Cyber Security Applications for Industry 4.0
Cyber Security Applications for Industry 4.0 (CSAI 4.0) provides integrated features of various disciplines in Computer Science, Mechanical, Electrical, and Electronics Engineering which are defined to be Smart systems. It is paramount that Cyber-Physical Systems (CPS) provide accurate, real-time monitoring and control for smart applications and services. With better access to information from real-time manufacturing systems in industrial sectors, the CPS aim to increase the overall equipment effectiveness, reduce costs, and improve efficiency. Industry 4.0 technologies are already enabling numerous applications in a variety of industries. Nonetheless, legacy systems and inherent vulnerabilities in an organization's technology, including limited security mechanisms and logs, make the move to smart systems particularly challenging.Features: Proposes a conceptual framework for Industry 4.0-based Cyber Security Applications concerning the implementation aspect Creates new business models for Industrialists on Control Systems and provides productive workforce transformation Outlines the potential development and organization of Data Protection based on strategies of cybersecurity features and planning to work in the new area of Industry 4.0 Addresses the protection of plants from the frost and insects, automatic hydroponic irrigation techniques, smart industrial farming and crop management in agriculture relating to data security initiatives The book is primarily aimed at industry professionals, academicians, and researchers for a better understanding of the secure data transition between the Industry 4.0 enabled connected systems and their limitations
Discrete Geometry and Mathematical Morphology
This book constitutes the proceedings of the Second IAPR International Conference on Discrete Geometry and Mathematical Morphology, DGMM 2022, which was held during October 24-27, 2022, in Strasbourg, France.The 33 papers included in this volume were carefully reviewed and selected from 45 submissions. They were organized in topical sections as follows: discrete and combinatorial topology; discrete tomography and inverse problems; multivariate and PDE-based mathematical morphology, morphological filtering; hierarchical and Graph-Based Models, Analysis and Segmentation; discrete geometry - models, transforms, and visualization; learning based morphology to Mathematical Morphology; and distance transform. The book also contains 3 invited keynote papers.
The Psychology of Evolving Technology
Technological innovations have advanced at an incredible speed since the introduction of the computer that it has altered the fabric of our society. The possession of computers, smart-devices, along with social media, texting and video games, is now an intimate part of the structure of our culture. This book is a framework to start a conversation on how technology is changing our lifestyles and transforming our world. There is now an entire generation that has been using technology through the most delicate developmental time in their lives. This book presents how to look at the cognitive and psychosocial developmental stages and what are the age-appropriate milestones and factsheet of behaviors at different ages. It provides insight into the strength and vulnerable characteristics at each stage and the prevalence of some negative conditions in our society. You will gain a perspective of the encouraging and challenging aspects of computer learning, smart devices, and how to start and keep the conversation going from infancy to adulthood in order to keep and maintain your virtues and ways to circumvent unfavorable consequences. In short, The Psychology of Evolving Technology looks at how cutting-edge and revolutionary high technologies have disrupted our society through its many luxuries and conveniences and how it has altered the outlook of our values, privileges, and expectations. You will - Determine what adjustments should be made to regulate new innovations to allow them to succeed and to not have a detrimental effect to on society - See how development stages in a child now interact with technology - Review how social media and influencer culture are changing the way we see ourselves in society Who This Book Is For All readers curious about the effect of technology on individuals, growing children, and the fabric of society
Multimedia Communications, Services and Security
This book constitutes the proceedings of the 11th International Conference, MCSS 2022, held in Krak籀w, Poland, during November 3-4, 2022. The 13 full papers included in this book were carefully reviewed and selected from 33 submissions. The papers cover ongoing research activities in the following topics: cybersecurity, multimedia services; intelligent monitoring; audio-visual systems; biometric applications; experiments and deployments.
Computational Mathematics Modeling in Cancer Analysis
This book constitutes the proceedings of the First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022), held in conjunction with MICCAI 2022, in Singapore in September 2022. Due to the COVID-19 pandemic restrictions, the CMMCA2022 was held virtually. DALI 2022 accepted 15 papers from the 16 submissions that were reviewed. A major focus of CMMCA2022 is to identify new cutting-edge techniques and their applications in cancer data analysis in response to trends and challenges in theoretical, computational and applied aspects of mathematics in cancer data analysis.
Autonomous Agents and Multiagent Systems. Best and Visionary Papers
This book constitutes thoroughly refereed and revised selected best and visionary papers from the Workshops held at the International Conference on Autonomous Agents and Multiagent Systems AAMAS 2022, which took place online, during May 9-13, 2022.The 5 best papers and 4 visionary papers included in this book stem from the following workshops: - 13th Workshop on Optimization and Learning in Multi-agent Systems (OptLearnMAS);- 23rd Workshop on Multi-Agent Based Simulation (MABS);- 6th Workshop on Agent-Based Modelling of Urban Systems (ABMUS);- 10th Workshop on Engineering Multi-Agent Systems (EMAS);- 1st Workshop on Rebellion and Disobedience in AI (RaD-AI).There was a total of 59 submissions to these workshops.
Digital Transformation in Policing: The Promise, Perils and Solutions
This book shares essential insights into how the social sciences and technology could foster new advances in managing the complexity inherent to the criminal and digital policing landscape. Said landscape is both dynamic and intricate, emanating as it does from crimes that are both persistent and transnational. Globalization, human and drug trafficking, cybercrime, terrorism, and other forms of transnational crime can have significant impacts on societies around the world. This necessitates a reassessment of what crime, national security and policing mean. Recent global events such as human and drug trafficking, the COVID-19 pandemic, violent protests, cyber threats and terrorist activities underscore the vulnerabilities of our current security and digital policing posture.This book presents concepts, theories and digital policing applications, offering a comprehensive analysis of current and emerging trends in digital policing. Pursuing an evidence-based approach, itoffers an extraordinarily perceptive and detailed view of issues and solutions regarding the crime and digital policing landscape. To this end, it highlights current technological and methodological solutions as well as advances concerning integrated computational and analytical solutions deployed in digital policing. It also provides a comprehensive analysis of the technical, ethical, legal, privacy and civil liberty challenges stemming from the aforementioned advances in the field of digital policing; and accordingly, offers detailed recommendations supporting the design and implementation of best practices including technical, ethical and legal approaches when conducting digital policing. The research gathered here fits well into the larger body of work on various aspects of AI, cybersecurity, national security, digital forensics, cyberterrorism, ethics, human rights, cybercrime and law. It provides a valuable reference for law enforcement, policymakers, cybersecurity experts, digital forensic practitioners, researchers, graduates and advanced undergraduates, and other stakeholders with an interest in counter-terrorism. In addition to this target audience, it offers a valuable tool for lawyers, criminologist and technology enthusiasts.
Artificial General Intelligence
This book constitutes the refereed proceedings of the 15th International Conference on Artificial General Intelligence, AGI 2022, held as a hybrid event in Seattle, WA, USA, in August 2022.The 31 full papers presented in this book were carefully reviewed and selected from 61 submissions. The papers cover topics from foundations of AGI, to AGI approaches and AGI ethics, to the roles of systems biology, goal generation, and learning systems, and so much more. Additionally, this volume contains 13 posters.
Swarm Intelligence
This book constitutes the proceedings of the 13th International Conference on Swarm Intelligence, ANTS 2022, held in M獺laga, Spain, in November 2022. The 19 full papers presented, together with 14 short papers and 4 extended abstracts were carefully reviewed and selected from 45 submissions. ANTS 2022 contributions are dealing with any aspect of swarm intelligence such as behavioral models of social insects, empirical and theoretical research in swarm intelligence, application of swarm intelligence methods, and much more.
Advances in Computational Collective Intelligence
This book constitutes refereed proceedings of the 14th International Conference on International Conference on Computational Collective Intelligence, ICCCI 2022, held in Hammamet, Tunisia, in September 2022. The 43 full papers and 15 short papers were thoroughly reviewed and selected from 421 submissions. The papers are grouped in topical ​sections on ​collective intelligence and collective decision-making; natural language processing; deep learning; computational intelligence for multimedia understanding; computational intelligence in medical applications; applications for industry 4.0; experience enhanced intelligence to IoT and sensors; cooperative strategies for decision making and optimization; machine learning methods.
Simplifying Medical Ultrasound
This book constitutes the proceedings of the Third International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2022, held on September 18, 2022, in conjunction with MICCAI 2022, the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference took place in Singapore. The 18 papers presented in this book were carefully reviewed and selected from 23 submissions. They were organized in topical sections as follows: classification and detection; Segmentation and Reconstruction; and Assessment, Guidance and Robotics.Chapters "Left Ventricle Contouring of Apical Three-Chamber Views on 2D Echocardiography" and "3D Cardiac Anatomy Reconstruction from 2D Segmentations: a Study using Synthetic Data" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Artificial Intelligence Boon or Bane?
The process of writing this book was a brainchild of a conversation that ensued between friends who were thinking about the development of artificial intelligence and how it has evolved over the years. The goal of this book( Part 1) is to provide programmers and computer scientists with a readable introduction to the problems and techniques of artificial intelligence (A.I.). The book can be used either as a text for a course on A.I. or as a self-study guide for computer professionals who want to learn what A.I. is all about. Artificial intelligence has truly changed the way in which life occurs presently, and it's truly insightful to note that AI has been in existence even before the terminology 'AI' had been coined. With the knowledge obtained on artificial intelligence; I am looking forward to giving future generation a peek on what artificial intelligence is and its contributions to our society over the years. Writing, editing, and publishing this book took an immense amount of time and it wouldn't have existed had it not been the invaluable efforts and contributions of several supportive, thoughtful, and incredible people, who have contributed their knowledge and some experience in this Book.
Artificial Intelligence Boon or Bane?
The process of writing this book was a brainchild of a conversation that ensued between friends who were thinking about the development of artificial intelligence and how it has evolved over the years. The goal of this book( Part 1) is to provide programmers and computer scientists with a readable introduction to the problems and techniques of artificial intelligence (A.I.). The book can be used either as a text for a course on A.I. or as a self-study guide for computer professionals who want to learn what A.I. is all about. Artificial intelligence has truly changed the way in which life occurs presently, and it's truly insightful to note that AI has been in existence even before the terminology 'AI' had been coined. With the knowledge obtained on artificial intelligence; I am looking forward to giving future generation a peek on what artificial intelligence is and its contributions to our society over the years. Writing, editing, and publishing this book took an immense amount of time and it wouldn't have existed had it not been the invaluable efforts and contributions of several supportive, thoughtful, and incredible people, who have contributed their knowledge and some experience in this Book.
Introduction to Compiler Design
This book is designed primarily for use as a textbook in a one-semester course on compiler design for undergraduate students and beginning graduate students. The only prerequisites for this book are familiarity with basic algorithms and data structures (lists, maps, recursion, etc.), a rudimentary knowledge of computer architecture and assembly language, and some experience with the Java programming language.A complete study of compilers could easily fill several graduate-level courses, and therefore some simplifications and compromises are necessary for a one-semester course that is accessible to undergraduate students. Following are some of the decisions made in order to accommodate the goals of this book.The book has a narrow focus as a project-oriented course on compilers. Compiler theory is kept to a minimum, but the project orientation retains the "fun" part of studying compilers.The source language being compiled is relatively simple, but it is powerful enough to be interesting and challenging. It has basic data types, arrays, procedures, functions, and parameters, but it relegates many other interesting language features to the project exercises.The target language is assembly language for a virtual machine with a stack-based architecture, similar to but much simpler than the Java Virtual Machine (JVM). This approach greatly simplifies code generation. Both an assembler and an emulator for the virtual machine are provided on the course web site.No special compiler-related tools are required or used within the book. Students require access only to a Java compiler and a text editor, but most students will want to use Java with an Integrated Development Environment (IDE).One very important component of a compiler is the parser, which verifies that a source program conforms to the language syntax and produces an intermediate representation of the program that is suitable for additional analysis and code generation. There are several different approaches to parsing, but in keeping with the focus on a one-semester course, this book emphasizes only one approach, recursive descent parsing with several lookahead tokens.
Text, Speech, and Dialogue
This book constitutes the proceedings of the 25th International Conference on Text, Speech, and Dialogue, TSD 2022, held in Brno, Czech Republic, in September 2022. The 43 papers presented in this volume were carefully reviewed and selected from 94 submissions. The topical sections "Text", "Speech", and "Dialogue" deal with the following issues: speech recognition; corpora and language resources; speech and spoken language generation; tagging, classification and parsing of text and speech; semantic processing of text and speech; integrating applications of text and speech processing; automatic dialogue systems; multimodal techniques and modelling.
Raspberry Pi Image Processing Programming
Understand the concepts of image processing with Python 3 and create applications using Raspberry Pi 4. This book covers image processing with the latest release of Python 3, using Raspberry Pi OS and Raspberry Pi 4B with the 8 GB RAM model as the preferred computing platform.This second edition begins with the installation of Raspberry Pi OS on the latest model of Raspberry Pi and then introduces Python programming language, IDEs for Python, and digital image processing. It also illustrates the theoretical foundations of Image processing followed by advanced operations in image processing. You'll then review image processing with NumPy, and Matplotlib followed by transformations, interpolation, and measurements of images. Different types of filters such as Kernels convolution filters, low pass filters, high pass filters, and Fourier filters are discussed in a clear, methodical manner. Additionally, the book examines variousimage processing techniques such as Morphology, Thresholding, and Segmentation, followed by a chapter on live webcam input with OpenCV, an image processing library with Python. The book concludes with an appendix covering a new library for image processing with Python, pgmagik, followed by a few important tips and tricks relevant to RPi.What You'll LearnGet started with Raspberry Pi and PythonUnderstand Image Processing with PillowSee how image processing is processed using Numpy and MatplotlibUse Pi camera and webcamWho This Book Is ForRaspberry Pi and IoT enthusiasts, and Python and Open Source professionals
Recent Trends in Image Processing and Pattern Recognition
This volume constitutes the refereed proceedings of the 4th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2021, held in Msida, Malta, in December 2021. Due to the COVID-19 pandemic the conference was held online. The 19 full papers and 14 short papers presented were carefully reviewed and selected from 84 submissions. The papers are organized in the following topical sections: ​ healthcare: medical imaging and informatics; computer vision and pattern recognition; document analysis and recognition; signal processing and machine learning; satellite imaging and remote sensing.
Reinforcement Learning with Hybrid Quantum Approximation in the Nisq Context
This book explores the combination of Reinforcement Learning and Quantum Computing in the light of complex attacker-defender scenarios. Reinforcement Learning has proven its capabilities in different challenging optimization problems and is now an established method in Operations Research. However, complex attacker-defender scenarios have several characteristics that challenge Reinforcement Learning algorithms, requiring enormous computational power to obtain the optimal solution. The upcoming field of Quantum Computing is a promising path for solving computationally complex problems. Therefore, this work explores a hybrid quantum approach to policy gradient methods in Reinforcement Learning. It proposes a novel quantum REINFORCE algorithm that enhances its classical counterpart by Quantum Variational Circuits. The new algorithm is compared to classical algorithms regarding the convergence speed and memory usage on several attacker-defender scenarios with increasing complexity. In addition, to study its applicability on today's NISQ hardware, the algorithm is evaluated on IBM's quantum computers, which is accompanied by an in-depth analysis of the advantages of Quantum Reinforcement Learning.
Soft Computing and Its Engineering Applications
This book constitutes the refereed proceedings of the Third International Conference on Soft Computing and its Engineering Applications, icSoftComp 2021, held in Changa, India, in December 2021. Due to the COVID-19 pandemic the conference was held online. The 29 full papers and 4 short papers presented were carefully reviewed and selected from 247 submissions. The papers present recent research on theory and applications in fuzzy computing, neuro computing, and evolutionary computing.
Science and Technologies for Smart Cities
This book constitutes the refereed proceedings of the 7th Annual SmartCity360簞 Summit which was organized in November 2021 in Porto, Portugal. Due to COVID-19 pandemic the conference was held virtually. The volume combines selected papers of 6 conferences, namely EdgeIoT 2021 - International Conference on Intelligent Edge Processing in the IoT Era; IC4S 2021 - International Conference on Cognitive Computing and Cyber Physical Systems; SmartGov 2021 - International Conference on Smart Governance for Sustainable Smart Cities; SmartGift 2021 - International Conference on Smart Grid and Innovative Frontiers in Telecommunications; e PFSM 2021 - International Conference on Privacy and Forensics in Smart Mobility. The 45 full papers were carefully selected from 109 submissions. The papers are organized in four thematic sections on Smart Grid and Innovative Frontiers in Telecommunications; Smart Governance for Sustainable Smart Cities; Privacy and Forensics in Smart Mobility;and Sensor Systems and Software.
Learning Kernel Classifiers
An overview of the theory and application of kernel classification methods. Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier--a limited, but well-established and comprehensively studied model--and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence analysis. This book provides the first comprehensive overview of both the theory and algorithms of kernel classifiers, including the most recent developments. It begins by describing the major algorithmic advances: kernel perceptron learning, kernel Fisher discriminants, support vector machines, relevance vector machines, Gaussian processes, and Bayes point machines. Then follows a detailed introduction to learning theory, including VC and PAC-Bayesian theory, data-dependent structural risk minimization, and compression bounds. Throughout, the book emphasizes the interaction between theory and algorithms: how learning algorithms work and why. The book includes many examples, complete pseudo code of the algorithms presented, and an extensive source code library.
Medical Image Computing and Computer Assisted Intervention - MICCAI 2022
The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;Part III: Breast imaging; colonoscopy; computer aided diagnosis;Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;Part VI: Image registration; image reconstruction;Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning - domain adaptation and generalization;Part VIII: Machine learning - weakly-supervised learning; machine learning - model interpretation; machine learning - uncertainty; machine learning theory and methodologies.
Medical Image Computing and Computer Assisted Intervention - MICCAI 2022
The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;Part III: Breast imaging; colonoscopy; computer aided diagnosis;Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;Part VI: Image registration; image reconstruction;Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning - domain adaptation and generalization;Part VIII: Machine learning - weakly-supervised learning; machine learning - model interpretation; machine learning - uncertainty; machine learning theory and methodologies.
The Stuff of Bits
An argument that the material arrangements of information--how it is represented and interpreted--matter significantly for our experience of information and information systems. Virtual entities that populate our digital experience, like e-books, virtual worlds, and online stores, are backed by the large-scale physical infrastructures of server farms, fiber optic cables, power plants, and microwave links. But another domain of material constraints also shapes digital living: the digital representations sketched on whiteboards, encoded into software, stored in databases, loaded into computer memory, and transmitted on networks. These digital representations encode aspects of our everyday world and make them available for digital processing. The limits and capacities of those representations carry significant consequences for digital society. In The Stuff of Bits, Paul Dourish examines the specific materialities that certain digital objects exhibit. He presents four case studies: emulation, the creation of a "virtual" computer inside another; digital spreadsheets and their role in organizational practice; relational databases and the issue of "the databaseable"; and the evolution of digital networking and the representational entailments of network protocols. These case studies demonstrate how a materialist account can offer an entry point to broader concerns--questions of power, policy, and polity in the realm of the digital.
Medical Image Computing and Computer Assisted Intervention - MICCAI 2022
The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;Part III: Breast imaging; colonoscopy; computer aided diagnosis;Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;Part VI: Image registration; image reconstruction;Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning - domain adaptation and generalization;Part VIII: Machine learning - weakly-supervised learning; machine learning - model interpretation; machine learning - uncertainty; machine learning theory and methodologies.
Regularized System Identification
This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the power of machine learning without losing sight of the system-theoretical principles of black-box identification. The authors' reformulation of the identification problem in the light of regularization theory not only offers new insight on classical questions, but paves the way to new and powerful algorithms for a variety of linear and nonlinear problems. Regression methods such as regularization networks and support vector machines are the basis of techniques that extend the function-estimation problem to the estimation of dynamic models. Many examples, also from real-world applications, illustrate the comparative advantages of the new nonparametric approach with respect to classic parametric prediction error methods.The challenges it addresses lie at the intersection of several disciplines so Regularized System Identification will be of interest to a variety of researchers and practitioners in the areas of control systems, machine learning, statistics, and data science.This is an open access book.
Medical Image Computing and Computer Assisted Intervention - MICCAI 2022
The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;Part III: Breast imaging; colonoscopy; computer aided diagnosis;Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;Part VI: Image registration; image reconstruction;Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning - domain adaptation and generalization;Part VIII: Machine learning - weakly-supervised learning; machine learning - model interpretation; machine learning - uncertainty; machine learning theory and methodologies.
Cashless Society 101
Did you know that cashless and contactless transactions increased by over 30% during 2020-2021? More than a third of consumers report that they never use cash to make purchases. As Artificial Intelligence (AI) and other technologies improve, their effects on society include shifting how people all over the world buy and sell goods and services. However, the seemingly simple shift to automation and digitization raises complex ethical questions of how consumers will be affected. In this book, author Brian Asingia explores how technology and ethics will coexist in an increasingly cashless future, considering questions such as: How will more than 1.7 billion "unbanked" consumers adapt to a cashless society?What are the benefits and challenges of going cashless, and how can an ethical cashless society address challenges?How does the anonymity of cryptocurrency level the playing field for consumers of different socioeconomic backgrounds?How can tech creators ensure that AI is as unbiased as possible?In Cashless Society 101: A Practical (Values to Action) Guide to Ethical Leadership and Inclusive Innovation, author Brian Asingia takes an in-depth look at these critical issues, and explores how an increasingly cashless world may transform our global society.ABOUT THE AUTHOR, ASINGIAAfter beginning his career on Wall Street, Brian Asingia branched out to work in the intersection between technology, finance, business, and the arts. He has consulted for startups, governments, diplomats, educational institutions, and programs. Asingia is now the CEO and co-founder of the DreamGalaxy Platform, an innovation studio that trains, advises, and funds ethical entrepreneurial leaders to launch, grow, and scale inclusive innovations. Always fascinated by modern ethics and the idea of a cashless society, Asingia turned his attention to writing. He was inspired to pen Cashless Society 101: A Practical (Values to Action) Guide to Ethical Leadership and Inclusive Innovation to inspire and engage the next generation of ethical entrepreneurial leaders around the world.
Practical Automated Machine Learning Using H2O.ai
Accelerate the adoption of machine learning by automating away the complex parts of the ML pipeline using H2O.aiKey Features: Learn how to train the best models with a single click using H2O AutoMLGet a simple explanation of model performance using H2O ExplainabilityEasily deploy your trained models to production using H2O MOJO and POJOBook Description: With the huge amount of data being generated over the internet and the benefits that Machine Learning (ML) predictions bring to businesses, ML implementation has become a low-hanging fruit that everyone is striving for. The complex mathematics behind it, however, can be discouraging for a lot of users. This is where H2O comes in - it automates various repetitive steps, and this encapsulation helps developers focus on results rather than handling complexities.You'll begin by understanding how H2O's AutoML simplifies the implementation of ML by providing a simple, easy-to-use interface to train and use ML models. Next, you'll see how AutoML automates the entire process of training multiple models, optimizing their hyperparameters, as well as explaining their performance. As you advance, you'll find out how to leverage a Plain Old Java Object (POJO) and Model Object, Optimized (MOJO) to deploy your models to production. Throughout this book, you'll take a hands-on approach to implementation using H2O that'll enable you to set up your ML systems in no time.By the end of this H2O book, you'll be able to train and use your ML models using H2O AutoML, right from experimentation all the way to production without a single need to understand complex statistics or data science.What You Will Learn: Get to grips with H2O AutoML and learn how to use itExplore the H2O Flow Web UIUnderstand how H2O AutoML trains the best models and automates hyperparameter optimizationFind out how H2O Explainability helps understand model performanceExplore H2O integration with scikit-learn, the Spring Framework, and Apache StormDiscover how to use H2O with Spark using H2O Sparkling WaterWho this book is for: This book is for engineers and data scientists who want to quickly adopt machine learning into their products without worrying about the internal intricacies of training ML models. If you're someone who wants to incorporate machine learning into your software system but don't know where to start or don't have much expertise in the domain of ML, then you'll find this book useful. Basic knowledge of statistics and programming is beneficial. Some understanding of ML and Python will be helpful.
Medical Image Computing and Computer Assisted Intervention - Miccai 2022
The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging; Part III: Breast imaging; colonoscopy; computer aided diagnosis; Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I; Part V: Image segmentation II; integration of imaging with non-imaging biomarkers; Part VI: Image registration; image reconstruction; Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning - domain adaptation and generalization; Part VIII: Machine learning - weakly-supervised learning; machine learning - model interpretation; machine learning - uncertainty; machine learning theory and methodologies.
Innopolis University - From Zero to Hero
This open access book describes the development of Innopolis, a young Russian university established in 2012 to focus on teaching excellence in computer science, engineering, and robotics. It reports on the problems that were faced in the first decade of its development, and the adopted solutions. It shows how the key aspects for the development of the faculty, the curricula, the university structure, and the challenge of internationalization have been successfully addressed by the university management and professors, and how the solutions are scalable for other newly founded research organizations.The book is divided in five parts: "The Beginning" describes the very early days in general, from the foundation and start-up of the university with the related processes. "The People" reports on the initial hiring of the faculty members, the selection of students, and the curriculum development. "The Activities" provide information about the creation of the single research institutions and labs, and their relation to industry. "The Future" gives an outlook on the planned internationalization and faculty strategy. Eventually, "A Visual Journey" shows a selection of photographs illustrating highlights of the whole process and the current achievements. The processes and the components described built the basis for the development of Innopolis, and many of them still have a big impact on its present and its future. The fewer mistakes are made at the beginning, the higher the probability to fully achieve the initial goals.
Hyperparameter Tuning for Machine and Deep Learning with R
This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The case studies presented in this book can be run on a regular desktop or notebook computer. No high-performance computing facilities are required. The idea for the book originated in a study conducted by Bartz & Bartz GmbH for the Federal Statistical Office of Germany (Destatis). Building on that study, the book is addressed to practitioners in industry as well as researchers, teachers and students in academia. The content focuses on the hyperparameter tuning of ML and DL algorithms, and is divided into two main parts: theory (Part I) and application (Part II).Essential topics covered include: a survey of important model parameters; four parameter tuning studies and one extensive global parameter tuning study; statistical analysis of the performance of ML and DL methods based on severity; and a new, consensus-ranking-based way to aggregate and analyze results from multiple algorithms. The book presents analyses of more than 30 hyperparameters from six relevant ML and DL methods, and provides source code so that users can reproduce the results. Accordingly, it serves as a handbook and textbook alike.
Progress in Artificial Intelligence
This book constitutes the proceedings of the 21st EPIA Conference on Artificial Intelligence, EPIA 2022, which took place in Lisbon, Portugal, in August/September 2022. The 64 papers presented in this volume were carefully reviewed and selected from 85 submissions. They were organized in topical sections as follows: AI4IS - Artificial Intelligence for Industry and Societies; AIL - Artificial Intelligence and Law; AIM - Artificial Intelligence in Medicine; AIPES - Artificial Intelligence in Power and Energy Systems; AITS - Artificial Intelligence in Transportation Systems; AmIA - Ambient Intelligence and Affective Environments; GAI - General AI; IROBOT - Intelligent Robotics; KDBI - Knowledge Discovery and Business Intelligence; KRR - Knowledge Representation and Reasoning; MASTA - Multi-Agent Systems: Theory and Applications; TeMA - Text Mining and Applications.
Hyperparameter Tuning for Machine and Deep Learning with R
This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The case studies presented in this book can be run on a regular desktop or notebook computer. No high-performance computing facilities are required. The idea for the book originated in a study conducted by Bartz & Bartz GmbH for the Federal Statistical Office of Germany (Destatis). Building on that study, the book is addressed to practitioners in industry as well as researchers, teachers and students in academia. The content focuses on the hyperparameter tuning of ML and DL algorithms, and is divided into two main parts: theory (Part I) and application (Part II).Essential topics covered include: a survey of important model parameters; four parameter tuning studies and one extensive global parameter tuning study; statistical analysis of the performance of ML and DL methods based on severity; and a new, consensus-ranking-based way to aggregate and analyze results from multiple algorithms. The book presents analyses of more than 30 hyperparameters from six relevant ML and DL methods, and provides source code so that users can reproduce the results. Accordingly, it serves as a handbook and textbook alike.
Hands-On Aiops
Welcome to your hands-on guide to artificial intelligence for IT operations (AIOps). This book provides in-depth coverage, including operations and technical aspects. The fundamentals of machine learning (ML) and artificial intelligence (AI) that form the core of AIOps are explained as well as the implementation of multiple AIOps uses cases using ML algorithms.The book begins with an overview of AIOps, covering its relevance and benefits in the current IT operations landscape. The authors discuss the evolution of AIOps, its architecture, technologies, AIOps challenges, and various practical use cases to efficiently implement AIOps and continuously improve it. The book provides detailed guidance on the role of AIOps in site reliability engineering (SRE) and DevOps models and explains how AIOps enables key SRE principles. The book provides ready-to-use best practices for implementing AIOps in an enterprise. Each component of AIOps and ML using Python code andtemplates is explained and shows how ML can be used to deliver AIOps use cases for IT operations.What You Will Learn Know what AIOps is and the technologies involved Understand AIOps relevance through use cases Understand AIOps enablement in SRE and DevOps Understand AI and ML technologies and algorithmsUse algorithms to implement AIOps use casesUse best practices and processes to set up AIOps practices in an enterprise Know the fundamentals of ML and deep learning Study a hands-on use case on de-duplication in AIOps Use regression techniques for automated baseliningUse anomaly detection techniques in AIOps Who This Book is For AIOps enthusiasts, monitoring and management consultants, observability engineers, site reliability engineers, infrastructure architects, cloud monitoring consultants, service management experts, DevOps architects, DevOps engineers, and DevSecOps experts
Hci International 2022 Posters
The four-volume set CCIS 1580, CCIS 1581, CCIS 1582, and CCIS 1583 contains the extended abstracts of the posters presented during the 24th International Conference on Human-Computer Interaction, HCII 2022, which was held virtually in June - July 2022. The total of 1276 papers and 275 posters included in the 40 HCII 2021 proceedings volumes was carefully reviewed and selected from 5583 submissions.The posters presented in these four volumes are organized in topical sections as follows: Part I: user experience design and evaluation; visual design and visualization; data, information and knowledge; interacting with AI; universal access, accessibility and design for aging. Part II: multimodal and natural interaction; perception, cognition, emotion and psychophysiological monitoring; human motion modelling and monitoring; IoT and intelligent living environments. Part III: learning technologies; HCI, cultural heritage and art; eGovernment and eBusiness; digital commerce and the customer experience; social media and the metaverse. Part IV: virtual and augmented reality; autonomous vehicles and urban mobility; product and robot design; HCI and wellbeing; HCI and cybersecurity.
Hci International 2022 - Posters
The four-volume set CCIS 1580, CCIS 1581, CCIS 1582, and CCIS 1583 contains the extended abstracts of the posters presented during the 24th International Conference on Human-Computer Interaction, HCII 2022, which was held virtually in June - July 2022. The total of 1276 papers and 275 posters included in the 40 HCII 2021 proceedings volumes was carefully reviewed and selected from 5583 submissions.The posters presented in these four volumes are organized in topical sections as follows: Part I: user experience design and evaluation; visual design and visualization; data, information and knowledge; interacting with AI; universal access, accessibility and design for aging. Part II: multimodal and natural interaction; perception, cognition, emotion and psychophysiological monitoring; human motion modelling and monitoring; IoT and intelligent living environments. Part III: learning technologies; HCI, cultural heritage and art; eGovernment and eBusiness; digital commerce and the customer experience; social media and the metaverse. Part IV: virtual and augmented reality; autonomous vehicles and urban mobility; product and robot design; HCI and wellbeing; HCI and cybersecurity.
Hci International 2022 Posters
The four-volume set CCIS 1580, CCIS 1581, CCIS 1582, and CCIS 1583 contains the extended abstracts of the posters presented during the 24th International Conference on Human-Computer Interaction, HCII 2022, which was held virtually in June - July 2022. The total of 1276 papers and 275 posters included in the 40 HCII 2021 proceedings volumes was carefully reviewed and selected from 5583 submissions.The posters presented in these four volumes are organized in topical sections as follows: Part I: user experience design and evaluation; visual design and visualization; data, information and knowledge; interacting with AI; universal access, accessibility and design for aging. Part II: multimodal and natural interaction; perception, cognition, emotion and psychophysiological monitoring; human motion modelling and monitoring; IoT and intelligent living environments. Part III: learning technologies; HCI, cultural heritage and art; eGovernment and eBusiness; digital commerce and the customer experience; social media and the metaverse. Part IV: virtual and augmented reality; autonomous vehicles and urban mobility; product and robot design; HCI and wellbeing; HCI and cybersecurity.
AI and Blockchain Technology in 6g Wireless Network
This book highlights future research directions and latent solutions by integrating AI and Blockchain 6G networks, comprising computation efficiency, algorithms robustness, hardware development and energy management. This book brings together leading researchers in Academia and industry from diverse backgrounds to deliver to the technical community an outline of emerging technologies, advanced architectures, challenges, open issues and future directions of 6G networks. This book is written for researchers, professionals and students to learn about the integration of technologies such as AI and Blockchain into 6G network and communications. This book addresses the topics such as consensus protocol, architecture, intelligent dynamic resource management, security and privacy in 6G to integrate AI and Blockchain and new real-time application with further research opportunities.
E-Infrastructure and E-Services for Developing Countries
This book constitutes the thoroughly refereed proceedings of the 13th International Conference on e-Infrastructure and e-Services for Developing Countries, AFRICOMM 2021, held in Zanzibar, Tanzania, in December 2021. The 31 full papers presented were carefully selected from 78 submissions. The papers discuss issues and trends, resent research, innovation and experiences related to e-Infrastructure and e-Services along with their associated policy and regulations with a deep focus on developing countries. In recognition of the challenges imposed by the COVID-19 pandemic, the conference organized a workshop to share experience on digital leaning and teaching at the time of pandemic, which garnered 3 papers.
Computer Vision Projects with Pytorch
Design and develop end-to-end, production-grade computer vision projects for real-world industry problems. This book discusses computer vision algorithms and their applications using PyTorch.The book begins with the fundamentals of computer vision: convolutional neural nets, RESNET, YOLO, data augmentation, and other regularization techniques used in the industry. And then it gives you a quick overview of the PyTorch libraries used in the book. After that, it takes you through the implementation of image classification problems, object detection techniques, and transfer learning while training and running inference. The book covers image segmentation and an anomaly detection model. And it discusses the fundamentals of video processing for computer vision tasks putting images into videos. The book concludes with an explanation of the complete model building process for deep learning frameworks using optimized techniques with highlights on model AI explainability.After reading this book, you will be able to build your own computer vision projects using transfer learning and PyTorch. What You Will LearnSolve problems in computer vision with PyTorch.Implement transfer learning and perform image classification, object detection, image segmentation, and other computer vision applicationsDesign and develop production-grade computer vision projects for real-world industry problemsInterpret computer vision models and solve business problemsWho This Book Is ForData scientists and machine learning engineers interested in building computer vision projects and solving business problems
Information and Communication Technologies for Development. Freedom and Social Inclusion in a Connected World
This book constitutes the refereed proceedings of the 17th IFIP WG 9.4 International Conference on Social Implications of Computers in Developing Countries, ICT4D 2022, which was supposed to be held in Lima, Peru, in May 2021, but was held virtually instead due to the COVID-19 pandemic.The 40 revised full papers presented were carefully reviewed and selected from 58 submissions. The papers present a wide range of perspectives and disciplines including (but not limited to) public administration, entrepreneurship, business administration, information technology for development, information management systems, organization studies, philosophy, and management. They are organized in the following topical sections: digital platforms and gig economy; education and health; inclusion and participation; and business innovation and data privacy.
Digital Forensics and Cyber Crime
This book constitutes the refereed proceedings of the 12th International Conference on Digital Forensics and Cyber Crime, ICDF2C 2021, held in Singapore in December 2021. Due to COVID-19 pandemic the conference was held virtually.The 22 reviewed full papers were selected from 52 submissions and present digital forensic technologies and techniques for a variety of applications in criminal investigations, incident response and information security. The focus of ICDS2C 2021 was on various applications and digital evidence and forensics beyond traditional cybercrime investigations and litigation.
Applied Recommender Systems with Python
This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an essential part of every internet-based business today. You'll start by learning basic concepts of recommender systems, with an overview of different types of recommender engines and how they function. Next, you will see how to build recommender systems with traditional algorithms such as market basket analysis and content- and knowledge-based recommender systems with NLP. The authors then demonstrate techniques such as collaborative filtering using matrix factorization and hybrid recommender systems that incorporate both content-based and collaborative filtering techniques. This is followed by a tutorial on building machine learning-based recommender systems using clustering and classification algorithms like K-means and random forest. The last chapters cover NLP, deep learning, and graph-based techniques to build a recommender engine. Each chapter includes data preparation, multiple ways to evaluate and optimize the recommender systems, supporting examples, and illustrations. By the end of this book, you will understand and be able to build recommender systems with various tools and techniques with machine learning, deep learning, and graph-based algorithms. What You Will LearnUnderstand and implement different recommender systems techniques with PythonEmploy popular methods like content- and knowledge-based, collaborative filtering, market basket analysis, and matrix factorization Build hybrid recommender systems that incorporate both content-based and collaborative filteringLeverage machine learning, NLP, and deep learning for building recommender systems Who This Book Is ForData scientists, machine learning engineers, and Python programmers interested in building and implementing recommender systems to solve problems.
Artificial Intelligence in Medical Sciences and Psychology
Get started with artificial intelligence for medical sciences and psychology. This book will help healthcare professionals and technologists solve problems using machine learning methods, computer vision, and natural language processing (NLP) techniques. The book covers ways to use neural networks to classify patients with diseases. You will know how to apply computer vision techniques and convolutional neural networks (CNNs) to segment diseases such as cancer (e.g., skin, breast, and brain cancer) and pneumonia. The hidden Markov decision making process is presented to help you identify hidden states of time-dependent data. In addition, it shows how NLP techniques are used in medical records classification. This book is suitable for experienced practitioners in varying medical specialties (neurology, virology, radiology, oncology, and more) who want to learn Python programming to help them work efficiently. It is also intended for data scientists, machine learning engineers, medical students, and researchers. What You Will Learn Apply artificial neural networks when modelling medical data Know the standard method for Markov decision making and medical data simulation Understand survival analysis methods for investigating data from a clinical trial Understand medical record categorization Measure personality differences using psychological models Who This Book Is For Machine learning engineers and software engineers working on healthcare-related projects involving AI, including healthcare professionals interested in knowing how AI can improve their work setting
Automated Deep Learning Using Neural Network Intelligence
Optimize, develop, and design PyTorch and TensorFlow models for a specific problem using the Microsoft Neural Network Intelligence (NNI) toolkit. This book includes practical examples illustrating automated deep learning approaches and provides techniques to facilitate your deep learning model development. The first chapters of this book cover the basics of NNI toolkit usage and methods for solving hyper-parameter optimization tasks. You will understand the black-box function maximization problem using NNI, and know how to prepare a TensorFlow or PyTorch model for hyper-parameter tuning, launch an experiment, and interpret the results. The book dives into optimization tuners and the search algorithms they are based on: Evolution search, Annealing search, and the Bayesian Optimization approach. The Neural Architecture Search is covered and you will learn how to develop deep learning models from scratch. Multi-trial and one-shot searching approaches of automatic neural network design are presented. The book teaches you how to construct a search space and launch an architecture search using the latest state-of-the-art exploration strategies: Efficient Neural Architecture Search (ENAS) and Differential Architectural Search (DARTS). You will learn how to automate the construction of a neural network architecture for a particular problem and dataset. The book focuses on model compression and feature engineering methods that are essential in automated deep learning. It also includes performance techniques that allow the creation of large-scale distributive training platforms using NNI. After reading this book, you will know how to use the full toolkit of automated deep learning methods. The techniques and practical examples presented in this book will allow you to bring your neural network routines to a higher level.What You Will LearnKnow the basic concepts of optimization tuners, search space, and trialsApply different hyper-parameter optimization algorithms to develop effective neural networksConstruct new deep learning models from scratchExecute the automated Neural Architecture Search to create state-of-the-art deep learning modelsCompress the model to eliminate unnecessary deep learning layersWho This Book Is For Intermediate to advanced data scientists and machine learning engineers involved in deep learning and practical neural network development
Artificial Neural Networks and Machine Learning - Icann 2022
The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022. The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications.
From Animals to Animats 16
This book constitutes the refereed proceedings of the 16th International Conference on Simulation of Adaptive Behavior, SAB 2022, held in Cergy-Pontoise, France, in September 2022.The 17 papers presented in this volume were carefully reviewed and selected from 23 submissions. They were organized in topical sections as follows: Embodiment; Brain-Inspired Control, Adaptation, and Learning; Bio-inspired Vision and navigation; Affective and Social Cognition and Collective Intelligence.
