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Prediction of Cardiovascular Disease Using Machine Learning Technique—A Modern Approach

Computers, Materials & Continua 2022年第4期71卷 855-869页

作者： Visvasam Devadoss Ambeth Kumar chetan swarup Indhumathi Murugan Abhishek Kumar Kamred Udham Singh Teekam Singh Ramu Dubey Department of Computer Science&Engineering Panimalar Engineering CollegeAnna UniversityChennai600123India Department of Basic Science College of Science&Theoretical StudiesSaudi Electronic UniversityRiyadh-Male Campus 13316Saudi Arabia Department of Computer Science&IT JAIN(Deemed to be University)Bangalore560069India Department of Computer Science and Information Engineering National Cheng Kung UniversityTainan 701Taiwan Department of Mathematics Graphic Era Hill UniversityDehradun248002India Department of Mathematics J.C.Bose University of Science&TechnologyYMCAFaridabad121006India

Cardio Vascular disease(CVD),involving the heart and blood vessels is one of the most leading causes of death throughout the *** are several risk factors for causing heart diseases like sedentary lifestyle,unhealthy diet,obesity,diabetes,hypertension,smoking and consumption of alcohol,stress,hereditary factory *** cardiovascular disease and improving and treating the risk factors at an early stage are of paramount importance to save the precious life of a human *** present,the highly stressful life with bad lifestyle activities causes heart disease at a very young *** main aim of this research is to predict the premature heart disease based on machine learning *** paper deals with a novel approach using the machine learning algorithm for predicting the cardiovascular disease at the premature stage *** Vector Machine(SVM)is used for segregating the CVD patients based on their symptoms and medical *** experimentation results by using the proposed method will facilitate the medical practitioners to provide suitable treatment for the patients on time.A sophisticated model has been developed with the current approach to examine the various stages of CVD and the performance metrics used have given effective and fruitful results as compared to other machine learning techniques.

关键词： Machine learning support vector machine classification cardiovascular disease

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Detection of Behavioral Patterns Employing a Hybrid Approach of Computational Techniques

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Computers, Materials & Continua 2022年第7期72卷 2015-2031页

作者： Rohit Raja chetan swarup Abhishek Kumar Kamred Udham Singh Teekam Singh Dinesh Gupta Neeraj Varshney Swati Jain Department of Information Technology Guru Ghasidas VishwavidyalayaBilaspur495009India Department of Basic Science College of Science&Theoretical StudiesSaudi Electronic University13316Saudi Arabia Department of Computer Science&IT JAIN(Deemed to be University)Bangalore560069India Computer Science and Information Science Cheng Kung University621301Taiwan School of Computer Science University of Petroleum and Energy StudiesDehradun248007India Department of CSE I K Gujral Punjab Technical UniversityJalandhar144603India Department of Computer Engineering and Applications GLA UniversityMathura281406India Department of Computer Science Government J Yoganandam Chhattisgarh CollegeRaipur492001India

As far as the present state is concerned in detecting the behavioral pattern of humans(subject)using morphological image processing,a considerable portion of the study has been conducted utilizing frontal vision data of human *** present research work had used a side vision of human-face data to develop a theoretical framework via a hybrid analytical model *** this example,hybridization includes an artificial neural network(ANN)with a genetic algorithm(GA).We researched the geometrical properties extracted from side-vision human-face *** additional study was conducted to determine the ideal number of geometrical characteristics to pick while *** close vicinity ofminimum distance measurements is done for these clusters,mapped for proper classification and decision process of behavioral *** identify the data acquired,support vector machines and artificial neural networks are utilized.A method known as an adaptiveunidirectional associative memory(AUTAM)was used to map one side of a human face to the other side of the same *** behavioral pattern has been detected based on two-class problem classification,and the decision process has been done using a genetic algorithm with best-fit *** developed algorithm in the present work has been tested by considering a dataset of 100 subjects and tested using standard databases like FERET,Multi-PIE,Yale Face database,RTR,CASIA,*** complexity measures have also been calculated under worst-case and best-case situations.

关键词： Adaptive-unidirectional-associative-memory technique artificial neural network genetic algorithm hybrid approach

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Prediction of Springback in Long Channels

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Acta Metallurgica Sinica(English Letters) 2015年第12期28卷 1525-1531页

作者： chetan P.Nikhare Mechanical Engineering Penn State Behrend

Sheet metal forming is one of the most preferred manufacturing processes in automotive and aerospace industries. However, due to increase in fuel prices and more stringent environmental regulation, these industries are facing many challenges to meet the criteria. Due to this, many efforts in design and manufacturing were considered and *** efforts were implementing lighter-weight materials like aluminum and magnesium（but they have higher elasticity as compared to steel） and implementing higher-strength steel with lower thickness. The main challenge found in both cases is springback after deformation. Springback is the elastic recovery after the part is unloaded. In this paper, the 3D channels with large length were deformed numerically and springback at different section was predicted. For this purpose, tailorwelded blank was considered. The geometric change along the long axis was also discussed. In addition, the effect of flange springback on wall springback was also analyzed. It was found that different section produced different springback and greater influence of flange springback. To validate the numerical simulation approach, the experiments on one case were performed and compared.

关键词： Channel forming Springback Numerical simulation Tailor-welded blanks

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Machine learning techniques for prediction of capacitance and remaining useful life of supercapacitors: A comprehensive review

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Journal of Energy Chemistry 2023年第2期77卷 438-451,I0011页

作者： Vaishali Sawant Rashmi Deshmukh chetan Awati Department of Technology Shivaji UniversityKolhapurMaharashtraIndia

Supercapacitors are appealing energy storage devices for their promising features like high power density,outstanding cycling stability,and a quick charge–discharge *** exceptional life cycle and ultimate power capability of supercapacitors are needed in the transportation and renewable energy generation ***,predicting the capacitance and lifecycle of supercapacitors is significant for selecting the suitable material and planning replacement intervals for *** addition,system failures can be better addressed by accurately forecasting the lifecycle of ***,the use of machine learning for performance prediction of energy storage materials has drawn increasing attention from researchers globally because of its superiority in prediction accuracy,time efficiency,and *** article presents a detailed review of the progress and advancement of ML techniques for the prediction of capacitance and remaining useful life(RUL)of *** review starts with an introduction to supercapacitor materials and ML applications in energy storage devices,followed by workflow for ML model building for supercapacitor ***,the summary of machine learning applications for the prediction of capacitance and RUL of different supercapacitor materials including EDLCs(carbon based materials),pesudocapacitive(oxides and composites)and hybrid materials is ***,the general perspective for future directions is also presented.

关键词： Supercapacitors Energy storage materials Artificial neural network Machine learning Capacitance prediction Remaining useful life

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Climate change detection and attribution in the Ganga-Brahmaputra-Meghna river basins

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Geoscience Frontiers 2021年第5期12卷 192-201页

作者： chetan Sharma Anoop Kumar Shukla Yongqiang Zhang Civil Engineering Department JIETJodhpurRajasthanIndia Key Laboratory of Water Cycle and Related Land Surface Processes Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China

Ganga-Brahmaputra-Meghna(GBM)river basin is the third-largest and one of the most populated river basins in the *** climate change is affecting most of the hydrometeorological variables across the globe,this study investigated the existence of climate change signal in all four climatological seasons in the GBM river basin and assessed the contribution of anthropogenic activities,i.e.,Greenhouse Gases(GHGs)emission in the *** decreasing trends in the monsoon and a small increase in pre-monsoon precipitation were *** change was detected in post-monsoon and winter season ***5 GCMs were used for climate change detection,change point estimation,and attribution *** Vector Machine(SVM)regression method was adopted to downscale GCM variables at the local ***-Carlo simulation approach was used to detect changes in different *** climate change‘signals’were detectable after the year 1980 using Signal to Noise ratio(SNR)method in the majority of central and north-western *** change point was detectable only in annual monsoon precipitation at the basin *** analysis indicated>50%contribution of anthropogenic activities(GHGs)to annual monsoon precipitation ***,there is high confidence that monsoon precipitation in GBM has significantly changed due to anthropogenic *** mitigation and adaption measures are also suggested,which may be adopted to manage the growing demand and water availability in the basin.

关键词： Ganga-Brahmaputra-Meghna(GBM) Climate change Support vector machine Signal to noise ratio Anthropogenic activities

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Understanding of tip clearance flow structure in high speed mixed flow compressor

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Propulsion and Power Research 2023年第3期12卷 356-379页

作者： Hemant Kumar chetan S.Mistry Department of Aerospace Engineering Indian Institute of TechnologyKharagpurWest Bengal 721302India

This paper addresses the necessity to make a physical interpretation of a highly complex three-dimensional tip clearance flow field study for high-speed mixed-flow compressor having stage exit static pressure to inlet total pressure ratio of 3.8 with 39,836 rpm rotor *** four different tip configurations namely the constant(l Z 0.016 and 0.019)and variable(l Z 0.011(inlet)-0.019(exit)and 0.019(inlet)-0.022(exit))tip clearances were numerically analysed using available experimental *** numerical investigation reveals that in contrast to the classic jet-wake pattern,two anomalous velocity profiles formed at the impeller exit which results in pressure losses in the vaneless *** the impeller inlet,the tip leakage flow rolls up to discrete tip leakage vortex structure for each tip clearance *** results in the formation of a region of momentum deficit,recirculation zone,which gets weakened as it moves *** tip clearance configuration is observed to profoundly influence the extent and vorticity of the tip leakage *** the splitter blade passage,the tip leakage flow and Coriolis flow interact with passage flow,resulting in the formation of two secondary passage vortices that move downstream along the pressure and suction surface of the splitter *** tip clearance configuration directly influences the impeller exit jetwake pattern by modulating the secondary passage vortices trajectory and ***,off-design analysis for tip clearances l Z 0.016 and l Z 0.019,depict distinctive tip leakage vortex *** operating near the stall conditions(80%of design mass flow rate),l Z 0.019 exhibits bubble shape tip leakage vortex breakdown occurring near the impeller *** result in a substantial change in the tip leakage vortex nature;expansion of the recirculation zone and early weakening of the vorticity in the tip leakage *** is observed that vortex breakdown plays a vital role in characte

关键词： Recirculation zone Vortex breakdown Tip leakage flow Mixed-flow compressor Jet-wake flow Vaned-diffuser

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Multiclass recognition of Alzheimer’s and Parkinson’s disease using various machine learning techniques: A study

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International Journal of Modeling, Simulation, and Scientific Computing 2022年第1期13卷 235-250页

作者： chetan Balaji D.S.Suresh Department of ECE Channabasaveshwara Institute of Technology Tumkur KarnatakaIndia Visvesvaraya Technological University BelagaviKarnatakaIndia

The aging population is primarily affected by Alzheimer’s disease(AD)that is an incur-able neurodegenerative *** is a need for an automated efficient technique to diagnose Alzheimer’s in its early *** techniques are used to diagnose *** and neuroimaging methodologies are widely used to highlight changes in the electrical activity of the brain signals that are helpful for early ***’s disease(PD)is a major neurological disease that results in an average of 50,000 new clinical diagnoses worldwide every *** voice features are majorly used as the main means to diag-nose *** major symptoms of PD are loss of intensity,the monotony of loudness and pitch,reduction in stress,unidentified silences,and *** though various innovative models are proposed by explorers about Alzheimer’s and Parkinson’s classifi-cation diseases,still there is a need for efficient learning methodologies and *** paper provides a review on using machine learning(ML)together with several fea-ture extraction techniques that is helpful in the early detection of AD with Parkinson’*** novelty and objective of this study are that the CAD technique is used to improve the accuracy of early diagnosis of *** proposed technique depends on the nonlinear process for data dimension reduction,feature removal,and classification using kernel-based support vector machine(SVM)*** dimension of the input space is radically diminished with kernel *** the learning set is labeled,it creates sense to utilize this information to make a dependable method of dropping the input space *** different techniques of ML are explained under the major approaches ***,artificial neural network(ANN),deep learning(DL),and ensemble methods.A comprehensive assessment is presented at SVM,ANN,and DL approaches for better detection of Alzheimer’s with PD highlighting future insights.

关键词： Electroencephalograph support vector machine Alzheimer’s disease control normal machine learning

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Determination of Parameters of Time-delayed Embedding Algorithm Using Koopman Operator-based Model Predictive Frequency Control

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CSEE Journal of Power and Energy Systems 2021年第6期7卷 1140-1151页

作者： Xiawen Li chetan Mishra Shichao Chen Yajun Wang Jaime De La Ree Dominion Energy RichmondVAUSA Thorlabs Quantum Electronics. JessupMDUSA Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State UniversityBlacksburgVAUSA

Power systems around the world have been registering a degenerating inertial response in view of the growth of inverter-based resources along with the withdrawal of conventional coal ***,there is a need for swift frequency support and its control,preferably by means of power electronic-interfaced storage devices,owing to their beneficial *** being particularly efficient,pragmatically,the traditional model-based non-linear control techniques are not highly popular in power system control design,primarily due to the complications faced in obtaining accurately suitable models for certain power system ***,the modelfree Koopman operator-based model predictive control(KMPC)has proven to be highly conducive for data-driven non-linear control *** principle behind KMPC is to change the coordinates in a manner to get an approximately linear model,which can then be controlled using a linear model predictive *** this study,we employed time-delayed embedding of measurements to reconstruct a new set of preferable coordinates,thereby suggesting an approach for finding the optimal number of time lags and the embedding dimensions which are the key parameters of this *** efficacy of this KMPC framework is established by adopting a decentralized frequency control problem through a decoupled synchronous machine system,which we proposed for both the Kundur two-area system as well as the IEEE 39-bus test system.

关键词： False nearest neighbors koopman operator model predictive control non-linear control time-delayed embedding

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Clinical Significance of Liver Function Abnormality in Patients with COVID-19:A Single-center Experience from Western India

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Journal of Clinical and Translational Hepatology 2021年第6期9卷 878-888页

作者： chetan R.Kalal Harshad Joshi Vivek Kumar Divya Gopal Darshana Rathod Ashish Shukla Tarang Gianchandani chetan Bhatt Department of Gastroenterology Hepatology and Liver TransplantSir HN Reliance Foundation Hospital and Research Cen-treMumbaiMaharashtraIndia Department of Critical Care Sir HN Reliance Foundation Hospital and Research CentreMumbaiMaharashtraIndia Department of Administration Sir HN Reliance Foundation Hospital and Research CentreMumbaiMaharashtraIndia

Background and Aims:The impact of coronavirus disease-2019(COVID-19)on liver function remains to be fully *** study was designed to investigate such and determine the clinical significance in determining mortality ***:A retrospective study was conducted in patients with COVID-19 from March 2020 to July *** details were retrieved from electronic medical records to obtain clinical characteristics,medical history,laboratory tests,therapeutic intervention,and outcome ***:A total of 184 patients with COVID-19 were included(median age:45.5 years),comprised of 62.5%*** total,22(12.0%)patients had severe infection and 162(88.0%)had mild to moderate ***,95(51.6%)showed abnormal liver function test(LFT)and 17(9.2%)showed normal LFT at *** median age,hospital stay,and LFT were significantly higher in severe ***-severe infection(p<0.001).Out of 12 deaths,the majority were due to severe infection(n=11).Deaths were also due to acute respiratory distress syndrome(n=5),cardiac reasons(n=3),and sepsis with multiorgan failure(n=3).The median age,hospital stay and number of intensive care unit admissions were higher in patients having abnormal LFT compared to normal *** of elevated aspartate aminotransferase(42.8%and 40.4%),alanine transaminase(43.7%and 41.6%),and hypoalbuminemia(71.4%and72.7%)at admission and discharge were more common in severe *** mean survival was significantly lower in severe infection compared to those with non-severe disease(17.2 vs.52.3 days;p<0.001).Conclusions:Incidence of abnormal liver function was higher in patients with severe COVID-19 and was associated with prolonged hospital stay;mortality was associated with severity of *** ruling out the risk of liver injury,it is crucial to vigilantly monitor the liver function parameters in patients with COVID-19 admitted to hospital.

关键词： ALT/AST Hospital stay Hypoalbuminemia Liver injury Severe disease

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Li3PO4:M(M=Tb,Cu)phosphors for radiation dosimetry

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Rare Metals 2017年第9期36卷 758-763页

作者： chetan B.Palan Nikhilesh Bajaj Anuj Soni Mukund Kulkarni Shreeniwas Omanwar Department of Physics Sant Gadge Baba Amravati University Amravati 444602India Department of Physics Toshniwal ACS CollegeSengaonHingoli 431542India Radiological Physics and Advisory Division Bhabha Atomic Research CentreMumbai 400094India

The dosimetric phosphors Li3PO4：M（M=Tb, Cu） were produced by modified solid-state *** structural and morphological characterization was carried out through X-ray diffraction（XRD） and scanning electron microscope（SEM）. Additionally, the photoluminescence（PL）, thermoluminescence（TL） and optically stimulated luminescence（OSL） properties of powder Li3PO4 doped with Tb and Cu were studied. It is advocated that Li3PO4： Cu phosphor not only shows higher OSL sensitivity（25 times or more） but also gives faster decay in OSL signals than that of Li3PO4： Tb^（3＋） phosphor. The minimum detectable dose（MDD） of Li3PO4：M（M=Tb,Cu） phosphors is found to be 21.69 × 10^（-3） and 3.33 ×10^（-6） J·kg^（-1）,respectively. In OSL mode, phosphor shows linear dose response in the range of 0.02-20.00 J·kg^（-1）.In TL mode, sensitivity of Li3PO4： Cu phosphor is more than that of Li3PO4： Tb phosphor. The kinetics parameters such as activation energy and frequency factors were determined by peak shape method, and photoionization cross sections of prepared phosphor were calculated.

关键词： Optically stimulated luminescence Radiationdosimetry Modified solid-state method Minimumdetectable dose

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