhang, Hang Zhang, Yajun Zhang, Jiachen Liang, Rui Huang, Bo Huang
Summary: This research proposes a novel approach for machining feature process planning using graph convolutional neural networks. By representing part information with attribute graphs and constructing a learning model, the proposed method achieves higher accuracy and resolves current limitations in machining feature process planning.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hong-Wei Xu, Wei Qin, Jin-Hua Hu, Yan-Ning Sun, You -Long Lv, Jie Zhang
Summary: Wafer fabrication is a complex manufacturing system, where understanding the correlation between parameters is crucial for identifying the cause of wafer defects. This study proposes a Copula network deconvolution-based framework for separating direct correlations, which involves constructing a complex network correlation diagram and designing a nonlinear correlation metric model. The proposed method enables explainable fault detection by identifying direct correlations.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Yida Hong, Wenqiang Li, Chuanxiao Li, Hai Xiang, Sitong Ling
Summary: An adaptive push method based on feature transfer is proposed to address sparsity and cold start issues in product intelligent design. By constructing a collaborative filtering algorithm model and transforming the rating model, the method successfully alleviates data sparsity and cold start problems.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hairui Fang, Jialin An, Bo Sun, Dongsheng Chen, Jingyu Bai, Han Liu, Jiawei Xiang, Wenjie Bai, Dong Wang, Siyuan Fan, Chuanfei Hu, Fir Dunkin, Yingjie Wu
Summary: This work proposes a model for real-time fault diagnosis and distance localization on edge computing devices, achieving lightweight design and high accuracy in complex environments. It also demonstrates a high frame rate on edge computing devices, providing a novel solution for industrial practice.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Yujun Jiao, Xukai Zhai, Luyajing Peng, Junkai Liu, Yang Liang, Zhishuai Yin
Summary: This paper proposes a digital twin-based motion forecasting framework that predicts the future trajectories of workers on construction sites, accurately predicting workers' motions in potential risk scenarios.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Ling-Zhe Zhang, Xiang-Dong Huang, Yan-Kai Wang, Jia-Lin Qiao, Shao-Xu Song, Jian-Min Wang
Summary: Time-series DBMSs based on the LSM-tree have been widely applied in various scenarios. The characteristics of time-series data workload pose challenges to efficient queries. To address issues like query latency and inaccurate range, we propose a novel compaction algorithm called Time-Tiered Compaction.
ADVANCED ENGINEERING INFORMATICS
(2024)
