The Unified Modeling Language, better known as UML, has become the de facto standard modeling language for analyzing and designing software applications and systems. Software analysis and design is just as much an art as it is a science. UML Diagramming: A Catalog of Cases shows the art and the science behind successful software analysis and design with more than 35 case studies of applications of a variety of industries, including: Transportation Healthcare Supply chain management Education Agriculture Manufacturing The book explains UML diagramming through case studies to help systems and software developers specify, visualize, construct, and document the artifacts of software systems. The cases demonstrate how UML embodies software engineering best practices for modeling large and complex systems. They show how UML is an intuitive diagramming language that can be easily understood by end-users and business professionals. These cases studies also demonstrate how UML is a powerful language for communicating software designs to help developers and end users validate application scope, requirements, and features. Case studies highlighted in the book included: WEBMED healthcare service system services Inventory management system Business process outsourcing (BPO) management system Weather monitoring system Product recommendation system Textile management system Smart traffic management system Online pharmacy management system Placement automation system Farm management system Art gallery management system Website development This catalog of UML case studies is an invaluable reference for students studying software engineering, programmers starting out their careers, and seasoned systems developers needing a reference guide.

Metaheuristic algorithms are considered as generic optimization tools that can solve very complex problems characterized by having very large search spaces. Metaheuristic methods reduce the effective size of the search space through the use of effective search strategies. Book Features: Provides a unified view of the most popular metaheuristic methods currently in use Includes the necessary concepts to enable readers to implement and modify already known metaheuristic methods to solve problems Covers design aspects and implementation in MATLAB (R) Contains numerous examples of problems and solutions that demonstrate the power of these methods of optimization The material has been written from a teaching perspective and, for this reason, this book is primarily intended for undergraduate and postgraduate students of artificial intelligence, metaheuristic methods, and/or evolutionary computation. The objective is to bridge the gap between metaheuristic techniques and complex optimization problems that profit from the convenient properties of metaheuristic approaches. Therefore, engineer practitioners who are not familiar with metaheuristic computation will appreciate that the techniques discussed are beyond simple theoretical tools, since they have been adapted to solve significant problems that commonly arise in such areas.

Combining theory and practice, this updated new edition provides a complete overview of how to create deep and meaningful quests for games. It uses the Unity game engine in conjunction with Fungus and other free plugins to provide an accessible entry into quest design. The book begins with an introduction to the theory and history of quests in games, before covering four theoretical components of quests: their spaces, objects, actors, and challenges. Each chapter also includes a practical section, with accompanying exercises and suggestions for the use of specific technologies for four crucial aspects of quest design: * level design * quest item creation * NPC and dialogue construction * scripting This book will be of great interest to all game designers looking to create new, innovative quests in their games. It will also appeal to new media researchers, as well as humanities scholars in the fields of mythology and depth-psychology that want to bring computer-assisted instruction into their classroom in an innovative way. The companion website includes lecture and workshop slides, and can be accessed at: www.designingquests.com

Combining theory and practice, this updated new edition provides a complete overview of how to create deep and meaningful quests for games. It uses the Unity game engine in conjunction with Fungus and other free plugins to provide an accessible entry into quest design. The book begins with an introduction to the theory and history of quests in games, before covering four theoretical components of quests: their spaces, objects, actors, and challenges. Each chapter also includes a practical section, with accompanying exercises and suggestions for the use of specific technologies for four crucial aspects of quest design: * level design * quest item creation * NPC and dialogue construction * scripting This book will be of great interest to all game designers looking to create new, innovative quests in their games. It will also appeal to new media researchers, as well as humanities scholars in the fields of mythology and depth-psychology that want to bring computer-assisted instruction into their classroom in an innovative way. The companion website includes lecture and workshop slides, and can be accessed at: www.designingquests.com

Data science and machine learning-two of the world's hottest fields-are attracting talent from a wide variety of technical, business, and liberal arts disciplines. Python, the world's #1 programming language, is also the most popular language for data science and machine learning. This is the first guide specifically designed to help millions of people with widely diverse backgrounds learn Python so they can use it for data science and machine learning. Leading data science instructor and practitioner Kennedy Behrman first walks through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data science programmer needs to master. Once you've learned these foundations, Behrman introduces intermediate and applied Python techniques for real-world problem-solving. Throughout, Foundational Python for Data Science presents hands-on exercises, learning assessments, case studies, and more-all created with Colab (Jupyter compatible) notebooks, so you can execute all coding examples interactively without installing or configuring any software.

This book presents a collection of research papers that address the challenge of how to develop software in a principled way that, in particular, enables reasoning. The individual papers approach this challenge from various perspectives including programming languages, program verification, and the systematic variation of software. Topics covered include programming abstractions for concurrent and distributed software, specification and verification techniques for imperative programs, and development techniques for software product lines. With this book the editors and authors wish to acknowledge - on the occasion of his 60th birthday - the work of Arnd Poetzsch-Heffter, who has made major contributions to software technology throughout his career. It features articles on Arnd's broad research interests including, among others, the implementation of programming languages, formal semantics, specification and verification of object-oriented and concurrent programs, programming language design, distributed systems, software modeling, and software product lines. All contributing authors are leading experts in programming languages and software engineering who have collaborated with Arnd in the course of his career. Overall, the book offers a collection of high-quality articles, presenting original research results, major case studies, and inspiring visions. Some of the work included here was presented at a symposium in honor of Arnd Poetzsch-Heffter, held in Kaiserslautern, Germany, in November 2018.

Machine Learning a branch of Artificial Intelligence is influencing the society, industry and academia at large. The adaptability of Python programming language to Machine Learning has increased its popularity further. Another technology on the horizon is Internet of Things (IoT). The present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer or have just started exploring IoT or Machine Learning with Python, then this book is for you. Features: Raspberry Pi as IoT is described along with the procedure for installation and configuration. A simple introduction to Python Programming Language along with its popular library packages like NumPy, Pandas, SciPy and Matplotlib are dealt in an exhaustive manner along with relevant examples. Machine Learning along with Python Scikit-Learn library is explained to audience with an emphasis on supervised learning and classification. Image processing on IoT is introduced to the audience who love to apply Machine Learning algorithms to Images The book follows hands-on approach and provide a huge collection of Python programs.

Learning by Doing with National Instruments Development Boards starts with a brief introduction to LabVIEW programming, which is required to explore the National Instrument platform, an introduction that includes detailed installation and licensing setup. Further, it gives the features and configuration setup of NI SPEEDY-33, NI ELVIS and myRIO boards. The focus of the book is on worked-out case studies for students working in different areas of electronics such as basic digital design, biomedical instrumentation, sensors and measurement. Data acquisition using SPEEDY-33, NI -ELVIS and myRIO kits is also odiscussed. The book also examines the myRIO platform.

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 focuses on the next generation optical networks as well as mobile communication technologies. The reader will find chapters on Cognitive Optical Network, 5G Cognitive Wireless, LTE, Data Analysis and Natural Language Processing. It also presents a comprehensive view of the enhancements and requirements foreseen for Machine Type Communication. Moreover, some data analysis techniques and Brazilian Portuguese natural language processing technologies are also described here.

Start Writing Production-Ready Go Code Fast Thousands of developers and teams want to start taking advantage of Go, the powerful language used in projects ranging from Kubernetes to Docker and Vault. Go Fundamentals is specifically designed to get you up-to-speed fast, to leverage your existing knowledge of other languages, and to help you avoid common mistakes made by Go newcomers. Based on author Mark Bates's and Cory LaNou's pioneering Gopher Guides training curricula, this guide will allow you to quickly understand and use Go syntax, core features, and idioms. Reflecting Go through version 1.18--which includes Go's exciting new support for generics--this guide prepares you to write robust, reliable, well-performing production code right from the outset. Learn how Go manages packages, modules, and dependencies Apply Go basics, such as variable declaration, types, and control flow Work effectively with collection types, iteration, functions, structs, and pointers Understand Go Slices and use them properly Write idiomatic Go, using principles such as embedding and composition Expertly use concurrency to improve code performance Create proper tests to quickly identify and fix problems Write simpler, better code with generics and interfaces Take advantage of channels, context, sync primatives, and other advanced features Go is lightweight, simple, and perfect for modern cloud-native and microservices development, which is why Go developers are in such high demand. With this guide and six months' experience with any modern programming language, you'll have what you need to leap into Go programming. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

"R and Data Mining "introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.

Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.

With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, "R and Data Mining" is a valuable, practical guide to a powerful method of analysis.
Presents an introduction into using R for data mining applications, covering most popular data mining techniquesProvides code examples and data so that readers can easily learn the techniquesFeatures case studies in real-world applicationsto help readers apply the techniques in their work"

Discusses core concepts and principles of deep learning in gaming and animation with applications. Covers application of neural networks for intelligent video game character. Discusses automated video generation and real time animation. Covers technological advancements in virtual reality (VR), and augmented reality (AR).

This book covers theoretical aspects of the physical processes, derivation of the governing equations and their solutions. It focusses on hydraulics, hydrology, and contaminant transport, including implementation of computer codes with practical examples. Python-based computer codes for all the solution approaches are provided for better understanding and easy implementation. The mathematical models are demonstrated through applications and the results are analyzed through data tables, plots, and comparison with analytical and experimental data. The concepts are used to solve practical applications like surface and ground water flow, flood routing, crop water requirement and irrigation scheduling. Combines the area of computational hydraulics, hydrology, and water resources engineering with Python Gives deep description of the basic equations and the numerical solutions of both 1D and 2D problems including the numerical codes Includes step-by-step translation of numerical algorithms in computer codes with focus on learners and practitioners Demonstration of theory, mathematical models through practical applications Analysis of each example through data tables, plots, and correlation with reality This book is aimed at senior undergraduates and graduate students in Civil Engineering, Coastal Engineering, Hydrology, and Water Resources Engineering.

In any serious engineering discipline, it would be unthinkable to construct a large system without having a precise notion of what is to be built and without verifying how the system is expected to function. Software engineering is no different in this respect.

Formal methods involve the use of mathematical notation and calculus in software development; such methods are difficult to apply to large-scale systems with practical constraints (e.g., limited developer skills, time and budget restrictions, changing requirements). Here Liu claims that formal engineering methods may bridge this gap. He advocates the incorporation of mathematical notation into the software engineering process, thus substantially improving the rigor, comprehensibility and effectiveness of the methods commonly used in industry.

This book provides an introduction to the SOFL (Structured Object-Oriented Formal Language) method that was designed and industry-tested by the author. Written in a style suitable for lecture courses or for use by professionals, there are numerous exercises and a significant real-world case study, so the readers are provided with all the knowledge and examples needed to successfully apply the method in their own projects.

Explaining cryptography and its mathematical issues in terms specifically designed to reach computer programmers, this book covers all that is needed to write professional level cryptographic code. An expanded and improved version of the very well received first edition, it includes approximately 100 pages of new material as well as numerous improvements in the original text. The CD-ROM features tools and programs for use with the text.

It's axiomatic to state that people fear what they do not understand, and this is especially true when it comes to technology. However, despite their prevalence, computers remain shrouded in mystery, and many users feel apprehensive when interacting with them. Smartphones have only exacerbated the issue. Indeed, most users of these devices leverage only a small fraction of the power they hold in their hands. How Things Work: The Computer Science Edition is a roadmap for readers who want to overcome their technophobia and harness the full power of everyday technology. Beginning with the basics, the book demystifies the mysterious world of computer science, explains its fundamental concepts in simple terms, and answers the questions many users feel too intimidated to ask. By the end of the book, readers will understand how computers and smart devices function and, more important, how they can make these devices work for them. To complete the picture, the book also introduces readers to the darker side of modern technology: security and privacy concerns, identity theft, and threats from the Dark Web.

Every programmer and software project manager must master the art of creating reusable software modules; they are the building blocks of large, reliable applications. Unlike some modern object-oriented languages, C provides little linguistic support or motivation for creating reusable application programming interfaces (APIs). While most C programmers use APIs and the libraries that implement them in almost every application they write, relatively few programmers create and disseminate new, widely applicable APIs. C Interfaces and Implementations shows how to create reusable APIs using interface-based design, a language-independent methodology that separates interfaces from their implementations. This methodology is explained by example. The author describes in detail 24 interfaces and their implementations, providing the reader with a thorough understanding of this design approach.

Features of C Interfaces and Implementations:

• Concise interface descriptions that comprise a reference manual for programmers interested in using the interfaces.
• A guided tour of the code that implements each chapter's interface tp help those modifying or extending an interface or designing related interfaces.
• In-depth focus on "algorithm engineering: " how to package data structures and related algorithms into reusable modules.
• Source code for 24 APIs and 8 sample applications is examined, with each presented as a "literate program" in which a thorough explanation is interleaved with the source code.
• Rarely documented C programming tricks-of-the-trade.
• Convenient access to all source code in the book via the World Wide Web at http: //www.cs.princeton.edu/software/cii/

Quickly learn the ropes with the Rust programming language using this practical, step-by-step guide In Beginning Rust Programming, accomplished programmer and author Ric Messier delivers a highly practical, real-world guide to coding with Rust. Avoiding dry, theoretical content and "Hello, world"-type tutorials of questionable utility, the book dives immediately into functional Rust programming that takes advantage of the language's blazing speed and memory efficiency. Designed from the ground up to give you a running start to using the multiparadigm system programming language, this book will teach you to: Solve real-world computer science problems of practical importance Use Rust's rich type system and ownership model to guarantee memory-safety and thread-safety Integrate Rust with other programming languages and use it for embedded devices Perfect for programmers with some experience in other languages, like C or C++, Beginning Rust Programming is also a great pick for students new to programming and seeking a user-friendly and robust language with which to start their coding career.

All traditional implementation techniques for functional languages fail to avoid useless repetition of work. They are not "optimal" in their implementation of sharing, often causing a catastrophic, exponential explosion in reduction time. Optimal reduction is an innovative graph reduction technique for functional expressions, introduced by Lamping in 1990, that solves the sharing problem. This work, the first on the subject, is a comprehensive account by two of its leading exponents. Practical implementation aspects are fully covered as are the mathematical underpinnings of the subject. The relationship to the pioneering work of Lévy and to Girard's more recent "Geometry of Interaction" are explored; optimal reduction is thereby revealed as a prime example of how a beautiful mathematical theory can lead to practical benefit. The book is essentially self-contained, requiring no more than basic familiarity with functional languages. It will be welcomed by graduate students and research workers in lambda calculus, functional programming or linear logic.

It's axiomatic to state that people fear what they do not understand, and this is especially true when it comes to technology. However, despite their prevalence, computers remain shrouded in mystery, and many users feel apprehensive when interacting with them. Smartphones have only exacerbated the issue. Indeed, most users of these devices leverage only a small fraction of the power they hold in their hands. How Things Work: The Computer Science Edition is a roadmap for readers who want to overcome their technophobia and harness the full power of everyday technology. Beginning with the basics, the book demystifies the mysterious world of computer science, explains its fundamental concepts in simple terms, and answers the questions many users feel too intimidated to ask. By the end of the book, readers will understand how computers and smart devices function and, more important, how they can make these devices work for them. To complete the picture, the book also introduces readers to the darker side of modern technology: security and privacy concerns, identity theft, and threats from the Dark Web.

Software development has been a troubling since it first started. There are seven chronic problems that have plagued it from the beginning: Incomplete and ambiguous user requirements that grow by >2% per month. Major cost and schedule overruns for large applications > 35% higher than planned. Low defect removal efficiency (DRE) < 85% on large systems. Cancelled projects that are not completed: > 30% above 10,000 function points. Poor quality and low reliability after the software is delivered: > 5 bugs per FP. Breach of contract litigation against software outsource vendors. Expensive maintenance and enhancement costs after delivery. These are endemic problems for software executives, software engineers and software customers but they are not insurmountable. In Software Development Patterns and Antipatterns, software engineering and metrics pioneer Capers Jones presents technical solutions for all seven. The solutions involve moving from harmful patterns of software development to effective patterns of software development. The first section of the book examines common software development problems that have been observed in many companies and government agencies. The data on the problems comes from consulting studies, breach of contract lawsuits, and the literature on major software failures. This section considers the factors involved with cost overruns, schedule delays, canceled projects, poor quality, and expensive maintenance after deployment. The second section shows patterns that lead to software success. The data comes from actual companies. The section's first chapter on Corporate Software Risk Reduction in a Fortune 500 company was based on a major telecom company whose CEO was troubled by repeated software failures. The other chapters in this section deal with methods of achieving excellence, as well as measures that can prove excellence to C-level executives, and with continuing excellence through the maintenance cycle as well as for software development.

Software development has been a troubling since it first started. There are seven chronic problems that have plagued it from the beginning: Incomplete and ambiguous user requirements that grow by >2% per month. Major cost and schedule overruns for large applications > 35% higher than planned. Low defect removal efficiency (DRE) < 85% on large systems. Cancelled projects that are not completed: > 30% above 10,000 function points. Poor quality and low reliability after the software is delivered: > 5 bugs per FP. Breach of contract litigation against software outsource vendors. Expensive maintenance and enhancement costs after delivery. These are endemic problems for software executives, software engineers and software customers but they are not insurmountable. In Software Development Patterns and Antipatterns, software engineering and metrics pioneer Capers Jones presents technical solutions for all seven. The solutions involve moving from harmful patterns of software development to effective patterns of software development. The first section of the book examines common software development problems that have been observed in many companies and government agencies. The data on the problems comes from consulting studies, breach of contract lawsuits, and the literature on major software failures. This section considers the factors involved with cost overruns, schedule delays, canceled projects, poor quality, and expensive maintenance after deployment. The second section shows patterns that lead to software success. The data comes from actual companies. The section's first chapter on Corporate Software Risk Reduction in a Fortune 500 company was based on a major telecom company whose CEO was troubled by repeated software failures. The other chapters in this section deal with methods of achieving excellence, as well as measures that can prove excellence to C-level executives, and with continuing excellence through the maintenance cycle as well as for software development.

Fundamentals of Engineering Programming with C and Fortran, first published in 1998, is a beginner's guide to problem solving with computers which shows how to quickly prototype a program for a particular engineering application. The book's side by side coverage of C and Fortran, the predominant computer languages in engineering, is unique. It emphasizes the importance of developing programming skills in C while carefully presenting the importance of maintaining a good reading knowledge of Fortran. Beginning with a brief description of computer architecture, the book then covers the fundamentals of computer programming for problem solving. It devotes separate chapters to data types and operators, control flow, type conversion, arrays, and file operations. The final chapter contains case studies that illustrate particular elements of modeling and visualization. Also included are a number of appendices covering C and Fortran language summaries and other useful topics. This concise and accessible book can be used as a text for introductory-level undergraduate courses on engineering programming or as a self-study guide for practising engineers.