This book is about describing the meaning of programming languages. The author teaches the skill of writing semantic descriptions as an efficient way to understand the features of a language. While a compiler or an interpreter offers a form of formal description of a language, it is not something that can be used as a basis for reasoning about that language nor can it serve as a definition of a programming language itself since this must allow a range of implementations. By writing a formal semantics of a language a designer can yield a far shorter description and tease out, analyse and record design choices. Early in the book the author introduces a simple notation, a meta-language, used to record descriptions of the semantics of languages. In a practical approach, he considers dozens of issues that arise in current programming languages and the key techniques that must be mastered in order to write the required formal semantic descriptions. The book concludes with a discussion of the eight key challenges: delimiting a language (concrete representation), delimiting the abstract content of a language, recording semantics (deterministic languages), operational semantics (non-determinism), context dependency, modelling sharing, modelling concurrency, and modelling exits. The content is class-tested and suitable for final-year undergraduate and postgraduate courses. It is also suitable for any designer who wants to understand languages at a deep level. Most chapters offer projects, some of these quite advanced exercises that ask for complete descriptions of languages, and the book is supported throughout with pointers to further reading and resources. As a prerequisite the reader should know at least one imperative high-level language and have some knowledge of discrete mathematics notation for logic and set theory.

Formal Languages and Applications provides a comprehensive study-aid and self-tutorial for graduates students and researchers. The main results and techniques are presented in an readily accessible manner and accompanied by many references and directions for further research. This carefully edited monograph is intended to be the gateway to formal language theory and its applications, so it is very useful as a review and reference source of information in formal language theory.

This book presents comprehensive studies on nine specification languages and their logics of reasoning. The editors and authors are authorities on these specification languages and their application.

In a unique feature, the book closes with short commentaries on the specification languages written by researchers closely associated with their original development. The book contains extensive references and pointers to future developments.

This book contains 25 short programs that will challenge your understanding of Pandas. Like any big project, the Pandas developers had to make some design decisions that at times seem surprising. This book uses those quirks as a teaching opportunity. By understanding the gaps in your knowledge, you'll become better at what you do. Some of the teasers are from the author's experience shipping bugs to production, and some from others doing the same. Teasers and puzzles are fun, and learning how to solve them can teach you to avoid programming mistakes and maybe even impress your colleagues and future employers. Working with data is central to nearly everything we do, from disease contact tracing and analyzing health records to smart meters that track utility consumption behavior. With the power of Python's pandas library, you can process and analyze this data in a highly efficient and simple-to-understand way. And with 25 brain teasers designed to turn this technology's quirks into a teaching opportunity, you'll be honing your data science skills while having fun at the same time. Following a simple format, you'll challenge yourself and your understanding of pandas. Read a short Python program that uses pandas, try to guess the output, run the code yourself, and then go to the next page for an explanation of the solution. From common pitfalls and hidden gotchas to unexpected twists and turns, you'll deepen your understanding of pandas, learn to write more efficient code, and reduce the number of bugs in the software you develop. You may even impress your colleagues and your employers, both present and future. Learn the tricks of the trade with Python's pandas, in one of the most fun and creative ways around. What You Need: To run the code you'll need Python version 3.8 or upper and Pandas version 1.0 or upper installed. We use Python version 3.8.3 and Pandas version 1.0.5; the output might change in future versions.

This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on the modeling and applications of the mathematical content. Emphasis is placed on the need for, and methods of, scientific computing for a range of different types of problems, supplying the evidence and justification to motivate the reader. Practical guidance on coding the methods is also provided, through simple-to-follow examples using Python. Topics and features: provides an accessible and applications-oriented approach, supported by working Python code for many of the methods; encourages both problem- and project-based learning through extensive examples, exercises, and projects drawn from practical applications; introduces the main concepts in modeling, python programming, number representation, and errors; explains the essential details of numerical calculus, linear, and nonlinear equations, including the multivariable Newton method; discusses interpolation and the numerical solution of differential equations, covering polynomial interpolation, splines, and the Euler, Runge-Kutta, and shooting methods; presents largely self-contained chapters, arranged in a logical order suitable for an introductory course on scientific computing. Undergraduate students embarking on a first course on numerical methods or scientific computing will find this textbook to be an invaluable guide to the field, and to the application of these methods across such varied disciplines as computer science, engineering, mathematics, economics, the physical sciences, and social science.

Python for Scientific Computation and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web.

This book introduces Python scripting for geographic information science (GIS) workflow optimization using ArcGIS. It builds essential programming skills for automating GIS analysis. Over 200 sample Python scripts and 175 classroom-tested exercises reinforce the learning objectives. Readers will learn to: * Write and run Python in the ArcGIS Python Window, the PythonWin IDE, and the PyScripter IDE * Work with Python syntax and data types * Call ArcToolbox tools, batch process GIS datasets, and manipulate map documents using the arcpy package * Read and modify proprietary and ASCII text GIS data * Parse HTML web pages and KML datasets * Create Web pages and fetch GIS data from Web sources. * Build user-interfaces with the native Python file dialog toolkit or the ArcGIS Script tools and PyToolboxes Python for ArcGIS is designed as a primary textbook for advanced-level students in GIS. Researchers, government specialists and professionals working in GIS will also find this book useful as a reference.

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.

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.

This textbook is an ideal introduction in college courses or self-study for learning computer programming using the C language. Written for those with minimal or no programming experience, Computer Programming in C for Beginners offers a heavily guided, hands-on approach that enables the reader to quickly start programming, and then progresses to cover the major concepts of C programming that are critical for an early stage programmer to know and understand. While the progression of topics is conventional, their treatment is innovative and designed for rapid understanding of the many concepts in C that have traditionally proven difficult for beginners, such as variable typing and scope, function definition, passing by value, pointers, passing by reference, arrays, structures, basic memory management, dynamic memory allocation, and linked lists, as well as an introductory treatment of searching and sorting algorithms. Written in an informal but clear narrative, the book uses extensive examples throughout and provides detailed guidance on how to write the C code to achieve the objectives of the example problems. Derived from the author's many years of teaching hands-on college courses, it encourages the reader to follow along by programming the progressively more complex exercise programs presented. In some sections, errors are purposely inserted into the code to teach the reader about the common pitfalls of programming in general, and the C language in particular.

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.

In ancient games such as chess or go, the most brilliant players can improve by studying the strategies produced by a machine. Robotic systems practice their own movements. In arcade games, agents capable of learning reach superhuman levels within a few hours. How do these spectacular reinforcement learning algorithms work? With easy-to-understand explanations and clear examples in Java and Greenfoot, you can acquire the principles of reinforcement learning and apply them in your own intelligent agents. Greenfoot (M.Koelling, King's College London) and the hamster model (D. Bohles, University of Oldenburg) are simple but also powerful didactic tools that were developed to convey basic programming concepts. The result is an accessible introduction into machine learning that concentrates on reinforcement learning. Taking the reader through the steps of developing intelligent agents, from the very basics to advanced aspects, touching on a variety of machine learning algorithms along the way, one is allowed to play along, experiment, and add their own ideas and experiments.

From the descriptive styles which mirror 19th Century Romanticism to the bold starkness of contemporary dialects, these stories offer myriad insights into the many facets of the masculine soul. These are not cat stories. Well.actually there is one. But for the most part this is a collection of first person narratives in short fiction which are certain to leave the reader begging to dialogue with every page.

As with his powerful and imaginative science fiction novels, "The Last Champion of Earth" and "The Planet of Mortal Worship," Donald Templeman entertains, stuns and unveils lurid insights into the human condition with every keystroke.

'Author Templeman is a skilled writer and accomplished storyteller"-WRITER'S DIGEST 12TH ANNUAL BOOK AWARDS

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.

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 book presents a number of approaches to Fine-Kinney-based multi-criteria occupational risk-assessment. For each proposed approach, it provides case studies demonstrating their applicability, as well as Python coding, which will enable readers to implement them into their own risk assessment process. The book begins by giving a review of Fine-Kinney occupational risk-assessment methods and their extension by fuzzy sets. It then progresses in a logical fashion, dedicating a chapter to each approach, including the fuzzy best and worst method, interval-valued Pythagorean fuzzy VIKOR and interval type-2 fuzzy QUALIFLEX. This book will be of interest to professionals and researchers working in the field of occupational risk management, as well as postgraduate and undergraduate students studying applications of fuzzy systems.

It is a textbook that provides a thorough introduction to the C++ programming language. Introduction to the C++ language in a substantial, non-tiring way, including hints and advices for writing clear, reliable, and efficient code. Numerous programming exercises of progressive difficulty and non-obvious short questions.

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.

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.

More than ever, FDL is the place for researchers, developers, industry designers, academia, and EDA tool companies to present and to learn about the latest scientific achievements, practical applications and users experiences in the domain of specification and design languages. FDL covers the modeling and design methods, and their latest supporting tools, for complex embedded systems, systems on chip, and heterogeneous systems.

FDL 2009 is the twelfth in a series of events that were held all over Europe, in selected locations renowned for their Universities and Reseach Institutions as well as the importance of their industrial environment in Computer Science and Micro-electronics. In 2009, FDL was organized in the attractive south of France area of Sophia Antipolis. together with the DASIP (Design and Architectures for Signal and Image Processing) Conference and the SAME (Sophia Antipolis MicroElectronics ) Forum.

All submitted papers were carefully reviewed to build a program with 27 full and 10 short contributions. From these, the Program Committee selected a shorter list, based on the evaluations of the reviewers, and the originality and relevance of the work that was presented at the Forum. The revised, and sometimes extended versions of these contributions constitute the chapters of this volume.

Advances in Design Methods from Modeling Languages for Embedded Systems and SoC's presents extensions to standard specification and description languages, as well as new language-based design techniques and methodologies to solve the challenges raised by mixed signal and multi-processor systems on a chip. It is intended as a reference for researchers and lecturers, as well as a state of the art milestone for designers and CAD developers.

Enterprises have made amazing advances by taking advantage of data about their business to provide predictions and understanding of their customers, markets, and products. But as the world of business becomes more interconnected and global, enterprise data is no long a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today. The Semantic Web treats data as a distributed resource on the scale of the World Wide Web, and incorporates features to address the challenges of massive data distribution as part of its basic design. The aim of the first two editions was to motivate the Semantic Web technology stack from end-to-end; to describe not only what the Semantic Web standards are and how they work, but also what their goals are and why they were designed as they are. It tells a coherent story from beginning to end of how the standards work to manage a world-wide distributed web of knowledge in a meaningful way. The third edition builds on this foundation to bring Semantic Web practice to enterprise. Fabien Gandon joins Dean Allemang and Jim Hendler, bringing with him years of experience in global linked data, to open up the story to a modern view of global linked data. While the overall story is the same, the examples have been brought up to date and applied in a modern setting, where enterprise and global data come together as a living, linked network of data. Also included with the third edition, all of the data sets and queries are available online for study and experimentation at data.world/swwo.

Features Contains ready-to-use coding recipes allowing fast prototyping and solving of mathematical problems using FEM. Suitable for upper-level undergraduates and graduates in applied mathematics, science, or engineering. Both MATLAB and Python programming codes are provided to give readers more flexibility in the practical framework implementation.

Provides guidance on performance enhancement and reliability of IC chips. Provides a detailed hybrid optimization strategy for the optimal arrangement of IC chips on a board. The MATLAB program for the hybrid optimization strategy along with its stability analysis is carried out in a detailed manner.

User Level: Most of the book is targeted at beginners in computing and programming. A few parts, such as the small electronics project and setting up a web server, assume some intermediate skills. The Raspberry Pi is one of the most successful open source hardware projects ever. For only $35, you get a full-blown PC, a multimedia center, and a web server--and this book gives you everything you need to get started. You'll learn the basics, progress to controlling the Pi, and then build your own electronics projects. This new edition is revised and updated with two new chapters on adding digital and analog sensors, and creating videos and a burglar alarm with the Pi camera. Get your Raspberry Pi up and running and doing cool stuff. You'll start with the basics: adding hardware, installing and configuring Debian Linux, and customizing the Pi's firmware to get the most out of your hardware. Then the fun begins. You'll connect the Pi to your home network, surf the web, and tweet messages. You'll learn how to get the most out of Midori, the Pi's standard browser, and control the desktops of other PCs with the Pi. Then you'll explore the Pi's versatility with a series of home projects. Turn it into a web server in your home network; convert the Pi into a powerful multimedia center so you can watch high-definition video and listen to your favorite music; and play classic video games. Then you'll use the GPIO pins on the Raspberry Pi to build your own electronics projects, such as an "out of memory" alarm. You'll learn how to use digital and analog sensors with the Pi, even though the Pi doesn't have analog input ports! Finally, you'll set up the Pi camera, create your own time-lapse videos, and build an automatic e-mailing burglar alarm. Power to the Pi! What You Need You need a Raspberry Pi and several things that you probably already have at home, such as a keyboard, a mouse, a monitor/TV set, and an SD card. To build the electronic projects you need a few cheap parts and the Pi camera.