As Web service technologies have matured in recent years, an increasing number of geospatial Web services designed to deal with spatial information over the network have emerged. Geospatial Web Services: Advances in Information Interoperability provides relevant theoretical frameworks and the latest empirical research findings and applications in the area. This book highlights the strategic role of geospatial Web services in a distributed heterogeneous environment and the life cycle of geospatial Web services for building interoperable geospatial applications.

This book gathers selected papers presented at the International Conference on Innovations in Information and Communication Technologies (ICI2CT 2020), held at National University of Singapore, Singapore, during 18-19 December 2020. It presents the works on the intersection of the Computer Science and Communication Engineering. Topics covered in the book include communications engineering, Internet and web technology, computer and information science, artificial intelligence, data science and management, and ICT applications.

For college-level Computer Science courses in Python Basic Programming and Problem Solving in Python As one of the most widely used programming languages in the software industry, Python is desirable to both learn and teach. Introduction to Programming Using Python is designed for students eager to learn about the world of programming. Applicable to a range of skill levels, this First Edition textbook provides students with the tools to harness the powerful syntax of Python and understand how to develop computer programs. The compactly written text leverages highly focused chapters, diving deep into the most significant topics to give students an in-depth (rather than superficial) understanding of the language. Using real-world examples and data, the author illustrates practical usage of Python in a way to which students can relate. The text itself is readable, organised, and informative, discussing main points of each topic first and then addressing the peripheral details. Students learn good programming habits the first time-bringing them in line with the best modern programming practices.

This book provides readers the "big picture" and a comprehensive survey of the domain of big data processing systems. For the past decade, the Hadoop framework has dominated the world of big data processing, yet recently academia and industry have started to recognize its limitations in several application domains and thus, it is now gradually being replaced by a collection of engines that are dedicated to specific verticals (e.g. structured data, graph data, and streaming data). The book explores this new wave of systems, which it refers to as Big Data 2.0 processing systems. After Chapter 1 presents the general background of the big data phenomena, Chapter 2 provides an overview of various general-purpose big data processing systems that allow their users to develop various big data processing jobs for different application domains. In turn, Chapter 3 examines various systems that have been introduced to support the SQL flavor on top of the Hadoop infrastructure and provide competing and scalable performance in the processing of large-scale structured data. Chapter 4 discusses several systems that have been designed to tackle the problem of large-scale graph processing, while the main focus of Chapter 5 is on several systems that have been designed to provide scalable solutions for processing big data streams, and on other sets of systems that have been introduced to support the development of data pipelines between various types of big data processing jobs and systems. Next, Chapter 6 focuses on covering the emerging frameworks and systems in the domain of scalable machine learning and deep learning processing. Lastly, Chapter 7 shares conclusions and an outlook on future research challenges. This new and considerably enlarged second edition not only contains the completely new chapter 6, but also offers a refreshed content for the state-of-the-art in all domains of big data processing over the last years. Overall, the book offers a valuable reference guide for professional, students, and researchers in the domain of big data processing systems. Further, its comprehensive content will hopefully encourage readers to pursue further research on the subject.

Portable Biosensors and Point-of-Care Systems describes the principles, design and applications of a new generation of analytical and diagnostic biomedical devices, characterized by their very small size, ease of use, multi-analytical capabilities and speed to provide handheld and mobile point-of-care (POC) diagnostics. The book is divided in four Parts. Part I is an in-depth analysis of the various technologies upon which portable diagnostic devices and biosensors are built. In Part II, advances in the design and optimization of special components of biosensor systems and handheld devices are presented. In Part III, a wide scope of applications of portable biosensors and handheld POC devices is described, ranging from the support of primary healthcare to food and environmental safety screening. Diverse topics are covered, including counterterrorism, travel medicine and drug development. Finally, Part IV of the book is dedicated to the presentation of commercially available products including a review of the products of point-of-care in-vitro-diagnostics companies, a review of technologies which have achieved a high Technology Readiness Level, and a special market case study of POC infusion systems combined with intelligent patient monitoring. This book is essential reading for researchers and experts in the healthcare diagnostic and analytical sector, and for electronics and material engineers working on portable sensors.

Semantic Web technologies and applications have become increasingly important as new methods for understanding and expressing information are discovered. Progressive Concepts for Semantic Web Evolution: Applications and Developments unites research on essential theories, models, and applications of Semantic Web research. Contributions focus on mobile ontologies and agents, fuzzy databases, and new approaches to retrieval and evaluation in the Semantic Web.

This book provides insights into the state of the art of digital cultural heritage using computer graphics, image processing, computer vision, visualization and reconstruction, virtual and augmented reality and serious games. It aims at covering the emergent approaches for digitization and preservation of Cultural Heritage, both in its tangible and intangible facets. Advancements in Digital Cultural Heritage research have been abundant in recent years covering a wide assortment of topics, ranging from visual data acquisition, pre-processing, classification, analysis and synthesis, 3D modelling and reconstruction, semantics and symbolic representation, metadata description, repository and archiving, to new forms of interactive and personalized presentation, visualization and immersive experience provision via advanced computer graphics, interactive virtual and augmented environments, serious games and digital storytelling. Different aspects pertaining to visual computing with regard to tangible (books, images, paintings, manuscripts, uniforms, maps, artefacts, archaeological sites, monuments) and intangible (e.g. dance and performing arts, folklore, theatrical performances) cultural heritage preservation, documentation, protection and promotion are covered, including rendering and procedural modelling of cultural heritage assets, keyword spotting in old documents, drone mapping and airborne photogrammetry, underwater recording and reconstruction, gamification, visitor engagement, animated storytelling, analysis of choreographic patterns, and many more. The book brings together and targets researchers from the domains of computing, engineering, archaeology and the arts, and aims at underscoring the potential for cross-fertilization and collaboration among these communities.

Software development and information systems design have a unique relationship, but are often discussed and studied independently. However, meticulous software development is vital for the success of an information system. Software Development Techniques for Constructive Information Systems Design focuses the aspects of information systems and software development as a merging process. This reference source pays special attention to the emerging research, trends, and experiences in this area which is bound to enhance the reader s understanding of the growing and ever-adapting field. Academics, researchers, students, and working professionals in this field will benefit from this publication s unique perspective.

Web portals continue to play a vital role in businesses by maintaining and extending business opportunities, as well as providing e-services to customers. Web Portal Design, Implementation, Integration, and Optimization discusses the challenges faced in building web services and integrating applications in order to reach the successful benefits web portals bring to an organisation. This collection of research aims to be a resource for researchers, developers, and industry practitioners involved in the technological, business, organisational and social dimensions of web portals.

This 2 volume-set of IFIP AICT 583 and 584 constitutes the refereed proceedings of the 16th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2020, held in Neos Marmaras, Greece, in June 2020.* The 70 full papers and 5 short papers presented were carefully reviewed and selected from 149 submissions. They cover a broad range of topics related to technical, legal, and ethical aspects of artificial intelligence systems and their applications and are organized in the following sections: Part I: classification; clustering - unsupervised learning -analytics; image processing; learning algorithms; neural network modeling; object tracking - object detection systems; ontologies - AI; and sentiment analysis - recommender systems. Part II: AI ethics - law; AI constraints; deep learning - LSTM; fuzzy algebra - fuzzy systems; machine learning; medical - health systems; and natural language. *The conference was held virtually due to the COVID-19 pandemic.

The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book. The authors emphasize the following: (1) the scalability over a large malware corpus; (2) the resiliency to common obfuscation techniques; (3) the portability over different platforms and architectures. First, the authors propose an approximate fingerprinting technique for android packaging that captures the underlying static structure of the android applications in the context of bulk and offline detection at the app-market level. This book proposes a malware clustering framework to perform malware clustering by building and partitioning the similarity network of malicious applications on top of this fingerprinting technique. Second, the authors propose an approximate fingerprinting technique that leverages dynamic analysis and natural language processing techniques to generate Android malware behavior reports. Based on this fingerprinting technique, the authors propose a portable malware detection framework employing machine learning classification. Third, the authors design an automatic framework to produce intelligence about the underlying malicious cyber-infrastructures of Android malware. The authors then leverage graph analysis techniques to generate relevant intelligence to identify the threat effects of malicious Internet activity associated with android malware. The authors elaborate on an effective android malware detection system, in the online detection context at the mobile device level. It is suitable for deployment on mobile devices, using machine learning classification on method call sequences. Also, it is resilient to common code obfuscation techniques and adaptive to operating systems and malware change overtime, using natural language processing and deep learning techniques. Researchers working in mobile and network security, machine learning and pattern recognition will find this book useful as a reference. Advanced-level students studying computer science within these topic areas will purchase this book as well.

Free/libre open source software (FLOSS) ecosystems such as Linux have had a tremendous impact on computing and society and have captured the attention of businesses, researchers, and policy makers. Research on FLOSS has been ongoing for almost two decades. From an economic perspective, the most common topics involve motivation and organization. As commercial participation in FLOSS has become common, the question of how to combine FLOSS practice with commercial practice has been the subject of research, particularly with a view to understanding how to ensure sustainability of the ecosystem. This book is based on a Shonan meeting on FLOSS ecosystem sustainability held in June 2017. The meeting brought together a blend of established and young researchers who were actively studying the FLOSS phenomenon. These researchers were drawn from a variety of disciplines including software engineering, human computer interaction, information systems, computer-supported cooperative work, data mining, cognitive science, psychology, operations research, and management. Industry practitioners who were active in the FLOSS space also participated. This book presents the results of discussion on fundamental questions related to the impact and sustainability of FLOSS ecosystems, including: * How does an ecosystem form? How do different stakeholders work together to form a community that develops and maintains valuable and freely available software, and how does an ecosystem with millions of repositories and developers operate given the lack of centralized planning? * How does an ecosystem evolve in response to the environment as technology and needs evolve over time? * How do newcomers learn the protocols and practices of an ecosystem? How would they sustain the ecosystem? What is the relationship between people and ecosystem sustainability?

As today's world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.