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Advanced ICTs for Disaster Management and Threat Detection: Collaborative and Distributed Frameworks
"This book offers state-of-the-art information and references for work undertaken in the challenging area of utilizing cutting-edge distributed and collaborative ICT to advance disaster management as a discipline to cope with current and future unforeseen threats"--Provided by publisher.
Data Science Advancements in Pandemic and Outbreak Management
Pandemics are disruptive. Thus, there is a need to prepare and plan actions in advance for identifying, assessing, and responding to such events to manage uncertainty and support sustainable livelihood and wellbeing. A detailed assessment of a continuously evolving situation needs to take place, and several aspects must be brought together and examined before the declaration of a pandemic even happens. Various health organizations; crisis management bodies; and authorities at local, national, and international levels are involved in the management of pandemics. There is no better time to revisit current approaches to cope with these new and unforeseen threats. As countries must strike a fine...
Internet of Things and Inter-cooperative Computational Technologies for Collective Intelligence
Over the past two decades, we have witnessed unprecedented innovations in the development of miniaturized electromechanical devices and low-power wireless communication making practical the embedding of networked computational devices into a rapidly widening range of material entities. This trend has enabled the coupling of physical objects and digital information into cyber-physical systems and it is widely expected to revolutionize the way resource computational consumption and provision will occur. Specifically, one of the core ingredients of this vision, the so-called Internet of Things (IoT), demands the provision of networked services to support interaction between conventional IT syst...
Next Generation Data Technologies for Collective Computational Intelligence
This book focuses on next generation data technologies in support of collective and computational intelligence. The book brings various next generation data technologies together to capture, integrate, analyze, mine, annotate and visualize distributed data – made available from various community users – in a meaningful and collaborative for the organization manner. A unique perspective on collective computational intelligence is offered by embracing both theory and strategies fundamentals such as data clustering, graph partitioning, collaborative decision making, self-adaptive ant colony, swarm and evolutionary agents. It also covers emerging and next generation technologies in support o...
Technology Integration Advancements in Distributed Systems and Computing
The functionality of distributed computing systems has advanced greatly in recent months, and staying abreast of the latest research within the field is difficult. Technology Integration Advancements in Distributed Systems and Computing offers a vital compendium of research and developments within the field of distributed computing, giving case studies, frameworks, architectures, and best practices for academics and practitioners alike. With authors from around the world and the latest research from experts within the field, this resource acts as both a reference guide and research handbook.
Machine Learning: Concepts, Methodologies, Tools and Applications
"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe
Global Applications of Pervasive and Ubiquitous Computing
As technology continues to play a vital role in our everyday lives, advancements in human-computer interaction studies embrace ubiquitous computing as a tool for information processing to evolve into the human environment. Global Applications of Pervasive and Ubiquitous Computing provides the global applications and efforts in building and applying pervasive and ubiquitous computer technology. This book provides an essential collection of research on information technology for educators, researchers, and practitioners aiming to advance the practice and understanding of pervasive and ubiquitous applications.
Empowering India Through Digital Literacy (Vol. 1)
Traditionally education is centered on sources such as schools, teachers and print media. The learners reached the information sources by enrolling with schools, teachers and libraries. Prior to the digital era, information was not accessible by the majority of people, and even those accessed were unable to obtain current information with respect to today's context. The modern society wants to know the information as it happens and when it happens, and the world is moving from an information society to a knowledge society. Thus education is given the highest priority and brainpower is becoming the most valuable asset of an organisation. Advances in digital technology have opened up many avenues of learning. Technology has made information accessible / transmittable from anywhere and by / to all groups of people. The higher education landscape is changing rapidly, challenging academic professionals to think critically about their roles in the field.
Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance
Over the last two decades, researchers are looking at imbalanced data learning as a prominent research area. Many critical real-world application areas like finance, health, network, news, online advertisement, social network media, and weather have imbalanced data, which emphasizes the research necessity for real-time implications of precise fraud/defaulter detection, rare disease/reaction prediction, network intrusion detection, fake news detection, fraud advertisement detection, cyber bullying identification, disaster events prediction, and more. Machine learning algorithms are based on the heuristic of equally-distributed balanced data and provide the biased result towards the majority d...
