Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert's knowledge in order to predict and monitor the health status in real time. The accuracy of the AI systems is drastically increasing by using machine learning, digitized medical data acquisition, wireless medical data communication, and computing infrastructure AI approaches, helping to solve complex issues in the biomedical industry and playing a vital role in future healthcare applications. The volume takes a multidisciplinary perspective of employing these new applications in biomedical engineering, exploring the combination of engineering principles with biological knowledge that contributes to the development of revolutionary and life-saving concepts.

Covers computational Intelligence techniques like fuzzy sets, artificial neural networks, deep neural networks, and genetic algorithm for Healthcare systems Provides easy understanding concepts like signal and image filtering techniques Includes discussion over filtering and classification problems Details studies with medical signal (ECG, EEG, EMG) and image (X-rays, FMRI, CT) datasets Describes evolution parameters such as signal-to-noise ratio, mean square error, accuracy, precision, and recall

Provides a comprehensive overview on the recent developments on clinical decision support systems, precision health and data science in medicine Examines the advancements, challenges and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Reviews melanoma detection by deep learning techniques

AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. The AI framework comprises of bootstrapping to create multiple training and testing data sets with various characteristics, design and analysis of statistical experiments to identify optimal feature subsets and optimal hyper-parameters for ML methods, data contamination to test for the robustness of the classifiers. Key Features: Using ML methods by itself doesn't ensure building classifiers that generalize well for new data Identifying optimal feature subsets and hyper-parameters of ML methods can be resolved using design and analysis of statistical experiments Using a bootstrapping approach to massive sampling of training and tests datasets with various data characteristics (e.g.: contaminated training sets) allows dealing with bias Developing of SAS-based table-driven environment allows managing all meta-data related to the proposed AI framework and creating interoperability with R libraries to accomplish variety of statistical and machine-learning tasks Computer programs in R and SAS that create AI framework are available on GitHub

* Fascinating cross-disciplinary work encompassing, AI, cognitive science, learning science, creative writing and thinking skills * Explores the role of the next wave of AI in creativity, education, literature and literacy * Written by experts in computing, education and creative writing * Explores the cutting edge and the limits of simulations of human creativity

This book examines the implications of disruptive technologies of the Fourth Industrial Revolution (4IR) on military innovation and the use of force. It provides an in-depth understanding of how both large and small militaries are seeking to leverage 4IR emerging technologies and the effects such technologies may have on future conflicts. The 4th Industrial Revolution (4IR), the confluence of disruptive changes brought by emerging technologies such as artificial intelligence, robotics, nanotechnologies, and autonomous systems, has a profound impact on the direction and character of military innovation and use of force. The core themes in this edited volume reflect on the position of emerging technologies in the context of previous Revolutions in Military Affairs; compare how large resource-rich states (US, China, Russia) and small resource-limited states (Israel, Sweden, Norway) are adopting and integrating novel technologies and explore the difference between various innovation and adaptation models. The book also examines the operational implications of emerging technologies in potential flashpoints such as the South China Sea and the Baltic Sea. Written by a group of international scholars, this book uncovers the varying 4IR defence innovation trajectories, enablers, and constraints in pursuing military-technological advantages that will shape the character of future conflicts. The chapters in this book were originally published as a special issue of the Journal of Strategic Studies.

Provides a comprehensive guide about how to use machine vision for Industry 4.0 applications like analysis of images for automated inspections, object detection, object tracking etc. Includes case studies of Robotics Internet of Things with its current and future applications in Healthcare, Agriculture, Transportation, etc. It highlights the inclusion of impaired people in industry, like intelligent assistant that helps deaf-mute people to transmit instructions and warnings in a manufacturing process. It examines the significant technological advancements in machine vision for industrial Internet of things and explores the commercial benefits using the real world applications from healthcare to transportation. Provides a conceptual framework of Machine vision for the various Industrial applications. Addresses scientific aspects for a wider audience such as senior and junior engineers, undergraduate and post-graduate students, researchers, and anyone else interested in the trends, development, and opportunities for the Machine Vision for Industry 4.0 applications.

This handbook provides an overview of research related to smart technologies and how they permeate the economic and social fabric. It covers a wide spectrum of topics and issues raised in the debate surrounding the increasing importance of smart technologies. It takes on a strongly multi- and interdisciplinary perspective, providing readers from different backgrounds and with varying knowledge of this topic with a comprehensive and comprehensible overview of the main upcoming technological trends from a scientifically eclectic viewpoint. This handbook draws together an international team of researchers from different scientific disciplines. The list of contributors comprises authors from Europe, North America, Australia and South Korea, and includes both internationally outstanding scientists and experts from a more policy-related and/or industry-related background.

The detailed survey on constraint handling techniques specifically penalty function approach is presented in the book; presents the Cohort Intelligence (CI) algorithm incorporated with a novel self-adaptive penalty function (SAPF) approach which helped in avoiding preliminary trials of selecting penalty parameter. The approach is referred to as CI-SAPF; CI-SAPF is further hybridized with Colliding Bodies Optimization (CBO) algorithm to promote a parameter less metaheuristic algorithm; presents solutions to several problems from discrete truss structure domain, mixed variable design engineering domain, and linear & nonlinear domain validating the CI-SAPF and CI-SAPF-CBO; behavior of SAPF approach on pseudo objective function, constraint violations, penalty function and penalty parameter have been analyzed and discussed in very detail; presents the in-depth analysis and comparison of the CI-SAPF, CI-SAPF-CBO and CBO algorithms with other contemporary techniques; provides the solution to real-world manufacturing problems of optimizing multi pass milling and turning processes using CI-SPF, CI-SAPF and CI-SAPF-CBO approaches.

Examines how digital media and the creation of digital immortals may affect religious understandings of death and the afterlife; Understands the impact of digital media on those living and those working with the bereaved; Explores the impact of digital memorialisation post death; Looks at the ways in which digital media may be changing conceptions and theologies of death

1) Discusses technical details of the Machine Learning tools and techniques in the different types of cancers 2) Machine learning and data mining in healthcare is a very important topic and hence there would be a demand for such a book 3) As compared to other titles, the proposed book focuses on different types of cancer disease and their prediction strategy using machine leaning and data mining.

Proposes to employ robots to improve the treatment of patients and leverage the load of the medical system. Demonstrates the concept of various robotics in healthcare telepresence, rehabilitation, therapy, and delivery robots to provide social distancing. Explores social robot aesthetics and how social interaction and embodied experience could be useful during social isolation. Includes anecdotes from applications used during the COVID-19 pandemic.

Crypto-Finance, Law and Regulation investigates whether crypto-finance will cause a paradigm shift in regulation from a centralised model to a model based on distributed consensus. This book explores the emergence of a decentralised and disintermediated crypto-market and investigates the way in which it can transform the financial markets. It examines three components of the financial market - technology, finance, and the law - and shows how their interrelationship dictates the structure of a crypto-market. It focuses on regulators' enforcement policies and their jurisdiction over crypto-finance operators and participants. The book also discusses the latest developments in crypto-finance, and the advantages and disadvantages of crypto-currency as an alternative payment product. It also investigates how such a decentralised crypto-finance system can provide access to finance, promote a shared economy, and allow access to justice. By exploring the law, regulation and governance of crypto-finance from a national, regional and global viewpoint, the book provides a fascinating and comprehensive overview of this important topic and will appeal to students, scholars and practitioners interested in regulation, finance and the law.

Introducing strong foundations to practical Cyber-Physical Systems Leveraging CPS for pandemic affected society Ensuring Secured and Privacy aware CPS for Sensitive Data in a pandemic situation Providing methodologies to deploy CPS in industries affect by a pandemic

Examines how digital media and the creation of digital immortals may affect religious understandings of death and the afterlife; Understands the impact of digital media on those living and those working with the bereaved; Explores the impact of digital memorialisation post death; Looks at the ways in which digital media may be changing conceptions and theologies of death

As transactions and other business functions move online and grow more popular every year, the finance and banking industries face increasingly complex data management and identity theft and fraud issues. AI can bring many financial and business functions to the next level, as systems using deep learning technologies are able to analyze patterns and spot suspicious behavior and potential fraud. In this volume, the focus is on the application of artificial intelligence in finance, business, and related areas. The book presents a selection of chapters presenting cutting-edge research on current business practices in finance and management. Topics cover the use of AI in e-commerce systems, financial services, fraud prevention, identifying loan-eligible customers, online business, Facebook social commerce, insurance industry, online marketing, and more.

Features: A systematic and comprehensive understanding of the Block chain technology and the potential in Healthcare. How security and privacy concerns of healthcare data can be addressed using Blockchain Technology. Concept of smart contracts for performing advance level scripting to create a blockchain network for providing a platform for the development of decentralized applications is discussed Chapter on role of blockchain based insurance application using Ethereum/Hyperledger is included Use cases of blockchain for various aspects of drug manufacturing and pharma supply chain..

Augmented Reality (AR) has many advantages that include increased engagement and interaction as well as enhanced innovation and responsiveness. AR technology has applications in almost all domains such as medical training, retail, repair and maintenance of complex equipment, interior design in architecture and construction, business logistics, tourism, and classroom education. Innovating with Augmented Reality: Applications in Education and Industry explains the concepts behind AR, explores some of its application areas, and gives an in-depth look at how this technology aligns with Education 4.0. Due to the rapid advancements in technology, future education systems must prepare students to work with the latest technologies by enabling them to learn virtually in augmented ways in varied platforms. By providing an illusion of physical objects, which takes the students to a new world of imagination, AR and Virtual Reality (VR) create virtual and interactive environments for better learning and understanding. AR applications in education are covered in four chapters of this book, including a chapter on how gamification can be made use of in the teaching and learning process. The book also covers other application areas of AR and VR. One such application area is the food and beverage industry with case studies on virtual 3D food, employee training, product-customer interaction, restaurant entertainment, restaurant tours, and product packaging. The application of AR in the healthcare sector, medical education, and related devices and software are examined in the book's final chapter. The book also provides an overview of the game development software, Unity, a real-time development platform for 2D and 3D AR and VR, as well as the software tools and techniques used in developing AR-based apps.

Includes innovative and new approaches for IoT in medical healthcare monitoring with 5G along with future directions Discusses the fundamental concepts and analysis of IoT and 5G in smart healthcare Focuses on methods used to apply IoT in monitoring devices for diagnosing diseases and transferring data using a 5G network. Presents new points of security and privacy concerns with expectations of IoT devices in 2030 where 91 billion devices will exist with over 10 connected devices per person Provides case studies depicting applications, best practices, as well as future predictions of IoT in everyday life Illustrates user focused wearable devices such as Fitbit health monitors and smartwatches where consumers are self-managing and self-monitoring their own health and providers are able to improve the experience of care

1) Focuses on the concepts and implementation strategies of various Deep Learning algorithms through properly curated examples. 2) The subject area will be valid for the next 10 years or so, as Deep Learning theory/algorithms and their applications will not be outdated easily. Hence there will be demand for such a book in the market. 3) In comparison to other titles, this book rigorously covers mathematical and conceptual details of relevant topics.

This book offers the latest research advances in the field of Industry 4.0, focusing on enabling technologies for its deployment in a comprehensive way. This book offers successful implementation of technologies such as artificial intelligence, augmented and virtual reality, autonomous and collaborative robots, cloud computing, and up-to-date guidelines. It investigates how the technologies and principles surrounding Industry 4.0 (e.g., interoperability, decentralized decisions, information transparency, etc.) serve as support for organizational routines and workers (and vice versa). Included are applications of technologies for different sectors and environments as well as for the supply chain management. It also offers a domestic and international mix of case studies that spotlight successes and failures. Features Provides a historical review of Industry 4.0 and its roots Discusses the applications of technologies in different sectors and environments (e.g., public vs. private) Presents key enabling technologies for successful implementation in any industrial and service environment Offers case studies of successes and failures to illustrate how to put theory into practice Investigates how technologies serve as support for organizational routines and workers

The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained-including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. Fully updated and revised, Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence, Fourth Edition features: A new chapter on deep neural networks, reflecting the growth of machine learning as a key technique for AI A new section on the use of Python, which has become the de facto standard programming language for many aspects of AI The rule-based and uncertainty-based examples in the book are compatible with the Flex toolkit by Logic Programming Associates (LPA) and its Flint extension for handling uncertainty and fuzzy logic. Readers of the book can download this commercial software for use free of charge. This resource and many others are available at the author's website: adrianhopgood.com. Whether you are building your own intelligent systems, or you simply want to know more about them, this practical AI textbook provides you with detailed and up-to-date guidance.

The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained-including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. Fully updated and revised, Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence, Fourth Edition features: A new chapter on deep neural networks, reflecting the growth of machine learning as a key technique for AI A new section on the use of Python, which has become the de facto standard programming language for many aspects of AI The rule-based and uncertainty-based examples in the book are compatible with the Flex toolkit by Logic Programming Associates (LPA) and its Flint extension for handling uncertainty and fuzzy logic. Readers of the book can download this commercial software for use free of charge. This resource and many others are available at the author's website: adrianhopgood.com. Whether you are building your own intelligent systems, or you simply want to know more about them, this practical AI textbook provides you with detailed and up-to-date guidance.

This book will raise awareness on emerging challenges of AIempowered cyber arms used in weapon systems and stockpiled in the global cyber arms race. Based on real life events, it provides a comprehensive analysis of cyber offensive and defensive landscape, analyses the cyber arms evolution from prank malicious codes into lethal weapons of mass destruction, reveals the scale of cyber offensive conflicts, explores cyber warfare mutation, warns about cyber arms race escalation and use of Artificial Intelligence (AI) for military purposes. It provides an expert insight into the current and future malicious and destructive use of the evolved cyber arms, AI and robotics, with emphasis on cyber threats to CBRNe and critical infrastructure. The book highlights international efforts in regulating the cyber environment, reviews the best practices of the leading cyber powers and their controversial approaches, recommends responsible state behaviour. It also proposes information security and cyber defence solutions and provides definitions for selected conflicting cyber terms. The disruptive potential of cyber tools merging with military weapons is examined from the technical point of view, as well as legal, ethical, and political perspectives.