Neha Gupta – författare

Sustainable Advanced Solar Passive House provides a platform to disseminate knowledge regarding the basics of solar energy, heat transfer, and solar houses, including designing concepts. Apart from a brief introduction to solar physics and thermodynamics, the book primarily deals with the technical description of solar houses and associated concepts. Different types of photovoltaic modules and their integration with the buildings are discussed with case studies, including energy balance equations and fundamental energy matrices. It discusses concepts like energy matrices, solar passive heating/cooling, architecture design, low-cost building, energy/exergy analysis, building integrated photovoltaic, and energy conservation.

Sustainable Advanced Solar Passive House provides a platform to disseminate knowledge regarding the basics of solar energy, heat transfer, and solar houses, including designing concepts. Apart from a brief introduction to solar physics and thermodynamics, the book primarily deals with the technical description of solar houses and associated concepts. Different types of photovoltaic modules and their integration with the buildings are discussed with case studies, including energy balance equations and fundamental energy matrices. It discusses concepts like energy matrices, solar passive heating/cooling, architecture design, low-cost building, energy/exergy analysis, building integrated photovoltaic, and energy conservation.

The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools.

This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them.

Features

The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools.

This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them.

Features

This book presents fundamental concepts of optimization problems and its real-world applications in various fields. The core concepts of optimization, formulations and solution procedures of various real-world problems are provided in an easy-to-read manner. The unique feature of this book is that it presents unified knowledge of the modelling of real-world decision-making problems and provides the solution procedure using the appropriate optimization techniques.

The book will help students, researchers, and faculty members to understand the need for optimization techniques for obtaining optimal solution for the decision-making problems. It provides a sound knowledge of modelling of real-world problems using optimization techniques. It is a valuable compendium of several optimization techniques for solving real-world application problems using optimization software LINGO. The book is useful for academicians, practitioners, students and researchers in the field of OR. It is written in simple language with a detailed explanation of the core concepts of optimization techniques. Readers of this book will understand the formulation of real-world problems and their solution procedures obtained using the appropriate optimization techniques.

This book presents fundamental concepts of optimization problems and its real-world applications in various fields. The core concepts of optimization, formulations and solution procedures of various real-world problems are provided in an easy-to-read manner. The unique feature of this book is that it presents unified knowledge of the modelling of real-world decision-making problems and provides the solution procedure using the appropriate optimization techniques.

The book will help students, researchers, and faculty members to understand the need for optimization techniques for obtaining optimal solution for the decision-making problems. It provides a sound knowledge of modelling of real-world problems using optimization techniques. It is a valuable compendium of several optimization techniques for solving real-world application problems using optimization software LINGO. The book is useful for academicians, practitioners, students and researchers in the field of OR. It is written in simple language with a detailed explanation of the core concepts of optimization techniques. Readers of this book will understand the formulation of real-world problems and their solution procedures obtained using the appropriate optimization techniques.

Artificial Intelligence for Capital Market throws light on the application of AI/ML techniques in the financial capital markets. This book discusses the challenges posed by the AI/ML techniques as these are prone to "black box" syndrome. The complexity of understanding the underlying dynamics for results generated by these methods is one of the major concerns which is highlighted in this book.

Features:

This book serves as a reference book for academicians, industry professionals, traders, finance managers and stock brokers. It may also be used as textbook for graduate level courses in financial services and financial analytics.

Artificial Intelligence for Capital Market throws light on the application of AI/ML techniques in the financial capital markets. This book discusses the challenges posed by the AI/ML techniques as these are prone to "black box" syndrome. The complexity of understanding the underlying dynamics for results generated by these methods is one of the major concerns which is highlighted in this book.

Features:

This book serves as a reference book for academicians, industry professionals, traders, finance managers and stock brokers. It may also be used as textbook for graduate level courses in financial services and financial analytics.

Business Analytics (BA) is an evolving phenomenon that showcases the increasing importance of using huge volumes of data to generate value for businesses. Advances in BA have offered great opportunities for organisations to improve, innovate, and develop existing or new processes, products, and services. BA is the process of transforming data into actionable insight by using statistical and mathematical analysis, descriptive, prescriptive, and predictive models, machine learning, information systems and network science methods, among others, along with a variety of data, expert knowledge, and fact-based management to support better and faster decision-making.

BA and Business Intelligence (BI) generate capabilities for companies to compete in the market effectively and has become one of the main functional areas in most companies. BA tools are used in diverse ways, for example, to identify consumer behaviour patterns and market trends, to derive valuable insights on the performance of stocks, to find information on the attrition rate of employees, to analyse and solve healthcare problems, to offer insight into inventory management and supply chain management, to analyse data from social networks, and to infer traffic behaviour and develop traffic management policy, among others.

BA and BI have become one of the most popular research areas in academic circles, as well as in the industry, driven by the increasing demand in the business world. This book aims to become a stimulus for innovative business solutions covering a wide range of aspects of business analytics, such as management science, information technology, descriptive, prescriptive, and predictive models, machine learning, network science, mathematical and statistical techniques. The book will encompass a valuable collection of chapters exploring and discussing computational frameworks, practices, and applications of BA that can assist industries and relevant stakeholders in decision-making and problem-solving exercises, with a view to driving competitive advantage.

Business Analytics (BA) is an evolving phenomenon that showcases the increasing importance of using huge volumes of data to generate value for businesses. Advances in BA have offered great opportunities for organisations to improve, innovate, and develop existing or new processes, products, and services. BA is the process of transforming data into actionable insight by using statistical and mathematical analysis, descriptive, prescriptive, and predictive models, machine learning, information systems and network science methods, among others, along with a variety of data, expert knowledge, and fact-based management to support better and faster decision-making.

BA and Business Intelligence (BI) generate capabilities for companies to compete in the market effectively and has become one of the main functional areas in most companies. BA tools are used in diverse ways, for example, to identify consumer behaviour patterns and market trends, to derive valuable insights on the performance of stocks, to find information on the attrition rate of employees, to analyse and solve healthcare problems, to offer insight into inventory management and supply chain management, to analyse data from social networks, and to infer traffic behaviour and develop traffic management policy, among others.

BA and BI have become one of the most popular research areas in academic circles, as well as in the industry, driven by the increasing demand in the business world. This book aims to become a stimulus for innovative business solutions covering a wide range of aspects of business analytics, such as management science, information technology, descriptive, prescriptive, and predictive models, machine learning, network science, mathematical and statistical techniques. The book will encompass a valuable collection of chapters exploring and discussing computational frameworks, practices, and applications of BA that can assist industries and relevant stakeholders in decision-making and problem-solving exercises, with a view to driving competitive advantage.

The book examines the social and cultural role of selfies in India. It looks at how the selfie, unlike the photograph, which was a gesture towards an external reality, remains intimately self-referential, yet reconfigures social ordering, identity formation, agency, and spaces in curious ways.

This volume approaches questions about the construction and performance of the self through the digital selfie and uses this situated, contextualized, and culturally specific phenomenon as a site to explore the themes of self-making, place-making, gender, subjectivity, and power. Highlighting the specific contexts of production, the authors examine the array of self-expressive capabilities realized in a multitude of uses of the selfie that simultaneously reconfigure the self, the space, and the world.

An important study of visual social media culture, the volume will be useful for interpreting everyday media experiences and will be of interest to students and researchers of image studies, visual studies, photography studies, visual culture, media studies, culture studies, cultural anthropology, digital humanities, popular culture, sociology of technology, and South Asian studies.

The book examines the social and cultural role of selfies in India. It looks at how the selfie, unlike the photograph, which was a gesture towards an external reality, remains intimately self-referential, yet reconfigures social ordering, identity formation, agency, and spaces in curious ways.

This volume approaches questions about the construction and performance of the self through the digital selfie and uses this situated, contextualized, and culturally specific phenomenon as a site to explore the themes of self-making, place-making, gender, subjectivity, and power. Highlighting the specific contexts of production, the authors examine the array of self-expressive capabilities realized in a multitude of uses of the selfie that simultaneously reconfigure the self, the space, and the world.

An important study of visual social media culture, the volume will be useful for interpreting everyday media experiences and will be of interest to students and researchers of image studies, visual studies, photography studies, visual culture, media studies, culture studies, cultural anthropology, digital humanities, popular culture, sociology of technology, and South Asian studies.

This handbook addresses how smart operations, management, and healthcare can be used to detect and analyze supply chain problems, business problems, and diseases. It also discusses the underlying methodologies and related security concerns.

Handbook of Disruptive Technologies: Operations, Business, Management, and Healthcare provides updated and timely insights, unique approaches or frameworks, practical applications, and case studies. It provides in-depth knowledge of disruptive technologies and applies data analytics to different areas to solve complex situations. The handbook uses data analytics in decision-making and policy framing and identifies practices and applications of disruptive technologies that can assist organizations in gaining a competitive advantage. Valuable insights, innovative approaches, practical applications, and case studies can be found in this handbook as it effectively consolidates and synthesizes information to provide a comprehensive understanding of the subject matter.

This book is tailored for researchers, academics, and professionals seeking to deepen their knowledge in the field.

This handbook addresses how smart operations, management, and healthcare can be used to detect and analyze supply chain problems, business problems, and diseases. It also discusses the underlying methodologies and related security concerns.

Handbook of Disruptive Technologies: Operations, Business, Management, and Healthcare provides updated and timely insights, unique approaches or frameworks, practical applications, and case studies. It provides in-depth knowledge of disruptive technologies and applies data analytics to different areas to solve complex situations. The handbook uses data analytics in decision-making and policy framing and identifies practices and applications of disruptive technologies that can assist organizations in gaining a competitive advantage. Valuable insights, innovative approaches, practical applications, and case studies can be found in this handbook as it effectively consolidates and synthesizes information to provide a comprehensive understanding of the subject matter.

This book is tailored for researchers, academics, and professionals seeking to deepen their knowledge in the field.