This book includes selected papers presented at International Conference on Computational Intelligence, Data Science and Cloud Computing (IEM-ICDC) 2020, organized by the Department of Information Technology, Institute of Engineering & Management, Kolkata, India, during 25-27 September 2020. It presents substantial new research findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.

This present book discusses the application of the methods to astrophysical data from different perspectives. In this book, the reader will encounter interesting chapters that discuss data processing and pulsars, the complexity and information content of our universe, the use of tessellation in astronomy, characterization and classification of astronomical phenomena, identification of extragalactic objects, classification of pulsars and many other interesting chapters. The authors of these chapters are experts in their field and have been carefully selected to create this book so that the authors present to the community a representative publication that shows a unique fusion of artificial intelligence and astrophysics.

This book provides a broad overview of essential features of subsurface environmental modelling at the science-policy interface, offering insights into the potential challenges in the field of subsurface flow and transport, as well as the corresponding computational modelling and its impact on the area of policy- and decision-making. The book is divided into two parts: Part I presents models, methods and software at the science-policy interface. Building on this, Part II illustrates the specifications using detailed case studies of subsurface environmental modelling. It also includes a systematic research overview and discusses the anthropogenic use of the subsurface, with a particular focus on energy-related technologies, such as carbon sequestration, geothermal technologies, fluid and energy storage, nuclear waste disposal, and unconventional oil and gas recovery.

This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

Data mining is still a relatively young field, expanding at the rate of technology while advancing tools and techniques for gaining knowledge, finding patterns, and managing databases. Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends is an updated look at the state of technology in the field of data mining and analytics. As processor speeds, database size, network capabilities, artificial intelligence, and most fields of hardware and software continue to improve at a staggering rate of increased capability and pace, it is vital for practitioners to stay abreast of the current issues and research in the field. This volume is perfect for IT specialists, data analysts, practitioners and academics alike, offering the latest technological, analytical, ethical, and commercial perspectives on topics in data mining.

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 machine-firefly algorithm (SVM-FFA), artificial neural network (ANN), and support vector machine-wavelet (SVM-Wavelet) 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.

"Contemporary Issues in Database Design and Information" presents the latest research ideas and topics on databases and software development. The chapters in this innovative publication provide a representation of topnotch research in all areas of the database and information systems development.

The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used. Application of hybrid neuro-fuzzy networks for analyzing stock markets was presented. The analysis of big historical, economic and physical data revealed the hidden Fibonacci pattern about the course of systemic world conflicts and their connection with the Kondratieff big economic cycles and the Schwabe-Wolf solar activity cycles. The book is useful for system analysts and practitioners working with complex systems in various spheres of human activity.

The book proposes new technologies and discusses innovative solutions to various problems in the field of communication, circuits, and systems, as reflected in high-quality papers presented at International Conference on Communication, Circuits, and Systems (IC3S 2020) held at KIIT, Bhubaneswar, India from 16 - 18 October 2020. It brings together new works from academicians, scientists, industry professionals, scholars, and students together to exchange research outcomes and open up new horizons in the areas of signal processing, communications, and devices.

This book proposes new control and protection schemes to improve the overall stability and security of future wide-area power systems. It focuses on the high penetration levels of renewable energy sources and distributed generation, particularly with the trend towards smart grids. The control methods discussed can improve the overall stability in normal and abnormal operation conditions, while the protection methods presented can be used to ensure the secure operation of systems under most severe contingencies. Presenting stability, security, and protection methods for power systems in one concise volume, this book takes the reader on a journey from concepts and fundamentals to the latest and future trends in each topic covered, making it an informative and intriguing read for researchers, graduate students, and practitioners alike.

With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals.

This book explores the main elements of e-Democracy, the term normally used to describe the implementation of democratic government processes by electronic means. It provides insights into the main technological and human issues regarding governance, government, participation, inclusion, empowerment, procurement and, last but not least, ethical and privacy issues. Its main aim is to bridge the gap between technological solutions, their successful implementation, and the fruitful utilization of the main set of e-Services totally or partially delivered by governments or non-government organizations. Today, various parameters actively influence e-Services' success or failure: cultural aspects, organisational issues, bureaucracy and workflows, infrastructure and technology in general, user habits, literacy, capacity or merely interaction design. This includes having a significant population of citizens who are willing and able to adopt and use online services; as well as developing the managerial and technical capability to implement applications that meet citizens' needs. This book helps readers understand the mutual dependencies involved; further, a selection of success stories and failures, duly commented on, enables readers to identify the right approach to innovation in governmental e-Services. With its balanced humanistic and technological approach, the book mainly targets public authorities, decision-makers, stakeholders, solution developers, and graduate students.

Encompassing a broad range of forms and sources of data, this textbook introduces data systems through a progressive presentation. Introduction to Data Systems covers data acquisition starting with local files, then progresses to data acquired from relational databases, from REST APIs and through web scraping. It teaches data forms/formats from tidy data to relationally defined sets of tables to hierarchical structure like XML and JSON using data models to convey the structure, operations, and constraints of each data form. The starting point of the book is a foundation in Python programming found in introductory computer science classes or short courses on the language, and so does not require prerequisites of data structures, algorithms, or other courses. This makes the material accessible to students early in their educational career and equips them with understanding and skills that can be applied in computer science, data science/data analytics, and information technology programs as well as for internships and research experiences. This book is accessible to a wide variety of students. By drawing together content normally spread across upper level computer science courses, it offers a single source providing the essentials for data science practitioners. In our increasingly data-centric world, students from all domains will benefit from the "data-aptitude" built by the material in this book.

The book presents papers from the 6th International Conference on Big Data and Cloud Computing Challenges (ICBCC 2019), held at the University of Missouri, Kansas City, USA, on September 9 and 10, 2019 and organized in collaboration with VIT Chennai. The book includes high-quality, original research on various aspects of big data and cloud computing, offering perspectives from the industrial and research communities on how to address the current challenges in the field. As such it is a valuable reference resource for researchers and practitioners in academia and industry.

This book highlights the latest advancements in the use of automated systems in the design, construction, operation and future of the built environment and its occupants. It considers how the use of automated decision-making frameworks, artificial intelligence and other technologies of automation are presently impacting the practice of architects, engineers, project managers and contractors, and articulates the near future changes to workflows, legal frameworks and the wider AEC industry. This book surveys and compiles the use of city apps, robots that operate buildings and fabricate structural elements, 3D printing, drones, sensors, algorithms, and advanced prefabricated modules. The book also contributes to the growing literature on smart cities, and explores the impacts on data privacy and data sovereignty that arise through the use of sensors, digital twins and intelligent transport systems. It provides a useful reference for further research and development in the area of automation in design and construction to architects, engineers, project managers, superintendents and construction lawyers, contractors, policy makers, and students.

Corporations accumulate a lot of valuable data and knowledge over time, but storing and maintaining this data can be a logistic and financial headache for business leaders and IT specialists. Uncovering Essential Software Artifacts through Business Process Archaeology introduces an emerging method of software modernisation used to effectively manage legacy systems and company operations supported by such systems. This book presents methods, techniques, and new trends on business process archaeology as well as some industrial success stories. Business experts, professionals, and researchers working in the field of information and knowledge management will use this reference source to efficiently and effectively implement and utilise business knowledge.

Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today's modern world. New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Addresses different scenarios when finding complex relationships in spatiotemporal data by modeling them as graphs, giving readers a comprehensive synopsis on two successful partition-based algorithms designed by the authors.

Electronic participation is an emerging and growing research area that makes use of internet solutions to enhance citizens' participation in government processes in order to provide a fair and efficient society. This book examines recommender-system technologies and voting advice applications as tools to enable electronic citizen participation during election campaigns. Further, making use of fuzzy classification, it provides an evaluation framework for eParticipation. A dynamic voting advice application developed for the 2017 Ecuador national election serves as a real-world case study to introduce readers to the practical implementation and evaluation issues. The book concludes with a comprehensive analysis of the 2017 election project based on altmetrics, Google Analytics and statistics from the case study.

This book contains selected papers presented at the 15th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, held in Maribor, Slovenia, in September 2020.*The 13 full papers included in this volume were carefully reviewed and selected from 21 submissions. Also included is a summary paper of a tutorial. As in previous years, one of the goals of the IFIP Summer School was to encourage the publication of thorough research papers by students and emerging scholars. The papers combine interdisciplinary approaches to bring together a host of perspectives, such as technical, legal, regulatory, socio-economic, social or societal, political, ethical, anthropological, philosophical, or psychological perspectives. *The summer school was held virtually.

This edited book presents scientific results of the International Semi-Virtual Workshop on Data Science and Digital Transformation in the Fourth Industrial Revolution (DSDT 2020) which was held on October 15, 2020, at Soongsil University, Seoul, Korea. The aim of this workshop was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The workshop organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 17 of the conference's most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.

This book provides a survey on research, development, and trends in innovative computing in communications engineering and computer science. It features selected and expanded papers from the EAI International Conference on Computer Science and Engineering 2018 (COMPSE 2018), with contributions by top global researchers and practitioners in the field. The content is of relevance to computer science graduates, researchers and academicians in computer science and engineering. The authors discuss new technologies in computer science and engineering that have reduced the dimension of data coverage worldwide, reducing the gaps and coverage of domains globally. They discuss how these advances have also contributed to strength in prediction, analysis, and decision in the areas such as Technology, Management, Social Computing, Green Computing, and Telecom. Contributions show how nurturing the research in technology and computing is essential to finding the right pattern in the ocean of data. Focuses on research areas of innovative computing and its application in engineering and technology; Includes contributions from researchers in computing and engineering from around the world; Features selected and expanded papers from EAI International Conference on Computer Science and Engineering 2018 (COMPSE 2018).

This book features a collection of high-quality research papers presented at the International Conference on Intelligent and Cloud Computing (ICICC 2019), held at Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India, on December 20, 2019. Including contributions on system and network design that can support existing and future applications and services, it covers topics such as cloud computing system and network design, optimization for cloud computing, networking, and applications, green cloud system design, cloud storage design and networking, storage security, cloud system models, big data storage, intra-cloud computing, mobile cloud system design, real-time resource reporting and monitoring for cloud management, machine learning, data mining for cloud computing, data-driven methodology and architecture, and networking for machine learning systems.