Bücher der Reihe Studies in Big Data

This book discusses harnessing the real power of cloud computing in optimization problems, presenting state-of-the-art computing paradigms, advances in applications, and challenges concerning both the theories and applications of cloud computing in optimization with a focus on diverse fields like the Internet of Things, fog-assisted cloud computing, and big data. In real life, many problems - ranging from social science to engineering sciences - can be identified as complex optimization problems. Very often these are intractable, and as a result researchers from industry as well as the academic community are concentrating their efforts on developing methods of addressing them. Further, the cloud computing paradigm plays a vital role in many areas of interest, like resource allocation, scheduling, energy management, virtualization, and security, and these areas are intertwined with many optimization problems. Using illustrations and figures, this book offers students and researchers a clear overview of the concepts and practices of cloud computing and its use in numerous complex optimization problems.

Towards Ubiquitous Journalism: Impacts of IoT on News.- From Data Journalism to Robotic Journalism: The Automation of News Processing.- The Technology-Led Narrative Turn.- Journalism Innovation and its Influences in the Future of News: a European Perspective Around Google DNI Fund Initiatives.- Innovating Journalism by Going Back in Time? The Curious Case of Newsletters as a News Source in Belgium.- New Formats for Local Journalism in the Era of Social Media and Big Data: From Transmedia to Storytelling.- Information Visualization and Usability: Tools for Human Comprehension.- Use of 360-Degree Video in Organizational Communication: Case Study of Humanitarian Aid NGOs.- Shared Spaces for News Content Production in Spanish Online Media.- Social Media Guidelines for Journalists in European Public Service Media.- Reinventing Television News: Innovative Formats in a Social Media Environment.- Mediamorphosis of Participation on Television: The News Programmes.- Value and Intelligence of Business Models in Journalism.- New Forms of Journalistic Legitimization in the Digital World.- From Meta-Journalism and Post-Journalism to Total Journalism. 

The book provides readers with an overview of the state of the art in the field of Industry 4.0 and related research advancements. The respective chapters identify and discuss new dimensions of both risk factors and success factors, along with performance metrics that can be employed in future research work. They also discuss a number of real-time issues, problems and applications with corresponding solutions and suggestions. Sharing new theoretical findings, tools and techniques for Industry 4.0, and covering both theoretical and application-oriented approaches, the book offers a valuable asset for newcomers to the field and practicing professionals alike.

The book presents solutions that reduce the transport costs, improve the predictability of prices based on data analytics and the current market conditions, and reduce the number of middle steps and agents between the farmer and the end consumer.

This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare.

Data management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry.

In this book, the editors explain how students enrolled in two digital forensic courses at their institution are exposed to experiential learning opportunities, where the students acquire the knowledge and skills of the subject-matter while also learning how to adapt to the ever-changing digital forensic landscape.

This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud.

The book provides readers with an overview of the state of the art in the field of Industry 4.0 and related research advancements. The respective chapters identify and discuss new dimensions of both risk factors and success factors, along with performance metrics that can be employed in future research work. They also discuss a number of real-time issues, problems and applications with corresponding solutions and suggestions. Sharing new theoretical findings, tools and techniques for Industry 4.0, and covering both theoretical and application-oriented approaches, the book offers a valuable asset for newcomers to the field and practicing professionals alike.

It bridges the gap between multimedia concepts and solutions by providing the current IOT frameworks, their applications in multimedia analysis, the strengths and limitations of the existing methods, and the future directions in multimedia IOT analytics.

This book presents the Recommender System for Improving Customer Loyalty. The data mining techniques employed in the Recommender System allow users to "learn" from the experiences of others, without sharing proprietary information.

This book introduces methods of re-processing images to extract numerical information that can be used to quantify the observables in environmental modelling. The habit of screening datasets leads to the discard of over 90% of the original dataset or images generated in the experiments or procedure.

This book presents a unified framework, based on specialized evolutionary algorithms, for the global induction of various types of classification and regression trees from data. cost-sensitive model trees for financial data or multi-test trees for gene expression data.

The World Wide Web can be considered a huge library that in consequence needs a capable librarian responsible for the classification and retrieval of documents as well as the mediation between library resources and users.

This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare.

Data management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry.

This contributed volume discusses diverse topics to demystify the rapidly emerging and evolving blockchain technology, the emergence of integrated platforms and hosted third-party tools, and the development of decentralized applications for various business domains.

The book presents solutions that reduce the transport costs, improve the predictability of prices based on data analytics and the current market conditions, and reduce the number of middle steps and agents between the farmer and the end consumer.

This book plays a significant role in improvising human life to a great extent. The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. Now, the exemplar model for soft computing is human brain. The use of various techniques of soft computing is nowadays successfully implemented in many domestic, commercial, and industrial applications due to the low-cost and very high-performance digital processors and also the decline price of the memory chips. This is the main reason behind the wider expansion of soft computing techniques and its application areas. These computing methods also play a significant role in the design and optimization in diverse engineering disciplines. With the influence and the development of the Internet of things (IoT) concept, the need for using soft computing techniques has become more significant than ever. In general, soft computing methods are closely similar to biological processes than traditional techniques, which are mostly based on formal logical systems, such as sentential logic and predicate logic, or rely heavily on computer-aided numerical analysis. Soft computing techniques are anticipated to complement each other. The aim of these techniques is to accept imprecision, uncertainties, and approximations to get a rapid solution. However, recent advancements in representation soft computing algorithms (fuzzy logic,evolutionary computation, machine learning, and probabilistic reasoning) generate a more intelligent and robust system providing a human interpretable, low-cost, approximate solution. Soft computing-based algorithms have demonstrated great performance to a variety of areas including multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, biomedical and health informatics, etc. Soft computing approaches such as genetic programming (GP), support vector machineΓÇôfirefly algorithm (SVM-FFA), artificial neural network (ANN), and support vector machineΓÇôwavelet (SVMΓÇôWavelet) have emerged as powerful computational models. These have also shown significant success in dealing with massive data analysis for large number of applications.All the researchers and practitioners will be highly benefited those who are working in field of computer engineering, medicine, biology application, signal processing, and mechanical engineering. This book is a good collection of state-of-the-art approaches for soft computing-based applications to various engineering fields. It is very beneficial for the new researchers and practitioners working in the field to quickly know the best performing methods. They would be able to compare different approaches and can carry forward their research in the most important area of research which has direct impact on betterment of the human life and health.This book is very useful because there is no book in the market which provides a good collection of state-of-the-art methods of soft computing-based models for multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, and biomedical and health informatics.

This book covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies.

The book discusses one of the major challenges in agriculture which is delivery of cultivate produce to the end consumers with best possible price and quality.

This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.

This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.

The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data.

This book presents state-of-the-art research on artificial intelligence and blockchain for future cybersecurity applications.

This book covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies.

This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9¿12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.