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Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

Computers, Materials & Continua 2024年第6期79卷 3585-3629页

作者： Imtiaz Ahmad Tariq Hussain Babar Shah Altaf Hussain Iqtidar ali Farman ali Institute of Computer Sciences and Information Technology The University of AgriculturePeshawarPakistan School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhouChina College of Technological Innovation Zayed UniversityDubaiUnited Arab Emirates School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063South Korea

Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and *** of them is a sensor network with embedded sensors working as the primary nodes,termed Wireless Sensor Networks(WSNs),in which numerous sensors are connected to at least one Base Station(BS).These sensors gather information from the environment and transmit it to a BS or gathering *** have several challenges,including throughput,energy usage,and network lifetime *** strategies have been applied to get over these *** may,therefore,be thought of as the best way to solve such ***,it is crucial to analyze effective Cluster Head(CH)selection to maximize efficiency throughput,extend the network lifetime,and minimize energy *** paper proposed an Accelerated Particle Swarm Optimization(APSO)algorithm based on the Low Energy Adaptive Clustering Hierarchy(LEACH),Neighboring Based Energy Efficient Routing(NBEER),Cooperative Energy Efficient Routing(CEER),and Cooperative Relay Neighboring Based Energy Efficient Routing(CR-NBEER)*** the help of APSO in the implementation of the WSN,the main methodology of this article has taken *** simulation findings in this study demonstrated that the suggested approach uses less energy,with respective energy consumption ranges of 0.1441 to 0.013 for 5 CH,1.003 to 0.0521 for 10 CH,and 0.1734 to 0.0911 for 15 *** sending packets ratio was also raised for all three CH selection scenarios,increasing from 659 to *** number of dead nodes likewise dropped for the given combination,falling between 71 and *** network lifetime was deemed to have risen based on the results found.A hybrid with a few valuable parameters can further improve the suggested APSO-based *** to underwater,WSN can make use of the proposed *** overall results have been evaluated and

关键词： Wireless sensor network cluster head selection low energy adaptive clustering hierarchy accelerated particle swarm optimization

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Can the Bass innovation diffusion model describe adsorption breakthrough curves of pharmaceutical contaminants?

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Green Chemical Engineering 2024年第2期5卷 145-149页

作者： Khim Hoong Chu Mohd ali Hashim Department of Chemical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur50603Malaysia

*** Fixed bed adsorption is a widely used separation process in the chemical industry for the processing of liquids and *** performance of fixed bed adsorption systems is often evaluated by analyzing the breakthrough curves,which represent the variation of the solute concentration in the effluent stream as a function of time or bed volume.

关键词： adsorption breakthrough curves

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Computer vision-based six layered ConvNeural network to recognize sign language for both numeral and alphabet signs

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Biomimetic Intelligence & Robotics 2024年第1期4卷 45-58页

作者： Muhammad Aminur Rahaman Kabiratun Ummi Oyshe Prothoma khan Chowdhury Tanoy Debnath Anichur Rahman Md.Saikat Islam khan Department of Computer Science and Engineering Green University of BangladeshDhakaBangladesh Department of Computer Science and Engineering National Institute of Textile Engineering and Research(NITER)Constituent Institute of Dhaka UniversityDhakaBangladesh Department of Computer Science and Engineering Mawlana Bhashani Science and Technology UniversityTangailBangladesh

People who have trouble communicating verbally are often dependent on sign language,which can be difficult for most people to understand,making interaction with them a difficult *** Sign Language Recognition(SLR)system takes an input expression from a hearing or speaking-impaired person and outputs it in the form of text or voice to a normal *** existing study related to the Sign Language Recognition system has some drawbacks,such as a lack of large datasets and datasets with a range of backgrounds,skin tones,and *** research efficiently focuses on Sign Language Recognition to overcome previous *** importantly,we use our proposed Convolutional Neural Network(CNN)model,“ConvNeural”,in order to train our ***,we develop our own datasets,“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”,both of which have ambiguous backgrounds.“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”both include images of Bangla characters and numerals,a total of 24,615 and 8437 images,***“ConvNeural”model outperforms the pre-trained models with accuracy of 98.38%for“BdSL_OPSA22_STATIC1”and 92.78%for“BdSL_OPSA22_STATIC2”.For“BdSL_OPSA22_STATIC1”dataset,we get precision,recall,F1-score,sensitivity and specificity of 96%,95%,95%,99.31%,and 95.78%***,in case of“BdSL_OPSA22_STATIC2”dataset,we achieve precision,recall,F1-score,sensitivity and specificity of 90%,88%,88%,100%,and 100%respectively.

关键词： Conv NeuralSign language CNN Static Feature extraction Convolution2D Fully connected layer Dropout

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A Novel Hybrid Ensemble Learning Approach for Enhancing Accuracy and Sustainability in Wind Power Forecasting

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Computers, Materials & Continua 2024年第5期79卷 3373-3395页

作者： Farhan Ullah Xuexia Zhang Mansoor khan Muhammad Abid Abdullah Mohamed School of Electrical Engineering Southwest Jiaotong UniversityChengdu611756China College of Intelligent Manufacturing and Control Engineering Qilu Institute of TechnologyJinan250200China College of Aerospace and Civil Engineering Harbin Engineering UniversityHarbin150001China Research Centre Future University in EgyptNew Cairo11835Egypt

Accurate wind power forecasting is critical for system integration and stability as renewable energy reliance *** approaches frequently struggle with complex data and non-linear connections. This article presentsa novel approach for hybrid ensemble learning that is based on rigorous requirements engineering *** approach finds significant parameters influencing forecasting accuracy by evaluating real-time Modern-EraRetrospective Analysis for Research and Applications (MERRA2) data from several European Wind farms usingin-depth stakeholder research and requirements elicitation. Ensemble learning is used to develop a robust model,while a temporal convolutional network handles time-series complexities and data gaps. The ensemble-temporalneural network is enhanced by providing different input parameters including training layers, hidden and dropoutlayers along with activation and loss functions. The proposed framework is further analyzed by comparing stateof-the-art forecasting models in terms of Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE),respectively. The energy efficiency performance indicators showed that the proposed model demonstrates errorreduction percentages of approximately 16.67%, 28.57%, and 81.92% for MAE, and 38.46%, 17.65%, and 90.78%for RMSE for MERRAWind farms 1, 2, and 3, respectively, compared to other existingmethods. These quantitativeresults show the effectiveness of our proposed model with MAE values ranging from 0.0010 to 0.0156 and RMSEvalues ranging from 0.0014 to 0.0174. This work highlights the effectiveness of requirements engineering in windpower forecasting, leading to enhanced forecast accuracy and grid stability, ultimately paving the way for moresustainable energy solutions.

关键词： Ensemble learning machine learning real-time data analysis stakeholder analysis temporal convolutional network wind power forecasting

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An overview and experimental analysis of WO3/TiO2 composite with enhanced electrochromic properties for smart windows application

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Tungsten 2024年第4期6卷 732-747页

作者： Ayesha khan Mayur A.Gaikwad Jin Hyeok Kim Anamika Kadam The Institute of Science Dr.Homi Bhabha State University Optoelectronics Convergence Research Center and Department of Materials Science and Engineering Chonnam National University

Internationally,standards for electrochromic（EC） requirements in smart window applications have been established,with ongoing global initiatives aimed at elevating them to highly advanced *** paper covers a comprehensive investigation of the structural,optical,morphological,and electrochemical properties of WO3/TiO2composite ***,an experimental analysis of WO3/TiO2was envisaged by a two-step ***,WO3thin films were hydrothermally deposited onto indium-doped tin oxide-coated glass substrates using an aqueous solution of Na2WO4·2H2O at a pH value of ***,a layer of TiO2was electrodeposited onto the WO3thin films.X-ray diffraction analysis confirmed the successful formation of WO3/TiO2composite films,with the WO3phase exhibiting a hexagonal tunnel *** electron microscopy revealed the formation of porous nanorods（NRs） of WO3,uniformly coated with TiO2,resulting in a porous morphology of the WO./*** EC performance of the WO3/TiO2films was thoroughly assessed through cyclic voltammetry and chronoamperometry measurements over a potential window ranging from-2.0 to+1.2 V（versus Ag/AgCl） in a 0.5 mol·L-1LiClO4-PC *** WO3/TiO2composite films exhibited cathodic electrochromism,characterized by a reversible color change from dark blue to *** improved EC performance in comparison to pure WO3films is attributed to enhanced double ion/electron insertion and extraction ***,the WO3/TiO2composite films demonstrated excellent optical modulation properties,with a significant modulation at 633 nm（46.87%）.The coloration efficiency reached a high value of 193.25 cm2·C-1,indicating their potential for practical EC ***,the WO3/TiO2composite films displayed exceptional EC stability,with no significant degradation observed over 2500 cyclic voltammetry *** superior EC performance can be attributed to the synergistic effect between the hexagonal WO3NRs

关键词： Electrochromism Smart window Stability WO3/TiO2

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Intelligent algorithm-based maximum power point tracker for an off-grid photovoltaic-powered direct-current irrigation system

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CLEAN ENERGY 2024年第3期8卷 48-61页

作者： Attia, Hussain Takruri, Maen Al-Ataby, ali Amer Univ Ras Al Khaimah Dept Elect Elect & Commun Engn Ras Al Khaymah U Arab Emirates

This research aims to enhance the performance of photovoltaic (PV) systems on a 2-fold basis. Firstly, it introduces an advanced deep artificial neural network algorithm for accurate and fast maximum power point tracking, ensuring optimal extraction of electrical power from PV arrays. Secondly, it proposes the use of 96-V, 2.98-kW direct-current (DC) water pumps for farm irrigation, aiming to improve efficiency, reduce cost and complexity, and overcome challenges associated with connecting faraway farm irrigation systems to the utility grid. In this study, it has been demonstrated that the use of DC pumps greatly improves system performance and efficiency by eliminating the need for isolation transformers, power passive filters and inverters, therefore simplifying the architecture of the system. The efficacy of the proposed methodology is confirmed by MATLAB (R)/Simulink (R) simulation results, whereby the proposed algorithm attains a mean squared error of 6.5705 x 10-5 and a system efficiency approaching 99.8%, ensuring a steady voltage under varying load conditions. This study demonstrates the use of direct-current electricity from solar PV to power farm irrigation pumps in a way that greatly improves system performance and efficiency, reduces cost and simplifies the architecture of the system. Graphical Abstract

关键词： artificial neural network photovoltaic arrays maximum power point tracking buck converter direct-current irrigation systems MATLAB/Simulink ENERGY-STORAGE

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Understanding the catalytic performance and deactivation behaviour of second-promoter doped Pt/WO_(χ)/γ-Al_(2)O_(3) catalysts in the glycerol hydrogenolysis for selective and cleaner production of 1,3-propanediol

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Journal of Energy Chemistry 2024年第7期94卷 486-507页

作者： Rafik Rajjak Shaikh Sittichai Damruang Rais Ahmad khan Supareak Praserthdam Piyasan Praserthdam Center of Excellence on Catalysis and Catalytic Reaction Engineering(CECC) Department of Chemical EngineeringFaculty of EngineeringChulalongkorn UniversityBangkok 10330Thailand Department of Chemistry College of ScienceKing Saud UniversityP.O.Box 2455Riyadh 11451Saudi Arabia High-Performance Computing Unit(CECC-HCU) Centre of Excellence on Catalysis and Catalytic Reaction Engineering(CECC)Department of Chemical EngineeringFaculty of EngineeringChulalongkorn UniversityBangkok 10330Thailand

The selective aqueous-phase glycerol hydrogenolysis is a promising reaction to produce commercially useful 1,3-propanediol(1,3-PDO).The Pt-WOx bifunctional catalyst can catalyse the glycerol hydrogenol-ysis but the catalyst deactivation via sintering,metal leaching,and coking can predominantly occur in the aqueous phase *** this work,the effect of reaction temperature,pressure and second promoter(Cu,Fe,Rh,Mn,Re,Ru,Ir,Sn,B,and P)on catalytic performance and deactivation behaviour of Pt/WOx/-Al2O3 was *** doped with Rh,Mn,Re,Ru,Ir,B,and P,the second promoter boosts catalytic activity by promoting great dispersion of Pt on support and increasing Pt surface *** increased Bronsted acid sites lead to selective synthesis of 1,3-PDO than 1,2-propanediol(1,2-PDO).The characterization studies of fresh and spent catalysts reveal that the main cause of catalyst deactivation is the Pt sintering,as interpreted based on XRD,CO chemisorption,and TEM *** Pt sintering is affected depending on the second promoter that can either or reduce the interaction between Pt,WO_(χ)/γ and Al_(2)O_(3).As an electron acceptor of Pt in Pt/WO_(χ)/γ-Al_(2)O_(3),Re and Mn as second promoters resulted in increased Pt^(2+) on the catalytic surface,which strengthens the contact between Pt andγ-Al_(2)O_(3) and WO_(χ),resulting in a decrease in Pt *** metal leaching and coking are not affected by the presence of second *** catalyst modified with a second promoter possesses improved catalytic activity and 1,3-PDO production,however the stability continues to remain a *** present work unrav-elled the determining parameters of catalytic activity and deactivation,thus providing a promising pro-tocol toward effective catalysts for glycerol hydrogenolysis.

关键词： Glycerol hydrogenolysis 1,3-propanediol Metal-support interaction Second promoter Liquid phase Catalyst deactivation

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Winding Function Model-based Performance Evaluation of a PM Transverse Flux Generator for Applications in Direct-drive Systems

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CES Transactions on Electrical Machines and Systems 2024年第2期8卷 216-226页

作者： Mehrage Ghods Jawad Faiz ali A Pourmoosa IEEE School of Electrical and Computer Engineering College of Engineeringthe University of Tehran

The magnetic flux in a permanent magnet transverse flux generator(PMTFG) is three-dimensional(3D), therefore, its efficacy is evaluated using 3D magnetic field analysis. Although the 3D finite-element method(FEM) is highly accurate and reliable for machine simulation, it requires a long computation time, which is crucial when it is to be used in an iterative optimization process. Therefore, an alternative to 3DFEM is required as a rapid and accurate analytical technique. This paper presents an analytical model for PMTFG analysis using winding function method. To obtain the air gap MMF distribution, the excitation magneto-motive force(MMF) and the turn function are determined based on certain assumptions. The magnetizing inductance, flux density, and back-electro-magnetomotive force of the winding are then determined. To assess the accuracy of the proposed method, the analytically calculated parameters of the generator are compared to those obtained by a 3D-FEM. The presented method requires significantly shorter computation time than the 3D-FEM with comparable accuracy.

关键词： Index Terms—Permanent magnet transverse flux generator Winding function 3D-FEM Cogging torque Prototyping

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Tubular Heat Enhancement Using Twisted Tape Inserts with Large Holes

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Energy Engineering 2024年第2期121卷 273-290页

作者： ali Jaber Abdulhamed Aws Al-Akam Wisam J.Khudhayer ali Sabri Allw Faculty of Engineering-Al-Mussayib University of BabylonHillaBabylon15001Iraq

Heat augmentation techniques play a vital role in the heating and cooling processes in industries,including solar collectors and many applications that utilize heat *** studies are based on inserting fillers inside the tubes to enhance heat *** investigation considered the effects of twisted tapes with large holes on a tubular heat exchanger’s(HX)heat transmission,pressure drop,and thermal boosting *** the experimental section,counter-swirl flow generators used twisted tapes with pairs of 1.0 cm-diameter holes and changes in porosity(Rp)at 1.30%and 2.70%.In the experiments,air was utilized as a working fluid in a tube with a circular *** turbulent flow was considered,with Reynolds numbers(Re)domain from 4800 to 9500,and a boundary condition with a uniform wall heat flux was *** findings expound that when the number of holes rose,the Nusselt number(Nu),the factor of friction(f),and the thermal enhancement factor(η)all increased as ***,as the friction factor increased,the Nusselt number of the tape-equipped tube was noticeably ***,it was discovered that the friction factor was between 70%and 94%lower than the values of the tube without tape,while the(Nu)was between 87%and 97%higher than the conventional tube *** maximum value ofηis 89%.According to the experimental results,empirical correlations for Nu,f,andηwere also generated.

关键词： Tubular heat exchanger tape inserts twisted tape

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Internet of Things Enabled DDoS Attack Detection Using Pigeon Inspired Optimization Algorithm with Deep Learning Approach

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Computers, Materials & Continua 2024年第9期80卷 4047-4064页

作者： Turki ali Alghamdi Saud S.Alotaibi Department of Computer Science and Artificial Intelligence College of ComputingUmm Al-Qura UniversityMakkah21955Saudi Arabia

Internet of Things(IoTs)provides better solutions in various fields,namely healthcare,smart transportation,home,*** Denial of Service(DoS)outbreaks in IoT platforms is significant in certifying the accessibility and integrity of IoT *** learning(DL)models outperform in detecting complex,non-linear relationships,allowing them to effectually severe slight deviations fromnormal IoT activities that may designate a DoS *** uninterrupted observation and real-time detection actions of DL participate in accurate and rapid detection,permitting proactive reduction events to be executed,hence securing the IoT network’s safety and ***,this study presents pigeon-inspired optimization with a DL-based attack detection and classification(PIODL-ADC)approach in an IoT *** PIODL-ADC approach implements a hyperparameter-tuned DL method for Distributed Denial-of-Service(DDoS)attack detection in an IoT ***,the PIODL-ADC model utilizes Z-score normalization to scale input data into a *** handling the convolutional and adaptive behaviors of IoT,the PIODL-ADCmodel employs the pigeon-inspired optimization(PIO)method for feature selection to detect the related features,considerably enhancing the recognition’s ***,the Elman Recurrent Neural Network(ERNN)model is utilized to recognize and classify DDoS ***,reptile search algorithm(RSA)based hyperparameter tuning is employed to improve the precision and robustness of the ERNN method.A series of investigational validations is made to ensure the accomplishment of the PIODL-ADC *** experimental outcome exhibited that the PIODL-ADC method shows greater accomplishment when related to existing models,with a maximum accuracy of 99.81%.

关键词： Internet of things denial of service deep learning reptile search algorithm feature selection

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