Continual advancements in web technology have highlighted the need for formatted systems that computers can utilize to easily read and sift through the hundreds of thousands of data points across the internet. Therefore, having the most relevant data in the least amount of time to optimize the productivity of users becomes a priority. Semantic Web Science and Real-World Applications provides emerging research exploring the theoretical and practical aspects of semantic web science and real-world applications within the area of big data. Featuring coverage on a broad range of topics such as artificial intelligence, social media monitoring, and microblogging recommendation systems, this book is ideally designed for IT consultants, academics, professionals, and researchers of web science seeking the current developments, requirements and standards, and technology spaces presented across academia and industries.

Cyber-attacks are rapidly becoming one of the most prevalent issues globally, and as they continue to escalate, it is imperative to explore new approaches and technologies that help ensure the security of the online community. Beyond cyber-attacks, personal information is now routinely and exclusively housed in cloud-based systems. The rising use of information technologies requires stronger information security and system procedures to reduce the risk of information breaches. Advanced Methodologies and Technologies in System Security, Information Privacy, and Forensics presents emerging research and methods on preventing information breaches and further securing system networks. While highlighting the rising concerns in information privacy and system security, this book explores the cutting-edge methods combatting digital risks and cyber threats. This book is an important resource for information technology professionals, cybercrime researchers, network analysts, government agencies, business professionals, academicians, and practitioners seeking the most up-to-date information and methodologies on cybercrime, digital terrorism, network security, and information technology ethics.

This book differs from traditional numerical analysis texts in that it focuses on the motivation and ideas behind the algorithms presented rather than on detailed analyses of them. It presents a broad overview of methods and software for solving mathematical problems arising in computational modeling and data analysis, including proper problem formulation, selection of effective solution algorithms, and interpretation of results. In the 20 years since its original publication, the modern, fundamental perspective of this book has aged well, and it continues to be used in the classroom. This Classics edition has been updated to include pointers to Python software and the Chebfun package, expansions on barycentric formulation for Lagrange polynomial interpretation and stochastic methods, and the availability of about 100 interactive educational modules that dynamically illustrate the concepts and algorithms in the book. Scientific Computing: An Introductory Survey, Second Edition is intended as both a textbook and a reference for computationally oriented disciplines that need to solve mathematical problems.

Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time. In the first volume of this comprehensive two-volume handbook, the authors present several methodologies to support Big Data analytics including database management, processing frameworks and architectures, data lakes, query optimization strategies, towards real-time data processing, data stream analytics, Fog and Edge computing, and Artificial Intelligence and Big Data. The second volume is dedicated to a wide range of applications in secure data storage, privacy-preserving, Software Defined Networks (SDN), Internet of Things (IoTs), behaviour analytics, traffic predictions, gender based classification on e-commerce data, recommender systems, Big Data regression with Apache Spark, visual sentiment analysis, wavelet Neural Network via GPU, stock market movement predictions, and financial reporting. The two-volume work is aimed at providing a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data analytics.

Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.

This volume features an extensive account of both research and expository papers in a wide area of engineering and mathematics and its various applications.Topics treated within this book include optimization of control points, game theory, equilibrium points, algorithms, Cartan matrices, integral inequalities, Volterra integro-differential equations, Caristi-Kirk theorems, Laplace type integral operators, etc.This useful reference text benefits graduate students, beginning research engineers and mathematicians as well as established researchers in these domains.

Wireless sensor networks have gained significant attention industrially and academically due to their wide range of uses in various fields. Because of their vast amount of applications, wireless sensor networks are vulnerable to a variety of security attacks. The protection of wireless sensor networks remains a challenge due to their resource-constrained nature, which is why researchers have begun applying several branches of artificial intelligence to advance the security of these networks. Research is needed on the development of security practices in wireless sensor networks by using smart technologies. Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks provides emerging research exploring the theoretical and practical advancements of security protocols in wireless sensor networks using artificial intelligence-based techniques. Featuring coverage on a broad range of topics such as clustering protocols, intrusion detection, and energy harvesting, this book is ideally designed for researchers, developers, IT professionals, educators, policymakers, practitioners, scientists, theorists, engineers, academicians, and students seeking current research on integrating intelligent techniques into sensor networks for more reliable security practices.

The definitive anthology of Tank Girl, collecting the classic, newly colored stories from original creators Alan Martin and Jamie Hewlett! Includes three exclusive art! All three volumes of the cult-classic Tank Girl comics (1988-1995) from legendary creators Alan Martin and Jamie Hewlett (Gorillaz). Dive into the twisted and chaotic world of Tank Girl, Jet Girl, Sub Girl and Booga, and experience the original stories that captured the hearts of readers everywhere, then shot them to oblivion (by accident of course)! With all new colouring, this is the complete Tank Girl collection you won't want to miss.

Due to the continuous technology advancements and customer demands, software systems are getting larger and more complex ever-increasingly. So, software systems may not necessarily be developed within the limited budget and delivered at the expected time. Quality is also another important issue that needs to be addressed in software development. Indeed, failing to meet the expected level of quality may lead to catastrophic consequences, especially for safety-critical systems (e.g., railway systems, airplanes, etc.). To manage the development of large and complex software systems, software engineering has been introduced, which aims at applying the principles of engineering to software development. By doing so, software systems can be developed within budget and delivered at the expected time with the expected level of quality. This Book is a project-oriented software engineering book, in which readers are expected to be involved in a software project. By doing so, it is intended to give readers the chance of having practical experience on the taught material and their programming skills. Moreover, readers can also enhance their skills on working as a team to accomplish a project in a way that meets the requirements of the customers. The aim of this book is to introduce the discipline of Software Engineering, focusing on the knowledge and technology required and how they can be applied in developing software systems in terms of their requirements, analysis, and design. It also aims at introducing the Unified Modeling Language (UML) to let readers have practical experience in specifying software requirements, analysis, and design.

In the modern era each new innovation poses its own special ethical dilemma. How can human society adapt to these new forms of expression, commerce, government, citizenship, and learning while holding onto its ethical and moral principles? The Changing Scope of Technoethics in Contemporary Society is a critical scholarly resource that examines the existing intellectual platform within the field of technoethics. Featuring coverage on a broad range of topics such as ethical perspectives on internet safety, technoscience, and ethical hacking communication, this book is geared towards academicians, researchers, and students seeking current research on domains of technoethics.

Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.