In this book, the authors focus on efficient ways to program instrumentation and automation systems using LabVIEW (TM), a system design platform and development environment commonly used for data acquisition, instrument control, and industrial automation on a variety of operating systems. Starting with the concepts of data flow and concurrent programming, the authors go on to address the development of state machines, event programming and consumer producer systems. Chapters cover the following topics: Introduction to LabVIEW (TM), debugging tools, structures, SubVIs, structures - LabVIEW (TM) features, organizing front panel and block diagram, using software resources, using hardware resources, implementing test machines with a basic architecture, controlling the user interface, error handling, responding to the user interactions, the ATM review project, communication between loops at different rates, preventing race conditions, advanced use of software resources, and real-time programming. This book helps undergraduate and graduate students learn how to identify the most suitable design patterns depending on the application, and how to implement them in conjunction with data acquisition and instrumentation control systems. It is also a helpful resource for engineers and scientists who want to implement binary files to record data, control the user interface and implement efficient ways of programming.

The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques. Deep Neural Networks for Multimodal Imaging and Biomedical Applications provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging. Featuring coverage on a broad range of topics such as prediction models, edge computing, and quantitative measurements, this book is ideally designed for researchers, academicians, physicians, IT consultants, medical software developers, practitioners, policymakers, scholars, and students seeking current research on biomedical advancements and developing computational methods in healthcare.

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs.

Shape grammar and space syntax have been separately developed but rarely combined in any significant way. The first of these is typically used to investigate or generate the formal or geometric properties of architecture, while the second is used to analyze the spatial, topological, or social properties of architecture. Despite the reciprocal relationship between form and space in architecture-it is difficult to conceptualize a completed building without a sense of both of these properties-the two major computational theories have been largely developed and applied in isolation from each another. Grammatical and Syntactical Approaches in Architecture: Emerging Research and Opportunities is a critical scholarly resource that explores the relationship between shape grammar and space syntax for urban planning and architecture and enables the creative discovery of both the formal and spatial features of an architectural style or type. This book, furthermore, presents a new method to selectively capture aspects of both the grammar and syntax of architecture. Featuring a range of topics such as mathematical analysis, spatial configuration, and domestic architecture, this book is essential for architects, policymakers, urban planners, researchers, academicians, and students.

Elgar Advanced Introductions are stimulating and thoughtful introductions to major fields in the social sciences, business and law, expertly written by the world's leading scholars. Designed to be accessible yet rigorous, they offer concise and lucid surveys of the substantive and policy issues associated with discrete subject areas. Providing a comprehensive overview of the current and future uses of Artificial Intelligence (AI) in healthcare, this Advanced Introduction discusses the issues surrounding the implementation, governance, impacts and risks of utilising AI in health organizations Key Features: Advises healthcare executives on how to effectively leverage AI to advance their strategies and plans and support digital transformation Discusses AI governance, change management, workforce management and the organization of AI experimentation and implementation Analyzes AI technologies in healthcare and their impacts on patient care, medical devices, pharmaceuticals, population health, and healthcare operations Provides risk mitigation approaches to address potential AI algorithm problems, liability and regulation Essential reading for policymakers, clinical executives and consultants in healthcare, this Advanced Introduction explores how to successfully integrate AI into healthcare organizations and will also prove invaluable to students and scholars interested in technological innovations in healthcare.

In Online Predators, An Internet Insurgency: A Field Manual for Teaching and Parenting in the Digital Arena Jeffrey A. Lee brings his ten plus years' experience in the fight against online child exploitation to bear in an easy to follow guide for all with a stake in the life of a child. This book equips parents, guardians, extended family, and educational professionals with practical strategies to help keep kids safe in a technology connected world. Instead of focusing on ever changing technology, Lee proposes a key fundamental change in the fight against online predation-to develop an insatiable curiosity about their child's online life, then get in the front lines and stay there.

Advances in Imaging and Electron Physics, Volume 215, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains.

Ascend AI Processor Architecture and Programming: Principles and Applications of CANN offers in-depth AI applications using Huawei's Ascend chip, presenting and analyzing the unique performance and attributes of this processor. The title introduces the fundamental theory of AI, the software and hardware architecture of the Ascend AI processor, related tools and programming technology, and typical application cases. It demonstrates internal software and hardware design principles, system tools and programming techniques for the processor, laying out the elements of AI programming technology needed by researchers developing AI applications. Chapters cover the theoretical fundamentals of AI and deep learning, the state of the industry, including the current state of Neural Network Processors, deep learning frameworks, and a deep learning compilation framework, the hardware architecture of the Ascend AI processor, programming methods and practices for developing the processor, and finally, detailed case studies on data and algorithms for AI.

Based on scientific understanding and empirical evidence of how humans understand and interact with robotic and autonomous systems, the author reviews the concerns that have been raised around the deployment of AI and robots in human society, and the potential for disruption and harm. He explains why transparency ought to be a fundamental design consideration for Human Computer Interaction (HCI) and artificial intelligent systems. Starting with a survey of global research in the field and what transparency means in the wider context of trust, control and ethics, the author then introduces a transparent robot control architecture, and the impact of transparency using real-time displays. He presents a case study of a muttering robot, and covers current and upcoming standards for transparency, as well as future perspectives for the design, manufacture and operation of autonomous robotic systems. Specifically, chapters cover transparency in the wider context of trust; a transparent robot control architecture, the impact of transparency using real-time displays, transparency using audio - the Muttering Robot, the effects of appearance on transparency, synthesis and further work, and several examples of Instinct reactive planner commands. This book provides key insights into transparency in robots and autonomous systems for industry, academic researchers and engineers working on intelligent autonomous system design, human robot interaction, AI, and machine ethics. It also offers points of interest for professionals developing governmental or organisational policies and standards for the design of intelligent autonomous and AI systems, and government and standard bodies working in the emerging applications of AI.

This book explores 10 unique facets of Internet health and safety, including physical safety, information security, and the responsible use of technology, offering takeaways from interviews with experts in the field and suggestions for proactively improving users' Internet safety. The Internet has become for many people—especially students and young adults—an essential and intrinsic part of their lives. It makes information available to be shared worldwide, at any time; enables learning about any topic; and allows for instantaneous communication. And it provides endless entertainment as well. But the benefits of online access are accompanied by serious potential risks. This book covers the key elements of Internet health and safety, including physical safety, information security, and the responsible use of technology. It begins with an introductory essay that gives readers the necessary conceptual framework, and then explains specific topics such as cyberbullying, file sharing, online predators, Internet fraud, and obscene and offensive content. The book also answers readers' questions in a "Q & A" section with a subject expert and includes a directory of resources that provides additional information and serves as a gateway to further study.

5G is the upcoming generation of the wireless network that will be the advanced version of 4G LTE+ providing all the features of a 4G LTE network and connectivity for IoT devices with faster speed and lower latency. The 5G network is going to be a service-oriented network, connecting billions of IoT devices and mobile phones through the wireless network, and hence, it needs a special emphasis on security. Security is the necessary enabler for the continuity of the wireless network business, and in 5G, network security for IoT devices is the most important aspect. As IoT is gaining momentum, people can remotely operate or instruct their network devices. Therefore, there is a need for robust security mechanisms to prevent unauthorized access to the devices. >Evolution of Software-Defined Networking Foundations for IoT and 5G Mobile Networks is a collection of innovative research on the security challenges and prevention mechanisms in high-speed mobile networks. The book explores the threats to 5G and IoT and how to implement effective security architecture for them. While highlighting topics including artificial intelligence, mobile technology, and ubiquitous computing, this book is ideally designed for cybersecurity experts, network providers, computer scientists, communication technologies experts, academicians, students, and researchers.