Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 discusses how the role of recent technologies applied to health settings can help fight virus outbreaks. Moreover, it provides guidelines on how governments and institutions should prepare and quickly respond to drastic situations using technology to support their communities in order to maintain life and functional as efficiently as possible. The book discusses topics such as AI-driven histopathology analysis for COVID-19 diagnosis, bioinformatics for subtype rational drug design, deep learning-based treatment evaluation and outcome prediction, sensor informatics for monitoring infected patients, and machine learning for tracking and prediction models. In addition, the book presents AI solutions for hospital management during an epidemic or pandemic, along with real-world solutions and case studies of successful measures to support different types of communities. This is a valuable source for medical informaticians, bioinformaticians, clinicians and other healthcare workers and researchers who are interested in learning more on how recently developed technologies can help us fight and minimize the effects of global pandemics.

The ubiquity of technology has not only brought the need for computer knowledge to every aspect of the modern business world; it has also increased our need to safely store the data we are now creating at a rate never experienced before. Delivery and Adoption of Cloud Computing Services in Contemporary Organizations brings together the best practices for storing massive amounts of data. Highlighting ways cloud services can work effectively in production and in real time, this book is an essential reference source for professionals and academics of various disciplines, such as computer science, consulting, information technology, information and communication sciences, healthcare, and finance.

This Springer book provides a perfect platform to submit chapters that discuss the prospective developments and innovative ideas in artificial intelligence and machine learning techniques in the diagnosis of COVID-19. COVID-19 is a huge challenge to humanity and the medical sciences. So far as of today, we have been unable to find a medical solution (Vaccine). However, globally, we are still managing the use of technology for our work, communications, analytics, and predictions with the use of advancement in data science, communication technologies (5G & Internet), and AI. Therefore, we might be able to continue and live safely with the use of research in advancements in data science, AI, machine learning, mobile apps, etc., until we can find a medical solution such as a vaccine. We have selected eleven chapters after the vigorous review process. Each chapter has demonstrated the research contributions and research novelty. Each group of authors must fulfill strict requirements.

This book is a collection of selected papers presented at the First International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC), held as an online conference due to COVID-19 (initially to be held in Macao, Special Administration Region (SAR) of China), during September 15-17, 2020. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It brings multi-disciplines together on IIoT, data science, cloud computing, software engineering approaches to design, development, testing and quality of products and services.

This Springer book provides a perfect platform to submit chapters that discuss the prospective developments and innovative ideas in artificial intelligence and machine learning techniques in the diagnosis of COVID-19. COVID-19 is a huge challenge to humanity and the medical sciences. So far as of today, we have been unable to find a medical solution (Vaccine). However, globally, we are still managing the use of technology for our work, communications, analytics, and predictions with the use of advancement in data science, communication technologies (5G & Internet), and AI. Therefore, we might be able to continue and live safely with the use of research in advancements in data science, AI, machine learning, mobile apps, etc., until we can find a medical solution such as a vaccine. We have selected eleven chapters after the vigorous review process. Each chapter has demonstrated the research contributions and research novelty. Each group of authors must fulfill strict requirements.

This book is a collection of selected papers presented at the First International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC), held as an online conference due to COVID-19 (initially to be held in Macao, Special Administration Region (SAR) of China), during September 15-17, 2020. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It brings multi-disciplines together on IIoT, data science, cloud computing, software engineering approaches to design, development, testing and quality of products and services.

This book constitutes the refereed post-conference proceedings of the Interdisciplinary Workshop on Trust, Identity, Privacy, and Security in the Digital Economy, DETIPS 2020; the First International Workshop on Dependability and Safety of Emerging Cloud and Fog Systems, DeSECSys 2020; Third International Workshop on Multimedia Privacy and Security, MPS 2020; and the Second Workshop on Security, Privacy, Organizations, and Systems Engineering, SPOSE 2020; held in Guildford, UK, in September 2020, in conjunction with the 25th European Symposium on Research in Computer Security, ESORICS 2020. A total of 42 papers was submitted. For the DETIPS Workshop 8 regular papers were selected for presentation. Topics of interest address various aspect of the core areas in relation to digital economy. For the DeSECSys Workshop 4 regular papers are included. The workshop had the objective of fostering collaboration and discussion among cyber-security researchers and practitioners to discuss the various facets and trade-o s of cyber security. In particular, applications, opportunities and possible shortcomings of novel security technologies and their integration in emerging application domains. For the MPS Workshop 4 regular papers are presented which cover topics related to the security and privacy of multimedia systems of Internet-based video conferencing systems (e.g., Zoom, Microsoft Teams, Google Meet), online chatrooms (e.g., Slack), as well as other services to support telework capabilities. For the SPOSE Workshop 3 full papers were accepted for publication. They reflect the discussion, exchange, and development of ideas and questions regarding the design and engineering of technical security and privacy mechanisms with particular reference to organizational contexts.

Enterprise security is an important area since all types of organizations require secure and robust environments, platforms and services to work with people, data and computing applications. The book provides selected papers of the Second International Workshop on Enterprise Security held in Vancouver, Canada, November 30-December 3, 2016 in conjunction with CloudCom 2015. The 11 papers were selected from 24 submissions and provide a comprehensive research into various areas of enterprise security such as protection of data, privacy and rights, data ownership, trust, unauthorized access and big data ownership, studies and analysis to reduce risks imposed by data leakage, hacking and challenges of Cloud forensics.

This book gives an overview of Cloud Computing (CC) and presents a literature review explaining the development of CC. Selected frameworks are discussed, including those suitable for this research. Technical and organisational challenges for CC are also identified. This book focuses on organisational challenges and recommendations to address organisational challenges. To help organisations achieve good Cloud design, deployment and services, there is a need for the proposal and development of a framework, the Cloud Computing Business Framework (CCBF), which explains how three research questions are connected together. The CCBF is a conceptual and an architectural framework to be validated through modelling, simulation, experiments and hybrid case studies. The architecture of the CCBF is presented to explain how different key areas can relate to each other and fit into the framework. Results of case studies, simulations, modelling and experiments are used to validate CCBF and are discussed in details which collaborators find results of CCBF useful for their Cloud adoption. Selected results have been published including four journals and one book chapter. Finally, future work plans are proposed and followed-up steps are explained.