Programming for Linguists

Programming for Linguists: Java (TM) Technology for Language Researchers is a practical introduction to programming using the Java Programming Language for linguists and related language professionals.

Explore the theoretical foundations and real-world power system applications of convex programming In Mathematical Programming for Power System Operation with Applications in Python , Professor Alejandro Garces delivers a comprehensive overview of power system operations models with a focus on convex optimization models and their implementation in Python. Divided into two parts, the book begins with a theoretical analysis of convex optimization models before moving on to related applications in power systems operations. The author eschews concepts of topology and functional analysis found in more mathematically oriented books in favor of a more natural approach. Using this perspective, he presents recent applications of convex optimization in power system operations problems. Mathematical Programming for Power System Operation with Applications in Python uses Python and CVXPY as tools to solve power system optimization problems and includes models that can be solved with the presented framework. The book also includes: A thorough introduction to power system operation, including economic and environmental dispatch, optimal power flow, and hosting capacity Comprehensive explorations of the mathematical background of power system operation, including quadratic forms and norms and the basic theory of optimization Practical discussions of convex functions and convex sets, including affine and linear spaces, politopes, balls, and ellipsoids In-depth examinations of convex optimization, including global optimums, and first and second order conditions Perfect for undergraduate students with some knowledge in power systems analysis, generation, or distribution, Mathematical Programming for Power System Operation with Applications in Python is also an ideal resource for graduate students and engineers practicing in the area of power system optimization.

New automated, application-independent methodology for designing and deploying sensor networks Following this book's clear explanations, examples, and illustrations, domain experts can design and deploy nontrivial networked sensing applications without much knowledge of the low-level networking aspects of deployment. This new approach is based on the Abstract Task Graph (ATaG), a data-driven programming model and an innovative methodology forarchitecture-independent programming and automatic software synthesis for sensor networks. ATaG programs are concise, understandable, and network-independent descriptions of global application functionality that can be automatically compiled onto any target deployment. The book begins with an overview chapter that addresses the important issues of programming methodologies and compares various programming models for sensor networks. Next, the authors set forth everything you need for designing and deploying sensor networks using ATaG, including: Detailed description of the ATaG model's features System-level support for architecture-independent programming Examination of the graphical programming and software synthesis environment for ATaG Case study illustrating the process of end-to-end application development and software synthesis using ATaG Throughout the book, the authors provide code excerpts and figures to help clarify key concepts and explain each step. For programmers, the graphical formalism of the ATaG program, coupled with the fact it uses an existing language (Java), means that no special training is needed to start developing and deploying applications in ATaG. Everything you need to know is clearly set forth in this book.

The only guide for developers and power users on how to build PC connectivity applications for Symbian OS. This unique handbook provides all the information that is needed for the job. Fully worked examples and a do's and don'ts section provide design recommendations and expose common pitfalls giving a highly practical focus. Explains the relevant parts of the protocols that need to be used Demonstrates how to create your own device side components to provide new services Shows how to handle custom servers and socket servers

Learn how to successfully implement trustworthy computing tasks using aspect-oriented programming This landmark publication fills a gap in the literature by not only describing the basic concepts of trustworthy computing (TWC) and aspect-oriented programming (AOP), but also exploring their critical interrelationships. The author clearly demonstrates how typical TWC tasks such as security checks, in-and-out conditions, and multi-threaded safety can be implemented using AOP. Following an introduction, the book covers: Trustworthy computing, software engineering, and computer science Aspect-oriented programming and Aspect.NET Principles and case studies that apply AOP to TWC Coverage includes Aspect.NET, the AOP framework developed by the author for the Microsoft.NET platform, currently used in seventeen countries. The author discusses the basics of Aspect.NET architecture, its advantages compared to other AOP tools, and its functionality. The book has extensive practical examples and case studies of trustworthy software design and code using the Aspect.NET framework. In addition, the book explores other software technologies and tools for using AOP for trustworthy software development, including Java and AspectJ. This book also includes a valuable chapter dedicated to ERATO, the author's teaching method employed in this book, which has enabled thousands of students to quickly grasp and apply complex concepts in computing and software engineering, while the final chapter presents an overall perspective on the current state of AOP and TWC with a view toward the future. Software engineers, architects, developers, programmers, and students should all turn to this book to learn this tested and proven method to create more secure, private, and reliable computing.

COMPREHENSIVE COVERAGE OF NONLINEAR PROGRAMMING THEORY AND ALGORITHMS, THOROUGHLY REVISED AND EXPANDED Nonlinear Programming: Theory and Algorithms—now in an extensively updated Third Edition—addresses the problem of optimizing an objective function in the presence of equality and inequality constraints. Many realistic problems cannot be adequately represented as a linear program owing to the nature of the nonlinearity of the objective function and/or the nonlinearity of any constraints. The Third Edition begins with a general introduction to nonlinear programming with illustrative examples and guidelines for model construction. Concentration on the three major parts of nonlinear programming is provided: Convex analysis with discussion of topological properties of convex sets, separation and support of convex sets, polyhedral sets, extreme points and extreme directions of polyhedral sets, and linear programming Optimality conditions and duality with coverage of the nature, interpretation, and value of the classical Fritz John (FJ) and the Karush-Kuhn-Tucker (KKT) optimality conditions; the interrelationships between various proposed constraint qualifications; and Lagrangian duality and saddle point optimality conditions Algorithms and their convergence, with a presentation of algorithms for solving both unconstrained and constrained nonlinear programming problems Important features of the Third Edition include: New topics such as second interior point methods, nonconvex optimization, nondifferentiable optimization, and more Updated discussion and new applications in each chapter Detailed numerical examples and graphical illustrations Essential coverage of modeling and formulating nonlinear programs Simple numerical problems Advanced theoretical exercises The book is a solid reference for professionals as well as a useful text for students in the fields of operations research, management science, industrial engineering, applied mathematics, and also in engineering disciplines that deal with analytical optimization techniques. The logical and self-contained format uniquely covers nonlinear programming techniques with a great depth of information and an abundance of valuable examples and illustrations that showcase the most current advances in nonlinear problems.

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.

An accessible treatment of the modeling and solution of integer programming problems, featuring modern applications and software In order to fully comprehend the algorithms associated with integer programming, it is important to understand not only how algorithms work, but also why they work. Applied Integer Programming features a unique emphasis on this point, focusing on problem modeling and solution using commercial software. Taking an application-oriented approach, this book addresses the art and science of mathematical modeling related to the mixed integer programming (MIP) framework and discusses the algorithms and associated practices that enable those models to be solved most efficiently. The book begins with coverage of successful applications, systematic modeling procedures, typical model types, transformation of non-MIP models, combinatorial optimization problem models, and automatic preprocessing to obtain a better formulation. Subsequent chapters present algebraic and geometric basic concepts of linear programming theory and network flows needed for understanding integer programming. Finally, the book concludes with classical and modern solution approaches as well as the key components for building an integrated software system capable of solving large-scale integer programming and combinatorial optimization problems. Throughout the book, the authors demonstrate essential concepts through numerous examples and figures. Each new concept or algorithm is accompanied by a numerical example, and, where applicable, graphics are used to draw together diverse problems or approaches into a unified whole. In addition, features of solution approaches found in today's commercial software are identified throughout the book. Thoroughly classroom-tested, Applied Integer Programming is an excellent book for integer programming courses at the upper-undergraduate and graduate levels. It also serves as a well-organized reference for professionals, software developers, and analysts who work in the fields of applied mathematics, computer science, operations research, management science, and engineering and use integer-programming techniques to model and solve real-world optimization problems.