This volume, the third of a series, consists of applications of Mathematica (R) to a potpourri of more advanced topics. These include differential geometry of curves and surfaces, differential equations and special functions and complex analysis. Some of the newest features of Mathematica (R) are demonstrated and explained and some problems with the current implementation pointed out and possible future improvements suggested. Contains a large number of worked out examples. Explains some of the most recent mathematical features of Mathematica (R). Considers topics discussed rarely or not at all in the context of Mathematica (R). Can be used to supplement several different courses. Based on actual university courses.

With two new chapters and a new preface, the award-winning book "The Halo Effect "continues to unmask the delusions found in the corporate world and provides a sharp understanding of what drives business success and failure.
Too many of today's most prominent management gurus make steel-clad guarantees based on claims of irrefutable research, promising to reveal the secrets of why one company fails and another succeeds, and how you can become the latter. Combining equal measures of solemn-faced hype and a wide range of popular business delusions, statistical and otherwise, these self-styled experts cloud our ability to think critically about the nature of success.
Central among these delusions is the Halo Effect--the tendency to focus on the high financial performance of a successful company and then spread its golden glow to all its attributes--clear strategy, strong values, brilliant leadership, and outstanding execution. But should the same company's sales head south, the very same attributes are universally derided--suddenly the strategy was wrong, the culture was complacent, and the leader became arrogant.
"The Halo Effect" not only identifies these delusions that keep us from understanding business performance, but also suggests a more accurate way to think about leading a company. This approach--focusing on strategic choice and execution, while recognizing the inherent riskiness of both--clarifies the priorities that managers face.
Brilliant and unconventional, irreverent and witty, "The Halo Effect" is essential reading for anyone wanting to separate fact from fiction in the world of business.

Developing a large-scale software system in C++ requires more than just a sound understanding of the logical design issues covered in most books on C++ programming. To be successful, you will also need a grasp of physical design concepts that, while closely tied to the technical aspects of development, include a dimension with which even expert software developers may have little or no experience.

This is the definitive book for all C++ software professionals involved in large development efforts such as databases, operating systems, compilers, and frameworks. It is the first C++ book that actually demonstrates how to design large systems, and one of the few books on object-oriented design specifically geared to practical aspects of the C++ programming language.

In this book, Lakos explains the process of decomposing large systems into physical (not inheritance) hierarchies of smaller, more manageable components. Such systems with their acyclic physical dependencies are fundamentally easier and more economical to maintain, test, and reuse than tightly interdependent systems. In addition to explaining the motivation for following good physical as well as logical design practices, Lakos provides you with a catalog of specific techniques designed to eliminate cyclic, compile-time, and link-time (physical) dependencies. He then extends these concepts from large to very large systems. The book concludes with a comprehensive top-down approach to the logical design of individual components. Appendices include a valuable design pattern "Protocol Hierarchy" designed to avoid fat interfaces while minimizing physical dependencies; the details of implementing an ANSI C compatible C++procedural interface; and a complete specification for a suite of UNIX-like tools to extract and analyze physical dependencies. Practical design rules, guidelines, and principles are also collected in an appendix and indexed for quick reference.
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Understand how to apply auto machine learning to data streams and create transactional machine learning (TML) solutions that are frictionless (require minimal to no human intervention) and elastic (machine learning solutions that can scale up or down by controlling the number of data streams, algorithms, and users of the insights). This book will strengthen your knowledge of the inner workings of TML solutions using data streams with auto machine learning integrated with Apache Kafka. Transactional Machine Learning with Data Streams and AutoML introduces the industry challenges with applying machine learning to data streams. You will learn the framework that will help you in choosing business problems that are best suited for TML. You will also see how to measure the business value of TML solutions. You will then learn the technical components of TML solutions, including the reference and technical architecture of a TML solution. This book also presents a TML solution template that will make it easy for you to quickly start building your own TML solutions. Specifically, you are given access to a TML Python library and integration technologies for download. You will also learn how TML will evolve in the future, and the growing need by organizations for deeper insights from data streams. By the end of the book, you will have a solid understanding of TML. You will know how to build TML solutions with all the necessary details, and all the resources at your fingertips. What You Will Learn Discover transactional machine learning Measure the business value of TML Choose TML use cases Design technical architecture of TML solutions with Apache Kafka Work with the technologies used to build TML solutions Build transactional machine learning solutions with hands-on code together with Apache Kafka in the cloud Who This Book Is For Data scientists, machine learning engineers and architects, and AI and machine learning business leaders.

Write your first code in Java 17 using simple, step-by-step examples that model real-word objects and events, making learning easy. With Java 17 for Absolute Beginners you'll be able to pick up the concepts without fuss. It teaches Java development in language anyone can understand, giving you the best possible start. You'll see clear code descriptions and layout so that you can get your code running as soon as possible. Author Iuliana Cosmina focuses on practical knowledge and getting you up to speed quickly-all the bits and pieces a novice needs to get started programming in Java. First, you'll discover what type of language Java is, what it is good for, and how it is executed. With the theory out of the way, you'll install Java, choose an editor such as IntelliJ IDEA, and write your first simple Java program. Along the way you'll compile and execute this program so it can run on any platform that supports Java. As part of this tutorial you'll see how to write high-quality code by following conventions and respecting well-known programming principles, making your projects more professional and efficient. Java 17 for Absolute Beginners gives you all you need to start your Java programming journey. No experience necessary. After reading this book, you'll come away with the basics to get started writing programs in Java. What You Will Learn Get started with Java 17 from scratch Use data types, operators, and the stream API Install and use the IntelliJ IDEA and the Gradle build tool Exchange data using the new JSON APIs Play with images using multi-resolution APIs Implement the publish-subscribe architecture Who This Book Is For Those who are new to programming and who want to start with Java.

For use as a core text supplement in any course covering common LISP such as Artificial Intelligence or Concepts of Programming Languages.

Teaching students new and more powerful ways of thinking about programs, this text contains a tutorial—full of examples—that explains all the essential concepts of Lisp programming, plus an up- to-date summary of ANSI Common Lisp, listing every operator in the language. Informative and fun, it gives students everything they need to start writing programs in Lisp both efficiently and effectively, and highlights such innovative Lisp features as automatic memory management, manifest typing, closures, and more.

Learn the fundamentals of the Java 17 LTS or Java Standard Edition version 17 Long Term Support release, including basic programming concepts and the object-oriented fundamentals necessary at all levels of Java development. Authors Kishori Sharan and Adam L. Davis walk you through writing your first Java program step-by-step. Armed with that practical experience, you'll be ready to learn the core of the Java language. Beginning Java 17 Fundamentals provides over 90 diagrams and 240 complete programs to help you learn the topics faster. While this book teaches you the basics, it also has been revised to include the latest from Java 17 including the following: value types (records), immutable objects with an efficient memory layout; local variable type inference (var); pattern matching, a mechanism for testing and deconstructing values; sealed types, a mechanism for declaring all possible subclasses of a class; multiline text values; and switch expressions. The book continues with a series of foundation topics, including using data types, working with operators, and writing statements in Java. These basics lead onto the heart of the Java language: object-oriented programming. By learning topics such as classes, objects, interfaces, and inheritance you'll have a good understanding of Java's object-oriented model. The final collection of topics takes what you've learned and turns you into a real Java programmer. You'll see how to take the power of object-oriented programming and write programs that can handle errors and exceptions, process strings and dates, format data, and work with arrays to manipulate data. What You Will Learn Write your first Java programs with emphasis on learning object-oriented programming How to work with switch expressions, value types (records), local variable type inference, pattern matching switch and more from Java 17 Handle exceptions, assertions, strings and dates, and object formatting Learn about how to define and use modules Dive in depth into classes, interfaces, and inheritance in Java Use regular expressions Take advantage of the JShell REPL tool Who This Book Is For Those who are new to Java programming, who may have some or even no prior programming experience.

The use of Python as a powerful computational tool is expanding with great strides. Python is a language which is easy to use, and the libraries of tools provides it with efficient versatility. As the tools continue to expand, users can create insightful models and simulations. While the tools offer an easy method to create a pipeline, such constructions are not guaranteed to provide correct results. A lot of things can go wrong when building a simulation - deviously so. Users need to understand more than just how to build a process pipeline. Modeling and Simulation in Python introduces fundamental computational modeling techniques that are used in a variety of science and engineering disciplines. It emphasizes algorithmic thinking skills using different computational environments, and includes a number of interesting examples, including Shakespeare, movie databases, virus spread, and Chess. Key Features: Several theories and applications are provided, each with working Python scripts. All Python functions written for this book are archived on GitHub. Readers do not have to be Python experts, but a working knowledge of the language is required. Students who want to know more about the foundations of modeling and simulation will find this an educational and foundational resource.

Ada 2012 is the latest version of the international standard for the programming language Ada. It is designated ISO/IEC 8652:2012 (E) and is a new edition replacing the 2005 version. The primary goals for the new version were to further enhance its capabilities particularly in those areas where its reliability and predictability are of great value. Many important new features have been included such as those defining dynamic contracts and for handling multiprocessors and are integrated within the existing language framework in an elegant and coherent manner. The Ada 2012 Rationale describes not only the changes from Ada 2005 but also the reason for the changes. It starts with an introduction providing a general overview and this is followed by seven chapters focusing on contracts and aspects; extended expressions; structure and visibility; tasking and real time; iterators and pools; predefined library and containers. The book concludes with an epilogue largely concerned with compatibility issues.

Designed as a self-study guide, the book describes the real-world tradeoffs encountered in building a production-quality, platform-retargetable compiler. The authors examine the implementation of lcc, a production-quality, research-oriented retargetable compiler, designed at AT&T Bell Laboratories for the ANSI C programming language. The authors' innovative approach-a "literate program" that intermingles the text with the source code-uses a line-by-line explanation of the code to demonstrate how lcc is built.

This book investigates two major systems: firstly, co-operating distributed grammar systems, where the grammars work on one common sequential form and the co-operation is realized by the control of the sequence of active grammars; secondly, parallel communicating grammar systems, where each grammar works on its own sequential form and co-operation is done by means of communicating between grammars. The investigation concerns hierarchies with respect to different variants of co-operation, relations with classical formal language theory, syntactic parameters such as the number of components and their size, power of synchronization, and general notions generated from artificial intelligence.

There are three fundamental components in Control-Flow Integrity (CFI) enforcement. The first component is accurately recovering the policy (CFG). Usually, the more precise the policy is, the more security CFI improves, but precise CFG generation was considered hard without the support of source code. The second component is embedding the CFI policy securely. Current CFI enforcement usually inserts checks before indirect branches to consult a read-only table which stores the valid CFG information. However, this kind of read-only table can be overwritten by some kinds of attacks (e.g., the Rowhammer attack and data-oriented programming). The third component is to efficiently enforce the CFI policy. In current approaches CFI checks are always executed whenever there is an indirect control flow transfer. Therefore, it is critical to minimize the performance impact of CFI checks. In this book, we propose novel solutions to handle these three fundamental components. To generate a precise CFI policy without the support of the source code, we systematically study two methods which recover CFI policy based on function signature matching at the binary level and propose our novel rule- and heuristic-based mechanism to more accurately recover function signature. To embed CFI policy securely, we design a novel platform which encodes the policy into the machine instructions directly without relying on consulting any read-only data structure, by making use of the idea of instruction-set randomization. Each basic block is encrypted with a key derived from the CFG. To efficiently enforce CFI policy, we make use of a mature dynamic code optimization platform called DynamoRIO to enforce the policy so that we are only required to do the CFI check when needed.

Get insight into data science techniques such as data engineering and visualization, statistical modeling, machine learning, and deep learning. This book teaches you how to select variables, optimize hyper parameters, develop pipelines, and train, test, and validate machine and deep learning models. Each chapter includes a set of examples allowing you to understand the concepts, assumptions, and procedures behind each model. The book covers parametric methods or linear models that combat under- or over-fitting using techniques such as Lasso and Ridge. It includes complex regression analysis with time series smoothing, decomposition, and forecasting. It takes a fresh look at non-parametric models for binary classification (logistic regression analysis) and ensemble methods such as decision trees, support vector machines, and naive Bayes. It covers the most popular non-parametric method for time-event data (the Kaplan-Meier estimator). It also covers ways of solving classification problems using artificial neural networks such as restricted Boltzmann machines, multi-layer perceptrons, and deep belief networks. The book discusses unsupervised learning clustering techniques such as the K-means method, agglomerative and Dbscan approaches, and dimension reduction techniques such as Feature Importance, Principal Component Analysis, and Linear Discriminant Analysis. And it introduces driverless artificial intelligence using H2O. After reading this book, you will be able to develop, test, validate, and optimize statistical machine learning and deep learning models, and engineer, visualize, and interpret sets of data. What You Will Learn Design, develop, train, and validate machine learning and deep learning models Find optimal hyper parameters for superior model performance Improve model performance using techniques such as dimension reduction and regularization Extract meaningful insights for decision making using data visualization Who This Book Is For Beginning and intermediate level data scientists and machine learning engineers

Java is now well-established as one of the world's major programming languages, used in everything from desktop applications to web-hosted applications, enterprise systems and mobile devices. Java applications cover cloud-based services, the Internet of Things, self-driving cars, animation, game development, big data analysis and many more domains. The second edition of Foundational Java: Key Elements and Practical Programming presents a detailed guide to the core features of Java - and some more recent innovations - enabling the reader to build their skills and confidence though tried-and-trusted stages, supported by exercises that reinforce the key learning points. All the most useful and commonly applied Java syntax and libraries are introduced, along with many example programs that can provide the basis for more substantial applications. Use of the Eclipse Integrated Development Environment (IDE) and the JUnit testing framework is integral to the book, ensuring maximum productivity and code quality when learning Java, although to ensure that skills are not confined to one environment the fundamentals of the Java compiler and run time are also explained. Additionally, coverage of the Ant tool will equip the reader with the skills to automatically build, test and deploy applications independent of an IDE. Topics and features: * Presents the most up-to-date information on Java, including Java 14 * Examines the key theme of unit testing, introducing the JUnit 5 testing framework to emphasize the importance of unit testing in modern software development * Describes the Eclipse IDE, the most popular open source Java IDE and explains how Java can be run from the command line * Includes coverage of the Ant build tool * Contains numerous code examples and exercises throughout * Provides downloadable source code, self-test questions, PowerPoint slides and other supplementary material at the website http://www.foundjava.com This hands-on, classroom-tested textbook/reference is ideal for undergraduate students on introductory and intermediate courses on programming with Java. Professional software developers will also find this an excellent self-study guide/refresher on the topic. Dr. David Parsons is National Postgraduate Director at The Mind Lab, Auckland, New Zealand. He has been teaching programming in both academia and industry since the 1980s and writing about it since the 1990s.

XcalableMP is a directive-based parallel programming language based on Fortran and C, supporting a Partitioned Global Address Space (PGAS) model for distributed memory parallel systems. This open access book presents XcalableMP language from its programming model and basic concept to the experience and performance of applications described in XcalableMP. XcalableMP was taken as a parallel programming language project in the FLAGSHIP 2020 project, which was to develop the Japanese flagship supercomputer, Fugaku, for improving the productivity of parallel programing. XcalableMP is now available on Fugaku and its performance is enhanced by the Fugaku interconnect, Tofu-D. The global-view programming model of XcalableMP, inherited from High-Performance Fortran (HPF), provides an easy and useful solution to parallelize data-parallel programs with directives for distributed global array and work distribution and shadow communication. The local-view programming adopts coarray notation from Coarray Fortran (CAF) to describe explicit communication in a PGAS model. The language specification was designed and proposed by the XcalableMP Specification Working Group organized in the PC Consortium, Japan. The Omni XcalableMP compiler is a production-level reference implementation of XcalableMP compiler for C and Fortran 2008, developed by RIKEN CCS and the University of Tsukuba. The performance of the XcalableMP program was used in the Fugaku as well as the K computer. A performance study showed that XcalableMP enables a scalable performance comparable to the message passing interface (MPI) version with a clean and easy-to-understand programming style requiring little effort.

This book brings together a number of researchers and developers from industry and academia who report on their work. It is of interest to language designers and the creators of toolkits, UIMSs, and other user interface tools.

For courses in Visual Basic Programming. A Current and Comprehensive Introduction to Visual Basic Programming Schneider's Introduction to Programming Using Visual Basic has been consistently praised in the industry since 1991 and is a favorite of instructors and students. The 11th Edition is updated for Visual Basic 2017, providing an ideal tool for students learning their first programming language. The text keeps pace with modern programming methodology while incorporating current content and good programming practices. Schneider emphasizes problem solving by discussing problem-solving techniques early and using them throughout the book. He also ensures each chapter is rich yet concise by developing chapters around crucial subjects rather than covering too many topics superficially. The new edition provides a broad range of real-world examples, section-ending exercises, case studies, and programming projects that provide students with the most current and hands-on experience of any Visual Basic book on the market. The number and range of projects give instructors the flexibility to adapt the course according to the interests and abilities of students. Some programming projects in later chapters can be assigned as end-of-the-semester projects. Also available with MyLab Programming MyLab (TM) is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student.With MyLab Programming, students work through hundreds of short, auto-graded coding exercises and receive immediate and helpful feedback based on their work. Note: You are purchasing a standalone product; MyLab Programming does not come packaged with this content. Students, if interested in purchasing this title with MyLab Programming, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab Programming, search for: 0135862167 / 9780135862162 Introduction to Programming Using Visual Basic Plus MyLab Programming - Access Card Package, 11e Package consists of: 0135416116 / 9780135416112 MyLab Programming Standalone Access Card 0135416035 / 9780135416037 Introduction to Programming Using Visual Basic

Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts. MATLAB Recipes: A Problem-Solution Approach, Second Edition provides practical, hands-on code snippets and guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. What You Will Learn Get up to date with the latest MATLAB up to and including MATLAB 2020b Code in MATLAB Write applications in MATLAB Build your own toolbox of MATLAB code to increase your efficiency and effectiveness Who This Book Is For Engineers, data scientists, and students wanting a book rich in examples using MATLAB.

Discover the new and updated features of PHP 8, such as the JIT compiler, union types, and attributes, with code examples of each. For each feature, the author includes real-life cases for its use and explains its benefits. What You Will Learn Utilize the new features of PHP 8 and modern development technologies Work with the JIT compiler in PHP 8 Discover PHP 8 using real-life cases Increase your available resources to become more valuable in your development team Who This Book Is For Experienced PHP programmers new to PHP 8.

Term rewriting systems, which developed out of mathematical logic, consist of sequences of discrete steps where one term is replaced with another. Their many applications range from automatic theorem proving systems to computer algebra. This book begins with several examples, followed by a chapter on basic notions that provides a foundation for the rest of the work. First-order and higher-order theories are presented, with much of the latter material appearing for the first time in book form. Subjects treated include orthogonality, termination, lambda calculus and term graph rewriting. There is also a chapter detailing the required mathematical background.

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.

If you need to parse or process text data in Linux or Unix, this classic book explains how to use flex and bison to solve your problems quickly - whether you're interpreting code, configuration files, or any other structured format. "Flex and Bison" is the long-awaited sequel to the classic O'Reilly book, "Lex and Yacc". In the nearly two decades since that book was published, the "Flex and Bison" utilities have proven to be more reliable and more powerful than the original Unix tools. This book covers the same core functionality vital to Linux and Unix program development, along with several important new topics. This thoroughly updated edition will help you: address syntax crunching that regular expressions tools can't handle; build compilers and interpreters, and handle a wide range of text processing functions; learn key programming techniques, including syntax trees and symbol tables; implement a full SQL grammar, with complete sample code; and, use new features such as pure (reentrant) lexers and parsers, powerful GLR parsers, and interfaces to C++. This book includes revised tutorial sections for novice users and reference sections for advanced users, with chapters that explain each utility's basic usage and simple, stand-alone applications. Dive into "Flex and Bison" and discover the wide range of uses these flexible tools provide.

Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of the TensorFlow library, this new book provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node. Deploying computer vision, audio, and natural language processing in the browser Fine-tuning machine learning models with client-side data Constructing and training a neural network Interactive AI for browser games using deep reinforcement learning Generative neural networks to generate music and pictures TensorFlow.js is an open-source JavaScript library for defining, training, and deploying deep learning models to the web browser. It's quickly gaining popularity with developers for its amazing set of benefits including scalability, responsiveness, modularity, and portability. Shanging Cai and Eric Nielsen are senior software engineers on the Google Brain team. Stan Bileschi is the technical lead for Google's TensorFlow Usability team, which built the TensorFlow Layers API. All three have advanced degrees from MIT. Together, they're responsible for writing most of TensorFlow.js.

Edited in collaboration with FoLLI, the Association of Logic, Language and Information this book constitutes the refereed proceedings of the Second Interdisciplinary Workshop on Logic, Language, and Meaning, TLLM 2020, held in Tsinghua, China, in December 2020. The 12 full papers together presented were fully reviewed and selected from 40 submissions. Due to COVID-19 the workshop will be held online. The workshop covers a wide range of topics where monotonicity is discussed in the context of logic, causality, belief revision, quantification, polarity, syntax, comparatives, and various semantic phenomena in particular languages.