Article
Computer Science, Artificial Intelligence
Sehej Jain, Kusum Kumari Bharti
Summary: This paper proposes a methodology to model the problem of disaster emergency response as an optimization problem and solve it using meta-heuristic algorithms. The empirical analysis on a benchmark dataset demonstrates the effectiveness of the meta-heuristic algorithms in finding near-optimal solutions for the problem.
Article
Engineering, Industrial
Qiong Liu, Renfei He, Limao Zhang
Summary: This study establishes a multi-objective optimization model for fire emergency response in metro stations using simulation-based analysis. It constructs a Hierarchical Timed Color Petri Nets model and adopts the Skyline operator to solve the MOO problem. The study demonstrates the feasibility and effectiveness of the proposed approach through a case study conducted at a metro station in Wuhan.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Computer Science, Artificial Intelligence
Jianghua Zhang, Yuchen Li, Guodong Yu
Summary: This paper addresses the design problem of emergency rescue networks in response to disasters under uncertainty. By constructing a MAD-based ambiguity set, the paper proposes a distributionally robust optimization model to minimize the preparedness cost and the expected penalty cost of demand shortage. The computational experiments demonstrate that the proposed model outperforms the stochastic optimization model in terms of solution time and solution quality, and the amount of data significantly impacts the model performance.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Multidisciplinary Sciences
Todor Stoilov, Krasimira Stoilova, Stanislav Dimitrov
Summary: This study assesses husbandry management by comparing economic results and aims to minimize risk and maximize return. The research formalizes risk as the standard deviation of return and the probability of losses, and analyzes the characteristics and optimal solutions of these problems. Empirical comparisons with real data demonstrate that applying both risk formalizations can decrease risk.
Article
Information Science & Library Science
Hongzhe Zhang, Xiaohang Zhao, Xiao Fang, Bintong Chen
Summary: Disaster response is crucial for saving lives and minimizing damages, and effective resource management is essential to successful disaster response. In this study, we address the problem of determining optimal quantities of requested resources by considering both current and future demands. We propose a novel deep learning method for predicting future demand and formulate the problem as a stochastic optimization model. Our approach outperforms existing methods in terms of performance, as demonstrated through real-world and simulated data, as well as in a multistakeholder and multiobjective setting through simulations.
INFORMATION SYSTEMS RESEARCH
(2023)
Article
Multidisciplinary Sciences
Wenxiao Li, Yushui Geng, Jing Zhao, Kang Zhang, Jianxin Liu
Summary: This paper introduces a novel hybrid genetic algorithm NSGA-II-BnF, which combines the hyperbolic tangent function with a metaheuristic algorithm to tackle multi-objective decision making problems. The algorithm addresses the challenge of diversity neglect in MOEAs through an elite exploitation strategy, including biased elite allocation and self-guided fast individual exploitation. Experimental results show that NSGA-II-BnF outperforms other algorithms on various test problems, highlighting its superior performance and applicability.
Review
Chemistry, Analytical
Nestor Alzate-Mejia, German Santos-Boada, Jose Roberto de Almeida-Amazonas
Summary: The human-centric characteristic of future communication network paradigms plays a crucial role in the relationship between telematics and human activities. The uncertainties introduced by the dynamic nature of user behavior pose challenges in network resource management, calling for improved modeling of human behavior context. Establishing such a model is key to enhancing resource assignment and management efficiency.
Article
Engineering, Electrical & Electronic
Zejun Yang, Andrea Marti, Ying Chen, Jose R. Marti
Summary: This paper presents a two-step optimization strategy to maximize the resilience of the power distribution network against hurricanes. The strategy integrates a pre-disaster preparedness plan and a post-disaster resource re-allocation procedure. The resource allocation optimization problem is formulated as a Mixed-Integer Nonlinear Programming (MINP) problem. The proposed method is tested on the IEEE 70-node system and it shows improved performance in reducing failure probability and enhancing system recovery ability.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Psychology, Multidisciplinary
Kiran Saleem, Salwa Muhammad Akhtar, Makia Nazir, Ahmad S. S. Almadhor, Yousaf Bin Zikria, Rana Zeeshan Ahmad, Sung Won Kim
Summary: This paper introduces a multi-agent system utilizing NB-IoT, cyan IIOT, and edge intelligence to enhance situation awareness and response capability in disaster sites. The belief-desire-intention reasoning mechanism is introduced to achieve timely information acquisition and efficient action in a dynamic environment.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Chemistry, Analytical
Shai Kendler, Barak Fishbain
Summary: Industrial activities involving harmful chemicals require advanced planning to deal with potential disasters. This study examined the tradeoff between the location and attributes of sensors used for assessing chemical contamination. The findings suggest that the quantity of sensors is more important than their quality when the locations are optimal.
Article
Environmental Sciences
Feiyue Wang, Ziling Xie, Hui Liu, Zhongwei Pei, Dingli Liu
Summary: This study proposes a multiobjective emergency resource allocation model considering uncertainty under the natural disaster chain. The proposed model and algorithm optimize timeliness, efficiency, and fairness in actual rescue, achieving the visualization of emergency trips and intelligent avoidance of risk areas.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Mathematics
Todor Stoilov, Krasimira Stoilova
Summary: The study introduces an algorithm for active business management, recommending reallocation of resources through solving portfolio problems to increase business income.
Article
Telecommunications
Wei Feng, Hao Liu, Yingbiao Yao, Diqiu Cao, Mingxiong Zhao
Summary: This paper optimizes offloading decision, computation, and bandwidth allocation in MEC networks through partial offloading to minimize average user latency. By decomposing the non-convex problem into subproblems and using the BCD method, the algorithm achieves better performance and fast convergence in terms of average latency.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Engineering, Civil
Rafael Fernandez, Juan Francisco Correal, Dina D'Ayala, Andres L. Medaglia
Summary: School infrastructure has a significant impact on education quality and student performance. Natural disasters pose threats to critical infrastructure, such as school facilities, while functional problems like inadequate classrooms, poor lighting, and insufficient ventilation are common in the region. Making decisions to prioritize school interventions on a national level becomes even more challenging due to limited resources and lack of information. To address this, a novel decision-making framework is proposed, using clustering procedures, a multi-criteria utility function, and an optimization component to prioritize school infrastructure investment with limited budgets. This framework allows for better public policy decisions and improves building quality from a multi-criteria perspective, enhancing safety and functional conditions. The framework is illustrated through a case study in the Dominican Republic's public-school infrastructure.
STRUCTURE AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Parisa Fallah, Meysam Rabiee, Abolghasem Yousefi-Babadi, Emad Roghanian, Mostafa Hajiaghaei-Keshteli
Summary: This research proposes a stochastic multi-objective mixed-integer linear programming model for an agile, flexible disaster supply chain network, and utilizes a novel group decision-making framework to select qualified suppliers. A robust probabilistic programming approach and metaheuristic algorithms are used to handle uncertainty and large-scale problems. The results of the study demonstrate the applicability of the proposed framework and methodologies.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Mechanics
Seyed Sajad Mirjavadi, Masoud Forsat, Mohammad Reza Barati, A. M. S. Hamouda
Summary: This study investigates the nonlinear free vibrations of porous functionally graded annular spherical shell segments and highlights the factors affecting the vibration characteristics.
MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES
(2022)
Article
Mechanics
Seyed Sajad Mirjavadi, Masoud Forsat, Mohammad Reza Barati, A. M. S. Hamouda
Summary: This article investigates the nonlinear vibration of variable thickness cylindrical panels made of multi-scale composite materials. The study defines the elastic properties of the materials and considers the changes in panel thickness. By using Jacobi elliptic functions to solve the governing equations, the exact frequency-amplitude curves of the panels are obtained. The study also examines the effects of various factors on the frequency-amplitude curves.
MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES
(2022)
Article
Mechanics
Seyed Sajad Mirjavadi, Masoud Forsat, Mohammad Reza Barati, A. M. S. Hamouda
Summary: This research examines the nonlinear free vibration behavior of truncated conical shell segments made from multi-scale epoxy/carbon nanotube/fiberglass material. A 3D Mori-Tanaka micro-mechanic method is used to define the hybrid material properties by incorporating random dispersion of carbon nanotubes and parallel alignment of glass fibers. The study focuses on the effects of fiber volume, fiber directions, semi-vertex angle, CNT weight fraction, and CNT aspect ratio on the nonlinear free vibrations of the multi-scale truncated conical shell segments.
MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES
(2022)
Article
Materials Science, Multidisciplinary
A. Esmaeili, C. Sbarufatti, K. Youssef, A. Jimenez-Suarez, A. Urena, A. M. S. Hamouda
Summary: This study investigated the effect of toroidal stirring-assisted sonication on CNT doped epoxy nanocomposites, showing that M2 batch exhibited better mechanical, electrical, and piezoresistivity performance compared to M1 batch. Tensile and fracture tests were conducted, revealing a 70% increase in tensile strength and a 17% increase in fracture toughness for M2 batch. Additionally, the piezoresistive-sensitivity of M2 batch increased by 14% compared to M1 batch. Different trends in piezoresistivity were observed in the fracture test before macroscopic damage, attributed to the state of CNT dispersion.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2022)
Article
Operations Research & Management Science
Zhitao Xu, Shaligram Pokharel, Adel Elomri
Summary: In this research, a two-stage stochastic model is proposed to design a closed-loop supply chain (CLSC) under a carbon trading scheme in the multi-period planning context. The model considers uncertain demands and carbon prices and provides a solution procedure with scenario reduction for efficient solving. The application of the model in the aluminum industry shows that it generates a network with capacity redundancy to cope with varying customer demands and carbon prices, with only a slight increase in cost and emissions compared to the deterministic model. Using scenario reduction, the model solves with reduced scenarios while maintaining similar network configuration and a decrease in computational burden.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Reem Al Sharif, Shaligram Pokharel, Mohamed Arselene Ayari, Marwa Essam, Salwa Aqeel
Summary: This study examines the application of open innovation in digital startups by conducting a qualitative analysis on the incubation program of a center in Qatar. The results indicate that open innovation and incubation can contribute positively to the development of digital startups.
Review
Chemistry, Multidisciplinary
Asma Mecheter, Shaligram Pokharel, Faris Tarlochan
Summary: This paper reviews the application of additive manufacturing technology in spare parts manufacturing, highlighting the supply chain opportunities and challenges. It also discusses the future research directions in this field.
APPLIED SCIENCES-BASEL
(2022)
Review
Energy & Fuels
Maryam Mohdsaeed H. I. Abdulla, Shaligram Pokharel
Summary: This paper provides a review of the application of immiscible CO2 injection in enhanced oil recovery. It evaluates the practicality of screening reservoir parameters for immiscible CO2 injection and discusses the critical parameters included in the analytical model for oil recovery calculations.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Maryam Hussain Abal-Seqan, Shaligram Pokharel, Khalid Kamal Naji
Summary: The success of a construction project is dependent on various factors such as the knowledge of project managers and the project type. This study identifies 23 critical factors based on a literature review, which are categorized into top-management support, project manager's skills, project team skills, and stakeholder-management knowledge. A framework with 23 hypotheses is developed to assess the relationship between these factors and project performance. The analysis of this framework is conducted using survey responses from 266 engineers working on construction projects in Qatar. The results demonstrate a positive correlation between critical success factors and project performance, with top-management support being ranked as the most important factor.
Review
Chemistry, Multidisciplinary
Abdulaziz Aldoseri, Khalifa N. N. Al-Khalifa, Abdel Magid Hamouda
Summary: The use of artificial intelligence (AI) is expanding in industries like healthcare, finance, and transportation. However, utilizing data for AI presents challenges such as data quality and privacy concerns. This paper provides a comprehensive review and analysis of these challenges, offering recommendations to address them and harness the power of AI for smarter decision-making and competitive advantage. The paper is expected to be highly valuable to the scientific research community for generating novel ideas on data strategies for AI.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Interdisciplinary Applications
Asma Mecheter, Shaligram Pokharel, Faris Tarlochan, Fujio Tsumori
Summary: This research proposes an optimization model for the trade-off analysis of spare parts supply through computer numerical control (CNC) manufacturing and additive manufacturing (AM). The model focuses on minimizing lead times and assessing the effectiveness of different manufacturing methods for spare parts with varying complexity. The findings show that AM is cost-effective for spare parts with high geometry complexity, while CNC-based manufacturing is economically feasible for spare parts with low geometry complexity and large sizes.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2023)
Article
Mechanics
Seyed Sajad Mirjavadi, Imran Khan, Masoud Forsat, Mohammad Reza Barati, A. M. S. Hamouda
Summary: This research analyzes the nonlinear vibration properties of stiffened toroidal convex/concave shells made of porous metal foam material in an elastic medium. The study considers metal foam as a porous material with uniform and nonuniform models. The governing equations of motion for eccentrically stiffened porous toroidal shell segments are derived using classical shell theory and the smeared stiffeners technique. The Jacobi elliptic functions are used to solve the nonlinear governing equations and obtain exact frequency-amplitude curves. The results demonstrate the significance of porosity distribution, geometric nonlinearity, foundation factors, stiffeners, and curvature radius on the vibration characteristics of porous toroidal convex/concave shells.
MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Reem Al Sharif, Shaligram Pokharel
Summary: The concept of smart cities requires heavy investment in information and communication technology for creating economic and social value. However, the complexity and associated risks of such technology can have negative effects on the security and privacy of smart cities. This paper focuses on the dimensions and risks associated with smart cities, using Qatar's smart city project as an example.
SUSTAINABLE SMART CITIES AND TERRITORIES
(2022)
Article
Computer Science, Information Systems
Aljazzi Fetais, Galal M. Abdella, Khalifa N. Al-Khalifa, Abdel Magid Hamouda
Summary: This paper introduces a fuzzy-based analytical hierarchy process (FAHP) to integrate factors affecting BPR and OC, aiming to ensure the success of BPR implementation. Through real case studies, expert validations, literature reviews, and correlation studies, the relationship between BPR factors and OC factors is explored.
APPLIED SYSTEM INNOVATION
(2022)
Article
Business
Khalifa Mohammed Al-Sobai, Shaligram Pokharel, Galal M. Abdella
Summary: This article proposes a framework and analytical methodologies to support decision-making for selecting cross-industry strategic projects, demonstrating its applicability in Qatar's real estate and transportation projects.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Engineering, Industrial
Hao Sun, Haiqing Wang, Ming Yang, Genserik Reniers
Summary: To maintain continuous production, chemical plant operators may choose to ignore or handle faults online rather than shutting down process systems. However, the interaction and interdependence between components in a digitalized process system are significant, and faults can propagate to downstream nodes, potentially leading to risk accumulation and major accidents. This study proposes a dynamic risk assessment method that integrates the system-theoretic accident model and process approach (STAMP) with the cascading failure propagation model (CFPM) to model the risk accumulation process. The proposed method is applied to a Chevron refinery crude unit and demonstrates its effectiveness in quantifying the process of risk accumulation and providing real-time dynamic risk profiles for decision-making.
Article
Engineering, Industrial
M. Rempel
Summary: This article examines a major maritime disaster scenario and explores the evacuation process in such a situation. The study finds that there are various factors that affect the number of lives saved, including the uncertainty of individuals' medical condition, the arrival time of maritime and air assets, and the decision policies used. The authors formulate the multi-domain operation as a sequential decision problem using a modeling framework and provide decision support through a hypothetical case study.
Review
Engineering, Industrial
D. Scorgie, Z. Feng, D. Paes, F. Parisi, T. W. Yiu, R. Lovreglio
Summary: This study investigates the application and effectiveness of VR safety training solutions in various industries such as construction, fire, aviation, and mining. The findings suggest a need for more studies that adopt theories and measure long-term retention. Two meta-analyses demonstrate that VR safety training outperforms traditional training in terms of knowledge acquisition and retention.
Article
Engineering, Industrial
Shital Thekdi, Terje Aven
Summary: This paper examines biases in risk studies and investigates how to identify and address them to ensure high-quality risk analysis. By considering biases related to systematic error, event inclusion, models, and cognitive factors, the paper explores their influence on risk characterization. The insights gained from this exploration can be valuable to risk analysts, policymakers, and other stakeholders involved in risk study applications.
Article
Engineering, Industrial
Maryam Lari
Summary: Occupational health and safety (OHS) are crucial for employee well-being and productivity. This study examines the impact of OHS practices on employee productivity in a UAE Fire and Security company, finding that OHS interventions can enhance workplace ambiance and significantly boost employee productivity.
Review
Engineering, Industrial
Elleke Ketelaars, Cyrille Gaudin, Simon Flandin, Germain Poizat
Summary: This systematic literature review examines the literature on resilience training (RT), specifically focusing on the effectiveness of RT interventions in preparing professionals to effectively respond to critical situations. The review identifies five types of RT and suggests the need for conceptual advancements, vocational education and training perspectives, and a cross-disciplinary approach in future research to enhance resilience in safety-related domains.
Article
Engineering, Industrial
Meng Shi, Zhichao Zhang, Wenke Zhang, Yi Ma, Hanbo Li, Eric Wai Ming Lee
Summary: This study investigates pedestrian behaviours and evacuation processes in both fire and non-fire conditions using Minecraft. The results demonstrate the potential of Minecraft for realistically simulating evacuation processes, as the behaviours and flow patterns of pedestrians in virtual experiments fit well with real-life experiments. The study also shows that pedestrians exhibit fire avoidance behaviours and orderly queuing during a fire emergency, resulting in faster evacuation.
Article
Engineering, Industrial
Andrea Bikfalvi, Esperanza Villar Hoz, Gerusa Gimenez Leal, Monica Gonzalez-Carrasco, Nuria Mancebo
Summary: This paper proposes a solution for integrating occupational safety and health (OSH) into education, combining theoretical foundations and empirical evidence. The findings include analysis of teachers as stakeholders, barriers and facilitators of OSH integration, and the development of an ICT tool for interaction and sharing in this field. The main contribution lies in envisioning, orchestrating, and validating a solution to integrate OSH into schools and ultimately contribute to sustainable development goals.
Article
Engineering, Industrial
David Rehak, Alena Splichalova, Martin Hromada, Neil Walker, Heidi Janeckova, Josef Ristvej
Summary: This article discusses the adoption of a new directive on the resilience of critical entities and emphasizes the importance of assessing their level of resilience in relation to current security threats. The authors have developed a tool, known as the CERFI Tool, which uses a probabilistic algorithm to predict the failure point of critical entity resilience based on the relationship between threat intensity and protection. The tool is important for increasing the safety of technically oriented infrastructures, particularly in the energy and transport sectors.
Review
Engineering, Industrial
Leonardo Leoni, Ahmad Bahootoroody, Mohammad Mahdi Abaei, Alessandra Cantini, Farshad Bahootoroody, Filippo De Carlo
Summary: This paper presents a systematic bibliometric analysis (SBA) on the research of machine learning and deep learning in the field of safety. The main research areas, application fields, relevant authors and studies, and temporal evolution are investigated. It is found that rotating equipment, structural health monitoring, batteries, aeroengines, and turbines are popular fields, and there is an increase in popularity of deep learning and new approaches such as deep reinforcement learning.
Article
Engineering, Industrial
Tom Becker, Peter Ayton
Summary: By analyzing global civil aviation data, we found that there is a significant increase in the number of accidents and safety critical incidents, as well as the fatalities, when the Pilot-in-Command acts as the Pilot Flying instead of the Pilot Monitoring. Most of these events occurred in technically airworthy aircraft without any emergencies, and the flight crew assessed them as preventable. These findings align with the crew assignment effect, suggesting that role-dependent status hierarchy and cognitive overload contribute to ineffective flight crew teamwork. The measures implemented to enhance flight crew teamwork, such as Crew Resource Management training, have not been successful in preventing these issues.
Article
Engineering, Industrial
Ben Hutchinson, Sidney Dekker, Andrew Rae
Summary: This study found that health and safety audits often fail to identify critical deficiencies, with corrective actions mainly focusing on superficial fixes rather than addressing significant operational risks.
Review
Engineering, Industrial
Sina Rasouli, Yaghoub Alipouri, Shahin Chamanzad
Summary: Construction projects are risky environments, but the development of Personal Protective Equipment (PPE) and comprehensive safety management can effectively control the number of accidents.
Article
Engineering, Industrial
Laura Mills, Verity Truelove
Summary: This study investigated the use of police location communities (PLCs) for obtaining information about roadside drug testing (RDT) among drivers, and found that drivers who used PLCs were more concerned about being caught for drug driving, had a better understanding of the related penalties and procedures, and knew others who also used PLCs to avoid detection for drug driving. Furthermore, the study found that the use of PLCs was associated with choosing back roads for driving, which may reduce the risk of detection for drug driving.
Review
Engineering, Industrial
Chao Wu, Xi Huang, Bing Wang
Summary: After decades of development, the safety discipline in China has made remarkable progress. The project led by the Safety & Security Theory Innovation and Promotion Center of Central South University has filled the gaps in safety science education by creating textbooks and courses for postgraduate students. These achievements have played an important role in the development of safety science and can serve as a reference for basic research and talent training in safety science globally.