This book explores categories of applications and driving factors surrounding the Smart City phenomenon. The contributing authors provide perspective on the Smart Cities, covering numerous applications and classes of applications. The book uses a top-down exploration of the driving factors in Smart Cities, by including focal areas including "Smart Healthcare," "Public Safety & Policy Issues," and "Science, Technology, & Innovation." Contributors have direct and substantive experience with important aspects of Smart Cities and discuss issues with technologies & standards, roadblocks to implementation, innovations that create new opportunities, and other factors relevant to emerging Smart City infrastructures. Features an exploration of Smart City issues and solutions from a variety of stakeholders in the evolving field Presents conversational, nuanced, and forward thinking perspectives on Smart Cities, their implications, limitations, obstacles, and opportunities Includes contributions from industry insiders who have direct, relevant experience with their respective subjects as well as positioning and corporate stature

As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.

Service delivery in the digital era is all about bringing together innovative ideas from various stakeholders in the private, public, and civil sectors to meet customer expectations. Like any business, government public service entities must provide public service delivery to their customers in an age that is heavily influenced by technological advancements. Information Systems Strategic Planning for Public Service Delivery in the Digital Era is an essential reference source that discusses issues related to public service delivery in the digital era and the degree to which governments may take advantage of the transformational potential of ICT to move towards seamless government, particularly for improving service delivery, democratic responsiveness, and public outreach. The book also provides a pragmatic framework for government entities to define their information systems strategic plan (ISSP), guiding the reader in a step-by-step practical description of the various technical concepts, current and future technology trends, and implementation considerations for formulating their ISSP to ensure the maximum gain from public service delivery. Including research on topics such as human capital, knowledge economy, and block chain technology, this book is ideally designed for academicians, public administrators, government officials, IT consultants.

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.

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.

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.

"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.

Databases are designed to support data storage, processing, and retrieval activities related to data management. The use of databases in various applications has resulted in an enormous wealth of data, which populates many types of databases around the world. Advanced Database Query Systems: Techniques, Applications and Technologies focuses on technologies and methodologies of database queries, XML and metadata queries, and applications of database query systems, aiming at providing a single account of technologies and practices in advanced database query systems. This book provides the state of the art information for academics, researchers and industry practitioners who are interested in the study, use, design and development of advanced and emerging database queries with ultimate aim of building competencies for exploiting the opportunities of the data and knowledge society.

a) Provides basic concepts of Natural Language Processing for getting started from scratch. b) Introduces advanced concepts for scaling, deep learning and real-world issues seen in the industry. c) Provides applications of Natural Language Processing over a diverse set of 15 industry verticals. d) Shares practical implementation including Python code, tools and techniques for a variety of Natural Language Processing applications and industrial products for a hands-on experience. e) Gives readers a sense of all there is to build successful Natural Language Processing projects: the concepts, applications, opportunities and hands-on material.

As it is with building a house, most of the work necessary to build a data warehouse is neither visible nor obvious when looking at the completed product. While it may be easy to plan for a data warehouse that incorporates all the right concepts, taking the steps needed to create a warehouse that is as functional and user-friendly as it is theoretically sound, is not especially easy. That's the challenge that Building and Maintaininga Data Warehouse answers. Based on a foundation of industry-accepted principles, this work provides an easy-to-follow approach that is cohesive and holistic. By offering the perspective of a successful data warehouse, as well as that of a failed one, this workdetails those factors that must be accomplished and those that are best avoided. Organized to logically progress from more general to specific information, this valuable guide: Presents areas of a data warehouse individually and in sequence, showing how each piece becomes a working part of the whole Examines the concepts and principles that are at the foundation of every successful data warehouse Explains how to recognize and attend to problematic gaps in an established data warehouse Provides the big picture perspective that planners and executives require Those considering the planning and creation of a data warehouse, as well as those who've already built one will profit greatly from the insights garnered by the author during his years of creating and gathering information on state-of-the-art data warehouses that are accessible, convenient, and reliable.

Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management focuses on the challenges of distributed systems imposed by data intensive applications and on the different state-of-the-art solutions proposed to overcome such challenges. Providing hints on how to manage low-level data handling issues when performing data intensive distributed computing, this publication is ideal for scientists, researchers, engineers, and application developers, alike. With the knowledge of the correct data management techniques for their applications, readers will be able to focus on their primary goal, assured that their data management needs are handled reliably and efficiently.

Advances in Computers remains at the forefront in presenting the new developments in the ever-changing field of information technology. Since 1960, Advances in Computers has chronicled the constantly shifting theories and methods of this technology that greatly shape our lives today.
"Information Repositories" focuses on the use of large data repositories to store and retrieve information.
This series is an invaluable addition to any university course in computer technology, as well as finding itself at home on the bookshelf of industrial practitioners.
* Includes in-depth surveys and tutorials on advances in Computer Technology. * Features the work of well-known authors and researchers in the field.
* Provides a broad overview of important developments.
* Contains extensive bibliographies.

Cloud technologies have revolutionized the way we store information and perform various computing tasks. With the rise of this new technology, the ability to secure information stored on the cloud becomes a concern. The Handbook of Research on Securing Cloud-Based Databases with Biometric Applications explores the latest innovations in promoting cloud security through human authentication techniques. Exploring methods of access by identification, including the analysis of facial features, fingerprints, DNA, dental characteristics, and voice patterns, this publication is designed especially for IT professionals, academicians, and upper-level students seeking current research surrounding cloud security.

This book provides an insight into recent technological trends and innovations in solutions and platforms to improve mobility of visually impaired people. The authors' goal is to help to contribute to the social and societal inclusion of the visually impaired. The book's topics include, but are not limited to, obstacle detection systems, indoor and outdoor navigation, transportation sustainability systems, and hardware/devices to aid visually impaired people. The book has a strong focus on practical applications tested in a real environment. Applications include city halls, municipalities, and companies that must keep up to date with recent trends in platforms, methodologies and technologies to promote urban mobility. Also discuss are broader realms including education, health, electronics, tourism, and transportation. Contributors include a variety of researchers and practitioners around the world.

Within a given enterprise, database management involves the monitoring, administration, and maintenance of the databases, which constantly change with new technologies and new forms of data. Cross-Disciplinary Models and Applications of Database Management: Advancing Approaches is an updated look at the latest tools and technology within the burgeoning field of database management. Perfect for the network administrator, technician, information technology specialist or consultant, or for academics and students, this volume presents the latest the field has to offer by way of cases and new research. As database languages, models, and systems change, it s vital for practitioners within the field to stay abreast of the latest research and methods being used around the world, and this book offers the most current advances available.

There is a large increase in the amount of information available on World Wide Web and also in number of online databases. This information abundance increases the complexity of locating relevant information. Such a complexity drives the need for improved and intelligent systems for search and information retrieval. Intelligent Agents are currently used to improve the search and retrieval information on World Wide Web. The use of existing search and retrieval engines with the addition of intelligent agents allows a more comprehensive search with a performance that can be measured. Intelligent Agents for Mining and Information Retrieval discusses the foundation as well as the pratical side of intelligent agents and their theory and applications for web data mining and information retrieval. The book can used for researchers at the undergraduate and post-graduate levels as well as a reference of the state-of-art for cutting edge researchers.

This handbook is organized under three major parts. The first part of this handbook deals with multimedia security for emerging applications. The chapters include basic concepts of multimedia tools and applications, biological and behavioral biometrics, effective multimedia encryption and secure watermarking techniques for emerging applications, an adaptive face identification approach for android mobile devices, and multimedia using chaotic and perceptual hashing function. The second part of this handbook focuses on multimedia processing for various potential applications. The chapter includes a detail survey of image processing based automated glaucoma detection techniques and role of de-noising, recent study of dictionary learning based image reconstruction techniques for analyzing the big medical data, brief introduction of quantum image processing and it applications, a segmentation-less efficient Alzheimer detection approach, object recognition, image enhancements and de-noising techniques for emerging applications, improved performance of image compression approach, and automated detection of eye related diseases using digital image processing. The third part of this handbook introduces multimedia applications. The chapter includes the extensive survey on the role of multimedia in medicine and multimedia forensics classification, a finger based authentication system for e-health security, analysis of recently developed deep learning techniques for emotion and activity recognition. Further, the book introduce a case study on change of ECG according to time for user identification, role of multimedia in big data, cloud computing, the Internet of things (IoT) and blockchain environment in detail for real life applications. This handbook targets researchers, policy makers, programmers and industry professionals in creating new knowledge for developing efficient techniques/framework for multimedia applications. Advanced level students studying computer science, specifically security and multimedia will find this book useful as a reference.

Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.
* Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes.
* Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy.
* Is written by one of the original developers of data profiling technology.
* Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets.