Games have fascinated people in activities related to entertainment, education, health care, etc. The augmented reality technology, using computational support, brings the game from the computer to the user space, mak...
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Games have fascinated people in activities related to entertainment, education, health care, etc. The augmented reality technology, using computational support, brings the game from the computer to the user space, making the interaction friendlier. This paper introduces augmented reality and makes considerations on the ARToolKit software, pointing out its interactive processes. The use of augmented reality in the development of games is illustrated by five case studies of games implemented with ARToolKit. The main characteristics of each game and the exploration of the augmented reality resources are discussed.
This paper describes the development of a Multi-Electrode Array (MEA) with Guided Network for Cell-to-Cell Communication Transduction using a standard integrated circuit (IC) fabrication process. Unlike conventional e...
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OBF (Orthonormal Basis Function) Fuzzy models have shown to be a promising approach to the areas of nonlinear system identification and control since they exhibit several advantages over those dynamic model topologies...
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ISBN:
(纸本)9780769531960
OBF (Orthonormal Basis Function) Fuzzy models have shown to be a promising approach to the areas of nonlinear system identification and control since they exhibit several advantages over those dynamic model topologies usually adopted in the literature. Although encouraging application results have been obtained, no automatic procedure had yet been developed to optimize the design parameters of these models. This paper elaborates on the use of a genetic algorithm (GA) especially designed for this task, in which a fitness function based on the Akaike information criterion plays a key role by considering both model accuracy and parsimony aspects. The use of linear (actually affine) and nonlinear local models is also investigated. The proposed methodology is evaluated in the modeling of a real nonlinear magnetic levitation system.
In this paper we address the issue of detecting defects in wood using features extracted from grayscale images. The feature set proposed here is based on the concept of texture and it is computed from the co-occurrenc...
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In this paper we address the issue of detecting defects in wood using features extracted from grayscale images. The feature set proposed here is based on the concept of texture and it is computed from the co-occurrence matrices. The features provide measures of properties such as smoothness, coarseness, and regularity. Comparative experiments using a color image based feature set extracted from percentile histograms are carried to demonstrate the efficiency of the proposed feature set. Two different learning paradigms, neural networks and support vector machines, and a feature selection algorithm based on multi-objective genetic algorithms were considered in our experiments. The experimental results show that after feature selection, the grayscale image based feature set achieves very competitive performance for the problem of wood defect detection relative to the color image based features
In this paper we address the issue of detecting defects in wood using features extracted from grayscale images. The feature set proposed here is based on the concept of texture and it is computed from the co-occurrenc...
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Chemical reaction networks by which individual cells gather and process information about their chemical environments have been dubbed "signal transduction" networks. Despite this suggestive terminology, the...
Chemical reaction networks by which individual cells gather and process information about their chemical environments have been dubbed "signal transduction" networks. Despite this suggestive terminology, there have been few attempts to analyze chemical signaling systems with the quantitative tools of information theory. Gradient sensing in the social amoeba Dictyostelium discoideum is a well characterized signal transduction system in which a cell estimates the direction of a source of diffusing chemoattractant molecules based on the spatiotemporal sequence of ligand-receptor binding events at the cell membrane. Using Monte Carlo techniques (MCell) we construct a simulation in which a collection of individual ligand particles undergoing Brownian diffusion in a three-dimensional volume interact with receptors on the surface of a static amoeboid cell. Adapting a method for estimation of spike train entropies described by Victor (originally due to Kozachenko and Leonenko), we estimate lower bounds on the mutual information between the transmitted signal (direction of ligand source) and the received signal (spatiotemporal pattern of receptor binding/unbinding events). Hence we provide a quantitative framework for addressing the question: how much could the cell know, and when could it know it? We show that the time course of the mutual information between the cell's surface receptors and the (unknown) gradient direction is consistent with experimentally measured cellular response times. We find that the acquisition of directional information depends strongly on the time constant at which the intracellular response is filtered.
This paper presents the proposal and development of a reconfigurable crossbar switch (RCS) architecture for network processors. Its main purpose is to increase the performance, and flexibility for environments with mu...
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This paper presents the proposal and development of a reconfigurable crossbar switch (RCS) architecture for network processors. Its main purpose is to increase the performance, and flexibility for environments with multiprocessors and computer clusters. The results include VHDL simulation of RCS and the use of it in a broadcast function implementation, found in message passing support middleware
This paper analyzes the effect of custom error control schemes on the energy efficiency in Bluetooth sensor networks. The energy efficiency metric considers in just one parameter the energy and reliability constraints...
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This paper analyzes the effect of custom error control schemes on the energy efficiency in Bluetooth sensor networks. The energy efficiency metric considers in just one parameter the energy and reliability constraints of the wireless sensor networks. New packet types are introduced using some error control strategies in the AUX1 packet, such as Hamming and BCH codes, with and without CRC for error detection. Two adaptive techniques are proposed that change the error control strategy based on the number of hops traversed by a packet through the network. The performance results are obtained through simulations in a channel with Rayleigh fading for networks with different number of hops, showing that error control can improve the energy efficiency of a Bluetooth-based sensor network.
As data integration over the Web has become an increasing demand, there is a growing desire to use XML as a standard format for data exchange. For sharing their grammars efficiently, most of the XML documents in use a...
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This paper proposes a supervised version of a learning algorithm for a constructive neuro-immune network. The proposed methodology is developed by taking ideas from the immune system and learning vector quantization. ...
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This paper proposes a supervised version of a learning algorithm for a constructive neuro-immune network. The proposed methodology is developed by taking ideas from the immune system and learning vector quantization. The resulting classification algorithm is characterized by high-performance, similar to the ones produced by alternative methods in the literature, and parsimonious solutions, with a much smaller set of prototypes per class when compared with the other approaches. The number of prototypes is automatically defined by the convergence criterion. The algorithm requires a single user-defined parameter for training, associated with the convergence criterion, and the computational cost is sufficiently reduced to support applications involving large data sets.
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