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Diagnosis of COVID-19 from Chest X-Ray Images Using Wavelets-Based Depthwise Convolution Network

Big Data Mining and Analytics 2021年第2期4卷 84-93页

作者： krishna Kant singh Akansha singh Department of ECE KIET Group of InstitutionsDelhi-NCRGhaziabad 201206India Department of CSE ASETAmity University Uttar PradeshNoida 201310India

Coronavirus disease 2019 also known as COVID-19 has become a pandemic. The disease is caused by a beta coronavirus called Severe Acute Respiratory Syndrome Coronavirus 2(SARS-Co V-2). The severity of the disease can be understood by the massive number of deaths and affected patients globally. If the diagnosis is fast-paced, the disease can be controlled in a better manner. Laboratory tests are available for diagnosis, but they are bounded by available testing kits and time. The use of radiological examinations that comprise Computed Tomography(CT) can be used for the diagnosis of the disease. Specifically, chest X-Ray images can be analysed to identify the presence of COVID-19 in a patient. In this paper, an automated method for the diagnosis of COVID-19 from the chest X-Ray images is proposed. The method presents an improved depthwise convolution neural network for analysing the chest X-Ray images. Wavelet decomposition is applied to integrate multiresolution analysis in the network. The frequency sub-bands obtained from the input images are fed in the network for identifying the *** network is designed to predict the class of the input image as normal, viral pneumonia, and COVID-19. The predicted output from the model is combined with Grad-CAM visualization for diagnosis. A comparative study with the existing methods is also performed. The metrics like accuracy, sensitivity, and F1-measure are calculated for performance evaluation. The performance of the proposed method is better than the existing methodologies and thus can be used for the effective diagnosis of the disease.

关键词： coronavirus COVID-19 deep learning convolution neural network X-Ray images

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A Fifth Order Alternative Mapped WENO Scheme for Nonlinear Hyperbolic Conservation Laws

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Advances in Applied Mathematics and Mechanics 2022年第1期14卷 275-298页

作者： Uttam singh Rajput krishna Mohan singh Department of Mechanical and Industrial Engineering Indian Institute of Technology RoorkeeRoorkee 247667India

In this work,we have developed a fifth-order alternative mapped weighted essentially nonoscillatory(AWENO-M)finite volume scheme using non-linear weights of mapped WENO reconstruction scheme of Henrick et al.(***.,207(2005),pp.542-567)for solving hyperbolic conservation *** reconstruction of numerical flux is done using primitive variables instead of conservative *** present scheme results in less spurious oscillations near discontinuities and shows higher-order accuracy at critical points compared to the alternative WENO scheme(AWENO)based on traditional non-linear weights of Jiang and Shu(***.,228(1996),pp.202-228).The third-order Runge-Kutta method has been used for solution advancement in *** Harten-Lax-van Leer-Contact(HLLC)shock-capturing method is used to provide necessary upwinding into the *** performance of the present scheme is evaluated in terms of accuracy,computational cost,and resolution of discontinuities by using various one and two-dimensional test cases.

关键词： High resolution scheme unsteady non-linear weights numerical fluxes alternative WENO scheme hyperbolic equations

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Satellite Image Classification Using a Hybrid Manta Ray Foraging Optimization Neural Network

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Big Data Mining and Analytics 2023年第1期6卷 44-54页

作者： Amit Kumar Rai Nirupama Mandal krishna Kant singh Ivan Izonin Department of Electronics Engineering Indian Institute of TechnologyDhanbad(ISMDhanbad)Dhanbad 826004India Department of Electronics and Communication Engineering Asansol Engineering CollegeAsansol 713305India Department of CSE ASETAmity UniversityNoida 201301India Department of Artificial Intelligence Lviv Polytechnic National UniversityLviv 79000Ukraine

A semi supervised image classification method for satellite images is proposed in this *** satellite images contain enormous data that can be used in various *** analysis of the data is a tedious task due to the amount of data and the heterogeneity of the ***,in this paper,a Radial Basis Function Neural Network(RBFNN)trained using Manta Ray Foraging Optimization algorithm(MRFO)is *** is a three-layer network comprising of input,output,and hidden layers that can process large *** trained network can discover hidden data patterns in unseen *** learning algorithm and seed selection play a vital role in the performance of the *** seed selection is done using the spectral indices to further improve the performance of the *** manta ray foraging optimization algorithm is inspired by the intelligent behaviour of manta *** emulates three unique foraging behaviours namelys chain,cyclone,and somersault *** satellite images contain enormous amount of data and thus require exploration in large search *** spiral movement of the MRFO algorithm enables it to explore large search spaces *** proposed method is applied on pre and post flooding Landsat 8 Operational Land Imager(OLI)images of New Brunswick *** method was applied to identify and classify the land cover changes in the area induced by *** images are classified using the proposed method and a change map is developed using post classification *** change map shows that a large amount of agricultural area was washed away due to *** measurement of the affected area in square kilometres is also performed for mitigation *** results show that post flooding the area covered by water is increased whereas the vegetated area is *** performance of the proposed method is done with existing state-of-the-art methods.

关键词： Radial Basis Function Neural Network(RBFNN) Manta Ray Foraging Optimization algorithm(MRFO) Landsat 8 classification change detection disaster mitigation planning

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A comprehensive review on hybrid electric vehicles: architectures and components

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Journal of Modern Transportation 2019年第2期27卷 77-107页

作者： krishna Veer singh Hari Om Bansal Dheerendra singh Power Electronics and Drives Laboratory Department of Electrical and Electronics Engineering Birla Institute of Technology and Science

The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuelefficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors’ role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability.

关键词： Hybrid electric vehicle Hybrid energy storage system Architecture Traction motors Bidirectional converter

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Constructing a biofunctionalized 3D-printed gelatin/sodium alginate/chitosan tri-polymer complex scaffold with improvised biological andmechanical properties for bone-tissue engineering

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Bio-Design and Manufacturing 2024年第1期7卷 57-73页

作者： Amit Kumar singh krishna Pramanik Amit Biswas Centre of Excellence in Tissue Engineering Department of Biotechnology and Medical EngineeringNational Institute of TechnologyRourkela 769008India

Sodium alginate(SA)/chitosan(CH)polyelectrolyte scaffold is a suitable substrate for tissue-engineering *** present study deals with further improvement in the tensile strength and biological properties of this type of scaffold to make it a potential template for bone-tissue *** experimented with adding 0%–15%(volume fraction)gelatin(GE),a protein-based biopolymer known to promote cell adhesion,proliferation,and *** resulting tri-polymer complex was used as bioink to fabricate SA/CH/GEmatrices by three-dimensional(3D)*** studies using scanning electron microscopy revealed the microfibrous porous architecture of all the structures,which had a pore size range of 383–419μm.X-ray diffraction and Fourier-transform infrared spectroscopy analyses revealed the amorphous nature of the scaffold and the strong electrostatic interactions among the functional groups of the polymers,thereby forming polyelectrolyte complexes which were found to improve mechanical properties and structural *** scaffolds exhibited a desirable degradation rate,controlled swelling,and hydrophilic characteristics which are favorable for bone-tissue *** tensile strength improved from(386±15)to(693±15)kPa due to the increased stiffness of SA/CH scaffolds upon addition of *** enhanced protein adsorption and in vitro bioactivity(forming an apatite layer)confirmed the ability of the SA/CH/GE scaffold to offer higher cellular adhesion and a bone-like environment to cells during the process of tissue *** vitro biological evaluation including the MTT assay,confocal microscopy analysis,and alizarin red S assay showed a significant increase in cell attachment,cell viability,and cell proliferation,which further improved biomineralization over the scaffold *** addition,SA/CH containing 15%gelatin designated as SA/CH/GE15 showed superior performance to the other fabricated 3D structures,demonstrating its pote

关键词： Scaffold Biomaterial Sodium alginate Chitosan Gelatin 3D printing Tissue engineering

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