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Isolation and characterization of marine biofilm forming bacteriafrom a ship＇s hull

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Frontiers in Biology 2018年第3期13卷 208-214页

作者： kavitha S Vimala Raghavan School of Biosciences and Technology Vellore Institute of Technology Vellore-632-014 Tamil Nadu India Centre for Nanotechnology Researchl Vellore Institute of Technologyl Vellore-632 014 Tamil Nadu India

Background Diverse aquatic microorganisms are capable of colonizing living and non-living surfaces leading to the formation of biofilms. Commonly visualized as a slimy layer, these biofilms are filled with hundreds of other microorganisms compared to free living planktonic cells. Microbial surface colonization and surface-associated metabolic activities also exert several macroscale deleterious effects, including biofouling, biocorrosion and the persistence and transmission of harmful or pathogenic microorganisms and virulence determinants. The present study deals with the isolation and screening of marine bacteria for biofilm formation. The screened isolates were characterized and identified as Pychrobacter celer, Pychrobacter alimentarius and Kocuria rhizophila by 16S rRNA *** Biofilm forming bacteria were isolated by spread plate technique and subjected to screening by microtiter plate assay. The potent biofilm formers were identified by molecular characterization using 16S rRNA gene *** Twelve bacterial isolates were obtained by pour plate technique and subjected to biofilm assay. Among the 12 isolates three isolates which showed maximum biofilm formation were subjected to molecular characterizationby 16S rRNA gene sequencing method. The isolates were identified as Pychrobacter celer, Pychrobacter alimentarius and Kocuria rhizophila. The EPS produced by the three biofilm forming bacteria was extracted and the protein and carbohydrate content *** Among the isolates screened, isolate 8 (Kocuria rhizophila) produced maximum protein and carbohydrate which was also in accordance with the results of microtiter plate assay.

关键词： biofilm, MTP assay, extracellular polymeric substances, 16S rRNA gene sequencing, Psychrobacter, Kocuria

Hybrid Convolutional Neural Network and Long Short-Term Memory Approach for Facial Expression Recognition

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Intelligent Automation & Soft Computing 2023年第1期35卷 689-704页

作者： M.N.kavitha A.RajivKannan Department of Computer Science&Engineering Kongu Engineering CollegePerunduraiErode638060Tamil NaduIndia Department of Computer Science&Engineering K.S.R.College of EngineeringTiruchengode637215Tamil NaduIndia

Facial Expression Recognition(FER)has been an importantfield of research for several *** of emotional characteristics is crucial to FERs,but is complex to process as they have significant intra-class *** characteristics have not been completely explored in static *** studies used Convolution Neural Networks(CNNs)based on transfer learning and hyperparameter optimizations for static facial emotional *** Swarm Optimizations(PSOs)have also been used for tuning ***,these methods achieve about 92 percent in terms of *** existing algorithms have issues with FER accuracy and ***,the overall FER performance is degraded *** address this issue,this work proposes a combination of CNNs and Long Short-Term Memories(LSTMs)called the HCNN-LSTMs(Hybrid CNNs and LSTMs)approach for *** work is evaluated on the benchmark dataset,Facial Expression Recog Image Ver(FERC).Viola-Jones(VJ)algorithms recognize faces from preprocessed images followed by HCNN-LSTMs feature extractions and FER ***,the success rate of Deep Learning Techniques(DLTs)has increased with hyperparameter tunings like epochs,batch sizes,initial learning rates,regularization parameters,shuffling types,and *** proposed work uses Improved Weight based Whale Optimization Algorithms(IWWOAs)to select near-optimal settings for these parameters using bestfitness *** experi-mentalfindings demonstrated that the proposed HCNN-LSTMs system outper-forms the existing methods.

关键词： Facial expression recognition Gaussianfilter hyperparameter optimization improved weight-based whale optimization algorithm deep learning(DL)

Feature Selection with Optimal Variational Auto Encoder for Financial Crisis Prediction

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Computer Systems Science & Engineering 2023年第4期45卷 887-901页

作者： kavitha Muthukumaran K.Hariharanath Vani Haridasan SSN School of Management KalavakkamChennai603110India

Financial crisis prediction(FCP)received significant attention in the financial sector for *** forecasting of the number of firms possible to fail is important to determine the growth index and strength of a nation’s ***,numerous approaches have been developed in the design of accurate FCP *** the same time,classifier efficacy and predictive accuracy are inadequate for real-time *** addition,several established techniques carry out well to any of the specific datasets but are not adjustable to distinct ***,there is a necessity for developing an effectual prediction technique for optimum classifier performance and adjustable to various *** paper presents a novel ***(MVO)based feature selection(FS)with an optimal variational auto encoder(OVAE)model for *** proposed *** based feature selection with optimal variational auto encoder(MVOFS-OVAE)model mainly aims to accomplish forecasting the financial *** achieving this,the proposed MVOFS-OVAE model primarily pre-processes the financial data using min-max *** addition,the MVOFS-OVAE model designs a feature subset selection process using the MVOFS *** by,the variational auto encoder(VAE)model is applied for the categorization of financial data into financial crisis or non-financial ***,the differential evolution(DE)algorithm is utilized for the parameter tuning of the VAE model.A series of simulations on the benchmark dataset reported the betterment of the MVOFS-OVAE approach over the recent state of art approaches.

关键词： Financial crisis prediction forecasting feature selection data classification machine learning

Student Behavior Modeling for an E-Learning System Offering Personalized Learning Experiences

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Computer Systems Science & Engineering 2022年第3期40卷 1127-1144页

作者： K.Abhirami M.K.kavitha Devi Department of Computer Science and Engineering Kings College of EngineeringPudukkottai613303India Department of Computer Science and Engineering Thiagarajar College of EngineeringMadurai625015India

With the advent of computing and communication technologies,it has become possible for a learner to expand his or her knowledge irrespective of the place and ***-based learning promotes active and independent *** scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning *** digital learning improves the quality of teaching and also promotes educational ***,the challenges in e-learning platforms include dissimilarities in learner’s ability and needs,lack of student motivation towards learning activities and provision for adaptive learning *** quality of learning can be enhanced by analyzing the online learner’s behavioral characteristics and their application of intelligent instructional *** is not possible to identify the difficulties faced during the process through evaluation after the completion of e-learning *** is thus essential for an e-learning system to include component offering adaptive control of learning and maintain user’s interest *** this research work,a framework is proposed to analyze the behavior of online learners and motivate the students towards the learning process accordingly so as to increase the rate of learner’s objective *** to the demands of e-learner,an intelligent model is presented in this study for e-learning system that apply supervised machine learning *** adaptive e-learning system suits every category of learner,improves the learner’s performance and paves way for offering personalized learning experiences.

关键词： Learner behavior modeling e-learning intelligent learning system machine learning algorithm

Binder-free heterostructure(g-C3N4/PPy) based thin film on semi-flexible nickel foam via hybrid spray technique for energy storage application

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Progress in Natural Science:Materials International 2020年第3期30卷 298-307页

作者： Navaneethan Duraisamy Prabhu S Ramesh R kavitha Kandiah Department of Chemistry J.K.K.Nataraja College of Arts and Science Komarapalayam 2. Department of Physics Periyar University Department of Microbiology Periyar University Center for New and Renewable Energy Department of Physics Periyar University

A semi-flexible binder-free graphitic carbon nitride(g-CN) intercalated polypyrrole(PPy) nanocomposite thin film was prepared via hybrid electrospray technique. A homogeneous thin film was achieved by the controlled spray process. A deposited thin film illustrated the amorphous nature of composite with high surface purity and good chemical composition. The surface analysis confirmed the smoother surface with well-defined distinct phases of g-CNand PPy matrix in the composite thin film. The electrochemical studies exhibited that a maximum areal capacity of the thin film was achieved to be 289.6 mF/cm~2 at a current density of 0.4 mA/cm~2,which is higher than that of pristine PPy(194.8 mF/cm~2). The heterostructure electrode illustrated that the life cycles of 99% could be up to 10,000 cycles with low resistance due to the synergetic effect of g-CNand PPy matrix with strong material adhesion(hybrid spray process) on the surface. A binder-free heterostructure thin film will play a significant role in the energy storage application.

关键词： Polypyrrole G-C3N4 Heterostructure Spray Thin film Electrochemical study

Propagation of an electromagnetic soliton in an anisotropic biquadratic ferromagnetic medium

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Chinese Physics B 2013年第3期22卷 275-281页

作者： L.kavitha M.Saravanan D.Gopi Department of Physics Periyar University The Abdus Salam International Centre for Theoretical Physics TriesteItaly Center for Nanoscience and Nanotechnology Periyar University Department of Chemistry Periyar University

Information storage technology based on anisotropic ferromagnets with sufficiently high magneto-optical effects has received much attention in recent ***-optical recording combines the merits of magnetic and optical *** investigate the magneto-optical effects on a biquadratic ferromagnet and show that the dynamics of the system are governed by a perturbed nonlinear Schro¨dinger *** evolutions of amplitude and velocity of the soliton are found to be time independent,thereby admitting the lossless propagation of the electromagnetic soliton in the medium,which may have potential applications in soliton based optical communication *** also exploit the role of perturbation,which has a significant impact on the propagation of an electromagnetic soliton.

关键词： solitons classical spin models Maxwell equations nonlinear dynamics

Determination of the mechanism of photoinduced toxicity of selected metal oxide nanoparticles(ZnO,CuO,Co_3O_4 and TiO_2)to *** bacteria

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Journal of Environmental Sciences 2013年第5期25卷 882-888页

作者： Thabitha P.Dasari kavitha Pathakoti Huey-Min Hwang Environmental Science Ph.D.Program Jackson State UniversityJacksonMS 39217USA Department of Biology Jackson State UniversityJacksonMS 39217USA

Cytotoxicity of selected metal oxide nanoparticles（MNPs）（ZnO,CuO,Co 3 O 4 and TiO 2）was investigated in Escherichia coli both under light and dark *** experiments were conducted with spread plate counting and the LC 50 values were *** determined the mechanism of toxicity via measurements of oxidative stress,reduced glutathione,lipid peroxidation,and metal *** overall ranking of the LC 50 values was in the order of ZnO 〈 CuO 〈 Co 3 O 4 〈 TiO 2 under dark condition and ZnO 〈 CuO 〈 TiO 2 〈 Co 3 O 4 under light *** MNPs were the most toxic among the tested *** results indicate depletion of reduced glutathione level and elevation of malondialdehyde level correlated with the increase in oxidative *** metal ions were found to have partial effect on the toxicity of MNPs to *** summary,the dynamic interactions of multiple mechanisms lead to the toxicity of the tested MNPs to ***.

关键词： metal oxide nanoparticles reactive oxygen species median lethal concentration reduced glutathione lipid peroxidation

Design and Analysis of Novel Three-Phase PFC for IM Drives

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Intelligent Automation & Soft Computing 2023年第1期35卷 231-241页

作者： V.kavitha K.Subramanian VIT University VelloreTamil Nadu632014India Faculty of School of Electrical Engineering VIT UniversityVelloreTamil Nadu632014India

Induction motor drives(IMDs)can achieve high performance levels comparable to dc motor drives.A major problem in getting high dynamic performance in an IMD is the coupling between theflux and torque producing components of stator *** is successfully overcome in FOC(Field-Oriented Control)IM,making it to the industry standard *** performance of an IMD with an improved power quality converter at the front end is presented in this *** the IMD,boost converter is employed to reduce power quality difficulties at the utility *** the boost converter contains only one switch,it results in a low processing time and *** ensure sinusoidal supply currents with high PF(Power Factor)and minimal THD(Total Harmonic Distortion),a novel PFC(Power Factor Corrector)control technique is *** enhance the performance of the converter and to lower distortions at the motor side,PI(Proportional Integral)controller is incorporated at the PFC *** it controls the DC bus *** proposed boost converter improves power quality by lowering overall harmonic distortion of AC mains current,improving power factor correction,and regulating dc-link *** is designed,modelled,and simulated in the MATLAB/simulink *** a DSP(Digital Signal Processor),the suggested system’s performance is experimentally *** system’s performance is evaluated for speed and load torque,and the power quality indices are determined to meet IEEE-519 standards under all operating *** the obtained results,it is evident that the proposed system mitigates the power quality issues effectively.

关键词： Induction motor PI controller boost converter power factor corrector

Deep Capsule Residual Networks for Better Diagnosis Rate in Medical Noisy Images

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Intelligent Automation & Soft Computing 2023年第5期36卷 2959-2971页

作者： P.S.Arthy A.kavitha Department of Electronics and Communication Engineering Anna UniversityChennai600025India Department of Electronics and Communication Engineering M.Kumarasamy College of EngineeringKarur639113India

With the advent of Machine and Deep Learning algorithms,medical image diagnosis has a new perception of diagnosis and clinical ***-tably,medical images are more susceptible to capturing noises despite the peak in intelligent imaging ***,the presence of noise images degrades both the diagnosis and clinical treatment *** existing intelligent meth-ods suffer from the deficiency in handling the diverse range of noise in the ver-satile medical *** paper proposes a novel deep learning network which learns from the substantial extent of noise in medical data samples to alle-viate this *** proposed deep learning architecture exploits the advan-tages of the capsule network,which is used to extract correlation features and combine them with redefined residual ***,the final stage of dense learning is replaced with powerful extreme learning machines to achieve a better diagnosis rate,even for noisy and complex *** experimen-tation has been conducted using different medical *** performances such as Peak-Signal-To-Noise Ratio(PSNR)and Structural-Similarity-Index-Metrics(SSIM)are compared with the existing deep learning ***-tionally,a comprehensive analysis of individual algorithms is *** experimental results prove that the proposed model has outperformed the other existing algorithms by a substantial margin and proved its supremacy over the other learning models.

关键词： Machine and deep learning algorithm capsule networks residual networks extreme learning machines correlation features

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