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Statistical Methods in Human Genetics (Indian Statistical Institute Series)

This book provides an overview of statistical concepts and basic methodology for the study of genetics of human traits and diseases. It attempts to provide a step-by-step description of problem identification, study design, methodology of data collection, data exploration, data summarization and visualization, and more advanced analytical methods for inferring genetic underpinnings of human phenotypes. The book provides codes in R programming language for implementation of most of the statistical methods described, which will enable practitioners to perform analysis of data on their own, without having to mold the data to fit the requirements of commercial statistical packages. Useful to anyone engaged in studies to understand and manage good health, the book is a useful guide for sustainable development of humankind. Primarily intended for practicing biologists especially those who carry out quantitative biological research, in particular, human geneticists, the book is also helpful in classroom teaching.

Applied Genetic Algorithm and Its Variants: Case Studies and New Developments (Springer Tracts in Nature-Inspired Computing)

This book provides fundamental concepts related to various types of genetic algorithms and practical applications in various domains such as medical imaging, manufacturing, and engineering design. The book discusses genetic algorithms which are used to solve a variety of optimization problems. The genetic algorithms are demonstrated to offer reliable search in complex spaces. The book presents high-quality research work by academics and researchers which is useful for young researchers and students.

Advances in Robust Control and Applications (Studies in Systems, Decision and Control #474)

The book presents recent applications and developments in the field of control of industrial systems, covering a wide range of modeling and feedback control using various robust approaches such as fuzzy systems, sliding mode control, and H-infinity. This book provides insights into theory, applications, and perspectives relevant to the field of robotic systems, exoskeletons, power systems, photovoltaic systems, etc., as well as general methodologies and paradigms around them. Each chapter provides an enriched understanding of a research topic along with a balanced treatment of the relevant theories, methods, or applications. It reports on the latest advances in the field. This book is a good reference for graduate students, researchers, educators, engineers, and scientists and contains a total of 15 chapters divided into five parts as follows. The first part of this book focuses on the application of fuzzy control to robotic systems and consists of three chapters. The second part of this book proposes the control of lower and upper limb exoskeletons and includes two chapters. The third part is dedicated to the control of power systems and comprises three chapters. The fourth part deals with various approaches to the modeling and control of industrial processes and comprises four chapters. The fifth and final part describes observers and fault-tolerant control systems and comprises five chapters.

A Deep Analysis of the Chinese Hukou System: Facts, Impacts, and Reform Paths

This book explores China's hukou system, by which individuals are registered in a specific geographic region, and the prospects for reform. The history of the hukou system and its instrumental role in Chinese urbanization and labor markets is explained, and readers get a sense of what issues are prioritized by Chinese policymakers as they contemplate reform or change to this system, from hukou-based labor market discrimination, inequality of opportunity, multi-dimensional poverty of rural migrants, the public health consequences of non-hukou migration, and old age insurance for migrants without hukous. The author concludes with a stirring and practical call for hukou reform, articulating a cost-benefit model and providing an array of policy suggestions. This book will interest scholars of Chinese society, demographics and future urbanization.

Wind Turbine Aerodynamic Performance Calculation

This book deals with horizontal-axis wind turbine aerodynamic performance prediction methods. It focuses on the traditional and newly-developed methods for the wind turbine aerodynamic performance calculation. The fundamental theories of fluid mechanics essential for understanding the other parts of this book are firstly introduced in Part I, followed by the blade element momentum theory in Part II, with special attentions to a systematic review of various correction models. Part III is mainly about the prescribed and free vortex wake methods, while the state-of-art computational fluid dynamics (CFD) methods are detailed in Part IV.Part III thoroughly describes the prescribed and free vortex wake methods which are still of great importance towards realistic investigation of wind turbine performance. Despite the highly computational cost, the CFD methods in Part IV have received increasing interest from the academic community since they provide more detailed information about the flow field around the wind turbine. This has shed a light in combination with the correction models introduced in Part II on more advanced research for wind turbine.This book is intended for researchers and students interested in aerodynamics of wind turbine and is particularly suitable for practicing engineers in wind energy. Readers can gain a comprehensive understanding in both classical and up-to-date methods for the study of wind turbine aerodynamics. The authors hope that this book can promote the research and development of wind turbines.

Quantum Field Theory and Functional Integrals: An Introduction to Feynman Path Integrals and the Foundations of Axiomatic Field Theory (SpringerBriefs in Physics)

Described here is Feynman's path integral approach to quantum mechanics and quantum field theory from a functional integral point of view. Therein lies the main focus of Euclidean field theory. The notion of Gaussian measure and the construction of the Wiener measure are covered. As well, the notion of classical mechanics and the Schrödinger picture of quantum mechanics are recalled. There, the equivalence to the path integral formalism is shown by deriving the quantum mechanical propagator from it. Additionally, an introduction to elements of constructive quantum field theory is provided for readers.

Applications of Artificial Intelligence and Neural Systems to Data Science (Smart Innovation, Systems and Technologies #360)

This book provides an overview on the current progresses in artificial intelligence and neural nets in data science. The book is reporting on intelligent algorithms and applications modeling, prediction, and recognition tasks and many other application areas supporting complex multimodal systems to enhance and improve human–machine or human–human interactions. This field is broadly addressed by the scientific communities and has a strong commercial impact since investigates on the theoretical frameworks supporting the implementation of sophisticated computational intelligence tools. Such tools will support multidisciplinary aspects of data mining and data processing characterizing appropriate system reactions to human-machine interactional exchanges in interactive scenarios. The emotional issue has recently gained increasing attention for such complex systems due to its relevance in helping in the most common human tasks (like cognitive processes, perception, learning, communication, and even "rational" decision-making) and therefore improving the quality of life of the end users.

Mathematical Modeling in Cultural Heritage: MACH2021 (Springer INdAM Series #55)

This book collects contributions presented at the INdAM Workshop "Mathematical modeling and Analysis of degradation and restoration in Cultural Heritage–MACH2021", held in Rome, Italy in September 2021. The book is focused on mathematical modeling and simulation techniques with the aim of improving the current strategies of conservation and restoration in cultural heritage, sharing different experiences and approaches.The main topics are corrosion and sulphation of materials, damage and fractures, stress in thermomechanical systems, contact and adhesion problems, and phase transitions.

Many-Body Schrödinger Equation: Scattering Theory and Eigenfunction Expansions (Mathematical Physics Studies)

Spectral properties for Schrödinger operators are a major concern in quantum mechanics both in physics and in mathematics. For the few-particle systems, we now have sufficient knowledge for two-body systems, although much less is known about N-body systems. The asymptotic completeness of time-dependent wave operators was proved in the 1980s and was a landmark in the study of the N-body problem. However, many problems are left open for the stationary N-particle equation. Due to the recent rapid development of computer power, it is now possible to compute the three-body scattering problem numerically, in which the stationary formulation of scattering is used. This means that the stationary theory for N-body Schrödinger operators remains an important problem of quantum mechanics. It is stressed here that for the three-body problem, we have a satisfactory stationary theory. This book is devoted to the mathematical aspects of the N-body problem from both the time-dependent and stationary viewpoints. The main themes are:(1) The Mourre theory for the resolvent of self-adjoint operators(2) Two-body Schrödinger operators—Time-dependent approach and stationary approach(3) Time-dependent approach to N-body Schrödinger operators(4) Eigenfunction expansion theory for three-body Schrödinger operatorsCompared with existing books for the many-body problem, the salient feature of this book consists in the stationary scattering theory (4). The eigenfunction expansion theorem is the physical basis of Schrödinger operators. Recently, it proved to be the basis of inverse problems of quantum scattering. This book provides necessary background information to understand the physical and mathematical basis of Schrödinger operators and standard knowledge for future development.

Numerical Methods for Inverse Scattering Problems

This book highlights the latest developments on the numerical methods for inverse scattering problems associated with acoustic, electromagnetic, and elastic waves. Inverse scattering problems are concerned with identifying unknown or inaccessible objects by wave probing data, which makes possible many industrial and engineering applications including radar and sonar, medical imaging, nondestructive testing, remote sensing, and geophysical exploration. The mathematical study of inverse scattering problems is an active field of research. This book presents a comprehensive and unified mathematical treatment of various inverse scattering problems mainly from a numerical reconstruction perspective. It highlights the collaborative research outputs by the two groups of the authors yet surveys and reviews many existing results by global researchers in the literature. The book consists of three parts respectively corresponding to the studies on acoustic, electromagnetic, and elastic scattering problems. In each part, the authors start with in-depth theoretical and computational treatments of the forward scattering problems and then discuss various numerical reconstruction schemes for the associated inverse scattering problems in different scenarios of practical interest. In addition, the authors provide an overview of the existing results in the literature by other researchers. This book can serve as a handy reference for researchers or practitioners who are working on or implementing inverse scattering methods. It can also serve as a graduate textbook for research students who are interested in working on numerical algorithms for inverse scattering problems.

Applied Functional Analysis

WAIC and WBIC with R Stan: 100 Exercises for Building Logic

Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. This book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in R and Stan. Whether you’re a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include:A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.A comprehensive guide to Sumio Watanabe’s groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.Detailed source programs and Stan codes that will enhance readers’ grasp of the mathematical concepts presented.A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!

WAIC and WBIC with Python Stan: 100 Exercises for Building Logic

Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you’re a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include:A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.A comprehensive guide to Sumio Watanabe’s groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.Detailed source programs and Stan codes that will enhance readers’ grasp of the mathematical concepts presented.A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!

Perception of Family and Work in Low-Fertility East Asia (SpringerBriefs in Population Studies)

This book is the first of its kind to incorporate subjective well-being (SWB) data to comprehensively explore perceptional factors that relate to fertility behavior in East Asia. The advantage of SWB data lies in the accessibility to rich information regarding perceptions, attitudes, and behaviors. With this advantage, the book inquires into the perceptions toward family and work and explores the attitudes that lead to low fertility in the region.To this end, first a comparative analysis with international cross-sectional data is performed and the East Asian characteristics of family and work perceptions are documented. Then, three democracies in the region are focused on—Japan, South Korea, and Taiwan—to investigate the relationships between cultural orientations, work–life balance, and fertility outcomes with panel data. In addition, East Asian results are compared with those in India, which has also been experiencing a rapid transition from a traditional society to an industrial one. The results support the idea that the friction between persistent gender-based role divisions and socioeconomic transformation in East Asia makes it difficult for women to balance family and work, prompting fertility decline to the lowest-low level in the region.

Proceedings of International Conference on Data Analytics and Insights, ICDAI 2023 (Lecture Notes in Networks and Systems #727)

The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Analytics and Insights (ICDAI 2023), organized by Techno International, Kolkata, India, during May 11–13, 2023. The book covers important topics like sensor and network data analytics and insights; big data analytics and insights; biological and biomedical data analysis and insights; optimization techniques, time series analysis and forecasting; power and energy systems data analytics and insights; civil and environmental data analytics and insights; and industry and applications.

Demystifying Causal Inference: Public Policy Applications with R

This book provides an accessible introduction to causal inference and data analysis with R, specifically for a public policy audience. It aims to demystify these topics by presenting them through practical policy examples from a range of disciplines. It provides a hands-on approach to working with data in R using the popular tidyverse package. High quality R packages for specific causal inference techniques like ggdag, Matching, rdrobust, dosearch etc. are used in the book.The book is in two parts. The first part begins with a detailed narrative about John Snow’s heroic investigations into the cause of cholera. The chapters that follow cover basic elements of R, regression, and an introduction to causality using the potential outcomes framework and causal graphs. The second part covers specific causal inference methods, including experiments, matching, panel data, difference-in-differences, regression discontinuity design, instrumental variables and meta-analysis, with the help of empirical case studies of policy issues. The book adopts a layered approach that makes it accessible and intuitive, using helpful concepts, applications, simulation, and data graphs. Many public policy questions are inherently causal, such as the effect of a policy on a particular outcome. Hence, the book would not only be of interest to students in public policy and executive education, but also to anyone interested in analysing data for application to public policy.

Machine Learning Methods

This book provides a comprehensive and systematic introduction to the principal machine learning methods, covering both supervised and unsupervised learning methods. It discusses essential methods of classification and regression in supervised learning, such as decision trees, perceptrons, support vector machines, maximum entropy models, logistic regression models and multiclass classification, as well as methods applied in supervised learning, like the hidden Markov model and conditional random fields. In the context of unsupervised learning, it examines clustering and other problems as well as methods such as singular value decomposition, principal component analysis and latent semantic analysis. As a fundamental book on machine learning, it addresses the needs of researchers and students who apply machine learning as an important tool in their research, especially those in fields such as information retrieval, natural language processing and text data mining. In order to understand the concepts and methods discussed, readers are expected to have an elementary knowledge of advanced mathematics, linear algebra and probability statistics. The detailed explanations of basic principles, underlying concepts and algorithms enable readers to grasp basic techniques, while the rigorous mathematical derivations and specific examples included offer valuable insights into machine learning.

Probability-Based Multi-objective Optimization for Material Selection

The second edition of this book illuminates the fundamental principle and applications of probability-based multi-objective optimization for material selection in viewpoint of system theory, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time. Hybrids of the new approach with experimental design methodologies (response surface methodology, orthogonal experimental design, and uniform experimental design) are all performed; robustness assessment and performance utility with desirable value are included; discretization treatment in the evaluation is presented; fuzzy-based approach and cluster analysis are involved; applications in portfolio investment and shortest path problem are concerned as well. The authors wish this work will cast a brick to attract jade and would make its contributions to relevant fields as a paving stone. It is designed to be used as a textbook for postgraduate and advanced undergraduate students in relevant majors, while also serving as a valuable reference book for scientists and engineers involved in related fields.

Benchmarks and Hybrid Algorithms in Optimization and Applications (Springer Tracts in Nature-Inspired Computing)

This book is specially focused on the latest developments and findings on hybrid algorithms and benchmarks in optimization and their applications in sciences, engineering, and industries. The book also provides some comprehensive reviews and surveys on implementations and coding aspects of benchmarks. The book is useful for Ph.D. students and researchers with a wide experience in the subject areas and also good reference for practitioners from academia and industrial applications.

ANOVA with Dependent Errors (SpringerBriefs in Statistics)

This book presents the latest results related to one- and two-way models for time series data. Analysis of variance (ANOVA) is a classical statistical method for IID data proposed by R.A. Fisher to investigate factors and interactions of phenomena. In contrast, the methods developed in this book apply to time series data. Testing theory of the homogeneity of groups is presented under a wide variety of situations including uncorrelated and correlated groups, fixed and random effects, multi- and high-dimension, parametric and nonparametric spectral densities. These methods have applications in several scientific fields. A test for the existence of interactions is also proposed. The book deals with asymptotics when the number of groups is fixed and sample size diverges. This framework distinguishes the approach of the book from panel data and longitudinal analyses, which mostly deal with cases in which the number of groups is large. The usefulness of the theory in this book is illustrated by numerical simulation and real data analysis. This book is suitable for theoretical statisticians and economists as well as psychologists and data analysts.

Advanced Trajectory Optimization, Guidance and Control Strategies for Aerospace Vehicles: Methods and Applications (Springer Aerospace Technology)

This book focuses on the design and application of advanced trajectory optimization and guidance and control (G&C) techniques for aerospace vehicles. Part I of the book focuses on the introduction of constrained aerospace vehicle trajectory optimization problems, with particular emphasis on the design of high-fidelity trajectory optimization methods, heuristic optimization-based strategies, and fast convexification-based algorithms. In Part II, various optimization theory/artificial intelligence (AI)-based methods are constructed and presented, including dynamic programming-based methods, model predictive control-based methods, and deep neural network-based algorithms. Key aspects of the application of these approaches, such as their main advantages and inherent challenges, are detailed and discussed. Some practical implementation considerations are then summarized, together with a number of future research topics. The comprehensive and systematic treatment of practical issues in aerospace trajectory optimization and guidance and control problems is one of the main features of the book, which is particularly suitable for readers interested in learning practical solutions in aerospace trajectory optimization and guidance and control. The book is useful to researchers, engineers, and graduate students in the fields of G&C systems, engineering optimization, applied optimal control theory, etc.

Marginal Revolution in Economics: A Reappraisal (Monographs in Mathematical Economics #6)

This volume is devoted to a reappraisal of the Marginal Revolution on the occasion of its 150th anniversary. The year 1871 should be remembered as one of the most important turning points in the history of economics. W. S. Jevons, C. Menger, and L. Walras published epochal works at the very beginning of the 1870s. Although these works were written independently, they shared a common mathematical structure based on classical analysis. For this reason, the emergence of the trio is called the Marginal Revolution. Indeed, 1871 is the starting point of modern economics in the proper sense. In 1971, several academic conferences were held on the occasion of the 100th anniversary of the Revolution, which exerted the stimulating influence upon the historical researches into the Revolution. Now more than fifty years have passed since then. Economic theory has experienced further substantial changes in researchers’ central interest, the way of reasonings and the styles of description during this period. In view of the new achievements acquired in recent fifty years, it seems an indispensable task for us to review and reevaluate the Marginal Revolution based upon the present status of economics.We also keep in mind that some concepts and doctrines once discarded could reappear in a later stage of history in a more or less transfigured form. The introductory chapter will be a guide for readers not only from the economics community but also from the mathematics community.

Gaps and Actions in Health Improvement from Hong Kong and Beyond: All for Health

This book provides a timely review on what has been accomplished, and what remains amiss, following the World Health Organization’s 1978 ‘Health for All’ campaign, by identifying enduring gaps in health care within a global context. The WHO declaration of "Health for All by the Year 2000" mapped out a road towards primary health care for all people and demarcated it as essential for human progress in terms of economic development and social justice. However, 45 years have gone by, and most societies and countries have yet achieved 'health for all’, despite so much having changed in technology, disease patterns, and population demographics. In promoting community health and improving service delivery, the book advocates the development and implementation of “All For Health” strategies to steer stakeholders in the right direction towards universal health care. The book covers the gaps and actions in health improvements, the ‘All For Health’ strategies, and the Health in All Policies (HiAP), reviewing and discussing issues through both Asian and international examples. Contributors include both academics and practitioners from diverse professional backgrounds including medicine, nursing, pharmacy, allied health, dietetics, social sciences, life sciences, education, business, administration, law, and public policy. Essential to scholars in public health and related disciplines, this book is also useful to policymakers, community and public health practitioners, and health care executives and interns.

Big Data Analytics in Intelligent IoT and Cyber-Physical Systems (Transactions on Computer Systems and Networks)

This book explores the complete system perspective, underlying theories, modeling, and applications of cyber-physical systems (CPS). Considering the interest of researchers and academicians, the editors present this book in a multidimensional perspective covering CPS at breadth. It covers topics ranging from discussion of rudiments of the system and efficient management to recent research challenges and issues. This book is divided into four sections discussing the fundamentals of CPS, engineering-based solutions, its applications, and advanced research challenges. The contents highlight the concept map of CPS including the latest technological interventions, issues, challenges, and the integration of CPS with IoT and big data analytics, modeling solutions, distributed management, efficient energy management, cyber-physical systems research, and education with applications in industrial, agriculture, and medical domains. This book is of immense interest to those in academia and industry.

Collaborative Optimization of Complex Energy Systems: Applications in Iron and Steel Industry (Engineering Applications of Computational Methods #17)

This book mainly focuses on the multi-media energy prediction technology and optimization methods of iron and steel enterprises. The technical methods adopted include swarm intelligence algorithm, neural network, reinforcement learning, and so on. Energy saving and consumption reduction in iron and steel enterprises have always been a research hotspot in the field of process control. This book considers the multi-media energy balance problem from the perspective of system, studies the energy flow and material flow in iron and steel enterprises, and provides energy optimization methods that can be used for planning, prediction, and scheduling under different production scenes. The main audience of this book is scholars and graduate students in the fields of control theory, applied mathematics, energy optimization, etc.