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Modelling and simulation of energy management of power-split hybrid electric vehicles using the discrete EVent system specification

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International Journal of Vehicle Systems Modelling and Testing 2024年第1期18卷 33-61页

作者： Maatoug, Abdelfettah Kharoubi, Sahraoui Maaskri, Moustafa Belalem, Ghalem Mahmoudi, Said Faculty of Applied Sciences Science and Technology Department University of Tiaret Tiaret14000 Algeria Faculty of Mathematics and Computer Science Computer Science Department University of Tiaret Tiaret14000 Algeria Faculty of Applied Sciences Electrical Engineering Department University of Tiaret Tiaret14000 Algeria Faculty of Exact and Applied Sciences Computer Science Department University of Oran 1 Ahmed Ben Bella Oran31000 Algeria Faculty of Engineering Computer Science Department University of Mons Mons7000 Belgium

This work provides a basis for studying energy management optimisation in power-split hybrid electric vehicles (PSHEVs) to reduce fuel consumption and increase powertrain efficiency by enforcing a strategy related to battery level and vehicle speed. Three modes were used to operate the vehicle to meet different situations related to available energy and desired speed. These are particularly abundance mode, ascetic mode and optimal mode. For this, a system was designed based on several sub-models written in the discrete EVent system (DEVS) specification. The vehicle's power train and control strategy models were created in the DEVSimPy environment, and a joint simulation was carried out from the composite sub models until the overall model is reached. Simulation results under several driving cycles showed that the proposed system improves the energy consumption of the vehicle in different operating modes of the engines and gives more opportunities to adopt electric motors in vehicle transmission. © 2024 Inderscience Enterprises Ltd.

关键词： Energy management

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Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles

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computers, Materials & Continua 2023年第7期76卷 573-589页

作者： Halah Hasan Mahmoud Marwan Kadhim Mohammed Al-Shammari Gehad Abdullah Amran Elsayed Tag eldin Ala R.Alareqi Nivin A.Ghamry Ehaa A.Lnajjar Esmail Almosharea Computer Center University of BaghdadBaghdad6751Iraq Department of Management Science and Engineering Dalian University of TechnologyLiaoningDalian116024China Department of Information Technology Faculty of Computer Sciences and Information Technology AL Razi UniversitySana’aYemen Faculty of Engineering and Technology Future University in EgyptNew Cairo11835Egypt Faculty of Engineering Mechanics Dalian University of TechnologyLiaoningDalian116024China Faculty of Computers and Artificial Intelligence Cairo UniversityGizaEgypt Department of Business Administration Dalian University of TechnologyLiaoningDalian116024China College of Software Engineering Dalian University of TechnologyChina

Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial *** of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine *** study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity *** Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity *** research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical *** results suggest that detecting the submarine early increases the likelihood of averting a *** dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access *** communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the *** swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its ***,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other *** dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.

关键词： Unmanned vehicles unmanned aerial vehicles unmanned underwater vehicles high altitude unmanned aerial vehicles anti-submarine warfare re-fragmentation dragonfly algorithm

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EDU-GAN:Edge Enhancement Generative Adversarial Networks with Dual-Domain Discriminators for Inscription Images Denoising

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computers, Materials & Continua 2024年第7期80卷 1633-1653页

作者： Yunjing Liu Erhu Zhang Jingjing Wang Guangfeng Lin Jinghong Duan School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an710048China Department of Information Science Xi’an University of TechnologyXi’an710054China School of Faculty of Painting Packaging Engineering and Digital MediaXi’an University of TechnologyXi’an710048China School of Computer Science and Engineering Xi’an University of TechnologyXi’an710048China

Recovering high-quality inscription images from unknown and complex inscription noisy images is a challenging research *** fromnatural images,character images pay more attention to stroke ***,existingmodelsmainly consider pixel-level informationwhile ignoring structural information of the character,such as its edge and glyph,resulting in reconstructed images with mottled local structure and character *** solve these problems,we propose a novel generative adversarial network(GAN)framework based on an edge-guided generator and a discriminator constructed by a dual-domain U-Net framework,i.e.,*** existing frameworks,the generator introduces the edge extractionmodule,guiding it into the denoising process through the attention mechanism,which maintains the edge detail of the restored inscription ***,a dual-domain U-Net-based discriminator is proposed to learn the global and local discrepancy between the denoised and the label images in both image and morphological domains,which is helpful to blind denoising *** proposed dual-domain discriminator and generator for adversarial training can reduce local artifacts and keep the denoised character structure *** to the lack of a real-inscription image,we built the real-inscription dataset to provide an effective benchmark for studying inscription image *** experimental results show the superiority of our method both in the synthetic and real-inscription datasets.

关键词： Dual-domain discriminators inscription images denoising edge-guided generator

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Neutrosophic Sets and Systems: A Decade of Scientific Contribution and Growth

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Neutrosophic Sets and Systems 2025年 81卷 438-465页

作者： Saqlain, Muhammad Merigó, José M. Kumam, Poom Department of Mathematics King Mongkut’s University of Technology Thonburi Bangkok10140 Thailand School of Computer Science Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway UltimoNSW2007 Australia

Neutrosophic Sets and Systems (NSS) has become an important Journal for neutrosophic theory and its applications in uncertainty modeling and decision sciences. In 2023, NSS celebrated its 10th anniversary, marking a decade of contributions to scientific literature. Motivated by this event, this paper provides a critical bibliometric analysis of NSS’s evolution as a leading academic journal in neutrosophy. This study explores the publication trends, citation impact, most productive authors, institutions, and global collaboration networks of NSS. The study maps bibliographic coupling, keyword co-occurrence and co-citation analysis using data from the Scopus database, secondary search using NSS webpage, and visualization tools like the VOSviewer. The findings identify Neutrosophic Sets, Decision-Making, and Fuzzy Sets as the most frequently studied keywords that highlight the increasing integration of neutrosophic approaches into multi-criteria decision-making (MCDM) and soft computing. The results indicate the most significant areas of research that are topology, soft set theory, hypersoft sets, and uncertainty modeling. The findings highlight the NSS increasing international collaboration, with contributions from America, Middle East, and Asia. Additionally, the analysis explores NSS’s alignment with sustainable development goals (SDGs), revealing notable contributions to good health and well-being (SDG 3), quality education (SDG 4), and peace, justice, and strong institutions (SDG 16). These contributions highlight how neutrosophic sets and systems is valuable across many researchers, from public health to governance to education. Overall, this paper serves as a fundamental study for researchers looking to explore emerging trends and novel applications of neutrosophic theories across diverse scientific and practical domains. © 2025, University of New Mexico. All rights reserved.

关键词： Bibliographies

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Dynamic Trust Management and AI-Based Multi-Factor Authentication for 6G Machine Type Communications 1

Dynamic Trust Management and AI-Based Multi-Factor Authentic...

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1st International Conference on Advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Sinha, Garima Agarwal, Ankita Faculty of Engineering and Technology Department of Computer Science Engineering Ramnagar District Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331518578

New security concerns about the transmission of sensitive data over enormous networks of linked devices have arisen with the advent of the 6G era and the broad adoption of massive machine-type communication (MTC). The authors of this paper provide a fresh strategy for MFA and dynamic trust management in 6G networks that make use of AI to solve these issues and improve MTC security. This study presents a novel approach to behavioural profiling that takes into account the strengths and weaknesses of machine-type devices. It was necessary to create simulated data to represent many situations due to the wide range of possible network circumstances, device characteristics, ambient variables, applications load of work, and security needs. The efficacy of the suggested remedy was evaluated during six simulation cycles. The findings showed that the framework can adapt to changing network circumstances and device behaviours, with stability demonstrated across many situations. The accuracy rates for implementing MFA ranged from 0.49 to 0.57. This MFA and AI-driven dynamic trust management framework has great potential to improve 6G network MTC security;its adaptability and resilience provide a solid basis for meeting the security concerns that will inevitably arise in the future of 6G networks. To maximize performance and assure successful deployment, more modifications and real-life testing are suggested. © 2025 IEEE.

关键词： Authentication Protocol

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Hybrid robust fault detection and isolation of satellite reaction wheel actuators

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Journal of Control and Decision 2024年第1期11卷 117-131页

作者： H.Abbasi Nozari S.J.Sadati Rostami Paolo Castaldi Silvio Simani Faculty of Electrical and Computer Engineering Babol Noshirvani University of TechnologyBabolIran Department of Electrical Electronic and Information EngineeringUniversity of BolognaCesenaItaly Department of Engineering University of FerraraFerraraItaly

In this paper,a combined robust fault detection and isolation scheme is studied for satellite system subject to actuator faults,external disturbances,and parametric *** proposed methodology incorporates a residual generation module,including a bank of filters,into an intelligent residual evaluation ***,residual filters are designed based on an improved nonlinear differential algebraic approach so that they are not affected by external *** residual evaluation module is developed based on the suggested series and parallel ***,a new ensemble classification scheme defined as blended learning integrates heterogeneous classifiers to enhance the performance.A wide range of simulations is carried out in a high-fidelity satellite simulator subject to the constant and time-varying actuator faults in the presence of disturbances,manoeuvres,uncertainties,and *** obtained results demonstrate the effectiveness of the proposed robust fault detection and isolation method compared to the traditional nonlinear differential algebraic approach.

关键词： Robust fault detection and isolation reaction wheels blended learning series and parallel fault detection and isolation forms satellite attitude control system

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Wind Power Prediction Based on Machine Learning and Deep Learning Models

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computers, Materials & Continua 2023年第1期74卷 715-732页

作者： Zahraa Tarek Mahmoud Y.Shams Ahmed M.Elshewey El-Sayed M.El-kenawy Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Mohamed A.El-dosuky Faculty of Computers and Information Computer Science DepartmentMansoura UniversityMansoura35561Egypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt Faculty of Computers and Information Computer Science DepartmentSuez UniversitySuezEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Arab East CollegesRiyadh13544Saudi Arabia

Wind power is one of the sustainable ways to generate renewable *** recent years,some countries have set renewables to meet future energy needs,with the primary goal of reducing emissions and promoting sustainable growth,primarily the use of wind and solar *** achieve the prediction of wind power generation,several deep and machine learning models are constructed in this article as base *** regression models are Deep neural network(DNN),k-nearest neighbor(KNN)regressor,long short-term memory(LSTM),averaging model,random forest(RF)regressor,bagging regressor,and gradient boosting(GB)*** addition,data cleaning and data preprocessing were performed to the *** dataset used in this study includes 4 features and 50530 *** accurately predict the wind power values,we propose in this paper a new optimization technique based on stochastic fractal search and particle swarm optimization(SFSPSO)to optimize the parameters of LSTM *** evaluation criteria were utilized to estimate the efficiency of the regression models,namely,mean absolute error(MAE),Nash Sutcliffe Efficiency(NSE),mean square error(MSE),coefficient of determination(R2),root mean squared error(RMSE).The experimental results illustrated that the proposed optimization of LSTM using SFS-PSO model achieved the best results with R2 equals 99.99%in predicting the wind power values.

关键词： Prediction of wind power data preprocessing performance evaluation

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Sliding mode control of three-phase AC/DC converters using exponential rate reaching law

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Journal of Systems engineering and Electronics 2022年第1期33卷 210-221页

作者： JEERANANTASIN Narin NUNGAM Suksun Department of Electrical and Computer Engineering Faculty of EngineeringKing Mongkut’s University of Technology North BangkokBangkok 10800Thailand

Sliding mode control(SMC) becomes a common tool in designing robust nonlinear control systems, due to its inherent characteristics such as insensitivity to system uncertainties and fast dynamic *** modes are involved in the SMC operation, namely reaching mode and sliding *** the reaching mode, the system state is forced to reach the sliding surface in a finite *** major drawback of the SMC approach is the occurrence of chattering in the sliding mode, which is undesirable in most ***, the trade-off between chattering reduction and fast reaching time must be considered in the conventional SMC *** paper proposes SMC design with a novel reaching law called the exponential rate reaching law(ERRL) to reduce chattering, and the control structure of the converter is designed based on the multiinput SMC that is applied to a three-phase AC/DC power *** simulation and experimental results show the effectiveness of the proposed technique.

关键词： exponential rate reaching law(ERRL) multi-input sliding mode control(SMC) chattering reduction three-phase AC-to-DC converter

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ResNet50-Based Deep Learning Model for Lung Disease Detection

ResNet50-Based Deep Learning Model for Lung Disease Detectio...

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2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Hajbe, Janhavi R. Patle, Sneha K. Talvekar, Shreya V. Khonde, Tanvi W. Yesankar, Prajyot R. Faculty of Engineering and Technology Department of Computer Science & Design Sawangi Maharashtra Wardha442001 India

ISBN: (纸本)9798331509828

By enabling a highly accurate examination of the chest x-ray, deep learning, for example, is changing the methods of recognizing lung disorders. In order to classify lung diseases, such as bacterial pneumonia, viral pneumonia, TB, and COVID-19, this work describes the use of ResNet50, a kind of CNN and a deep learning technique. We prove the potential of deep learning to discern these diseases from the two conventional approaches and most importantly, the patterns one could implicitly observe. The article also discusses the challenges that deep learning may pose on to the healthcare industry including data privacy, availability of data and the issue of overfitting. The paper links with this part by looking at the future of this area of specialization, which includes;multimodal fusion, operational AI, real-time identification, personalized care, data issues, and concerns, and ethics. But if deep learning is successful in addressing all the above-discussed challenges then it can bring the situation to the real world where the identification of lung diseases happens in a previous phase which in turn results in better treatment procedures and higher patient outcomes. © 2025 IEEE.

关键词： Lung cancer

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Comparing Centralized and Decentralized Storage in Microgrids: Implications for Consumer Behavior 28

Comparing Centralized and Decentralized Storage in Microgrid...

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28th International Electrical Power Distribution Conference, EPDC 2024

作者： Dousti, Hazhir Hagh, Mehrdad Tarafdar Jirdehi, Mehdi Ahmadi Kermanshah University of Technology Faculty of Electrical Engineering Department of Electrical Engineering Kermanshah Iran University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran

ISBN: (纸本)9798350385502

Due to the increase in demand for electricity, the lack of fossil fuels, and the use of renewable energy sources, the use of energy storage systems becomes necessary. The use of storage systems in different parts of microgrids has countless advantages. These benefits include improving the overall efficiency of the system, increasing the stability of the network, the possibility of optimal control strategies at both the national and regional levels and the effective identification of vulnerabilities in the system. This paper focuses on the issue of coordinated and optimal energy management in a microgrid, especially when dealing with centralized and decentralized storage. This study simultaneously examines the impact of the presence of storage systems in both centralized and decentralized modes, as well as the creation of incentive policies to reduce demand. It examines the interaction between these two factors and their effects on cost reduction and overall network voltage deviation. The work has been done on a standard IEEE network with 69 buses using MATLAB software. It has been shown that in the presence of decentralized energy storage, network performance and consumer consumption are better, and network losses and voltage deviations are also reduced. © 2024 IEEE.

关键词： Renewable energy

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