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An Intelligent Big Data Security Framework Based on AEFS-KENN Algorithms for the Detection of Cyber-Attacks from Smart Grid Systems

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Big Data Mining and Analytics 2024年第2期7卷 399-418页

作者： Sankaramoorthy Muthubalaji Naresh Kumar Muniyaraj Sarvade Pedda Venkata Subba Rao kavitha Thandapani Pasupuleti Rama Mohan Thangam Somasundaram Yousef Farhaoui Department of Electrical and Electronics Engineering CMR College of Engineering&TechnologyHyderabad 501401India Department of Electronics and Communication Engineering Vardhaman College of Engineering KacharamShamshabad 501218India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and TechnologyHyderabad 501301India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600062India Department of Electrical and Electronics Engineering Bharat Institute of Engineering and TechnologyHyderabad 501510India Department of Computer Science and Engineering Amrita School of ComputingAmrita Vishwa VidhyapeethamBengaluru 560035India T-IDMS Department of Computer ScienceFaculty of Sciences and TechniquesMoulay Ismail UniversityErrachidia 52000Morocco

Big data has the ability to open up innovative and ground-breaking prospects for the electrical grid,which also supports to obtain a variety of technological,social,and financial *** is an unprecedented amount of heterogeneous big data as a consequence of the growth of power grid technologies,along with data processing and advanced *** main obstacles in turning the heterogeneous large dataset into useful results are computational burden and information *** original contribution of this paper is to develop a new big data framework for detecting various intrusions from the smart grid systems with the use of AI ***,an AdaBelief Exponential Feature Selection(AEFS)technique is used to efficiently handle the input huge datasets from the smart grid for boosting ***,a Kernel based Extreme Neural Network(KENN)technique is used to anticipate security vulnerabilities more *** Polar Bear Optimization(PBO)algorithm is used to efficiently determine the parameters for the estimate of radial basis ***,several types of smart grid network datasets are employed during analysis in order to examine the outcomes and efficiency of the proposed AdaBelief Exponential Feature Selection-Kernel based Extreme Neural Network(AEFS-KENN)big data security *** results reveal that the accuracy of proposed AEFS-KENN is increased up to 99.5%with precision and AUC of 99%for all smart grid big datasets used in this study.

关键词： smart grid Machine Learning(ML) big data analytics AdaBelief Exponential Feature Selection(AEFS) Polar Bear Optimization(PBO) Kernel Extreme Neural Network(KENN)

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Robust Deep Transfer Learning Based Object Detection and Tracking Approach

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Intelligent Automation & Soft Computing 2023年第3期35卷 3613-3626页

作者： C.Narmadha T.kavitha R.Poonguzhali V.Hamsadhwani Ranjan walia Monia B.Jegajothi Electronics and Communication Engineering Periyar Maniammai Institute of Science&Technology(PMIST)Thanjavur613403India Department of Computer Science and Engineering Periyar Maniammai Institute of Science&TechnologyThanjavur613403India Department of Electrical and Electronics Engineering Periyar Maniammai Institute of Science and TechnologyThanjavur613403India Electrical Engineering Department Model Institute of Engineering&Technology(Autonomous)Jammu181122India Department of Computer Science and Engineering Shri Mata Vaishno Devi UniversityKatra182320India Center for Energy Research Chennai Institute of TechnologyChennai600069India

At present days,object detection and tracking concepts have gained more importance among researchers and business ***,deep learning(DL)approaches have been used for object tracking as it increases the perfor-mance and speed of the tracking *** paper presents a novel robust DL based object detection and tracking algorithm using Automated Image Anno-tation with ResNet based Faster regional convolutional neural network(R-CNN)named(AIA-FRCNN)*** AIA-RFRCNN method performs image anno-tation using a Discriminative Correlation Filter(DCF)with Channel and Spatial Reliability tracker(CSR)called DCF-CSRT *** AIA-RFRCNN model makes use of Faster RCNN as an object detector and tracker,which involves region proposal network(RPN)and Fast *** RPN is a full convolution network that concurrently predicts the bounding box and score of different *** RPN is a trained model used for the generation of the high-quality region proposals,which are utilized by Fast R-CNN for detection ***,Residual Network(ResNet 101)model is used as a shared convolutional neural network(CNN)for the generation of feature *** performance of the ResNet 101 model is further improved by the use of Adam optimizer,which tunes the hyperparameters namely learning rate,batch size,momentum,and weight ***,softmax layer is applied to classify the *** performance of the AIA-RFRCNN method has been assessed using a benchmark dataset and a detailed comparative analysis of the results takes *** outcome of the experiments indicated the superior characteristics of the AIA-RFRCNN model under diverse aspects.

关键词： Object detection tracking deep learning deep transfer learning image annotation

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Oppositional Harris Hawks Optimization with Deep Learning-Based Image Captioning

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Computer Systems Science & Engineering 2023年第1期44卷 579-593页

作者： V.R.kavitha K.Nimala A.Beno K.C.Ramya Seifedine Kadry Byeong-Gwon Kang Yunyoung Nam Department of Computer Science and Engineering Prathyusha Engineering CollegeThiruvallur602025India Department of Networking and Communications SRM Institute of Science and TechnologyChennaiIndia Department of Electronics and Communication Engineering Dr.Sivanthi Aditanar College of EngineeringTiruchendur628215India Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Department of Information and Communication Engineering Soonchunhyang UniversityAsanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Image Captioning is an emergent topic of research in the domain of artificial intelligence(AI).It utilizes an integration of Computer Vision(CV)and Natural Language Processing(NLP)for generating the image *** use in several application areas namely recommendation in editing applications,utilization in virtual assistance,*** development of NLP and deep learning(DL)modelsfind useful to derive a bridge among the visual details and textual *** this view,this paper introduces an Oppositional Harris Hawks Optimization with Deep Learning based Image Captioning(OHHO-DLIC)*** OHHO-DLIC technique involves the design of distinct levels of ***,the feature extraction of the images is carried out by the use of EfficientNet ***,the image captioning is performed by bidirectional long short term memory(BiLSTM)model,comprising encoder as well as *** last,the oppositional Harris Hawks optimization(OHHO)based hyperparameter tuning process is performed for effectively adjusting the hyperparameter of the EfficientNet and BiLSTM *** experimental analysis of the OHHO-DLIC technique is carried out on the Flickr 8k Dataset and a comprehensive comparative analysis highlighted the better performance over the recent approaches.

关键词： Image captioning natural language processing artificial intelligence machine learning deep learning

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Probabilistic QOS Aware Congestion Control in Wireless Multimedia Sensor Networks

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Circuits and Systems 2016年第9期7卷 2081-2094页

作者： Muthuselvi Mayandi kavitha Velayudhan Pillai Department of Computer Science and Engineering University College of Engineering Nagercoil Anna University Chennai India Department of Computer Science and Engineering University College of Engineering Kancheepuram Anna University Chennai India

The general problem faced in the field of Wireless Multimedia Sensor Networks (WMSNs) is congestion. The most common method in the area of WMSNs to minimize congestion is traffic control. Quality Of Service (QOS) is widely used in WMSNs to guarantee preferential service for critical applications by controlling end-to-end delay, reducing data loss and by providing adequate bandwidth. The present work is on Probabilistic QOS Aware Congestion Control (PQACC) which employs probabilistic method based congestion prediction and priority based data transmission rate adjustment, where inelastic real-time traffic and elastic non-real-time traffic are treated separately. Using the present PQACC approach, average throughput, average source-to-sink delay and average packet loss probability are improved by 9%, 10.33% and 16.03% compared to EWPBRC and achieved 5.97%, 7.05% and 11.69% improvement compared to FEWPBRC. Simulation result reveals that, congestion is effectively predicted, controlled and provides necessary level of QOS in terms of delay, throughput and packet loss, hence making this approach possible in mission critical applications.

关键词： Congestion Control WMSN Traffic Control QOS Probabilistic Method Inelastic Traffic Elastic Traffic

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Simultaneous Quantitative Determination of Nitidine, Chelerythrine and Sanguinarine Using HPTLC from Callus Extract of <i>Zanthoxylum rhetsa</i>

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American Journal of Analytical Chemistry 2018年第8期9卷 386-396页

作者： kavitha Perala Veeresham Ciddi University College of Pharmaceutical Sciences Kakatiya University Warangal India

Nitidine, Chelerythrine and Sanguinarine, all these three alkaloids are benzophenanthridine alkaloids. Nitidine was used as an anti-HIV, anti-malarial and anti-cancer. Chelerythrine had anti-cancer and anti-inflammatory activities. Sanguinarine was widely used as an anti-plaquestic and anti-cancer. High performance thin layer chromatography (HPTLC) method was used for simultaneous quantification of Nitidine, Chelerythrine and Sanguinarine in callus extract of Zanthoxylum rhetsa by using Silica gel 60 F254 as stationary phase and ethyl acetate:methanol:water:diethylamine (30:5:2:0.5 v/v) as mobile phase at 280 nm. The linearity concentration range was 5 - 160 μg/band of each alkaloid. The Rf values of Nitidine, Chelerythrine and Sanguinarine were found to be 0.28, 0.49 and 0.73. The limit of detection and limit of quantification were found to be 0.026, 0.088 μg/spot and 0.010 and 0.033 μg/spot, 0.0104 and 0.035 μg/spot respectively for Nitidine, Chelerythrine and Sanguinarine. HPTLC method was developed and validated according to ICH guidelines for simultaneous estimation of Nitidine, Chelerythrine and Sanguinarine and proved to be simple, specific, accurate, robust and rapid.

关键词： Nitidine Chelerythrine Sanguinarine HPTLC

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Papillary Cystadenoma of Larynx: A Case Report

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International Journal of Otolaryngology and Head & Neck Surgery 2013年第6期2卷 280-285页

作者： Tammam Abou Ali Basel Al Sabah kavitha Gopalan kavitha Gopalan Department of ENT Farwaniya Hospital Al-Farwaniyah Kuwait Department of ENT Zain & Al Sabah Hospital Kuwait City Kuwait

An uncommon clinical entity of papillary cystadenoma of the larynx in a lady of 37-year-old is presented. The diagnosis after clinical examination was achieved by video-stroboscopy, CT scan of the neck, biopsy and histopathological examination. This case study emphasizes the importance of recognition of this lesion by the clinician as the differential diagnosis includes lesions with similar clinical appearance.

关键词： Papillary Cystadenoma Larynx Minor Salivary Gland Tumors

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Knowledge and attitudes towards the use of histological assessments in ulcerative colitis by gastroenterologists vs pathologists

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World Journal of Gastroenterology 2023年第2期29卷 378-389页

作者： Aviv Pudipeddi Caroline Fung Britt Christensen Robert V Bryant kavitha Subramaniam John Chetwood Sudarshan Paramsothy Rupert W Leong Gastroenterology and Liver Services Concord Repatriation General HospitalSydney 2139Australia Faculty of Medicine and Health Concord Clinical SchoolUniversity of SydneySydney 2138Australia Department of Anatomical Pathology Concord Repatriation General HospitalSydney 2139Australia Department of Gastroenterology Royal Melbourne HospitalMelbourne 3050Australia Department of Medicine University of MelbourneMelbourne 3052Australia Department of Gastroenterology and Hepatology The Queen Elizabeth HospitalAdelaide 5011Australia Gastroenterology and Hepatology Unit Canberra HospitalCanberra 2605Australia Australian National University Medical School Australian National UniversityCanberra 2601Australia Faculty of Medicine and Health Sciences Macquarie University HospitalSydney 2109Australia

BACKGROUND Histological remission is increasingly accepted as a treatment endpoint in the management of ulcerative colitis(UC).However,the knowledge of histology guidelines and the attitudes towards their use in clinical practice by gastroenterologists and pathologists is *** To evaluate the knowledge of histology guidelines and attitudes towards the use of histology in UC by gastroenterologists and *** A prospective,cross-sectional nationwide survey of gastroenterologists and pathologists who analyse UC specimens was *** survey consisted of 34 questions to assess gastroenterologists’and pathologists’knowledge(score out of 19)and attitudes towards histological assessment in *** questions were formulated using the European Crohn’s and Colitis position paper on histopathology and the British Society of Gastroenterology biopsy reporting *** included knowledge of histological assessment of disease activity and dysplasia,knowledge of histological scoring systems for ulcerative colitis,uptake of histology scoring systems in routine practice,attitudes towards the role of histological activity,and the use of histological activity in clinical *** Of 89 responders(77 gastroenterologists,12 pathologists),there was almost universal acceptance that histological assessment should form part of UC evaluation[95%gastroenterologists,92%pathologists].However,gastroenterologists reported that 92%of their pathologists do not use a histological scoring *** of a formal histological scoring system was preferred by 77%of gastroenterologists and 58%of *** groups lacked awareness of the Geboes Score,Nancy Index and Robarts Histopathological Index scoring systems with 91%,87%,and 92%of gastroenterologists respectively;and 83%,83%,and 92%pathologists respectively,being uncertain of scoring systems’remission *** knowledge score was not significantly different between gastroenterologist

关键词： Histology Scoring system Ulcerative colitis Survey

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Determination of Optimum Film Thickness and Composition of Cu(InAl)Se<sub>2</sub>Thin Films as anAbsorber for Solar Cell Applications

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World Journal of Nano Science and Engineering 2011年第4期1卷 108-118页

作者： Balakrishnan kavitha Muthusamy Dhanam 不详

Cu(InAl)Se2 [CIAS] thin films have been prepared by chemical bath deposition [CBD] technique. X-ray diffraction [XRD] and Energy dispersive X-ray analysis [EDAX] spectra have been employed to confirm the structure and composition of the prepared films. The structural parameters have been estimated from XRD and EDAX spectra and their variation with film thickness and composition has been discussed in this paper in detail. From the discussion we enabled to find the optimum film thickness and composition of CIAS thin films for solar cell applications.

关键词： CBD XRD EDAX CIAS Thin Films

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AModified Search and Rescue Optimization Based Node Localization Technique inWSN

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Computers, Materials & Continua 2022年第1期70卷 1229-1245页

作者： Suma Sira Jacob K.Muthumayil M.kavitha Lijo Jacob Varghese M.Ilayaraja Irina V.Pustokhina Denis A.Pustokhin Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Information Technology PSNA College of Engineering and TechnologyDindigul624622India Department of Electronics and Communication Engineering K.Ramakrishnan College of TechnologyTiruchirappalli621112India Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India School of Computing Kalasalingam Academy of Research and EducationKrishnankoil626128India Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia

Wireless sensor network(WSN)is an emerging technology which find useful in several application areas such as healthcare,environmentalmonitoring,border surveillance,*** issues that exist in the designing of WSN are node localization,coverage,energy efficiency,security,and so *** spite of the issues,node localization is considered an important issue,which intends to calculate the coordinate points of unknown nodes with the assistance of *** efficiency of the WSN can be considerably influenced by the node localization ***,this paper presents a modified search and rescue optimization based node localization technique(MSRONLT)*** major aim of theMSRO-NLT technique is to determine the positioning of the unknown nodes in *** the traditional search and rescue optimization(SRO)algorithm suffers from the local optima problemwith an increase in number of iterations,MSRO algorithm is developed by the incorporation of chaotic maps to improvise the diversity of the *** application of the concept of chaotic map to the characteristics of the traditional SRO algorithm helps to achieve better exploration ability of the MSRO *** order to validate the effective node localization performance of the MSRO-NLT algorithm,a set of simulations were performed to highlight the supremacy of the presented model.A detailed comparative results analysis showcased the betterment of the MSRO-NLT technique over the other compared methods in terms of different measures.

关键词： Node localization WSN chaotic map search and rescue optimization algorithm localization error

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Hybrid Energy-Efficient Transmission Protocol for Heterogeneous Wireless Sensor Networks

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Circuits and Systems 2016年第6期7卷 897-906页

作者： Ramaswami Jothi kavitha Britto Elizabeth Caroline Department of ECE University College of Engineering Panruti (A Constituent College of Anna University) Panruti India Department of ECE IFET College of Engineering Villupuram India

Heterogeneous Wireless Sensor Networks (WSNs) have different sensing ranges and computing power in the midst of various resource constraints such as limited battery power, reduced transmit power and network potential. This paper proposes new hybrid energy efficient transmission protocol called Hybrid Transmission Protocol (HTP). The proposed algorithm focuses on the issues of throughput dreadful conditions and limited power on mobile nodes due to conflicts in multi-cell wireless networks. The design principle of the proposed routing algorithm is to introduce a new border cluster between the sink nodes and the cluster-heads in order to lengthen the lifetime of the network nodes with minimized energy consumption to attain energy efficiency. The creation of clusters is done by making use of the sensor nodes formation that has a Cluster-Head (CH) used for performing the data aggregation in the sensor nodes of the cluster. Later the data that is aggregated is transmitted with multiple hops to the base station and in turn, this process leads to the reduction in the bandwidth through the elimination of the redundant data present in a cluster. The performance results indicate that the HTP proposed gained greater network lifetime, better performance and higher throughput compared to the other available algorithms.

关键词： Heterogeneous WSN Border Cluster FND PNA

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