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A Novel Soft Clustering Approach for Gene expression Data

Computer Systems Science & engineering 2022年第12期43卷 871-886页

作者： e.kavitha R.Tamilarasan Arunadevi Baladhandapani M.K.Jayanthi Kannan A Constituent College of Anna University University College of EngineeringVillupuram605103India A Constituent College of Anna University University College of EngineeringPattukkottai614701India Department of electronics and Communication engineering Dr.N.G.P Institute of TechnologyCoimbatore641048India Department of Computer Science engineering Faculty of Engineering and TechnologyJAIN(Deemed to be University)Bangalore562112India

Gene expression data represents a condition matrix where each rowrepresents the gene and the column shows the condition. Micro array used todetect gene expression in lab for thousands of gene at a time. Genes encode proteins which in turn will dictate the cell function. The production of messengerRNA along with processing the same are the two main stages involved in the process of gene expression. The biological networks complexity added with thevolume of data containing imprecision and outliers increases the challenges indealing with them. Clustering methods are hence essential to identify the patternspresent in massive gene data. Many techniques involve hierarchical, partitioning,grid based, density based, model based and soft clustering approaches for dealingwith the gene expression data. Understanding the gene regulation and other usefulinformation from this data can be possible only through effective clustering algorithms. Though many methods are discussed in the literature, we concentrate onproviding a soft clustering approach for analyzing the gene expression data. Thepopulation elements are grouped based on the fuzziness principle and a degree ofmembership is assigned to all the elements. An improved Fuzzy clustering byLocal Approximation of Memberships (FLAMe) is proposed in this workwhich overcomes the limitations of the other approaches while dealing with thenon-linear relationships and provide better segregation of biological functions.

关键词： Reinforcement membership centroid threshold statistics bioinformatics gene expression data

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Clustering Gene expression Data Through Modified Agglomerative M-CURe Hierarchical Algorithm

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Computer Systems Science & engineering 2022年第6期41卷 1027-1041页

作者： e.kavitha R.Tamilarasan N.Poonguzhali M.K.Jayanthi Kannan A Constituent College of Anna University University College of EngineeringVillupuram605103India A Constituent College of Anna University University College of EngineeringPattukkottai614701India Department of Computer Science and engineering Manakula Vinayagar Institute of TechnologyPuducherry605107India Department of Computer Science engineering Faculty of Engineering and TechnologyJAIN(Deemed-To-Be University)Bangalore562112India

Gene expression refers to the process in which the gene information isused in the functional gene product synthesis. They basically encode the proteinswhich in turn dictate the functionality of the cell. The first step in gene expressionstudy involves the clustering usage. This is due to the reason that biological networks are very complex and the genes volume increases the comprehending challenges along with the data interpretation which itself inhibit vagueness, noise andimprecision. For a biological system to function, the essential cellular moleculesmust interact with its surrounding including RNA, DNA, metabolites and proteins. Clustering methods will help to expose the structures and the patterns inthe original data for taking further decisions. The traditional clustering techniquesinvolve hierarchical, model based, partitioning, density based, grid based and softclustering methods. Though many of these methods provide a reliable output inclustering, they fail to incorporate huge data of gene expressions. Also, thereare statistical issues along with choosing the right method and the choice of dissimilarity matrix when dealing with gene expression data. We propose to use amodified clustering algorithm using representatives (M-CURe) in this workwhich is more robust to outliers as compared to K-means clustering and also ableto find clusters with size variances.

关键词： Clustering gene identifiers representatives dimension reduction

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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

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OSCILLATORY BeHAVIOR OF SOLUTIONS OF CeRTAIN THIRD ORDeR MIXeD NeUTRAL DIFFeReNCe eQUATIONS

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Acta Mathematica Scientia 2013年第1期33卷 218-226页

作者： e.THANDAPANI N.kavitha Ramanujan Institute for Advanced Study in Mathematics University of MadrasChennai 600 005India

The objective of this paper is to study the oscillatory and asymptotic properties of the mixed type third order neutral difference equation of the form△（an△^2（xn＋bnxn-τ1＋cnxn＋τ2））＋qnx^βn＋1-σ1＋pnx^^βn＋1＋σ2=0,where （an）, （bn}, （cn}, （qn} and （pn} are positive real sequences, β is a ratio of odd positive integers, τ1, τ2, and σ2 are positive integers. We establish some sufficient conditions which ensure that all solutions are either oscillatory or converges to zero. Some examples are presented to illustrate the main results.

关键词： oscillation third order mixed type neutral difference equation

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Development of Algorithm for Person Re-Identification Using extended Openface Method

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Computer Systems Science & engineering 2023年第1期44卷 545-561页

作者： S.Michael Dinesh A.R.kavitha Anna University Chennai600025India Department of Computer Science&engineering SRM Institute of Science&TechnologyChennai600026India

Deep learning has risen in popularity as a face recognition technology in recent ***,a deep convolutional neural network(DCNN)developed by Google,recognizes faces with 128 bytes per *** also claims to have achieved 99.96%on the reputed Labelled Faces in the Wild(LFW)***-ever,the accuracy and validation rate of Facenet drops down eventually,there is a gradual decrease in the resolution of the *** research paper aims at developing a new facial recognition system that can produce a higher accuracy rate and validation rate on low-resolution face *** proposed system extended Openface performs facial recognition by using three different features i)facial landmark ii)head pose iii)eye *** extracts facial landmark detection using Scattered Gated expert Network Constrained Local Model(SGeN-CLM).It also detects the head pose and eye gaze using enhanced Constrained Local Neur-alfield(eCLNF).extended openface employs a simple Support Vector Machine(SVM)for training and testing the face *** system’s performance is assessed on low-resolution datasets like LFW,Indian Movie Face Database(IMFDB).The results demonstrated that extended Openface has a better accuracy rate(12%)and validation rate(22%)than Facenet on low-resolution images.

关键词： Constrained local model enhanced constrained local neuralfield enhanced hog scattered gated expert network support vector machine

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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

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enhancing perianal disease management with integrated physical and psychological approaches

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World Journal of Clinical Cases 2025年第2期13卷 59-63页

作者： Uchenna e Okpete Haewon Byeon Department of Digital Anti-aging Healthcare(BK21) Inje UniversityGimhae 50834South Korea

This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal *** study sheds light on how illness perception,anxiety,and depression significantly influence recovery *** et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor *** article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for *** study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.

关键词： Perianal disease Post-operative recovery Anxiety Depression Pain management emotional well-being Multidisciplinary approach

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Brain-derived neurotrophic factor alterations and cognitive decline in schizophrenia:Implications for early intervention

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World Journal of Psychiatry 2025年第1期15卷 189-193页

作者： Uchenna e Okpete Haewon Byeon Department of Digital Anti-aging Healthcare(BK21) Inje UniversityGimhae 50834South Korea

This manuscript explores the recent study by Cui et al which assessed the interplay between inflammatory cytokines and brain-derived neurotrophic factor(BDNF)levels in first-episode schizophrenia *** study revealed that higher levels of interleukin-6 and tumor necrosis factor-αcorrelated with reduced BDNF levels and poorer cognitive *** is a severe psy-chiatric disorder impacting approximately 1%of the global population,charac-terized by positive symptoms(hallucinations and delusions),negative symptoms(diminished motivation and cognitive impairments)and disorganized thoughts and *** research highlights the role of BDNF as a potential biomarker for early diagnosis and therapeutic *** findings from Cui et al’s study suggest that targeting neuroinflammation and enhancing BDNF levels may improve cognitive *** treatment approaches involve a com-bination of pharmacological and non-pharmacological interventions tailored to individual patient ***,monitoring cognitive and neuroinflammatory markers is essential for improving patient outcomes and quality of ***-quently,this manuscript highlights the need for an integrated approach to schizo-phrenia management,considering both clinical symptoms and underlying neuro-biological changes.

关键词： Schizophrenia Cognitive impairment Neuroinflammatory markers Brain-derived neurotrophic factor Interleukin Personalized treatment

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Diabetic Retinopathy Diagnosis Using Interval Neutrosophic Segmentation with Deep Learning Model

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Computer Systems Science & engineering 2023年第3期44卷 2129-2145页

作者： V.Thanikachalam M.G.kavitha V.Sivamurugan Department of Information Technology Sri Sivasubramaniya Nadar College of EngineeringChennai603110India Department of Computer Science and engineering University College of Engineering PtukottaiRajamadam614701India

In recent times,Internet of Things(IoT)and Deep Learning(DL)mod-els have revolutionized the diagnostic procedures of Diabetic Retinopathy(DR)in its early stages that can save the patient from vision *** the same time,the recent advancements made in Machine Learning(ML)and DL models help in developing Computer Aided Diagnosis(CAD)models for DR recognition and *** this background,the current research works designs and develops an IoT-enabled effective Neutrosophic based Segmentation with Optimal Deep Belief Network(ODBN)model i.e.,NS-ODBN model for diagnosis of *** presented model involves Interval Neutrosophic Set(INS)technique to dis-tinguish the diseased areas in fundus *** addition,three feature extraction techniques such as histogram features,texture features,and wavelet features are used in this ***,Optimal Deep Belief Network(ODBN)model is utilized as a classification model for *** model involves Shuffled Shepherd Optimization(SSO)algorithm to regulate the hyperparameters of DBN technique in an optimal *** utilization of SSO algorithm in DBN model helps in increasing the detection performance of the model *** presented technique was experimentally evaluated using benchmark DR dataset and the results were validated under different evaluation *** resultant values infer that the proposed INS-ODBN technique is a promising candidate than other existing techniques.

关键词： Diabetic retinopathy machine learning internet of things deep belief network image segmentation

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NeCAB family of neuronal calcium-binding proteins in health and disease

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Neural Regeneration Research 2025年第5期20卷 1236-1243页

作者： Diones Bueno Michael K.e.Schafer Sudena Wang Michael J.Schmeisser Axel Methner Institute for Molecular Medicine University Medical Center of the Johannes Gutenberg-UniversityMainzGermany Department of Anesthesiology University Medical Center of the Johannes Gutenberg-UniversityMainzGermany Institute of Anatomy University Medical Center of the Johannes Gutenberg-UniversityMainzGermany

The N-terminal eF-hand calcium-binding proteins 1–3(NeCAB1–3) constitute a family of predominantly neuronal proteins characterized by the presence of at least one eF-hand calcium-binding domain and a functionally less well characterized C-terminal antibiotic biosynthesis monooxygenase domain. All three family members were initially discovered due to their interactions with other proteins. NeCAB1 associates with synaptotagmin-1, a critical neuronal protein involved in membrane trafficking and synaptic vesicle exocytosis. NeCAB2 interacts with predominantly striatal G-protein-coupled receptors, while NeCAB3 partners with amyloid-β A4 precursor protein-binding family A members 2 and 3, key regulators of amyloid-β production. This demonstrates the capacity of the family for interactions with various classes of proteins. NeCAB proteins exhibit distinct subcellular localizations: NeCAB1 is found in the nucleus and cytosol, NeCAB2 resides in endosomes and the plasma membrane, and NeCAB3 is present in the endoplasmic reticulum and Golgi apparatus. The antibiotic biosynthesis monooxygenase domain, an evolutionarily ancient component, is akin to atypical heme oxygenases in prokaryotes but is not wellcharacterized in vertebrates. Prokaryotic antibiotic biosynthesis monooxygenase domains typically form dimers, suggesting that calcium-mediated conformational changes in NeCAB proteins may induce antibiotic biosynthesis monooxygenase domain dimerization, potentially activating some enzymatic properties. However, the substrate for this enzymatic activity remains uncertain. Alternatively, calcium-mediated conformational changes might influence protein interactions or the subcellular localization of NeCAB proteins by controlling the availability of protein–protein interaction domains situated between the eF hands and the antibiotic biosynthesis monooxygenase domain. This review summarizes what is known about genomic organization, tissue expression, intracellular localization, interac

关键词： calcium eF hand mitochondria nervous system signal transduction

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