الصفحة 6
الصفحة 6
High performance computing – HiPC 2005 ; 12th International Conference, Goa, India, December 18-21, 2005, Proceedings
Contains the refereed proceedings of the 12th International Conference on High-Performance Computing. Beginning with the keynote section and the presentation of the 2 awarded best contributions, this book is organized in topical sections on algorithms, applications, architecture, systems software, communication networks, and systems and networks.
High performance computational science and engineering : IFIP TC5 Workshop on High Performance Computational Science and Engineering (HPCSE), World Computer Congress, August 22-27, 2004, Toulouse, France
The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of referred international conferences in computer science and interdisciplinary fields are featured. These results often precede journal publication and represent the most current research. The principal aim of the IFIP series is to encourage education and the dissemination and exchange of information about all aspects of computing.
Hebbian Learning and Negative Feedback Networks
This book is the outcome of a decade’s research into a speci?c architecture and associated learning mechanism for an arti?cial neural network: the - chitecture involves negative feedback and the learning mechanism is simple Hebbian learning. The research began with my own thesis at the University of Strathclyde, Scotland, under Professor Douglas McGregor which culminated with me being awarded a PhD in 1995 [52], the title of which was “Negative Feedback as an Organising Principle for Arti?cial Neural Networks”. Naturally enough, having established this theme, when I began to sup- vise PhD students of my own, we continued to develop this concept and this book owes much to the research and theses of these students at the Applied Computational Intelligence Research Unit in the University of Paisley . All of Chapters 3 to 8 deal with single stream arti?cial neural networks.
Health Information Science ; 9th International Conference, HIS 2020, Amsterdam, The Netherlands, October 20–23, 2020, Proceedings
This book constitutes the proceedings of the 9th International Conference on Health Information Science, HIS 2020, which took place in Amsterdam, The Netherlands, during October 20-23, 2020. The 11 full papers and 6 short papers presented in this volume were carefully reviewed and selected from 62 submissions. They were organized in topical sections named: mental health; medical record processing; medical information systems; medical diagnosis with machine learning; and health behavior and medication.
Hands-On Data Structures and Algorithms with Python : Store, manipulate, and access data effectively ; 3rd ed.
Expands your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer. By the end of this Python book, you'll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications
Handbook on Craniofacial Superimposition : The MEPROCS Project
This book is the first comprehensive guide to a new soft computing technique which is used in complex forensic cases. The chapters include detailed technical and practical overviews, and discussions about the latest tools, open problems and ethical and legal issues involved. The book will be of interest to researchers and practitioners in forensic medicine and computational intelligence.
Handbook on artificial intelligence -empowered applied software engineering ; Vol.1 : Novel methodologies to engineering smart software systems
Provides a structured overview of artificial intelligence-empowered applied software engineering. Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions lead current research towards the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence.
Handbook of Nature-Inspired and Innovative Computing : Integrating Classical Models with Emerging Technologies
This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies" is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.
Handbook of Mathematical Models in Computer Vision
In this edited volume we present the most prominent mathematical models that are considered in computational vision. To this end, tasks of increasing complexity are considered and we present the state-of-the-art methods to cope with such tasks. The volume consists of six thematic areas that provide answers to the most dominant questions of computational vision: Image reconstruction, Segmentation and object extraction, Shape modeling and registration, Motion analysis and tracking, 3D from images, geometry and reconstruction Applications in medical image analysis
Handbook Of Mathematical Models For Languages And Computation
Introduces a variety of concepts in discrete mathematics and mathematical modeling for languages and computation. The authors pay special attention to the implementation of mathematical concepts to explain clearly how to encode them in computational practice. All computer programs are written in C#. The theory of computation is used to address challenges arising in many computer science areas such as artificial intelligence, language processors, compiler writing, information and coding systems, programming language design, computer architecture and more. To grasp topics concerning this theory readers need to familiarize themselves with its computational and language models, based on concepts of discrete mathematics including sets, relations, functions, graphs and logic.
Handbook of Geometric Computing : Applications in Pattern Recognition, Computer Vision, Neuralcomputing, and Robotics
Many computer scientists, engineers, applied mathematicians, and physicists use geometry theory and geometric computing methods in the design of perception-action systems, intelligent autonomous systems, and man-machine interfaces. This handbook brings together the most recent advances in the application of geometric computing for building such systems, with contributions from leading experts in the important fields of neuroscience, neural networks, image processing, pattern recognition, computer vision, uncertainty in geometric computations, conformal computational geometry, computer graphics and visualization, medical imagery, geometry and robotics, and reaching and motion planning. For the first time, the various methods are presented in a comprehensive, unified manner.
Handbook of big data analytics ; Vol.2 : Applications in ICT, security and business analytics
Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time.
Handbook of big data analytics ; Vol.1 : Methodologies
Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time. This volume presents several methodologies to support Big Data analytics including database management, processing frameworks and architectures, data lakes, query optimization strategies, towards real-time data processing, data stream analytics, Fog and Edge computing, and Artificial Intelligence and Big Data.
Guide to Deep Learning Basics : Logical, Historical and Philosophical Perspectives
This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton.
Grid computing in life science ; 1st International Workshop on Life Science Grid, LSGRID 2004 Kanazawa, Japan, May 31-June 1, 2004, Revised Selected and Invited Papers
Researchers in the ?eld of life sciences rely increasingly on information te- nology to extract and manage relevant knowledge. The complex computational and data management needs of life science research make Grid technologies an attractive support solution. However, many important issues must be addressed before the Life Science Grid becomes commonplace. The 1st International Life Science Grid Workshop (LSGRID 2004) was held in Kanazawa Japan, May 31–June 1, 2004. This workshop focused on life s- ence applications of grid systems especially for bionetwork research and systems biology which require heterogeneous data integration from genome to phenome, mathematical modeling and simulation from molecular to population levels, and high-performance computing including parallel processing, special hardware and grid computing.
Graph-theoretic concepts in computer science ; Vol. 3787 ; 31st International Workshop, WG 2005, Metz, France, June 23-25, 2005, Revised Selected Papers
that aims to unite theory and practice by demonstrating how graph-theoretic concepts can be applied to various areas in Computer Science. This book provides results for various classes of graphs, graph computations, graph algorithms, and graph-theoretical applications in various fields.
Graph-theoretic concepts in computer science ; 30th International workshop, WG 2004, Bad Honnef, Germany, June 21-23, 2004, Revised Papers
During its 30-year existence, the International Workshop on Graph-Theoretic Concepts in Computer Science has become a distinguished and high-quality computer science event. The workshop aims at uniting theory and practice by demonstrating how graph-theoretic concepts can successfully be applied to v- ious areas of computer science and by exposing new theories emerging from applications. In this way, WG provides a common ground for the exchange of information among people dealing with several graph problems and working in various disciplines. Thereby, the workshop contributes to forming an interdis- plinary research community. The original idea of the Workshop on Graph-Theoretic Concepts in C- puter Science was ingenuity in all theoretical aspects and applications of graph concepts, wherever applied. Within the last ten years, the development has strengthened in particular the topic of structural graph properties in relation to computational complexity.
Graph-based representations in pattern recognition ; 6th IAPR-TC-15 International Workshop, GbRPR 2007, Alicante, Spain, June 11-13, 2007, Proceedings
Constitutes the refereed proceedings of the 6th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2007, held in Alicante, Spain in June 2007.
Graph-based representations in pattern recognition ; 5th IAPR International Workshop, GbRPR 2005, Poitiers, France, April 11-13, 2005, Proceedings
Many vision problems have to deal with di?erent entities (regions, lines, line junctions, etc.) and their relationships. These entities together with their re- tionships may be encoded using graphs or hypergraphs. The structural inf- mation encoded by graphs allows computer vision algorithms to address both the features of the di?erent entities and the structural or topological relati- ships between them. Moreover, turning a computer vision problem into a graph problem allows one to access the full arsenal of graph algorithms developed in computer science. The Technical Committee (TC15, http://www.iapr.org/tcs.html) of the IAPR (International Association for Pattern Recognition) has been funded in order to federate and to encourage research work in these ?elds. Among its - tivities, TC15 encourages the organization of special graph sessions at many computer vision conferences and organizes the biennial workshop GbR.
Graph-based Knowledge Representation : Computational Foundations of Conceptual Graphs
This book studies a graph-based knowledge representation and reasoning formalism stemming from conceptual graphs, with a substantial focus on the computational properties.Knowledge can be symbolically represented in many ways, and the authors have chosen labeled graphs for their modeling and computational qualities. the authors have attempted to answer, the following question:`how far is it possible to go in knowledge representation and reasoning by representing knowledge with graphs and reasoning with graph operations?''
