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1st IEEE Afro-Mediterranean Conference on Artificial Intelligence, AMCAI 2023

作者： Boukhris, Abdelouafi Antari, Jilali Asri, Hiba Sadiq, Abderrahmane Ibn Zohr University Laboratory of Computer Systems Engineering Mathematics and Applications Polydisciplinary Faculty of Taroudant Taroudant Morocco LISI Laboratory Faculty of Sciences Semlalia Department of Computer Sciences Marrakech Morocco

ISBN: (纸本)9798350394689

Plant diseases negatively affect crop production;the quality and the quantity of crop production are being interrupted. Identifying diseases manually is a hard task and time consuming, also the majority of farmers don't have the necessary knowledge to do this operation. So, we need agriculture engineer which are rare. To address these issues, we need an accurate and automated detection system for crop disease. A new technique based on deep learning to detect crop disease is required. In this paper, we propose a new technique called ALS-NN (Autoencoder Latent Space-Neural network) which combines two models Autoencoder and Neural Network. The Autoencoder compress data into Latent Space representation, and the Neural Network is used for classification based on compressed data. The dataset used in this paper is PlantVillage with 4 types of Tomato diseases. Our system achieved 91% accuracy. © 2023 IEEE.

关键词： Deep learning

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An Injection Circuit Coupling Low-DC Voltage Impedance Matching system With Flexible Resonance Points for Square-Wave Voltage Power Amplifier in EM Exploration

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IEEE Transactions on Power Electronics 2025年第8期40卷 11032-11050页

作者： Pang, Ying Zhu, Yongji Ji, Yanju Li, Gang Xiang, Zeng Gong, Cheng Han, Rong Tian, Wei Guo, Qun Wong, Man-Chung Lin, Jun Jilin University State Key Laboratory of Deep Earth Exploration and Imaging College of Instrumentation and Electrical Engineering Changchun130026 China Jilin University College of Instrumentation and Electrical Engineering Changchun130021 China Tongda Electromagnetic Energy Company Ltd. Changsha410000 China University of Macau State Key Laboratory of Analog and Mixed-Signal VLSI 999078 China University of Macau Institute of Microelectronics 999078 China University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology 999078 China Dalian University of Technology School of Optoelectronic Engineering and Instrumentation Science Dalian116024 China Guangxi University School of Electrical Engineering Nanning530000 China Dalian Maritime University College of Marine Electrical Engineering Dalian116000 China University of Macau State Key Laboratory of Internet of Things for Smart City 999078 China

This article focuses on reactive power compensation and impedance matching of square-wave voltages. Square-wave voltage is the operating voltage in electromagnetic method (EM) exploration. The characteristics of a square-wave voltage are very different from those of a sinusoidal voltage in the power grid. Although some papers proposed impedance matching converters for square-wave voltages, they solved the high dc voltage requirement problem. The problem is caused by square-wave voltage having multiple and variable spectral components. An impedance-matching converter with an injection circuit (IMFR) for square-wave voltage is proposed. IMFR is composed of a thyristor-controlled inductor and capacitor (TCLC) part and injection circuit coupling active H-bridge part. TCLC can be controlled to resonate at the highest energy fundamental frequency for damping the largest part of the dc voltage requirement. The use of TCLC offsets the varying fundamental frequency demand on the dc voltage. First, this article gives a joint design and optimization approach for the lowest dc voltage requirement. Second, a synergistic control method of proposed IMFR is provided implementing IMFR. Third, two groups of comparative experiments show that the proposed IMFR can enlarge the current by 11.8%-38.5%. The effect on the current increase is 4.4%-7.9% higher than using only the H-bridge of the previous method when they are operated with the same dc voltage. © 1986-2012 IEEE.

关键词： Natural frequencies

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BHJO: A Novel Hybrid Metaheuristic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfish Search Optimizers for Solving engineering Design Problems

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computer Modeling in engineering & Sciences 2024年第10期141卷 219-265页

作者： Farouq Zitouni Saad Harous Abdulaziz S.Almazyad Ali Wagdy Mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer Science and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer Science College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China

Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BHJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,HBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BHJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BHJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BHJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BHJOalgorithmabout its counterparts,shedd

关键词： Global optimization hybridization of metaheuristics beluga whale optimization honey badger algorithm jellyfish search optimizer chaotic maps opposition-based learning

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Hybrid Metaheuristics Feature Selection with Stacked Deep Learning-Enabled Cyber-Attack Detection Model

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computer systems Science & engineering 2023年第5期45卷 1679-1694页

作者： Mashael M Asiri Heba G.Mohamed Mohamed K Nour Mesfer Al Duhayyim Amira Sayed A.Aziz Abdelwahed Motwakel Abu Sarwar Zamani Mohamed I.Eldesouki Department of Computer Science College of Science&Art atMahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Due to exponential increase in smart resource limited devices and high speed communication technologies,Internet of Things(IoT)have received significant attention in different application ***,IoT environment is highly susceptible to cyber-attacks because of memory,processing,and communication *** traditional models are not adequate for accomplishing security in the IoT environment,the recent developments of deep learning(DL)models find *** study introduces novel hybrid metaheuristics feature selection with stacked deep learning enabled cyber-attack detection(HMFS-SDLCAD)*** major intention of the HMFS-SDLCAD model is to recognize the occurrence of cyberattacks in the IoT *** the preliminary stage,data pre-processing is carried out to transform the input data into useful *** addition,salp swarm optimization based on particle swarm optimization(SSOPSO)algorithm is used for feature selection ***,stacked bidirectional gated recurrent unit(SBiGRU)model is utilized for the identification and classification of ***,whale optimization algorithm(WOA)is employed for optimal hyperparameter optimization *** experimental analysis of the HMFS-SDLCAD model is validated using benchmark dataset and the results are assessed under several *** simulation outcomes pointed out the improvements of the HMFS-SDLCAD model over recent approaches.

关键词： Cyberattacks security deep learning internet of things feature selection data classification

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Numerical Modelling of The system of Doubly Nonlinear Diffusion Equations with Convective Transfer and Damping

Numerical Modelling of The System of Doubly Nonlinear Diffus...

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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Sadullaeva, Shakhlo Azimbaevna Anarova, Shahzoda Amanbayevna Khaydarov, Abdugaffor Fayzullayeva, Zarnigor Nazirova, Dilorom Mirkhodzhaeva, Nazhiba departament Intellegent systems Joint Belarusian-Uzbek Intersectoral Institute of Applied Technical Qualifications Tashkent Uzbekistan Department of Convergence of Digital Technologies Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis National University of Uzbekistan Tashkent Uzbekistan Department of Informatics Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis NUUz Tashkent Uzbekistan

ISBN: (纸本)9798400716928

Currently, studies of double nonlinear equations and systems of double nonlinear equations representing many processes found in nature are considered relevant and necessary. These equations and systems, as a rule, are nonlinear, degenerate, and have properties that are absent in linear theory and therefore make them quite difficult for both analytical and numerical analysis of the solution. For this reason, great attention is paid to the research of nonlinear mathematical models, the construction of efficient numerical solution schemes and algorithms, and the creation of software using the capabilities of computer technologies. In this article, the mathematical model of the diffusion process in a two-component nonlinear medium under the influence of time-dependent convective transfer and damping is studied. The calculation scheme, algorithm, and software for nonlinear problems were developed. Based on a study of the qualitative properties of a nonlinear mathematical model of a reaction-diffusion system, computer modeling of reaction-diffusion processes was carried out. The developed computational schemes, algorithms, and software packages for solving systems of parabolic equations with double nonlinearity provide high productivity in studying the theory and processes of numerical solutions of such problems. © 2024 ACM.

关键词： Nonlinear equations

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DNBP-CCA:A Novel Approach to Enhancing Heterogeneous Data Traffic and Reliable Data Transmission for Body Area Network

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computers, Materials & Continua 2024年第5期79卷 2851-2878页

作者： Abdulwadood Alawadhi Mohd.Hasbullah Omar Abdullah Almogahed Noradila Nordin Salman A.Alqahtani Atif M.Alamri InterNetWorks Research Laboratory School of ComputingUniversiti Utara MalaysiaSintok06010Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaParit RajaJohor86400Malaysia School of Games&Creative Technology University for the Creative ArtsFarnhamGU97DSUK Computer Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, includingcontention during finite backoff periods, association delays, and traffic channel access through clear channelassessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions,and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propose Dynamic Next Backoff Period and Clear ChannelAssessment (DNBP-CCA) schemes to address these issues. The DNBP-CCA schemes leverage a combination ofthe Dynamic Next Backoff Period (DNBP) scheme and the Dynamic Next Clear Channel Assessment (DNCCA)scheme. The DNBP scheme employs a fuzzy Takagi, Sugeno, and Kang (TSK) model’s inference system toquantitatively analyze backoff exponent, channel clearance, collision ratio, and data rate as input parameters. Onthe other hand, the DNCCA scheme dynamically adapts the CCA process based on requested data transmission tothe coordinator, considering input parameters such as buffer status ratio and acknowledgement ratio. As a result,simulations demonstrate that our proposed schemes are better than some existing representative approaches andenhance data transmission, reduce node collisions, improve average throughput, and packet delivery ratio, anddecrease average packet drop rate and packet delay.

关键词： Internet of Medical Things body area networks backoff period tsk fuzzy model clear channel assessment media access control

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A Cooperative Co-Evolution Algorithm with Variable-Importance Grouping for Large-Scale Optimization 13

A Cooperative Co-Evolution Algorithm with Variable-Importanc...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Li, Yongfeng Zhang, Yuze Ma, Lijia Ji, Junkai Liu, Dugang Leung, Victor C. M. Li, Jianqiang Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Guangdong Laboratory of Artificial Intelligence and Digital Economy Shenzhen518123 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China The University of British Columbia Department of Electrical and Computer Engineering VancouverV6T 1Z4 Canada

ISBN: (纸本)9798350308365

Cooperative co-evolution (CC) is a promising direction in solving large-scale multiobjective optimization problems (LMOPs). However, most existing methods of grouping decision variables face some difficulties when searching in the huge search space. Specifically, the methods of grouping decision variables can be classified into two types, i.e., high-consumption grouping methods and non-consumption grouping methods. On the one hand, the former ones divide the decision variables into different groups based on the correlation analysis between variables, which consume much evaluation. This way may lead to premature convergence within limited computational resources. On the other hand, the later ones allocate the decision variables into sub-groups based on some metrics, e.g., order and size, which consume no evaluation while may cause the search fall into local optima. To alleviate the above issues, this paper proposes a CC-based algorithm with a variable-importance grouping (VIG) method, called VICCA. Firstly, the decision variables are classified into several subgroups according to their importance quantified by a meta-gene construction method. Secondly, a CC strategy is designed to simultaneously optimize all subgroups of decision variables formed by VIG using the differential evolution operator, which aims to accelerate the convergence speed. Thirdly, a global evolutionary strategy is proposed to optimize original decision variable space by the competitive swarm optimizer, aiming to maintain the diversity. Finally, the experiments demonstrate that our proposed VICCA has the significant advantage in solving LMOPs when compared with state-of-the-art evolutionary algorithms. © 2024 IEEE.

关键词： Optimization algorithms

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Smart transmission matrix measurement of multimode fibers using digital holography and deep learning for confidential data transmission

Smart transmission matrix measurement of multimode fibers us...

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digital Holography and Three-Dimensional Imaging, DH 2022

作者： Rothe, Stefan Zhang, Qian Pohle, Dennis Koukourakis, Nektarios Czarske, Juergen W. TU Dresden Faculty of Electrical and Computer Engineering Laboratory of Measurement and Sensor System Technique Dresden01062 Germany

We present smart measurements of the transmission matrix of multimode fibers (MMF). The modal crosstalk of the MMF is exploited by authorized communication participants against an eavesdropper towards physical layer s... 详细信息

ISBN: (纸本)9781957171128

关键词： Multimode fibers

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Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1262-1272页

作者： Mingming Ha Ding Wang Derong Liu School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Faculty of Information Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent Systemthe Beijing Laboratory of Smart Environmental Protectionand the Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA IEEE

The core task of tracking control is to make the controlled plant track a desired *** traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps *** this paper,a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control *** the regulator problem,the iterative value function of tracking control problem cannot be regarded as a Lyapunov function.A novel stability analysis method is developed to guarantee that the tracking error converges to *** discounted iterative scheme under the new cost function for the special case of linear systems is ***,the tracking performance of the present scheme is demonstrated by numerical results and compared with those of the traditional approaches.

关键词： Adaptive critic design adaptive dynamic programming(ADP) approximate dynamic programming discrete-time nonlinear systems reinforcement learning stability analysis tracking control value iteration(VI)

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Surface-functionalized design of blood-contacting biomaterials for preventing coagulation and promoting hemostasis

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Friction 2023年第8期11卷 1371-1394页

作者： Yi WANG Weijie ZHAI Shujie CHENG Jinghua LI Hongyu ZHANG State Key Laboratory of Tribology in Advanced Equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China Basic Research Key Laboratory of General Surgery for Digital Medicine Affiliated Hospital of Hebei UniversityBaoding 071000China Beijing Key Laboratory of Advanced Manufacturing Technology Faculty of Materials and ManufacturingBeijing University of TechnologyBeijing 100124China

The anticoagulation and hemostatic properties of blood-contacting materials are opposite lines of research, but their realization mechanisms are inspired by each other. Contact between blood and implantable biomaterials is a classic problem in tribological research, as both antithrombotic and hemostatic materials are closely associated with this problem. Thrombus formation on the surfaces of blood-contacting biomedical devices can detrimentally affect their performance and patient life, so specific surface functionalization is required. Currently, intensive research has focused on the development of super-lubricated or super-hydrophobic coatings, as well as coatings that deliver antithrombotic drugs. In addition, hemostatic biomaterials with porous structures, biochemical substances, and strongly adhesive hydrogels can be used to achieve rapid and effective hemostasis via physical or biochemical mechanisms. This article reviews methods of preparing anticoagulant coatings on material surfaces and the current status of rapid hemostatic materials. It also summarizes fundamental concepts for the design and synthesis of anticoagulant and hemostatic materials by discussing thrombosis and hemostasis mechanisms in biomedical devices and normal organisms. Because there are relatively few reports reviewing the progress in surface-functionalized design for anticoagulation and hemostasis, it is anticipated that this review can provide a useful summary of the applications of both bio-adhesion and bio-lubrication techniques in the field of biomedical engineering.

关键词： anticoagulation hemostasis lubrication hydrogel fibrous membrane

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