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

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

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.

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.

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.

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.

Research on Economic Inequality is a well-established publication of quality research. Volume 31 provides original research on intergenerational earnings mobility, the factors determining adult health inequality, the evolution of wealth inequality in different regions of the world, inequality of employment opportunities, and the effects of the type of labour agreement on wage inequality and on an extended measure (income plus wealth) of well-being.

Opportunity, Mobility and Inequality presents newly published, rich datasets and deepens our understanding of these issues, uncovering novel innovations around how we conceive and measure such economic entities.

Research on Economic Inequality is a well-established publication of quality research. Volume 31 provides original research on intergenerational earnings mobility, the factors determining adult health inequality, the evolution of wealth inequality in different regions of the world, inequality of employment opportunities, and the effects of the type of labour agreement on wage inequality and on an extended measure (income plus wealth) of well-being.

Opportunity, Mobility and Inequality presents newly published, rich datasets and deepens our understanding of these issues, uncovering novel innovations around how we conceive and measure such economic entities.

This Edited Volumecontains a selection of refereed and revised papers originally presented at thesecond International Symposium on Signal Processing and Intelligent RecognitionSystems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The programcommittee received 175 submissions. Each paper was peer reviewed by at leastthree or more independent referees of the program committee and the 59 paperswere finally selected. The papers offer stimulating insights into biometrics, digital watermarking,recognition systems, image and video processing, signal and speech processing,pattern recognition, machine learning and knowledge-based systems. The book isdirected to the researchers and scientists engaged in various field of signalprocessing and related areas.

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries.The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.

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

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

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.

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.

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.

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.

Research on Economic Inequality is a well-established publication of quality research. Volume 31 provides original research on intergenerational earnings mobility, the factors determining adult health inequality, the evolution of wealth inequality in different regions of the world, inequality of employment opportunities, and the effects of the type of labour agreement on wage inequality and on an extended measure (income plus wealth) of well-being.

Opportunity, Mobility and Inequality presents newly published, rich datasets and deepens our understanding of these issues, uncovering novel innovations around how we conceive and measure such economic entities.

Research on Economic Inequality is a well-established publication of quality research. Volume 31 provides original research on intergenerational earnings mobility, the factors determining adult health inequality, the evolution of wealth inequality in different regions of the world, inequality of employment opportunities, and the effects of the type of labour agreement on wage inequality and on an extended measure (income plus wealth) of well-being.

Opportunity, Mobility and Inequality presents newly published, rich datasets and deepens our understanding of these issues, uncovering novel innovations around how we conceive and measure such economic entities.

This Edited Volumecontains a selection of refereed and revised papers originally presented at thesecond International Symposium on Signal Processing and Intelligent RecognitionSystems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The programcommittee received 175 submissions. Each paper was peer reviewed by at leastthree or more independent referees of the program committee and the 59 paperswere finally selected. The papers offer stimulating insights into biometrics, digital watermarking,recognition systems, image and video processing, signal and speech processing,pattern recognition, machine learning and knowledge-based systems. The book isdirected to the researchers and scientists engaged in various field of signalprocessing and related areas.

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries.The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.