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Hydroelectric and Hydrogen Storage Systems for Electric Energy Produced from Renewable Energy Sources

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Energy Engineering 2024年第10期121卷 2719-2741页

作者： Saif Serag Adil Echchelh Biagio Morrone department of Engineering Universitàdella Campania“Luigi Vanvitelli”Aversa(CE)81031Italy Laboratory of electronics Treatment information Mechanic and EnergeticUniversity of Ibn TofailKenitra14000Morocco

Renewable energy sources are essential formitigating the greenhouse effect and supplying energy to resource-scarce ***,their intermittent nature necessitates efficient storage solutions to enhance system efficiency and manage energy *** paper investigates renewable and clean storage systems,specifically examining the storage of electricity generated from renewable sources using hydropower plants and hydrogen,both of which are highly efficient and promising for future energy production and *** study utilizes extensive literature data to analyze the impact of various parameters on the cost per kWh of electricity production in hybrid renewable systems incorporating hydropower and hydrogen storage *** indicate that these hybrid systems can store electricity efficiently and cost-effectively,with production costs ranging from 0.126 to 0.3$/kWh for renewablehydropower systems and 0.118 to 0.42$/kWh for renewable-hydrogen systems,with expected cost reductions over the next decade due to technological advancements and increased market *** novelty of this study lies in its comprehensive comparison of hybrid renewable systems integrating hydropower and hydrogen storage,providing detailed cost analysis and future *** identifies key parameters influencing the cost and efficiency of these systems,offering insights into optimizing storage solutions for renewable ***,this research underscores the potential of hybrid systems to reduce dependency on fossil fuels,particularly during peak demand periods,and emphasizes the importance of seasonal and geographic considerations in selecting energy *** study highlights the importance of policy support and investment in hybrid renewable systems and calls for further research into optimizing these systems for different seasonal and geographic ***,the integration of renewable energy sources with hydropower and hydrogen storage offers a promising pathwa

关键词： Energy storage hydropower hydrogen renewable energy hybrid system

Multispectral point cloud superpoint segmentation

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Science China(Technological Sciences) 2024年第4期67卷 1270-1281页

作者： WANG QingWang WANG MingYe ZHANG ZiFeng SONG Jian ZENG Kai SHEN Tao GU YanFeng Faculty of information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Computer Technologies Application Kunming 650500China School of electronics and information Engineering Harbin Institute of TechnologyHarbin 150001China

The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing superpoint segmentation methods focus only on local geometric structures,resulting in inconsistent spectral features of points within a *** feature inconsistencies degrade the performance of subsequent ***,this study proposes a novel Superpoint Segmentation method that jointly utilizes spatial Geometric and Spectral information for multispectral point cloud superpoint segmentation(GSI-SS).Specifically,a similarity metric that combines spatial geometry and spectral information is proposed to facilitate the consistency of geometric structures and object attributes within segmented *** the formation of the primary superpoints,an intersuperpoint pointexchange mechanism that maximizes feature consistency within the final superpoints is *** are conducted on two real multispectral point cloud datasets,and the proposed method achieved higher recall,precision,F score,and lower global consistency and feature classification *** experimental results demonstrate the superiority of the proposed GSI-SS over several state-of-the-art methods.

关键词： multispectral point cloud superpoint segmentation over-segmentation spatial-spectral joint metric

State-of-charge Balance Control and Safe Region Analysis for Distributed Energy Storage Systems with Constant Power Loads

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1733-1745页

作者： Yijing Wang Yangzhen Zhang Zhiqiang Zuo Xialin Li department of Electrical and information Engineering Tianjin UniversityTianjin 300384China

This paper presents a fully distributed state-of-charge balance control (DSBC) strategy for a distributed energy storage system (DESS). In this framework, each energy storage unit (ESU) processes the state-of-charge (SoC) information from its neighbors locally and adjusts the virtual impedance of the droop controller in real-time to change the current sharing. It is shown that the SoC balance of all ESUs can be achieved. Due to virtual impedance, voltage deviation of the bus occurs inevitably and increases with load power. Meanwhile, widespread of the constant power load (CPL) in the power system may cause instability. To ensure reliable operation of DESS under the proposed DSBC, the concept of the safe region is put forward. Within the safe region, DESS is stable and voltage deviation is acceptable. The boundary conditions of the safe region are derived from the equivalent model of DESS, in which stability is analyzed in terms of modified Brayton-Moser's criterion. Both simulations and hardware experiments verify the accuracy of the safe region and effectiveness of the proposed DSBC strategy.

关键词： Constant power load(CPL) distributed control distributed energy storage system(DESS) safe region state-of-charge(SoC)

Scientific Elegance in NIDS: Unveiling Cardinality Reduction, Box-Cox Transformation, and ADASYN for Enhanced Intrusion Detection

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Computers, Materials & Continua 2024年第6期79卷 3897-3912页

作者： Amerah Alabrah department of information Systems College of Computer and information Sciences King Saud UniversityRiyadh11451Saudi Arabia

The emergence of digital networks and the wide adoption of information on internet platforms have given rise to threats against users’private *** intruders actively seek such private data either for sale or other inappropriate ***,national and international organizations have country-level and company-level private information that could be accessed by different network ***,the need for a Network Intruder Detection System(NIDS)becomes essential for protecting these networks and *** the evolution of NIDS,Artificial Intelligence(AI)assisted tools and methods have been widely adopted to provide effective ***,the development of NIDS still faces challenges at the dataset and machine learning levels,such as large deviations in numeric features,the presence of numerous irrelevant categorical features resulting in reduced cardinality,and class imbalance in multiclass-level *** address these challenges and offer a unified solution to NIDS development,this study proposes a novel framework that preprocesses datasets and applies a box-cox transformation to linearly transform the numeric features and bring them into closer *** reduction was applied to categorical features through the binning ***,the class imbalance dataset was addressed using the adaptive synthetic sampling data generation ***,the preprocessed,refined,and oversampled feature set was divided into training and test sets with an 80–20 ratio,and two experiments were *** Experiment 1,the binary classification was executed using four machine learning classifiers,with the extra trees classifier achieving the highest accuracy of 97.23%and an AUC of *** Experiment 2,multiclass classification was performed,and the extra trees classifier emerged as the most effective,achieving an accuracy of 81.27%and an AUC of *** results were evaluated based on training,testing,and total time,and a com

关键词： Adaptive synthetic sampling class imbalance features cardinality network security over sampling

Control of GaN inverted pyramids growth on c-plane patterned sapphire substrates

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Journal of Semiconductors 2024年第6期45卷 92-96页

作者： Luming Yu Xun Wang Zhibiao Hao Yi Luo Changzheng Sun Bing Xiong Yanjun Han Jian Wang Hongtao Li Lin Gan Lai Wang Beijing National Research Center for information Science and Technology Department of Electronic EngineeringTsinghua UniversityBei-jing 100084China Center for Flexible electronics Technology Tsinghua UniversityBeijing 100084China

Growth of gallium nitride(GaN)inverted pyramids on c-plane sapphire substrates is benefit for fabricating novel devices as it forms the semipolar *** this work,GaN inverted pyramids are directly grown on c-plane patterned sapphire substrates(PSS)by metal organic vapor phase epitaxy(MOVPE).The influences of growth conditions on the surface morphol-ogy are experimentally studied and explained by Wulff *** competition of growth rate among{0001},{1011},and{1122}facets results in the various surface morphologies of GaN.A higher growth temperature of 985 ℃ and a lowerⅤ/Ⅲratio of 25 can expand the area of{}facets in GaN inverted *** the other hand,GaN inverted pyramids with almost pure{}facets are obtained by using a lower growth temperature of 930℃,a higherⅤ/Ⅲratio of 100,and PSS with pattern arrangement perpendicular to the substrate primary flat.

关键词： inverted pyramids GaN MOVPE crystal growth competition model

Joint position optimization,user association,and resource allocation for load balancing in UAV-assisted wireless networks

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Digital Communications and Networks 2024年第1期10卷 25-37页

作者： Daosen Zhai Huan Li Xiao Tang Ruonan Zhang Haotong Cao School of electronics and information Northwestern Polytechnical UniversityXian710072China State Key Laboratory of Integrated Services Networks Xidian UniversityXian710071China department of Computing Hong Kong Polytechnic UniversityHong Kong SARChina

Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum *** tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded *** fully exploit its potential,we jointly optimize the UAV position,user association,spectrum allocation,and power allocation to maximize the sum-log-rate of all users in two adjacent *** tackle the complicated joint optimization problem,we first design a genetic-based algorithm to optimize the UAV ***,we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method,so as to obtain the optimal user association and spectrum allocation *** further propose an iterative power allocation algorithm based on the sequential convex approximation *** simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput,and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.

关键词： Load balance Unmanned aerial vehicle Userassociation Resource management

A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

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Computers, Materials & Continua 2024年第6期79卷 4081-4105页

作者： Yasser Hachaichi Ayman E.Khedr Amira M.Idrees College of Computing and information Technology at Khulais Department of Information SystemsUniversity of JeddahJeddah21959Saudi Arabia Faculty of Computers and information Technology Future University in EgyptCairo11835Egypt

The diversity of data sources resulted in seeking effective manipulation and *** challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of *** of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search *** research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO *** the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain *** proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant *** confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve ***,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different *** proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

关键词： Optimization particle swarm optimization algorithm feature selection logistics supply chain management backlogs

Cloud‐based video streaming services:Trends,challenges,and opportunities

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 265-285页

作者： Tajinder Kumar Purushottam Sharma Jaswinder Tanwar Hisham Alsghier Shashi Bhushan Hesham Alhumyani Vivek Sharma Ahmed I.Alutaibi CSE department JMIETIYamunanagarHaryanaIndia department of information Technology ASETAmity University Uttar PradeshNoidaIndia Tata Communications Limited New DelhiIndia department of information Technology College of Computer and Information SciencesMajmaah UniversityMajmaahSaudi Arabia Amity School of Engineering and Technology Amity UniversityPatnaBiharIndia department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityMajmaahSaudi Arabia

Cloud computing has drastically changed the delivery and consumption of live streaming *** designs,challenges,and possible uses of cloud computing for live streaming are studied.A comprehensive overview of the technical and business issues surrounding cloudbased live streaming is provided,including the benefits of cloud computing,the various live streaming architectures,and the challenges that live streaming service providers face in delivering high‐quality,real‐time *** different techniques used to improve the performance of video streaming,such as adaptive bit‐rate streaming,multicast distribution,and edge computing are discussed and the necessity of low‐latency and high‐quality video transmission in cloud‐based live streaming is *** such as improving user experience and live streaming service performance using cutting‐edge technology,like artificial intelligence and machine learning are *** addition,the legal and regulatory implications of cloud‐based live streaming,including issues with network neutrality,data privacy,and content moderation are *** future of cloud computing for live streaming is examined in the section that follows,and it looks at the most likely new developments in terms of trends and *** technology vendors,live streaming service providers,and regulators,the findings have major policy‐relevant *** on how stakeholders should address these concerns and take advantage of the potential presented by this rapidly evolving sector,as well as insights into the key challenges and opportunities associated with cloud‐based live streaming are provided.

关键词： cloud computing video analysis video coding

Joint computation offloading and parallel scheduling to maximize delay-guarantee in cooperative MEC systems

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Digital Communications and Networks 2024年第3期10卷 693-705页

作者： Mian Guo Mithun Mukherjee Jaime Lloret Lei Li Quansheng Guan Fei Ji School of electronics and information Guangdong Polytechnic Normal UniversityGuangzhouChina School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjingChina Universitat Politecnica de Valencia 46022ValenciaSpain South China University of Technology China

The growing development of the Internet of Things(IoT)is accelerating the emergence and growth of new IoT services and applications,which will result in massive amounts of data being generated,transmitted and pro-cessed in wireless communication *** Edge Computing(MEC)is a desired paradigm to timely process the data from IoT for value *** MEC,a number of computing-capable devices are deployed at the network edge near data sources to support edge computing,such that the long network transmission delay in cloud computing paradigm could be *** an edge device might not always have sufficient resources to process the massive amount of data,computation offloading is significantly important considering the coop-eration among edge ***,the dynamic traffic characteristics and heterogeneous computing capa-bilities of edge devices challenge the *** addition,different scheduling schemes might provide different computation delays to the offloaded ***,offloading in mobile nodes and scheduling in the MEC server are coupled to determine service *** paper seeks to guarantee low delay for computation intensive applica-tions by jointly optimizing the offloading and scheduling in such an MEC *** propose a Delay-Greedy Computation Offloading(DGCO)algorithm to make offloading decisions for new tasks in distributed computing-enabled mobile devices.A Reinforcement Learning-based Parallel Scheduling(RLPS)algorithm is further designed to schedule offloaded tasks in the multi-core MEC *** an offloading delay broadcast mechanism,the DGCO and RLPS cooperate to achieve the goal of delay-guarantee-ratio ***,the simulation results show that our proposal can bound the end-to-end delay of various *** under slightly heavy task load,the delay-guarantee-ratio given by DGCO-RLPS can still approximate 95%,while that given by benchmarked algorithms is reduced to intolerable *** simulation resul

关键词： Edge computing Computation offloading Parallel scheduling Mobile-edge cooperation Delay guarantee