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Computer Modeling in Engineering & Sciences 2020年第12期125卷 991-1031页

作者： Avaneesh Singh manish kumar bajpai PDPM Indian Institute of Information Technology Design and ManufacturingJabalpur482005India

We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 *** proposed SEIHCRD model is an extension of the SEIR ***-compartments have added death,hospitalized,and critical,which improves the basic understanding of disease spread and *** have studiedCOVID-19 cases of six countries,where the impact of this disease in the highest are Brazil,India,Italy,Spain,the United Kingdom,and the United *** estimating model parameters based on available clinical data,the modelwill propagate and forecast dynamic *** calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category *** calculates two types of Case fatality rate one is CFR daily,and the other is total *** proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of *** SEIHCRD model outperforms the classic ARXmodel and the ARIMA ***,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target *** result shows RMSE has improved by 56%–74%,and MAPE has a 53%–89%improvement in prediction accuracy.

关键词： COVID-19 coronavirus SIER model SEIHCRD model parameter estimation mathematical model India Brazil United Kingdom United States Spain Italy hospital beds ICU beds basic reproduction number case fatality rate

A Novel Approach for Enhancement of Geometric and Contrast Resolution Properties of Low Contrast Images

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 628-638页

作者： Koushlendra kumar Singh manish kumar bajpai Rajesh kumar Pandey Department of Computer Science and Engineering National Institute of Technology Jamshedpur 831014 India Indian Institute of Information Technology Design & Manufacturing Jabalpur MP 482005 India Department of Mathematical Sciences In- dian Institute of Technology Varanasi U.P. 221005 India

The present work encompasses a new image enhancement algorithm using newly constructed Chebyshev fractional order differentiator. We have used Chebyshev polynomials to design Chebyshev fractional order differentiator. We have generated the high pass filter corresponding to it. The designed filters are applied for decomposing the input image into four bands and low-low(L-L) sub-band is updated using correction coefficients. Reconstructed image with updated L-L sub-band provides the enhanced image. The visual results obtained are encouraging for image enhancement. The applicability of the developed algorithm is illustrated on three different test *** effects of order of differentiation on the edges of images have also been presented and discussed.

关键词： Chebyshev polynomial based approximation contrast enhancement fractional order differentiator

Study of Non-Pharmacological Interventions on COVID-19 Spread

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Computer Modeling in Engineering & Sciences 2020年第12期125卷 967-990页

作者： Avaneesh Singh Saroj kumar Chandra manish kumar bajpai PDPM Indian Institute of Information Technology Design and ManufacturingJabalpur482005India

COVID-19 disease has emerged as one of the life threatening threat to the society.A novel beta coronavirus causes *** began as unidentified pneumonia of unknown etiology in Wuhan City,Hubei province in China emerged in December *** vaccine has been produced till *** models are used to study the impact of different measures used to decrease *** models have been designed to estimate the numbers of spreaders in different scenarios in the present *** the present manuscript,three different mathematical models have been proposed with different scenarios,such as screening,quarantine,andNPIs,to estimate the number of virus *** analysis shows that the numbers of COVID-19 patients will be more without screening the peoples coming from other *** every people suffering fromCOVID-19 disease are *** screening and quarantine with NPIs have been implemented to study their impact on the *** has been found that NPI measures can reduce the number of *** NPI measures reduce the spread function’s growth and provide decision makers more time to prepare with in dealing with the disease.

关键词： Coronavirus COVID-19 mathematical modelling epidemic

Prediction of bearing capacity of pile foundation using deep learning approaches

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 870-886页

作者： manish kumar Divesh Ranjan kumar Jitendra KHATTI Pijush SAMUI Kamaldeep Singh GROVER Department of Civil Engineering SRM Institute of Science and Technology Tiruchirappalli CampusTrichy 621105India Department of Civil Engineering National Institute of Technology PatnaBihar 800005India Department of Civil Engineering Faculty of EngineeringThammasat School of EngineeringThammasat UniversityBangkok10200Thailand Department of Civil Engineering Rajasthan Technical UniversityKota 324010India

The accurate prediction of bearing capacity is crucial in ensuring the structural integrity and safety of pile *** research compares the Deep Neural Networks(DNN),Convolutional Neural Networks(CNN),Recurrent Neural Networks(RNN),Long Short-Term Memory(LSTM),and Bidirectional LSTM(BiLSTM)algorithms utilizing a data set of 257 dynamic pile load tests for the first ***,this research illustrates the multicollinearity effect on DNN,CNN,RNN,LSTM,and BiLSTM models’performance and accuracy for the first time.A comprehensive comparative analysis is conducted,employing various statistical performance parameters,rank analysis,and error matrix to evaluate the performance of these *** performance is further validated using external validation,and visual interpretation is provided using the regression error characteristics(REC)curve and Taylor *** from the comparative analysis reveal that the DNN(Coefficient of determination(R^(2))_(training(TR))=0.97,root mean squared error(RMSE)_(TR)=0.0413;R^(2)_(testing(TS))=0.9,RMSE_(TS)=0.08)followed by BiLSTM(R^(2)_(TR)=0.91,RMSE_(TR)=0.782;R^(2)_(TS)=0.89,RMSE_(TS)=0.0862)model demonstrates the highest performance *** is noted that the BiLSTM model is better than LSTM because the BiLSTM model,which increases the amount of information for the network,is a sequence processing model made up of two LSTMs,one of which takes the input in a forward manner,and the other in a backward *** prediction of pile-bearing capacity is strongly influenced by ram weight(having a considerable multicollinearity level),and the effect of the considerable multicollinearity level has been determined for the model based on the recurrent neural network *** this study,the recurrent neural network model has the least performance and accuracy in predicting the pile-bearing capacity.

关键词： deep learning algorithms high-strain dynamic pile test bearing capacity of the pile

Identification of optimal composition with superior electrochemical properties along the zero Mn^(3+)line in Na_(0.75)(Mn-Al-Ni)O_(2)pseudo ternary system

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Journal of Energy Chemistry 2024年第9期96卷 206-216页

作者： Hari Narayanan Vasavan manish Badole Samriddhi Saxena Velaga Srihari Asish kumar Das Pratiksha Gami Neha Dagar Sonia Deswal Pradeep kumar Himanshu kumar Poswal Sunil kumar Department of Metallurgical Engineeringnd Materials Science Indian Institute of Technology IndoreSimrol 453552India High Pressure&Synchrotron Radiation Physics Division Bhabha Atomic Research Centre400085 MumbaiIndia School of Physical Sciences Indian Institute of Technology MandiHimachal Pradesh 175005India Center for Electric Vehiclend Intelligent Transport Systems Indian Institute of Technology IndoreSimrol 453552India

Biphasic layered oxide cathodes,known for their superior electrochemical performance,are prime candidates for commercializing in Na-ion ***,we unveil a series of P3/P2 monophasic and biphasic Al-substituted Na_(3/4)Mn_(5-x/8)Al_(2x/8)Ni_(3-x/8)O_(2)layered oxide cathodes that lie along the‘zero Mn^(3+)line’in the Na_(3/4)(Mn-Al-Ni)O_(2)pseudo-ternary *** structural analysis showed a larger Na^(+)conduction bottleneck area in both P3 and P2 structures with a higher Al3+content,which enhanced their rate *** each composition,the P3/P2 biphasic compound with nearly equal fractions of P3 and P2 phases outperformed their monophasic counterparts in almost all electrochemical performance *** synchrotron XRD measurements obtained for the monophasic P3 and biphasic P2/P3 samples revealed the absence of the O3 phase during *** high structure stability and faster Na^(+)transport kinetics in the biphasic samples underpins the enhancement of electrochemical properties in the Al-substituted P3/P2 *** results highlight fixed oxidation state lines as a novel tool to identify and design layered oxide cathodes for Na-ion batteries in pseudo-ternary diagrams involving Jahn-Teller active cations.

关键词： Layered oxides Biphasic cathode Operando Synchrotron XRD Electrochemical behavior Cyclic performance

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钒技术在难减排行业和能源转型中的作用评估

钢铁钒钛 2024年第4期45卷 84-94页

作者： David ASantos manish KDixit Pranav Pradeep kumar Sarbajit Banerjee 德克萨斯农工大学化学系德克萨斯农工大学材料科学和工程系德克萨斯农工大学建筑科学系德克萨斯农工大学土木与环境工程学院

重工业的减碳和可再生能源技术的出现皆与获得矿物资源有着密不可分的联系。因此，迫切需要对关键元素在减少温室气体排放方面的作用进行基准评估。考察了钒作为微合金元素在建筑碳减排以及作为电网储能用液流电池的主要成分在能源转型... 详细信息

重工业的减碳和可再生能源技术的出现皆与获得矿物资源有着密不可分的联系。因此，迫切需要对关键元素在减少温室气体排放方面的作用进行基准评估。考察了钒作为微合金元素在建筑碳减排以及作为电网储能用液流电池的主要成分在能源转型中的作用。研究结果表明，钒可使每年减少总计1.85亿t碳排放。其中，中国和欧盟的减排幅度分别为各自排放量的1.15%和0.18%。研究结果强调了关键金属在发展低碳基础设施中的作用，同时指出了进行全面评估并施加政策干预减轻供应链风险的必要性。

关键词：钒微合金化液流电池碳减排

Endoscopic ultrasound-guided pancreatic fluid collection drainage: Where are we?

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World Journal of Gastrointestinal Endoscopy 2024年第6期16卷 273-281页

作者： Anupam kumar Singh manish Manrai Rakesh Kochhar Department of Gastroenterology Postgraduate Institute of Medical Education and ResearchChandigarh 160012India Department of Gastroenterology Command HospitalLucknow 226002India Department of Gastroenterology Paras HospitalPanchkula 134109India

Pancreatic fluid collections(PFCs)result from injury to the pancreas from acute or chronic pancreatitis,surgery,or *** of these collections has evolved over the last 2 *** choice of interventions includes percu-taneous,endoscopic,minimally invasive surgery,or a combined *** drainage is the drainage of PFCs by creating an artificial communication between the collection and gastrointestinal lumen that is maintained by placing a stent across the fistulous *** this editorial,we endeavored to update the current status of endoscopic ultrasound-guided drainage of PFCs.

关键词： Pancreatic fluid collections Endoscopic ultrasound-guided drainage Endoscopic necrosectomy Lumen apposing metal stent Review

Machine Learning-based Electric Load Forecasting for Peak Demand Control in Smart Grid

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Computers, Materials & Continua 2023年第3期74卷 4785-4799页

作者： manish kumar Nitai Pal Department of Electrical Engineering Indian Institute of Technology(ISM)Dhanbad826004India Department of Nuclear Science&Technology Pandit Deendayal Energy UniversityGandhinagarIndia

Increasing energy demands due to factors such as population,globalization,and industrialization has led to increased challenges for existing energy *** ways of energy generation and energy consumption like smart grids and smart homes are implemented to face these challenges with reliable,cheap,and easily available sources of *** integration of renewable energy and other clean distributed generation is increasing continuously to reduce carbon and other air pollutants *** the integration of distributed energy sources and increase in electric demand enhance instability in the ***-term electrical load forecasting reduces the grid fluctuation and enhances the robustness and power quality of the *** load forecasting in advance on the basic historical data modelling plays a crucial role in peak electrical demand control,reinforcement of the grid demand,and generation balancing with cost *** accurate forecasting of electrical data is a very challenging task due to the nonstationary and nonlinearly nature of the *** learning and artificial intelligence have recognized more accurate and reliable load forecastingmethods based on historical load *** purpose of this study is to model the electrical load of Jajpur,Orissa Grid for forecasting of load using regression type machine learning algorithms Gaussian process regression(GPR).The historical electrical data and whether data of Jajpur is taken for modelling and simulation and the data is decided in such a way that the model will be considered to learn the connection among past,current,and future dependent variables,factors,and the relationship among *** on this modelling of data the network will be able to forecast the peak load of the electric grid one day *** study is very helpful in grid stability and peak load control management.

关键词： Artificial intelligence electric load forecasting machine learning peak-load control renewable energy smart grids

A Clinical Data Analysis Based Diagnostic Systems for Heart Disease Prediction Using Ensemble Method

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Big Data Mining and Analytics 2023年第4期6卷 513-525页

作者： Ankit kumar Kamred Udham Singh manish kumar Department of Computer Engineering and Applications GLA UniversityMathura 281406India School of Computing Graphic Era Hill UniversityDehradun 248002India Department of Electronics and Communication Engineering GLA UniversityMathura 281406India.

The correct diagnosis of heart disease can save lives,while the incorrect diagnosis can be *** UCI machine learning heart disease dataset compares the results and analyses of various machine learning approaches,including deep *** used a dataset with 13 primary characteristics to carry out the *** vector machine and logistic regression algorithms are used to process the datasets,and the latter displays the highest accuracy in predicting coronary *** programming is used to process the *** research initiatives have used machine learning to speed up the healthcare *** also used conventional machine learning approaches in our investigation to uncover the links between the numerous features available in the dataset and then used them effectively in anticipation of heart infection *** the accuracy and confusion matrix has resulted in some favorable *** get the best results,the dataset contains certain unnecessary features that are dealt with using isolation logistic regression and Support Vector Machine(SVM)classification.

关键词： artificial intelligence support vector machine logistic regression cleveland dataset supervised algorithm human sensing

Multiple Forgery Detection in Video Using Convolution Neural Network

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Computers, Materials & Continua 2022年第10期73卷 1347-1364页

作者： Vinay kumar Vineet Kansal manish Gaur Centre for Advanced Studies Dr.A P J Abdul Kalam Technical UniversityLucknowIndia Institute of Engineering and Technology Dr.A P J Abdul Kalam Technical UniversityLucknowIndia

With the growth of digital media data manipulation in today’s era due to the availability of readily handy tampering software,the authenticity of records is at high risk,especially in *** is a dire need to detect such problem and do the necessary *** this work,we propose an approach to detect the interframe video forgery utilizing the deep features obtained from the parallel deep neural network model and thorough analytical *** proposed approach only uses the deep features extracted from the CNN model and then applies the conventional mathematical approach to these features to find the forgery in the *** work calculates the correlation coefficient from the deep features of the adjacent frames rather than calculating directly from the *** divide the procedure of forgery detection into two phases–video forgery detection and video forgery *** video forgery detection,this approach detect input video is original or *** the video is not original,then the video is checked in the next phase,which is video forgery *** the video forgery classification,method review the forged video for insertion forgery,deletion forgery,and also again check for *** proposed work is generalized and it is tested on two different *** experimental results of our proposed model show that our approach can detect the forgery with the accuracy of 91%on VIFFD dataset,90%in TDTV dataset and classify the type of forgery–insertion and deletion with the accuracy of 82%on VIFFD dataset,86%on TDTV *** work can helps in the analysis of original and tempered video in various domain.

关键词： Digital forensic forgery detection video authentication video interframe forgery video processing deep learning