Visual Complexity and Intelligent Computer Graphics Techniques Enhancements

Visual Complexity and Intelligent Computer Graphics Techniques Enhancements PDF Author: Dimitri Plemenos
Publisher: Springer Science & Business Media
ISBN: 3642012582
Category : Computers
Languages : en
Pages : 255

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Book Description
In this book, three main notions will be used in the editors search of improvements in various areas of computer graphics: Artificial Intelligence, Viewpoint Complexity and Human Intelligence. Several Artificial Intelligence techniques are used in presented intelligent scene modelers, mainly declarative ones. Among them, the mostly used techniques are Expert systems, Constraint Satisfaction Problem resolution and Machine-learning. The notion of viewpoint complexity, that is complexity of a scene seen from a given viewpoint, will be used in improvement proposals for a lot of computer graphics problems like scene understanding, virtual world exploration, image-based modeling and rendering, ray tracing and radiosity. Very often, viewpoint complexity is used in conjunction with Artificial Intelligence techniques like Heuristic search and Problem resolution. The notions of artificial Intelligence and Viewpoint Complexity may help to automatically resolve a big number of computer graphics problems. However, there are special situations where is required to find a particular solution for each situation. In such a case, human intelligence has to replace, or to be combined with, artificial intelligence. Such cases, and proposed solutions are also presented in this book.

Visual Complexity and Intelligent Computer Graphics Techniques Enhancements

Visual Complexity and Intelligent Computer Graphics Techniques Enhancements PDF Author: Dimitri Plemenos
Publisher: Springer Science & Business Media
ISBN: 3642012582
Category : Computers
Languages : en
Pages : 255

Get Book Here

Book Description
In this book, three main notions will be used in the editors search of improvements in various areas of computer graphics: Artificial Intelligence, Viewpoint Complexity and Human Intelligence. Several Artificial Intelligence techniques are used in presented intelligent scene modelers, mainly declarative ones. Among them, the mostly used techniques are Expert systems, Constraint Satisfaction Problem resolution and Machine-learning. The notion of viewpoint complexity, that is complexity of a scene seen from a given viewpoint, will be used in improvement proposals for a lot of computer graphics problems like scene understanding, virtual world exploration, image-based modeling and rendering, ray tracing and radiosity. Very often, viewpoint complexity is used in conjunction with Artificial Intelligence techniques like Heuristic search and Problem resolution. The notions of artificial Intelligence and Viewpoint Complexity may help to automatically resolve a big number of computer graphics problems. However, there are special situations where is required to find a particular solution for each situation. In such a case, human intelligence has to replace, or to be combined with, artificial intelligence. Such cases, and proposed solutions are also presented in this book.

Visual Complexity and Intelligent Computer Graphics Techniques Enhancements

Visual Complexity and Intelligent Computer Graphics Techniques Enhancements PDF Author: Dimitri Plemenos
Publisher: Springer
ISBN: 3642012590
Category : Computers
Languages : en
Pages : 255

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Book Description
In this book, three main notions will be used in the editors search of improvements in various areas of computer graphics: Artificial Intelligence, Viewpoint Complexity and Human Intelligence. Several Artificial Intelligence techniques are used in presented intelligent scene modelers, mainly declarative ones. Among them, the mostly used techniques are Expert systems, Constraint Satisfaction Problem resolution and Machine-learning. The notion of viewpoint complexity, that is complexity of a scene seen from a given viewpoint, will be used in improvement proposals for a lot of computer graphics problems like scene understanding, virtual world exploration, image-based modeling and rendering, ray tracing and radiosity. Very often, viewpoint complexity is used in conjunction with Artificial Intelligence techniques like Heuristic search and Problem resolution. The notions of artificial Intelligence and Viewpoint Complexity may help to automatically resolve a big number of computer graphics problems. However, there are special situations where is required to find a particular solution for each situation. In such a case, human intelligence has to replace, or to be combined with, artificial intelligence. Such cases, and proposed solutions are also presented in this book.

Complex Networks

Complex Networks PDF Author: Ronaldo Menezes
Publisher: Springer
ISBN: 364201206X
Category : Computers
Languages : en
Pages : 232

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Book Description
Though the reductionist approachto biology and medicine has led to several imp- tant advances, further progresses with respect to the remaining challenges require integration of representation, characterization and modeling of the studied systems along a wide range of spatial and time scales. Such an approach, intrinsically - lated to systems biology, is poised to ultimately turning biology into a more precise and synthetic discipline, paving the way to extensive preventive and regenerative medicine [1], drug discovery [20] and treatment optimization [24]. A particularly appealing and effective approach to addressing the complexity of interactions inherent to the biological systems is provided by the new area of c- plex networks [34, 30, 8, 13, 12]. Basically, it is an extension of graph theory [10], focusing on the modeling, representation, characterization, analysis and simulation ofcomplexsystemsbyconsideringmanyelementsandtheirinterconnections.C- plex networks concepts and methods have been used to study disease [17], tr- scription networks [5, 6, 4], protein-protein networks [22, 36, 16, 39], metabolic networks [23] and anatomy [40].

Biologically-Inspired Optimisation Methods

Biologically-Inspired Optimisation Methods PDF Author: Andrew Lewis
Publisher: Springer
ISBN: 3642012620
Category : Technology & Engineering
Languages : en
Pages : 365

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Book Description
This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences on e-Science, Grid Computing and Evolutionary computation.

Computer and Information Science 2009

Computer and Information Science 2009 PDF Author: Roger Lee
Publisher: Springer
ISBN: 3642012094
Category : Technology & Engineering
Languages : en
Pages : 310

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Book Description
This volume includes the best papers of the IEEE/ACIS International Conference on Computer and Information Science, ICIS 2009, held on June 2009 in Shanghai, China.

Opportunities and Challenges for Next-Generation Applied Intelligence

Opportunities and Challenges for Next-Generation Applied Intelligence PDF Author: Been-Chian Chien
Publisher: Springer Science & Business Media
ISBN: 3540928138
Category : Mathematics
Languages : en
Pages : 341

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Book Description
The term “Artificial Intelligence” has been used since 1956 and has become a very popular research field. Generally, it is the study of the computations that enable a system to perceive, reason and act. In the early days, it was expected to achieve the same intelligent behavior as a human, but found impossible at last. Its goal was thus revised to design and use of intelligent methods to make systems more ef- cient at solving problems. The term “Applied Intelligence” was thus created to represent its practicality. It emphasizes applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation, robotics, business, finance, medicine, bio-medicine, bio-informatics, cyberspace, and man-machine interactions. To endow the intelligent behavior of a system, many useful and interesting techniques have been developed. Some of them are even borrowed from the na- ral observation and biological phenomenon. Neural networks and evolutionary computation are two examples of them. Besides, some other heuristic approaches like data mining, adaptive control, intelligent manufacturing, autonomous agents, bio-informatics, reasoning, computer vision, decision support systems, expert s- tems, fuzzy logic, robots, intelligent interfaces, internet technology, planning and scheduling, are also commonly used in applied intelligence.

Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing PDF Author: Roger Lee
Publisher: Springer Science & Business Media
ISBN: 3642012027
Category : Mathematics
Languages : en
Pages : 289

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Book Description
The purpose of the 10th ACIS International Conference on Software Engineering Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD rd 2009), held in Daegu, Korea on May 27–29, 2009, the 3 International Workshop st on e-Activity (IWEA 2009) and the 1 International Workshop on Enterprise Architecture Challenges and Responses (WEACR 2009) is to aim at bringing together researchers and scientist, businessmen and entrepreneurs, teachers and students to discuss the numerous fields of computer science, and to share ideas and information in a meaningful way. Our conference officers selected the best 24 papers from those papers accepted for presentation at the conference in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rounds of rigorous review. In chapter 1, Igor Crk and Chris Gniady propose a network-aware energy m- agement mechanism that provides a low-cost solution that can significantly reduce energy consumption in the entire system while maintaining responsiveness of local interactive workloads. Their dynamic mechanisms reduce the decision delay before the disk is spun-up, reduce the number of erroneous spin-ups in local wo- stations, decrease the network bandwidth, and reduce the energy consumption of individual drives. In chapter 2, Yoshihito Saito and Tokuro Matsuo describe a task allocation mechanism and its performance concerning with software developing. They run simulations and discuss the results in terms of effective strategies of task allocation.

Evolutionary Image Analysis and Signal Processing

Evolutionary Image Analysis and Signal Processing PDF Author: Stefano Cagnoni
Publisher: Springer
ISBN: 3642016367
Category : Technology & Engineering
Languages : en
Pages : 213

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Book Description
The publication of this book on evolutionaryImage Analysis and Signal P- cessing (IASP) has two main goals. The ?rst, occasional one is to celebrate the 10th edition of EvoIASP, the workshop which has been the only event speci?cally dedicated to this topic since 1999. The second, more important one is to give an overview of the opportunities o?ered by Evolutionary C- putation (EC) techniques to computer vision,pattern recognition,and image and signal processing. It is not possible to celebrate EvoIASP properly without ?rst ackno- edging EvoNET, the EU-funded network of excellence, which has made it possible for Europe to build a strong European research community on EC. Thanks to the success of the ?rst, pioneering event organized by EvoNET, held in 1998 in Paris, it was possible to realize that not only was EC a f- tile ground for basic research but also there were several application ?elds to which EC techniques could o?er a valuable contribution. That was how the ideaofcreatingasingleevent,EvoWorkshops,outofacollectionofworkshops dedicated to applications of EC, was born. Amongst the possible application ?elds for EC, IASP was selected almost accidentally, due to the occasional presence, within EvoNET, of less than a handful of researchers who were interested in it. I would lie if I stated that the event was a great success since its very start, but it was successful enough to survive healthily for a couple of years, before reaching its present size, relevance, and popularity.

Transfer in Reinforcement Learning Domains

Transfer in Reinforcement Learning Domains PDF Author: Matthew Taylor
Publisher: Springer Science & Business Media
ISBN: 3642018815
Category : Computers
Languages : en
Pages : 237

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Book Description
In reinforcement learning (RL) problems, learning agents sequentially execute actions with the goal of maximizing a reward signal. The RL framework has gained popularity with the development of algorithms capable of mastering increasingly complex problems, but learning difficult tasks is often slow or infeasible when RL agents begin with no prior knowledge. The key insight behind "transfer learning" is that generalization may occur not only within tasks, but also across tasks. While transfer has been studied in the psychological literature for many years, the RL community has only recently begun to investigate the benefits of transferring knowledge. This book provides an introduction to the RL transfer problem and discusses methods which demonstrate the promise of this exciting area of research. The key contributions of this book are: Definition of the transfer problem in RL domains Background on RL, sufficient to allow a wide audience to understand discussed transfer concepts Taxonomy for transfer methods in RL Survey of existing approaches In-depth presentation of selected transfer methods Discussion of key open questions By way of the research presented in this book, the author has established himself as the pre-eminent worldwide expert on transfer learning in sequential decision making tasks. A particular strength of the research is its very thorough and methodical empirical evaluation, which Matthew presents, motivates, and analyzes clearly in prose throughout the book. Whether this is your initial introduction to the concept of transfer learning, or whether you are a practitioner in the field looking for nuanced details, I trust that you will find this book to be an enjoyable and enlightening read. Peter Stone, Associate Professor of Computer Science

Challenges and Opportunities of Connected k-Covered Wireless Sensor Networks

Challenges and Opportunities of Connected k-Covered Wireless Sensor Networks PDF Author: Habib M. Ammari
Publisher: Springer
ISBN: 3642018785
Category : Technology & Engineering
Languages : en
Pages : 360

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Book Description
“The decomposition of the difficulties to be resolved, or the objects to be known, should be pushed up to the simplest elements ... Such elements are seized directly and completely by the intuition. ” René Descartes, Discours de la méthode (1637) Wireless sensor networks have received significant attention because of their - portant role and many conveniences in our lives. Indeed, the recent and fast - vances in inexpensive sensor technology and wireless communications have made the design and development of large-scale wireless sensor networks cost-effective and appealing to a wide range of mission-critical situations, including civilian, natural, industrial, and military applications, such as health and environmental monitoring, seism monitoring, industrial process automation, and battlefields s- veillance, respectively. A wireless sensor network consists of a large number of - ny, low-powered devices, called sensors, which are randomly or deterministically deployed in a field of interest while collaborating and coordinating for the successful accomplishment of their mission. These sensors suffer from very scarce resources and capabilities, such as bandwidth, storage, CPU, battery power (or - ergy), sensing, and communication, to name a few, with energy being the most critical one. The major challenge in the design process of this type of network is mainly due to the limited capabilities of the sensors, and particularly, their energy, which makes them unreliable.