The internet of things (IoT) revolution has given rise to smart cities and villages all over the world. With technology advancements such as cloud computing, fog computing, and software-defined networking, it is necessary to examine ways that these environments can implement innovation for cost-effective citizen services and e-governance. Also, as cyber-physical systems are becoming more vulnerable with IoT attacks threatening their security and privacy, there is an even greater need for solutions that offer protection for all of these advancing technologies. The Handbook of Research on Implementation and Deployment of IoT Projects in Smart Cities is an essential research publication that combines theory and practice, reflecting on advancing technologies for the automation, protection, and sustainability of urban environments. Highlighting a wide range of topics such as blockchain, smart grid, and sustainability, this book is ideal for researchers, academicians, scientists, engineers, programmers, IT consultants, professionals, and policymakers.

The Internet of Medical Things (IoMT) allows clinicians to monitor patients remotely via a network of wearable or implantable devices. The devices are embedded with software or sensors to enable them to send and receive data via the internet so that healthcare professionals can monitor health data such as vital statistics, metabolic rates or drug delivery regimens, and can provide advice or treatment plans based on this real-world, real-time data. This edited book discusses key IoT technologies that facilitate and enhance this process, such as computer algorithms, network architecture, wireless communications, and network security. Providing a systemic review of trends, challenges and future directions of IoMT technologies, the book examines applications such as breast cancer monitoring systems, patient-centric systems for handling, tracking and monitoring virus variants, and video-based solutions for monitoring babies. The book discusses machine learning techniques for the management of clinical data and includes security issues such as the use of blockchain technology. Written by a range of international researchers, this book is a great resource for computer engineering researchers and practitioners in the fields of data mining, machine learning, artificial intelligence and the IoT in the healthcare sector.

E-health applications such as tele-medicine, tele-radiology, tele-ophthalmology, and tele-diagnosis are very promising and have immense potential to improve global healthcare. They can improve access, equity, and quality through the connection of healthcare facilities and healthcare professionals, diminishing geographical and physical barriers. One critical issue, however, is related to the security of data transmission and access to the technologies of medical information. Currently, medical-related identity theft costs billions of dollars each year and altered medical information can put a person's health at risk through misdiagnosis, delayed treatment or incorrect prescriptions. Yet, the use of hand-held devices for storing, accessing, and transmitting medical information is outpacing the privacy and security protections on those devices. Researchers are starting to develop some imperceptible marks to ensure the tamper-proofing, cost effective, and guaranteed originality of the medical records. However, the robustness, security and efficient image archiving and retrieval of medical data information against these cyberattacks is a challenging area for researchers in the field of e-health applications. Intelligent Data Security Solutions for e-Health Applications focuses on cutting-edge academic and industry-related research in this field, with particular emphasis on interdisciplinary approaches and novel techniques to provide security solutions for smart applications. The book provides an overview of cutting-edge security techniques and ideas to help graduate students, researchers, as well as IT professionals who want to understand the opportunities and challenges of using emerging techniques and algorithms for designing and developing more secure systems and methods for e-health applications.

The technology of Artificial Intelligence is here, and moving fast, without ethical standards in place. A Blueprint for the Regulation of Artificial Intelligence Technologies leans on classical western philosophy for its ethical grounding. Values such as conscience, rights, equity, and discrimination, establish a basis for regulatory standards. Multiple international agencies with governing interests are compared. The development of ethical standards is suggested through two new non-governmental organizations (NGOs). The first is to develop standards that evolve from practice, while the second acts as an ombudsman to settle abuse. Both NGOs are envisioned to cooperate with regulators. More than seeking a perfect solution, the book aims to balance the tension between conflicting interests, with the goal to keep this dangerously wonderful technology under global human control. For that to materialize, the technology needs to have a seat on the table of global ethics. The final chapter lists fourteen thinking points to achieve an ethics balance for new technologies.

The Art of Investigative Interviewing, Fourth Edition, builds on the successes of the previous editions providing the reader guidance on conducting investigative interviews, both ethically and professionally. The book can be used by anyone who is involved in investigative interviewing. It is a perfect combination of real, practical, and effective techniques, procedures, and actual cases. The reader learns key elements of investigative interviewing, such as human psychology, proper interview preparation, tactical concepts, controlling the interview environment, and evaluating the evidence obtained from the interview. New to this edition will be coverage of Open Source Intelligence (OSINT) tools, workplace investigations, fraud investigations and the role of audit. Larry Fennelly joins original author Inge Sebyan Black, both well-known and respected in the field, providing everything an interviewer needs to know in order to conduct successful interviews with integrity and within the law. Written for anyone involved in investigative interviewing.

Most technologies have been harnessed to enable educators to conduct their business remotely. However, the social context of technology as a mediating factor needs to be examined to address the perceptions of barriers to learning due to the lack of social interaction between a teacher and a learner in such a setting. Developing Technology Mediation in Learning Environments is an essential reference source that widens the scene of STEM education with an all-encompassing approach to technology-mediated learning, establishing a context for technology as a mediating factor in education. Featuring research on topics such as distance education, digital storytelling, and mobile learning, this book is ideally designed for teachers, IT consultants, educational software developers, researchers, administrators, and professionals seeking coverage on developing digital skills and professional knowledge using technology.

Advances in Computers, Volume 119, presents innovations in computer hardware, software, theory, design, and applications, with this updated volume including new chapters on Fast Execution of RDF Queries Using Apache Hadoop, A Study of DVFS Methodologies for Multicore Systems with Islanding Feature, Effectiveness of State-of-the-art Dynamic Analysis Techniques in Identifying Diverse Android Malware and Future Enhancements, Eyeing the Patterns: Data Visualization Using Doubly-Seriated Color Heatmaps, Eigenvideo for Video Indexing.

Artificial Intelligence in Cancer: Diagnostic to Tailored Treatment provides theoretical concepts and practical techniques of AI and its applications in cancer management, building a roadmap on how to use AI in cancer at different stages of healthcare. It discusses topics such as the impactful role of AI during diagnosis and how it can support clinicians to make better decisions, AI tools to help pathologists identify exact types of cancer, how AI supports tumor profiling and can assist surgeons, and the gains in precision for oncologists using AI tools. Additionally, it provides information on AI used for survival and remission/recurrence analysis. The book is a valuable source for bioinformaticians, cancer researchers, oncologists, clinicians and members of the biomedical field who want to understand the promising field of AI applications in cancer management.

Data has never mattered more. Our lives are increasingly shaped by it and how it is defined, collected and used. But who counts in the collection, analysis and application of data? This important book is the first to look at queer data - defined as data relating to gender, sex, sexual orientation and trans identity/history. The author shows us how current data practices reflect an incomplete account of LGBTQ lives and helps us understand how data biases are used to delegitimise the everyday experiences of queer people. Guyan demonstrates why it is important to understand, collect and analyse queer data, the benefits and challenges involved in doing so, and how we might better use queer data in our work. Arming us with the tools for action, this book shows how greater knowledge about queer identities is instrumental in informing decisions about resource allocation, changes to legislation, access to services, representation and visibility.

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.