检索结果-南通市图书馆

An Intelligent Approach for Accurate Prediction of Chronic Diseases

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第8期46卷 2571-2587页

作者： S.Kavi priya N.Saranya Mepco Schlenk Engineering College SivakasiTamilnaduIndia

Around the globe,chronic diseases pose a serious hazard to healthcare *** majority of the deaths are due to chronic diseases,and it causes burdens across the *** analyzing healthcare data and extracting patterns healthcare administrators,victims,and healthcare communities will get an advantage if the diseases are early *** majority of the existing works focused on increasing the accuracy of the techniques but didn’t concentrate on other performance ***,the proposed work improves the early detection of chronic disease and safeguards the lives of the patients by increasing the specificity and sensitivity of the classifiers along with the *** proposed work used a hybrid optimization algorithm called the Hybrid Gravitational Search algorithm and Particle Swarm Optimization algorithm(HGSAPSO)to upgrade the detection of chronic *** classifier parameters with their optimized parameters are compared and *** such as Artificial Neural Network(ANN),Support Vector Machines(SVM),K-Nearest Neighbor(Knn),and Decision tree(DT)are *** care data are obtained from the UCI machine learning repository to evaluate the proposed *** proposed work is assessed on 6 benchmark datasets and the performance metrics such as Accuracy,Specificity,Sensitivity,F-measure,Recall,and Precision are *** experimental results exhibit that the proposed work attains better accuracy on Artificial Neural Network-Hybrid Gravitational Search algorithm and Particle Swarm Optimization algorithm(ANN-HGSAPSO)classifier compared to other ***-HGSAPSO provides 93%accuracy for Chronic Kidney Disease(CKD),Cardio Vascular Disease(CVD)96%,Diabetes 82%,Hepatitis 94%,Wisconsin Breast Cancer(WBC)91%,and for Liver disease dataset 96%.

关键词： Chronic diseases optimization gravitational search algorithm particle swarm optimization machine learning algorithms

Real-Time Multi Fractal Trust Evaluation Model for Efficient Intrusion Detection in Cloud

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Intelligent Automation & Soft Computing 2023年第8期37卷 1895-1907页

作者： S.priya R.S.Ponmagal Department of Computer Science and Engineering School of ComputingSRM Institute of Science and TechnologyChengapattu603203Tamil NaduIndia Department of Computing Technologies School of ComputingSRM Institute of Science and TechnologyChengapattu603203Tamil NaduIndia

Handling service access in a cloud environment has been identified as a critical challenge in the modern internet world due to the increased rate of intrusion *** address such threats towards cloud services,numerous techniques exist that mitigate the service threats according to different *** rule-based approaches are unsuitable for new threats,whereas trust-based systems estimate trust value based on behavior,flow,and other ***,the methods suffer from mitigating intrusion attacks at a higher *** article presents a novel Multi Fractal Trust Evaluation Model(MFTEM)to overcome these *** method involves analyzing service growth,network growth,and quality of service *** process estimates the user’s trust in various ways and the support of the user in achieving higher service performance by calculating Trusted Service Support(TSS).Also,the user’s trust in supporting network stream by computing Trusted Network Support(TNS).Similarly,the user’s trust in achieving higher throughput is analyzed by computing Trusted QoS Support(TQS).Using all these measures,the method adds the Trust User Score(TUS)value to decide on the clearance of user *** proposed MFTEM model improves intrusion detection accuracy with higher performance.

关键词： Intrusion detection cloud systems trusted service support trusted network support trust user score trusted QoS support

Identification of Arbuscular mycorrhizal multiplicity in the saline-sodic soils

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

International Journal of Agricultural and Biological Engineering 2014年第2期7卷 56-67页

作者： Srimathi priya L Kumutha K Arthee R Pandiyarajan P Department of Agricultural Microbiology Tamil Nadu Agricultural UniversityCoimbatore-641003India Department of Agricultural Microbiology Anbil Dharmalingam Agricultural CollegeTrichy-641009India

This study focused on the Arbuscular mycorrhizal(AM)fungal diversity in the saline-sodic soils based on native spore density and most probable number(MPN)*** through spore morphology showed existence of five genera in the various crop *** physico-chemical analysis of the native soils revealed that they were saline-sodic with pH ranging from(8.7±0.5)to(9.5±0.6)and habituated five different genera of AM fungi including Glomus,Scutellospora,Acaulospora,Sclerocystis and *** location revealed presence of varied species of AM fungus namely Acaulospora and Glomus in rhizosphere of maize;Scutellospora and Glomus in tulsi;four isolates of Glomus in onion;Glomus and Sclerocystis in guava;three isolates of Glomus in rice;Glomus in neem and Gigaspora and Glomus in *** molecular identification through nested PCR analysis showed amplification of 600 bp size in SSU rDNA gene in samples A and C(predominated by Acaulospora and Glomus mosseae respectively).

关键词： AM fungal identification saline-sodic soil crop rhizosphere spore density nested PCR technology glomalean fungus

On examining the predictive capabilities of two variants of the PINN in validating localized wave solutions in the generalized nonlinear Schr?dinger equation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Communications in Theoretical Physics 2024年第11期76卷 161-174页

作者： K Thulasidharan N Sinthuja N Vishnu priya M Senthilvelan Department of Physics Vellore Institute of TechnologyVellore-632014TamilnaduIndia Department of Physics Anna UniversityChennai-600025TamilnaduIndia Department of Mathematics Indian Institute of ScienceBangalore 560012KarnatakaIndia Department of Nonlinear Dynamics Bharathidasan UniversityTiruchirappalli-620024TamilnaduIndia

We introduce a novel neural network structure called strongly constrained theory-guided neural network(SCTgNN),to investigate the behaviour of the localized solutions of the generalized nonlinear Schr?dinger(NLS)*** equation comprises four physically significant nonlinear evolution equations,namely,the NLS,Hirota,Lakshmanan-Porsezian-Daniel and fifth-order NLS *** generalized NLS equation demonstrates nonlinear effects up to quintic order,indicating rich and complex dynamics in various fields of *** combining concepts from the physics-informed neural network and theory-guided neural network(TgNN)models,the SCTgNN aims to enhance our understanding of complex phenomena,particularly within nonlinear systems that defy conventional *** begin,we employ the TgNN method to predict the behaviour of localized waves,including solitons,rogue waves and breathers,within the generalized NLS *** then use the SCTgNN to predict the aforementioned localized solutions and calculate the mean square errors in both the SCTgNN and TgNN in predicting these three localized *** findings reveal that both models excel in understanding complex behaviour and provide predictions across a wide variety of situations.

关键词： generalized nonlinear Schr?dinger equation soliton rogue waves breathers SCTgNN TgNN

Identification, quantification and agerelated changes of human trabecular meshwork stem cells

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Eye and Vision 2019年第1期6卷 261-270页

作者： Yogapriya Sundaresan Muthukkaruppan Veerappan Krishnadas Subbiah Ramasamy Gowri priya Chidambaranathan Department of Immunology and Stem Cell Biology Aravind Medical Research FoundationMaduraiTamil NaduIndia. Glaucoma Clinic Aravind Eye Hospital and Post Graduate Institute of OphthalmologyMaduraiTamil NaduIndia

Background:Loss of cells in the human trabecular meshwork(TM)has been reported with ageing and in *** study aims to identify,quantify and determine the age-related changes of human TM stem cells(TMSCs).Methods:Isolation of TM cells/paraffin sectioning was carried out using human corneoscleral rings and whole *** TM cells/sections were immunostained for the stem cell markers ATP-binding cassette protein G2(ABCG2),nerve growth factor receptor p75 and AnkyrinG(AnkG).Images were acquired using Leica SP8 confocal *** isolated cells were analyzed for two parameters-ABCG2 expression and nucleus to cytoplasmic ratio(N/C ratio).The total number of TM cells and those positive for ABCG2 and p75 in each section were *** rank order correlation was used to determine the association between age and the cell ***:The TMSCs were identified based on two parameters-high ABCG2 expression and high N/C ratio>*** stem cells were also positive for p75 and *** TMSC content based on the two parameters was 21.0±1.4%in60 *** stem cells with high ABCG2 and p75 expression were restricted to the Schwalbe’s line region of the TM.A significant correlation was observed between the reduction in TMSC content and TM cell count during ***:The human TMSCs were identified and quantified based on two parameter *** study established a significant association between age-related reduction in TMSC content and TM cell loss.

关键词： Human trabecular meshwork Trabecular meshwork stem cells Two-parameter analysis Age-related changes Primary open angle glaucoma

Feature Selection with Deep Reinforcement Learning for Intrusion Detection System

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第9期46卷 3339-3353页

作者： S.priya K.Pradeep Mohan Kumar Department of Computer Science and Engineering SRM Institute of Science and TechnologyRamapuramChennai600089India Department of Computing Technologies SRM Institute of Science and TechnologyKattankulathurChennai603203India

An intrusion detection system(IDS)becomes an important tool for ensuring security in the *** recent times,machine learning(ML)and deep learning(DL)models can be applied for the identification of intrusions over the network *** resolve the security issues,this paper presents a new Binary Butterfly Optimization algorithm based on Feature Selection with DRL technique,called BBOFS-DRL for intrusion *** proposed BBOFSDRL model mainly accomplishes the recognition of intrusions in the *** attain this,the BBOFS-DRL model initially designs the BBOFS algorithm based on the traditional butterfly optimization algorithm(BOA)to elect feature ***,DRL model is employed for the proper identification and classification of intrusions that exist in the ***,beetle antenna search(BAS)technique is applied to tune the DRL parameters for enhanced intrusion detection *** ensuring the superior intrusion detection outcomes of the BBOFS-DRL model,a wide-ranging experimental analysis is performed against benchmark *** simulation results reported the supremacy of the BBOFS-DRL model over its recent state of art approaches.

关键词： Intrusion detection security reinforcement learning machine learning feature selection beetle antenna search

Entropy optimization on Casson nanofluid flow with radiation and Arrhenius activation energy over different geometries:A numerical and statistical approach

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Propulsion and Power Research 2024年第3期13卷 375-393页

作者： M.priya P.Bala Anki Reddy Department of Mathematics S.A.S.Vellore Institute of TechnologyVellore 632014India

This study employs numerical and statistical approaches to investigate the entropy optimization of steady Casson nanofluidflow over three different geometries subject to boundary conditions induced by *** linear regression is employed to statistically *** present model incorporates several novel elements,such as Arrhenius activation energy,Brownian motion,the Cattaneo-Christov dualflux,thermophoresis,thermal radiation,and so ***,a comparison is presented between Newtonian and *** applying the proper similarity transformations,ordinary differential equations(ODEs)are ob-tained by converting foundational partial differential equations(PDEs).The Runge-Kutta fourth-order method is utilised to solve the obtained ODEs along with the shooting *** out-comes are visually depicted via tables and *** velocity drops with increasing Grashof number,and the magneticfield becomes progressively more forceful as the suction parameter *** temperature gets reduced with the increase of the suction parameter,solute Grashof number increases with the magneticfield,thermophoresis,and radiation *** entropy is observed to rise with the increase of the effective parameters(magneticfield,Brinkmann num-ber and radiation).The MAD(mean absolute deviation),MSE(mean squared error),and RMSE(root mean square error)values are approaching zero,indicating that the derived outcomes are highly accurate.A lower MAPE(mean absolute percentage error)suggests that the model has a higher level of ***,the outcomes of the present model are more precise and *** study has various potential applications such as power plant heat exchangers,material processing industries,and solar thermal energy systems.

关键词： Cassonfluid Arrhenius activation energy Entropy generation Thermophoresis Multiple linear regression

EliteVec: Feature Fusion for Depression Diagnosis Using Optimized Long Short-Term Memory Network

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Intelligent Automation & Soft Computing 2023年第5期36卷 1745-1766页

作者： S.Kavi priya K.Pon Karthika Mepco Schlenk Engineering College(Autonomous) Sivakasi626005TamilnaduIndia

Globally,depression is perceived as the most recurrent and risky disor-der among young people and adults under the age of *** has a strong inﬂuence on the usage of words which can be observed in the form of written texts or stories posted on social *** the help of Natural Language Proces-sing(NLP)and Machine Learning(ML)techniques,the depressive signs expressed by people can be identiﬁed at the earliest stage from their Social Media *** proposed work aims to introduce an efﬁcacious depression detection model unifying an exemplary feature extraction scheme and a hybrid Long Short-Term Memory network(LSTM)*** feature extraction process combines a novel feature selection method called Elite Term Score(ETS)and Word2Vec to extract the syntactic and semantic information ***,the ETS method leverages the document level,class level,and corpus level prob-abilities for computing the weightage/score of the ***,the ideal and per-tinent set of features with a high ETS score is selected,and the Word2vec model is trained to generate the intense feature vector representation for the set of selected ***,the resultant word vector obtained is called EliteVec,which is fed to the hybrid LSTM model based on Honey Badger optimizer with population reduction technique(PHB)which predicts whether the input textual content is depressive or *** PHB algorithm is integrated to explore and exploit the opti-mal hyperparameters for strengthening the performance of the LSTM *** comprehensive experiments are carried out with two different Twitter depres-sion corpus based on accuracy and Root Mean Square Error(RMSE)*** results demonstrated that the proposed EliteVec+LSTM+PHB model outperforms the state-of-art models with 98.1%accuracy and 0.0559 RMSE.

关键词： Depression detection dimensionality reduction feature extraction feature selection hybrid LSTM network population reduction honey badger optimization social media twitter

Differential changes in intrinsic innervation and interstitial cells of Cajal in small bowel atresia in newborns

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

World Journal of Gastroenterology 2010年第45期16卷 5716-5721页

作者： Stefan Gfroerer Roman Metzger Henning Fiegel priya Ramachandran Udo Rolle Department of Paediatric Surgery Johann Wolfgang Goethe-University Frankfurt/MTheodor-Stern-Kai 760590 Frankfurt/MGermany Department of Paediatric Surgery University of Leipzig04103 LeipzigGermany Department of Pediatric Surgery Kanchi Kamakoti Childs Trust Hospital12-A ChennaiIndia

AIM: To investigate morphological changes of the enteric nervous system (ENS) and the interstitial cells of Cajal (ICCs) in small bowel ***: Resected small bowel specimens from affected patients (n = 7) were divided into three parts (proximal, atretic, distal). Standard histology and enzyme immunohistochemistry anti-S100, anti-protein gene product (PGP) 9.5, anti-neurofilament (NF), antic-kit-receptor (CD117) was carried out on conventional paraffin sections of the proximal and distal part. RESULTS: The neuronal and glial markers (PGP 9.5, NF, S-100) were expressed in hypertrophied ganglia and nerve fibres within the myenteric and submucosal plexuses. Furthermore, the submucous plexus contained typical giant ganglia. The innervation pattern of the proximal bowel resembled intestinal neuronal dysplasia. The density of myenteric ICCs was clearly reduced in the proximal bowel, whereas a moderate number of muscular ICCs were found. The anti-CD117 immunore- action revealed additional numerous mast cells. The distal bowel demonstrated normal morphology and density of the ENS, the ICCs and the mast ***: The proximal and distal bowel in small bowel atresia revealed clear changes in morphology and density of the ENS and ICCs.

关键词： Small bowel atresia Enteric nervous system Gastrointestinal motility Interstitial cells of Cajal