Meenakshi Sharma – författare

MicroRNA Advances and Application in Plant Biology presents a broad range of tools and techniques used for microRNA identification and utilization for diversity analysis in plants, crop improvement, and gene regulation. With expert insights, this book addresses those concepts through curated chapters that are well-illustrated with informative data, tables, figures, and photographs. While biological microRNA database resources have been created for the better understanding of structural and functional properties of primary-microRNAs (pri-microRNAs) to mature microRNAs, there remains a need for foundation understanding of how microRNAs may play a very crucial role in a plant lifecycle as an regulatory and stress tolerance molecule.There are still many unanswered questions about the structural and functional properties of the microRNAs, like the role of microRNA in crop improvement, gene regulation, stress tolerance, disease resistance plant, plant communication, and environmental interaction.

This powerful new volume explores the diverse and sometimes unexpected roles that IoT and AI technologies played during the recent COVID-19 global pandemic. The book discusses the how existing and new state-of-the art technology has been and can be applied for global health crises in a multitude of ways.

The chapters in Pandemic Detection and Analysis through Smart Computing Technologies look at exciting technological solutions for virus detection, prediction, classification, prevention, and communication outreach. The book considers the various modes of transmission of the virus as well as how technology has been implemented for personalized healthcare systems and how it can be used for future pandemics.

The huge importance of social and mobile communication and networks during the pandemic is addressed such as in business, education, and healthcare; in research and development; for health information and outreach; in social life; and more. A chapter also addresses using smart computing for forecasting the damage caused by COVID-19 using time series analyses.

This up-to-the-minute volume illuminates on the many ways AI, IoT, machine learning, and other technologies have important roles in the diverse challenges faced during COVID-19 and how they can be enhanced for future pandemic situations. The volume will be of high interest to those in different fields of computer science and other domains as well as to data scientists, government agencies and policymakers, doctors and healthcare professionals, engineers, economists, and many other professionals. This book will also be very helpful to faculty, students, and research scholars in understanding the pre- and post-effect of this pandemic.

This powerful new volume explores the diverse and sometimes unexpected roles that IoT and AI technologies played during the recent COVID-19 global pandemic. The book discusses the how existing and new state-of-the art technology has been and can be applied for global health crises in a multitude of ways.

The chapters in Pandemic Detection and Analysis through Smart Computing Technologies look at exciting technological solutions for virus detection, prediction, classification, prevention, and communication outreach. The book considers the various modes of transmission of the virus as well as how technology has been implemented for personalized healthcare systems and how it can be used for future pandemics.

The huge importance of social and mobile communication and networks during the pandemic is addressed such as in business, education, and healthcare; in research and development; for health information and outreach; in social life; and more. A chapter also addresses using smart computing for forecasting the damage caused by COVID-19 using time series analyses.

This up-to-the-minute volume illuminates on the many ways AI, IoT, machine learning, and other technologies have important roles in the diverse challenges faced during COVID-19 and how they can be enhanced for future pandemic situations. The volume will be of high interest to those in different fields of computer science and other domains as well as to data scientists, government agencies and policymakers, doctors and healthcare professionals, engineers, economists, and many other professionals. This book will also be very helpful to faculty, students, and research scholars in understanding the pre- and post-effect of this pandemic.

This book presents a framework for integrating blended learning and massive open online courses (MOOCs) in the Indian education system. It argues that blended teaching and learning is the most suitable approach to education in a post-COVID-19 world. Drawing on case studies used in blended learning practices around the world, the book provides ample resources for beginners to improvise the spread of knowledge around information technology in higher education. It discusses various concepts such as flip learning in blended learning models and examines the self-assessment tools and structures it offers to institutions for building competencies.

In addition to addressing the challenges and opportunities of adopting the digital mode of teaching, the book also offers techniques and concepts helpful for designing MOOCs. It covers concepts such as curriculum designing, content flow, teaching behavior, and evaluation patterns, which are important aspects of online teaching. An indispensable guide to navigating the shift from offline to online teaching, this book will be of interest to students, teachers, and researchers of education, education technology, digital education, and information technology. It will also be useful to policymakers, educational institutions, EdTech start-ups, NGOs in the education sector, and online education centers.

This book presents a framework for integrating blended learning and massive open online courses (MOOCs) in the Indian education system. It argues that blended teaching and learning is the most suitable approach to education in a post-COVID-19 world. Drawing on case studies used in blended learning practices around the world, the book provides ample resources for beginners to improvise the spread of knowledge around information technology in higher education. It discusses various concepts such as flip learning in blended learning models and examines the self-assessment tools and structures it offers to institutions for building competencies.

In addition to addressing the challenges and opportunities of adopting the digital mode of teaching, the book also offers techniques and concepts helpful for designing MOOCs. It covers concepts such as curriculum designing, content flow, teaching behavior, and evaluation patterns, which are important aspects of online teaching. An indispensable guide to navigating the shift from offline to online teaching, this book will be of interest to students, teachers, and researchers of education, education technology, digital education, and information technology. It will also be useful to policymakers, educational institutions, EdTech start-ups, NGOs in the education sector, and online education centers.

This comprehensive and timely book, New Age Analytics: Transforming the Internet through Machine Learning, IoT, and Trust Modeling, explores the importance of tools and techniques used in machine learning, big data mining, and more. The book explains how advancements in the world of the web have been achieved and how the experiences of users can be analyzed. It looks at data gathering by the various electronic means and explores techniques for analysis and management, how to manage voluminous data, user responses, and more.

This volume provides an abundance of valuable information for professionals and researchers working in the field of business analytics, big data, social network data, computer science, analytical engineering, and forensic analysis. Moreover, the book provides insights and support from both practitioners and academia in order to highlight the most debated aspects in the field.

This comprehensive and timely book, New Age Analytics: Transforming the Internet through Machine Learning, IoT, and Trust Modeling, explores the importance of tools and techniques used in machine learning, big data mining, and more. The book explains how advancements in the world of the web have been achieved and how the experiences of users can be analyzed. It looks at data gathering by the various electronic means and explores techniques for analysis and management, how to manage voluminous data, user responses, and more.

This volume provides an abundance of valuable information for professionals and researchers working in the field of business analytics, big data, social network data, computer science, analytical engineering, and forensic analysis. Moreover, the book provides insights and support from both practitioners and academia in order to highlight the most debated aspects in the field.

The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience.

Features

The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience.

Features

This book focuses on low-carbon sustainable cement production, performance, environmental efficiency, and other topics linked to calcined clays for sustainable concrete. It comprises select proceedings of the International Conference on Calcined Clays for Sustainable Concrete 2022, which was held at École Polytechnique Fédérale de Lausanne (EPFL)—Switzerland. The contents of this book focus on the influence of processing and clay mineralogy on the reactivity and rheology of calcined clay systems, Portland-calcined clay-limestone systems: hydration, durability, and performance, and calcined clay-alkali systems: hydration, durability, and performance, etc. This book can serve as a useful reference to researchers, academicians, and practitioners alike.