Search results for ""author sanghamitra bandyopadhyay""

This volume of Research on Economic Inequality contains research on how we measure poverty, inequality and welfare and how these measurements contribute towards policies for social mobility. The volume contains eleven papers, some of which focus on the uneven impact of the Covid-19 pandemic on poverty and welfare. Opening with debates on theoretical issues that lie at the forefront of the measurement of inequality and poverty literature, the first two chapters go on to propose new methods for measuring wellbeing and inequality in multidimensional categorical environments, and for measuring pro-poor growth in a Bayesian setting. The following three papers present theoretical innovations for measuring poverty and inequality, namely, in estimating the dynamic probability of being poor using a Bayesian approach, and when presented with ordinal variables. The next three chapters are contributions on empirical methods in the measurement of poverty, inclusive economic growth and mobility, with a focus on India, Israel and a unique longitudinal dataset for Chile. The volume concludes with three chapters exploring the impact of the Covid-19 pandemic as an economic shock on income and wealth poverty in EU countries and in an Argentinian city slum.

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Research on Economic Inequality is a well-established publication of quality research. This 30th volume features insightful and original papers from the 9th Society for the Study of Economic Inequality (ECINEQ) meeting. Mobility and Inequality Trends begins by illustrating the trajectory of income inequality in the world over the course of recent decades before the second paper makes a crucial distinction between ‘bad’ inequality, which is detrimental to society, and ‘good’ inequality, which is beneficial. Focus then shifts to bad inequality, one paper covering the relationship between intergenerational elasticity and inequality of opportunity, and the second studying the relationship between intergenerational mobility and life satisfaction in Spain. The volume then progresses to defend the use of intermediate views of inequality when constructing indicators of social welfare obtained through the use of average income and the Gini coefficient before investigating the advantage of using a multifaceted approach to income mobility measurement. To conclude Mobility and Inequality Trends presents an intensive exploration of income inequality in China and then studies the effects of the policy measure “Minimum Living Income. Finally, the last paper studies the impact of the COVID-19 pandemic on economic stimulus policies.

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An invaluable tool in Bioinformatics, this unique volume provides both theoretical and experimental results, and describes basic principles of computational intelligence and pattern analysis while deepening the reader's understanding of the ways in which these principles can be used for analyzing biological data in an efficient manner. This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques, either individually or in a hybridized manner. The purpose is to analyze biological data and enable extraction of more meaningful information and insight from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and microarray data. These data types are complex and advanced methods are required, including the use of domain-specific knowledge for reducing search space, dealing with uncertainty, partial truth and imprecision, efficient linear and/or sub-linear scalability, incremental approaches to knowledge discovery, and increased level and intelligence of interactivity with human experts and decision makers Chapters authored by leading researchers in CI in biology informatics. Covers highly relevant topics: rational drug design; analysis of microRNAs and their involvement in human diseases. Supplementary material included: program code and relevant data sets correspond to chapters.

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This volume contains research on how we measure poverty, inequality and welfare and how we use such measurements to devise policies to deliver social mobility. It contains ten papers, some of which were presented at the third meeting of The Theory and Empirics of Poverty, Inequality and Mobility at Queen Mary University of London, London, October 2016. The volume begins with theoretical issues at the frontier of the literature. Three papers discuss the impact of social welfare policies on poverty measurement, and with innovations on the measurement of relative bipolarisation. Two papers address the conceptualisation of multidimensional poverty by incorporating inequality within the poor, and that of chronic poverty for time dependent analyses, with applications to India and Haiti, and Ethiopia respectively. The second half of the volume consists of empirical contributions, using novel techniques and datasets to investigate the dynamics of poverty and welfare. These studies track the dynamics of poverty using unique datasets for China, the Caucasus and Italy. The volume concludes with investigations about within-household inequalities between siblings due to the unequal effects of conditional cash transfers in Cambodia and a cross-country study on the effect of historical income inequality on entrepreneurship in developing countries.

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Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, they are scattered in different journals, conference proceedings and technical reports, thus causing inconvenience to readers, students and researchers.This book, unique in its nature, is aimed at providing a treatise in a unified framework, with both theoretical and experimental results, describing the basic principles of soft computing and demonstrating the various ways in which they can be used for analyzing biological data in an efficient manner. Interesting research articles from eminent scientists around the world are brought together in a systematic way such that the reader will be able to understand the issues and challenges in this domain, the existing ways of tackling them, recent trends, and future directions. This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in the latter.

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