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Mapping the Spatial Distributions of Water Quality and Their Interpolation with Land Use/Land Cover Using GIS and Remote Sensing in Noyyal River Basin, Tamil Nadu, India

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Journal of Geoscience and Environment Protection 2017年第8期5卷 211-220页

作者： Geetha Selvarani Arumaikkani sivakumar chelliah Maheswaran Gopalan Department of Civil Engineering K.S.R. College of Engineering Namakkal District Tamil Nadu India Department of Mechanical Engineering K.S.R. College of Engineering Namakkal District Tamil Nadu India VSA Group of Institutions VSA School of Engineering & Management Salem Tamil Nadu India

Noyyal River is historically, ecologically and culturally significant river in Kongu region of western Tamilnadu. More than 100 villages are situated along the banks of the Noyyal River and it’s the was the best site of inhabitation on both the sides of the river up to 3 km from the river before the emergence of the issue of industrial pollution. But now river Noyyal was highly polluted by domestic and industrial growth by discharging of both domestic and industrial are discharged without any treatment. So methodology was proposed to identify the suitable zone for groundwater quality by using land use/land cover data along with groundwater quality in analytic hierarchy process. Suitability of groundwater for drinking was identified in the study area by collecting 63 samples in both postmonsoon and premonsoon as per Indian standards. To evaluate the land use pattern of the study area, land use/land cover map was prepared from satellite images of LISS III by using supervised classification according to National Remote Sensing Agency (NRSA) using Erdas imagine 8.4 software. Using ArcGIS software, weighted overlay analyses were carried out to identify the suitable zones for groundwater quality in postmonsoon and premonsoon and finally these two thematic maps were integrated with land use/land cover map to identify the suitable zone for quality of water. The interpretation shows that groundwater in most of the locations were unsuitable for drinking purposes.

关键词： Noyyal River Drinking Water Quality Total Dissolved Solids GIS Land Use

Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

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Computers, Materials & Continua 2024年第1期78卷 1189-1205页

作者： K.Akilandeswari Nithya Rekha sivakumar Hend Khalid Alkahtani Shakila Basheer Sara Abdelwahab Ghorashi Department of Computer Sciences Government Arts College(Autonomous)Salem636007India Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and *** exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and *** many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during ***,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare *** first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction ***,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable *** attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced *** that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and *** evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several *** quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

关键词： Internet of Things smart health care monitoring human activity recognition intelligent agent learning statistical partial regression support vector

Insights into the anorexic mechanism of Khat:an integrated in vivo,ex vivo,and in silico investigations

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Traditional Medicine Research 2024年第10期9卷 36-51页

作者： Ahmed Ali Jerah Manal Mohamed Elhassan Taha Abdullah Farasani sivakumar Sivagurunathan Moni Emad Sayed Shaheen Andleeb Khan Ibrahim Abdo Khardali Magbool Oraiby Heyam Mohamed Ali Sidahmed Siddig Ibrahim Abdelwahab Department of Medical Laboratory Technology College of Applied Medical SciencesJazan UniversityJazan 45142Saudi Arabia Health Research Centre Jazan UniversityJazan 45142Saudi Arabia Department of Pharmaceutics College of PharmacyJazan UniversityJazan 45142Saudi Arabia Department of Biosciences Faculty of ScienceIntegral UniversityLucknow 226026India Poison Control and Medical Forensic Chemistry Center General Directorate of Health AffairsJazan 45142Saudi Arabia Department of Pharmaceutical Chemistry Faculty of PharmacyAl-Neelain UniversityKhartoum 16458Sudan

Background:Chewing Khat(Catha edulis)releases cathine and cathinone,which may reduce appetite via an unknown *** study investigated the peripheral and central effects of fresh leaves and buds of Catha edulis water extract(CEWE)on appetite biomarkers,gene expression,and body weight,using in vivo,ex vivo,and in silico ***:Rats of both sexes were orally administered CEWE at different doses and durations in three different *** chromatography-mass spectroscopy(LC-MS)-MS was used to detect cathinone and cathine in the murine *** effect of Khat on serotonin receptors was studied in isolated rat fundus *** of the two Khat ligands was performed on G(The 5-hydroxytryptamine-type 2C receptor(5-HT2C)in an agonist-bound active conformation)and H(5-HT2C in an antagonist-bound inactive conformation)proteins to determine which ligands are most likely to act as agonists or ***:Significant differences(P0.05).The expression of the ghrelin and leptin genes was also unaffected,but the expression of the 5-hydroxytryptamine(5-HT)gene decreased(P<0.05)with CEWE *** antagonizes 5-HT receptors in isolated rat fundus *** findings indicated that the khat ligands bound to 5-HT2C *** and cathinone levels in rat plasma were ***:Khat extract may suppress appetite by antagonizing the 5-HT *** research is required to understand its mechanism and potential applications.

关键词： Catha edulis appetite leptin ghrelin 5-hydroxytryptamine molecular docking

Strength Characteristics of Treated Soil with Proposed Layer Formation

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Journal of Wuhan University of Technology(Materials Science) 2023年第1期38卷 117-135页

作者： N sivakumar A Mandal Srinivasan venkatraman Department of Civil Engineering Visvesvaraya National Institute of TechnologyNagpur-440010India

The engineering characteristics of the soil,soil-fly ash and fly ash-lime,were examined to utilize as base layer material in civil *** influence of fly ash percentage and the effect of curing on California bearing ratio(CBR)and unconfined compressive strength(UCS),of soil and soil-fly ash mixing and layered system were examined to estimate the optimum *** volumetric swelling of the optimal mixture was estimated to be within the allowable *** microscope analysis and X-ray diffraction tests were performed.A model test analyses with three layers were conducted by finite element method and stress-strain behavior was observed.

关键词： Scanning electron microscopy simulation sustainable materials waste reduction X-ray diffraction

Ensemble Deep Learning for IoT Based COVID 19 Health Care Pollution Monitor

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Intelligent Automation & Soft Computing 2023年第2期35卷 2383-2398页

作者： Nithya Rekha sivakumar Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Internet of things(IoT)has brought a greater transformation in health-care sector thereby improving patient care,minimizing treatment *** pre-sent method employs classical mechanisms for extracting features and a regression model for *** methods have failed to consider the pollu-tion aspects involved during COVID 19 *** Ensemble Deep Learning and Framingham Feature Extraction(FFE)techniques,a smart health-care system is introduced for COVID-19 pandemic disease *** Col-lected feature or data via predictive mechanisms to form pollution *** maps are used to implement real-time countermeasures,such as storing the extracted data or feature in a Cloud server to minimize concentrations of air *** integrated with patient management systems,this solution would minimize pollution emitted via patient’s sensors by offering spaces in the cloud server when pollution thresholds are ***,the Gini Index factor infor-mation gain technique eliminates unimportant and redundant attributes while selecting the most relevant,reducing computing overhead and optimizing system ***,the COVID-19 disease prognosis ensemble deep learning-based classiﬁer is *** analysis is planned to measure the prediction accuracy,error,precision and recall for different numbers of *** results show that prediction accuracy is improved by 8%,error rate was reduced by 47%and prediction time is minimized by 36%compared to exist-ing methods.

关键词： Internet of Things Covid-19 ensemble deep learning framingham feature extraction

Deep Neural Artificial Intelligence for IoT Based Tele Health Data Anal

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Computers, Materials & Continua 2022年第3期70卷 4467-4483页

作者： Nithya Rekha sivakumar Ahmed Zohair Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational *** makes an effort to get the better of issues of health service delivery involving time factor,space and laborious terrains,validating cost-efficiency and finer ingress in both developed and developing *** health has been categorized into either real-time electronic communication,or store-andforward *** recent years,a third-class has been perceived as remote healthcare monitoring or tele health,presuming data obtained via Internet of Things(IOT).Although,tele health data analytics and machine learning have been researched in great depth,there is a dearth of studies that entirely concentrate on the progress of ML-based techniques for tele health data analytics in the IoT healthcare *** by this fact,in this work a method called,Weighted Bayesian and Polynomial Taylor Deep Network(WB-PTDN)is proposed to improve health prediction in a computationally efficient and accurate ***,the Independent Component Data Arrangement model is designed with the objective of normalizing the data obtained from the Physionet ***,with the normalized data as input,Weighted Bayesian Feature Extraction is applied to minimize the dimensionality involved and therefore extracting the relevant features for further health risk ***,to obtain reliable predictions concerning tele health data analytics,First Order Polynomial Taylor DNN-based Feature Homogenization is proposed that with the aid of First Order Polynomial Taylor function updates the new results based on the result analysis of old values and therefore provides increased transparency in decision *** comparison of proposed and existing methods indicates that the WB-PTDN method achieves higher accuracy,true positive rate and lesser response time for IoT based tele health data analytics than the traditional methods.

关键词： Telehealth internet of things independent component weighted bayesian first order polynomial taylor deep neural network

Enhanced Disease Identification Model for Tea Plant Using Deep Learning

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Intelligent Automation & Soft Computing 2023年第1期35卷 1261-1275页

作者： Santhana Krishnan Jayapal sivakumar Poruran Department of Electronics and Communication Engineering University College of EngineeringThirukkuvalaiNagapattinamTamilnadu610204India Department of Electronics and Communication Engineering Dr.NGP Institute of TechnologyCoimbatoreTamilnadu641048India

Tea plant cultivation plays a significant role in the Indian *** Tea board of India supports tea farmers to increase tea production by preventing various diseases in Tea *** climatic factors and other parameters cause these *** this paper,the image retrieval model is developed to identify whether the given input tea leaf image has a disease or is *** in image retrieval is a hot topic in the industry as it doesn’t require any form of metadata related to the images for storing or *** Hashing with Integrated Autoencoders is our proposed method for image retrieval in Tea Leaf *** is an efficient andflexible way of retrieving Tea Leaf *** has an integrated autoencoder which makes it better than the state-of-the-art methods giving better results for the MAP(mean average precision)scores,which is used as a parameter to judge the efficiency of the *** autoencoders used with skip connections increase the weightage of the prominent features present in the previous *** constitutes a hybrid model for hashing and retrieving images from a tea leaf data *** proposed model will examine the input tea leaf image and identify the type of tea leaf *** relevant image will be retrieved based on the resulting type of *** model is only trained on scarce data as a real-life scenario,making it practical for many applications.

关键词： Image retrieval autoencoders deep hashing plant disease tea leaf blister blight

SIMAP500: A novel risk score to identify recipients at higher risk of hepatocellular carcinoma recurrence following liver transplantation

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World Journal of Transplantation 2024年第3期14卷 132-143页

作者： Amr Alnagar Nekisa Zakeri Konstantinos Koilias Rosemary E Faulkes Rachel Brown Owen Cain M Thamara P R Perera Keith J Roberts Rebeca Sanabria-Mateos David C Bartlett Yuk Ting Ma Shivan sivakumar Shishir Shetty Tahir Shah Bobby V M Dasari Department of HBP and Liver Transplantation Surgery Queen Elizabeth HospitalUniversity Hospitals BirminghamBirmingham B152GWUnited Kingdom Centre for Liver Research Institute of Biomedical ResearchBirmingham B152TTUnited Kingdom Department of Hepatology Queen Elizabeth HospitalUniversity Hospitals BirminghamBirmingham B152GWUnited Kingdom Department of Pathology University Hospitals Birmingham NHS Foundation TrustBirmingham B152GWUnited Kingdom Department of Oncology Queen Elizabeth HospitalUniversity Hospitals of BirminghamBirmingham B152GWUnited Kingdom

BACKGROUND Recurrence of hepatocellular carcinoma(HCC)following liver transplantation(LT)has a devastating influence on recipients’survival;however,the risk of recur-rence is not routinely *** stratification is vital with a long LT waiting time,as that could influence the recurrence despite strict listing *** This study aims to identify predictors of recurrence and develop a novel risk pre-diction score to forecast HCC recurrence following *** A retrospective review of LT for HCC recipients at University Hospitals Bir-mingham between July 2011 and February *** and multivariate analyses were performed to identify recurrence predictors,based on which the novel SIMAP500(satellite nodules,increase in size,microvascular invasion,AFP>500,poor differentiation)risk score was *** 234 LTs for HCC were performed with a median follow-up of 5.3 *** developed in 25 patients(10.7%).On univariate analyses,RETREAT score>3,α-fetoprotein(AFP)at listing 100-500 and>500,bridging,increased tumour size between imaging at the listing time and explant histology,increase in the size of viable tumour between listing and explant,presence of satellite nodules,micro-and macrovascular invasion on explant and poor differentiation of tumours were significantly associated with recurrence,based on which,the SIMAP500 risk score is *** SIMAP500 demonstrated an excellent predictive ability(c-index=0.803)and outper-formed the RETREAT score(c-index=0.73).SIMAP500 is indicative of the time to disease *** SIMAP500 risk score identifies the LT recipients at risk of HCC *** stratification allows patient-centric post-transplant surveillance *** validation of the score is recommended.

关键词： Liver transplantation Hepatocellular carcinoma Recurrence Survival

ANovel Light Weight CNN Framework Integrated with Marine Predator Optimization for the Assessment of Tear Film-Lipid Layer Patterns

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Computer Modeling in Engineering & Sciences 2023年第7期136卷 87-106页

作者： Bejoy Abraham Jesna Mohan Linu Shine sivakumar Ramachandran Department of Computer Science and Engineering College of Engineering MuttatharaThiruvananthapuramKerala695008India Department of Computer Science and Engineering Mar Baselios College of Engineering and TechnologyThiruvananthapuramKerala695015India Department of Electronics and Communication Engineering College of Engineering TrivandrumKerala695016India

Tear film,the outermost layer of the eye,is a complex and dynamic structure responsible for tear *** tear film lipid layer is a vital component of the tear film that provides a smooth optical surface for the cornea and wetting the ocular *** eye syndrome(DES)is a symptomatic disease caused by reduced tear production,poor tear quality,or excessive *** diagnosis is a difficult task due to its multifactorial *** of several clinical tests available,the evaluation of the interference patterns of the tear film lipid layer forms a potential tool for DES *** instrument known as Tearscope Plus allows the rapid assessment of the lipid layer.A grading scale composed of five categories is used to classify lipid layer *** reported work proposes the design of an automatic system employing light weight convolutional neural networks(CNN)and nature inspired optimization techniques to assess the tear film lipid layer patterns by interpreting the images acquired with the Tearscope *** designed framework achieves promising results compared with the existing state-of-the-art techniques.

关键词： Dry-eye syndrome tearscope plus tear film deep neural networks