This book explains in depth the issues and challenges faced by rice farmers in India in relation to production and productivity, and the possible adaptation strategies to climate change. Based on five years of groundbreaking research on emerging trends in cultivation in major rice growing regions in India, it begins by describing production and yield trends across different rice growing regions. It then offers a comprehensive review of relevant literature and the quantification methodologies and approaches used to analyze the impact of climate change. The book also analyzes climate change impacts on rice productivity and production, applying field-tested quantification methods, such as the Just-Pope production function where time series and cross-section data are simultaneously used for all regions. The results are presented for five geographical regions of India - northern, eastern, western, central and southern - for better comparison and readability. The analyses cover scenarios for both mid-century (2021-2050) and end-century (2071-2100), and in the context of climate change, they also incorporate both medium and high carbon emission scenarios. Thus the future rice production and productivity trends are clearly projected for making necessary interventions. Lastly, the book outlines the essentials of an enabling environment policy and discusses the institutional and policy options necessary to ensure sustainable rice production in India. It also makes the case for introducing appropriate and affordable adaptation strategies to support farmers in different rice-growing regions. The cost-benefit analysis of strategies presented in this book provides an invaluable tool for officials at agriculture departments planning up-scaling of agricultural productivity. The projections are also useful for policy makers and planners developing future investment plans to support rice production in their country. Overall, this book is of interest to a wide audience, including professionals and business enterprises dealing with rice, as well as to academic researchers and students.

Businesses constantly face online hacking threats or security breaches in their online mainframe that expose sensitive information to the wrong audience. Companies look to store their data in a separate location, distancing the availability of the information and reducing the risk of data breaches. Modern organizations need to remain vigilant against insider attacks, cloud computing risks, and security flaws within their mainframe. Detection and Mitigation of Insider Attacks in a Cloud Infrastructure: Emerging Research and Opportunities is an essential reference source that discusses maintaining a secure management of sensitive data, and intellectual property and provides a robust security algorithm on consumer data. Featuring research on topics such as public cryptography, security principles, and trustworthy computing, this book is ideally designed for IT professionals, business managers, researchers, students, and professionals seeking coverage on preventing and detecting the insider attacks using trusted cloud computing techniques.

This book provides an overview of climate change in India using river basin data and analytical and econometric methods. It, first, makes a quantitative assessment of how climate change affects agricultural and food production systems; second, predicts how these systems may respond to climate change; and third, suggests adaptation measures and strategies to improve the income of farmers, increase production, save water and conserve environment.The work will be greatly useful to policy-makers, researchers and teachers of agricultural economics, environmental studies and economics and development studies as also to research organizations dealing with climate modelling and resource management.

This book provides an overview of climate change in India using river basin data and analytical and econometric methods. It, first, makes a quantitative assessment of how climate change affects agricultural and food production systems; second, predicts how these systems may respond to climate change; and third, suggests adaptation measures and strategies to improve the income of farmers, increase production, save water and conserve environment.The work will be greatly useful to policy-makers, researchers and teachers of agricultural economics, environmental studies and economics and development studies as also to research organizations dealing with climate modelling and resource management.

This book argues that embeddedness and community participation bring unique propositions for social entrepreneurship to foster social inclusion. It uncovers the role of local knowledge and grassroots level innovations to create necessary environment for the positive social change to roll. Social enterprises have proven to reduce drudgery of poor and excluded by offering creative and innovative solutions for long standing social problems. The grassroots level creative problem solving mechanisms they initiate travel through a variety of local dynamics and cultural contexts. However, social innovations quite often do not achieve their intended results, especially when they fail to understand the local contexts and embed themselves in such dynamism. In this background, the book attempts to understand and analyse the 'connect' between the social innovations and local dynamism. It argues that the community-driven innovation management which is based on local knowledge inspires the social entrepreneurial process and builds capacities and infrastructure to foster social inclusion. Each chapter in this book offers development scholars rich narration about how social problems have been approached, addressed, and altered through rich insights from communities and the social entrepreneurial teams.

This book constitutes the refereed proceedings of the 6th International Conference on Big Data analytics, BDA 2018, held in Warangal, India, in December 2018. The 29 papers presented in this volume were carefully reviewed and selected from 93 submissions. The papers are organized in topical sections named: big data analytics: vision and perspectives; financial data analytics and data streams; web and social media data; big data systems and frameworks; predictive analytics in healthcare and agricultural domains; and machine learning and pattern mining.

This volume constitutes the papers of several workshops which were held in conjunction with the 27th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held as virtual event in April 2022. The 30 revised full papers presented in this book were carefully reviewed and selected from 65 submissions. DASFAA 2022 presents the following five workshops: * First workshop on Pattern mining and Machine learning in Big complex Databases (PMBD 2021) * 6th International Workshop on Graph Data Management and Analysis (GDMA 2022) * First International Workshop on Blockchain Technologies (IWBT2022) * 8th International Workshop on Big Data Management and Service (BDMS 2022) * First workshop on Managing Air Quality Through Data Science * 7th International Workshop on Big Data Quality Management (BDQM 2022).

This book constitutes the proceedings of the 10th International Conference on Big Data Analytics, BDA 2022, which took place in Hyderabad, India, in December 2022. The 7 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 36 submissions. The book also contains 4 keynote talks in full-paper length. The papers are organized in the following topical sections: Big Data Analytics: Vision and Perspectives; Data Science: Architectures; Data Science: Applications; Graph Analytics; Pattern Mining; Predictive Analytics in Agriculture.

The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 short papers, are presented in this three-volume set was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are included. The conference was planned to take place in Hyderabad, India, but it was held virtually due to the COVID-19 pandemic.

The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 short papers, are presented in this three-volume set was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are included. The conference was planned to take place in Hyderabad, India, but it was held virtually due to the COVID-19 pandemic.

The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 short papers, are presented in this three-volume set was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are included. The conference was planned to take place in Hyderabad, India, but it was held virtually due to the COVID-19 pandemic.

This book constitutes the proceedings of the 8th International Conference on Big Data Analytics, BDA 2021, which took place during December 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 full and 3 short papers included in this volume were carefully reviewed and selected from 41 submissions. The contributions were organized in topical sections named as follows: medical and health applications; machine/deep learning; IoTs, sensors, and networks; fundamentation; pattern mining and data analytics.

The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021.The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.

The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021.The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.

The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021.The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.

This book constitutes the proceedings of the 8th International Conference on Big Data Analytics, BDA 2020, which took place during December 15-18, 2020, in Sonepat, India. The 11 full and 3 short papers included in this volume were carefully reviewed and selected from 48 submissions; the book also contains 4 invited and 3 tutorial papers. The contributions were organized in topical sections named as follows: data science systems; data science architectures; big data analytics in healthcare; information interchange of Web data resources; and business analytics.

This book explains in depth the issues and challenges faced by rice farmers in India in relation to production and productivity, and the possible adaptation strategies to climate change. Based on five years of groundbreaking research on emerging trends in cultivation in major rice growing regions in India, it begins by describing production and yield trends across different rice growing regions. It then offers a comprehensive review of relevant literature and the quantification methodologies and approaches used to analyze the impact of climate change. The book also analyzes climate change impacts on rice productivity and production, applying field-tested quantification methods, such as the Just-Pope production function where time series and cross-section data are simultaneously used for all regions. The results are presented for five geographical regions of India - northern, eastern, western, central and southern - for better comparison and readability. The analyses cover scenarios for both mid-century (2021-2050) and end-century (2071-2100), and in the context of climate change, they also incorporate both medium and high carbon emission scenarios. Thus the future rice production and productivity trends are clearly projected for making necessary interventions. Lastly, the book outlines the essentials of an enabling environment policy and discusses the institutional and policy options necessary to ensure sustainable rice production in India. It also makes the case for introducing appropriate and affordable adaptation strategies to support farmers in different rice-growing regions. The cost-benefit analysis of strategies presented in this book provides an invaluable tool for officials at agriculture departments planning up-scaling of agricultural productivity. The projections are also useful for policy makers and planners developing future investment plans to support rice production in their country. Overall, this book is of interest to a wide audience, including professionals and business enterprises dealing with rice, as well as to academic researchers and students.

This book constitutes the refereed proceedings of the 7th International Conference on Big Data analytics, BDA 2019, held in Ahmedabad, India, in December 2019.The 25 papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections named: big data analytics: vision and perspectives; search and information extraction; predictive analytics in medical and agricultural domains; graph analytics; pattern mining; and machine learning.

This book argues that embeddedness and community participation bring unique propositions for social entrepreneurship to foster social inclusion. It uncovers the role of local knowledge and grassroots level innovations to create necessary environment for the positive social change to roll. Social enterprises have proven to reduce drudgery of poor and excluded by offering creative and innovative solutions for long standing social problems. The grassroots level creative problem solving mechanisms they initiate travel through a variety of local dynamics and cultural contexts. However, social innovations quite often do not achieve their intended results, especially when they fail to understand the local contexts and embed themselves in such dynamism. In this background, the book attempts to understand and analyse the 'connect' between the social innovations and local dynamism. It argues that the community-driven innovation management which is based on local knowledge inspires the social entrepreneurial process and builds capacities and infrastructure to foster social inclusion. Each chapter in this book offers development scholars rich narration about how social problems have been approached, addressed, and altered through rich insights from communities and the social entrepreneurial teams.

This book constitutes the refereed conference proceedings of the 5th International Conference on Big Data Analytics, BDA 2017, held in Hyderabad, India, in December 2017. The 21 revised full papers were carefully reviewed and selected from 80 submissions and cover topics on big data analytics, information and knowledge management, mining of massive datasets, computational modeling, data mining and analysis.