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3rd International Conference on Intelligent systems and Applications, ICISA 2024

作者： Kianypor, Hossein Husseinzadeh Kashan, Ali Nikbakhsh, Ehsan Hosseinpour, Maedeh Faculty of Operations Management IÉSEG School of Management Paris France Faculty of Industrial and Systems Engineering Tarbiat Modares University Tehran Iran Faculty of Industrial Engineering K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9789819798384

Nowadays, the preservation of natural resources and their use in optimal ways has attracted both academic study and industrial implementation. The design of supply chain networks plays a pivotal role in effective supply chain management. Optimal decisions in this area ensure the flexibility and responsiveness of the entire system. Also, the role of supply chains in waste management is crucial as it enables the efficient movement and handling of materials, ensuring proper disposal or recycling. An effective supply chain helps the collection, processing, and distribution of waste, optimizing resource use and minimizing environmental impact. This study developed a mixed-integer linear programming (MILP) model to manage agricultural waste in the palm date industry, serving as a case study for producing medium-density fiberboards (MDF). It employs a robust optimization approach to enhance the network's adaptability in accommodating uncertainties related to customer demands. Computational analysis is also provided to present the significance of the model. Also, managerial insights are extracted from the final results, and sensitivity analyses are presented to handle agricultural wastes adequately. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sensitivity analysis

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Experimental analysis of a vibro-acoustic response of an airborne structure to boundary layer excitation 64

Experimental analysis of a vibro-acoustic response of an air...

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64th Israel Annual Conference on Aerospace Sciences, IACAS 2025

作者： Naschletashvili, Maayan Stalnov, Oksana Ben-Gida, Hadar Technion Israel Institute of Technology Haifa3200003 Israel Elbit Systems Ltd. Haifa3100401 Israel Faculty of Aerospace Engineering Israel

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Optimizing drones delivery path for low-noise flight 64

Optimizing drones delivery path for low-noise flight

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64th Israel Annual Conference on Aerospace Sciences, IACAS 2025

作者： Deutscher, Barak Stalnov, Oksana Ben-Gida, Hadar Technion Israel Institute of Technology Haifa3200003 Israel Elbit Systems Ltd. Haifa3100401 Israel Faculty of Aerospace Engineering Israel

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Deep Learning Based Side-Channel Attack Detection for Mobile Devices Security in 5G Networks

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1012-1026页

作者： Amjed A.Ahmed Mohammad Kamrul Hasan Ali Alqahtani Shayla Islam Bishwajeet Pandey Leila Rzayeva Huda Saleh Abbas Azana Hafizah Mohd Aman Nayef Alqahtani Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Imam Alkadhim University College Department of Computer Techniques EngineeringBaghdad 10066Iraq Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Department of Networks and Communications Engineering College of Computer Science and Information SystemsNajran UniversityNajran 61441Saudi Arabia Institute of Computer Science and Digital Innovation UCSI UniversityKuala Lumpur 56000Malaysia Department of Intelligent Systems and Cyber Security Astana IT UniversityAstana 20000Kazakstan Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMadinah 42353Saudi Arabia Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Hofuf 31982Saudi Arabia

Mobile devices within Fifth Generation(5G)networks,typically equipped with Android systems,serve as a bridge to connect digital gadgets such as global positioning system,mobile devices,and wireless routers,which are vital in facilitating end-user communication ***,the security of Android systems has been challenged by the sensitive data involved,leading to vulnerabilities in mobile devices used in 5G *** vulnerabilities expose mobile devices to cyber-attacks,primarily resulting from security ***-permission apps in Android can exploit these channels to access sensitive information,including user identities,login credentials,and geolocation *** such attack leverages"zero-permission"sensors like accelerometers and gyroscopes,enabling attackers to gather information about the smartphone's *** underscores the importance of fortifying mobile devices against potential future *** research focuses on a new recurrent neural network prediction model,which has proved highly effective for detecting side-channel attacks in mobile devices in 5G *** conducted state-of-the-art comparative studies to validate our experimental *** results demonstrate that even a small amount of training data can accurately recognize 37.5％of previously unseen user-typed ***,our tap detection mechanism achieves a 92％accuracy rate,a crucial factor for text *** findings have significant practical implications,as they reinforce mobile device security in 5G networks,enhancing user privacy,and data protection.

关键词： Fifth Generation(5G)networks smartphone information leakage Side-Channel Attack(SCA) deep learning

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Numerical analysis of serrated chip formation in turning AZ31 magnesium alloy in dry condition and internally cooled tool

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International Journal of Advanced Manufacturing technology 2025年第5期138卷 2213-2232页

作者： Zakaria, Muhammad Syamil Danish, Mohd Azmi, Azwan Iskandar Khalil, Ahmad Nabil Mohd Rubaiee, Saeed Faculty of Mechanical Engineering Technology Pauh Putra Campus Universiti Malaysia Perlis Perlis Pauh02000 Malaysia Department of Mechanical and Materials Engineering University of Jeddah Jeddah21589 Saudi Arabia Department of Industrial and Systems Engineering University of Jeddah Jeddah21589 Saudi Arabia

The mechanism of chip formation plays a crucial role in the determination of cutting stability and the machinability of a material. Currently, the predominant emphasis of studies in the field of chip formation mechanism lies in conventional machining, with very less attention given to investigations pertaining to the influence of internal cooling conditions. This study aims to explore the serrated chip formation process of internal cooling machining known as submerged convective cooling (SCC) in the turning process using cutting simulation techniques. The research focuses on the use of AZ31 magnesium alloy as the subject of investigation. This study investigates the effects of varying cutting speeds and different cutting conditions (dry and SCC) on chip serration during turning. Subsequently, the simulation modelling technique was used to determine and analyse the relation between temperature and strain rate throughout the process of chip formation. The modelling of the serrated chip formation under SCC conditions and dry cutting was ultimately conducted. Results demonstrated that chip segmentation ratio increases with the increase of cutting speed in both SCC and dry conditions. The extent of chip serration exhibits an upward trend when subjected to SCC condition, which is attributed to the strain hardening of AZ31 magnesium alloy in SCC and the dominant thermal softening of dry cutting. Combination of strain rate and temperature affects the chip segmentation ratio. SCC has a lower adiabatic shear banding temperature for all cutting speeds;hence, it has a greater chip segmentation ratio than dry cutting. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Chip formation Finite element model Internal cooling Magnesium alloy

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Artificial Intelligence Revolutionising the Automotive Sector:A Comprehensive Review of Current Insights, Challenges, and Future Scope

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Computers, Materials & Continua 2025年第3期82卷 3643-3692页

作者： Md Naeem Hossain MdAbdur Rahim Md Mustafizur Rahman Devarajan Ramasamy Faculty of Mechanical and Automotive Engineering Technology Universiti Malaysia Pahang Al-Sultan AbdullahPekan26600Malaysia Institute for Intelligent Systems Research and Innovation(ISSRI) Deakin UniversityWarun PondsVIC3216Australia Automotive Engineering Centre Universiti Malaysia Pahang Al-Sultan AbdullahPekan26600Malaysia

The automotive sector is crucial in modern society,facilitating essential transportation needs across personal,commercial,and logistical domains while significantly contributing to national economic development and employment *** transformative impact of Artificial Intelligence(AI)has revolutionised multiple facets of the automotive industry,encompassing intelligent manufacturing processes,diagnostic systems,control mechanisms,supply chain operations,customer service platforms,and traffic management *** extensive research exists on the above aspects of AI applications in automotive contexts,there is a compelling need to synthesise this knowledge comprehensively to guide and inspire future *** review introduces a novel taxonomic framework that provides a holistic perspective on AI integration into the automotive sector,focusing on next-generation AI methods and their critical implementation ***,the proposed conceptual framework for real-time condition monitoring of electric vehicle subsystems delivers actionable maintenance recommendations to stakeholders,addressing a critical gap in the *** review highlights that AI has significantly expedited the development of autonomous vehicles regarding navigation,decision-making,and safety features through the use of advanced algorithms and deep learning ***,it identifies advanced driver assistance systems,vehicle health monitoring,and predictive maintenance as the most impactful AI applications,transforming operational safety and maintenance efficiency in modern automotive *** work is beneficial to understanding the various use cases of AI in the different automotive domains,where AI maintains a state-of-the-art for sector-specific applications,providing a strong foundation for meeting Industry 4.0 needs and encouraging AI use among more nascent industry *** current work is intended to consolidate previous works while shedding som

关键词： Artificial intelligence AI techniques automotive sector autonomous vehicle decision-making VHMS

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Cross-city insights on sustainable consumption:consistency and disparities in willingness to buy and pay for green air conditioners

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Frontiers of Environmental Science & engineering 2025年第4期19卷 169-185页

作者： Jiachao Ke Shujie Zhao Yaozhong Guo Qingbin Song Ni Sheng Jinhui Li National Observation and Research Station of Coastal Ecological Environments in Macao Macao Environmental Research Institute Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao SAR 999078China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao SAR 999078China 3.School of EnvironmentTsinghua UniversityBeijing 100084China The Institute for Sustainable Development Macao University of Science and TechnologyMacao SAR 999078China School of Business Macao University of Science and TechnologyMacao SAR 999078China

The intensification of climate change action has made air conditioners a key target for emission *** study examines the factors influencing residents’willingness to buy(WTB)and willingness to pay(WTP)for green air conditioners across six cities in the Pearl River Delta(PRD)region,aiming to understand consumer behavior and inform targeted market *** a novel Contingent Valuation Method(CVM),this study surveyed 1732 residents through online and face-to-face *** logistic and ordered logistic regression analyses identified key factors affecting WTB and WTP,including gender,income,education,knowledge of green air conditioners,and confidence in their emission reduction ***,the study reveals significant regional disparities in WTP and payment amounts through the Kruskal-Wallis H and Mann-Whitney U *** results also highlight Shenzhen has significant difference and highest payment value than other *** findings provide valuable insights into regional disparities and common factors in green consumption,offering guidance for market strategies and policy development aimed at promoting green air conditioners.

关键词： Contingent valuation method Green air conditioners WTB and WTP Influence factors Consistency and difference

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Stability and bifurcation analysis of delayed tri-trophic food chain model in poisoned environment with fear effect and additional food

Stability and bifurcation analysis of delayed tri-trophic fo...

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作者： Ramasamy, Sivasamy Banjerdpongchai, David Park, PooGyeon Center of Excellence in Intelligent Control Automation of Process Systems Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Electrical Engineering Pohang University of Science and Technology Pohang Korea Republic of

One of the most important goals of theoretical ecologists is to find a strategy for controlling the chaos in ecological models to maintain healthy ecosystems. We investigate the influence of fear and the supply of additional food to predators in a delayed tri-trophic food chain model, where interference among the species is determined by Holling type-II functional response. The proposed model incorporates the fact that the growth rates of prey and middle predators are decreased due to the fear of middle and special predators, respectively. The additional food is supplied to both predators by either nature or external agencies. Furthermore, the poisoned prey in the predator's environment is taken into account. In the proposed model, we use two time delays: one for the growth term of the middle predator and another for the gestation delay of the special predator. We determine the conditions for the existence of ecologically feasible equilibrium points and their local and global stability. In addition, we establish the conditions for the existence of Hopf bifurcation around interior equilibrium to seek periodic behavior in nondelayed and delayed models. Numerical investigations are performed to justify the proposed theoretical findings through phase portraits, time series of solutions, and bifurcation diagrams. We observe that the chaotic dynamics of a tri-trophic food chain model can be controlled by the proper choice of the fear effect and by supplying additional food parameters. As a result, our findings provide more ecological insights into the dynamics of the delayed tri-trophic food chain model with the fear effect and additional food supply. © 2023 John Wiley & Sons, Ltd.

关键词： Hopf bifurcation

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A Novel Framework for Gauging Information Extracted from Smartphones Using Neutrosophic Logic

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Neutrosophic Sets and systems 2025年 76卷 154-171页

作者： Abou Alzahab, R.M. Ismail, Amr Abd Elkhalik, S.H. Shams, M.Y. El-Bakry, H.M. Salama, A.A. Department of Mathematics and Computer Science Faculty of Science Port Said University Egypt Department of Cybersecurity College of Engineering and Information Technology Buraydah Private Colleges Buraydah51418 Saudi Arabia Department. of Communication and Computer Engineering Air Defense University Egypt Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh33516 Egypt Department of Information Systems. Faculty of Computer and Information Science Mansoura University Egypt

Smartphones contain a vast amount of information about their users, which can be used as evidence in criminal cases. However, the sheer volume of data can make it challenging for forensic investigators to identify and use the most relevant information. Neutrosophic logic is a generalization of fuzzy logic that allows for uncertainty and vagueness, making it a more potent tool for dealing with the ambiguity of real-world data. The proposed framework aims to identify and utilize the most relevant information for forensic investigators, making it easier to solve criminal cases using Neutrosophic logic. This novel approach provides a more powerful tool for dealing with the ambiguity of smartphone data, ultimately improving the accuracy and effectiveness of forensic investigations. Our research has utilized Neutrosophic logic to evaluate the degree of truth, falsity, or Indeterminacy of this information. Additionally, this study analyzes conversations between individuals using Excel’s fuzzy lookup add-in to determine the percentage of truth and false in each conversation. The results were compiled into a dataset and utilized a Neutrosophic Python code to evaluate the information. The results indicate the percentage of truth, false, and Indeterminacy in each conversation and which can be used to determine its admissibility as evidence and which not. © 2025, University of New Mexico. All rights reserved.

关键词： Smartphones

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Cost-Optimized Task Offloading for Dependent Applications in Collaborative Edge and Cloud Computing

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IEEE Internet of Things Journal 2025年第9期12卷 12975-12988页

作者： Yuan, Haitao Hu, Qinglong Wang, Shen Bi, Jing Buyya, Rajkumar Lu, Jinhu Yang, Jinhong Zhang, Jia Zhou, MengChu Beihang University School of Automation Science and Electrical Engineering Beijing100191 China City University of Hong Kong Department of Computer Science Kowloon Tong Hong Kong Beijing University of Technology School of Software Engineering Faculty of Information Technology Beijing100124 China Laboratory School of Computing and Information Systems MelbourneVIC3010 Australia CSSC Systems Engineering Research Institute Beijing100036 China Southern Methodist University Lyle School of Engineering Department of Computer Science DallasTX75205 United States New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States

A collaborative system that includes mobile devices (MDs), edge nodes (ENs), and the cloud is needed where ENs at the network edge can run offloaded tasks of MDs with limited resources and energy for timely processing for latency-sensitive applications. Unlike existing studies, we formulate a total cost minimization problem for the system for applications, which can be divided into several interdependent subtasks. Each subtask can be executed in MDs, ENs, and the cloud. This work formulates a mixed-integer nonlinear program to minimize the total system cost. To address it, a novel meta-heuristic optimization algorithm called Genetic Simulated-annealing-based Particle swarm optimization with Auto-Encoder (GSPAE) is proposed, which innovatively combines feature extraction of deep learning and global search of meta-heuristic optimization. Genetic operations provide diverse solutions, the Metropolis acceptance of annealing offers a robust global search, and autoencoders (AEs) extract distribution characteristics of particles toward high-quality regions for fast convergence. Thus, GSPAE optimizes the associations between ENs and MDs and the scheduling of subtasks among MDs, ENs, and the cloud. Experiments with large-scale Google cluster datasets show that compared to state-of-the-art benchmark methods, GSPAE reduces the total cost by at least 17% while strictly meeting limits of application latency, available energy, computing, and communication resources of ENs and MDs. © 2014 IEEE.

关键词： Mobile edge computing

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