997 resultados para Continuous classes


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This paper presents a new method to calculate sky view factors (SVFs) from high resolution urban digital elevation models using a shadow casting algorithm. By utilizing weighted annuli to derive SVF from hemispherical images, the distance light source positions can be predefined and uniformly spread over the whole hemisphere, whereas another method applies a random set of light source positions with a cosine-weighted distribution of sun altitude angles. The 2 methods have similar results based on a large number of SVF images. However, when comparing variations at pixel level between an image generated using the new method presented in this paper with the image from the random method, anisotropic patterns occur. The absolute mean difference between the 2 methods is 0.002 ranging up to 0.040. The maximum difference can be as much as 0.122. Since SVF is a geometrically derived parameter, the anisotropic errors created by the random method must be considered as significant.

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Wheat dextrin soluble fibre may have metabolic and health benefits, potentially acting via mechanisms governed by the selective modulation of the human gut microbiota. Our aim was to examine the impact of wheat dextrin on the composition and metabolic activity of the gut microbiota. We used a validated in vitro three-stage continuous culture human colonic model (gut model) system comprised of vessels simulating anatomical regions of the human colon. To mimic human ingestion, 7 g of wheat dextrin (NUTRIOSE® FB06) was administered to three gut models, twice daily at 10.00 and 15.00, for a total of 18 days. Samples were collected and analysed for microbial composition and organic acid concentrations by 16S rRNA-based fluorescence in situ hybridisation and gas chromatography approaches, respectively. Wheat dextrin mediated a significant increase in total bacteria in vessels simulating the transverse and distal colon, and a significant increase in key butyrate-producing bacteria Clostridium cluster XIVa and Roseburia genus in all vessels of the gut model. The production of principal short-chain fatty acids, acetate, propionate and butyrate, which have been purported to have protective, trophic and metabolic host benefits, were increased. Specifically, wheat dextrin fermentation had a significant butyrogenic effect in all vessels of the gut model and significantly increased production of acetate (vessels 2 and 3) and propionate (vessel 3), simulating the transverse and distal regions of the human colon, respectively. In conclusion, wheat dextrin NUTRIOSE® FB06 is selectively fermented in vitro by Clostridium cluster XIVa and Roseburia genus and beneficially alters the metabolic profile of the human gut microbiota.

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A simple tube-in-tube reactor based on the gas-permeable membrane Teflon AF-2400 was used in the continuous flow reaction of gaseous ammonia with isothiocyanates and one isocyanate. A colourimetric in-line titration technique is also reported as a simple method to quantify the amount of ammonia taken up by the solvent in the system.

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Certain milk factors can promote the growth of a host-friendly gastrointestinal microflora. This may explain why breast-fed infants experience fewer intestinal infections than their formula-fed counterparts. The effect of formula supplementation with two such factors was investigated in this study. Infant faecal specimens were used to ferment formulas supplemented with glycomacropeptide and α-lactalbumin in a two-stage compound continuous culture model. Bacteriology was determined by fluorescence in situ hybridisation. Vessels that contained breast milk as well as α-lactalbumin and glycomacropeptide had stable counts of bifidobacteria while lactobacilli increased significantly only in vessels with breast milk. Bacteroides, clostridia and Escherichia coli decreased significantly in all runs. Acetate was the principal acid found along with high amounts of propionate and lactate. Supplementation of infant formulas with appropriate milk proteins may be useful in simulating the beneficial bacteriological effects of breast milk.

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There are well-known difficulties in making measurements of the moisture content of baked goods (such as bread, buns, biscuits, crackers and cake) during baking or at the oven exit; in this paper several sensing methods are discussed, but none of them are able to provide direct measurement with sufficient precision. An alternative is to use indirect inferential methods. Some of these methods involve dynamic modelling, with incorporation of thermal properties and using techniques familiar in computational fluid dynamics (CFD); a method of this class that has been used for the modelling of heat and mass transfer in one direction during baking is summarized, which may be extended to model transport of moisture within the product and also within the surrounding atmosphere. The concept of injecting heat during the baking process proportional to the calculated heat load on the oven has been implemented in a control scheme based on heat balance zone by zone through a continuous baking oven, taking advantage of the high latent heat of evaporation of water. Tests on biscuit production ovens are reported, with results that support a claim that the scheme gives more reproducible water distribution in the final product than conventional closed loop control of zone ambient temperatures, thus enabling water content to be held more closely within tolerance.

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The use of a mesofluidic flow reactor is described for performing Curtius rearrangement reactions of carboxylic acids in the presence of diphenylphosphoryl azide and trapping of the intermediate isocyanates with various nucleophiles.

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In order to overcome divergence of estimation with the same data, the proposed digital costing process adopts an integrated design of information system to design the process knowledge and costing system together. By employing and extending a widely used international standard, industry foundation classes, the system can provide an integrated process which can harvest information and knowledge of current quantity surveying practice of costing method and data. Knowledge of quantification is encoded from literatures, motivation case and standards. It can reduce the time consumption of current manual practice. The further development will represent the pricing process in a Bayesian Network based knowledge representation approach. The hybrid types of knowledge representation can produce a reliable estimation for construction project. In a practical term, the knowledge management of quantity surveying can improve the system of construction estimation. The theoretical significance of this study lies in the fact that its content and conclusion make it possible to develop an automatic estimation system based on hybrid knowledge representation approach.

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Sophisticated, intentional decision-making is a hallmark of mature, self-aware behaviour. Although neural, psychological, interpersonal, and socioeconomic elements that contribute to such adaptive, foresighted behaviour mature and/or change throughout the life-span, here we concentrate on relevant maturational processes that take place during adolescence, a period of disproportionate developmental opportunity and risk. A brief, eclectic overview is presented of recent evidence, new challenges, and current thinking on the fundamental mechanisms that mature throughout adolescence to support adaptive, self-controlled decision-making. This is followed by a proposal for the putative contribution of frontostriatal mechanisms to the moment-to-moment assembly of evaluative heuristics that mediate increased decision-making sophistication, promoting the maturation of self-regulated behaviour through adolescence and young adulthood.

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Advances in hardware and software technologies allow to capture streaming data. The area of Data Stream Mining (DSM) is concerned with the analysis of these vast amounts of data as it is generated in real-time. Data stream classification is one of the most important DSM techniques allowing to classify previously unseen data instances. Different to traditional classifiers for static data, data stream classifiers need to adapt to concept changes (concept drift) in the stream in real-time in order to reflect the most recent concept in the data as accurately as possible. A recent addition to the data stream classifier toolbox is eRules which induces and updates a set of expressive rules that can easily be interpreted by humans. However, like most rule-based data stream classifiers, eRules exhibits a poor computational performance when confronted with continuous attributes. In this work, we propose an approach to deal with continuous data effectively and accurately in rule-based classifiers by using the Gaussian distribution as heuristic for building rule terms on continuous attributes. We show on the example of eRules that incorporating our method for continuous attributes indeed speeds up the real-time rule induction process while maintaining a similar level of accuracy compared with the original eRules classifier. We termed this new version of eRules with our approach G-eRules.

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Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.