984 resultados para Natural Semantic Metalanguage


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The ideal dermal matrix should be able to provide the right biological and physical environment to ensure homogenous cell and extracellular matrix (ECM) distribution, as well as the right size and morphology of the neo-tissue required. Four natural and synthetic 3D matrices were evaluated in vitro as dermal matrices, namely (1) equine collagen foam, TissuFleece®, (2) acellular dermal replacement, Alloderm®, (3) knitted poly(lactic-co-glycolic acid) (10:90)–poly(-caprolactone) (PLGA–PCL) mesh, (4) chitosan scaffold. Human dermal fibroblasts were cultured on the specimens over 3 weeks. Cell morphology, distribution and viability were assessed by electron microscopy, histology and confocal laser microscopy. Metabolic activity and DNA synthesis were analysed via MTS metabolic assay and [3H]-thymidine uptake, while ECM protein expression was determined by immunohistochemistry. TissuFleece®, Alloderm® and PLGA–PCL mesh supported cell attachment, proliferation and neo-tissue formation. However, TissuFleece® contracted to 10% of the original size while Alloderm® supported cell proliferation predominantly on the surface of the material. PLGA–PCL mesh promoted more homogenous cell distribution and tissue formation. Chitosan scaffolds did not support cell attachment and proliferation. These results demonstrated that physical characteristics including porosity and mechanical stability to withstand cell contraction forces are important in determining the success of a dermal matrix material.

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In this paper we describe a Semantic Grid application designed to enable museums and indigenous communities in distributed locations, to collaboratively discuss, describe and annotate digital objects and documents in museums that originally belonged to or are of cultural or historical significance to indigenous groups. By extending and refining an existing application, Vannotea, we enable users on access grid nodes to collaboratively attach descriptive, rights and tribal care metadata and annotations to digital images, video or 3D representations. The aim is to deploy the software within museums to enable the traditional owners to describe and contextualize museum content in their own words and from their own perspectives. This sharing and exchange of knowledge will hopefully revitalize cultures eroded through colonization and globalization and repair and strengthen relationships between museums and indigenous communities.

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Consider a person searching electronic health records, a search for the term ‘cracked skull’ should return documents that contain the term ‘cranium fracture’. A information retrieval systems is required that matches concepts, not just keywords. Further more, determining relevance of a query to a document requires inference – its not simply matching concepts. For example a document containing ‘dialysis machine’ should align with a query for ‘kidney disease’. Collectively we describe this problem as the ‘semantic gap’ – the difference between the raw medical data and the way a human interprets it. This paper presents an approach to semantic search of health records by combining two previous approaches: an ontological approach using the SNOMED CT medical ontology; and a distributional approach using semantic space vector space models. Our approach will be applied to a specific problem in health informatics: the matching of electronic patient records to clinical trials.

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Compressed natural gas (CNG) engines are thought to be less harmful to the environment than conventional diesel engines, especially in terms of particle emissions. Although, this is true with respect to particulate matter (PM) emissions, results of particle number (PN) emission comparisons have been inconclusive. In this study, results of on-road and dynamometer studies of buses were used to derive several important conclusions. We show that, although PN emissions from CNG buses are significantly lower than from diesel buses at low engine power, they become comparable at high power. For diesel buses, PN emissions are not significantly different between acceleration and operation at steady maximum power. However, the corresponding PN emissions from CNG buses when accelerating are an order of magnitude greater than when operating at steady maximum power. During acceleration under heavy load, PN emissions from CNG buses are an order of magnitude higher than from diesel buses. The particles emitted from CNG buses are too small to contribute to PM10 emissions or contribute to a reduction of visibility, and may consist of semivolatile nanoparticles.

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Motor vehicle emission factors are generally derived from driving tests mimicking steady state conditions or transient drive cycles. However, neither of these test conditions completely represents real world driving conditions. In particular, they fail to determine emissions generated during the accelerating phase – a condition in which urban buses spend much of their time. In this study we analyse and compare the results of time-dependant emission measurements conducted on diesel and compressed natural gas (CNG) buses during an urban driving cycle on a chassis dynamometer and we derive power-law expressions relating carbon dioxide (CO2) emission factors to the instantaneous speed while accelerating from rest. Emissions during acceleration are compared with that during steady speed operation. These results have important implications for emission modelling particularly under congested traffic conditions.

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The chapter investigates Shock Control Bumps (SCB) on a Natural Laminar Flow (NLF) aerofoil; RAE 5243 for Active Flow Control (AFC). A SCB approach is used to decelerate supersonic flow on the suction/pressure sides of transonic aerofoil that leads delaying shock occurrence or weakening of shock strength. Such an AFC technique reduces significantly the total drag at transonic speeds. This chapter considers the SCB shape design optimisation at two boundary layer transition positions (0 and 45%) using an Euler software coupled with viscous boundary layer effects and robust Evolutionary Algorithms (EAs). The optimisation method is based on a canonical Evolution Strategy (ES) algorithm and incorporates the concepts of hierarchical topology and parallel asynchronous evaluation of candidate solution. Two test cases are considered with numerical experiments; the first test deals with a transition point occurring at the leading edge and the transition point is fixed at 45% of wing chord in the second test. Numerical results are presented and it is demonstrated that an optimal SCB design can be found to significantly reduce transonic wave drag and improves lift on drag (L/D) value when compared to the baseline aerofoil design.

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Rice grassy stunt virus is a member of the genus Tenuivirus, is persistently transmitted by a brown planthopper, and has occurred in rice plants in South, Southeast, and East Asia (similar to North and South America). We determined the complete nucleotide (nt) sequences of RNAs 1 (9760 nt), 2 (4069 nt), 3 (3127 nt), 4 (2909 nt), 5 (2704 nt), and 6 (2590 nt) of a southern Philippine isolate from South Cotabato and compared them with those of a northern Philippine isolate from Laguna (Toriyama et al., 1997, 1998). The numbers of nucleotides in the terminal untranslated regions and open reading frames were identical between the two isolates except for the 5′ untranslated region of the complementary strand of RNA 4. Overall nucleotide differences between the two isolates were only 0.08% in RNA 1, 0.58% in RNA 4, and 0.26% in RNA 5, whereas they were 2.19% in RNA 2, 8.38% in RNA 3, and 3.63% in RNA 6. In the intergenic regions, the two isolates differed by 9.12% in RNA 2, 11.6% in RNA 3, and 6.86% in RNA 6 with multiple consecutive nucleotide deletion/insertions, whereas they differed by only 0.78% in RNA 4 and 0.34% in RNA 5. The nucleotide variation in the intergenic region of RNA 6 within the South Cotabato isolate was only 0.33%. These differences in accumulation of mutations among individual RNA segments indicate that there was genetic reassortment in the two geographical isolates; RNAs 1, 4, and 5 of the two isolates came from a common ancestor, whereas RNAs 2, 3, and 6 were from two different ancestors.

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The genetic structure of rice tungro bacilliform virus (RTBV) populations within and between growing sites was analyzed in a collection of natural field isolates from different rice varieties grown in eight tungro-endemic sites of the Philippines. Total DNA extracts from 345 isolates were digested with EcoRV restriction enzyme and hybridized with a full-length probe of RTBV, a procedure shown in preliminary experiments capable of revealing high levels of polymorphism in RTBV field isolates. In the total population, 17 distinct EcoRV-based genome profiles (genotypes) were identified and used as indicators for virus diversity. Distinct sets of genotypes occurred in Isabela and North Cotabato provinces suggesting a geographic isolation of virus populations. However, among the sites in each province, there were few significant differences in the genotype compositions of virus populations. The number of genotypes detected at a site varied from two to nine with a few genotypes dominating. In general the isolates at a site persisted from season to season indicating a genetic stability for the local virus population. Over the sampling time, IRRI rice varieties, which have green leafhopper resistance genes, supported similar virus populations to those supported by other varieties, indicating that the variety of the host exerted no apparent selection pressures. Insect transmission experiments on selected RTBV field isolates showed that dramatic shifts in genotype and phenotype distributions can occur in response to host /environmental shifts.

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We define a semantic model for purpose, based on which purpose-based privacy policies can be meaningfully expressed and enforced in a business system. The model is based on the intuition that the purpose of an action is determined by its situation among other inter-related actions. Actions and their relationships can be modeled in the form of an action graph which is based on the business processes in a system. Accordingly, a modal logic and the corresponding model checking algorithm are developed for formal expression of purpose-based policies and verifying whether a particular system complies with them. It is also shown through various examples, how various typical purpose-based policies as well as some new policy types can be expressed and checked using our model.

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This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.

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This paper presents a robust stochastic model for the incorporation of natural features within data fusion algorithms. The representation combines Isomap, a non-linear manifold learning algorithm, with Expectation Maximization, a statistical learning scheme. The representation is computed offline and results in a non-linear, non-Gaussian likelihood model relating visual observations such as color and texture to the underlying visual states. The likelihood model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The likelihoods are expressed as a Gaussian Mixture Model so as to permit convenient integration within existing nonlinear filtering algorithms. The resulting compactness of the representation is especially suitable to decentralized sensor networks. Real visual data consisting of natural imagery acquired from an Unmanned Aerial Vehicle is used to demonstrate the versatility of the feature representation.

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This paper presents an overview of the experiments conducted using Hybrid Clustering of XML documents using Constraints (HCXC) method for the clustering task in the INEX 2009 XML Mining track. This technique utilises frequent subtrees generated from the structure to extract the content for clustering the XML documents. It also presents the experimental study using several data representations such as the structure-only, content-only and using both the structure and the content of XML documents for the purpose of clustering them. Unlike previous years, this year the XML documents were marked up using the Wiki tags and contains categories derived by using the YAGO ontology. This paper also presents the results of studying the effect of these tags on XML clustering using the HCXC method.

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The flying capacitor multicell inverter (FCMI) possesses natural balancing property. With the phase-shifted (PS) carrier-based scheme, natural balancing can be achieved in a straightforward manner. However, to achieve natural balancing with the harmonically optimal phase-disposition (PD) carrierbased scheme, the conventional approaches require (n-1) x (n-1) trapezoidal carrier signals for an n-level inverter, which is (n-1) x (n-2) times more than that in the standard PD scheme. This paper proposes two improved natural balancing strategies for FMI under PD scheme, which use the same (n-1) carrier signals as used in the standard PD scheme. In the first scheme, on-line detection is performed of the band in which the modulation signal is located, corresponding period number of the carrier, and rising or falling half cycle of the carrier waveform to generate the switching signals based on certain rules. In the second strategy, the output voltage level selection is first processed and the switching signals are then generated according to a rule based on preferential cell selection algorithm. These methods are easy to use and can be simply implemented as compared to the other available methods. Simulation and experimental results are presented for a five-level inverter to verify these proposed schemes.

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This technical report is concerned with one aspect of environmental monitoring—the detection and analysis of acoustic events in sound recordings of the environment. Sound recordings offer ecologists the advantage of cheaper and increased sampling but make available so much data that automated analysis becomes essential. The report describes a number of tools for automated analysis of recordings, including noise removal from spectrograms, acoustic event detection, event pattern recognition, spectral peak tracking, syntactic pattern recognition applied to call syllables, and oscillation detection. These algorithms are applied to a number of animal call recognition tasks, chosen because they illustrate quite different modes of analysis: (1) the detection of diffuse events caused by wind and rain, which are frequent contaminants of recordings of the terrestrial environment; (2) the detection of bird and calls; and (3) the preparation of acoustic maps for whole ecosystem analysis. This last task utilises the temporal distribution of events over a daily, monthly or yearly cycle.