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Explainable Artificial Intelligence(XAI)Model for Cancer Image Classification

Computer Modeling in Engineering & sciences 2024年第10期141卷 401-441页

作者： amit singhal.krishna kant agrawal.angel.s quezada Adrian Rodriguez Aguiñaga samantha Jiménez satya Prakash Yadav Department of Computer science&Engineering Raj Kumar Goel Institute of TechnologyGhaziabad201017India Department of school of Computing science and Engineering Galgotias UniversityGreater Noida203201India Tecnológico Nacional de México Campus Tijuana Baja California22414México Universidad Autónoma de Baja California TijuanaBaja California22414México Department of Computer science and Engineering G.LBajaj Institute of Technology and Management(GLBITM)Affiliated to Dr.A.P.J.Abdul Kalam Technical UniversityLucknow201306India school of Computer science Engineering and Technology(sCsET) Bennett UniversityGreater Noida201310India

The use of Explainable Artificial Intelligence(XAI)models becomes increasingly important for making decisions in smart healthcare *** is to make sure that decisions are based on trustworthy algorithms and that healthcare workers understand the decisions made by these *** models can potentially enhance interpretability and explainability in decision-making processes that rely on artificial ***,the intricate nature of the healthcare field necessitates the utilization of sophisticated models to classify cancer *** research presents an advanced investigation of XAI models to classify cancer *** describes the different levels of explainability and interpretability associated with XAI models and the challenges faced in deploying them in healthcare *** addition,this study proposes a novel framework for cancer image classification that incorporates XAI models with deep learning and advanced medical imaging *** proposed model integrates several techniques,including end-to-end explainable evaluation,rule-based explanation,and useradaptive *** proposed XAI reaches 97.72%accuracy,90.72%precision,93.72%recall,96.72%F1-score,9.55%FDR,9.66%FOR,and 91.18%*** will discuss the potential applications of the proposed XAI models in the smart healthcare *** will help ensure trust and accountability in AI-based decisions,which is essential for achieving a safe and reliable smart healthcare environment.

关键词： Explainable artificial intelligence artificial intelligence XAI healthcare cancer image classification

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Photo-induced optical changes in GexAs40se60-x thin films

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Progress in Natural science:Materials International 2010年第1期20卷 54-60页

作者： Rashmi CHAUHAN amit Kumar sRIVAsTAVA Arvind TRIPATHI krishna kant sRIVAsTAVA Department of Physic DAV College Kanpur 208001India Material science Programme ⅡT Kanpur 208016 India Epsilonium systems Commercial Complex ChunniganjKanpur 208001India Department of Physics DBs College Kanpur 208006India

Ge-As-se chalcogenide thin films show a wide range of photosensitivity,which is utilized for the fabrication of micro-optical elements for integrated *** photosensitivity of GexAs40se60-x（x=0,15）chalcogenide thin films for UV light was *** that purpose,the bulk samples of GexAs40se60-x（x=0,15）chalcogenide glasses were prepared using conventional melt quenching technique,and thin films were prepared using thermal evaporation *** thin films were exposed to UV light for two *** natures of bulk samples and thin films were verified by XRD and chemical compositions were verified by EDX *** thicknesses of the thin films were measured using a thickness *** optical analysis of these thin films was done using transmission spectra in wavelength range of 300-900 *** bandgap was determined by first peak of transmission derivative as well as extrapolation of Tauc's plot.R2analysis was done using R software to ensure that the material is indirect bandgap *** is observed that two hours UV exposure causes photo-darkening along with photo-expansion in As40se60thin films,while photo-bleaching and photo-densification for Ge15As40se45thin ***,the amounts of photo-induced optical changes for Ge15As40se45thin films are smaller than those for As40se60thin *** changes in optical absorption,bandgap and thickness are understood based on the bonding rearrangement caused by UV exposure.

关键词： chalcogenide glasses thin films optical properties photo-induced effect optical band gap UV exposure R software

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Linear and nonlinear optical changes in amorphous As2se3 thin film upon UV exposure

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Progress in Natural science:Materials International 2011年第3期21卷 205-210页

作者： Rashmi CHAUHAN amit Kumar sRIVAsTAVA Arvind TRIPATHI krishna kant sRIVAsTAVA Department of Physic DAV CollegeCSJM UniversityKanpur208001India Department of Physics DBS CollegeCSJM UniversityKanpur208006India Materials science Programme 4. Research Foundation for Education and Technology 5. Department of Physics DBS CollegeCSJM University

Amorphous As2se3chalcogenide thin film was exposed to UV light(i line and g line) using mercury lamp for 30 min. XRD,UV/VIs spectroscopy and thickness measurements were taken for unexposed and exposed thin film for structural and optical *** optical constants(linear refractive index,extinction coefficient and linear optical absorption coefficient) of the film were calculated from transmission spectra using swanepoel *** bandgap was determined using Tauc’s relation of indirect bandgap *** of the material was described by single-oscillator Wemple-DeDiDomenico model. Nonlinear optical constants(χ~((3)) and n2) were determined from linear optical parameters using semi-empirical relations in long wavelength *** changes in linear optical parameters(increase in refractive index,and extinction coefficient;reduction in optical bandgap),nonlinear optical parameter(increase inχ~((3))) are proposed for various photonic applications.

关键词： amorphous chalcogenide thin films UV exposure optical properties swanepoel method Wemple-DeDiDomenico model semi-empirical relations

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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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Reconstructing Missing Hourly Real-Time Precipitation Data Using a Novel Intermittent sliding Window Period Technique for Automatic Weather station Data

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Journal of Meteorological Research 2017年第4期31卷 774-790页

作者： Nagaraja HEMA krishna kant Department of Computer science and Engineering/Information Technology Jaypee Institute of Information Technology Noida 201307 India

Precipitation is the most discontinuous atmospheric parameter because of its temporal and spatial variability. Precipitation observations at automatic weather stations（AWss） show different patterns over different time periods. This paper aims to reconstruct missing data by finding the time periods when precipitation patterns are similar, with a method called the intermittent sliding window period（IsWP） technique—a novel approach to reconstructing the majority of non-continuous missing real-time precipitation data. The IsWP technique is applied to a 1-yr precipitation dataset（January 2015 to January 2016）, with a temporal resolution of 1 h, collected at 11 AWss run by the Indian Meteorological Department in the capital region of Delhi. The acquired dataset has missing precipitation data amounting to 13.66%, of which 90.6% are reconstructed successfully. Furthermore, some traditional estimation algorithms are applied to the reconstructed dataset to estimate the remaining missing values on an hourly basis. The results show that the interpolation of the reconstructed dataset using the IsWP technique exhibits high quality compared with interpolation of the raw dataset. By adopting the IsWP technique, the root-mean-square errors（RMsEs）in the estimation of missing rainfall data—based on the arithmetic mean, multiple linear regression, linear regression,and moving average methods—are reduced by 4.2%, 55.47%, 19.44%, and 9.64%, respectively. However, adopting the IsWP technique with the inverse distance weighted method increases the RMsE by 0.07%, due to the fact that the reconstructed data add a more diverse relation to its neighboring AWss.

关键词： automatic weather station intermittent sliding window period interpolation mean absolute error reconstruction of missing precipitation data

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

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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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PRECEsION： progressive recovery and restoration planning of interdependent services in enterprise data centers

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Digital Communications and Networks 2018年第1期4卷 39-47页

作者： Ibrahim El-shekeil amitangshu Pal krishna kant Computer and Information sciences Temple University Philaclelphioa. PA 19122 USA

The primary focus of this paper is to design a progressive restoration plan for an enterprise data center environment following a partial or full disruption. Repairing and restoring disrupted components in an enterprise data center requires a significant amount of time and human effort. Following a major disruption, the recovery process involves multiple stages, and during each stage, the partially recovered infrastructures can provide limited services to users at some degraded service level. However, how fast and efficiently an enterprise infrastructure can be recovered de- pends on how the recovery mechanism restores the disrupted components, considering the inter-dependencies between services, along with the limitations of expert human operators. The entire problem turns out to be NP- hard and rather complex, and we devise an efficient meta-heuristic to solve the problem. By considering some real-world examples, we show that the proposed meta-heuristic provides very accurate results, and still runs 600-2800 times faster than the optimal solution obtained from a general purpose mathematical solver [1].

关键词： Progressive restoration planning Enterprise data center Genetic algorithm Integer linear program Multi-layer networks

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High-energy ion treatments of amorphous As40se60 thin films for optical applications

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Progress in Natural science:Materials International 2014年第3期24卷 239-246页

作者： Rashmi Chauhan Arvind Tripathi krishna kant srivastava Department of Physic DAV College CSJM University Research Foundation for Education and Technology 3. Department of Physics DBS College CSJM University

The treatment of 100 MeV Ag swift-heavy ion(sHI) irradiation with five different fluences(3 1010, 1 1011, 3 1011, 1 1012, and3 1012ions/cm2) was used to design optical and structural properties of amorphous(a-) As40se60 chalcogenide thin films. swanepoel method was applied on transmission measurements to determine the changes in optical bandgap, Tauc parameter and linear optical parameters, i.e., linear optical absorption, extinction coefficient and linear refractive index. Dispersion of the material was determined by Wemple–DiDomenico *** in nonlinear optical parameters of third-order optical susceptibility and nonlinear refractive index were determined using semi-empirical relations. Changes in surface morphology of the films were investigated using sEM observation, which indicated that fluence 3 1012ions/cm2was upper threshold limit for these films for ion treatment. It is observed that optical bandgap reduces from 1.76 eV to 1.64 eV, and nonlinear refractive index increases from 1.31 10 10[esu] to 1.74 10 10[esu]. Linear refractive index initially increases from 2.80 to 3.52(for fluence3 1010ions/cm2) and then keeps decreasing. The observed changes in optical properties upon irradiation were explained in terms of structural rearrangements by Raman measurement. The study was compiled with the previous literature to propose sHI as an effective optical engineering technique to achieve desired changes according to the need of optical/photonic applications.

关键词： Amorphous chalcogenide thin films Ion irradiation Linear and nonlinear optical properties swanepoel method semi-empirical relations Raman measurements

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Arbuscular Mycorrhizal (AM) Diversity in Prosopis cineraria (L.) Druce Under Arid Agroecosystems

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Agricultural sciences in China 2008年第6期7卷 754-761页

作者： Neelam Verma Jagadish Chandra Tarafdar krishna kant srivastava Jitendra Panwar Arid Forest Research Institute Jodhpur 342 005 Rajasthan India Central Arid Zone Research Institute Biological sciences Group Birla Institute of Technology & Science

Arbuscular mycorrhizal （AM） fungi associated with Prosopis cineraria （Khejri） were assessed for their qualitative and quantitative distribution from eight districts of Rajasthan. A total of three species of Acaulospora, one species of Entrophospora, two species of Gigaspora, twenty-one species of Glomus, seven species of sclerocystis and three species of scutellospora were recorded. A high diversity of AM fungi was observed and it varied at different study sites. Among these six genera, Glomus occurred most frequently. Glomus fasciculatum, Glomus aggregatum, and Glomus mosseae were found to be the most predominant AM fungi in infecting Prosopis cineraria. Acaulospora, G. fasciculatum, sclerocystis was found in all the fields studied, while scutellospora species were found only in few sites. A maximum of thirty-six AM fungal species were isolated and identified from Jodhpur, whereas only thirteen species were found from Jaisalmer. spores of Glomusfasciculatum were found to be most abundant under Prosopis cineraria.

关键词： arbuscular mycorrhizae arid agroecosystems diversity Prosopis cineraria

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Process-structure-property relationship for plasma-sprayed iron-based amorphous/crystalline composite coatings

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International Journal of Minerals,Metallurgy and Materials 2022年第1期29卷 144-152页

作者： Abhishek Pathak Biswajyoti Mukherjee krishna kant Pandey Aminul Islam Pavan Bijalwan Monojit Dutta Atanu Banerjee Anup Kumar Keshri Research and Development Unit Tata SteelJamshedpur 831001India Plasma spray Coating Laboratory Metallurgical and Materials EngineeringIndian Institute of Technology PatnaBihta 801106India

This study explores the fabrication of Fe-based amorphous/crystalline coating by air plasma spraying and its dependency on the coating parameters(plasma power,primary gas flow rate,powder feed rate,and stand-off distance).X-ray diffraction of the coatings deposited at optimized spray parameters showed the presence of amorphous/crystalline *** deposited at a lower plasma power and highest gas flow rate exhibited better density,hardness,and wear *** coatings demonstrated equally good resistance against the corrosive environment(3.5wt%NaCl solution).Mechanical,wear,and tribological studies indicated that a single process parameter optimization cannot provide good coating performance;instead,all process parameters have a unique role in defining better properties for the coating by con-trolling the in-flight particle temperature and velocity profile,followed by the cooling pattern of molten droplet before impingement on the substrate.

关键词： Fe-based alloys amorphous alloys plasma spray coating mechanical corrosion and wear

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