This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.

In recent years, popular media have inundated audiences with sensationalised headlines recounting data breaches, new forms of surveillance and other dangers of our digital age. Despite their regularity, such accounts treat each case as unprecedented and unique. This book proposes a radical rethinking of the history, present and future of our relations with the digital, spatial technologies that increasingly mediate our everyday lives. From smartphones to surveillance cameras, to navigational satellites, these new technologies offer visions of integrated, smooth and efficient societies, even as they directly conflict with the ways users experience them. Recognising the potential for both control and liberation, the authors argue against both acquiescence to and rejection of these technologies. Through intentional use of the very systems that monitor them, activists from Charlottesville to Hong Kong are subverting, resisting and repurposing geographic technologies. Using examples as varied as writings on the first telephones to the experiences of a feminist collective for migrant women in Spain, the authors present a revolution of everyday technologies. In the face of the seemingly inevitable dominance of corporate interests, these technologies allow us to create new spaces of affinity, and a new politics of change.

The book is a collection of invited papers on Computational Intelligence for Privacy and Security. The majority of the chapters are extended versions of works presented at the special session on Computational Intelligence for Privacy and Security of the International Joint Conference on Neural Networks (IJCNN-2010) held July 2010 in Barcelona, Spain. The book is devoted to Computational Intelligence for Privacy and Security. It provides an overview of the most recent advances on the Computational Intelligence techniques being developed for Privacy and Security. The book will be of interest to researchers in industry and academics and to post-graduate students interested in the latest advances and developments in the field of Computational Intelligence for Privacy and Security.

This book constitutes the refereed proceedings of the 27th IFIP TC 11 International Information Security Conference, SEC 2012, held in Heraklion, Crete, Greece, in June 2012. The 42 revised full papers presented together with 11 short papers were carefully reviewed and selected from 167 submissions. The papers are organized in topical sections on attacks and malicious code, security architectures, system security, access control, database security, privacy attitudes and properties, social networks and social engineering, applied cryptography, anonymity and trust, usable security, security and trust models, security economics, and authentication and delegation.

This book contains some selected papers from the International Conference on Extreme Learning Machine (ELM) 2017, held in Yantai, China, October 4-7, 2017. The book covers theories, algorithms and applications of ELM. Extreme Learning Machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental `learning particles' filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that "random hidden neurons" capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. This conference will provide a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. It gives readers a glance of the most recent advances of ELM.

Thisvolumecontainstheinvitedandregularpaperspresentedat TCS 2010, the 6thIFIP International Conference on Theoretical Computer Science, organised by IFIP Tech- cal Committee 1 (Foundations of Computer Science) and IFIP WG 2.2 (Formal - scriptions of Programming Concepts) in association with SIGACT and EATCS. TCS 2010 was part of the World Computer Congress held in Brisbane, Australia, during September 20-23, 2010 ( ). TCS 2010 is composed of two main areas: (A) Algorithms, Complexity and Models of Computation, and (B) Logic, Semantics, Speci?cation and Veri?cation. The selection process led to the acceptance of 23 papers out of 39 submissions, eachofwhichwasreviewedbythreeProgrammeCommitteemembers.TheProgramme Committee discussion was held electronically using Easychair. The invited speakers at TCS 2010 are: Rob van Glabbeek (NICTA, Australia) Bart Jacobs (Nijmegen, The Netherlands) Catuscia Palamidessi (INRIA and LIX, Paris, France) Sabina Rossi (Venice, Italy) James Harland (Australia) and Barry Jay (Australia) acted as TCS 2010 Chairs. We take this occasion to thank the members of the Programme Committees and the external reviewers for the professional and timely work; the conference Chairs for their support; the invited speakers for their scholarly contribution; and of course the authors for submitting their work to TCS 2010

This book focuses on flight vehicles and their navigational systems, discussing different forms of flight structures and their control systems, from fixed wings to rotary crafts. Software simulation enables testing of the hardware without actual implementation, and the flight simulators, mechanics, glider development and navigation systems presented here are suitable for lab-based experimentation studies. It explores laboratory testing of flight navigational sensors, such as the magnetic, acceleration and Global Positioning System (GPS) units, and illustrates the six-axis inertial measurement unit (IMU) instrumentation as well as its data acquisition methodology. The book offers an introduction to the various unmanned aerial vehicle (UAV) systems and their accessories, including the linear quadratic regulator (LQR) method for controlling the rotorcraft. It also describes a Matrix Laboratory (MATLAB) control algorithm that simulates and runs the lab-based 3 degrees of freedom (DOF) helicopter, as well as LabVIEW software used to validate controller design and data acquisition. Lastly, the book explores future developments in aviation techniques.

The authors give a detailed summary about the fundamentals and the historical background of digital communication. This includes an overview of the encoding principles and algorithms of textual information, audio information, as well as images, graphics, and video in the Internet. Furthermore the fundamentals of computer networking, digital security and cryptography are covered. Thus, the book provides a well-founded access to communication technology of computer networks, the internet and the WWW. Numerous pictures and images, a subject-index and a detailed list of historical personalities including a glossary for each chapter increase the practical benefit of this book that is well suited as well as for undergraduate students as for working practitioners.

Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from data. We focus on genetic programming in this book because it is the paradigmatic type of machine learning method for automating the generation of programs and because it has the advantage of performing a global search in the space of candidate solutions (data mining algorithms in our case), but in principle other types of search methods for this task could be investigated in the future.

Universally acclaimed as the book on garbage collection. A complete and up-to-date revision of the 2012 Garbage Collection Handbook. Thorough coverage of parallel, concurrent and real-time garbage collection algortithms including C4, Garbage First, LXR, Shenandoah, Transactional Sapphire and ZGC, and garbage collection on the GPU. Clear explanation of the trickier aspects of garbage collection, including the interface to the run-time system, handling of finalisation and weak references, and support for dynamic languages. New chapters on energy aware garbage collection, and persistence and garbage collection. The e-book includes more than 40,000 hyperlinks to algorithms, figures, glossary entries, indexed items, original research papers and much more. Backed by a comprehensive online database of over 3,400 garbage collection-related publications

In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods.

This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies.

This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.

Articles in this book examine various materials and how to determine directly the limit state of a structure, in the sense of limit analysis and shakedown analysis. Apart from classical applications in mechanical and civil engineering contexts, the book reports on the emerging field of material design beyond the elastic limit, which has further industrial design and technological applications. Readers will discover that "Direct Methods" and the techniques presented here can in fact be used to numerically estimate the strength of structured materials such as composites or nano-materials, which represent fruitful fields of future applications. Leading researchers outline the latest computational tools and optimization techniques and explore the possibility of obtaining information on the limit state of a structure whose post-elastic loading path and constitutive behavior are not well defined or well known. Readers will discover how Direct Methods allow rapid and direct access to requested information in mathematically constructive manners without cumbersome step-by-step computation. Both researchers already interested or involved in the field and practical engineers who want to have a panorama of modern methods for structural safety assessment will find this book valuable. It provides the reader with the latest developments and a significant amount of references on the topic.

This book investigates the susceptibility of intrinsic physically unclonable function (PUF) implementations on reconfigurable hardware to optical semi-invasive attacks from the chip backside. It explores different classes of optical attacks, particularly photonic emission analysis, laser fault injection, and optical contactless probing. By applying these techniques, the book demonstrates that the secrets generated by a PUF can be predicted, manipulated or directly probed without affecting the behavior of the PUF. It subsequently discusses the cost and feasibility of launching such attacks against the very latest hardware technologies in a real scenario. The author discusses why PUFs are not tamper-evident in their current configuration, and therefore, PUFs alone cannot raise the security level of key storage. The author then reviews the potential and already implemented countermeasures, which can remedy PUFs' security-related shortcomings and make them resistant to optical side-channel and optical fault attacks. Lastly, by making selected modifications to the functionality of an existing PUF architecture, the book presents a prototype tamper-evident sensor for detecting optical contactless probing attempts.

This book is an attempt to bring value to the enterprise pursuits in the areas of research and innovation around the specific issues in terms of topic selection, open data resources and researcher orientation. Over the last 300 years, industrial revolutions have had game-changing impact on societies. Presently, by and large, we are at the crossroads of the fourth industrial revolution, where phygital systems are going to play a massive role, where digital systems can simulate and go beyond the limitations of the physical world, thereby enabling a new world order. This transformation is cutting across every sphere known to mankind. The world will become a globally localized marketplace. In today's business world, sustainability is a corporate agenda. Enterprises are also aiming to be purpose-driven, adaptive and resilient to disruptions. The contributions to community and environment are part of their corporate branding. The book explores and presents a part of the open data sets from government institutions to achieve the sustainable goals at local level, in turn contributing towards global mission. As the topic suggests, the authors are looking at some of the specific issues in the areas of environment, agriculture and health care through the lens of data science. The authors believe that the above three areas chosen have deep relevance in today's world. The intent is to explore these issues from a data and analytics perspective and identify cracks through which deeper inroads can be made. Conscious efforts have been taken to make use of all the major data science techniques like prediction, classification, clustering, and correlation. Given the above background, deeper waters will be explored through the contents of this book.

Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. * Foundational reinforcement learning concepts and methods * The most popular deep reinforcement learning agents solving high-dimensional environments * Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

This book provides the most updated information of how membrane lipids mediate protein signaling from studies carried out in animal and plant cells. Also, there are some chapters that go beyond and expand these studies of protein-lipid interactions at the structural level. The book begins with a literature review from investigations associated to sphingolipids, followed by studies that describe the role of phosphoinositides in signaling and closing with the function of other key lipids in signaling at the plasma membrane and intracellular organelles.

Graph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, such as approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computational molecular biology and computational chemistry. Centered around the fundamental issue of graph isomorphism, this text goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. This book introduces graph algorithms on an intuitive basis followed by a detailed exposition in a literate programming style, with correctness proofs as well as worst-case analyses. Furthermore, full C++ implementations of all algorithms presented are given using the LEDA library of efficient data structures and algorithms.

The book offers an original view on channel coding, based on a unitary approach to block and convolutional codes for error correction. It presents both new concepts and new families of codes. For example, lengthened and modified lengthened cyclic codes are introduced as a bridge towards time-invariant convolutional codes and their extension to time-varying versions. The novel families of codes include turbo codes and low-density parity check (LDPC) codes, the features of which are justified from the structural properties of the component codes. Design procedures for regular LDPC codes are proposed, supported by the presented theory. Quasi-cyclic LDPC codes, in block or convolutional form, represent one of the most original contributions of the book. The use of more than 100 examples allows the reader gradually to gain an understanding of the theory, and the provision of a list of more than 150 definitions, indexed at the end of the book, permits rapid location of sought information.

Reflects recent developments in its emphasis on randomized and approximation algorithms and communication models

All topics are considered from an algorithmic point of view stressing the implications for algorithm design

Digital Intermediation offers a new framework for understanding content creation and distribution across automated media platforms - a new mediatisation process. The book draws on empirical and theoretical research to carefully identify and describe a number of unseen digital infrastructures that contribute to a predictive media production process through technologies, institutions and automation. Field data is drawn from several international sites, including Los Angeles, San Francisco, Portland, London, Amsterdam, Munich, Berlin, Hamburg, Sydney and Cartagena. By highlighting an increasingly automated content production and distribution process, the book responds to a number of regulatory debates on the societal impact of social media platforms. It highlights emerging areas of key importance that shape the production and distribution of social media content, including micro-platformization and digital first personalities. The book explains how technologies, institutions and automation are used within agencies to increase exposure for the talent they manage, while providing inside access to the processes and requirements of producers who create content for platform algorithms. Finally, it outlines user agency as a strategy for those who seek diversity in the information they access on automated social media content distribution platforms. The findings in this book provide key recommendations for policymakers working within digital media platforms, and will be invaluable reading for students and academics interested in automated media environments.

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: multi-objective genetic programming, learning heuristics, Kaizen programming, Evolution of Everything (EvE), lexicase selection, behavioral program synthesis, symbolic regression with noisy training data, graph databases, and multidimensional clustering. It also covers several chapters on best practices and lesson learned from hands-on experience. Additional application areas include financial operations, genetic analysis, and predicting product choice. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.

Mixed-Signal Embedded Microcontrollers are commonly used in integrating analog components needed to control non-digital electronic systems. They are used in automatically controlled devices and products, such as automobile engine control systems, wireless remote controllers, office machines, home appliances, power tools, and toys. Microcontrollers make it economical to digitally control even more devices and processes by reducing the size and cost, compared to a design that uses a separate microprocessor, memory, and input/output devices. In many undergraduate and post-graduate courses, teaching of mixed-signal microcontrollers and their use for project work has become compulsory. Students face a lot of difficulties when they have to interface a microcontroller with the electronics they deal with. This book addresses some issues of interfacing the microcontrollers and describes some project implementations with the Silicon Lab C8051F020 mixed-signal microcontroller. The intended readers are college and university students specializing in electronics, computer systems engineering, electrical and electronics engineering; researchers involved with electronics based system, practitioners, technicians and in general anybody interested in microcontrollers based projects.

"Optimal Design of Distributed Control and Embedded Systems "focuses on the design of special control and scheduling algorithms based on system structural properties as well as on analysis of the influence of induced time-delay on systems performances. It treats the optimal design of distributed and embedded control systems (DCESs) with respect to communication and calculation-resource constraints, quantization aspects, and potential time-delays induced by the associated communication and calculation model.

Particular emphasis is put on optimal control signal scheduling based on the system state. In order to render this complex optimization problem feasible in real time, a time decomposition is based on periodicity induced by the static scheduling is operated. The authors present a co-design approach which subsumes the synthesis of the optimal control laws and the generation of an optimal schedule of control signals on real-time networks as well as the execution of control tasks on a single processor. The authors also operate a control structure modification or a control switching based on a thorough analysis of the influence of the induced time-delay system influence on stability and system performance in order to optimize DCES performance in case of calculation and communication resource limitations. Although the richness and variety of classes of DCES preclude a completely comprehensive treatment or a single best method of approaching them all, this co-design approach has the best chance of rendering this problem feasible and finding the optimal or some sub-optimal solution. The text is rounded out with references to such applications as car suspension and unmanned vehicles.

"Optimal Design of Distributed Control and Embedded Systems" will be of most interest to academic researchers working on the mathematical theory of DCES but the wide range of environments in which they are used also promotes the relevance of the text for control practitioners working in the avionics, automotive, energy-production, space exploration and many other industries."

A best-seller in its French edition, the construction of this book is original and its success in the French market demonstrates its appeal. It is based on three principles: 1. An organization of the chapters by families of algorithms : exhaustive search, divide and conquer, etc. At the contrary, there is no chapter only devoted to a systematic exposure of, say, algorithms on strings. Some of these will be found in different chapters. 2. For each family of algorithms, an introduction is given to the mathematical principles and the issues of a rigorous design, with one or two pedagogical examples. 3. For its most part, the book details 150 problems, spanning on seven families of algorithms. For each problem, a precise and progressive statement is given. More important, a complete solution is detailed, with respect to the design principles that have been presented ; often, some classical errors are pointed at. Roughly speaking, two thirds of the book are devoted to the detailed rational construction of the solutions.

This book presents the original concepts and modern techniques for specification, synthesis, optimisation and implementation of parallel logical control devices. It deals with essential problems of reconfigurable control systems like dependability, modularity and portability. Reconfigurable systems require a wider variety of design and verification options than the application-specific integrated circuits. The book presents a comprehensive selection of possible design techniques. The diversity of the modelling approaches covers Petri nets, state machines and activity diagrams. The preferences of the presented optimization and synthesis methods are not limited to increasing of the efficiency of resource use. One of the biggest advantages of the presented methods is the platform independence, the FPGA devices and single board computers are some of the examples of possible platforms. These issues and problems are illustrated with practical cases of complete control systems. If you expect a new look at the reconfigurable systems designing process or need ideas for improving the quality of the project, this book is a good choice.g process or need ideas for improving the quality of the project, this book is a good choice.