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Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

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computers, Materials & Continua 2024年第9期80卷 4475-4496页

作者： Xiwang Guo Liangbo Zhou Zhiwei Zhang Liang Qi Jiacun Wang Shujin Qin Jinrui Cao College of Information and Control Engineering Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Research Center of the Economic and Social Development of Henan East Provincial Joint Shangqiu Normal UniversityShangqiu476000China Department of Computer Science New Jersey City UniversityJersey CityNJ 07305USA

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle *** on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is *** enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular *** established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,*** a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

关键词： Parallel disassembly line balancing problem multi-product multiskilled workers discrete chemical reaction optimization algorithm

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Analyzing the Impact of Preprocessing Techniques on the Efficiency and Accuracy of Sentiment Classification Algorithms 15

Analyzing the Impact of Preprocessing Techniques on the Effi...

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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Nikhila Kanigiri, Sai Mekuriyaw, Chachi Goodman, Garrett Alexiou, Michail S. Kennesaw State University Department of Computer Science MariettaGA United States Miami University Computer Science and Software Engineering OxfordOH United States

ISBN: (纸本)9798350368833

In the era of data-driven decision-making, the ability to rapidly and accurately analyze vast amounts of textual data is essential. This paper examines the role of text pre-processing techniques in enhancing the effectiveness of sentiment classification algorithms. Such algorithms are pivotal in interpreting the emotional tone of texts and serving as a preliminary step towards reverse-engineering complex data systems. Through comprehensive analysis, we assess the impact of various preprocessing strategies such as keyword removal, lemmatization, and stemming and their combination on the performance of both traditional and advanced machine learning models, including Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Bidirectional Encoder Representations from Transformers (BERT). The current study evaluates the balance between efficiency and accuracy in sentiment analysis algorithms, illustrating the impact of preprocessing techniques. In addition, it aims to serve as a guideline for selecting preprocessing methods that optimize model performance in both sentiment analysis and textual data reverse-engineering. © 2024 IEEE.

关键词： Adversarial machine learning

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ML-based Anomalies Detection in Wireless Network Link Layer of the Internet of Things (IoT) 5

ML-based Anomalies Detection in Wireless Network Link Layer ...

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5th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2023

作者： Goswami, Pankaj Kumar Goswami, Garima Mahdi, Hussain Falih Vaish, Arti Dewangan, Bhupesh Kumar Choudhury, Tanupriya Teerthanker Mahaveer University Moradabad India University of Diyala Department of Computer and Software Engineering Baquba Iraq OP Jindal University Department of Computer Science and Engineering Punjipathra Raigarh India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350337525

Internet of things is the most emergent technology, expanding interconnected device networks day by day to enhance the ease of device control and monitoring. IoTs are not covering the commercial utility but also providing emergency benefits to health care centres too. The extensive number of device connections over a network challenges a huge cost of operation management. The most recent research activity deals with anomaly detection in IoT networks over wide IoT networks. The automatic malfunctioning over the network is the most tedious task for researchers. The real-world IoT system analysis motivates this work to identify the anomalies in wireless networks. The link layer is selected to analyse, identifies and detect the wireless network anomalies. A comprehensive review on the performance threshold of machine learning-based algorithms is presented for automatic detection. © 2023 IEEE.

关键词： Internet of things

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Improving Federated Learning Efficiency with PruneFL: A Healthcare Perspective 24

Improving Federated Learning Efficiency with PruneFL: A Heal...

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13th International Conference on Computing and Pattern Recognition, ICCPR 2024

作者： Shahid, Alvina Arshad, Muhammad Muneeb Azam, Farooque Anwar, Muhammad Waseem Shafi, Imran Department of Computer and Software Engineering EME College National University of Sciences and Technology Punjab Islamabad Pakistan School of Interdisciplinary Engineering and Sciences National University of Sciences and Technology Punjab Islamabad Pakistan

ISBN: (纸本)9798400717482

In healthcare, accessing diverse and large datasets for machine learning poses challenges due to data privacy concerns. Federated learning (FL) addresses this by training models on decentralized data while preserving privacy. We propose PruneFL, a FL paradigm that leverages model pruning to reduce complexity and enhance efficiency. PruneFL strikes a balance between model accuracy and efficiency by reducing parameters, accelerating convergence, and minimizing communication overhead. Our approach addresses critical FL challenges and demonstrates efficacy in resource-constrained environments like healthcare. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

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Fortifying Healthcare Data Security in the Cloud:A Comprehensive Examination of the EPM-KEA Encryption Protocol

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computers, Materials & Continua 2024年第5期79卷 3397-3416页

作者： Umi Salma Basha Shashi Kant Gupta Wedad Alawad SeongKi Kim Salil Bharany Computer Science and Information Technology Jazan UniversityJazanSaudi Arabia CSE Eudoxia Research UniversityNew CastleUSA Department of Information Technology College of Computer ScienceQassim UniversityBuraydahSaudi Arabia National Center of Excellence in Software Sangmyung UniversitySeoulKorea Department of Computer Science and Engineering Lovely Professional UniversityPhagwaraPunjabIndia

A new era of data access and management has begun with the use of cloud computing in the healthcare *** the efficiency and scalability that the cloud provides, the security of private patient data is still a majorconcern. Encryption, network security, and adherence to data protection laws are key to ensuring the confidentialityand integrity of healthcare data in the cloud. The computational overhead of encryption technologies could leadto delays in data access and processing rates. To address these challenges, we introduced the Enhanced ParallelMulti-Key Encryption Algorithm (EPM-KEA), aiming to bolster healthcare data security and facilitate the securestorage of critical patient records in the cloud. The data was gathered from two categories Authorization forHospital Admission (AIH) and Authorization for High Complexity *** use Z-score normalization forpreprocessing. The primary goal of implementing encryption techniques is to secure and store massive amountsof data on the cloud. It is feasible that cloud storage alternatives for protecting healthcare data will become morewidely available if security issues can be successfully fixed. As a result of our analysis using specific parametersincluding Execution time (42%), Encryption time (45%), Decryption time (40%), Security level (97%), and Energyconsumption (53%), the system demonstrated favorable performance when compared to the traditional *** suggests that by addressing these security concerns, there is the potential for broader accessibility to cloudstorage solutions for safeguarding healthcare data.

关键词： Cloud computing healthcare data security enhanced parallel multi-key encryption algorithm(EPM-KEA)

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Global video object segmentation with spatial constraint module

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Computational Visual Media 2023年第2期9卷 385-400页

作者： Yadang Chen Duolin Wang Zhiguo Chen Zhi-Xin Yang Enhua Wu Engineering Research Center of Digital Forensics Ministry of EducationSchool of Computer and SoftwareNanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Internet of Things for Smart City Department of Electromechanical EngineeringUniversity of MacaoMacao 999078China State Key Laboratory of Computer Science Institute of SoftwareUniversity of Chinese Academy of SciencesBeijing 100190China Faculty of Science and Technology University of MacaoMacao 999078China

We present a lightweight and efficient semisupervised video object segmentation network based on the space-time memory *** some extent,our method solves the two difficulties encountered in traditional video object segmentation:one is that the single frame calculation time is too long,and the other is that the current frame’s segmentation should use more information from past *** algorithm uses a global context(GC)module to achieve highperformance,real-time *** GC module can effectively integrate multi-frame image information without increased memory and can process each frame in real ***,the prediction mask of the previous frame is helpful for the segmentation of the current frame,so we input it into a spatial constraint module(SCM),which constrains the areas of segments in the current *** SCM effectively alleviates mismatching of similar targets yet consumes few additional *** added a refinement module to the decoder to improve boundary *** model achieves state-of-the-art results on various datasets,scoring 80.1%on YouTube-VOS 2018 and a J&F score of 78.0%on DAVIS 2017,while taking 0.05 s per frame on the DAVIS 2016 validation dataset.

关键词： video object segmentation semantic segmentation global context(GC)module spatial constraint

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A Systematic Review of Approaches for Reviewing Security-Related Aspects in Agile Requirements Specification of Web Applications

A Systematic Review of Approaches for Reviewing Security-Rel...

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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Munir, Aqsa Assiri, Mohammed Alam, Saba Naveed Khan, Muzna Butt, Wasi Haider Humayun, Mamoona Department of Computer and Software Engineering Islamabad Pakistan College of Sciences and Humanities Aflaj Prince Sattam Bin Abdulaziz University Department of Computer Science Saudi Arabia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Department of Software Engineering Saudi Arabia College of Computer and Information Sciences Jouf University Department of Information Systems Al-Jouf Saudi Arabia

ISBN: (纸本)9798350327595

Imperfections in requirement specification can cause serious issues during software development life cycle. It might bring about inferior quality products due to missing attributes, for example, security. Specifically, Web Applications are considered as obvious target for getting significant information. Security aspects have gotten hard to manage in web applications because security requirements are not regularly seen appropriately and often details are missing which lead into ill-characterized security-related aspects. With the help of systemic literature review (SLR), we have identified 32 major research works which were published in period of year 2010 to 2020. We identified 38 security-related aspects of web applications and also 13 techniques and tools for security related aspects in agile requirement specification. We have also analyzed 22 challenges in reviewing security related aspects in agile development life cycle. © 2023 IEEE.

关键词： Agile software development Quality requirements Requirement engineering Security specification Web applications

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ForTT-Gen: Network Traffic Generator for Malware Forensics Analysis Training 12

ForTT-Gen: Network Traffic Generator for Malware Forensics A...

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12th International Symposium on Digital Forensics and Security, ISDFS 2024

作者： Bistene, Jonas Vasconcelos Das Chagas, Clayton Escouper Dos Santos, Anderson Fernandes Pereira De Souza Dias, Gabriela Moutinho Salles, Ronaldo Moreira Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil Military Institute of Engineering Department of Computer Engineering Rio de Janeiro Brazil Ciicesi Estg Polytechnic of Porto Porto Portugal

ISBN: (纸本)9798350330366

The generation and replication of network traffic are essential tasks for testing, analyzing, simulating, and evaluating the behavior and efficiency of systems, protocols, applications, and network services. However, it faces various challenges and limitations when generating or replicating network traffic in a realistic, responsive, and scalable manner, using appropriate models. This work proposes a modeling of a program for generating and replicating network traffic, called Forensic Training Traffic Generator (ForTT-Gen), aims to address the challenge associated with generating and replicating network traffic generated by malware by creating files that can be used in the analysis of network packets inherent to forensic analysts' training. ForTT-Gen is a tool that can generate and replicate network traffic using a hybrid model that combines the replication of real data and the generation of synthetic data through statistical techniques. Experimental results demonstrate the model's ability to reliably. Accurately reproducing the statistical patterns of the original traffic, is evidenced by a determination coefficient of 1 and a Pearson coefficient of 0.9, all within a 0,58 confidence interval with 95% certainty. © 2024 IEEE.

关键词： Malware

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Energy-Efficient Shop Scheduling Using Space-Cooperation Multi-Objective Optimization

IEEE Transactions on Sustainable Computing

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IEEE Transactions on Sustainable Computing 2025年第3期10卷 601-615页

作者： Ding, Jiepin Xia, Jun Yang, Yaning Zhou, Junlong Chen, Mingsong Li, Keqin East China Normal University MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application Shanghai200062 China Ningxia Normal University School of Physics and Electronic Information Engineering Guyuan756500 China Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China State University of New York Department of Computer Science New PaltzNY12561 United States

Since Industry 5.0 emphasizes that manufacturing enterprises should raise awareness of social contribution to achieve sustainable development, more and more meta-heuristic algorithms are investigated to save energy in manufacturing systems. Although non-dominated sorting-based meta-heuristics have been recognized as promising multi-objective optimization methods for solving the energy-efficient flexible job shop scheduling problem (EFJSP), it is hard to guarantee the quality of the Pareto front (e.g., total energy consumption, makespan) due to the lack of population diversity. This is mainly because an improper individual comparison inevitably reduces population diversity, thus limiting exploration and exploitation abilities during population updates. To achieve efficient population evolution, this paper introduces a novel space-cooperation multi-objective optimization (SCMO) method that can effectively solve EFJSP to obtain scheduling schemes with better trade-offs. By cooperatively evaluating the similarity among individuals in both the decision space and objective space, we propose a space-cooperation population update method based on a three-vector representation that can accurately eliminate repetitive individuals to derive higher-quality Pareto solutions. To further improve search efficiency, we propose a difference-driven local search, which selectively changes the positions of operations with higher differences to search for neighbors effectively. Based on the Taguchi method, we conduct experiments to obtain a suitable parameter combination of SCMO. Comprehensive experimental results show that, compared to state-of-the-art methods, our SCMO method achieves the highest HV and NR and the lowest IGD, with an average of 0.990, 0.952, and 0.001, respectively. Meanwhile, compared to traditional local search approaches, our difference-driven local search obtains twice the HV on instance Mk12 and reduces the solving time from 1521 s to 475 s. © 2016 IEEE.

关键词： Job shop scheduling

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A Review of Lightweight Security and Privacy for Resource-Constrained IoT Devices

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computers, Materials & Continua 2024年第1期78卷 31-63页

作者： Sunil Kumar Dilip Kumar Ramraj Dangi Gaurav Choudhary Nicola Dragoni Ilsun You Department of Computer Science and Engineering National Institute of Technology JamshedpurJamshedpurIndia School of Computing Science and Engineering VIT University BhopalBhopal466114India Center for Industrial Software The Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkSonderborgOdenseDenmark Department of Applied Mathematics and Computer Science Technical University of DenmarkLyngby2800Denmark Department of Information Security Cryptologyand MathematicsKookmin UniversitySeoulSouth Korea

The widespread and growing interest in the Internet of Things(IoT)may be attributed to its usefulness in many different *** settings are probed for data,which is then transferred via linked *** are several hurdles to overcome when putting IoT into practice,from managing server infrastructure to coordinating the use of tiny *** it comes to deploying IoT,everyone agrees that security is the biggest *** is due to the fact that a large number of IoT devices exist in the physicalworld and thatmany of themhave constrained resources such as electricity,memory,processing power,and square *** research intends to analyse resource-constrained IoT devices,including RFID tags,sensors,and smart cards,and the issues involved with protecting them in such restricted *** lightweight cryptography,the information sent between these gadgets may be *** order to provide a holistic picture,this research evaluates and contrasts well-known algorithms based on their implementation cost,hardware/software efficiency,and attack resistance *** also emphasised how essential lightweight encryption is for striking a good cost-to-performance-to-security ratio.

关键词： IoT a sensor device lightweight cryptography block cipher smart card security and privacy

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