901 resultados para Uninterpretable features


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Abstract interpretation-based data-flow analysis of logic programs is at this point relatively well understood from the point of view of general frameworks and abstract domains. On the other hand, comparatively little attention has been given to the problems which arise when analysis of a full, practical dialect of the Prolog language is attempted, and only few solutions to these problems have been proposed to date. Such problems relate to dealing correctly with all builtins, including meta-logical and extra-logical predicates, with dynamic predicates (where the program is modified during execution), and with the absence of certain program text during compilation. Existing proposals for dealing with such issues generally restrict in one way or another the classes of programs which can be analyzed if the information from analysis is to be used for program optimization. This paper attempts to fill this gap by considering a full dialect of Prolog, essentially following the recently proposed ISO standard, pointing out the problems that may arise in the analysis of such a dialect, and proposing a combination of known and novel solutions that together allow the correct analysis of arbitrary programs using the full power of the language.

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This work studies the physiology of Schizosaccharomyces pombe strain 938 in the production of white wine with high malic acid levels as the sole fermentative yeast, as well as in mixed and sequential fermentations with Saccharomyces cerevisiae Cru Blanc. The induction of controlled maloalcoholic fermentation through the use of Schizosaccharomyces spp. is now being viewed with much interest. The acetic, malic and pyruvic acid concentrations, relative density and pH of the musts were measured over the entire fermentation period. In all fermentations in which Schizo. pombe 938 was involved, nearly all the malic acid was consumed and moderate acetic concentrations produced. The urea content and alcohol level of these wines were notably lower than in those made with Sacch. cerevisiae Cru Blanc alone. The pyruvic acid concentration was significantly higher in Schizo. pombe fermentations. The sensorial properties of the different final wines varied widely.

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Detecting user affect automatically during real-time conversation is the main challenge towards our greater aim of infusing social intelligence into a natural-language mixed-initiative High-Fidelity (Hi-Fi) audio control spoken dialog agent. In recent years, studies on affect detection from voice have moved on to using realistic, non-acted data, which is subtler. However, it is more challenging to perceive subtler emotions and this is demonstrated in tasks such as labelling and machine prediction. This paper attempts to address part of this challenge by considering the role of user satisfaction ratings and also conversational/dialog features in discriminating contentment and frustration, two types of emotions that are known to be prevalent within spoken human-computer interaction. However, given the laboratory constraints, users might be positively biased when rating the system, indirectly making the reliability of the satisfaction data questionable. Machine learning experiments were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. Our results indicated that standard classifiers were significantly more successful in discriminating the abovementioned emotions and their intensities (reflected by user satisfaction ratings) from annotator data than from user data. These results corroborated that: first, satisfaction data could be used directly as an alternative target variable to model affect, and that they could be predicted exclusively by dialog features. Second, these were only true when trying to predict the abovementioned emotions using annotator?s data, suggesting that user bias does exist in a laboratory-led evaluation.

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The neutronics hall of the Nuclear Engineering Department at the Polytechnical University of Madrid has been characterized. The neutron spectra and the ambient dose equivalent produced by an 241AmBe source were measured at various source-to-detector distances on the new bench. Using Monte Carlo methods a detailed model of the neutronics hall was designed, and neutron spectra and the ambient dose equivalent were calculated at the same locations where measurements were carried out. A good agreement between measured and calculated values was found.

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Se revisan los métodas de valoración de arbolado

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In this work the results of a geochemical and isotopic survey of 37 gas discharges was carried out in continental Spain are presented and discussed. On the basis of the gas chemical composition, four different areas can be distinguished, as follows: 1) Selva-Emborda (SE) region; 2) Guadalentin Valley (GV); 3) Campo de Calatrava (CC) and 3) the inner part of Spain (IS). The SE, GV and CC areas are characterized by CO2-rich gases, while IS has N2 as main gas compound. The CO2-rich gases can be distinguished at their turn on the basis on the helium and carbon isotopic composition. The SE and CC areas have a strong mantle signature (up to 3 Ra). Nevertheless, the carbon isotopic composition of CC is within the mantle range and that of SE is slightly more negative (down to -8‰ PDB). The GV gases have a lower mantle signature (61 Ra) with respect to SE and CC and more negative carbon isotopes (6-10‰ PDB). It is worth to mention that the SE, GV and CC areas are related to the youngest volcanic activity in continental Spain, for example the Garrotxa Volcanic Field in Catalonia records the latest event dated at 10,000 years, and the isotopic features, particularly those of helium, are suggesting the presence of magmatic bodies still cooling at depth. The N2-rich gases, i.e. those from the IS area, has an atmospheric origin, as highlighted by the N2/Ar ratio that ranges between those of air and ASW (Air Saturated Water). The isotopic composition of carbon is distinctly negative (down to -21‰ PDB) and that of helium is typically crustal (0.02-0.08 Ra), confirming that these gas discharges are related to a relatively shallow source.

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This study evaluated the effect of adding soy protein isolate (SPI) and long-chain perception, trained and untrained panel inulin (INL) blends with 10 different SPI : INL ratios on the textural, rheological and 17 microstructural properties of freshly made and frozen/thawed potato puree. All the potato puree samples were subjected to a sensory texture pro?le analysis and a 21 trained panel rated the intensity of six descriptors, while an untrained panel did the same on six selected frozen/thawed products. The main SPI : INL ratio effect remained signi?cant for all the descriptors evaluated, when the analysis of variance was applied considering the untrained assessors as random effects. However, only trained panel scores for creaminess corresponded well with untrained assessor. Rheological ?ow index values were linked with variations in perceived consistency, and geometric and surface textural attributes were explained by structural features such as the presence of INL crystallites and SPI coarse strands.

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Using a laboratory impact tester, impacts were applied to fruits of different varieties of apples and pears. The response to impact was analized, and many parameters were recorded, to be correlated to bruise susceptibility and to ripeness changes. Different methods for the detection and evaluation of the bruised Area and its features were studied, using direct observation and various reactives. Different types of bruises were established.

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Mealiness is a negative attribute of sensory texture that combines the sensation of a disaggregated tissue with the sensation of lack of juiciness. Since January 1996, a wide EC Project entitled : "Mealiness in fruits. Consumers perception and means for detection'" is being carried out. Within it, three sensory panels have been trained at : the Institute of Food Research (IFR, United Kingdom), the Instituto de Agroquímica y Tecnología de los Alimentos (IATA, Spain) and the Institut voor Agrotechnologisch Onderzoek (ATO-DLO, Netherlands) to assess mealiness in apples. In all three cases, mealiness has been described as a multidimensional sensory descriptor capable of gathering the loss of consistency (of crispness and of hardness) and of juiciness. Also within the EC Project several instrumental procedures have been tested for mealiness assessment. In this sense the Physical Properties Laboratory (ETS1A-UPM) has focused its aims in a first stage on performing instrumental tests for assessing some textural descriptors as crispiness, hardness and juiciness. The results obtained within these tests have shown to correlate well with the sensory measurements (Barreiro et Ruiz-Altisent, 1997) in apples, but also have succeed when trying to generate several texture degradation levels on peaches from which mealiness appears to be the last stage (Ortiz et al. 1997).

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Mealiness is a negative attribute of sensory texture, characterised by the lack of juiciness decrease in the total amount of of water content of tissues. Peach mealy textures are known as \ and leatheriness. Besides the lack of juiciness and flavour, that characterises mealy fruits, in associated with internal browning near the stone and an incapacity of ripening although there i ripe appearance. It is considered as a physiological disorder that appears in stone fruits probably < unbalanced pectolitic enzyme activity during storage. Since January 1996, a wide EC Project entitled: "Mealiness in fruits. Consumer perception and i detection" is being carried out. Within it, the Physical Properties Laboratory (ETSIA-UPM) working to develop instrumental procedures to detect mealiness in different types of fruits (s contributions by Barreiro to AgEng). The results obtained have shown to correlate well with \ measurements in apples (Barreiro et al), also we have succeeded in identifying individual mealy j the basis of instrumental measurement in peaches. The definition of these texture categories will be used in further studies as a base for new individual classification.

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Most CPV systems are based on Fresnel lenses. Among these, LPI-patented Fresnel-Köhler (FK) concentrator outstands owing to performance and practical reasons. The VentanaTM power train is the first off-the-shelf commercial product based on the FK and comprises both the primary (POE) lenses (a 36-units 1×1 m2 acrylic panel manufactured by EVONIK and 10×) and glass (or Savosil) secondary optics (SOE). This high concentration optical train (Cg=1,024×, ~250mm optical depth) fits with 5×5 mm2 (at least) solar cells. The optical train is the fruit of a 1-year development that has included design, modeling, prototyping and characterization, and through the process LPI had the opportunity to find out how well the actual performance correlates with models, but also learned practical aspects of a CPV system of this kind, some of which have very positive impact on system performance and reliability.

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The Software Engineering (SE) community has historically focused on working with models to represent functionality and persistence, pushing interaction modelling into the background, which has been covered by the Human Computer Interaction (HCI) community. Recently, adequately modelling interaction, and specifically usability, is being considered as a key factor for success in user acceptance, making the integration of the SE and HCI communities more necessary. If we focus on the Model-Driven Development (MDD) paradigm, we notice that there is a lack of proposals to deal with usability features from the very first steps of software development process. In general, usability features are manually implemented once the code has been generated from models. This contradicts the MDD paradigm, which claims that all the analysts? effort must be focused on building models, and the code generation is relegated to model to code transformations. Moreover, usability features related to functionality may involve important changes in the system architecture if they are not considered from the early steps. We state that these usability features related to functionality can be represented abstractly in a conceptual model, and their implementation can be carried out automatically.

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Speech is the major function, emergence and which development radically changes all course of formation of the identity of the child already in the early childhood. If language and speech development in solitary born children is investigated today quite well, at twin children this process practically is not studied. Our research was carried out for the purpose of studying of an originality of mastering by speech by heterosexual children of pair of twins within communicative and pragmatist approach (T.N. Ushakov,G. V. Chirkina). Application of this approach to the analysis of process of communication at twin children allowed us to allocate those peculiar receptions and means of communication which they functionally develop in a situation of pair of twins, as allows them to show the phenomena of the speech which are not meeting at solitary born contemporaries. In this work results of supervision and research of pair of heterosexual twins of the second year of the life, carried out by a technique developed by us under the scientific guide of G. V. Chirkina

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Video-based vehicle detection is the focus of increasing interest due to its potential towards collision avoidance. In particular, vehicle verification is especially challenging due to the enormous variability of vehicles in size, color, pose, etc. In this paper, a new approach based on supervised learning using Principal Component Analysis (PCA) is proposed that addresses the main limitations of existing methods. Namely, in contrast to classical approaches which train a single classifier regardless of the relative position of the candidate (thus ignoring valuable pose information), a region-dependent analysis is performed by considering four different areas. In addition, a study on the evolution of the classification performance according to the dimensionality of the principal subspace is carried out using PCA features within a SVM-based classification scheme. Indeed, the experiments performed on a publicly available database prove that PCA dimensionality requirements are region-dependent. Hence, in this work, the optimal configuration is adapted to each of them, rendering very good vehicle verification results.

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MFCC coefficients extracted from the power spectral density of speech as a whole, seems to have become the de facto standard in the area of speaker recognition, as demonstrated by its use in almost all systems submitted to the 2013 Speaker Recognition Evaluation (SRE) in Mobile Environment [1], thus relegating to background this component of the recognition systems. However, in this article we will show that selecting the adequate speaker characterization system is as important as the selection of the classifier. To accomplish this we will compare the recognition rates achieved by different recognition systems that relies on the same classifier (GMM-UBM) but connected with different feature extraction systems (based on both classical and biometric parameters). As a result we will show that a gender dependent biometric parameterization with a simple recognition system based on GMM- UBM paradigm provides very competitive or even better recognition rates when compared to more complex classification systems based on classical features