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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Duan, Xuan Liu, Songbai Ji, Junkai Li, Lingjie Lin, Qiuzhen Tan, Kay Chen College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China Shenzhen China The Hong Kong Polytechnic University Department of Computing Hong Kong

ISBN: (纸本)9798350308365

To enhance the generalization of multi-objective feature selection (MOFS) in classification, this paper proposes an evolutionary multitasking algorithm, diverging from previous approaches that exclusively target selected features. The algorithm integrates information from both selected and unselected features, introducing a novel objective to minimize the accuracy of unselected features. This objective, combined with the goal of minimizing classification errors for selected features, forms an auxiliary MOFS task. The paper presents a dual-population evolutionary multitasking framework that synergizes the main MOFS task with the auxiliary task. A knowledge transfer mechanism, based on accuracy preferences, seamlessly shares insights from the auxiliary to the main task, aiming to identify improved Pareto feature subsets. Empirical results demonstrate the superior performance of several state-of-the-art multi-objective algorithms within this framework, highlighting significant improvements across diverse datasets. © 2024 IEEE.

关键词： Feature Selection

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A recurrent neural network architecture for android mobile data analysis for detecting malware infected data

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Soft Computing 2024年第21期28卷 12917-12928页

作者： Murugan, Prabhu Manimaran, A. Sundar, Ramesh Dakshinamoorthy, Prabakar Rajaram, Gnanajeyaraman Garg, Shruti Department of ECE Saveetha School of Engineering Simats Chennai602105 India Department of Artificial Intelligence and Machine Learning Saveetha School of Engineering Simats Chennai602105 India Department of Netwoking and Communication School of Computing SRM Institute of Science and Technology SRM Nagar Kattankulathur India Department of Data Science and Business System School of Computing SRM Institute of Science and Technology SRM Nagar Kattankulathur India Department of Applied Machine Learning Saveetha School of Engineering Saveetha Institute of Medical and Technological Sciences Tamilnadu Chennai India Birla Institute of Technology Mesra Ranchi India

One of the latest modern communication devices is a mobile device seriously affected by multiple malware. Malware is a virus software installed automatically by hackers on various computing devices. Malware corrupts the system software, kills *.exe files, and tries to access user-sensitive data from the device. Around the world, 80% of people use smartphones, and 70% use Android phones. All Android phones are installed with anti-virus software but not used properly. Thus, it creates a pathway for malware to enter Android mobile devices and deploy vulnerabilities. Several earlier methods have focused on using the malware detection method by analyzing static data, which cannot identify the dynamic behavior of the malware. Thus, this paper implemented one of the deep learning algorithms, RNN, for identifying and detecting malware activities in Android mobile devices statically and dynamically. An IoT network architecture is proposed for experimenting with the RNN algorithms verifying the performance. The results of the RNN method show that it is better than other models in malware detection in mobile devices. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Android malware

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Estimation of Critical Temperature of Thermal Explosion for Energetic Materials Based on Non-isothermal Kinetic Equation dα/dt =A_0 exp(bT)[1+(T–T_0 )b]f(α)

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Chemical Research in Chinese Universities 2010年第5期26卷 829-832页

作者： ZHAO Feng-qi HU Rong-zu ZHANG Hai GAO Hong-xu ZHAO Hong-an MA Hai-xia Xi ＇an Modern Chemistry Research Institute Xi ＇an 710065 P. R. China Department of Mathematics/nstitute of Data Analysis and Computed Chemistry College of Communication Science and Engineering College of Chemical Engineering Northwest University Xi ＇an 710069 P. R. China Institute of System and lnformation Science Xi＇an Jiaotong University Xi ＇an 710049 P. R. China

Critical temperature（Tb） of thermal explosion for energetic materials is estimated from Semenov＇s thermal explosion theory and the non-isothermal kinetic equation da/dt=Aoexp（bT）[1＋（T-T0）b][（a） deduced via reasonable hypotheses, where To is the initial point of the deviation from the baseline of DSC curve. The final formula is （Tb-Te0）{ 1＋1/[1＋（ Tb-T00）b]}=1. We can easily obtain the initial temperature（T0/） and onset temperature（Tci） from the non-isothermal DSC curves, the values of Too and Tc0 from the equation TOi or ei=T00 or c0＋α1βi＋a2βi^2＋…＋aL-2L-2βiL-2, i=1,2,…L, the value of b from the equation： In[β/（Tei-T0i）]=ln[A0/G（a）]＋bTei, so as to calculate the value of Tb. The result obtained with this method coincides completely with the value of Tb obtained by Hu-Yang-Liang-Wu method.

关键词： Critical temperature Thermal exolosion DSC Energetic material Non-isothermal

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Ev-IDID: Enhancing Solutions to Interactive Dynamic Influence Diagrams through Evolutionary Algorithms 21

Ev-IDID: Enhancing Solutions to Interactive Dynamic Influenc...

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21st International Conference on Autonomous Agents and Multiagent systems, AAMAS 2022

作者： Ma, Biyang Pan, Yinghui Zeng, Yifeng Ming, Zhong School of Computer Science and Engineering Minnan Normal University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Department of Computer and Information Sciences Northumbria University United Kingdom College of Computer Science and Software Engineering Shenzhen University China

ISBN: (纸本)9781713854333

Interactive dynamic influence diagrams (I-DIDs) are a general framework for multiagent sequential decision making under uncertainty. Due to the model complexity, a significant amount of research has been invested into solving the model through various types of either exact or approximate algorithms. However, there is no tool that allows users to specify the algorithm parameters and visualise the model solutions. In this demo, we develop an interactive I-DID system that implements most of the state-of-art I-DID algorithms and develops a new type of algorithms based on evolutionary computation. In particular, we propose a multi-population genetic algorithm for solving the I-DID models and automate the generation of behavioural models in the solutions. This demo will facilitate the I-DID research development and practical applications, and elicit a new wave of I-DID solutions based on evolutionary algorithms. © 2022 International Foundation for Autonomous Agents and Multiagent systems (***). All rights reserved.

关键词： Decision making

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UNIVERSAL APPROXIMATION OF PARAMETRIC OPTIMIZATION VIA NEURAL NETWORKS WITH PIECEWISE LINEAR POLICY APPROXIMATION

arXiv

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arXiv 2023年

作者： Bae, Hyunglip Kim, Jang Ho Kim, Woo Chang Department of Industrial and System Engineering KAIST Korea Republic of Depart of Industrial and Management System Engineering Department of Big Data Analytics Kyung Hee University Korea Republic of

Parametric optimization solves a family of optimization problems as a function of parameters. It is a critical component in situations where optimal decision making is repeatedly performed for updated parameter values, but computation becomes challenging when complex problems need to be solved in real-time. Therefore, in this study, we present theoretical foundations on approximating optimal policy of parametric optimization problem through Neural Networks and derive conditions that allow the Universal Approximation Theorem to be applied to parametric optimization problems by constructing piecewise linear policy approximation explicitly. This study fills the gap on formally analyzing the constructed piecewise linear approximation in terms of feasibility and optimality and show that Neural Networks (with ReLU activations) can be valid approximator for this approximation in terms of generalization and approximation error. Furthermore, based on theoretical results, we propose a strategy to improve feasibility of approximated solution and discuss training with suboptimal solutions. © 2023, CC BY.

关键词： Decision making

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Effect of Plastic Deformation on Microstructure and Properties of Cu-(1 wt%-6 wt%) Ag Alloy

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Journal of Wuhan University of Technology(Materials Science) 2024年第3期39卷 747-753页

作者：茹亚东 ZHANG Zhongyuan 高召顺 ZHANG Ling ZUO Tingting XUE Jiangli TANG Zhixiang DA Bo LIU Yongsheng XIAO Liye Institute of Electrical Engineering Chinese Academy of SciencesBeijing 100190China Department of Physics Shanghai University of Electric PowerShanghai 201306China University of Chinese Academy of Sciences Beijing 100190China International Joint Labora-tory for Light Alloys(MOE) College of Materials Science and EngineeringChongqing UniversityChongqing 400044China Research and Services Division of Materials Data and Integrated System National Institute for Materials ScienceTsukuba 305-0047Japan

In the present study,the Cu-(1 wt%-6 wt%)Ag alloys were prepared by melting,forging and wire *** effects of plastic deformation on microstructure evolution and properties of the alloys were *** results show that non-equilibrium eutectic colonies exist in the Cu-(3 wt%-6 wt%)Ag alloy and no eutectic colonies in the 1 wt%-2 wt%Ag containing *** eutectic colonies are aligned along the drawing direction and refined with the increase of draw *** to the refinement of eutectic colonies,the Cu-Ag alloy exhibits higher strength with the increase of draw *** Cu-6Ag alloy exhibits excellent comprehensive properties with a strength of 930 MPa and a conductivity of 82%IACS when the draw ratio reaches 5.7.

关键词： Cu-Ag alloy high strength and high conductivity microstructure eutectic structure strengthening mechanism

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Effect of Delignification Method on the type of Cellulose Water Hyacinth ( Eichornia crassipes) as a Material for Sustainable Sodium-Ion Battery Technology 3

Effect of Delignification Method on the type of Cellulose Wa...

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3rd International Symposium on Physics and Applications 2023, ISPA 2023

作者： Anugerah Putra Pradana, Revaldo Rafi Setopratama, Andyan Zulaiha Ahmad, Chanifa Prasetyo, Andry Nur Abti, Salsabilla Darminto Department of Physics Faculty of Science and Data Analytics Institute Technology Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia Department of Chemistry Faculty of Science and Data Analytics Institute Technology Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia Department of Material Engineering and Metallurgy Faculty of Industrial Technology and System Engineering Institute Technology Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia

Biopolymers developed for solid electrolyte materials of sodium-ion batteries are of great interest these days. The main precursor in the form of cellulose biopolymers has been successfully isolated from water hyacinths (Eichornia crassipes). The first stage is maceration using 2% NaOH to produce cellulose-Iα and Ethanol 60% to produce cellulose-Iβ by hydrothermal reaction process at 150 °C and continued at the bleaching stage with H2O2 solution at 50 °C until it changes color. Then the sample is washed to a neutral pH and dried in an oven at 60 °C. Cellulose-Iα yields were obtained with a yield of 33.98% and cellulose-Iβ of 39.11%. The cellulose-I that has been obtained is modified to obtain cellulose-II type by mercerization method, where cellulose-I type is reacted with 20% NaOH for 5 hours. The mixture is then washed to neutral and dried. Cellulose-II yield was obtained with a yield of 69.21%. Samples were characterized by XRD, FTIR, and SEM. The cellulose content of hyacinths before delignification was 36.69%. The cellulose content of hyacinths after delignification for cellulose-Iα and cellulose-Iβ types was 64.26% and 48.58% respectively. FTIR analysis proved the presence of hydroxyl and carboxyl functional groups in hyacinth cellulose. XRD analysis showed that all three samples were identified with cellulose-Iα, cellulose-Iβ, and cellulose-II amorphous structures with a crystallinity index of 28.62% and the largest crystallite size based on the hkl field (121) of cellulose-Iβ type samples was ∼10 nm. SEM analysis shows that cellulose-Iα, cellulose-Iβ has a slim fiber diameter size and straight, smooth surface and microfibrils around the fiber. While cellulose-II shows visualization of a diameter that looks larger and twisted, the surface is rough and there are no microfibrils around the fibers. © Published under licence by IOP Publishing Ltd.

关键词： Sodium hydroxide

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FedMoS: Taming Client Drift in Federated Learning with Double Momentum and Adaptive Selection 42

FedMoS: Taming Client Drift in Federated Learning with Doubl...

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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Wang, Xiong Chen, Yuxin Li, Yuqing Liao, Xiaofei Jin, Hai Li, Bo Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Wuhan China Wuhan University School of Cyber Science and Engineering Wuhan China Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350334142

Federated learning (FL) enables massive clients to collaboratively train a global model by aggregating their local updates without disclosing raw data. Communication has become one of the main bottlenecks that prolongs the training process, especially under large model variances due to skewed data distributions. Existing efforts mainly focus on either single momentum-based gradient descent, or random client selection for potential variance reduction, yet both often lead to poor model accuracy and system efficiency. In this paper, we propose FedMoS, a communication-efficient FL framework with coupled double momentum-based update and adaptive client selection, to jointly mitigate the intrinsic variance. Specifically, FedMoS maintains customized momentum buffers on both server and client sides, which track global and local update directions to alleviate the model discrepancy. Taking momentum results as input, we design an adaptive selection scheme to provide a proper client representation during FL aggregation. By optimally calibrating clients' selection probabilities, we can effectively reduce the sampling variance, while ensuring unbiased aggregation. Through a rigid analysis, we show that FedMoS can attain the theoretically optimal O(T - 2/3) convergence rate. Extensive experiments using real-world datasets further validate the superiority of FedMoS, with 58%-87% communication reduction for achieving the same target performance compared to state-of-the-art techniques. © 2023 IEEE.

关键词： Momentum

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Multi-Agent Based Stochastic Dynamical Model to Measure Community Resilience

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Journal of Social Computing 2022年第3期3卷 262-286页

作者： Jaber Valinejad Lamine Mili C.Natalie Van Der Wal Data and System Science Lab Harvard Medical SchoolHarvard UniversityCambridgeMA 02138USA Bradley Department of Electrical and Computer Engineering Virginia TechNorthern Virginia CenterFalls ChurchVA 22043USA Department of Multi-Actor Systems Faculty of TechnologyPolicy and ManagementDelft University of TechnologyDelft2600 AAthe Netherlands.

Emergency services and utilities need appropriate planning tools to analyze and improve infrastructure and community resilience to *** as a key metric of community resilience is the social well-being of a community during a disaster,which is made up of mental and physical social *** factors influencing community resilience directly or indirectly are emotional health,emergency services,and the availability of critical infrastructures services,such as food,agriculture,water,transportation,electric power,and communications *** turns out that in computational social science literature dealing with community resilience,the role of these critical infrastructures along with some important social characteristics is not *** address these weaknesses,we develop a new multi-agent based stochastic dynamical model,standardized by overview,design concepts,details,and decision(ODD+D)protocol and derived from neuro-science,psychological and social sciences,to measure community resilience in terms of mental and physical *** this model,we analyze the micro-macro level dependence between the emergency services and power systems and social characteristics such as fear,risk perception,informationseeking behaviour,cooperation,flexibility,empathy,and experience,in an artificial ***,we simulate this model in two case studies and show that a high level of flexibility,experience,and cooperation enhances community *** for both theory and practice are discussed.

关键词： community resilience collective behavior emergency services power systems critical infrastructures artificial society overview,design concepts,details,and decision(ODD+D) cyber-physical-social system

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IoT-Based Portable Fingerprint Attendance system Using the Minutiae Based Algorithm 7

IoT-Based Portable Fingerprint Attendance System Using the M...

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7th IEEE Information Technology International Seminar, ITIS 2021

作者： Idhom, Mohammad Purbasari, Intan Yuniar Fauzi, Akhmad Susrama Mas Diyasa, I Gede University of Pembangunan Nasional 'Veteran' Jawa Timur Department of Data Science Surabaya Indonesia University of Pembangunan Nasional 'Veteran' Jawa Timur Department of Informatics Engineering Surabaya Indonesia University of Pembangunan Nasional 'Veteran' Jawa Timur Department of Information System Surabaya Indonesia

ISBN: (纸本)9781665408073

Attendance really needs to be done in order to know the attendance and time of arrival and return of someone from employees or workers to the education system. Attendance, which at first was only done manually, like signatures on paper, has now become more advanced, which is done using an electronic device using a fingerprint presence system. by using the concept of the internet of things which facilitates the online presence system through a network such as wi-fi, as well as portable or can also be carried everywhere. This portable IoT fingerprint presence system (PoFAS-Class) uses the Algortima Minutiae Based method where the algorithm detects lines or strokes on each human fingerprint. The components to help the success of the tool are the Nodemcu ESP8266 as a Microcontroller, Fingerprint Sensor, TFT OLED Screen, Battery Charger Module, and Web Information to register fingerprints and to inform users. Tool testing is done using a sample of 240 users who are registered into the presence information system, and the average processing time used to register a user's fingerprint on the sensor is © 2021 IEEE.

关键词： Internet of things

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