945 resultados para International Pragmatics Conference


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To investigate the threshold level of defocus that induces a measurable objective change in accommodation response to a target at an intermediate distance.

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Multi-agent systems implicate a high degree of concurrency at both the Inter- and Intra-Agent levels. Scalable, fault tolerant, Agent Grooming Environment (SAGE), the second generation, FIPA compliant MAS requires a built in mechanism to achieve both the Inter- and Intra-Agent concurrency. This paper dilates upon an attempt to provide a reliable, efficient and light-weight solution to provide intra-agent concurrency with-in the internal agent architecture of SAGE. It addresses the issues related to using the JAVA threading model to provide this level of concurrency to the agent and provides an alternative approach that is based on an eventdriven, concurrent and user-scalable multi-tasking model for the agent's internal model. The findings of this paper show that our proposed approach is suitable for providing an efficient and lightweight concurrent task model for SA GE and considerably outweighs the performance of multithreaded tasking model based on JAVA in terms of throughput and efficiency. This has been illustrated using the practical implementation and evaluation of both models. © 2004 IEEE.

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Many conventional statistical machine learning al- gorithms generalise poorly if distribution bias ex- ists in the datasets. For example, distribution bias arises in the context of domain generalisation, where knowledge acquired from multiple source domains need to be used in a previously unseen target domains. We propose Elliptical Summary Randomisation (ESRand), an efficient domain generalisation approach that comprises of a randomised kernel and elliptical data summarisation. ESRand learns a domain interdependent projection to a la- tent subspace that minimises the existing biases to the data while maintaining the functional relationship between domains. In the latent subspace, ellipsoidal summaries replace the samples to enhance the generalisation by further removing bias and noise in the data. Moreover, the summarisation enables large-scale data processing by significantly reducing the size of the data. Through comprehensive analysis, we show that our subspace-based approach outperforms state-of-the-art results on several activity recognition benchmark datasets, while keeping the computational complexity significantly low.

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Multi-agent systems (MAS) advocate an agent-based approach to software engineering based on decomposing problems in terms of decentralized, autonomous agents that can engage in flexible, high-level interactions. This chapter introduces scalable fault tolerant agent grooming environment (SAGE), a second-generation Foundation for Intelligent Physical Agents (FIPA)-compliant multi-agent system developed at NIIT-Comtec, which provides an environment for creating distributed, intelligent, and autonomous entities that are encapsulated as agents. The chapter focuses on the highlight of SAGE, which is its decentralized fault-tolerant architecture that can be used to develop applications in a number of areas such as e-health, e-government, and e-science. In addition, SAGE architecture provides tools for runtime agent management, directory facilitation, monitoring, and editing messages exchange between agents. SAGE also provides a built-in mechanism to program agent behavior and their capabilities with the help of its autonomous agent architecture, which is the other major highlight of this chapter. The authors believe that the market for agent-based applications is growing rapidly, and SAGE can play a crucial role for future intelligent applications development. © 2007, IGI Global.

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In this paper we propose a novel family of kernels for multivariate time-series classification problems. Each time-series is approximated by a linear combination of piecewise polynomial functions in a Reproducing Kernel Hilbert Space by a novel kernel interpolation technique. Using the associated kernel function a large margin classification formulation is proposed which can discriminate between two classes. The formulation leads to kernels, between two multivariate time-series, which can be efficiently computed. The kernels have been successfully applied to writer independent handwritten character recognition.

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The local Fe ferromagnetic (FM) moment at the grain boundaries of a ceramic sample of Ca2FeReO6 double perovskite was investigated by means of x-ray magnetic circular dichroism spectroscopy at the Fe L-2,L-3 edges and compared to the overall bulk magnetization. We found that, at the grain boundaries, the Fe FM moments at H=5 T are much smaller than expected and that the MxH curve is harder than in the bulk magnetization. These results suggest a larger degree of Fe/Re antisite disorder at the grain boundaries of this sample, shedding light into the intriguing nonmetallic resistivity behavior despite the reported presence of free carriers. (c) 2007 American Institute of Physics.

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Laser mediated stimulation of biological process was amongst its very first effects documented by Mester et al. but the ambiguous and tissue-cell context specific biological effects of laser radiation is now termed ‘Photobiomodulation’. We found many parallels between the reported biological effects of lasers and a multiface-ted growth factor, Transforming Growth Factor-β (TGF-β). This review outlines the interestingparallelsbetween the twofieldsand our rationalefor pursuingtheir potential causal correlation. We explored this correlation using an in vitro assay systems and a human clinical trial on healing wound extraction sockets that we reported in a recent publication. In conclusion we report that low power laser irradiation can activate latent TGF-β1 and β3 complexes and suggest that this might be one of the major modes of the photobiomodulatory effects of low power lasers.

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Scanning tunneling microscopy/spectroscopy studies were carried out on single crystals of colossal magnetoresistive manganite Pr0.68Pb0.32MnO3 at different temperatures in order to probe their spatial homogeneity across the metal-insulator transition temperature TM-I(similar to 255 K). A metallic behavior of the local conductance was observed for temperatures T < TM-I. Zero bias conductance (dI/dV)v=(0), which is directly proportional to the local surface density of states at the Fermi level, shows a single distribution at temperatures T < 200 K suggesting a homogeneous electronic phase at low temperatures. In a narrow temperature window of 200 K < T < TM-I, however, an inhomogeneous distribution of (dI/dV)v=(0) has been observed. This result gives evidence for phase separation in the transition region in this compound.

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Scanning tunneling microscopy/spectroscopy studies were carried out on single crystals of colossal magnetoresistive manganite Pr0.68Pb0.32MnO3 at different temperatures in order to probe their spatial homogeneity across the metal-insulator transition temperature TM-I(similar to 255 K). A metallic behavior of the local conductance was observed for temperatures T < TM-I. Zero bias conductance (dI/dV)v=(0), which is directly proportional to the local surface density of states at the Fermi level, shows a single distribution at temperatures T < 200 K suggesting a homogeneous electronic phase at low temperatures. In a narrow temperature window of 200 K < T < TM-I, however, an inhomogeneous distribution of (dI/dV)v=(0) has been observed. This result gives evidence for phase separation in the transition region in this compound.

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Scanning tunneling microscopy/spectroscopy studies were carried out on single crystals of colossal magnetoresistive manganite Pr0. 68Pb0.32MnO3 at different temperatures in order to probe their spatial homogeneity across the metal-insulator transition temperature TM-I(similar to 255 K). A metallic behavior of the local conductance was observed for temperatures T < TM-I. Zero bias conductance (dI/dV)v=(0), which is directly proportional to the local surface density of states at the Fermi level, shows a single distribution at temperatures T < 200 K suggesting a homogeneous electronic phase at low temperatures. In a narrow temperature window of 200 K < T < TM-I, however, an inhomogeneous distribution of (dI/dV)v=(0) has been observed. This result gives evidence for phase separation in the transition region in this compound.

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A large part of today's multi-core chips is interconnect. Increasing communication complexity has made essential new strategies for interconnects, such as Network on Chip. Power dissipation in interconnects has become a substantial part of the total power dissipation. Techniques to reduce interconnect power have thus become a necessity. In this paper, we present a design methodology that gives values of bus width for interconnect links, frequency of operation for routers, in Network on Chip scenario that satisfy required throughput and dissipate minimal switching power. We develop closed form analytical expressions for the power dissipation, with bus width and frequency as variables and then use Lagrange multiplier method to arrive at the optimal values. We present a 4 port router in 90 nm technology library as case study. The results obtained from analysis are discussed.

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RECONNECT is a Network-on-Chip using a honeycomb topology. In this paper we focus on properties of general rules applicable to a variety of routing algorithms for the NoC which take into account the missing links of the honeycomb topology when compared to a mesh. We also extend the original proposal [5] and show a method to insert and extract data to and from the network. Access Routers at the boundary of the execution fabric establish connections to multiple periphery modules and create a torus to decrease the node distances. Our approach is scalable and ensures homogeneity among the compute elements in the NoC. We synthesized and evaluated the proposed enhancement in terms of power dissipation and area. Our results indicate that the impact of necessary alterations to the fabric is negligible and effects the data transfer between the fabric and the periphery only marginally.

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This paper proposes a Single Network Adaptive Critic (SNAC) based Power System Stabilizer (PSS) for enhancing the small-signal stability of power systems over a wide range of operating conditions. SNAC uses only a single critic neural network instead of the action-critic dual network architecture of typical adaptive critic designs. SNAC eliminates the iterative training loops between the action and critic networks and greatly simplifies the training procedure. The performance of the proposed PSS has been tested on a Single Machine Infinite Bus test system for various system and loading conditions. The proposed stabilizer, which is relatively easier to synthesize, consistently outperformed stabilizers based on conventional lead-lag and linear quadratic regulator designs.

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We propose a compact model which predicts the channel charge density and the drain current which match quite closely with the numerical solution obtained from the Full-Band structure approach. We show that, with this compact model, the channel charge density can be predicted by taking the capacitance based on the physical oxide thickness, as opposed to C-eff, which needs to be taken when using the classical solution.

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One of the major tasks in swarm intelligence is to design decentralized but homogenoeus strategies to enable controlling the behaviour of swarms of agents. It has been shown in the literature that the point of convergence and motion of a swarm of autonomous mobile agents can be controlled by using cyclic pursuit laws. In cyclic pursuit, there exists a predefined cyclic connection between agents and each agent pursues the next agent in the cycle. In this paper we generalize this idea to a case where an agent pursues a point which is the weighted average of the positions of the remaining agents. This point correspond to a particular pursuit sequence. Using this concept of centroidal cyclic pursuit, the behavior of the agents is analyzed such that, by suitably selecting the agents' gain, the rendezvous point of the agents can be controlled, directed linear motion of the agents can be achieved, and the trajectories of the agents can be changed by switching between the pursuit sequences keeping some of the behaviors of the agents invariant. Simulation experiments are given to support the analytical proofs.