This book is for anyone who wants to gain an understanding of Blockchain technology and its potential. The book is research-oriented and covers different verticals of Blockchain technology. It discusses the characteristics and features of Blockchain, includes techniques, challenges, and future trends, along with case studies for deeper understanding. Blockchain Technology: Exploring Opportunities, Challenges, and Applications covers the core concepts related to Blockchain technology starting from scratch. The algorithms, concepts, and application areas are discussed according to current market trends and industry needs. It presents different application areas of industry and academia and discusses the characteristics and features of this technology. It also explores the challenges and future trends and provides an understanding of new opportunities. This book is for anyone at the beginner to intermediate level that wants to learn about the core concepts related to Blockchain technology.

"High Performance Deformable Image Registration Algorithms for Manycore Processors" develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans.

This book demonstrates:

How to redesign widely used image registration algorithms so as to best expose the underlying parallelism available in these algorithmsHow to pose and implement the parallel versions of the algorithms within the single instruction, multiple data (SIMD) model supported by GPUsProgramming "tricks" that can help readers develop other image processing algorithms, including registration algorithms for the GPU

This book presents watermarking algorithms derived from signal processing methods such as wavelet transform, matrix decomposition and cosine transform to address the limitations of current technologies. For each algorithm, mathematical foundations are explained with analysis conducted to evaluate performances on robotness and efficiency. Combining theories and practice, it is suitable for information security researchers and industrial engineers.

This book is for anyone who wants to gain an understanding of Blockchain technology and its potential. The book is research-oriented and covers different verticals of Blockchain technology. It discusses the characteristics and features of Blockchain, includes techniques, challenges, and future trends, along with case studies for deeper understanding. Blockchain Technology: Exploring Opportunities, Challenges, and Applications covers the core concepts related to Blockchain technology starting from scratch. The algorithms, concepts, and application areas are discussed according to current market trends and industry needs. It presents different application areas of industry and academia and discusses the characteristics and features of this technology. It also explores the challenges and future trends and provides an understanding of new opportunities. This book is for anyone at the beginner to intermediate level that wants to learn about the core concepts related to Blockchain technology.

This book proposes tools for analysis of multidimensional and metric data, by establishing a state-of-the-art of the existing solutions and developing new ones. It mainly focuses on visual exploration of these data by a human analyst, relying on a 2D or 3D scatter plot display obtained through Dimensionality Reduction. Performing diagnosis of an energy system requires identifying relations between observed monitoring variables and the associated internal state of the system. Dimensionality reduction, which allows to represent visually a multidimensional dataset, constitutes a promising tool to help domain experts to analyse these relations. This book reviews existing techniques for visual data exploration and dimensionality reduction such as tSNE and Isomap, and proposes new solutions to challenges in that field. In particular, it presents the new unsupervised technique ASKI and the supervised methods ClassNeRV and ClassJSE. Moreover, MING, a new approach for local map quality evaluation is also introduced. These methods are then applied to the representation of expert-designed fault indicators for smart-buildings, I-V curves for photovoltaic systems and acoustic signals for Li-ion batteries.

The increasing complexity of telecommunication networks requires us to develop adequate mathematical models. We must find their characteristics, optimize them subject to chosen criteria, and develop the corresponding control algorithms. Multidimensional queueing models are used to design and optimize modern and next-generation networks (NGN). The central problem of the related mathematical theory is to apply multidimensional and large-size queueing models to improve efficiency. In this book new methods are successively developed and applied to solve related problems. The book is recommended for researchers engaged with the mathematical theory of telecommunications traffic.

Offers fundamental theories and practical and more sophisticated applications of Evolutionary Computation in varied industries Provides insight into various platforms, paradigms, techniques, and tools used in Evolutionary Computation for diverse fields Presents an understanding related to optimization, performance tuning, virtualization, deployment models, and their applications Covers a variety of applications for social and essential models and is based on real life examples Useful for decision making based on optimized data through Evolutionary Computation in multi-dimensions

This book provides a platform for academics and practitioners for sharing innovative results, approaches, developments, and research projects in computer science and information technology, focusing on the latest challenges in advanced computing and solutions introducing mathematical and engineering approaches. The book presents discussions in the area of advances and challenges of modern computer science, including telecommunications and signal processing, machine learning and artificial intelligence, intelligent control systems, modeling and simulation, data science and big data, data visualization and graphics systems, distributed, cloud and high-performance computing, and software engineering. The papers included are presented at TELECCON 2019 organized by Peter the Great St. Petersburg University during November 18-19, 2019.

This book presents a unique, understandable view of machine learning using many practical examples and access to free professional software and open source code. The user-friendly software can immediately be used to apply everything you learn in the book without the need for programming. After an introduction to machine learning and artificial intelligence, the chapters in Part II present deeper explanations of machine learning algorithms, performance evaluation of machine learning models, and how to consider data in machine learning environments. In Part III the author explains automatic speech recognition, and in Part IV biometrics recognition, face- and speaker-recognition. By Part V the author can then explain machine learning by example, he offers cases from real-world applications, problems, and techniques, such as anomaly detection and root cause analyses, business process improvement, detecting and predicting diseases, recommendation AI, several engineering applications, predictive maintenance, automatically classifying datasets, dimensionality reduction, and image recognition. Finally, in Part VI he offers a detailed explanation of the AI-TOOLKIT, software he developed that allows the reader to test and study the examples in the book and the application of machine learning in professional environments. The author introduces core machine learning concepts and supports these with practical examples of their use, so professionals will appreciate his approach and use the book for self-study. It will also be useful as a supplementary resource for advanced undergraduate and graduate courses on machine learning and artificial intelligence.

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

This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions. This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns. A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.

Blockchain and other trustless systems have gone from being relatively obscure technologies, which were only known to a small community of computer scientists and cryptologists, to mainstream phenomena that are now considered powerful game changers for many industries. This book explores and assesses real-world use cases and case studies on blockchain and related technologies. The studies describe the respective applications and address how these technologies have been deployed, the rationale behind their application, and finally, their outcomes. The book shares a wealth of experiences and lessons learned regarding financial markets, energy, SCM, healthcare, law and compliance. Given its scope, it is chiefly intended for academics and practitioners who want to learn more about blockchain applications.

Provides a comprehensive review on new swarm intelligence Offers practical implementation of PSO with MATLAB code Presents statistical analysis techniques so that researchers can analyze their own experiment design Discusses swarm intelligence algorithms in social sector and oil and gas industries Covers recent findings and the implementation techniques to Machine Learning

Nature-based algorithms play an important role among artificial intelligence algorithms. Among them are global optimization algorithms called swarm intelligence algorithms. These algorithms that use the behavior of simple agents and various ways of cooperation between them, are used to solve specific problems that are defined by the so-called objective function. Swarm intelligence algorithms are inspired by the social behavior of various animal species, e.g. ant colonies, bird flocks, bee swarms, schools of fish, etc. The family of these algorithms is very large and additionally includes various types of modifications to enable swarm intelligence algorithms to solve problems dealing with areas other than those for which they were originally developed. This book presents 24 swarm algorithms together with their modifications and practical applications. Each chapter is devoted to one algorithm. It contains a short description along with a pseudo-code showing the various stages of its operation. In addition, each chapter contains a description of selected modifications of the algorithm and shows how it can be used to solve a selected practical problem. This book should also be useful for undergraduate and postgraduate students studying nature-based optimization algorithms, and can be a helpful tool for learning these algorithms, along with their modifications and practical applications. In addition, it can be a useful source of knowledge for scientists working in the field of artificial intelligence, as well as for engineers interested in using this type of algorithms in their work. If the reader wishes to expand his knowledge beyond the basics of swarm intelligence algorithms presented in this book and is interested in more detailed information, we recommend the book "Swarm Intelligence Algorithms: A Tutorial" (Edited by A. Slowik, CRC Press, 2020). It contains a detailed explanation of how each algorithm works, along with relevant program codes in Matlab and the C ++ programming language, as well as numerical examples illustrating step-by-step how individual algorithms work.

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

This book is a unique and note-worthy enquiry into the implications of algorithmic knowledge for human subjectivity Eran Fisher provides timely insight on a relevant field of research, i.e., how algorithms impact our society This book will make a timely contribution to the social study of algorithms and will prove especially valuable for scholars working at the intersections of media and communication studies, internet studies, information studies, the sociology of technology, the philosophy of technology, and science and technology studies

Do you have creative ideas that you wish you could transform into code? Do you want to boost your problem solving and logic skills? Do you want to enhance your career by adopting an algorithmic mindset? In our increasingly digital world, coding is an essential skill. Communicating an algorithm to a machine to perform a set of tasks is vital. Beginner's Guide to Code Algorithms: Experiments to Enhance Productivity and Solve Problems written by Deepankar Maitra teaches you how to think like a programmer. The author unravels the secret behind writing code - building a good algorithm. Algorithmic thinking leads to asking the right question and enables a shift from issue resolution to value creation. Having this mindset will make you more marketable to employers. This book takes you on a problem-solving journey to expand your mind and increase your willingness to experiment with code. You will: Learn the art of building an algorithm through hands-on exercises Understand how to develop code for inspiring productivity concepts Build a mentality of developing algorithms to solve problems Develop, test, review, and improve code through guided experimentation This book is designed to develop a culture of logical thinking through intellectual stimulation. It will benefit students and teachers of programming, business professionals, as well as experienced users of Microsoft Excel who wish to become proficient with macros.

This book gathers selected high-quality research papers presented at Arab Conference for Emerging Technologies 2020 organized virtually in Cairo during 21-23 June 2020. This book emphasizes the role and recent developments in the field of emerging technologies and artificial intelligence, and related technologies with a special focus on sustainable development in the Arab world. The book targets high-quality scientific research papers with applications, including theory, practical, prototypes, new ideas, case studies and surveys which cover machine learning applications in data science.

This book provides a literature review of techniques used to pass from continuous to combinatorial space, before discussing a detailed example with individual steps of how cuckoo search (CS) can be adapted to solve combinatorial optimization problems. It demonstrates the application of CS to three different problems and describes their source code. The content is divided into five chapters, the first of which provides a technical description, together with examples of combinatorial search spaces. The second chapter summarizes a diverse range of methods used to solve combinatorial optimization problems. In turn, the third chapter presents a description of CS, its formulation and characteristics. In the fourth chapter, the application of discrete cuckoo search (DCS) to solve three POCs (the traveling salesman problem, quadratic assignment problem and job shop scheduling problem) is explained, focusing mainly on a reinterpretation of the terminology used in CS and its source of inspiration. In closing, the fifth chapter discusses random-key cuckoo search (RKCS) using random keys to represent positions found by cuckoo search in the TSP and QAP solution space.

Artificial Intelligence is a seemingly neutral technology, but it is increasingly used to manage workforces and make decisions to hire and fire employees. Its proliferation in the workplace gives the impression of a fairer, more efficient system of management. A machine can't discriminate, after all. Augmented Exploitation explores the reality of the impact of AI on workers' lives. While the consensus is that AI is a completely new way of managing a workplace, the authors show that, on the contrary, AI is used as most technologies are used under capitalism: as a smokescreen that hides the deep exploitation of workers. Going beyond platform work and the gig economy, the authors explore emerging forms of algorithmic governance and AI-augmented apps that have been developed to utilise innovative ways to collect data about workers and consumers, as well as to keep wages and worker representation under control. They also show that workers are not taking this lying down, providing case studies of new and exciting form of resistance that are springing up across the globe.

What are citizens of a free country willing to tolerate in the name of public safety? Jon Fasman journeys from the US to London - one of the most heavily surveilled cities on earth - to China and beyond, to expose the legal, political, and moral issues surrounding how the state uses surveillance technology. Automatic licence-plate readers allow police to amass a granular record of where people go, when, and for how long. Drones give the state eyes - and possibly weapons - in the skies. Algorithms purport to predict where and when crime will occur, and how big a risk a suspect has of reoffending. Specially designed tools can crack a device's encryption keys, rending all privacy protections useless. And facial recognition technology poses perhaps a more dire and lasting threat than any other form of surveillance. Jon Fasman examines how these technologies help police do their jobs, and what their use means for our privacy rights and civil liberties, exploring vital questions, such as: Should we expect to be tracked and filmed whenever we leave our homes? Should the state have access to all of the data we generate? Should private companies? What might happen if all of these technologies are combined and put in the hands of a government with scant regard for its citizens' civil liberties? Through on-the-ground reporting and vivid storytelling, Fasman explores one of the most urgent issues of our time.

This book is useful to understand and write alongside non-human agents, examine the impact of algorithms and AI on writing, and accommodate relationships with autonomous agents. This ground-breaking future-driven framework prepares scholars and practitioners to investigate and plan for the social, digital literacy, and civic implications arising from emerging technologies. This book prepares researchers, students, practitioners, and citizens to work with AI writers, virtual humans, and social robots. This book explores prompts to envision how fields and professions will change. The book's unique integration with Fabric of Digital Life, a database and structured content repository for conducting social and cultural analysis of emerging technologies, provides concrete examples throughout. Readers gain imperative direction for collaborative, algorithmic, and autonomous writing futures.

This title includes a number of Open Access chapters. Data structure and software engineering is an integral part of computer science. This volume presents new approaches and methods to knowledge sharing, brain mapping, data integration, and data storage. The author describes how to manage an organization's business process and domain data and presents new software and hardware testing methods. The book introduces a game development framework used as a learning aid in a software engineering at the university level. It also features a review of social software engineering metrics and methods for processing business information. It explains how to use Pegasys to create and manage sequence analysis workflows.

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

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