925 resultados para 700103 Information processing services


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Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unseen data. Alternative algorithms have been developed such as the Prism algorithm. Prism constructs modular rules which produce qualitatively better rules than rules induced by TDIDT. However, along with the increasing size of databases, many existing rule learning algorithms have proved to be computational expensive on large datasets. To tackle the problem of scalability, parallel classification rule induction algorithms have been introduced. As TDIDT is the most popular classifier, even though there are strongly competitive alternative algorithms, most parallel approaches to inducing classification rules are based on TDIDT. In this paper we describe work on a distributed classifier that induces classification rules in a parallel manner based on Prism.

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The ability to create accurate geometric models of neuronal morphology is important for understanding the role of shape in information processing. Despite a significant amount of research on automating neuron reconstructions from image stacks obtained via microscopy, in practice most data are still collected manually. This paper describes Neuromantic, an open source system for three dimensional digital tracing of neurites. Neuromantic reconstructions are comparable in quality to those of existing commercial and freeware systems while balancing speed and accuracy of manual reconstruction. The combination of semi-automatic tracing, intuitive editing, and ability of visualizing large image stacks on standard computing platforms provides a versatile tool that can help address the reconstructions availability bottleneck. Practical considerations for reducing the computational time and space requirements of the extended algorithm are also discussed.

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Climate data are used in a number of applications including climate risk management and adaptation to climate change. However, the availability of climate data, particularly throughout rural Africa, is very limited. Available weather stations are unevenly distributed and mainly located along main roads in cities and towns. This imposes severe limitations to the availability of climate information and services for the rural community where, arguably, these services are needed most. Weather station data also suffer from gaps in the time series. Satellite proxies, particularly satellite rainfall estimate, have been used as alternatives because of their availability even over remote parts of the world. However, satellite rainfall estimates also suffer from a number of critical shortcomings that include heterogeneous time series, short time period of observation, and poor accuracy particularly at higher temporal and spatial resolutions. An attempt is made here to alleviate these problems by combining station measurements with the complete spatial coverage of satellite rainfall estimates. Rain gauge observations are merged with a locally calibrated version of the TAMSAT satellite rainfall estimates to produce over 30-years (1983-todate) of rainfall estimates over Ethiopia at a spatial resolution of 10 km and a ten-daily time scale. This involves quality control of rain gauge data, generating locally calibrated version of the TAMSAT rainfall estimates, and combining these with rain gauge observations from national station network. The infrared-only satellite rainfall estimates produced using a relatively simple TAMSAT algorithm performed as good as or even better than other satellite rainfall products that use passive microwave inputs and more sophisticated algorithms. There is no substantial difference between the gridded-gauge and combined gauge-satellite products over the test area in Ethiopia having a dense station network; however, the combined product exhibits better quality over parts of the country where stations are sparsely distributed.

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The arousal-biased competition model predicts that arousal increases the gain on neural competition between stimuli representations. Thus, the model predicts that arousal simultaneously enhances processing of salient stimuli and impairs processing of relatively less-salient stimuli. We tested this model with a simple dot-probe task. On each trial, participants were simultaneously exposed to one face image as a salient cue stimulus and one place image as a non-salient stimulus. A border around the face cue location further increased its bottom-up saliency. Before these visual stimuli were shown, one of two tones played: one that predicted a shock (increasing arousal) or one that did not. An arousal-by-saliency interaction in category-specific brain regions (fusiform face area for salient faces and parahippocampal place area for non-salient places) indicated that brain activation associated with processing the salient stimulus was enhanced under arousal whereas activation associated with processing the non-salient stimulus was suppressed under arousal. This is the first functional magnetic resonance imaging study to demonstrate that arousal can enhance information processing for prioritized stimuli while simultaneously impairing processing of non-prioritized stimuli. Thus, it goes beyond previous research to show that arousal does not uniformly enhance perceptual processing, but instead does so selectively in ways that optimizes attention to highly salient stimuli.

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John Searle’s Chinese Room Argument (CRA) purports to demonstrate that syntax is not sufficient for semantics, and, hence, because computation cannot yield understanding, the computational theory of mind, which equates the mind to an information processing system based on formal computations, fails. In this paper, we use the CRA, and the debate that emerged from it, to develop a philosophical critique of recent advances in robotics and neuroscience. We describe results from a body of work that contributes to blurring the divide between biological and artificial systems; so-called animats, autonomous robots that are controlled by biological neural tissue and what may be described as remote-controlled rodents, living animals endowed with augmented abilities provided by external controllers. We argue that, even though at first sight, these chimeric systems may seem to escape the CRA, on closer analysis, they do not. We conclude by discussing the role of the body–brain dynamics in the processes that give rise to genuine understanding of the world, in line with recent proposals from enactive cognitive science.

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This paper focuses on outsourcing vendors, their characteristics and the vendor selection process. It draws on current research and two research studies, one specifi- cally examining outsourcing vendors and the other examining vendor-client issues. We first outline the development of the market for the outsourcing of information technology/information systems services and activities, then detail the characteristics of different types of vendor companies and their competitive positions, before providing a client perspective to the issue of vendor selection.

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Key Performance Indicators (KPIs) are the main instruments of Business Performance Management. KPIs are the measures that are translated to both the strategy and the business process. These measures are often designed for an industry sector with the assumptions about business processes in organizations. However, the assumptions can be too incomplete to guarantee the required properties of KPIs. This raises the need to validate the properties of KPIs prior to their application to performance measurement. This paper applies the method called EXecutable Requirements Engineering Management and Evolution (EXTREME) for validation of the KPI definitions. EXTREME semantically relates the goal modeling, conceptual modeling and protocol modeling techniques into one methodology. The synchronous composition built into protocol modeling enables raceability of goals in protocol models and constructive definitions of a KPI. The application of the method clarifies the meaning of KPI properties and procedures of their assessment and validation.

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Background: The oral health conditions of indigenous peoples in Amazonia are closely associated with ecological and dietary changes related to interaction with non-Indians. Aim: The study investigated the incidence of caries in an indigenous community from Central Brazil focusing on gender differences. Subjects and methods: The research was conducted among the Xavante Indians and was based on longitudinal data collected in two surveys (1999 and 2004). The study included 128 individuals, 63 (49.2%) males and 65 (50.8%) females, divided in four age brackets (6-12, 13-19, 20-34, 35-60 years of age). The DMFT (decayed, missing and filled teeth) index and incidences (difference between 1999 and 2004) were calculated for each individual. The proportion of incidence was also calculated. Differences in caries risk between gender and age brackets were compared by parametric and non-parametric tests. Results: There were statistically significant differences in relation to caries incidence between age brackets and gender. The greatest incidence was observed in the 20-34 age bracket, which presented 3.30 new decayed teeth, twice the risk of the 6-12 age bracket (p0.01), chosen as reference. While females in most age groups did not show higher risk for caries when compared to males, there was a 4.04-fold risk in the 20-34 age bracket (p0.01). Conclusion: It is concluded that factors related to the social functions of each sex (gender issues) and differential access to information, health services, and education may help to understand the differences observed in the incidence of caries.

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This study investigated the orienting of visual attention in rats using a 3-hole nose-poke task analogous to Posner, Information processing in cognition: the Loyola Symposium, Erlbaum, Hillsdale, (1980) covert attention task for humans. The effects of non-predictive (50% valid and 50% invalid) and predictive (80% valid and 20% invalid) peripheral visual cues on reaction times and response accuracy to a target stimulus, using Stimuli-Onset Asynchronies (SOAs) varying between 200 and 1,200 ms, were investigated. The results showed shorter reaction times in valid trials relative to invalid trials for both subjects trained in the non-predictive and predictive conditions, particularly when the SOAs were 200 and 400 ms. However, the magnitude of this validity effect was significantly greater for subjects exposed to predictive cues, when the SOA was 800 ms. Subjects exposed to invalid predictive cues exhibited an increase in omission errors relative to subjects exposed to invalid non-predictive cues. In contrast, valid cues reduced the proportion of omission errors for subjects trained in the predictive condition relative to subjects trained in the non-predictive condition. These results are congruent with those usually reported for humans and indicate that, in addition to the exogenous capture of attention promoted by both predictive and non-predictive peripheral cues, rats exposed to predictive cues engaged an additional slower process equivalent to human`s endogenous orienting of attention. To our knowledge, this is the first demonstration of an endogenous-like process of covert orienting of visual attention in rats.

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The ventral tegmental area (VTA) is a nodal link in reward circuitry. Based on its striatal output, it has been subdivided in a caudomedial part which targets the ventromedial striatum, and a lateral part which targets the ventrolateral striatum [Ikemoto S (2007) Dopamine reward circuitry: two projection systems from the ventral midbrain to the nucleus accumbens-olfactory tubercle complex. Brain Res Rev 56:27-78]. Whether these two VTA parts are interconnected and to what extent the VTA innervates the substantia nigra compacta (SNc) and retrorubral nucleus (RR) are critical issues for understanding information processing in the basal ganglia. Here, VTA projections to the VTA-nigral complex were examined in rats, using Phaseolus vulgaris leucoagglutinin (PHA-L) as anterograde tracer. The results show that the dorsolateral VTA projects to itself, as well as to the dorsal tier of the SNc and RR, largely avoiding the caudomedial VTA. The ventrolateral VTA innervates mainly the interfascicular nucleus. The components of the caudomedial VTA (the interfascicular, paranigral and caudal linear nuclei) are connected with each other. In addition, the caudomedial VTA (especially the paranigral and caudal linear nuclei) innervates the lateral VTA, and, to a lesser degree, the SNc and RR. The caudal pole of the VTA sends robust, bilateral projections to virtually all the VTA-nigral complex, which terminate in the dorsal and ventral tiers. Modest inputs from the medial supramammillary nucleus to ventromedial parts of the VTA-nigral complex were also identified. In double-immunostained sections, PHA-L-labeled varicosities were sometimes found apposed to tyrosine hydroxylase-positive neurons in the ventral mesencephalon. Overall, the results underscore that VTA projections to the VTA-nigral complex are substantial and topically organized. In general, these projections, like the spiralated striato-nigro-striatal loops, display a medial-to-lateral organization. This anatomical arrangement conceivably permits the ventromedial striatum to influence the activity of the lateral striatum. The caudal pole of the VTA appears to be a critical site for a global recruitment of the mesotelencephalic system. (C) 2008 IBRO. Published by Elsevier Ltd. All rights reserved.

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Entanglement is an essential quantum resource for the acceleration of information processing as well as for sophisticated quantum communication protocols. Quantum information networks are expected to convey information from one place to another by using entangled light beams. We demonstrated the generation of entanglement among three bright beams of light, all of different wavelengths (532.251, 1062.102, and 1066.915 nanometers). We also observed disentanglement for finite channel losses, the continuous variable counterpart to entanglement sudden death.

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This article reports a relaxation study in an oriented system containing spin 3/2 nuclei using quantum state tomography (QST). The use of QST allowed evaluating the time evolution of all density matrix elements starting from several initial states. Using an appropriated treatment based on the Redfield theory, the relaxation rate of each density matrix element was measured and the reduced spectral densities that describe the system relaxation were determined. All the experimental data could be well described assuming pure quadrupolar relaxation and reduced spectral densities corresponding to a superposition of slow and fast motions. The data were also analyzed in the context of Quantum Information Processing, where the coherence loss of each qubit of the system was determined using the partial trace operation. (C) 2008 Elsevier Inc. All rights reserved.

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This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described.

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In this paper, a novel statistical test is introduced to compare two locally stationary time series. The proposed approach is a Wald test considering time-varying autoregressive modeling and function projections in adequate spaces. The covariance structure of the innovations may be also time- varying. In order to obtain function estimators for the time- varying autoregressive parameters, we consider function expansions in splines and wavelet bases. Simulation studies provide evidence that the proposed test has a good performance. We also assess its usefulness when applied to a financial time series.

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Sign language animations can lead to better accessibility of information and services for people who are deaf and have low literacy skills in spoken/written languages. Due to the distinct word-order, syntax, and lexicon of the sign language from the spoken/written language, many deaf people find it difficult to comprehend the text on a computer screen or captions on a television. Animated characters performing sign language in a comprehensible way could make this information accessible. Facial expressions and other non-manual components play an important role in the naturalness and understandability of these animations. Their coordination to the manual signs is crucial for the interpretation of the signed message. Software to advance the support of facial expressions in generation of sign language animation could make this technology more acceptable for deaf people. In this survey, we discuss the challenges in facial expression synthesis and we compare and critique the state of the art projects on generating facial expressions in sign language animations. Beginning with an overview of facial expressions linguistics, sign language animation technologies, and some background on animating facial expressions, a discussion of the search strategy and criteria used to select the five projects that are the primary focus of this survey follows. This survey continues on to introduce the work from the five projects under consideration. Their contributions are compared in terms of support for specific sign language, categories of facial expressions investigated, focus range in the animation generation, use of annotated corpora, input data or hypothesis for their approach, and other factors. Strengths and drawbacks of individual projects are identified in the perspectives above. This survey concludes with our current research focus in this area and future prospects.