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Hybrid Teaching Learning Approach for Improving Network Lifetime in Wireless Sensor Networks

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Computers, Materials & Continua 2022年第1期70卷 1975-1992页

作者： P.baskaran K.Karuppasamy Easwari Engineering College Chennai600089India Computer Science and Engineering RVS College of Engineering&TechnologyCoimbatore641402India

In a wireless sensor network(WSN),data gathering is more effectually done with the clustering *** is a critical strategy for improving energy efficiency and extending the longevity of a *** modeling-based clustering is proposed to enhance energy efficiency where nodes that hold higher residual energy may be clustered to collect data and broadcast it to the base ***,existing approaches may not consider data redundancy while collecting data from adjacent nodes or overlapping ***,an improved clustering approach is anticipated to attain energy efficiency by implementingMapReduction for regulatingmapping and reducing complexity in routing mechanisms for eliminating redundancy and *** order to optimize the network performance,this work considers intelligent behaviors’to adapt with network changes and to introduce computational intelligence *** the proposed research,improved teaching learning based optimization is used to evaluate the coordinates of target nodes and nodes upgradation for determining energy *** upgradation is performed by integratingMap reduction to attain modification in Hop size of *** variation reduces communication ***,network lifetime is increased,and redundancy is *** comparingwith existing approaches here,sleep and wake-up nodes are considered for data *** proposed algorithm clearly demonstrates 50%,16%&12%improvement in nodes lifetime,residual energy and throughput respectively compared to other *** it shows progressive improvement in reducing average waiting time,average queuing time and average energy utilization as 30%,20%and 46%*** has been done in NS-2 environment for distributed heterogeneous networks.

关键词： Map reduction optimization Teaching-learning energy efficiency network lifetime heterogeneous network

Identifying Influential Communities Using IID for a Multilayer Networks

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Intelligent Automation & Soft Computing 2023年第5期36卷 1715-1731页

作者： C.Suganthini R.baskaran Department of Computer Science and Engineering College of Engineering GuindyAnna UniversityChennaiTamilnaduIndia

In online social networks(OSN),they generate several speciﬁc user activities daily,corresponding to the billions of data points ***,although users exhibit signiﬁcant interest in social media,they are uninterested in the content,discussions,or opinions available on certain ***,this study aims to identify inﬂuential communities and understand user behavior across networks in the information diffusion *** media platforms,such as Facebook and Twitter,extract data to analyze the information diffusion process,based on which they cascade information among the individuals in the ***,this study proposes an inﬂuential information diffusion model that identiﬁes inﬂuential communities across these two social media ***-over,it addresses site migration by visualizing a set of overlapping communities using hyper-edge ***,the overlapping community structure is used to identify similar communities with identical user ***,the com-munity structure helps in determining the node activation and user inﬂuence from the information cascade ***,the Fraction of Intra/Inter-Layer(FIL)dif-fusion score is used to evaluate the efﬁciency of the inﬂuential information diffu-sion model by analyzing the trending inﬂuential communities in a multilayer ***,from the experimental result,it observes that the FIL diffusion score for the proposed method achieves better results in terms of accuracy,preci-sion,recall and efﬁciency of community detection than the existing methods.

关键词： Inﬂuential information diffusion model community detection inﬂuential communities social network

Rapid Fault Analysis by Deep Learning-Based PMU for Smart Grid System

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Intelligent Automation & Soft Computing 2023年第2期35卷 1581-1594页

作者： J.Shanmugapriya K.baskaran Department of EEE Park College of Engineering and TechnologyCoimbatore641659India Department of EEE Alagappa Chettiar Government College of Engineering and TechnologyKaraikudi630004India

Smart Grids(SG)is a power system development concept that has received signiﬁcant attention *** signiﬁes real-time data for speciﬁc communication *** best capabilities for monitoring and controlling the grid are essential to system *** of the most critical needs for smart-grid execution is fast,precise,and economically synchronized measurements,which are made feasible by Phasor Measurement Units(PMU).PMUs can pro-vide synchronized measurements and measure voltages as well as current phasors *** utilize GPS time-stamping at Coordinated Universal Time(UTC)to capture electric phasors with great accuracy and *** research tends to Deep Learning(DL)advances to design a Residual Network(ResNet)model that can accurately identify and classify defects in grid-connected *** part of fault detection and probe,the proposed strategy uses a ResNet-50 tech-nique to evaluate real-time measurement data from geographically scattered *** a result of its excellent signal classiﬁcation efﬁciency and ability to extract high-quality signal features,its fault diagnosis performance is *** results demonstrate that the proposed method is effective in detecting and classifying faults at sufﬁcient *** proposed approaches classify the fault type with a precision of 98.5%and an accuracy of 99.1%.The long-short-term memory(LSTM),Convolutional Neural Network(CNN),and CNN-LSTM algo-rithms are applied to compare the ***-world data tends to evaluate these networks.

关键词： Smart grid phasor measurement units global positioning system coordinated universal time deep learning residual network–50

Using different analytical techniques to study beach rocks of Tamilnadu,India

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Nuclear Science and Techniques 2009年第3期20卷 140-145页

作者： ravisankar R Department of Physics Sri Sivasubramania Nadar College of Engineering Kalavakkam Chennai 603110 Tamilnadu India

Beach rocks samples were collected from South East Coast of Tamilnadu, India. The mineralogical composition was determined using FT-IR and XRD. The natural radioactive measurements to detect radioactive elements were determined by gamma ray spectrometer. The multi-element analyses were carried out by INAA (Instrumental neutron activation analysis), with the standard Estuarine Sediment as reference material. The geochemical behavior of elements in the region is discussed. The occurrence of the radioactive and non-radioactive elements is discussed for their geological significance. The results were used to assess environmental toxicity of heavy metals and radiation hazard in the study area.

关键词：分光计 INAA 放射性元素核技术

Cardiac CT blooming artifacts:clinical significance,root causes and potential solutions

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Visual Computing for Industry,Biomedicine,and Art 2022年第1期5卷 352-364页

作者： Jed DPack Mufeng Xu Ge Wang Lohendran baskaran James Min Bruno De Man GE Research NiskayunaNY 12309USA Rensselaer Polytechnic Institute Troy NY 12180USA Weill Cornell Medicine New York NY 10065USA National Heart Centre Singapore 169609Singapore Cleerly New York NY 10065USA

This review paper aims to summarize cardiac CT blooming artifacts,how they present clinically and what their root causes and potential solutions are.A literature survey was performed covering any publications with a specific interest in calcium blooming and stent blooming in cardiac *** claims from literature are compared and interpreted,aiming at narrowing down the root causes and most promising solutions for blooming *** than 30 journal publications were identified with specific relevance to blooming *** main reported causes of blooming artifacts are the partial volume effect,motion artifacts and beam *** proposed solutions are classified as high-resolution CT hardware,high-resolution CT reconstruction,subtraction techniques and post-processing techniques,with a special emphasis on deep learning(DL)*** partial volume effect is the leading cause of blooming *** partial volume effect can be minimized by increasing the CT spatial resolution through higherresolution CT hardware or advanced high-resolution CT *** addition,DL techniques have shown great promise to correct for blooming artifacts.A combination of these techniques could avoid repeat scans for subtraction techniques.

关键词： Cardiac CT Coronary artery imaging Calcium blooming In-stent restenosis Partial volume Motion artifacts Beam hardening

Rare earth(Gd,La) co-doped ZnO nanoflowers for direct sunlight driven photocatalytic activity

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Journal of Rare Earths 2023年第1期41卷 77-84页

作者： baskaran Palanivel Romulo R.Macadangdang Jr Md Shahadat Hossain Fahad A.Alharthi Mohanraj Kumar Jih-Hsing Chang Sreedevi Gedi Department of Physics Kings Engineering CollegeSriperumbudurKancheepuram602117TamilnaduIndia Department of Medical Technology Institute of Arts and SciencesFar Eastern UniversityManilaPhilippines Department of Innovation Systems Engineering Graduate School of EngineeringUtsunomiya UniversityYoto 7-1-2Utsunomiya321-8585Japan Chemistry Department College of ScienceKing Saud UniversityRiyadh1145Saudi Arabia Department of Environmental Engineering and Management Chaoyang University of Technology168Jifeng E.Rd.Wufeng DistrictTaichung41349TaiwanChina School of Chemical Engineering Yeungnam UniversityGyeongsan38541Republic of Korea

In this work Gd/La@ZnO nanoflower photocatalyst was successfully synthesized by a co-precipitation method and applied for rhodamine B(Rh B) and tetracycline(TCN) degradation under direct sunlight *** doping of rare earth elements extends the optical absorption wavelength of ZnO from UV region(390 nm) to visible-light region(401 nm).In addition,the co-doped ZnO nanoflower exhibits a lower charge recombination efficiency which was confirmed by photoluminescence emission ***,the co-doped ZnO nanoflower exhibits the maximum degradation efficiency of 91% for Rh B and 74% for TCN under sunlight *** calculated synergistic index of co-doped ZnO is higher than that of the pure *** radicals’ production was confirmed by terephthalic acid(TA) and nitro-blue tetrazolium(NBT) *** holes and hydroxyl(·OH) radicals play the major role in degradation reaction and it was confirmed by scavenger’s ***,the recycling test confirms the stability of the photocatalyst.

关键词： Gd La ZnO Nanoflower Photocatalyst Sunlight

Optical absorption of Tl^+ ions in KBr_(1-x)I_x:TlI mixed crystals

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Nuclear Science and Techniques 2009年第4期20卷 208-218页

作者： Eswaran P ravisankar R Nagarajan S Department of Physics SMK Fomra Institute of Technology Department of Physics Government Arts CollegeThiruvannamalai Department of Physics Pondicherry Engineering College

Optical absorption spectra of the mixed crystals of KBr1-xIx:Tl+ crystals studied at room temperature are *** absorption spectra indicated the appearance of additional bands on the low energy side of the Characteristic A,B and C absorption bands of KBr:Tl+ single crystals with increasing iodine *** with earlier reports,the additional bands were attributed to the complex Tl+centers in the mixed configuration surrounded by Br-and I-ions as nearest *** absorption spectra of gamma irradiated mixed crystals showed F band,which shifts towards low energy side with the composition of iodine ions in the mixed crystals.

关键词：能级核技术光谱吸收碘离子

Atmospheric deposition of 7Be,210Pb and 210Po during typhoons and thunderstorm in Shanghai, China and global data synthesis

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Science China Earth Sciences 2020年第4期63卷 602-614页

作者： Juan DU Mark baskaran Jinzhou DU State Key Laboratory of Estuarine and Coastal Research East China Normal UniversityShanghai 200241China Department of Geology Wayne State UniversityDetroit 48202USA

Atmospherically-delivered ~7Be,^(210)Po and ^(210)Pb in bulk precipitation and air samples collected around the globe have provided valuable quantification on the rates of removal, as well as proportional mixing of attendant air masses;however, such studies during thunderstorm and typhoon events are limited. We report the first continuous time-series rainwater sampling and analysis of ~7Be,^(210)Pb and ^(210)Po from two typhoons and one thunderstorm during 2015 summer in Shanghai. The depositional fluxes within individual rain events of typhoons and thunderstorms varied by a factor of 10 for ~7Be, 5.7 for ^(210)Pb, 7.4 for ^(210)Po,and 7.0 for ~7Be/^(210)Pb activity ratios(AR). Such large observed variations in the depositional fluxes of ~7Be,^(210)Pb,^(210)Po and ~7Be/^(210)Pb activity ratios were attributed to air masses injected from surrounding high pressure system adjoining the typhoon to low pressure system within the typhoon. Based on ~7Be/^(210)Pb activity ratios, we estimated the variations in the fraction of maritime and continental air masses into the typhoon. Observed constancy in the ^(210)Po/^(210)Pb AR indicates that the residence times of air masses contributing to the typhoon during heavy rain are similar. From a synthesis of global fallout of ~7Be and ^(210)Pb during pulse events(precipitation≥50 mm from single rainout event), we quantify the importance of pulse events in the atmospheric fallout of these radionuclides.

关键词： 7Be 210Pb 210Po Typhoon Thunderstorm Air masses intrusions

Emotion Deduction from Social Media Text Data Using Machine Learning Algorithm

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Journal of Computer and Communications 2023年第11期11卷 183-196页

作者： Thambusamy Velmurugan baskaran Jayapradha PG and Research Department of Computer Science Dwaraka Doss Govardhan Doss Vaishnav College Chennai India PG and Research Department of Computer Science Dr. Ambedkar Government Arts College Chennai India

Emotion represents the feeling of an individual in a given situation. There are various ways to express the emotions of an individual. It can be categorized into verbal expressions, written expressions, facial expressions and gestures. Among these various ways of expressing the emotion, the written method is a challenging task to extract the emotions, as the data is in the form of textual dat. Finding the different kinds of emotions is also a tedious task as it requires a lot of pre preparations of the textual data taken for the research. This research work is carried out to analyse and extract the emotions hidden in text data. The text data taken for the analysis is from the social media dataset. Using the raw text data directly from the social media will not serve the purpose. Therefore, the text data has to be pre-processed and then utilised for further processing. Pre-processing makes the text data more efficient and would infer valuable insights of the emotions hidden in it. The preprocessing steps also help to manage the text data for identifying the emotions conveyed in the text. This work proposes to deduct the emotions taken from the social media text data by applying the machine learning algorithm. Finally, the usefulness of the emotions is suggested for various stake holders, to find the attitude of individuals at that moment, the data is produced. .

关键词： Data Pre-Processing Machine Learning Algorithms Emotion Deduction Sentiment Analysis