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Beginning Object-Oriented Programming with VB 2005 : From novice to professional
Beginning Object-Oriented Programming with VB 2005 is a comprehensive resource of correct coding procedures. Author Daniel Clark takes you through all the stages of a programming project, including analysis, modeling, and development, all using object-oriented programming techniques and Visual Basic .NET. Clark explores the structure of classes and their hierarchies, as well as inheritance and interfaces. He also introduces the .NET Framework and the Visual Studio integrated development environment, or IDE. A real-world case study walks you through the design of a solution. You can then transform the design into a functional VB .NET application. The application includes a graphical user interface (GUI), a business logic class library, and integration with a back-end database. Throughout the book, you'll explore the fundamentals of software design, object-oriented programming, Visual Basic .NET 2.0, and the Unified Modeling Language (UML).
Beginning Java Data Structures and Algorithms : Sharpen your problem solving skills by learning core computer science concepts in a pain-free manner
Teaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and big O notation, later explains bubble, merge, quicksort, and other popular programming patterns. You’ll also learn about data structures such as binary trees, hash tables, and graphs. The book progresses to advanced concepts, such as algorithm design paradigms and graph theory. By the end of the book, you will know how to correctly implement common algorithms and data structures within your applications.
Beginning J2ME : From novice to professional
Have you thought about building games for your cell phone or other wireless devices? Whether you are a first–time wireless Java developer, or an experienced professional Beginning J2ME, Third Edition brings exciting wireless and mobile Java application development right to your door! This book will empower you with numerous topics: sound HTTPS support, user interface API enhancements, sound/music API, a Game API, 3D graphics, and Bluetooth. Further, this book is easy to read and includes many practical, hands–on, and ready–to–use code examples. You will not be disappointed.
Beginning GIMP : From novice to professional
Beginning GIMP: From Novice to Professional explains how to use the open source image manipulation program, GIMP version 2.4. You'll learn how to install GIMP on Windows, Linux, and MacOS X platforms. Once you've installed the application, you'll learn about the interface and configuration options, and then jump into a quick–and–simple project to familiarize yourself even further. With four–color graphics and screenshots throughout, you'll learn how to prepare camera images for display on web pagesincluding functions like rescaling, cropping, and balancing color. The book also explains with great detail how to utilize layers, paths, and masks. You'll also learn how to draw lines and shapes, use patterns and gradients, and even create your own brushes, patterns, and gradients.
Bayesian Networks and Decision Graphs
Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis. The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams.It contians two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems.
Artificial intelligence in image-based screening, diagnostics, and clinical care of cardiopulmonary diseases
In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases.
Artificial intelligence hardware design : Challenges and solutions
Learn foundational and advanced topics in Neural Processing Unit design with real-world examples from leading voices in the field. A thorough introduction to neural networks and neural network development history, as well as Convolutional Neural Network (CNN) models Explorations of various parallel architectures, including the Intel CPU, Nvidia GPU, Google TPU, and Microsoft NPU, emphasizing hardware and software integration for performance improvement Discussions of streaming graph for massive parallel computation with the Blaize GSP and Graphcore IPU An examination of how to optimize convolution with UCLA Deep Convolutional Neural Network accelerator filter decomposition
Artificial intelligence for multisource geospatial information
Collects 10 original research contributions published in the Special Issue entitled “Artificial Intelligence for Multisource Geospatial Information” of the ISPRS International Journal of Geo-Information. The focus is on different methods of Geospatial Artificial Intelligence (GeoAI) based on deep learning using different network architectures, clustering, soft computing, and semantic approaches. They are proposed to deal with a variety of Geospatial Big Data (GBD), such as georeferenced texts and photos in social networks, remote sensing images, cartographic maps, multidimensional geo databases, metadata in spatial data infrastructures, and for different tasks, such as for multisource georeferenced text integration and geodata flexible querying, for social sensing by applying sentiment analysis, clustering and geo analysis, for segmentation of roads, clouds and snow, and for detection of small targets and people on the streets.
Artificial intelligence applied to medical imaging and computational biology
Medical imaging and computational biology continuously pose new fundamental medical and biological questions that often give rise to novel challenges in Artificial Intelligence. These research fields present an increasing need for the application of cutting-edge computational approaches that generally involve machine learning or computational intelligence techniques, which can effectively perform bioimage and biosignal processing in different clinical areas.
Artificial general intelligence
This book focused on engineering general intelligence – autonomous, self-reflective, self-improving, commonsensical intelligence.Each author explains a specific aspect of AGI in detail in each chapter, while also investigating the common themes in the work of diverse groups, and posing the big, open questions in this vital area.
Architecture of computing systems - ARCS 2008 ; 21st International Conference, Dresden, Germany, February 25-28, 2008. Proceedings
This book constitutes the refereed proceedings of the 21st International Conference on Architecture of Computing Systems, ARCS 2008, held in Dresden, Germany, in February 2008.
Arabic and Chinese Handwriting Recognition ; SACH 2006 Summit College Park, MD, USA, September 27-28, 2006 Selected Papers
Cheriet provides an overview of the problems of Arabic recognition and how systems can use natural language processing techniques to correct errors in lexicon-based systems.
Applied cryptography and network security ; 6th International Conference, ACNS 2008, New York, NY, USA, June 3-6, 2008. Proceedings
This book constitutes the refereed proceedings of the 6th International Conference on Applied Cryptography and Network Security, ACNS 2008, held in New York, NY, USA, in June 2008.
Applications of Membrane Computing
Membrane computing is a branch of natural computing which investigates computing models abstracted from the structure and functioning of living cells and from their interactions in tissues or higher-order biological structures. The models considered, called membrane systems (P systems), are parallel, distributed computing models, processing multisets of symbols in cell-like compartmental architectures. In many applications membrane systems have considerable advantages – among these are their inherently discrete nature, parallelism, transparency, scalability and nondeterminism.
Applications of Graph Transformations with Industrial Relevance ; 3rd International Symposium, AGTIVE 2007, Kassel, Germany, October 10-12, 2007, Revised Selected and Invited Papers
This book constitutes the thoroughly refereed post-conference proceedings of the Third International Symposium on Applications of Graph Transformations, AGTIVE 2007, held in Kassel, Germany, in October 2007.
Anisotropy Across Fields and Scales
This book focuses on processing, modeling, and visualization of anisotropy information…
Analyzing computer system performance with Perl::PDQ
Analyzing computer system performance is often regarded by most system administrators, IT professionals and software engineers as a black art that is too time consuming to learn and apply. Finally, this book by acclaimed performance analyst Dr. Neil Gunther makes this subject understandable and applicable through programmatic examples. The means to this end is the open-source performance analyzer Pretty Damn Quick (PDQ) written in Perl As the epigraph in this book points out, Common sense is the pitfall of performance analysis. The performance analysis framework that replaces common sense is revealed in the first few chapters of Part I. The important queueing concepts embedded in PDQ are explained in a very simple style that does not require any knowledge of formal probability theory. Part II begins with a full specification of how to set up and use PDQ replete with examples written in Perl. Subsequent chapters present applications of PDQ to the performance analysis of multicomputer architectures, benchmark results, client/server scalability, and Web-based applications.
Alternative breast imaging : Four model-based approaches
Medical imaging has been transformed over the past 30 years by the advent of computerized tomography (CT), magnetic resonance imaging (MRI), and various advances in x-ray and ultrasonic techniques. An enabling force behind this progress has been the (so far) exponentially increasing power of computers, which has made it practical to explore fundamentally new approaches. In particular, what our group terms "model-based" modalities-which produce tissue property images from data using nonlinear, iterative numerical modeling techniques-have become increasingly feasible. Alternative Breast Imaging: Four Model-Based Approaches explores our research on four such modalities, particularly with regard to imaging of the breast: (1) MR elastography (MRE), (2) electrical impedance spectroscopy (EIS), (3) microwave imaging spectroscopy (MIS), and (4) near infrared spectroscopic imaging (NIS).
Algorithms on Trees and Graphs : With Python Code
Introduces graph algorithms on an intuitive basis followed by a detailed exposition using structured pseudocode, with correctness proofs as well as worst-case analyses. Centered around the fundamental issue of graph isomorphism, the content goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. Numerous illustrations, examples, problems, exercises, and a comprehensive bibliography support students and professionals in using the book as a text and source of reference. Furthermore, Python code for all algorithms presented is given in an appendix. Topics and features: Algorithms are first presented on an intuitive basis, followed by a detailed exposition using structured pseudocode / Correctness proofs are given, together with a worst-case analysis of the algorithms / Full implementation of all the algorithms in Python / An extensive chapter is devoted to the algorithmic techniques used in the book / Solutions to all the problems
Algorithms in Invariant Theory
The book of Sturmfels is both an easy-to-read textbook for invariant theory and a challenging research monograph that introduces a new approach to the algorithmic side of invariant theory. The Groebner bases method is the main tool by which the central problems in invariant theory become amenable to algorithmic solutions.
