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Artificial Intelligence in Microbial Research: Bridging the Gap (Microorganisms for Sustainability #45)
by Valentina E. Balas Aditya Khamparia Venkatesh Dutta Devendra Pandey Babita PandeyThis book explores the convergence of microbiology and artificial intelligence (AI) and delves into the intricate world of microbial systems enhanced by cutting-edge AI technologies. The book begins by establishing a foundation in the fundamentals of microbial ecosystems and AI principles. It elucidates the integration of AI in microbial genomics, demonstrating how advanced algorithms analyze genomic data and contribute to genetic engineering. Bioinformatics and computational microbiology are explored, showcasing AI's role in predictive modeling and computational tools. The intersection of AI and microbial applications extends to drug discovery, precision agriculture, and pathogen detection. Readers gain insights into AI-driven drug development, the optimization of agricultural practices using microbial biostimulants, and early warning systems for crop diseases. The book highlights AI's role in microbial biotechnology, elucidating its impact on bioprocessing, fermentation, and other biotechnological applications. Climate-smart agriculture and microbial adaptations to environmental challenges are discussed, emphasizing sustainable practices. This book caters to a diverse audience including teachers, researchers, microbiologist, computer bioinformaticians, plant and environmental scientists. The book serves as additional reading material for undergraduate and graduate students of computer science, biomedical, agriculture, human science, forestry, ecology, soil science, and environmental sciences and policy makers to be a useful to read.
Artificial Intelligence in Orthopaedic Surgery Made Easy
by Filippo Familiari Olimpio Galasso Giorgio GaspariniThis book is an essential reference guide for the use of artificial intelligence in orthopaedic surgery. It covers all related topics, from machine and deep learning, through practical applications in all orthopaedic sub-disciplines, to ethical issues and potential risks. International renowned experts equip the reader with solid scientific foundations and practical tips combining accurate literature reviews with high-quality original images. Addressing a hot topic for the present and next generation of medical specialists, this book is a must read for orthopaedic surgeons, radiologists and health informatic specialists alike.
Artificial Intelligence in PET/CT Oncologic Imaging
by Athanasios D. Gouliamos John A. Andreou Paris A. KosmidisThis book presents artificial intelligence applications that may help in detecting disease, defining tissue characterization (benign vs malignant), staging and correlation with molecular biomarkers. Originally positioned as a means for noninvasive molecular phenotyping and quantification in the 1970s, PET's technological improvements in the 2000s generated renewed interest in quantification, which has grown over the last five years. This progress is parallel with the development of Artificial intelligence (AI) systems for Oncology which aim at providing the best possible treatment to patients suffering from lung, breast, brain, prostate, liver and other types of cancer. The chapters provide an overview of the use of AI in PET/CT imaging for various types of cancer, and it will be an invaluable tool especially for nuclear medicine physicians and oncologists.
Artificial Intelligence in Process Fault Diagnosis: Methods for Plant Surveillance
by Richard J. FickelschererArtificial Intelligence in Process Fault Diagnosis A comprehensive guide to the future of process fault diagnosis Automation has revolutionized every aspect of industrial production, from the accumulation of raw materials to quality control inspections. Even process analysis itself has become subject to automated efficiencies, in the form of process fault analyzers, i.e., computer programs capable of analyzing process plant operations to identify faults, improve safety, and enhance productivity. Prohibitive cost and challenges of application have prevented widespread industry adoption of this technology, but recent advances in artificial intelligence promise to place these programs at the center of manufacturing process analysis. Artificial Intelligence in Process Fault Diagnosis brings together insights from data science and machine learning to deliver an effective introduction to these advances and their potential applications. Balancing theory and practice, it walks readers through the process of choosing an ideal diagnostic methodology and the creation of intelligent computer programs. The result promises to place readers at the forefront of this revolution in manufacturing. Artificial Intelligence in Process Fault Diagnosis readers will also find: Coverage of various AI-based diagnostic methodologies elaborated by leading expertsGuidance for creating programs that can prevent catastrophic operating disasters, reduce downtime after emergency process shutdowns, and moreComprehensive overview of optimized best practices Artificial Intelligence in Process Fault Diagnosis is ideal for process control engineers, operating engineers working with processing industrial plants, and plant managers and operators throughout the various process industries.
Artificial Intelligence in Radiation Oncology and Biomedical Physics (Imaging in Medical Diagnosis and Therapy)
by Lei Xing Gilmer ValdesThis pioneering book explores how machine learning and other AI techniques impact millions of cancer patients who benefit from ionizing radiation. It features contributions from global researchers and clinicians, focusing on the clinical applications of machine learning for medical physics. AI and machine learning have attracted much recent attention and are being increasingly adopted in medicine, with many clinical components and commercial software including aspects of machine learning integration. General principles and important techniques in machine learning are introduced, followed by discussion of clinical applications, particularly in radiomics, outcome prediction, registration and segmentation, treatment planning, quality assurance, image processing, and clinical decision-making. Finally, a futuristic look at the role of AI in radiation oncology is provided. This book brings medical physicists and radiation oncologists up to date with the most novel applications of machine learning to medical physics. Practitioners will appreciate the insightful discussions and detailed descriptions in each chapter. Its emphasis on clinical applications reaches a wide audience within the medical physics profession.
Artificial Intelligence in a Throughput Model: Some Major Algorithms
by Waymond RodgersPhysical and behavioral biometric technologies such as fingerprinting, facial recognition, voice identification, etc. have enhanced the level of security substantially in recent years. Governments and corporates have employed these technologies to achieve better customer satisfaction. However, biometrics faces major challenges in reducing criminal, terrorist activities and electronic frauds, especially in choosing appropriate decision-making algorithms. To face this challenge, new developments have been made, that amalgamate biometrics with artificial intelligence (AI) in decision-making modeling. Advanced software algorithms of AI, processing information offered by biometric technology, achieve better results. This has led to growth in the biometrics technology industry, and is set to increase the security and internal control operations manifold. This book provides an overview of the existing biometric technologies, decision-making algorithms and the growth opportunity in biometrics. The book proposes a throughput model, which draws on computer science, economics and psychology to model perceptual, informational sources, judgmental processes and decision choice algorithms. It reviews how biometrics might be applied to reduce risks to individuals and organizations, especially when dealing with digital-based media.
Artificial Intelligence of Things for Achieving Sustainable Development Goals (Lecture Notes on Data Engineering and Communications Technologies #192)
by Sanjay Misra Kerstin Siakas Georgios LampropoulosThis book covers various topics and trends regarding Artificial Intelligence (AI), Internet of Things (IoT), and their applications in society, industry, and environment for achieving Sustainable Development Goals (SDGs) suggested by the United Nations. Additionally, it discusses their advancements and fusion as well as the realization of Artificial Intelligence of Things (AIoT). The book aims to provide an overview and recent research into the fusion, integration, advancements, and impact of these technologies in the context of SDGs achievement. The topics include the applications of AI, IoT, big data, AI-based and IoT-based cloud computing, machine learning and deep learning techniques, and blockchain among others for achieving SDGs. It also presents findings and discussions on potential application domains, addresses open issues and challenges, offers solutions, and provides suggestions for future research for achieving SDGs. The chapters are clustered, according to particular SDGsor areas of focus, into: i) the realization of AIoT for SDGs, ii) the role of AIoT in achieving society and wellbeing-related SDGs, iii) the fulfillment of industrial sectors, infrastructure, and economy-related SDGs through AIoT, and iv) the use of AIoT to aid natural resources and environment-related SDGs. The book assists researchers, practitioners, professionals, and academicians of various scientific fields in exploring and better understanding these state-of-the-art technologies, their advancements, impact, future potentials and benefits, and their role in successfully achieving SDGs.The book:· Offers an in-depth overview of AIoT for achieving SDGs.· Presents the fusion of AI and IoT for bringing a significant change in everyday life and fulfilling SDGs.· Highlights innovative solutions and results of AIoT integration in several domains for achieving SDGs.· Showcases the influence of AIoT on promoting and improving sustainability in the context of SDGs.· Discusses the issues, benefits, solutions, and impact of AIoT in society, industry, and environment for achieving SDGs.
Artificial Intelligence on Dark Matter and Dark Energy: Reverse Engineering of the Big Bang (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Ariel FernándezAs we prod the cosmos at very large scales, basic tenets of physics seem to crumble under the weight of contradicting evidence. This book helps mitigate the crisis. It resorts to artificial intelligence (AI) for answers and describes the outcome of this quest in terms of an ur-universe, a quintessential compact multiply connected space that incorporates a fifth dimension to encode space-time as a latent manifold. In some ways, AI is bolder than humans because the huge corpus of knowledge, starting with the prodigious Standard Model (SM) of particle physics, poses almost no burden to its conjecture-framing processes. Why not feed AI with the SM enriched by the troubling cosmological phenomenology on dark matter and dark energy and see where AI takes us vis-à-vis reconciling the conflicting data with the laws of physics? This is precisely the intellectual adventure described in this book and – to the best of our knowledge – in no other book on the shelf. As the reader will discover, many AI conjectures and validations ultimately make a lot of sense, even if their boldness does not feel altogether "human" yet. This book is written for a broad readership. Prerequisites are minimal, but a background in college math/physics/computer science is desirable. This book does not merely describe what is known about dark matter and dark energy but also provides readers with intellectual tools to engage in a quest for the deepest cosmological mystery.
Artificial Intelligence on Medical Data: Proceedings of International Symposium, ISCMM 2021 (Lecture Notes in Computational Vision and Biomechanics #37)
by Mousumi Gupta Sujata Ghatak Amlan Gupta Abir Lal MukherjeeThis book includes high-quality papers presented at the Second International Symposium on Computer Vision and Machine Intelligence in Medical Image Analysis (ISCMM 2021), organized by Computer Applications Department, SMIT in collaboration with Department of Pathology, SMIMS, Sikkim, India, and funded by Indian Council of Medical Research, during 11 – 12 November 2021. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.
Artificial Intelligence, Computational Modelling and Criminal Proceedings: A Framework for A European Legal Discussion (Legal Studies in International, European and Comparative Criminal Law #4)
by Serena QuattrocoloThis book discusses issues relating to the application of AI and computational modelling in criminal proceedings from a European perspective. Part one provides a definition of the topics. Rather than focusing on policing or prevention of crime – largely tackled by recent literature – it explores ways in which AI can affect the investigation and adjudication of crime. There are two main areas of application: the first is evidence gathering, which is addressed in Part two. This section examines how traditional evidentiary law is affected by both new ways of investigation – based on automated processes (often using machine learning) – and new kinds of evidence, automatically generated by AI instruments. Drawing on the comprehensive case law of the European Court of Human Rights, it also presents reflections on the reliability and, ultimately, the admissibility of such evidence. Part three investigates the second application area: judicial decision-making, providing an unbiased review of the meaning, benefits, and possible long-term effects of ‘predictive justice’ in the criminal field. It highlights the prediction of both violent behaviour, or recidivism, and future court decisions, based on precedents. Touching on the foundations of common law and civil law traditions, the book offers insights into the usefulness of ‘prediction’ in criminal proceedings.
Artificial Intelligence, Entrepreneurship and Risk: Reflections and Positions at the Crossroads between Philosophy and Management (Technikzukünfte, Wissenschaft und Gesellschaft / Futures of Technology, Science and Society)
by Christian Hugo HoffmannThis book embarks on a thought-provoking journey that seeks to illuminate the intricate connections between the dynamic realms of AI, Entrepreneurship and Risk Management. This book illuminates the philosophical foundations of AI, examines the fundamental beliefs surrounding AI's nature, and its effects for the human condition. Drawing on the works of eminent philosophers, economists and business leaders alike, the authors of this volume engage in inspirational discussions on ethics, philosophy of technology, and the potential societal ramifications of advancing AI technologies. By grounding the exploration in philosophical reflections, the authors set the stage for a comprehensive understanding of AI's role in entrepreneurship and the inherent risks it entails.
Artificial Intelligence, Ethics and the Future of Warfare: Global Perspectives
by Kaushik RoyThis volume examines how the adoption of AI technologies is likely to impact strategic and operational planning, and the possible future tactical scenarios for conventional, unconventional, cyber, space and nuclear force structures. In addition to developments in the USA, Britain, Russia and China, the volume also explores how different Asian and European countries are actively integrating AI into their military readiness. It studies the effect of AI and related technologies in training regimens and command structures. The book also covers the ethical and legal aspects of AI augmented warfare.The volume will be of great interest to scholars, students and researchers of military and strategic studies, defence studies, artificial intelligence and ethics.
Artificial Intelligence, Finance, and Sustainability: Economic, Ecological, and Ethical Implications
by Thomas Walker Dieter Gramlich Akram SadatiAs the world increasingly recognizes the importance of sustainability, businesses and investors are looking for ways to integrate sustainable practices into their operations and investment decisions. At the same time, advancements in artificial intelligence (AI) and technology are transforming the finance industry and are enabling more data-driven decision-making. The intersection of these fields presents a significant opportunity to accelerate progress towards a more sustainable future, while also improving financial performance. This book explores the crucial role of AI in sustainability and finance, examining how financial technologies and machine learning are shaping the approach of finance professionals towards environmental, social, and governance (ESG) issues. It provides a comprehensive and integrated perspective on how these areas are becoming increasingly intertwined and examines the ethical and social implications of AI in finance and its potential to unlock new opportunities for sustainability. By focusing on the practical implications of these intersections and including both case studies and expert analysis, the book provides valuable insights for practitioners, policymakers, academics, and students alike.
Artificial Intelligence, Learning and Computation in Economics and Finance (Understanding Complex Systems)
by Ragupathy VenkatachalamThis book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, computer science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded.Theoretical and empirical studies featured in this book draw on a variety of approaches such as agent-based modeling, numerical simulations, computable economics, as well as employing tools from artificial intelligence and machine learning algorithms. The use of computational approaches to perform counterfactual thought experiments are also introduced, which help transcend the limits posed by traditional mathematical and statistical tools.The book also includes discussions on methodology, epistemology, history and issues concerning prediction, validation, and inference, all of which have become pertinent with the increasing use of computational approaches in economic analysis.
Artificial Intelligence-Aided Materials Design: AI-Algorithms and Case Studies on Alloys and Metallurgical Processes
by Rajesh Jha Bimal Kumar JhaThis book describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials, including hard and soft magnetic alloys, nickel-base superalloys, titanium-base alloys, and aluminum-base alloys. Readers new to AI/ML algorithms can use this book as a starting point and use the MATLAB® and Python implementation of AI/ML algorithms through included case studies. Experienced AI/ML researchers who want to try new algorithms can use this book and study the case studies for reference. Offers advantages and limitations of several AI concepts and their proper implementation in various data types generated through experiments and computer simulations and from industries in different file formats Helps readers to develop predictive models through AI/ML algorithms by writing their own computer code or using resources where they do not have to write code Covers downloadable resources such as MATLAB GUI/APP and Python implementation that can be used on common mobile devices Discusses the CALPHAD approach and ways to use data generated from it Features a chapter on metallurgical/materials concepts to help readers understand the case studies and thus proper implementation of AI/ML algorithms under the framework of data-driven materials science Uses case studies to examine the importance of using unsupervised machine learning algorithms in determining patterns in datasets This book is written for materials scientists and metallurgists interested in the application of AI, ML, and data science in the development of new materials.
Artificial Intelligence-based Infrared Thermal Image Processing and its Applications
by Kurt Ammer U. Snekhalatha K. Palani ThanarajInfrared thermography is a fast and non-invasive technology that provides a map of the temperature distribution on the body’s surface. This book provides a description of designing and developing a computer-assisted diagnosis (CAD) system based on thermography for diagnosing such common ailments as rheumatoid arthritis (RA), diabetes complications, and fever. It also introduces applications of machine-learning and deep-learning methods in the development of CAD systems. Key Features: • Covers applications of various image processing techniques in thermal imaging applications for the diagnosis of different medical conditions • Describes the development of a computer diagnostics system (CAD) based on thermographic data • Discusses deep-learning models for accurate diagnosis of various diseases • Includes new aspects in rheumatoid arthritis and diabetes research using advanced analytical tools • Reviews application of feature fusion algorithms and feature reduction algorithms for accurate classification of images This book is aimed at researchers and graduate students in biomedical engineering, medicine, image processing, and CAD.
Artificial Intelligence-based Smart Power Systems
by Jens Bo Holm-Nielsen Sanjeevikumar Padmanaban Sivaraman Palanisamy Sharmeela ChenniappanARTIFICIAL INTELLIGENCE-BASED SMART POWER SYSTEMS Authoritative resource describing artificial intelligence and advanced technologies in smart power systems with simulation examples and case studies Artificial Intelligence-based Smart Power Systems presents advanced technologies used in various aspects of smart power systems, especially grid-connected and industrial evolution. It covers many new topics such as distribution phasor measurement units, blockchain technologies for smart power systems, the application of deep learning and reinforced learning, and artificial intelligence techniques. The text also explores the potential consequences of artificial intelligence and advanced technologies in smart power systems in the forthcoming years. To enhance and reinforce learning, the editors include many learning resources throughout the text, including MATLAB, practical examples, and case studies. Artificial Intelligence-based Smart Power Systems includes specific information on topics such as: Modeling and analysis of smart power systems, covering steady state analysis, dynamic analysis, voltage stability, and more Recent advancement in power electronics for smart power systems, covering power electronic converters for renewable energy sources, electric vehicles, and HVDC/FACTs Distribution Phasor Measurement Units (PMU) in smart power systems, covering the need for PMU in distribution and automation of system reconfigurations Power and energy management systems Engineering colleges and universities, along with industry research centers, can use the in-depth subject coverage and the extensive supplementary learning resources found in Artificial Intelligence-based Smart Power Systems to gain a holistic understanding of the subject and be able to harness that knowledge within a myriad of practical applications.
Artificial Intelligence: A Modern Approach
by Stuart Russell Peter NorvigArtificial Intelligence: A Modern Approach (AIMA) is a university textbook on artificial intelligence, written by Stuart J. Russell and Peter Norvig. It was first published in 1995 and the fourth edition of the book was released 28 April 2020. It is used in over 1400 universities worldwide and has been called "the most popular artificial intelligence textbook in the world". It is considered the standard text in the field of artificial intelligence. The book is intended for an undergraduate audience but can also be used for graduate-level studies with the suggestion of adding some of the primary sources listed in the extensive bibliography.
Artificial Intelligence: Building Smarter Machines
by Stephanie Sammartino McPhersonIn 2011 a computer named Watson outscored two human competitors on the TV quiz show Jeopardy! and snagged the million-dollar prize. Watson isn't the only machine keeping up with humans. The field of artificial intelligence (AI) is booming, with drones, robots, and computers handling tasks that once only humans could perform. Such advances raise challenging questions. Do Watson and other computers really think? Can machines acquire self-awareness? Is AI a promising or a dangerous technology? No machine, not even Watson, yet comes close to matching human intelligence, but many scientists believe it is only a matter of time before we reach this milestone. What will such a future look like?
Artificial Intelligence: Economic Perspectives and Models
by Wim Naudé Thomas Gries and Nicola DimitriIs Artificial Intelligence a more significant invention than electricity? Will it result in explosive economic growth and unimaginable wealth for all, or will it cause the extinction of all humans? Artificial Intelligence: Economic Perspectives and Models provides a sober analysis of these questions from an economics perspective. It argues that to better understand the impact of AI on economic outcomes, we must fundamentally change the way we think about AI in relation to models of economic growth. It describes the progress that has been made so far and offers two ways in which current modelling can be improved: firstly, to incorporate the nature of AI as providing abilities that complement and/or substitute for labor, and secondly, to consider demand-side constraints. Outlining the decision-theory basis of both AI and economics, this book shows how this, and the incorporation of AI into economic models, can provide useful tools for safe, human-centered AI.
Artificial Intelligence: Everything you need to know about the coming AI. A Ladybird Expert Book (The Ladybird Expert Series #27)
by Michael Wooldridge'I propose to consider the question, 'Can machines think?' Alan Turing (1950)Part of the ALL-NEW Ladybird Expert series.This book is for everyone living in the age of Artificial Intelligence. And this is an accessible and authoritative introduction to one of the most important conversations of our time . . . Written by computer scientist Michael Wooldridge, Artificial Intelligence chronicles the development of intelligent machines, from Turing's dream of machines that think, to today's digital assistants like Siri and Alexa. AI is not something that awaits us in the future. Inside you'll learn how we have come to rely on embedded AI software and what a world of ubiquitous AI might look like.What's inside?- The British mathematician Alan Turing- Can machines 'understand'?- Logical and Behavioural AI- The reality of AI today- AI tomorrow- And much more . . . For an adult readership, the Ladybird Expert series is produced in the same iconic small hardback format pioneered by the original Ladybirds. Each beautifully illustrated book features the first new illustrations produced in the original Ladybird style for nearly forty years.
Artificial Intelligence: Evolution, Ethics and Public Policy
by Pankaj Sharma Saswat SarangiWhat will the future be? A dystopian landscape controlled by machines or a brave new world full of possibilities? Perhaps the answer lies with Artificial Intelligence (AI)—a phenomenon much beyond technology that has, continues to, and will shape lives in ways we do not understand yet. This book traces the evolution of AI in contemporary history. It analyses how AI is primarily being driven by "capital" as the only "factor of production" and its consequences for the global political economy. It further explores the dystopian prospect of mass unemployment by AI and takes up the ethical aspects of AI and its possible use in undermining natural and fundamental rights. A tract for the times, this volume will be a major intervention in an area that is heavily debated but rarely understood. It will be essential reading for researchers and students of digital humanities, politics, economics, science and technology studies, physics, and computer science. It will also be key reading for policy makers, cyber experts and bureaucrats.
Artificial Intelligence: Humans at the Heart of Algorithms
by Alan DixAn authoritative and accessible one-stop resource, the first edition of An Introduction to Artificial Intelligence presented one of the first comprehensive examinations of AI. Designed to provide an understanding of the foundations of artificial intelligence, it examined the central computational techniques employed by AI, including knowledge representation, search, reasoning and learning, as well as the principal application domains of expert systems, natural language, vision, robotics, software agents and cognitive modelling. Many of the major philosophical and ethical issues of AI were also introduced. This new edition expands and revises the book throughout, with new material to augment existing chapters, including short case studies, as well as adding new chapters on explainable AI, big data and deep learning, temporal and web-scale data, statistical methods and data wrangling. It expands the book’s focus on human-centred AI, covering gender, ethnic and social bias, the need for transparency, intelligent user interfaces, and designing interactions to aid machine learning. With detailed, well-illustrated examples and exercises throughout, this book provides a substantial and robust introduction to artificial intelligence in a clear and concise coursebook form. It stands as a core text for all students and computer scientists approaching AI.You can also visit the author website for further resources: https://alandix.com/aibook/.
Artificial Intimacy: Virtual Friends, Digital Lovers, and Algorithmic Matchmakers
by Rob BrooksWhat happens when the human brain, which evolved over eons, collides with twenty-first-century technology? Machines can now push psychological buttons, stimulating and sometimes exploiting the ways people make friends, gossip with neighbors, and grow intimate with lovers. Sex robots present the humanoid face of this technological revolution—yet although it is easy to gawk at their uncanniness, more familiar technologies based in artificial intelligence and virtual reality are insinuating themselves into human interactions. Digital lovers, virtual friends, and algorithmic matchmakers help us manage our feelings in a world of cognitive overload. Will these machines, fueled by masses of user data and powered by algorithms that learn all the time, transform the quality of human life?Artificial Intimacy offers an innovative perspective on the possibilities of the present and near future. The evolutionary biologist Rob Brooks explores the latest research on intimacy and desire to consider the interaction of new technologies and fundamental human behaviors. He details how existing artificial intelligences can already learn and exploit human social needs—and are getting better at what they do. Brooks combines an understanding of core human traits from evolutionary biology with analysis of how cultural, economic, and technological contexts shape the ways people express them. Beyond the technology, he asks what the implications of artificial intimacy will be for how we understand ourselves.
Artificial Life: The Quest for a New Creation
by Steven LevyBiologists, mathematicians, and computer scientists learn what computers can do when given the opportunity to "think".