1. Provides a toolkit of templates for common VR interactions, as well as practical advice on when to use them and how to tailor them for specific use cases; 2. Includes case studies detailing the practical application of interaction theory discussed in each chapter; 3. Presents tables of guidelines for practicing VR developers, for reference during software development; 4. Covers procedures for Interface Evaluation - formulas and testing methodologies to ensure that VR interfaces are effective, efficient, engaging, error-tolerant, and easy to learn; 5. Non-linear organisation - chapters of the book on different concepts can be read to gain knowledge on a single topic, without requiring other chapters to be read beforehand; 6. Includes ancillaries - PowerPoint slides, 3D models, videos, and a teacher's guide

Software engineering is as much about teamwork as it is about technology. This introductory textbook covers both. For courses featuring a team project, it offers tips and templates for aligning classroom concepts with the needs of the students' projects. Students will learn how software is developed in industry by adopting agile methods, discovering requirements, designing modular systems, selecting effective tests, and using metrics to track progress. The book also covers the 'why' behind the 'how-to', to prepare students for advances in industry practices. The chapters explore ways of eliciting what users really want, how clean architecture divides and conquers the inherent complexity of software systems, how test coverage is essential for detecting the inevitable defects in code, and much more. Ravi Sethi provides real-life case studies and examples to demonstrate practical applications of the concepts. Online resources include sample project materials for students, and lecture slides for instructors.

Python is an amazing programming language. It can be applied to almost any programming task. It allows for rapid development and debugging. Getting started with Python is like learning any new skill: it's important to find a resource you connect with to guide your learning. Luckily, there's no shortage of excellent books that can help you learn both the basic concepts of programming and the specifics of programming in Python. With the abundance of resources, it can be difficult to identify which book would be best for your situation. Python for Beginners is a concise single point of reference for all material on python. * Provides concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python tools * Offers practical advice for each major area of development with both Python 3.x and Python 2.x * Based on the latest research in cognitive science and learning theory * Helps the reader learn how to write effective, idiomatic Python code by leveraging its best-and possibly most neglected-features This book focuses on enthusiastic research aspirants who work on scripting languages for automating the modules and tools, development of web applications, handling big data, complex calculations, workflow creation, rapid prototyping, and other software development purposes. It also targets graduates, postgraduates in computer science, information technology, academicians, practitioners, and research scholars.

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.

Software Security: Concepts & Practices is designed as a textbook and explores fundamental security theories that govern common software security technical issues. It focuses on the practical programming materials that will teach readers how to implement security solutions using the most popular software packages. It's not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Features The book presents the implementation of a unique socio-technical solution for real-time cybersecurity awareness. It provides comprehensible knowledge about security, risk, protection, estimation, knowledge and governance. Various emerging standards, models, metrics, continuous updates and tools are described to understand security principals and mitigation mechanism for higher security. The book also explores common vulnerabilities plaguing today's web applications. The book is aimed primarily at advanced undergraduates and graduates studying computer science, artificial intelligence and information technology. Researchers and professionals will also find this book useful.

This book covers the proceedings of ICISSI 2022 (International Conference on Intelligent Systems and Smart Infrastructure) held at Prayagraj, Uttar Pradesh during April 21-22, 2022. The conference was jointly organised by Shambhunath Institute of Engineering and Technology, Prayagraj UP India, Institute of Engineering and Technology (IET) Lucknow, U.P India, and Manipal University Jaipur, Rajasthan India with an aim to provide a platform for researchers, scientists, technocrats, academicians and engineers to exchange their innovative ideas and new challenges being faced in the field of emerging technologies. The papers presented in the conference have been compiled in form of chapters to focus on the core technological developments in the emerging fields like machine learning, intelligence systems, smart infrastructure, advanced power technology etc.

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.

Build and use systems that safely automate software delivery from testing through release with this jargon-busting guide to Continuous Delivery pipelines. In Grokking Continuous Delivery you will learn how to: Design effective CD pipelines for new and legacy projects Keep your software projects release-ready Maintain effective tests Scale CD across multiple applications Ensure pipelines give the right signals at the right time Use version control as the source of truth Safely automate deployments with metrics Describe CD in a way that makes sense to your colleagues Grokking Continuous Delivery teaches you the design and purpose of continuous delivery systems that you can use with any language or stack. You'll learn directly from your mentor Christie Wilson, Google engineer and co-creator of the Tekton CI/CD framework. Using crystal-clear, well-illustrated examples, Christie lays out the practical nuts and bolts of continuous delivery for developers and pipeline designers. In each chapter, you'll uncover the proper approaches to solve the real-world challenges of setting up a CD pipeline. With this book as your roadmap, you'll have a clear plan for bringing CD to your team without the need for costly trial-and-error experimentation. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Keep your codebase release-ready. A continuous delivery pipeline automates version control, testing, and deployment with minimal developer intervention. Master the tools and practices of continuous delivery, and you'll be able to add features and push updates quickly and consistently. About the book Grokking Continuous Delivery is a friendly guide to setting up and working with a continuous delivery pipeline. Each chapter takes on a different scenario you'll face when setting up a CD system, with real-world examples like automated scaling and testing legacy applications. Taking a tool-agnostic approach, author Christie Wilson guides you each step of the way with illustrations, crystal-clear explanations, and practical exercises to lock in what you're learning. What's inside Design effective CD pipelines for new and legacy projects Ensure your pipelines give the right signals at the right times Version control as the source of truth Safely automate deployments About the reader For software engineers who want to add CD to their development process. About the author Christie Wilson is a software engineer at Google, where she co-created Tekton, a cloud-native CI/CD platform built on Kubernetes. Table of Contents PART 1 Introducing continuous delivery 1 Welcome to Grokking Continuous Delivery 2 A basic pipeline PART 2 Keeping software in a deliverable state at all times 3 Version control is the only way to roll 4 Use linting effectively 5 Dealing with noisy tests 6 Speeding up slow test suites 7 Give the right signals at the right times PART 3 Making delivery easy 8 Easy delivery starts with version control 9 Building securely and reliably 10 Deploying confidently PART 4 CD design 11 Starter packs: From zero to CD 12 Scripts are code, too 13 Pipeline design

Technology and organizations co-evolve, as is illustrated by the growth of information and communication technology (ICT) and global software engineering (GSE). Technology has enabled the development of innovations in GSE. The literature on GSE has emphasized the role of the organization at the expense of technology. This book explores the role of technology in the evolution of globally distributed software engineering. To date, the role of the organization has been examined in coordinating GSE activities because of the prevalence of the logic of rationality (i.e., the efficiency ethos, mechanical methods, and mathematical analysis) and indeterminacy (i.e., the effectiveness ethos, natural methods, and functional analysis). This logic neglects the coordination role of ICT. However, GSE itself is an organizational mode that is technology-begotten, technology-dominated, and technology-driven, as is its coordination. GSE is a direct reflection of ICT innovation, change, and use, yet research into the role technology of GSE has been neglected. Global Software Engineering: Virtualization and Coordination considers existing fragmented explanations and perspectives in GSE research, poses new questions about GSE, and proposes a framework based on the logic of virtuality (i.e., creativity ethos, electrical methods, and technological analysis) rather than of rationality and indeterminacy. Virtuality is the primary perspective in this book's comprehensive study of GSE. The book concludes with an integrated explanation of GSE coordination made possible through ICT connectivity and capitalization.

As the number of Internet of Things (IoT) elements grows exponentially, their interactions can generate a massive amount of raw and multi-structured data. The challenge with this data explosion is to transform any raw data into information and knowledge, which can be used by people and systems to make intelligent decisions. Industrial IoT Application Architectures and Use Cases explores how artificial intelligence (AI), data analytics, and IoT technology combine to promote intelligent decision-making and automation in a range of industries. With faster, more stable AI algorithms and approaches, knowledge discovery and dissemination from IoT-device data can be simplified and streamlined. An era of powerful cognitive technology is beginning due to cloud-based cognitive systems that are forming the foundation of game-changing intelligent applications. This book presents next-generation use cases of IoT and IoT data analytics for a variety of industrial verticals as given below: An Intelligent IoT framework for smart water management An IoT-enabled smart traffic control system for congestion control and smart traffic management An intelligent airport system for airport management and security surveillance An IoT framework for healthcare to integrate and report patient information Fuzzy scheduling with IoT for tracking and monitoring hotel assets An IoT system for designing drainage systems and monitoring drainage pipes Predictive maintenance of plant equipment to decide the actual mean time to malfunction Integrated neural networks and IoT systems for predictive equipment maintenance IoT integration in blockchain for smart waste management This book also includes a chapter on the IoT paradigm and an overview of uses cases for personal, social, and industrial applications.

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.

This reference text provides the theoretical foundations, the emergence, and the application areas of Blockchain in an easy-to-understand manner that would be highly helpful for the researchers, academicians, and industry professionals to understand the disruptive potentials of Blockchain. It explains Blockchain concepts related to Industry 4.0, Smart Healthcare, and the Internet of Things (IoT) and explores Smart Contracts and Consensus algorithms. This book will serve as an ideal reference text for graduate students and academic researchers in electrical engineering, electronics and communication engineering, computer engineering, and information technology. This book * Discusses applications of blockchain technology in diverse sectors such as industry 4.0, education, finance, and supply chain. * Provides theoretical concepts, applications, and research advancements in the field of blockchain. * Covers industry 4.0 digitization platform and blockchain for data management in industry 4.0 in a comprehensive manner. * Emphasizes analysis and design of consensus algorithms, fault tolerance, and strategy to choose the correct consensus algorithm. * Introduces security issues in the industrial internet of things, internet of things, blockchain integration, and blockchain-based applications. The text presents in-depth coverage of theoretical concepts, applications and advances in the field of blockchain technology. This book will be an ideal reference for graduate students and academic researchers in diverse engineering fields such as electrical, electronics and communication, computer, and information technology.

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.

Using the implementation of a deep learning framework as an example, C++ Template Metaprogramming in Practice: A Deep Learning Framework explains the application of metaprogramming in a relatively large project and emphasizes ways to optimize systems performance. The book is suitable for developers with a basic knowledge of C++. Developers familiar with mainstream deep learning frameworks can also refer to this book to compare the differences between the deep learning framework implemented with metaprogramming and compile-time computing with deep learning frameworks using object-oriented methods. Consisting of eight chapters, the book starts with two chapters discussing basic techniques of metaprogramming and compile-time computing. The rest of the book's chapters focus on the practical application of metaprogramming in a deep learning framework. It examines rich types and systems, expression templates, and writing complex meta-functions, as well as such topics as: Heterogeneous dictionaries and policy templates An introduction to deep learning Type system and basic data types Operations and expression templates Basic layers Composite and recurrent layers Evaluation and its optimization Metaprogramming can construct flexible and efficient code. For C++ developers who are familiar with object-oriented programming, the main difficulty in learning and mastering C++ metaprogramming is establishing the thinking mode of functional programming. The meta-programming approach involved at compile time is functional, which means that the intermediate results of the construction cannot be changed, and the impact may be greater than expected. This book enables C++ programmers to develop a functional mindset and metaprogramming skills. The book also discusses the development cost and use cost of metaprogramming and provides workarounds for minimizing these costs.

"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.

* Provides simple, conceptual descriptions of everyday technologies * Includes clear examples and diagrams that demonstrate the principles and techniques, not just a "how-to" punch list * Covers advanced topics for readers who want to dive into the deep end of the technology pool * Avoids jargon-where terminology does appear, the text will provide clear, concise definitions

This book provides insights into contemporary issues and challenges in multi-criteria decision models. It is a useful guide for identifying, understanding and categorising multi-criteria decision models, and ultimately implementing the analysis for effective decision-making. The use of multi-criteria decision models in software reliability engineering is a relatively new field of study, and this book collects all the latest methodologies, tools and techniques in one single volume. It covers model selection, assessment, resource allocation, release management, up-grade planning, open-source systems, bug tracking system management and defect prediction. Multi-Criteria Decision Models in Software Reliability: Methods and Applications will cater to researchers, academicians, post-graduate students, software developers, software reliability engineers and IT managers.

Smart shipping is a future method for transporting ocean cargo and exploring the resources of oceans for medical drugs, food, energy resources, and other products. A smart ship is an integration of shipping with many fields such as fishing, manufacturing, navigation, communication, computing, control, sensing, etc., to provide better shipping and services. The purpose of this edited book is to provide state-of-the-art approaches and novel technologies for smart ships, covering a range of topics in these areas so that it will be an excellent reference book for the researchers, students, and professionals in these areas. It presents the fundamental technologies needed to build smart ships, and gives a clear explanation of them. This book will serve as a good reference for researchers to know the state of the art and to discover uncovered territory and develop new applications, as well as being a guideline for building future smart ships. Yang Xiao is a Full Professor in the Department of Computer Science at the University of Alabama, Tuscaloosa, Alabama, USA. Tieshan Li is a Full Professor in the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.

- This book covers the production of dissertations in an area where students are much more comfortable writing code than writing academically. - With practical examples of bachelor dissertations and practical research methods utilised in the field of computer science and computer games such as survey methodologies, experimental methodologies, case studies, analysis techniques and reporting techniques, this book will break down the sometimes complicated-seeming nature of the dissertation. - Written to be concise yet comprehensive and with easily accessible language and examples, this book will take the mystery out of undergraduate dissertations in this field.

Updates content and introduces topics such as business changes and outsourcing. Addresses new cyber security risks such as IoT and Distributed Networks (i.e., blockchain). Covers strategy based on the OODA loop in the cycle. Demonstrates application of the concepts through short case studies of real-world incidents chronologically delineating related events. Discusses certifications and reference manuals in cyber security and digital forensics. Includes an entire chapter on tools used by professionals in the field.

The text provides a comprehensive overview of the design aspects of the internet of things devices and covers the fundamentals of big data and data science. It explores various scenarios such as what are the middleware and frameworks available and how to build a stable, standards-based, and Secure internet of things device. It discusses important concepts including embedded programming techniques, machine-to-machine architecture, and the internet of things for smart city applications. It will serve as an ideal design book for professionals, senior undergraduate, and graduate students in the fields including electrical engineering, electronics and communication engineering, and computer engineering. The book- Covers applications and architecture needed to deliver solutions to end customers and readers. Discusses practical aspects of implementing the internet of things in diverse areas including manufacturing, and software development. Highlights big data concepts and embedded programming techniques. Presents technologies including machine to machine, integrated sensors, and radio-frequency identification. Introduces global system for mobile communication and precise details of standards based on internet of things architecture models. The book focuses on practical design aspects such as how to finalize a processor integrated circuit, which operating system to use, etc. in a single volume. It will serve as an ideal text for professionals, senior undergraduate, and graduate students in diverse engineering domains including electrical, electronics and communication, computer.

How do you detangle a monolithic system and migrate it to a microservice architecture? How do you do it while maintaining business-as-usual? As a companion to Sam Newman's extremely popular Building Microservices, this new book details a proven method for transitioning an existing monolithic system to a microservice architecture. With many illustrative examples, insightful migration patterns, and a bevy of practical advice to transition your monolith enterprise into a microservice operation, this practical guide covers multiple scenarios and strategies for a successful migration, from initial planning all the way through application and database decomposition. You'll learn several tried and tested patterns and techniques that you can use as you migrate your existing architecture. Ideal for organizations looking to transition to microservices, rather than rebuild Helps companies determine whether to migrate, when to migrate, and where to begin Addresses communication, integration, and the migration of legacy systems Discusses multiple migration patterns and where they apply Provides database migration examples, along with synchronization strategies Explores application decomposition, including several architectural refactoring patterns Delves into details of database decomposition, including the impact of breaking referential and transactional integrity, new failure modes, and more

Defines concepts and processes of software and software development, such as agile processes, requirements engineering, and software architecture, design, construction Uncovers and answers various misconceptions about the software development process and presents an up-to-date reflection on the state of practice in the industry Details how non-software engineers can better communicate their needs to software engineers and more effectively participate in design and testing to ultimately lower software development and maintenance costs Helps answer the question: How can I better leverage embedded software in my design? Adds new chapters on software architecture, software engineering and systems, and software engineering and disruptive technologies, as well as information on cybersecurity Features new appendices that describe a sample automation system, covering software requirements, architecture, and design

This comprehensive reference text discusses nature inspired algorithms and their applications. It presents the methodology to write new algorithms with the help of MATLAB programs and instructions for better understanding of concepts. It covers well-known algorithms including evolutionary algorithms, genetic algorithm, particle Swarm optimization and differential evolution, and recent approached including gray wolf optimization. A separate chapter discusses test case generation using techniques such as particle swarm optimization, genetic algorithm, and differential evolution algorithm. The book- Discusses in detail various nature inspired algorithms and their applications Provides MATLAB programs for the corresponding algorithm Presents methodology to write new algorithms Examines well-known algorithms like the genetic algorithm, particle swarm optimization and differential evolution, and recent approaches like gray wolf optimization. Provides conceptual linking of algorithms with theoretical concepts The text will be useful for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering. Discussing nature inspired algorithms and their applications in a single volume, this text will be useful as a reference text for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering. It discusses important algorithms including deterministic algorithms, randomized algorithms, evolutionary algorithms, particle swarm optimization, big bang big crunch (BB-BC) algorithm, genetic algorithm and grey wolf optimization algorithm. "

Semantic web technologies (SWTs) offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. This book provides a roadmap for semantic web technologies (SWTs) and highlights their role in a wide range of domains including cloud computing, Internet of Things, big data, sensor network, and so forth. It also explores the prospects of these technologies including different data interchange formats, query languages, ontologies, Linked Data, and notations. The role of SWTs in 'epidemic Covid-19', 'e-learning platforms and systems', 'block chain', 'open online courses', and 'visual analytics in healthcare' is described as well. This book: Explores all the critical aspects of semantic web technologies (SWTs) Discusses the impact of SWTs on cloud computing, Internet of Things, big data, and sensor network Offers a comprehensive examination of the emerging research in the areas of SWTs and their related domains Provides a template to develop a wide range of smart and intelligent applications Includes latest applications and examples with real data This book is aimed at researchers and graduate students in computer science, informatics, web technology, cloud computing, and Internet of Things.