Jayanta Kumar Ghosh

Bio: Jayanta Kumar Ghosh is an academic researcher from University of Calcutta. The author has contributed to research in topics: Hyperspectral imaging & Warning system. The author has an hindex of 12, co-authored 96 publications receiving 472 citations. Previous affiliations of Jayanta Kumar Ghosh include Indian Institutes of Technology & Indian Institute of Technology Roorkee.

COVID-19 pandemic in India: a mathematical model study.

Abstract: The present novel coronavirus (SARS-CoV-2) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. But there is no vaccine, anti-viral medicine for such infection. So at this moment, a major worldwide problem is that how we can control this pandemic. On the other hand, India is high population density country, where the coronavirus infection disease (COVID-19) has started from 1 March 2020. Due to high population density, human to human social contact rate is very high in India. So controlling pandemic COVID-19 in early stage is very urgent and challenging problem of India. Mathematical models are employed to study the disease dynamics, identify the influential parameters and access the proper prevention strategies for reduction outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the influential model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impact have also been studied. Prediction are given on the future trends of the virus transmission under some control measures. Finally, the positive measures to control the disease have been summarized in the conclusion section.

COVID-19 Pandemic in India: A Mathematical Model Study

Abstract: The present novel coronavirus (SARS-CoV-2) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. But there is no vaccine, anti-viral medicine for such infection. So at this moment, a major worldwide problem is that how we can control this pandemic. On the other hand, India is high population density country, where the coronavirus infection disease (COVID-19) has started from 1 March 2020. Due to high population density, human to human social contact rate is very high in India. So controlling pandemic COVID-19 in early stage is very urgent and challenging problem of India. Mathematical models are employed to study the disease dynamics, identify the influential parameters and access the proper prevention strategies for reduction outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the influential model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impact have also been studied. Prediction are given on the future trends of the virus transmission under some control measures. Finally, the positive measures to control the disease have been summarized in the conclusion section.

Median change vector analysis algorithm for land-use land-cover change detection from remote-sensing data

Abstract: Improved change vector analysis (ICVA) has recently been promoted as an effective algorithm for multi-class change detection. Unlike the conventional change vector analysis (CVA) that works on two-dimensional data, the ICVA works on multidimensional data. However, ICVA has limitations when the change vector is fraught with similar direction cosine values. In this article, a new algorithm, named median change vector analysis (MCVA) has been proposed for multi-class change detection. The algorithm is based on an enhanced 2n-dimensional feature space comprising direction cosine values of both the change vector and the median vector, which allows for more accurate detection of change classes than those obtained from ICVA. As a case study, the proposed algorithm has been implemented on Landsat-7 Enhanced Thematic Mapper Plus (ETM+) images of a typical Indian city and surrounding areas for land-cover change detection.

Knowledge-Based Landslide Susceptibility Zonation System

Abstract: The landslide susceptibility of a region is important for socioeconomic considerations and engineering applications. Thus, an automated system for mapping of landslide susceptibility could be of significant benefit for society. In this paper, a knowledge-based landslide susceptibility zonation (LSZ) system has been proposed. The system consists of input, understanding, expert, and output modules. The input module accepts thematic images of contributing factors for landslides. The understanding module interprets input images to extract relevant information as required by the expert module. The expert module consists of knowledge base and inference strategy to categorize a region into different landslide intensities. Finally the output module provides a LSZ map. It is a pixel-based system and provides output having the scale same as that of the input maps. The system has been tested to prepare a landslide susceptibility map for the Tehri-Garhwal region in India's lower Himalayas, and further validated with studies for two other different regions. The proposed system provides output commensurate with that provided by experts. The categories of hazard zones have a discrepancy as little as 6.2% in high hazard zones and near to 1.5% and 4% in moderate and low hazard zones, respectively. The high hazard zones in the LSZ maps from the proposed system are supersets of that obtained by experts (i.e., the proposed system provides safer LSZ map). Thus, it can be concluded that the proposed system can be used for preparation of LSZ maps. In the future, the methodology may be extended for real time assessment and prediction of landslide hazards.

Looping and reconfiguration dynamics of a flexible chain with internal friction

Abstract: In recent past, experiments and simulations have suggested that apart from the solvent friction, friction arising from the protein itself plays an important role in protein folding by affecting the intra-chain loop formation dynamics. This friction is termed as internal friction in the literature. Using a flexible Gaussian chain with internal friction we analyze the intra-chain reconfiguration and loop formation times for all three topology classes namely end-to-end, end-to-interior and interior-to-interior. In a nutshell, bypassing expensive simulations we show how simple models like that of Rouse and Zimm can support the single molecule experiment and computer simulation results on intra-chain diffusion coefficients, looping time and even can predict the effects of tail length on the looping time.

Differential Equations and Dynamical Systems

Abstract: Series Preface * Preface to the Third Edition * 1 Linear Systems * 2 Nonlinear Systems: Local Theory * 3 Nonlinear Systems: Global Theory * 4 Nonlinear Systems: Bifurcation Theory * References * Index

Spectral mixture modeling - A new analysis of rock and soil types at the Viking Lander 1 site. [on Mars]

Abstract: A Viking Lander 1 image was modeled as mixtures of reflectance spectra of palagonite dust, gray andesitelike rock, and a coarse rocklike soil. The rocks are covered to varying degrees by dust but otherwise appear unweathered. Rocklike soil occurs as lag deposits in deflation zones around stones and on top of a drift and as a layer in a trench dug by the lander. This soil probably is derived from the rocks by wind abrasion and/or spallation. Dust is the major component of the soil and covers most of the surface. The dust is unrelated spectrally to the rock but is equivalent to the global-scale dust observed telescopically. A new method was developed to model a multispectral image as mixtures of end-member spectra and to compare image spectra directly with laboratory reference spectra. The method for the first time uses shade and secondary illumination effects as spectral end-members; thus the effects of topography and illumination on all scales can be isolated or removed. The image was calibrated absolutely from the laboratory spectra, in close agreement with direct calibrations. The method has broad applications to interpreting multispectral images, including satellite images.

Encyclopedia of Quality of Life and Well-Being Research

Abstract: The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the €(D) includes 7% for Germany, the €(A) includes 10% for Austria. Prices indicated with ** include VAT for electronic products; 19% for Germany, 20% for Austria. All prices exclusive of carriage charges. Prices and other details are subject to change without notice. All errors and omissions excepted. A.C. Michalos (Ed.) Encyclopedia of Quality of Life and Well-Being Research