Other types of hardware

Xem 1-20 trên 67 kết quả Other types of hardware
  • Even since computers were invented many decades ago, many researchers have been trying to understand how human beings learn and many interesting paradigms and approaches towards emulating human learning abilities have been proposed. The ability of learning is one of the central features of human intelligence, which makes it an important ingredient in both traditional Artificial Intelligence (AI) and emerging Cognitive Science.

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  • Swarm Intelligence is a research field that studies the emergent collective intelligence of self-organized and decentralized simple agents. It is based on the social behavior that can be observed in nature, such as in flocks of birds, fish schools and bee hives, where a group of individuals with limited capabilities are able to emerge with intelligent solutions for complex problems.

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  • Very often the process of globalization is referred the word economy evolution. Often we measure and study globalization in the economic relevance. The economy is possibly the most recognized dimension of globalization. That is why we see many new phenomena and processes on economic macro levels and economic sectoral horizons as well as on specific “geography of globalization”. The book The Economic Geography of Globalization consists of 13 chapters divided into two sections: Globalization and Macro Process and Globalization and Sectoral Process. ...

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  • Although many other models of concurrent and distributed systems have been developed since the introduction in 1964 Petri nets are still an essential model for concurrent systems with respect to both the theory and the applications. The main attraction of Petri nets is the way in which the basic aspects of concurrent systems are captured both conceptually and mathematically. The intuitively appealing graphical notation makes Petri nets the model of choice in many applications.

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  • In a highly interactive Internet environment, the research issues in knowledge management vary based on the development of new technology and modes of interaction in the knowledge community. Due to the development of mobile and Web 2.0 technology, knowledge transfer, storage and retrieval have become much more rapid. The technologies and methods continue to get more and more diverse. At the same time, the types of online communities with high levels of interaction become more and more multi-dimensional.

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  • Notwithstanding the tremendous effort to solve the face recognition problem, it is not possible yet to design a face recognition system with a potential close to human performance. New computer vision and pattern recognition approaches need to be investigated. Even new knowledge and perspectives from different fields like, psychology and neuroscience must be incorporated into the current field of face recognition to design a robust face recognition system.

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  • Over the past decade, there has been a strong revival of interest in agent-based technology, with a recognition that it impacts many areas such as artificial intelligence, distributed computing, and software engineering. Agent-based technology can be used to solve a variety of business and technology problems. Examples of such applications include electronic commerce, grid computing, social networks, and adaptive virtual environment.

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  • The Internet is now a household term in many countries. With otherwise serious people beginning to joyride along the Information Superhighway, computer networking seems to be moving toward the status of TV sets and microwave ovens. The Internet has unusually high media coverage, and social science majors are descending on Usenet newsgroups, online virtual reality environments, and the Web to conduct research on the new "Internet Culture."

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  • Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: a knowledge base, a computerized model, and a user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions.

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  • In recent years many successful machine learning applications have been developed, ranging from data mining programs that learn to detect fraudulent credit card transactions, to information filtering systems that learn user’s reading preferences, to autonomous vehicles that learn to drive on public highways. At the same time, machine learning techniques such as rule induction, neural networks, genetic learning, case-based reasoning, and analytic learning have been widely applied to real-world problems.

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  • Artificial Intelligence (AI) is often referred to as a branch of science which deals with helping machines find solutions to complex problems in a more human-like fashion. It is generally associated with Computer Science, but it has many important links with other fields such as Maths, Psychology, Cognition, Biology and Philosophy. The AI success is due to its technology has diffused into everyday life. Neural networks, fuzzy controls, decision trees and rule-based systems are already in our mobile phones, washing machines and business applications....

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  • Face plays an important role in human communication. Facial expressions and gestures incorporate nonverbal information which contributes to human communication. By recognizing the facial expressions from facial images, a number of applications in the field of human computer interaction can be facilitated. Last two decades, the developments, as well as the prospects in the field of multimedia signal processing have attracted the attention of many computer vision researchers to concentrate in the problems of the facial expression recognition....

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  • This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. Concerning evolutionbased optimization methods, this book presents diverse versions of genetic algorithms, genetic programming, and performance studies and analyses, as well as several particle swarm optimizers and hybrid approaches using neural networks and artificial immunological systems for multi-objective optimization....

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  • The research of neural networks has experienced several ups and downs in the 20th century. The last resurgence is believed to be initiated by several seminal works of Hopfield and Tank in the 1980s, and this upsurge has persisted for three decades. The Hopfield neural networks, either discrete type or continuous type, are actually recurrent neural networks (RNNs). The hallmark of an RNN, in contrast to feedforward neural networks, is the existence of connections from posterior layer(s) to anterior layer(s) or connections among neurons in the same layer....

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  • Evolutionary computation has been widely used in computer science for decades. Even though it started as far back as the 1960s with simulated evolution, the subject is still evolving. During this time, new metaheuristic optimization approaches, like evolutionary algorithms, genetic algorithms, swarm intelligence, etc., were being developed and new fields of usage in artificial intelligence, machine learning, combinatorial and numerical optimization, etc., were being explored.

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  • This book has a unique title” Advances in Computer Science and IT”, although it is not entirely new there is a trend of similar titles in many international conferences. However, for a book this title certainly has innovation and many articles presented in the text shows there uniqueness likewise the title.

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  • Entitites or computer programs that learn from their environment and can act based on what they have learned can be defined as intelligent agents. These agents can be as simple as triggering an alarm in case of a fire or as complex as human beings. Intelligent agents and their applications to solve real-world problems are getting smarter and diversified day by day.

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  • This book is consisting of 24 chapters which are focusing on the basic and applied research regarding e‐learning systems. Authors made efforts to provide theoretical as well as practical approaches to solve open problems through their elite research work.

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  • A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains.

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  • Cognitive maps have emerged as an important tool in modeling and decision making. In a nutshell they are signed di-graphs that capture the cause/effect relationships that subject matter experts believe exist in a problem space under consideration. Each node in the map represents some variable concept.

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