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Stop manually analyzing binary! Practical Binary Analysis is the first book of its kind to present advanced binary analysis topics, such as binary instrumentation, dynamic taint analysis, and symbolic execution, in an accessible way. After an introduction on the basics of binary formats, disassembly, and code injection, you´ll dive into more complex subjects, and by the end of the book, you´ll be able to build your own binary analysis tools on Linux. Practical Binary Analysis will help interested people become well-rounded binary analysts, who are capable of developing and exploring new ideas on their own.
Service-oriented computing has become one of the predominant factors in IT research and development efforts over the last few years. In spite of several standardization efforts that advanced from research labs into industrial-strength technologies and tools, there is still much human effort required in the process of finding and executing Web services. Here, Dieter Fensel and his team lay the foundation for understanding the Semantic Web Services infrastructure, aimed at eliminating human intervention and thus allowing for seamless integration of information systems. They focus on the currently most advanced SWS infrastructure, namely SESA and related work such as the Web Services Execution Environment (WSMX) activities and the Semantic Execution Environment (OASIS SEE TC) standardization effort. Their book is divided into four parts: Part I provides an introduction to the field and its history, covering basic Web technologies and the state of research and standardization in the Semantic Web field. Part II presents the SESA architecture. The authors detail its building blocks and show how they are consolidated into a coherent software architecture that can be used as a blueprint for implementation. Part III gives more insight into middleware services, describing the necessary conceptual functionality that is imposed on the architecture through the basic principles. Each such functionality is realized using a number of so-called middleware services. Finally, Part IV shows how the SESA architecture can be applied to real-world scenarios, and provides an overview of compatible and related systems. The book targets professionals as well as academic and industrial researchers working on various aspects of semantic integration of distributed information systems. They will learn how to apply the Semantic Web Services infrastructure to automate and semi-automate tasks, by using existing integration technologies. In addition, the book is also suitable for advanced graduate students enrolled in courses covering knowledge management, the Semantic Web, or integration of information systems, as it will educate them about basic technologies for Semantic Web Services and general issues related to integration of information systems.
This book provides a comprehensive, modern introduction to convex optimization, a field that is becoming increasingly important in applied mathematics, economics and finance, engineering, and computer science, notably in data science and machine learning. Written by a leading expert in the field, this book includes recent advances in the algorithmic theory of convex optimization, naturally complementing the existing literature. It contains a unified and rigorous presentation of the acceleration techniques for minimization schemes of first- and second-order. It provides readers with a full treatment of the smoothing technique, which has tremendously extended the abilities of gradient-type methods. Several powerful approaches in structural optimization, including optimization in relative scale and polynomial-time interior-point methods, are also discussed in detail. Researchers in theoretical optimization as well as professionals working on optimization problems will find this book very useful. It presents many successful examples of how to develop very fast specialized minimization algorithms. Based on the author´s lectures, it can naturally serve as the basis for introductory and advanced courses in convex optimization for students in engineering, economics, computer science and mathematics.
This volume aims to stimulate discussions on research involving the use of data and digital images as an understanding approach for analysis and visualization of phenomena and experiments. The emphasis is put not only on graphically representing data as a way of increasing its visual analysis, but also on the imaging systems which contribute greatly to the comprehension of real cases. Scientific Visualization and Imaging Systems encompass multidisciplinary areas, with applications in many knowledge fields such as Engineering, Medicine, Material Science, Physics, Geology, Geographic Information Systems, among others. This book is a selection of 13 revised and extended research papers presented in the International Conference on Advanced Computational Engineering and Experimenting -ACE-X conferences 2010 (Paris), 2011 (Algarve), 2012 (Istanbul) and 2013 (Madrid). The examples were particularly chosen from materials research, medical applications, general concepts applied in simulations and image analysis and other interesting related problems.
Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation. In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you´ll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts. What You´ll Learn Understand the fundamentals of the Python programming language Apply Python to numerical computational programming projects in engineering and science Discover the Pythonic way of life Apply data types, operators, and arrays Carry out plotting for visualization Work with functions and loops Who This Book Is For Engineers, scientists, researchers, and students who are new to Python. Some prior programming experience would be helpful but not required.
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.
O´Reilly´s bestselling book on Linux´s bash shell is at it again. Now that Linux is an established player both as a server and on the desktop Learning the bash Shell has been updated and refreshed to account for all the latest changes. Indeed, this third edition serves as the most valuable guide yet to the bash shell. As any good programmer knows, the first thing users of the Linux operating system come face to face with is the shell the UNIX term for a user interface to the system. In other words, it´s what lets you communicate with the computer via the keyboard and display. Mastering the bash shell might sound fairly simple but it isn´t. In truth, there are many complexities that need careful explanation, which is just what Learning the bash Shell provides. If you are new to shell programming, the book provides an excellent introduction, covering everything from the most basic to the most advanced features. And if you´ve been writing shell scripts for years, it offers a great way to find out what the new shell offers. Learning the bash Shell is also full of practical examples of shell commands and programs that will make everyday use of Linux that much easier. With this book, programmers will learn: - How to install bash as your login shell - The basics of interactive shell use, including UNIX file and directory structures, standard I/O, and background jobs - Command line editing, history substitution, and key bindings - How to customize your shell environment without programming - The nuts and bolts of basic shell programming, flow control structures, command-line options and typed variables - Process handling, from job control to processes, coroutines and subshells - Debugging techniques, such as trace and verbose modes - Techniques for implementing system-wide shell customization and features related to system security
John Vince describes a range of mathematical topics to provide a foundation for an undergraduate course in computer science, starting with a review of number systems and their relevance to digital computers, and finishing with differential and integral calculus. Readers will find that the author´s visual approach will greatly improve their understanding as to why certain mathematical structures exist, together with how they are used in real-world applications. Each chapter includes full-colour illustrations to clarify the mathematical descriptions, and in some cases, equations are also coloured to reveal vital algebraic patterns. The numerous worked examples will consolidate comprehension of abstract mathematical concepts. Foundation Mathematics for Computer Science covers number systems, algebra, logic, trigonometry, coordinate systems, determinants, vectors, matrices, geometric matrix transforms, differential and integral calculus, and reveals the names of the mathematicians behind such inventions. During this journey, John Vince touches upon more esoteric topics such as quaternions, octonions, Grassmann algebra, Barycentric coordinates, transfinite sets and prime numbers. Whether you intend to pursue a career in programming, scientific visualisation, systems design, or real-time computing, you should find the author´s literary style refreshingly lucid and engaging, and prepare you for more advanced texts.
In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.