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A Novel Outlier Detection with Feature Selection Enabled Streaming Data Classification

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Intelligent Automation & Soft Computing 2023年第2期35卷 2101-2116页

作者： r.rajakumar S.Sathiya devi Anna University Chennai600025India University College of Engineering BIT CampusAnna UniversityTiruchirappalli620024India

Due to the advancements in information technologies,massive quantity of data is being produced by social media,smartphones,and sensor *** investigation of data stream by the use of machine learning(ML)approaches to address regression,prediction,and classiﬁcation problems have received consid-erable *** the same time,the detection of anomalies or outliers and feature selection(FS)processes becomes *** study develops an outlier detec-tion with feature selection technique for streaming data classiﬁcation,named ODFST-SDC ***,streaming data is pre-processed in two ways namely categorical encoding and null value *** addition,Local Correla-tion Integral(LOCI)is used which is signiﬁcant in the detection and removal of ***,red deer algorithm(rDA)based FS approach is employed to derive an optimal subset of ***,kernel extreme learning machine(KELM)classiﬁer is used for streaming data classiﬁ*** design of LOCI based outlier detection and rDA based FS shows the novelty of the *** order to assess the classiﬁcation outcomes of the ODFST-SDC technique,a series of simulations were performed using three benchmark *** experimental results reported the promising outcomes of the ODFST-SDC technique over the recent approaches.

关键词： Streaming data classiﬁcation outlier removal feature selection machine learning metaheuristics

A Novel radial Basis Function Neural Network Approach for ECG Signal Classification

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Intelligent Automation & Soft Computing 2023年第1期35卷 129-148页

作者： S.Sathishkumar r.devi Priya Department of Information Technology Adhiyamaan College of EngineeringHosur621004India Department of Information Technology Kongu Engineering CollegeErode638060India

ions in the ECG *** cardiologist and medical specialistfind numerous difficulties in the process of traditional *** specified restrictions are eliminated in the proposed *** fundamental aim of this work is tofind the r-r *** analyze the blockage,different approaches are implemented,which make the computation as facile with high *** information are recovered from the MIT-BIH *** retrieved data contain normal and pathological ECG *** obtain a noiseless signal,Gaborfilter is employed and to compute the amplitude of the signal,DCT-DOST(Discrete cosine based Discrete orthogonal stock well transform)is *** amplitude is computed to detect the cardiac *** r peak of the underlying ECG signal is noted and the segment length of the ECG cycle is *** Genetic algorithm(GA)retrieves the primary highlights and the classifier integrates the data with the chosen attributes to optimize the *** addition,the GA helps in performing hereditary calculations to reduce the problem of multi-target ***,the rBFNN(radial basis function neural network)is applied,which diminishes the local minima present in the *** shows enhancement in characterizing the ordinary and anomalous ECG signals.

关键词： Electrocardiogram signal gaborfilter discrete cosine based discrete orthogonal stock well transform genetic algorithm radial basis function neural network

Deep insights into the advancements and applications of perovskite based photovoltaic cells

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Journal of Energy Chemistry 2018年第3期27卷 753-763页

作者： Chandni devi rajesh Mehra Electronics and Communication Department NITTTR

The organometal halide perovskite materials have a blend of surprising optoelectronic properties, for example high value of absorption coefficient and abrupt optical retention edge, lifetime, long charge carrier diffusion length and many more. Brought in conjunction with the capacity for manufacturing at low temperature, likewise from the solution, devices based on perovskite, particularly solar cells have been contemplated seriously with striking advancements in performance, in the course of recent years. The amalgamation of minimal effort, high efficiency and extra applications gives incredible potential to commercialization of these cells. The applications and performance of perovskite cells frequently relate with the structures of the device. Numerous creative structures of the devices were produced, targeting for vast scale manufacture, diminishing creation cost, upgrading the PCE and subsequently expanding the prospective for future applications. This paper outlines the various advanced structures of PSC, challenges confronted by these PSCs and their future perspectives. The commercial applications of PSC are additionally talked about in this paper.

关键词： Solar cells Flexibility ETM Perovskite HTM Structures

A Novel Fuzzy Inference System-Based Endmember Extraction in Hyperspectral Images

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Intelligent Automation & Soft Computing 2023年第8期37卷 2459-2476页

作者： M.r.Vimala devi S.Kalaivani School of Electronics Engineering Vellore Institute of TechnologyVellore632051India

Spectral unmixing helps to identify different components present in the spectral mixtures which occur in the uppermost layer of the area owing to the low spatial resolution of hyperspectral *** spectral unmixing methods are globally based and do not consider the spectral variability among its endmembers that occur due to illumination,atmospheric,and environmental ***,endmember bundle extraction plays a major role in overcoming the above-mentioned limitations leading to more accurate abundance ***,a two-stage approach is proposed to extract endmembers through endmember bundles in hyperspectral *** divide and conquer method is applied as the first step in subset images with only the non-redundant bands to extract endmembers using the Vertex Component Analysis(VCA)and N-FINDr algorithms.A fuzzy rule-based inference system utilizing spectral matching parameters is proposed in the second step to categorize *** endmember with the minimum error is chosen as the final endmember in each specific *** proposed method is simple and automatically considers endmember variability in hyperspectral *** efficiency of the proposed method is evaluated using two real hyperspectral *** average spectral angle and abundance angle are used to analyze the performance measures.

关键词： Hyperspectral image spectral unmixing spectral matching endmember bundles fuzzy inference system

A review on Efficient routing Mechanisms in Urban Scenario of Vehicular Ad⁃Hoc Networks

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Journal of Harbin Institute of Technology(New Series) 2023年第6期30卷 83-94页

作者： Kalpana devi S Thenmozhi r Department of Computing Technologies SRM Institute of Science and TechnologyKattankulathurChennai 603203India

Efficient routing protocols are crucial for enabling secure communication among the highly mobile and self-configurable nodes in Vehicular Ad-Hoc Networks(VANETs). In this work, we present a performance evaluation of different routing protocols in VANETs based on the currently available research. Our study focuses on analyzing the strength and weaknesses of the routing protocols, namely, Ad-Hoc On-demand Distance Vector(AODV), Dynamic Source routing(DSr), and Destination-Sequenced Distance-Vector(DSDV), under varying network conditions. We examine the protocols’ performance based on key metrics such as throughput, delay, and energy consumption. We also highlight the advantages and limitations of each protocol in different scenarios, such as varying vehicular densities and mobility patterns. Our results show that AODV outperforms DSr and DSDV in terms of throughput and delay, while DSr consumes the least energy. We also observe that the performance of the routing protocols varies with the density of vehicles and the mobility patterns of the nodes. Our study highlights the importance of conducting real-world experiments to evaluate the performance of routing protocols in VANETs, as they provide more realistic and accurate results than simulation-based studies. Our findings can help in the selection and design of efficient and secure routing protocols for VANETs.

关键词： routing metrics VANET mobile nodes simulation

High Throughput Scheduling Algorithms for Input Queued Packet Switches

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Computers, Materials & Continua 2022年第1期70卷 1527-1540页

作者： r.Chithra devi D.Jemi Florinabel Narayanan Prasanth Department of IT Dr.Sivanthi Aditanar College of EngineeringTiruchendur628205India Department of CSE Dr.Sivanthi Aditanar College of EngineeringTiruchendur628205India School of CSE Vellore Institute of TechnologyVellore632014India

The high-performance computing paradigm needs high-speed switching fabrics to meet the heavy traffic generated by their *** switching fabrics are efficiently driven by the deployed scheduling *** this paper,we proposed two scheduling algorithms for input queued switches whose operations are based on ranking *** first,we proposed a Simple 2-Bit(S2B)scheme which uses binary ranking procedure and queue size for scheduling the ***,the Virtual Output Queue(VOQ)set with maximum number of empty queues receives higher rank than other VOQ’*** simulation,we showed S2B has better throughput performance than Highest ranking First(HrF)arbitration under uniform,and non-uniform traffic *** further improve the throughput-delay performance,an Enhanced 2-Bit(E2B)approach is *** approach adopts an integer representation for rank,which is the number of empty queues in a VOQ *** simulation result shows E2B outperforms S2B and HrF scheduling algorithms with maximum throughput-delay ***,the algorithms are simulated under hotspot traffic and E2B proves to be more efficient.

关键词： Crossbar switch input queued switch virtual output queue scheduling algorithm high performance computing

ENTrOPY TOLErANT FUZZY C-MEANS IN MEDICAL IMAGES

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Journal of Innovative Optical Health Sciences 2011年第4期4卷 447-462页

作者： S.r.KANNAN S.rAMATHILAGAM r.devi YUEH-MIN HUANG Department of Mathematics ramanujan School of Mathematical Sciences Pondicherry University India Department of Mathematics Periyar Government College CuddaloreIndia Department of Engineering Science National Cheng Kung University TainanTaiwan

Segmenting the Dynamic Contrast-Enhanced Breast Magnetic resonance Images(DCE-BMrI)is an extremely important task to diagnose the disease because it has the highest specificity when acquired with high temporal and spatial resolution and is also corrupted by heavy noise,outliers,and other imaging *** this paper,we intend to develop efficient robust segmentation algorithms based on fuzzy clustering approach for segmenting the *** proposed segmentation algorithms have been amalgamated with effective kernel-induced distance measure on standard fuzzy c-means algorithm along with the spatial neighborhood information,entropy term,and tolerance vector into a fuzzy clustering structure for segmenting the *** significant feature of our proposed algorithms is its capability tofind the optimal membership grades and obtain effective cluster centers automatically by minimizing the proposed robust objective ***,this article demonstrates the superiority of the proposed algorithms for segmenting DCE-BMrI in comparison with other recent kernel-based fuzzy c-means *** the clustering accuracies of the proposed algorithms are validated by using silhouette method in comparison with existed fuzzy clustering algorithms.

关键词： Fuzzy clustering algorithms entropy method segmentation medical images

NONCONSTANT PrEY HArVESTING IN rATIO-DEPENDENT PrEDATOr-PrEY SYSTEM INCOrPOrATING A CONSTANT PrEY rEFUGE

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International Journal of Biomathematics 2012年第2期5卷 85-104页

作者： SAPNA devi DST Centre for Interdisciplinary Mathematical Sciences Banaras Hindu University Varanasi-221005 India

This paper deals with the problem of nonconstant harvesting of prey in a ratio-dependent predator-prey system incorporating a constant prey refuge. Here we use the reasonable catch-rate function instead of usual catch-per-unit-effort hypothesis. The existence, as well as the stability of possible equilibria, is carried out. Bionomic equilibrium of the system is determined and optimal harvest policy is studied with the help of Pontryagin＇s maximum principle. The key results developed in this paper are illustrated using numer- ical simulations. Our results indicate that dynamic behavior of the system very much depends on the prey refuge parameter and increasing amount of refuge could increase prey density and may lead to the extinction of predator population density.

关键词： Predator-prey prey refuge taxation ratio-dependent stability bionomic equilibrium harvesting optimal equilibrium.

FUZZY.C-MEANS IN FINDING SUBTYPES OF CANCErS IN CANCEr DATABASE

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Journal of Innovative Optical Health Sciences 2014年第1期7卷 109-128页

作者： S.r.KANNAN S.rAMTHILAGAM r.devi T.P.HONG Department of Mathematics Pondicherry Central University India Department of Mathematics Periyar Government College Tamil Nadu Department of Computer Science and Information Engineering National University of Kaohsiung Taiwan

Finding subtypes of cancer in breast cancer database is an extremely dificult task because ofheavy noise by measurement *** of the recent clustering techniques for breast cancerdatabase to achieve cancerous and noncancerous often weigh down the interpretability of ***,this paper tries to find effective Fuzzy C-Means-based clustering techniques toidentify the proper subtypes of cancer in breast cancer database,This paper obtains the objectivefunction of ffective Fuzzy C-Means clustering techriques by incorporating the kermel induceddist ance function,renyi's entropy function,weighted dist ance measure and neighborhood ternsbased spatial *** efectiveness of the proposed methods are proved through the ex-perimental works on Lung cancer database,IrIS dataset,Wine dat aset,Checkerboard dataset,Time Series dataset and Yeast ***,the proposed methods are implemented suc-cesfully to cluster the breast cancer dat abase into cancerous and *** clusteringaccuracy has been validat ed through error matrix and silhouette method.

关键词： Fuzzy C-Means kenel induced distance entropy terms cancer database