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Methodologies and Applications of Computational Statistics for Machine Intelligence
With the field of computational statistics growing rapidly, there is a need for capturing the advances and assessing their impact. Advances in simulation and graphical analysis also add to the pace of the statistical analytics field. Computational statistics play a key role in financial applications, particularly risk management and derivative pricing, biological applications including bioinformatics and computational biology, and computer network security applications that touch the lives of people. With high impacting areas such as these, it becomes important to dig deeper into the subject and explore the key areas and their progress in the recent past. Methodologies and Applications of Computational Statistics for Machine Intelligence serves as a guide to the applications of new advances in computational statistics. This text holds an accumulation of the thoughts of multiple experts together, keeping the focus on core computational statistics that apply to all domains. Covering topics including artificial intelligence, deep learning, and trend analysis, this book is an ideal resource for statisticians, computer scientists, mathematicians, lecturers, tutors, researchers, academic and corporate libraries, practitioners, professionals, students, and academicians. 2021, IGI Global. All rights reserved. -
Neuro-Systemic applications in learning
Neuroscience research deals with the physiology, biochemistry, anatomy and molecular biology of neurons and neural circuits and especially their association with behavior and learning. Of late, neuroscience research is playing a pivotal role in industry, science writing, government program management, science advocacy, and education. In the process of learning as experiencing knowledge, the human brain plays a vital role as the central governing system to map the images of learning in the human brain which may be called educational neuroscience. It provides means to develop a common language and bridge the gulf between educators, psychologists and neuroscientists. The emerging field of educational neuroscience presents opportunities as well as challenges for education, especially when it comes to assess the learning disorders and learning intentions of the students. The most effective learning involves recruiting multiple regions of the brain for the learning task. These regions are associated with such functions as memory, the various senses, volitional control, and higher levels of cognitive functioning. By considering biological factors, research has advanced the understanding of specific learning difficulties, such as dyslexia and dyscalculia. Likewise, neuroscience is uncovering why certain types of learning are more rewarding than others. Of late, a lot of research has gone in the field of neural networks and deep learning. It is worthwhile to consider these research areas in investigating the interplay between the human brain and human formal/natural learning. This book is intended to bring together the recent advances in neuroscience research and their influence on the evolving learning systems with special emphasis on the evolution of a learner-centric framework in outcome based education by taking into cognizance the learning abilities and intentions of the learners. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Deep Learning for Sustainable Agriculture
The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. 2022 Elsevier Inc. All rights reserved. -
Blockchain Technology for Emerging Applications: A Comprehensive Approach
Blockchain Technology for Emerging Applications: A Comprehensive Approach explores recent theories and applications of the execution of blockchain technology. Chapters look at a wide range of application areas, including healthcare, digital physical frameworks, web of-things, smart transportation frameworks, interruption identification frameworks, ballot-casting, architecture, smart urban communities, and digital rights administration. The book addresses the engineering, plan objectives, difficulties, constraints, and potential answers for blockchain-based frameworks. It also looks at blockchain-based design perspectives of these intelligent architectures for evaluating and interpreting real-world trends. Chapters expand on different models which have shown considerable success in dealing with an extensive range of applications, including their ability to extract complex hidden features and learn efficient representation in unsupervised environments for blockchain security pattern analysis. 2022 Elsevier Inc. All rights reserved. -
Cyber-Physical Systems: AI and COVID-19
Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS). The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture. 2022 Elsevier Inc. All rights reserved. -
Data Analytics for Social Microblogging Platforms
Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data. 2023 Elsevier Inc. All rights reserved. -
PUNCHING UP IN STAND-UP COMEDY: Speaking Truth to Power
Punching Up in Stand-Up Comedy explores the new forms, voices and venues of stand-up comedy in different parts of the world and its potential role as a counterhegemonic tool for satire, commentary and expression of identity especially for the disempowered or marginalised. The title brings together essays and perspectives on stand-up and satire from different cultural and political contexts across the world which raise pertinent issues regarding its role in contemporary times, especially with the increased presence of OTT platforms and internet penetration that allows for easy access to this art form. It examines the theoretical understanding of the different aspects of the humour, aesthetics and politics of stand-up comedy, as well as the exploration of race, gender, politics and conflicts, urban culture and LGBTQ+ identities in countries such as Indonesia, Finland, France, Iran, Italy, Morocco, India and the USA. It also asks the question whether, along with contesting and destabilising existing discursive frameworks and identities, a stand-up comic can open up a space for envisaging a new social, cultural and political order? This book will appeal to people interested in performance studies, media, popular culture, digital culture, sociology, digital sociology and anthropology, and English literature. Chapter 9 of this book is freely available as a downloadable Open Access PDF at https://www.taylorfrancis.com under a Creative Commons (CC-BY) 4.0 license. Funded by the University of Helsinki. 2023 selection and editorial matter, Rashi Bhargava and Richa Chilana; individual chapters, the contributors. -
Internet of healthcare things: Machine learning for security and privacy
The book addresses privacy and security issues providing solutions through authentication and authorization mechanisms, blockchain, fog computing, machine learning algorithms, so that machine learning-enabled IoT devices can deliver information concealed in data for fast, computerized responses and enhanced decision-making. The main objective of this book is to motivate healthcare providers to use telemedicine facilities for monitoring patients in urban and rural areas and gather clinical data for further research. To this end, it provides an overview of the Internet of Healthcare Things (IoHT) and discusses one of the major threats posed by it, which is the data security and data privacy of health records. Another major threat is the combination of numerous devices and protocols, precision time, data overloading, etc. In the IoHT, multiple devices are connected and communicate through certain protocols. Therefore, the application of emerging technologies to mitigate these threats and provide secure data communication over the network is discussed. This book also discusses the integration of machine learning with the IoHT for analyzing huge amounts of data for predicting diseases more accurately. Case studies are also given to verify the concepts presented in the book. 2022 John Wiley & Sons Ltd. All rights reserved. -
Deep Learning for Sustainable Agriculture
The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. 2022 Elsevier Inc. All rights reserved. -
The Emerald Handbook of Destination Recovery in Tourism and Hospitality
Featuring a broad geographical range of examples and pan-disciplinary perspectives, The Emerald Handbook of Destination Recovery in Tourism and Hospitality is an essential reference and illuminating guide on developments in the theory and practice of tourism development post-pandemic. 2023 Priyakrushna Mohanty, Anukrati Sharma, James Kennell and Azizul Hassan. -
Blockchain for IoT
Blockchain for IoT provides the basic concepts of Blockchain technology and its applications to varied domains catering to socio-technical fields. It also introduces intelligent Blockchain platforms by way of infusing elements of computational intelligence into Blockchain technology. With the help of an interdisciplinary approach, it includes insights into real-life IoT applications to enable the readers to assimilate the concepts with ease. This book provides a balanced approach between theoretical understanding and practical applications. Features: A self-contained approach to integrating the principles of Blockchain with elements of computational intelligence. A rich and novel foundation of Blockchain technology with reference to the internet of things conjoined with the tenets of artificial intelligence in yielding intelligent Blockchain platforms. Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject. Information presented in an accessible way for research students of computer science and information technology, as well as software professionals who can inherit the much-needed developmental ideas to boost up their computing knowledge on distributed platforms. This book is aimed primarily at undergraduates, postgraduates, and researchers studying Blockchain. 2023 selection and editorial matter, Debarka Mukhopadhyay, Siddhartha Bhattacharyya, Balachandran Krishnan and Sudipta Roy. All rights reserved. -
Crisis management, destination recovery and sustainability: Tourism at a crossroads
The COVID-19 pandemic brought travel to a halt and the global tourism industry has been one of the sectors hit hardest during the pandemic. This book looks at how the tourism industry can enhance its resilience and prepare for future crises more effectively. The book provides insights into the economic, social, geopolitical and environmental implications of the COVID-19 pandemic on the tourism and hospitality industries and the responses in diverse international contexts. It highlights key concepts and includes cases with real-life applications. The book also discusses future research directions in a post-pandemic scenario. This book will be an invaluable resource for practitioners in the areas of tourism and crisis management and for readers to compare and contrast tourism destination recovery and crisis management practices through different research methodologies and settings. 2023 selection and editorial matter, James Kennell, Priyakrushna Mohanty, Anukrati Sharma and Azizul Hassan. All rights reserved. -
Emerging Nanomaterials for Catalysis and Sensor Applications
This book reviews emerging nanomaterials in catalysis and sensors. The catalysis section covers the role of nano-photocatalysts in organic synthesis and health care application, oxidation and sulphoxidation reactions, liquid phase oxidation, hydrogen evolution and environmental remediation. It highlights the correlation of surface properties and catalytic activity of the mesoporous materials. The sensor section discusses the fabrication and development of various electrochemical, chemical, and biosensors. Features: Combines catalysis and sensor applications of nanomaterials, including detailed synthesis techniques of these materials. Explores methods of designing, engineering, and fabricating nanomaterials. Covers material efficiency, their detection limit for sensing different analytes and other properties of the materials. Discusses sustainability of nano materials in the industrial sector. Includes case studies to address the challenges faced by research and development sectors. This book is aimed at researchers and graduate students in Chemical Engineering, Nanochemistry, Water Treatment Engineering and Labs, Industries, Research Labs in Catalysis and Sensors, Environmental Engineering, and Process Engineering. 2023 selection and editorial matter, Anitha Varghese and Gurumurthy Hegde; individual chapters, the contributors. -
Elementary Statistical Methods
This is the first book of two volumes covering the basics of statistical methods and analysis. Significant topics include concepts of research and data analysis, descriptive statistics, probability and distributions, correlation and regression, and statistical inference. The book includes useful examples and exercises as well as relevant case studies for proper implementation of the discussed tools. This book will be a valuable text for undergraduate students of statistics, management, economics, and psychology, wanting to gain basic understanding of statistics and the usage of its various concepts. The Editor(s) (if applicable) and The Author(s). under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Tourism and Hospitality in Asia: Crisis, Resilience and Recovery
This book analyses the ways in which crises, including COVID-19, can be managed within the tourism and hospitality industries in Asia, in ways that support the future of these industries and help to make them more resilient. This book supports efforts to develop a new direction for the tourism and hospitality industry by considering their development holistically in the context of sustainable development. Going further, this book highlights actions to make the tourism system more resilient to external shocks and crises. Readers of this book will get insights into the economic, social, technological, and environmental implications of crises on the tourism and hospitality industry in Asia, including issues within the food and beverage industry in the Asian post-COVID-19 period. This book has three major objectives: to explore the crisis context of Asian tourism and hospitality, to present multiple cases from countries in Asia, and finally to envisage the paths to make the Asian tourism system more resilient, through the discussion of new trends and issues emerging following the pandemic. This book examines the economic, social, environmental, and technological implications of crises on the Asian tourism and hospitality industry and discusses the various ways of managing these crises more efficiently, contributing new knowledge to the industry. In its wider context, this book covers tourism management, crisis management, and destination management. At the more micro level, themes explored include tourism economics, marketing management, hospitality management, food and beverage management and tourism technology. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Physics of Gravitational Waves: Sources and Detection Methods
[No abstract available] -
Analytics Enabled Decision Making
Analytics is changing the landscape of businesses across sectors globally. This has led to the stimulation of interest of scholars and practitioners worldwide in this domain. The emergence of big data, has fanned the usages of machine learning techniques and the acceptance of Analytics Enabled Decision Making. This book provides a holistic theoretical perspective combined with the application of such theories by drawing on the experiences of industry professionals and academicians from around the world. The book discusses several paradigms including pattern mining, clustering, classification, and data analysis to name a few. The main objective of this book is to offer insight into the process of decision-making that is accelerated and made more precise with the help of analytics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Machine Intelligence: Computer Vision and Natural Language Processing
Machines are being systematically empowered to be interactive and intelligent in their operations, offerings. and outputs. There are pioneering Artificial Intelligence (AI) technologies and tools. Machine and Deep Learning (ML/DL) algorithms, along with their enabling frameworks, libraries, and specialized accelerators, find particularly useful applications in computer and machine vision, human machine interfaces (HMIs), and intelligent machines. Machines that can see and perceive can bring forth deeper and decisive acceleration, automation, and augmentation capabilities to businesses as well as people in their everyday assignments. Machine vision is becoming a reality because of advancements in the computer vision and device instrumentation spaces. Machines are increasingly software-defined. That is, vision-enabling software and hardware modules are being embedded in new-generation machines to be self-, surroundings, and situation-aware. Machine Intelligence emphasizes computer vision and natural language processing as drivers of advances in machine intelligence. The book examines these technologies from the algorithmic level to the applications level. It also examines the integrative technologies enabling intelligent applications in business and industry. Features: Motion images object detection over voice using deep learning algorithms Ubiquitous computing and augmented reality in HCI Learning and reasoning in Artificial Intelligence Economic sustainability, mindfulness, and diversity in the age of artificial intelligence and machine learning Streaming analytics for healthcare and retail domains Covering established and emerging technologies in machine vision, the book focuses on recent and novel applications and discusses state-of-the-art technologies and tools. 2024 Taylor & Francis Group, LLC. -
Data Engineering and Data Science: Concepts and Applications
DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the one-stop shop for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesnt need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library. 2023 Scrivener Publishing LLC. -
Natural Language Processing and Information Retrieval: Principles and Applications
This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. This text emphasizes the existing problem domains and possible new directions in natural language processing and information retrieval. It discusses the importance of information retrieval with the integration of machine learning, deep learning, and word embedding. This approach supports the quick evaluation of real-time data. It covers important topics including rumor detection techniques, sentiment analysis using graph-based techniques, social media data analysis, and language-independent text mining. Features: Covers aspects of information retrieval in different areas including healthcare, data analysis, and machine translation. Discusses recent advancements in language- and domain-independent information extraction from textual and/or multimodal data. Explains models including decision making, random walk, knowledge graphs, word embedding, n-grams, and frequent pattern mining. Provides integrated approaches of machine learning, deep learning, and word embedding for natural language processing. Covers latest datasets for natural language processing and information retrieval for social media like Twitter. The text is primarily written for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. 2024 selection and editorial matter, Muskan Garg, Sandeep Kumar and Abdul Khader Jilani Saudagar chapters.