The present book includes a set of selected best papers from the 3rd International Conference on Recent Developments in Science, Engineering and Technology (REDSET 2016), held in Gurgaon, India, from 21 to 22 October 2016. The conference focused on the experimental, theoretical and application aspects of innovations in computational intelligence and provided a platform for the academicians and scientists. This book provides an insight into ongoing research and future directions in this novel, continuously evolving field. Many decades have been devoted to creating and refining methods and tools for computational intelligence such as Artificial Neural Networks, Evolutionary Computation, Fuzzy Logic, Computational Swarm Intelligence and Artificial Immune Systems. However, their applications have not yet been broadly disseminated. Computational intelligence can be used to provide solutions to many real-life problems, which could be translated into binary languages, allowing computers to process them. These problems, which involve various fields such as robotics, bioinformatics, computational biology, gene expression, cancer classification, protein function prediction, etc., could potentially be solved using computational intelligence techniques.

This proceedings volume contains nine selected papers that were presented in the International Symposium in Statistics, 2012 held at Memorial University from July 16 to 18. These nine papers cover three different areas for longitudinal data analysis, four dealing with longitudinal data subject to measurement errors, four on incomplete longitudinal data analysis, and the last one for inferences for longitudinal data subject to outliers. Unlike in the independence setup, the inferences in measurement errors, missing values, and/or outlier models, are not adequately discussed in the longitudinal setup. The papers in the present volume provide details on successes and further challenges in these three areas for longitudinal data analysis. This volume is the first outlet with current research in three important areas in the longitudinal setup. The nine papers presented in three parts clearly reveal the similarities and differences in inference techniques used for three different longitudinal setups. Because the research problems considered in this volume are encountered in many real life studies in biomedical, clinical, epidemiology, socioeconomic, econometrics, and engineering fields, the volume should be useful to the researchers including graduate students in these areas.

This is the first book in longitudinal categorical data analysis with parametric correlation models developed based on dynamic relationships among repeated categorical responses. This book is a natural generalization of the longitudinal binary data analysis to the multinomial data setup with more than two categories. Thus, unlike the existing books on cross-sectional categorical data analysis using log linear models, this book uses multinomial probability models both in cross-sectional and longitudinal setups. A theoretical foundation is provided for the analysis of univariate multinomial responses, by developing models systematically for the cases with no covariates as well as categorical covariates, both in cross-sectional and longitudinal setups. In the longitudinal setup, both stationary and non-stationary covariates are considered. These models have also been extended to the bivariate multinomial setup along with suitable covariates. For the inferences, the book uses the generalized quasi-likelihood as well as the exact likelihood approaches.The book is technically rigorous, and, it also presents illustrations of the statistical analysis of various real life data involving univariate multinomial responses both in cross-sectional and longitudinal setups. This book is written mainly for the graduate students and researchers in statistics and social sciences, among other applied statistics research areas. However, the rest of the book, specifically the chapters from 1 to 3, may also be used for a senior undergraduate course in statistics.

With impending and burgeoning societal issues affecting both developed and emerging nations, the global engineering community has a responsibility and an opportunity to truly make a difference and contribute. The papers in this collection address what materials and resources are integral to meeting basic societal sustainability needs in critical areas of energy, transportation, housing, and recycling. Contributions focus on the engineering answers for cost-effective, sustainable pathways; the strategies for effective use of engineering solutions; and the role of the global engineering community. Authors share perspectives on the major engineering challenges that face our world today; identify, discuss, and prioritize engineering solution needs; and establish how these fit into developing global-demand pressures for materials and human resources.

Topics covered in this collection include the following: *Enabling & Understanding Sustainability - Ferrous & Non-ferrous Metals Processing *Understanding & Enabling Sustainability - (Rechargeable) Batteries *Enabling & Understanding Sustainability - Rare Earth Element Applications *Enabling & Understanding Sustainability - Building Materials & Slag Valorisation *Designing Materials and Systems for Sustainability *Understanding & Enabling Sustainability - Light Metals Recycling & Waste Valorisation *Understanding & Enabling Sustainability - Education Research Innovation I *Understanding & Enabling Sustainability - Education Research Innovation II + Electronic Equipment

A Comprehensive Review of Developing Environmentally Friendly Lubricants A push from environmentally savvy consumers along with recent changes in governmental regulations have paved the way for a marketplace of products with high levels of environmental performance. Fueled by the growing demand for biobased lubricants, Environmentally Friendly and Biobased Lubricants highlights the development of environmentally friendly additives that are compatible with environmental regulations and describes the approaches being used in this emerging area. Derived from research topics shared over the years at various technical sessions of the Society of Tribologists and Lubrication Engineers (STLE) Annual Meetings, the book includes a critical assessment of gaps and weaknesses in the field of environmentally friendly fluids and biobased lubricants. Each chapter is written by authors selected from the environmentally friendly fluids and biobased lubricants sessions of STLE and also incorporates input from prominent researchers invited to take part in the book. Expert contributors discuss the control, production, usage, and disposal of lubricants; factor in related policies, laws, and regulations around the world; and include case studies demonstrating the uses and values of commercially viable biobased lubricants. The book is divided into five sections that cover advanced environmentally friendly base oils and feedstocks, biobased hydraulic lubricants and biodegradability, chemically/enzymatically modified environmentally friendly base oils, vegetable oil-based environmentally friendly fluids, and additives for environmentally friendly fluids.

This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup. Unlike the existing books, this book uses a class of auto-correlation structures to model the longitudinal correlations for the repeated discrete data that accommodates all possible Gaussian type auto-correlation models as special cases including the equi-correlation models. This new dynamic modelling approach is utilized to develop theoretically sound inference techniques such as the generalized quasi-likelihood (GQL) technique for consistent and efficient estimation of the underlying regression effects involved in the model, whereas the existing 'working' correlations based GEE (generalized
estimating equations) approach has serious theoretical limitations both for consistent and efficient estimation, and the existing random effects based correlations approach is not suitable to model the longitudinal correlations. The book has exploited the random effects carefully only to model the correlations of the familial data. Subsequently, this book has modelled the correlations of the longitudinal data collected from the members of a large number of independent families by using the class of auto-correlation structures conditional on the random effects. The book also provides models and inferences for discrete longitudinal data in the adaptive clinical trial set up.
The book is mathematically rigorous and provides details for the development of estimation approaches under selected familial and longitudinal models. Further, while the book provides special cares for mathematics behind the correlation models, it also presents the
illustrations of the statistical analysis of various real life data.
This book will be of interest to the researchers including graduate students in biostatistics and econometrics, among other applied statistics research areas. Brajendra Sutradhar is a University Research Professor at Memorial University in St. John's, Canada. He is an elected member of the International Statistical Institute and a fellow of the American Statistical Association. He has published about 110 papers in statistics journals in the area of multivariate analysis, time series analysis including forecasting, sampling, survival analysis for correlated failure times, robust inferences in generalized linear mixed models with outliers, and generalized linear longitudinal mixed models with bio-statistical and econometric applications. He has served as an associate editor for six years for Canadian Journal of Statistics and for four years for the Journal of Environmental and Ecological Statistics. He has served for 3 years as a member of the advisory committee on statistical methods in Statistics Canada. Professor Sutradhar was awarded 2007 distinguished service award of Statistics Society of Canada for his many years of services to the
society including his special services for society's annual meetings.

This is the first book in longitudinal categorical data analysis with parametric correlation models developed based on dynamic relationships among repeated categorical responses. This book is a natural generalization of the longitudinal binary data analysis to the multinomial data setup with more than two categories. Thus, unlike the existing books on cross-sectional categorical data analysis using log linear models, this book uses multinomial probability models both in cross-sectional and longitudinal setups. A theoretical foundation is provided for the analysis of univariate multinomial responses, by developing models systematically for the cases with no covariates as well as categorical covariates, both in cross-sectional and longitudinal setups. In the longitudinal setup, both stationary and non-stationary covariates are considered. These models have also been extended to the bivariate multinomial setup along with suitable covariates. For the inferences, the book uses the generalized quasi-likelihood as well as the exact likelihood approaches.The book is technically rigorous, and, it also presents illustrations of the statistical analysis of various real life data involving univariate multinomial responses both in cross-sectional and longitudinal setups. This book is written mainly for the graduate students and researchers in statistics and social sciences, among other applied statistics research areas. However, the rest of the book, specifically the chapters from 1 to 3, may also be used for a senior undergraduate course in statistics.

This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup. Unlike the existing books, this book uses a class of auto-correlation structures to model the longitudinal correlations for the repeated discrete data that accommodates all possible Gaussian type auto-correlation models as special cases including the equi-correlation models. This new dynamic modelling approach is utilized to develop theoretically sound inference techniques such as the generalized quasi-likelihood (GQL) technique for consistent and efficient estimation of the underlying regression effects involved in the model, whereas the existing 'working' correlations based GEE (generalized estimating equations) approach has serious theoretical limitations both for consistent and efficient estimation, and the existing random effects based correlations approach is not suitable to model the longitudinal correlations. The book has exploited the random effects carefully only to model the correlations of the familial data. Subsequently, this book has modelled the correlations of the longitudinal data collected from the members of a large number of independent families by using the class of auto-correlation structures conditional on the random effects. The book also provides models and inferences for discrete longitudinal data in the adaptive clinical trial set up. The book is mathematically rigorous and provides details for the development of estimation approaches under selected familial and longitudinal models. Further, while the book provides special cares for mathematics behind the correlation models, it also presents the illustrations of the statistical analysis of various real life data. This book will be of interest to the researchers including graduate students in biostatistics and econometrics, among other applied statistics research areas. Brajendra Sutradhar is a University Research Professor at Memorial University in St. John's, Canada. He is an elected member of the International Statistical Institute and a fellow of the American Statistical Association. He has published about 110 papers in statistics journals in the area of multivariate analysis, time series analysis including forecasting, sampling, survival analysis for correlated failure times, robust inferences in generalized linear mixed models with outliers, and generalized linear longitudinal mixed models with bio-statistical and econometric applications. He has served as an associate editor for six years for Canadian Journal of Statistics and for four years for the Journal of Environmental and Ecological Statistics. He has served for 3 years as a member of the advisory committee on statistical methods in Statistics Canada. Professor Sutradhar was awarded 2007 distinguished service award of Statistics Society of Canada for his many years of services to the society including his special services for society's annual meetings.

This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.

This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.

The present book includes a set of selected best papers from the 3rd International Conference on Recent Developments in Science, Engineering and Technology (REDSET 2016), held in Gurgaon, India, from 21 to 22 October 2016. The conference focused on the experimental, theoretical and application aspects of innovations in computational intelligence and provided a platform for the academicians and scientists. This book provides an insight into ongoing research and future directions in this novel, continuously evolving field. Many decades have been devoted to creating and refining methods and tools for computational intelligence such as Artificial Neural Networks, Evolutionary Computation, Fuzzy Logic, Computational Swarm Intelligence and Artificial Immune Systems. However, their applications have not yet been broadly disseminated. Computational intelligence can be used to provide solutions to many real-life problems, which could be translated into binary languages, allowing computers to process them. These problems, which involve various fields such as robotics, bioinformatics, computational biology, gene expression, cancer classification, protein function prediction, etc., could potentially be solved using computational intelligence techniques.

Topics covered in this collection include the following: *Enabling & Understanding Sustainability - Ferrous & Non-ferrous Metals Processing *Understanding & Enabling Sustainability - (Rechargeable) Batteries *Enabling & Understanding Sustainability - Rare Earth Element Applications *Enabling & Understanding Sustainability - Building Materials & Slag Valorisation *Designing Materials and Systems for Sustainability *Understanding & Enabling Sustainability - Light Metals Recycling & Waste Valorisation *Understanding & Enabling Sustainability - Education Research Innovation I *Understanding & Enabling Sustainability - Education Research Innovation II + Electronic Equipment

This volume compiles topics from the REWAS 2013 symposium at the TMS Annual Meeting, focusing on different aspects of sustainability. It discusses how to realize sustainability in such areas as transportation, the built environment, electrical and electronic equipment and infrastructure, energy production, and water systems. Enabling sustainability topics include the use of metals and materials processing, recycling and recovery, as well as process design and modeling. The book focuses on understanding sustainability through life cycle management and analysis, systems modeling and design, and education and consumer awareness.

This book constitutes the refereed proceedings of the 4th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2017, held in Gurgaon, India, in October 2017. The 66 revised full papers presented were carefully reviewed and selected from 329 submissions. The papers are organized in topical sections on big data analysis, data centric programming, next generation computing, social and web analytics, security in data science analytics.

This proceedings volume contains nine selected papers that were presented in the International Symposium in Statistics, 2012 held at Memorial University from July 16 to 18. These nine papers cover three different areas for longitudinal data analysis, four dealing with longitudinal data subject to measurement errors, four on incomplete longitudinal data analysis, and the last one for inferences for longitudinal data subject to outliers. Unlike in the independence setup, the inferences in measurement errors, missing values, and/or outlier models, are not adequately discussed in the longitudinal setup. The papers in the present volume provide details on successes and further challenges in these three areas for longitudinal data analysis. This volume is the first outlet with current research in three important areas in the longitudinal setup. The nine papers presented in three parts clearly reveal the similarities and differences in inference techniques used for three different longitudinal setups. Because the research problems considered in this volume are encountered in many real life studies in biomedical, clinical, epidemiology, socioeconomic, econometrics, and engineering fields, the volume should be useful to the researchers including graduate students in these areas.

This proceedings volume contains eight selected papers that were presented in the International Symposium in Statistics (ISS) 2015 On Advances in Parametric and Semi-parametric Analysis of Multivariate, Time Series, Spatial-temporal, and Familial-longitudinal Data, held in St. John's, Canada from July 6 to 8, 2015. The main objective of the ISS-2015 was the discussion on advances and challenges in parametric and semi-parametric analysis for correlated data in both continuous and discrete setups. Thus, as a reflection of the theme of the symposium, the eight papers of this proceedings volume are presented in four parts. Part I is comprised of papers examining Elliptical t Distribution Theory. In Part II, the papers cover spatial and temporal data analysis. Part III is focused on longitudinal multinomial models in parametric and semi-parametric setups. Finally Part IV concludes with a paper on the inferences for longitudinal data subject to a challenge of important covariates selection from a set of large number of covariates available for the individuals in the study.

The book "yah Dhoop Tumhari Hai" is a collection of poems on various topics of life, society and environment. The book tries to express the human sentiments under the adverse condition of individual and social crcumstances in simple words and phrases used by common man. It depicts the dialogue between the man and nature through poetry in cotemporary form and style. The contents of book are also contemporary and mostly about the youth struggling with the challenges and opportunities of their time and space. The book describes mainly the life and society of Indian subcontinent in lucid words and verses where economical growth has created in equality and resulted in material and mental proverty as well among the down trodden. The neo rich class, a product of social and political developments has much conflicts and contradictions towards their ethical values creating the social embalance and turmoil which has given a ground to the writing of the book. This has been expressed in different words and meaning in the poems of the book. The book also describes the relation between man and nature where they share each other's happiness and sorrow. The land and river, the sun and moon, the stars and cloud, the wind and mountain, all converse with each other while living together. The poetries of this book make a record of these conversation where they symbolize the eternal love and affection with one and all.

A Comprehensive Review of Developing Environmentally Friendly Lubricants A push from environmentally savvy consumers along with recent changes in governmental regulations have paved the way for a marketplace of products with high levels of environmental performance. Fueled by the growing demand for biobased lubricants, Environmentally Friendly and Biobased Lubricants highlights the development of environmentally friendly additives that are compatible with environmental regulations and describes the approaches being used in this emerging area. Derived from research topics shared over the years at various technical sessions of the Society of Tribologists and Lubrication Engineers (STLE) Annual Meetings, the book includes a critical assessment of gaps and weaknesses in the field of environmentally friendly fluids and biobased lubricants. Each chapter is written by authors selected from the environmentally friendly fluids and biobased lubricants sessions of STLE and also incorporates input from prominent researchers invited to take part in the book. Expert contributors discuss the control, production, usage, and disposal of lubricants; factor in related policies, laws, and regulations around the world; and include case studies demonstrating the uses and values of commercially viable biobased lubricants. The book is divided into five sections that cover advanced environmentally friendly base oils and feedstocks, biobased hydraulic lubricants and biodegradability, chemically/enzymatically modified environmentally friendly base oils, vegetable oil-based environmentally friendly fluids, and additives for environmentally friendly fluids.