Social media and crowdsourcing are important tools for solving complex problems. The benefit of crowdsourcing is that it leverages the power of human intelligence cost effectively and with less time. Social Media and Crowdsourcing: Application and Analytics examines the concepts of social media and crowdsourcing as well as their analytical aspects. It explores how these technologies contribute to the real world and examines such applications as promoting social good, agriculture, healthcare, tourism, disaster management, education, crime control, and cultural heritage. The book also looks at ethical issues in crowdsourcing and future scenarios and challenges for policy. Highlights of the book include: A crowdsourcing application in agriculture Crowdsourcing outline for a contemporary aided medicinal backup system Crowdsourcing-based recommendation in the tourism industry Crowdsourcing mechanisms for reviving cultural heritage Expanding the overarching concept of utilizing social media and crowdsourcing to solve various real-life problems, the book discusses how to bring together the wisdom of crowd for various decision-making problems in agricultural, disaster management, and healthcare. It addresses the various ethical issues arising out of various crowdsourcing-based applications. It puts forward diverse methodologies to involve crowdsourcing in education to implement new strategies to enhance learning outcomes. The book also addresses various problem-solving techniques for recommender applications in the travel and tourism industry. Providing a systematic discussion of the many sectors using crowdsourcing as an essential part of social innovation, the book is a theoretical and methodological look at the application of social media.

Sundarbans, a UNESCO heritage site, is the world’s largest single chunk of mangroves distributed on the Indian and Bangladesh coasts. The mangroves and associated ecosystems are one of the most fertile ecosystems of the earth. Sundarbans Mangrove Systems: A Geo-Informatics Approach portrays different perspectives of studying Sundarbans and mangroves using geospatial analysis. This book highlights the major issues with the Sundarbans mangrove forest, its future conservation strategies and its ecological importance using geo-informatics technology. It explains the usage of remote sensing data for providing information about the present state of mangroves and their tropic status, including assessment in terms of extent, density of community, condition, diversity, identifying potential habitats and heterogeneity. Furthermore, it discusses the use of hyperspectral remote sensing data for species level classification of mangroves, community zonation for biodiversity assessment and for preparing management plans for conservation. KEY FEATURES Exclusively covers the ecological state of Sundarbans (mangrove systems) through geo-informatic studies Describes the application of a combination of geomorphological, biogeochemical and remote sensing methods to the analysis of temporal changes Includes environmental factors affecting the health and decline of mangroves Covers biodiversity and ecological controls in mangroves ecosystems Discusses a remote sensing approach for tropical forested island and mangroves mapping This book is aimed at graduate students and researchers in environmental sciences, ecology, marine sciences, biology, geosciences and GIS/remote sensing areas.

Sundarbans, a UNESCO heritage site, is the world's largest single chunk of mangroves distributed on the Indian and Bangladesh coasts. The mangroves and associated ecosystems are one of the most fertile ecosystems of the earth. Sundarbans Mangrove Systems: A Geo-Informatics Approach portrays different perspectives of studying Sundarbans and mangroves using geospatial analysis. This book highlights the major issues with the Sundarbans mangrove forest, its future conservation strategies and its ecological importance using geo-informatics technology. It explains the usage of remote sensing data for providing information about the present state of mangroves and their tropic status, including assessment in terms of extent, density of community, condition, diversity, identifying potential habitats and heterogeneity. Furthermore, it discusses the use of hyperspectral remote sensing data for species level classification of mangroves, community zonation for biodiversity assessment and for preparing management plans for conservation. KEY FEATURES Exclusively covers the ecological state of Sundarbans (mangrove systems) through geo-informatic studies Describes the application of a combination of geomorphological, biogeochemical and remote sensing methods to the analysis of temporal changes Includes environmental factors affecting the health and decline of mangroves Covers biodiversity and ecological controls in mangroves ecosystems Discusses a remote sensing approach for tropical forested island and mangroves mapping This book is aimed at graduate students and researchers in environmental sciences, ecology, marine sciences, biology, geosciences and GIS/remote sensing areas.

The second international conference on INformation Systems Design and Intelligent Applications (INDIA - 2015) held in Kalyani, India during January 8-9, 2015. The book covers all aspects of information system design, computer science and technology, general sciences, and educational research. Upon a double blind review process, a number of high quality papers are selected and collected in the book, which is composed of two different volumes, and covers a variety of topics, including natural language processing, artificial intelligence, security and privacy, communications, wireless and sensor networks, microelectronics, circuit and systems, machine learning, soft computing, mobile computing and applications, cloud computing, software engineering, graphics and image processing, rural engineering, e-commerce, e-governance, business computing, molecular computing, nano computing, chemical computing, intelligent computing for GIS and remote sensing, bio-informatics and bio-computing. These fields are not only limited to computer researchers but also include mathematics, chemistry, biology, bio-chemistry, engineering, statistics, and all others in which computer techniques may assist.

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques - genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries. The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.

The second international conference on INformation Systems Design and Intelligent Applications (INDIA - 2015) held in Kalyani, India during January 8-9, 2015. The book covers all aspects of information system design, computer science and technology, general sciences, and educational research. Upon a double blind review process, a number of high quality papers are selected and collected in the book, which is composed of two different volumes, and covers a variety of topics, including natural language processing, artificial intelligence, security and privacy, communications, wireless and sensor networks, microelectronics, circuit and systems, machine learning, soft computing, mobile computing and applications, cloud computing, software engineering, graphics and image processing, rural engineering, e-commerce, e-governance, business computing, molecular computing, nano-computing, chemical computing, intelligent computing for GIS and remote sensing, bio-informatics and bio-computing. These fields are not only limited to computer researchers but also include mathematics, chemistry, biology, bio-chemistry, engineering, statistics, and all others in which computer techniques may assist.

With increased climate variability, aggravated natural hazards in the form of extreme events are affecting the lives and livelihoods of many people. This work serves as a basis for formulating a 'preparedness plan' to ensure the effective policy formulation for planned development. Increased demand and competition with a high degree of variability have forced people to struggle in order to prosper. Good governance and innovative policy formulation are necessary to create a resilient society. This may promote a paradigm shift in the mindset on and perceptions of natural hazards and their impacts on development and growth. This new perspective will make people more concerned about minimizing the loss of life, property, and environmental damage and directly safeguard the development process. This book presents a detailed methodological approach to monitoring meteorological, hydrological, and climate change aspects to help resolve issues related to our environment, resources, and economies in the changing climate situation.

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques - genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries. The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.

Protein-protein interactions are extremely valuable towards protein functions and cellular processes or we can say that protein-protein interactions play an important role in living cells. Therefore, if we can control the interactions between proteins, as a result, we can control some functionality of cells. Main functionality of a protein is carried out by its domains. So, domain is a structural or/and functional unit of protein. Behind protein-protein interactions there exist some domain-domain interactions. Therefore, under standing protein-protein interaction at domain level gives a global view of protein-protein interaction network.In this book, we have made an attempt to infer domain-domain interactions from interacting and non-interacting protein pairs then we have predicted protein-protein interactions based on inferred domain-domain interactions.

This book constitutes the refereed proceedings of the Second MICCAI Workshop on Deep Generative Models, DG4MICCAI 2022, held in conjunction with MICCAI 2022, in September 2022. The workshops took place in Singapore. DG4MICCAI 2022 accepted 12 papers from the 15 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community.

This book constitutes the refereed proceedings of the First MICCAI Workshop on Deep Generative Models, DG4MICCAI 2021, and the First MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2021, held in conjunction with MICCAI 2021, in October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic. DG4MICCAI 2021 accepted 12 papers from the 17 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community. For DALI 2021, 15 papers from 32 submissions were accepted for publication. They focus on rigorous study of medical data related to machine learning systems.