100 resultados para Data Pre-processing


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We investigated the on-line processing of unaccusative and unergative sentences in a group of eight Greek-speaking individuals diagnosed with Broca aphasia and a group of language-unimpaired subjects used as the baseline. The processing of unaccusativity refers to the reactivation of the postverbal trace by retrieving the mnemonic representation of the verb’s syntactically defined antecedent provided in the early part of the sentence. Our results demonstrate that the Broca group showed selective reactivation of the antecedent for the unaccusatives. We consider several interpretations for our data, including explanations focusing on the transitivization properties of nonactive and active voice-alternating unaccusatives, the costly procedure claimed to underlie the parsing of active nonvoice-alternating unaccusatives, and the animacy of the antecedent modulating the syntactic choices of the patients.

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Global communicationrequirements andloadimbalanceof someparalleldataminingalgorithms arethe major obstacles to exploitthe computational power of large-scale systems. This work investigates how non-uniform data distributions can be exploited to remove the global communication requirement and to reduce the communication costin parallel data mining algorithms and, in particular, in the k-means algorithm for cluster analysis. In the straightforward parallel formulation of the k-means algorithm, data and computation loads are uniformly distributed over the processing nodes. This approach has excellent load balancing characteristics that may suggest it could scale up to large and extreme-scale parallel computing systems. However, at each iteration step the algorithm requires a global reduction operationwhichhinders thescalabilityoftheapproach.Thisworkstudiesadifferentparallelformulation of the algorithm where the requirement of global communication is removed, while maintaining the same deterministic nature ofthe centralised algorithm. The proposed approach exploits a non-uniform data distribution which can be either found in real-world distributed applications or can be induced by means ofmulti-dimensional binary searchtrees. The approachcanalso be extended to accommodate an approximation error which allows a further reduction ofthe communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing element

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This chapter introduces the latest practices and technologies in the interactive interpretation of environmental data. With environmental data becoming ever larger, more diverse and more complex, there is a need for a new generation of tools that provides new capabilities over and above those of the standard workhorses of science. These new tools aid the scientist in discovering interesting new features (and also problems) in large datasets by allowing the data to be explored interactively using simple, intuitive graphical tools. In this way, new discoveries are made that are commonly missed by automated batch data processing. This chapter discusses the characteristics of environmental science data, common current practice in data analysis and the supporting tools and infrastructure. New approaches are introduced and illustrated from the points of view of both the end user and the underlying technology. We conclude by speculating as to future developments in the field and what must be achieved to fulfil this vision.

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The nature and scale of pre-Columbian land use and the consequences of the 1492 “Columbian Encounter” (CE) on Amazonia are among the more debated topics in New World archaeology and paleoecology. However, pre-Columbian human impact in Amazonian savannas remains poorly understood. Most paleoecological studies have been conducted in neotropical forest contexts. Of studies done in Amazonian savannas, none has the temporal resolution needed to detect changes induced by either climate or humans before and after A.D. 1492, and only a few closely integrate paleoecological and archaeological data. We report a high-resolution 2,150-y paleoecological record from a French Guianan coastal savanna that forces reconsideration of how pre-Columbian savanna peoples practiced raised-field agriculture and how the CE impacted these societies and environments. Our combined pollen, phytolith, and charcoal analyses reveal unexpectedly low levels of biomass burning associated with pre-A.D. 1492 savanna raised-field agriculture and a sharp increase in fires following the arrival of Europeans. We show that pre-Columbian raised-field farmers limited burning to improve agricultural production, contrasting with extensive use of fire in pre-Columbian tropical forest and Central American savanna environments, as well as in present-day savannas. The charcoal record indicates that extensive fires in the seasonally flooded savannas of French Guiana are a post-Columbian phenomenon, postdating the collapse of indigenous populations. The discovery that pre-Columbian farmers practiced fire-free savanna management calls into question the widely held assumption that pre-Columbian Amazonian farmers pervasively used fire to manage and alter ecosystems and offers fresh perspectives on an emerging alternative approach to savanna land use and conservation that can help reduce carbon emissions.

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It is now established that native language affects one's perception of the world. However, it is unknown whether this effect is merely driven by conscious, language-based evaluation of the environment or whether it reflects fundamental differences in perceptual processing between individuals speaking different languages. Using brain potentials, we demonstrate that the existence in Greek of 2 color terms—ghalazio and ble—distinguishing light and dark blue leads to greater and faster perceptual discrimination of these colors in native speakers of Greek than in native speakers of English. The visual mismatch negativity, an index of automatic and preattentive change detection, was similar for blue and green deviant stimuli during a color oddball detection task in English participants, but it was significantly larger for blue than green deviant stimuli in native speakers of Greek. These findings establish an implicit effect of language-specific terminology on human color perception.

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An important constraint on how hemodynamic neuroimaging signals such as fMRI can be interpreted in terms of the underlying evoked activity is an understanding of neurovascular coupling mechanisms that actually generate hemodynamic responses. The predominant view at present is that the hemodynamic response is most correlated with synaptic input and subsequent neural processing rather than spiking output. It is still not clear whether input or processing is more important in the generation of hemodynamics responses. In order to investigate this we measured the hemodynamic and neural responses to electrical whisker pad stimuli in rat whisker barrel somatosensory cortex both before and after the local cortical injections of the GABAA agonist muscimol. Muscimol would not be expected to affect the thalamocortical input into the cortex but would inhibit subsequent intra-cortical processing. Pre-muscimol infusion whisker stimuli elicited the expected neural and accompanying hemodynamic responses to that reported previously. Following infusion of muscimol, although the temporal profile of neural responses to each pulse of the stimulus train was similar, the average response was reduced in magnitude by ∼79% compared to that elicited pre-infusion. The whisker-evoked hemodynamic responses were reduced by a commensurate magnitude suggesting that, although the neurovascular coupling relationships were similar for synaptic input as well as for cortical processing, the magnitude of the overall response is dominated by processing rather than from that produced from the thalamocortical input alone.

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n the past decade, the analysis of data has faced the challenge of dealing with very large and complex datasets and the real-time generation of data. Technologies to store and access these complex and large datasets are in place. However, robust and scalable analysis technologies are needed to extract meaningful information from these datasets. The research field of Information Visualization and Visual Data Analytics addresses this need. Information visualization and data mining are often used complementary to each other. Their common goal is the extraction of meaningful information from complex and possibly large data. However, though data mining focuses on the usage of silicon hardware, visualization techniques also aim to access the powerful image-processing capabilities of the human brain. This article highlights the research on data visualization and visual analytics techniques. Furthermore, we highlight existing visual analytics techniques, systems, and applications including a perspective on the field from the chemical process industry.

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The validity of the linguistic relativity principle continues to stimulate vigorous debate and research. The debate has recently shifted from the behavioural investigation arena to a more biologically grounded field, in which tangible physiological evidence for language effects on perception can be obtained. Using brain potentials in a colour oddball detection task with Greek and English speakers, a recent study suggests that language effects may exist at early stages of perceptual integration [Thierry, G., Athanasopoulos, P., Wiggett, A., Dering, B., & Kuipers, J. (2009). Unconscious effects of language-specific terminology on pre-attentive colour perception. Proceedings of the National Academy of Sciences, 106, 4567–4570]. In this paper, we test whether in Greek speakers exposure to a new cultural environment (UK) with contrasting colour terminology from their native language affects early perceptual processing as indexed by an electrophysiological correlate of visual detection of colour luminance. We also report semantic mapping of native colour terms and colour similarity judgements. Results reveal convergence of linguistic descriptions, cognitive processing, and early perception of colour in bilinguals. This result demonstrates for the first time substantial plasticity in early, pre-attentive colour perception and has important implications for the mechanisms that are involved in perceptual changes during the processes of language learning and acculturation.

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We report findings from psycholinguistic experiments investigating the detailed timing of processing morphologically complex words by proficient adult second (L2) language learners of English in comparison to adult native (L1) speakers of English. The first study employed the masked priming technique to investigate -ed forms with a group of advanced Arabic-speaking learners of English. The results replicate previously found L1/L2 differences in morphological priming, even though in the present experiment an extra temporal delay was offered after the presentation of the prime words. The second study examined the timing of constraints against inflected forms inside derived words in English using the eye-movement monitoring technique and an additional acceptability judgment task with highly advanced Dutch L2 learners of English in comparison to adult L1 English controls. Whilst offline the L2 learners performed native-like, the eye-movement data showed that their online processing was not affected by the morphological constraint against regular plurals inside derived words in the same way as in native speakers. Taken together, these findings indicate that L2 learners are not just slower than native speakers in processing morphologically complex words, but that the L2 comprehension system employs real-time grammatical analysis (in this case, morphological information) less than the L1 system.

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Tests of the new Rossby wave theories that have been developed over the past decade to account for discrepancies between theoretical wave speeds and those observed by satellite altimeters have focused primarily on the surface signature of such waves. It appears, however, that the surface signature of the waves acts only as a rather weak constraint, and that information on the vertical structure of the waves is required to better discriminate between competing theories. Due to the lack of 3-D observations, this paper uses high-resolution model data to construct realistic vertical structures of Rossby waves and compares these to structures predicted by theory. The meridional velocity of a section at 24° S in the Atlantic Ocean is pre-processed using the Radon transform to select the dominant westward signal. Normalized profiles are then constructed using three complementary methods based respectively on: (1) averaging vertical profiles of velocity, (2) diagnosing the amplitude of the Radon transform of the westward propagating signal at different depths, and (3) EOF analysis. These profiles are compared to profiles calculated using four different Rossby wave theories: standard linear theory (SLT), SLT plus mean flow, SLT plus topographic effects, and theory including mean flow and topographic effects. Our results support the classical theoretical assumption that westward propagating signals have a well-defined vertical modal structure associated with a phase speed independent of depth, in contrast with the conclusions of a recent study using the same model but for different locations in the North Atlantic. The model structures are in general surface intensified, with a sign reversal at depth in some regions, notably occurring at shallower depths in the East Atlantic. SLT provides a good fit to the model structures in the top 300 m, but grossly overestimates the sign reversal at depth. The addition of mean flow slightly improves the latter issue, but is too surface intensified. SLT plus topography rectifies the overestimation of the sign reversal, but overestimates the amplitude of the structure for much of the layer above the sign reversal. Combining the effects of mean flow and topography provided the best fit for the mean model profiles, although small errors at the surface and mid-depths are carried over from the individual effects of mean flow and topography respectively. Across the section the best fitting theory varies between SLT plus topography and topography with mean flow, with, in general, SLT plus topography performing better in the east where the sign reversal is less pronounced. None of the theories could accurately reproduce the deeper sign reversals in the west. All theories performed badly at the boundaries. The generalization of this method to other latitudes, oceans, models and baroclinic modes would provide greater insight into the variability in the ocean, while better observational data would allow verification of the model findings.

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The optically stimulated luminescence (OSL) signal within quartz may be enhanced by thermal transfer during pre-heating. This may occur via a thermally induced charge transfer from low temperature traps to the OSL traps. Thermal transfer may affect both natural and artificially irradiated samples. The effect, as empirically measured via recuperation tests, is typically observed to be negligible for old samples (<1% of natural signal). However, thermal transfer remains a major concern in the dating of young samples as thermal decay and transfers of geologically unstable traps (typically in the TL range 160–280°C) may be incomplete. Upon pre-heating such a sample might undergo thermal transfer to the dating trap and result in a De overestimate. As a result, there has been a tendency for workers to adopt less rigorous pre-heats for young samples. We have investigated the pre-heat dependence of 23 young quartz samples from various depositional environments using pre-heats between 170°C and 300°C, employing the single aliquot regeneration (SAR) protocol. SAR De's were also calculated for 25 additional young quartz samples of different depositional environments and compared with previous multiple aliquot additive dose (MAAD) data. Results demonstrate no significant De dependence upon pre-heat temperatures. A close correspondence between MAAD data and the current SAR data for the samples tested is also illustrated.

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Exascale systems are the next frontier in high-performance computing and are expected to deliver a performance of the order of 10^18 operations per second using massive multicore processors. Very large- and extreme-scale parallel systems pose critical algorithmic challenges, especially related to concurrency, locality and the need to avoid global communication patterns. This work investigates a novel protocol for dynamic group communication that can be used to remove the global communication requirement and to reduce the communication cost in parallel formulations of iterative data mining algorithms. The protocol is used to provide a communication-efficient parallel formulation of the k-means algorithm for cluster analysis. The approach is based on a collective communication operation for dynamic groups of processes and exploits non-uniform data distributions. Non-uniform data distributions can be either found in real-world distributed applications or induced by means of multidimensional binary search trees. The analysis of the proposed dynamic group communication protocol has shown that it does not introduce significant communication overhead. The parallel clustering algorithm has also been extended to accommodate an approximation error, which allows a further reduction of the communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing elements.

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The ability to match individual patients to tailored treatments has the potential to greatly improve outcomes for individuals suffering from major depression. In particular, while the vast majority of antidepressant treatments affect either serotonin or noradrenaline or a combination of these two neurotransmitters, it is not known whether there are particular patients or symptom profiles which respond preferentially to the potentiation of serotonin over noradrenaline or vice versa. Experimental medicine models suggest that the primary mode of action of these treatments may be to remediate negative biases in emotional processing. Such models may provide a useful framework for interrogating the specific actions of antidepressants. Here, we therefore review evidence from studies examining the effects of drugs which potentiate serotonin, noradrenaline or a combination of both neurotransmitters on emotional processing. These results suggest that antidepressants targeting serotonin and noradrenaline may have some specific actions on emotion and reward processing which could be used to improve tailoring of treatment or to understand the effects of dual-reuptake inhibition. Specifically, serotonin may be particularly important in alleviating distress symptoms, while noradrenaline may be especially relevant to anhedonia. The data reviewed here also suggest that noradrenergic-based treatments may have earlier effects on emotional memory that those which affect serotonin.

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The WFDEI meteorological forcing data set has been generated using the same methodology as the widely used WATCH Forcing Data (WFD) by making use of the ERA-Interim reanalysis data. We discuss the specifics of how changes in the reanalysis and processing have led to improvement over the WFD. We attribute improvements in precipitation and wind speed to the latest reanalysis basis data and improved downward shortwave fluxes to the changes in the aerosol corrections. Covering 1979–2012, the WFDEI will allow more thorough comparisons of hydrological and Earth System model outputs with hydrologically and phenologically relevant satellite products than using the WFD.

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In recent years, there has been an increasing interest in the adoption of emerging ubiquitous sensor network (USN) technologies for instrumentation within a variety of sustainability systems. USN is emerging as a sensing paradigm that is being newly considered by the sustainability management field as an alternative to traditional tethered monitoring systems. Researchers have been discovering that USN is an exciting technology that should not be viewed simply as a substitute for traditional tethered monitoring systems. In this study, we investigate how a movement monitoring measurement system of a complex building is developed as a research environment for USN and related decision-supportive technologies. To address the apparent danger of building movement, agent-mediated communication concepts have been designed to autonomously manage large volumes of exchanged information. In this study, we additionally detail the design of the proposed system, including its principles, data processing algorithms, system architecture, and user interface specifics. Results of the test and case study demonstrate the effectiveness of the USN-based data acquisition system for real-time monitoring of movement operations.