Each Student Book and ActiveBook have has clearly laid out pages with a range of supportive features to aid learning and teaching: Getting to know your unit sections ensure learners understand the grading criteria and unit requirements. Getting ready for Assessment sections focus on preparation for external assessment with guidance for learners on what to expect. Hints and tips will help them prepare for assessment and sample answers are provided for a range of question types including, short and long answer questions, all with a supporting commentary. Learners can also prepare for internal assessment using this feature. A case study of a learner completing the internal assessment for that unit covering 'How I got started', 'How I brought it all together' and 'What I got from the experience'. Pause Point feature provide opportunities for learners to self-evaluate their learning at regular intervals. Each Pause Point point feature gives learners a Hint or Extend option to either revisit and reinforce the topic or to encourage independent research or study skills. Case Study and Theory into Practice features enable development of problem-solving skills and place the theory into real life situations learners could encounter. Assessment Activity/Practice provide scaffolded assessment practice activities that help prepare learners for assessment. Within each assessment practice activity, a Plan, Do and Review section supports learners' formative assessment by making sure they fully understand what they are being asked to do, what their goals are and how to evaluate the task and consider how they could improve. Dedicated Think Future pages provide case studies from the industry, with a focus on aspects of skills development that can be put into practice in a real work environment and further study.

Advances in Delay-Tolerant Networks: Architecture and Enhanced Performance, Second Edition provides an important overview of delay-tolerant networks (DTNs) for researchers in electronics, computer engineering, telecommunications and networking for those in academia and R&D in industrial sectors. Part I reviews the technology involved and the prospects for improving performance, including different types of DTN and their applications, such as satellite and deep-space communications and vehicular communications. Part II focuses on how the technology can be further improved, addressing topics, such as data bundling, opportunistic routing, reliable data streaming, and the potential for rapid selection and dissemination of urgent messages. Opportunistic, delay-tolerant networks address the problem of intermittent connectivity in a network where there are long delays between sending and receiving messages, or there are periods of disconnection.

Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts.

Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly caused by a bacteria or a virus. The prime targets of this infectious disease are children below the age of 5 and adults above the age of 65, mostly due to their poor immunity and lower rates of recovery. Globally, pneumonia has prevalent footprints and kills more children as compared to any other immunity-based disease, causing up to 15% of child deaths per year, especially in developing countries. Out of all the available imaging modalities, such as computed tomography, radiography or X-ray, magnetic resonance imaging, ultrasound, and so on, chest radiographs are most widely used for differential diagnosis between Normal and Pneumonia. In the CAC system designs implemented in this book, a total of 200 chest radiograph images consisting of 100 Normal images and 100 Pneumonia images have been used. These chest radiographs are augmented using geometric transformations, such as rotation, translation, and flipping, to increase the size of the dataset for efficient training of the Convolutional Neural Networks (CNNs). A total of 12 experiments were conducted for the binary classification of chest radiographs into Normal and Pneumonia. It also includes in-depth implementation strategies of exhaustive experimentation carried out using transfer learning-based approaches with decision fusion, deep feature extraction, feature selection, feature dimensionality reduction, and machine learning-based classifiers for implementation of end-to-end CNN-based CAC system designs, lightweight CNN-based CAC system designs, and hybrid CAC system designs for chest radiographs. This book is a valuable resource for academicians, researchers, clinicians, postgraduate and graduate students in medical imaging, CAC, computer-aided diagnosis, computer science and engineering, electrical and electronics engineering, biomedical engineering, bioinformatics, bioengineering, and professionals from the IT industry.

Online high school education is challenging with limited resources for teachers to turn to. In most cases, teachers rely on trial-and-error. This research-based and practitioner-focused text provides best practice techniques and utilizes analogies from brick-and-mortar education to provide a conceptual framework to a better understanding of how online education functions and how to be engage students and how to build and maintain a positive digital culture. This book provides real-world solutions to online and hybrid educators. The aim of this is to train educators to develop online culture, healthy and inclusive communication, and how to use the online classroom environment in parallel or stand-alone with a face-to-face classroom. Engagement strategies will be discussed as well as the use of multi-tiered systems of support to engage students. The desired impact is to increase learning, growth and to prepare high school students for the next step in their academic career.

Semantic computing is critical for the development of semantic systems and applications that must utilize semantic analysis, semantic description, semantic interfaces, and semantic integration of data and services to deliver their objectives. Semantic computing has enormous capabilities to enhance the efficiency and throughput of systems that are based on key emerging concepts and technologies such as semantic web, internet of things, blockchain technology, and knowledge graphs. Thus, research that expounds advanced concepts, methods, technologies, and applications of semantic computing for solving challenges in real-world domains is vital. Advanced Concepts, Methods, and Applications in Semantic Computing is a scholarly reference book that provides a sound theoretical foundation for the application of semantic methods, concepts, and technologies for practical problem solving. It is designed as a comprehensive and reliable resource on how semantic-oriented approaches can be used to aid new emergent technologies and tackle real-world problems. Covering topics that include deep learning, machine learning, blockchain technology, and semantic web services, this book is ideal for professionals, academicians, researchers, and students working in the field of semantic computing in various disciplines, including but not limited to software engineering, systems engineering, knowledge engineering, electronic commerce, computer science, and information technology.

Image Processing for Automated Diagnosis of Cardiac Diseases highlights current and emerging technologies for the automated diagnosis of cardiac diseases. It presents concepts and practical algorithms, including techniques for the automated diagnosis of organs in motion using image processing. This book is suitable for biomedical engineering researchers, engineers and scientists in research and development, and clinicians who want to learn more about and develop advanced concepts in image processing to overcome the challenges of automated diagnosis of heart disease.

The study of cyberspace is relatively new within the field of social sciences, yet interest in the subject is significant. Conflicts, Crimes and Regulations in Cyberspace contributes to the scientific debate being brought to the fore by addressing international and methodological issues, through the use of case studies. This book presents cyberspace as a socio-technical system on an international level. It focuses on state and non-state actors, as well as the study of strategic concepts and norms. Unlike global studies, the socio-technical approach and "meso" scale facilitate the analysis of cyberspace in international relations. This is an area of both collaboration and conflict for which specific modes of regulation have appeared.

Gamification is being used everywhere; despite its apparent plethora of benefits, the unbalanced use of its main mechanics can end up in catastrophic results for a company or institution. Currently, there is a lack of knowledge of what it is, leading to its unregulated and ad hoc use without any prior planning. This unbalanced use prejudices the achievement of the initial goals and impairs the user's evolution, bringing potential negative reflections. Currently, there are few specifications and modeling languages that allow the creation of a system of rules to serve as the basis for a gamification engine. Consequently, programmers implement gamification in a variety of ways, undermining any attempt at reuse and negatively affecting interoperability. Next-Generation Applications and Implementations of Gamification Systems synthesizes all the trends, best practices, methodologies, languages, and tools that are used to implement gamification. It also discusses how to put gamification in action by linking academic and informatics researchers with professionals who use gamification in their daily work to disseminate and exchange the knowledge, information, and technology provided by the international communities in the area of gamification throughout the 21st century. Covering topics such as applied and cloud gamification, chatbots, deep learning, and certifications and frameworks, this book is ideal for programmers, computer scientists, software engineers, practitioners of technological companies, managers, academicians, researchers, and students.

AI and Cloud Computing, Volume 120 in the Advances in Computers series, highlights new advances in the field, with this updated volume presenting interesting chapters on topics including A Deep-forest based Approach for Detecting Fraudulent Online Transaction, Design of Cyber-Physical-Social Systems with Forensic-awareness Based on Deep Learning, Review on Privacy-preserving Data Comparison Protocols in Cloud Computing, Fingerprint Liveness Detection Using an Improved CNN with the Spatial Pyramid Pooling Structure, Protecting Personal Sensitive Data Security in the Cloud with Blockchain, and more.

Advances in Mathematics for Industry 4.0 examines key tools, techniques, strategies, and methods in engineering applications. By covering the latest knowledge in technology for engineering design and manufacture, chapters provide systematic and comprehensive coverage of key drivers in rapid economic development. Written by leading industry experts, chapter authors explore managing big data in processing information and helping in decision-making, including mathematical and optimization techniques for dealing with large amounts of data in short periods.

SECURITY AND PRIVACY IN THE INTERNET OF THINGS Provides the authoritative and up-to-date information required for securing IoT architecture and applications The vast amount of data generated by the Internet of Things (IoT) has made information and cyber security vital for not only personal privacy, but also for the sustainability of the IoT itself. Security and Privacy in the Internet of Things brings together high-quality research on IoT security models, architectures, techniques, and application domains. This concise yet comprehensive volume explores state-of-the-art mitigations in IoT security while addressing important security and privacy challenges across different IoT layers. The book provides timely coverage of IoT architecture, security technologies and mechanisms, and applications. The authors outline emerging trends in IoT security and privacy with a focus on areas such as smart environments and e-health. Topics include authentication and access control, attack detection and prevention, securing IoT through traffic modeling, human aspects in IoT security, and IoT hardware security. Presenting the current body of knowledge in a single volume, Security and Privacy in the Internet of Things: Discusses a broad range of IoT attacks and defense mechanisms Examines IoT security and privacy protocols and approaches Covers both the logical and physical security of IoT devices Addresses IoT security through network traffic modeling Describes privacy preserving techniques in smart cities Explores current threat and vulnerability analyses Security and Privacy in the Internet of Things: Architectures, Techniques, and Applications is essential reading for researchers, industry practitioners, and students involved in IoT security development and IoT systems deployment.