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International Youth Conference on Radio Electronics, electrical and Power engineering (REEPE)

作者： Nam H. Pham Oleg N. Kuzetsov Canh T. Doan Electrical Power Systems Department National Research University “MPEI” Moscow Russian Federation Department of Electrical and Electronic Engineering Technology Institute of Engineering and Technology Vinh University Viet Nam Department of Relay Protection and Automation of Energy Systems National Research University “MPEI” Moscow Russian Federation Faculty of Engineering and Technology Hong Duc University Vietnam

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Photovoltaics (PV) play an essential role in energy networks by promoting clean, sustainable energy and reducing reliance on fossil fuels. However, their operational characteristics introduce new challenges, particularly concerning grid reliability and voltage stability. In this paper, the impact of solar photovoltaic plant (SPP) penetration on voltage behavior in the central region of Vietnam is examined using dynamic models at different integration levels, ranging from 0% to 40%. The results reveal that while low SPP penetration has minimal effects, high penetration levels (30% and 40%) significantly reduce reactive power support, exacerbating voltage collapse risks. These findings underscore the necessity for advanced voltage and reactive power control strategies to ensure grid stability in high-SPP scenarios.

关键词： Photovoltaic systems Reactive power Reactive power control Power system dynamics Power system stability Stability analysis Threshold voltage Synchronous generators Reliability Voltage control

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Towards Fast Automatic Design of Silicon Dangling Bond Logic

Towards Fast Automatic Design of Silicon Dangling Bond Logic

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Design, automation and Test in Europe Conference and Exhibition

作者： Jan Drewniok Marcel Walter Samuel Sze Hang Ng Konrad Walus Robert Wille Chair for Design Automation Technical University of Munich Germany Department of Electrical and Computer Engineering University of British Columbia Vancouver Canada Software Competence Center Hagenberg GmbH Austria

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

In recent years, Silicon Dangling Bond (SiDB) logic has emerged as a promising beyond-CMOS technology. Unlike conventional circuit technology, where logic is realized through transistors, SiDB logic utilizes quantum dots with variable charge states. By strategically arranging these dots, logic functions can be constructed. However, determining such arrangements is a tremendously complex task. Because of that, the automatic obtainment of SiDB logic implementations is inefficient. To address this challenge, we propose an idea to speed up the design process by utilizing dedicated search space pruning strategies. Initial results show that the combined pruning techniques yield 1) a drastic reduction of the search space, and 2) a corresponding reduction in runtime by up to a factor of 33.

关键词： Runtime Quantum dots Europe Logic gates Logic functions Silicon Logic Transistors Standards

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Arithmetic Optimization Algorithm with Machine Learning based Smart Irrigation System in IoT Environment 5

Arithmetic Optimization Algorithm with Machine Learning base...

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5th IEEE International Conference on electrical, computer and Communication Technologies, ICECCT 2023

作者： Aruna, M. Badari Narayana, Patel Kumar, S. Narasimha Ala Walid, Md. Abul Prasad Patra, Jyoti Kumar, B. Suresh NMIT Department of EEE Karnataka Bangalore India Mahatma Gandhi Institute of Technology Department of Mechanical Engineering TS Hyderabad India Chaitanya Bharati Institute of Technology Gandipet Mechanical Engineering Department Hyderabad India Department of Computer Science and Engineering Khulna9203 Bangladesh Faculty Electrical Odisha University of Technology and Research OUTR Mahalaxmi Vihar Ghatikia Techno Campus Odisha Bhubaneswar India Chaitanya Bharathi Institute of Technology Department of EEE Telangana Hyderabad India

ISBN: (纸本)9781665493604

An integration of new technologies like agro-hydroinformatics and computational intelligence, and information technology (IT) roles a vital play in developing a sustainable precision irrigation method with the effectual management of sensed data assuming plants, weather, and soil. Machine learning (ML) is a fast-developing technology for precision irrigation schemes, because of their capability to simulate human decision-making but also resolve the multi-variable, non-linear, and time-variant problems affecting irrigation management. An essential drive of ML is for providing data from preceding experiences and statistical data to machines towards it is carried out their allocated task of resolving a particular problem. Therefore, this study develops an Arithmetic Optimization Algorithm with Machine Learning based Smart irrigation system (AOAML-SIS) technique in IoT environment. Initially, the AOAML-SIS technique exploits the IoT sensors for data collection process. For determining the need for irrigation, the AOALM-SIS technique utilizes multilayer perceptron (MLP) classification model. Since the MLP parameters play a vital role, the parameter tuning process is carried out by the AOA algorithm. The experimental assessment of the AOAML-SIS technique takes place on agriculture data. The simulation values inferred the effectual irrigation classification efficacy of the AOAML-SIS technique over other models. © 2023 IEEE.

关键词： Machine learning

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GWSVM: A Robust GMM-Based Pattern Weighting for SVM

GWSVM: A Robust GMM-Based Pattern Weighting for SVM

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electrical, Energy, and Artificial Intelligence (EICEEAI), International engineering Conference on

作者： Mohammad R. Moosavi Ayman Amer Behrooz Nasihatkon Reza Boostani Department of Computer Science and Engineering and IT School of Electrical and Computer Engineering (Shiraz University) Shiraz Iran Faculty of Engineering Zarqa University Zarqa Jordan College of Engineering University of Business and Technology Jeddah Saudi Arabia Faculty of Computer Engineering (K.N Toosi University of Technology) Tehran Iran

ISBN: (数字)9798350373363

ISBN: (纸本)9798350373370

Support Vector Machine (SVM) is an efficient classifier due to its generalization capability; however, it suffers from high sensitivity to noisy data. A new weighted SVM classifier is proposed here to overcome this problem by a pattern weighting approach based on Gaussian Mixture Models (GMM), called hereinafter GWSVM. The weight learning is a procedure of knowledge extraction from the feature space. First, a clustering phase is carried out according to Gap Statistic and Subtractive Clustering (SC) methods. Then a GMM is trained using the clustered data and pattern weights are determined based on the GMM outputs. In the third phase, a redefined optimization formula regarding the weighted patterns is used, so SVM decision boundary is adjusted sensibly. GWSVM is applied to some UCI repository datasets and its performance is presented. The results show the supremacy of our novel classifier in comparison with other versions of SVM. Further, to evaluate robustness and generalization power of GWSVM, the impact of white noise with different variances is investigated. Applying GWSVM and SVM classifiers to noisy data manifests effectiveness of GWSVM in noisy environment.

关键词： Support vector machines Iris Sensitivity Mixture models White noise Feature extraction Vectors

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Reinforcement of Medical Image Security Through Steganography and Encryption Techniques

Reinforcement of Medical Image Security Through Steganograph...

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Electronic engineering (ICEEM), International Conference on

作者： Fatma Khallaf Walid El-Shafai El-Sayed M. El-Rabaie Fathi E. Abd El-Samie Department of Electronics and Communication Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Electrical Engineering Faculty of Engineering Ahram Canadian University Giza Egypt Department of Computer Science Security Engineering Laboratory Prince Sultan University Riyadh Saudi Arabia

Patients' data is stored in Electronic Health Records (EHRs) for confidentiality purposes. However, the insecure networks of hospitals and clinics puts patient information at risk. To address this ethical issue, secure communication is crucial. The Digital Imaging and Communications in Medicine (DICOM) standard governs the transmission of EHRs to maintain data integrity and confidentiality. This paper combines cryptography and steganography techniques to transmit medical information and images across hospital networks, securely. The introduced framework comprises encryption of patients' data using DNA-based Advanced Encryption Standard (AES), hiding the information within images using Least Significant Bit (LSB) embedding, compressing the stego images using Discrete Wavelet Transform (DWT), and reversal of the process at the receiver end. Simulation experiments demonstrate that this framework comprising both encryption and steganography outperforms existing methods in securing the medical data.

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A review of green hydrogen production based on solar energy;techniques and methods

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Energy Harvesting and Systems 2024年第1期11卷

作者： Hassan, Qusay Tabar, Vahid Sohrabi Sameen, Aws Zuhair Salman, Hayder M. Jaszczur, Marek Department of Mechanical Engineering University of Diyala Diyala Iraq Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran College of Medical Techniques Al-Farahidi University Baghdad Iraq Faculty of Energy and Fuels AGH University of Science and Technology Krakow Poland Department of Computer Science Al-Turath University College Baghdad Iraq

The study examines the methods for producing hydrogen using solar energy as a catalyst. The two commonly recognised categories of processes are direct and indirect. Due to the indirect processes low efficiency, excessive heat dissipation, and dearth of readily available heat-resistant materials, they are ranked lower than the direct procedures despite the direct procedures superior thermal performance. Electrolysis, bio photosynthesis, and thermoelectric photo-degradation are a few examples of indirect approaches. It appears that indirect approaches have certain advantages. The heterogeneous photocatalytic process minimises the quantity of emissions released into the environment;thermochemical reactions stand out for having low energy requirements due to the high temperatures generated;and electrolysis is efficient while having very little pollution created. Electrolysis has the highest exergy and energy efficiency when compared to other methods of creating hydrogen, according to the evaluation. © 2024 the author(s), published by De Gruyter.

关键词： Hydrogen production

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Diffusion-based Auction Mechanism for Efficient Resource Management in 6G-enabled Vehicular Metaverses

arXiv

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arXiv 2024年

作者： Kang, Jiawen Tong, Yongju Zhong, Yue Chen, Junlong Xu, Minrui Niyato, Dusit Deng, Runrong Mao, Shiwen School of Automation Guangdong University of Technology Guangzhou510006 China School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States

The rise of 6G-enable Vehicular Metaverses is transforming the automotive industry by integrating immersive, real-time vehicular services through ultra-low latency and high bandwidth connectivity. In 6G-enable Vehicular Metaverses, vehicles are represented by Vehicle Twins (VTs), which serve as digital replicas of physical vehicles to support real-time vehicular applications such as large Artificial Intelligence (AI) model-based Augmented Reality (AR) navigation, called VT tasks. VT tasks are resource-intensive and need to be offloaded to ground Base Stations (BSs) for fast processing. However, high demand for VT tasks and limited resources of ground BSs, pose significant resource allocation challenges, particularly in densely populated urban areas like intersections. As a promising solution, Unmanned Aerial Vehicles (UAVs) act as aerial edge servers to dynamically assist ground BSs in handling VT tasks, relieving resource pressure on ground BSs. However, due to high mobility of UAVs, there exists information asymmetry regarding VT task demands between UAVs and ground BSs, resulting in inefficient resource allocation of UAVs. To address these challenges, we propose a learning-based Modified Second-Bid (MSB) auction mechanism to optimize resource allocation between ground BSs and UAVs by accounting for VT task latency and accuracy. Moreover, we design a diffusion-based reinforcement learning algorithm to optimize the price scaling factor, maximizing the total surplus of resource providers and minimizing VT task latency. Finally, simulation results demonstrate that the proposed diffusion-based MSB auction outperforms traditional baselines, providing better resource distribution and enhanced service quality for vehicular users. Copyright © 2024, The Authors. All rights reserved.

关键词： Automotive industry

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Improved Metaheuristics with Machine Learning Enabled Medical Decision Support System

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computers, Materials & Continua 2022年第11期73卷 2423-2439页

作者： Sara A.Althubiti JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Romany F.Mansour Fayadh Alenezi Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Research Center-CIENS Escuela Naval de Suboficiales A.R.C.“Barranquilla”BarranquillaColombia Electronics and Telecommunications Engineering Program Universidad Autónoma del CaribeBarranquilla080001Colombia Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080001Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga 72511Egypt Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia

Smart healthcare has become a hot research topic due to the contemporary developments of Internet of Things(IoT),sensor technologies,cloud computing,and ***,the latest advances of Artificial Intelligence(AI)tools find helpful for decision-making in innovative healthcare to diagnose several *** Cancer(OC)is a kind of cancer that affects women’s ovaries,and it is tedious to identify OC at the primary stages with a high mortality *** OC data produced by the Internet of Medical Things(IoMT)devices can be utilized to differentiate *** this aspect,this paper introduces a new quantum black widow optimization with a machine learningenabled decision support system(QBWO-MLDSS)for smart *** primary intention of the QBWO-MLDSS technique is to detect and categorize the OC rapidly and ***,the QBWO-MLDSS model involves a Z-score normalization approach to pre-process the *** addition,the QBWO-MLDSS technique derives a QBWO algorithm as a feature selection to derive optimum feature ***,symbiotic organisms search(SOS)with extreme learning machine(ELM)model is applied as a classifier for the detection and classification of ELM model,thereby improving the overall classification *** design of QBWO and SOS for OC detection and classification in the smart healthcare environment shows the study’s *** experimental result analysis of the QBWO-MLDSS model is conducted using a benchmark dataset,and the comparative results reported the enhanced outcomes of the QBWO-MLDSS model over the recent approaches.

关键词： Ovarian cancer decision support system smart healthcare IoMT deep learning feature selection

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Software Quality Pre-Estimation Based on Time Series

Software Quality Pre-Estimation Based on Time Series

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International IEEE Conference and Workshop: Óbuda on electrical and Power engineering (CANDO-EPE)

作者： György Schuster Obuda University Budapest Hungary Department of Instrumentation and Automation Kando Kalman Faculty of Electrical Engineering Institute of Electronics and Communication Systems

The development of safety-critical software is crucial. This is particularly emphasized in areas where most or all of the tasks are entrusted to software. Errors in such software can have serious consequences, including life-threatening situations, economic damage, and other serious problems. This category includes on-board software for vehicles and autonomous vehicles, software for autonomous devices for space exploration, special industrial devices and weapons systems, etc. Choosing a software manufacturer is a serious challenge for the customer. Since we cannot apply the test methods of classic production processes in the case of software, we must therefore examine the manufacturer. It is quite clear that a specific manufacturer must have appropriate qualifications. But what if there are several manufacturers with the same certification and you have to choose between them.

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Development of ANFIS Controller for Trajectory Tracking Control Using ROBO2L MATLAB Toolbox for KUKA Industrial Robot via RSI

Development of ANFIS Controller for Trajectory Tracking Cont...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Mohamed Mousa Ahmad Al-Mahasneh Mohammed Baniyounis Rolf Biesenbach Jan Falkenhain Mechatronics Engineering Department Philadelphia University Amman Jordan Institute for Automation and Industry 4.0 Bochum University of Applied Sciences Bochum Germany Electrical Engineering and Computer Science Department Bochum University of Applied Sciences Bochum Germany

ISBN: (数字)9798350374131

ISBN: (纸本)9798350374148

A new control scheme is proposed in the MATLAB/Simulink environment based on ANFIS technology using ROBO2L MATLAB toolbox with RSI to control the motion of the real KUKA robot. In detail, the control system has two subsystems designed for trajectory tracking error regulation in closed-loop control. One is a fuzzy logic controller, and the other is an ANFIS controller. These two controllers were used to control the velocity of the KUKA robot located inside the Hochschule Bochum laboratory. The testing process for these controllers was done by switching between FLC and ANFIS controllers and then studying each response separately. The results were compared with a linear controller produced in Hochschule Bochum experiments. The ROBO2L MATLAB toolbox provides many functions, such as sending and receiving positions and rotation for the end effector via UDP/IP communication, which RSI established to provide remote control for the robot using a PC. This work mainly emphasizes the ability to track the trajectories supported by the robotics toolbox in smooth motion. After observing the simulation results, the comparison between the linear, FLC, and ANFIS controllers is confirmed. The performance of the proposed approach is efficient for trajectory tracking control for the manipulator.

关键词： Fuzzy logic Trajectory tracking Simulation Switches Control systems Trajectory Steady-state

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