Asynchronous On-Chip Networks and Fault-Tolerant Techniques is the first comprehensive study of fault-tolerance and fault-caused deadlock effects in asynchronous on-chip networks, aiming to overcome these drawbacks and ensure greater reliability of applications. As a promising alternative to the widely used synchronous on-chip networks for multicore processors, asynchronous on-chip networks can be vulnerable to faults even if they can deliver the same performance with much lower energy and area compared with their synchronous counterparts - faults can not only corrupt data transmission but also cause a unique type of deadlock. By adopting a new redundant code along with a dynamic fault detection and recovery scheme, the authors demonstrate that asynchronous on-chip networks can be efficiently hardened to tolerate both transient and permanent faults and overcome fault-caused deadlocks. This book will serve as an essential guide for researchers and students studying interconnection networks, fault-tolerant computing, asynchronous system design, circuit design and on-chip networking, as well as for professionals interested in designing fault-tolerant and high-throughput asynchronous circuits.

Digital Image Processing with C++ presents the theory of digital image processing, and implementations of algorithms using a dedicated library. Processing a digital image means transforming its content (denoising, stylizing, etc.), or extracting information to solve a given problem (object recognition, measurement, motion estimation, etc.). This book presents the mathematical theories underlying digital image processing, as well as their practical implementation through examples of algorithms implemented in the C++ language, using the free and easy-to-use CImg library. Chapters cover in a broad way the field of digital image processing and proposes practical and functional implementations of each method theoretically described. The main topics covered include filtering in spatial and frequency domains, mathematical morphology, feature extraction and applications to segmentation, motion estimation, multispectral image processing and 3D visualization. Students or developers wishing to discover or specialize in this discipline, teachers and researchers wishing to quickly prototype new algorithms, or develop courses, will all find in this book material to discover image processing or deepen their knowledge in this field.

'One of the best software design books of all time' - BookAuthority Cory Althoff is a self-taught programmer. After a year of self-study, he learned to program well enough to land a job as a software engineer II at eBay. But once he got there, he realised he was severely under-prepared. He was overwhelmed by the amount of things he needed to know but hadn't learned. His journey learning to program, and his experience in first software engineering job were the inspiration for this book. This book is not just about learning to program, although you will learn to code. If you want to program professionally, it is not enough to learn to code; that is why, in addition to helping you learn to program, Althoff also cover the rest of the things you need to know to program professionally that classes and books don't teach you. The Self-taught Programmer is a roadmap, a guide to take you from writing your first Python program to passing your first technical interview. The book is divided into five sections: 1. Learn to program in Python 3 and build your first program. 2. Learn object-oriented programming and create a powerful Python program to get you hooked. 3. Learn to use tools like Git, Bash and regular expressions. Then use your new coding skills to build a web scraper. 4. Study computer science fundamentals like data structures and algorithms. 5. Finish with best coding practices, tips for working with a team and advice on landing a programming job. You can learn to program professionally. The path is there. Will you take it? From the author I spent one year writing The Self-Taught Programmer. It was an exciting and rewarding experience. I treated my book like a software project. After I finished writing it, I created a program to pick out all of the code examples from the book and execute them in Python to make sure all 300+ examples worked properly. Then I wrote software to add line numbers and color to every code example. Finally, I had a group of 200 new programmers 'beta read' the book to identify poorly explained concepts and look for any errors my program missed. I hope you learn as much reading my book as I did writing it. Best of luck with your programming!

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.

Are you a programmer who wants to get started quickly in a new language? This book is for you. Are you a novice who wants to learn to program? This book is not for you. Are you a Python programmer who needs encyclopaedic information? This book is not for you. Like any mainstream language, Python has loops, if statements, assignment statements, functions, etc. I'll show you what these look like in Python. I won't waste your time telling you what they're good for. Python has features you may not be familiar with--iterators, list comprehensions, maybe even dictionaries. I'll spend more time on these. I'll cover some of the library functions I found most immediately useful, and tell you where to find more. In short, this book will help you hit the ground running. Next week, you'll be ready to buy that Python encyclopaedia.

Since databases are the primary repositories of information for today's organizations and governments, database security has become critically important. Introducing the concept of multilevel security in relational databases, this book provides a comparative study of the various models that support multilevel security policies in the relational database-illustrating the strengths and weaknesses of each model. Multilevel Security for Relational Databases covers multilevel database security concepts along with many other multilevel database security models and techniques. It presents a prototype that readers can implement as a tool for conducting performance evaluations to compare multilevel secure database models. The book supplies a complete view of an encryption-based multilevel security database model that integrates multilevel security for the relational database with a system that encrypts each record with an encryption key according to its security class level. This model will help you utilize an encryption system as a second security layer over the multilevel security layer for the database, reduce the multilevel database size, and improve the response time of data retrieval from the multilevel database. Considering instance-based multilevel database security, the book covers relational database access controls and examines concurrency control in multilevel database security systems. It includes database encryption algorithms, simulation programs, and Visual studio and Microsoft SQL Server code.

This book describes a cross-domain architecture and design tools for networked complex systems where application subsystems of different criticality coexist and interact on networked multi-core chips. The architecture leverages multi-core platforms for a hierarchical system perspective of mixed-criticality applications. This system perspective is realized by virtualization to establish security, safety and real-time performance. The impact further includes a reduction of time-to-market, decreased development, deployment and maintenance cost, and the exploitation of the economies of scale through cross-domain components and tools. Describes an end-to-end architecture for hypervisor-level, chip-level, and cluster level. Offers a solution for different types of resources including processors, on-chip communication, off-chip communication, and I/O. Provides a cross-domain approach with examples for wind-power, health-care, and avionics. Introduces hierarchical adaptation strategies for mixed-criticality systems Provides modular verification and certification methods for the seamless integration of mixed-criticality systems. Covers platform technologies, along with a methodology for the development process. Presents an experimental evaluation of technological results in cooperation with industrial partners. The information in this book will be extremely useful to industry leaders who design and manufacture products with distributed embedded systems in mixed-criticality use-cases. It will also benefit suppliers of embedded components or development tools used in this area. As an educational tool, this material can be used to teach students and working professionals in areas including embedded systems, computer networks, system architecture, dependability, real-time systems, and avionics, wind-power and health-care systems.

GPS Tracking with Java EE Components: Challenges of Connected Cars highlights how the self-driving car is actually changing the automotive industry, from programing embedded software to hosting services and data crunching, in real time, with really big data. The book analyzes how the challenges of the Self Driving Car (SDC) exceed the limits of a classical GPS Tracking System (GTS.) It provides a guidebook on setting up a tracking system by customizing its components. It also provides an overview of the prototyping and modeling process, and how the reader can modify this process for his or her own software. Every component is introduced in detail and includes a number of design decisions for development. The book introduces Java EE (JEE) Modules, and shows how they can be combined to a customizable GTS, and used as seed components to enrich existing systems with live tracking. The book also explores how to merge tracking and mapping to guide SDCs, and focuses on client server programming to provide useful information. It also discusses the challenges involved with the live coordination of moving cars. This book is designed to aid GTS developers and engineers in the automotive industry. It can also help Java Developers, not only interested in GPS Tracking, but in modern software design from many individual modules. Source code and sample applications will be available on the book's website.

This book is a theoretical and practical deep dive into the craft of worldbuilding for video games, with an explicit focus on how different job disciplines contribute to worldbuilding. In addition to providing lenses for recognizing the various components in creating fictional and digital worlds, the author positions worldbuilding as a reciprocal and dynamic process, a process which acknowledges that worldbuilding is both created by and instrumental in the design of narrative, gameplay, art, audio, and more. Collaborative Worldbuilding for Video Games encourages mutual respect and collaboration among teams and provides game writers and narrative designers tools for effectively incorporating other job roles into their own worldbuilding practice and vice versa. Features: Provides in-depth exploration of worldbuilding via respective job disciplines Deep dives and case studies into a variety of games, both AAA and indie Includes boxed articles for deeper interrogation and exploration of key ideas Contains templates and checklists for practical tips on worldbuilding

A more accessible approach than most competitor texts, which move into advanced, research-level topics too quickly for today's students. Part I is comprehensive in providing all necessary mathematical underpinning, particularly for those who need more opportunity to develop their mathematical competence. More confident students may move directly to Part II and dip back into Part I as a reference. Ideal for use as an introductory text for courses in quantum computing. Fully worked examples illustrate the application of mathematical techniques. Exercises throughout develop concepts and enhance understanding. End-of-chapter exercises offer more practice in developing a secure foundation.

Told over a series of daily journal logs, One-Week Dungeons: Diaries of a Seven-Day Roguelike Challenge chronicles the journeys of eleven 7DRL participants as they race to build their dream games before the clock expires.

Making a great board game and pitching it to publishers are two completely different things. If you've got a game that you want to share with the world but don't know what to do next, this book will help you navigate through exactly what steps to take. You'll discover: How to find the right publisher Exactly what publishers are looking for How to create a sell sheet that will actually sell your game How to negotiate the best deal and get paid more for your game What to look out for in contracts to make sure you don't get exploited You'll learn from Joe's experiences as a full-time board game designer and instructor, along with tips and stories from a dozen other published designers, plus the exact things that publishers want. Direct from 16 established publishers.

Tackles a topic in a concise and accessible way that most believe too advanced to pick up easily. Author has over 40 years teaching and industry experience which they utilize in this book. Contains an appendix with extended code and examples of topics discussed in text.

This new volume provides the information needed to understand the simplex method, the revised simplex method, dual simplex method, and more for solving linear programming problems. Following a logical order, the book first gives a mathematical model of the linear problem programming and describes the usual assumptions under which the problem is solved. It gives a brief description of classic algorithms for solving linear programming problems as well as some theoretical results. It goes on to explain the definitions and solutions of linear programming problems, outlining the simplest geometric methods and showing how they can be implemented. Practical examples are included along the way. The book concludes with a discussion of multi-criteria decision-making methods. Advances in Optimization and Linear Programming is a highly useful guide to linear programming for professors and students in optimization and linear programming.

It explores a variety of modern applications in soft computing, including bioinspired computing, reconfigurable computing, fuzzy logic, fusion-based learning, intelligent healthcare systems, bioinformatics, data mining, functional approximation, genetic and evolutionary algorithms, hybrid models, machine learning, meta heuristics, neuro fuzzy system, and optimization principles. The book acts as a reference book for AI developers, researchers, and academicians as it addresses the recent technological developments in the field of soft computing.

All games are potentially transformative experiences because they engage the player in dynamic action. When repurposed in an educational context, even highly popular casual games played online to pass the time can engage players in a way that deepens learning. Games as Transformative Experiences for Critical Thinking, Cultural Awareness, and Deep Learning: Strategies & Resources examines the learning value of a wide variety of games across multiple disciplines. Organized just like a well-made game, the book is divided into four parts highlighting classroom experiences, community and culture, virtual learning, and interdisciplinary instruction. The author crosses between the high school and college classroom and addresses a range of disciplines, both online and classroom practice, the design of curriculum, and the transformation of assessment practices. In addition to a wealth of practical exercises, resources, and lesson ideas, the book explains how to use a wide and diverse range of games from casual to massively multiplayer online games for self-improvement as well as classroom situations.

Discusses concepts such as Basic Programming Principles, OOP Principles, Database Programming, GUI Programming, Network Programming, Data Analytics and Visualization, Statistical Analysis, Virtual Reality, Web Development, Machine Learning, Deep Learning Provides the code and the output for all the concepts discussed Includes a case study at the end of each chapter

Videogames and Agency explores the trend in videogames and their marketing to offer a player higher volumes, or even more distinct kinds, of player freedom. The book offers a new conceptual framework that helps us understand how this freedom to act is discussed by designers, and how that in turn reflects in their design principles. What can we learn from existing theories around agency? How do paratextual materials reflect design intention with regards to what the player can and cannot do in a videogame? How does game design shape the possibility space for player action? Through these questions and selected case studies that include AAA and independent games alike, the book presents a unique approach to studying agency that combines game design, game studies, and game developer discourse. By doing so, the book examines what discourses around player action, as well as a game's design can reveal about the nature of agency and videogame aesthetics. This book will appeal to readers specifically interested in videogames, such as game studies scholars or game designers, but also to media studies students and media and screen studies scholars less familiar with digital games.

"The first edition of Deep Learning with Python is one of the best books on the subject. The second edition made it even better." - Todd Cook The bestseller revised! Deep Learning with Python, Second Edition is a comprehensive introduction to the field of deep learning using Python and the powerful Keras library. Written by Google AI researcher Francois Chollet, the creator of Keras, this revised edition has been updated with new chapters, new tools, and cutting-edge techniques drawn from the latest research. You'll build your understanding through practical examples and intuitive explanations that make the complexities of deep learning accessible and understandable. about the technology Machine learning has made remarkable progress in recent years. We've gone from near-unusable speech recognition, to near-human accuracy. From machines that couldn't beat a serious Go player, to defeating a world champion. Medical imaging diagnostics, weather forecasting, and natural language question answering have suddenly become tractable problems. Behind this progress is deep learning-a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications across every industry sector about the book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. You'll learn directly from the creator of Keras, Francois Chollet, building your understanding through intuitive explanations and practical examples. Updated from the original bestseller with over 50% new content, this second edition includes new chapters, cutting-edge innovations, and coverage of the very latest deep learning tools. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. what's inside Deep learning from first principles Image-classification, imagine segmentation, and object detection Deep learning for natural language processing Timeseries forecasting Neural style transfer, text generation, and image generation about the reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. about the author Francois Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does AI research, with a focus on abstraction and reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.

Key Features: This work aims to be the most approachable book about UX. Many books on the topic are highly specialized and are not easy to read for people who just want to understand it better. This book is easy to read and aims to popularize the UX mindset while debunking its main misconceptions. Small format size makes it easy to carry around. Includes content relatable and meaningful to the readers by taking many examples from everyday life with a conversational and light writing style. It tackles the psychology, design, research, process, strategy, and ethics behind offering the best experience with products, systems, or services. Includes a glossary.

This book is designed as a reference book and presents a systematic approach to analyze evolutionary and nature-inspired population-based search algorithms. Beginning with an introduction to optimization methods and algorithms and various enzymes, the book then moves on to provide a unified framework of process optimization for enzymes with various algorithms. The book presents current research on various applications of machine learning and discusses optimization techniques to solve real-life problems. The book compiles the different machine learning models for optimization of process parameters for production of industrially important enzymes. The production and optimization of various enzymes produced by different microorganisms are elaborated in the book It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making Covers the best-performing methods and approaches for optimization sustainable enzymes production with AI integration in a real-time environment Featuring valuable insights, the book helps readers explore new avenues leading towards multidisciplinary research discussions The book is aimed primarily at advanced undergraduates and graduates studying machine learning, data science and industrial biotechnology. Researchers and professionals will also find this book useful.

Quickly learn the most widely used front-end development language with ease and confidence React JS Foundations: Building User Interfaces with ReactJS - An Approachable Guide walks readers through the fundamental concepts of programming with the explosively popular front-end tool known as React JS. Written by an accomplished full-stack engineer, speaker, and community organizer, React JS Foundations teaches readers how to understand React and how to begin building applications with it. The book: Explains and clarifies technical terminology with relevant and modern examples to assist people new to programming understand the language Helps experienced programmers quickly get up to speed with React Is stocked throughout with practical and applicable examples of day-to-day React work Perfect for beginner, intermediate, and advanced programmers alike, React JS Foundations will quickly bring you up to speed on one of the most useful and widely used front-end languages on the web today. You can start building your first application today.

Basics of Game Design is for anyone wanting to become a professional game designer. Focusing on creating the game mechanics for data-driven games, it covers role-playing, real-time strategy, first-person shooter, simulation, and other games. Written by a 25-year veteran of the game industry, the guide offers detailed explanations of how to design the data sets used to resolve game play for moving, combat, solving puzzles, interacting with NPCs, managing inventory, and much more. Advice on developing stories for games, building maps and levels, and designing the graphical user interface is also included.

Features Teaches software design by showing programmers how to build the tools they use every day. Each chapter includes exercises to help readers check and deepen their understanding. All the example code can be downloaded, re-used, and modified under an open license.