13 resultados para Classes of Degeneracy

em Universidad Politécnica de Madrid


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We establish an axiomatic model of multi-measures, capturing some classes of measures studied in the fuzzy sets literature, where they are applied to only one or two arguments.

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A research has been carried out in two-lanehighways in the Madrid Region to propose an alternativemodel for the speed-flowrelationship using regular loop data. The model is different in shape and, in some cases, slopes with respect to the contents of Highway Capacity Manual (HCM). A model is proposed for a mountainous area road, something for which the HCM does not provide explicitly a solution. The problem of a mountain road with high flows to access a popular recreational area is discussed, and some solutions are proposed. Up to 7 one-way sections of two-lanehighways have been selected, aiming at covering a significant number of different characteristics, to verify the proposed method the different classes of highways on which the Manual classifies them. In order to enunciate the model and to verify the basic variables of these types of roads a high number of data have been used. The counts were collected in the same way that the Madrid Region Highway Agency performs their counts. A total of 1.471 hours have been collected, in periods of 5 minutes. The models have been verified by means of specific statistical test (R2, T-Student, Durbin-Watson, ANOVA, etc.) and with the diagnostics of the contrast of assumptions (normality, linearity, homoscedasticity and independence). The model proposed for this type of highways with base conditions, can explain the different behaviors as traffic volumes increase, and follows a polynomial multiple regression model of order 3, S shaped. As secondary results of this research, the levels of service and the capacities of this road have been measured with the 2000 HCM methodology, and the results discussed. © 2011 Published by Elsevier Ltd.

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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. Existing proposals generally restrict in one way or another the classes of programs which can be analyzed. This paper attempts to fill this gap by considering a full dialect of Prolog, essentially the recent 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 which use the full power of the language.

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Dynamic scheduling increases the expressive power of logic programming languages, but also introduces some overhead. In this paper we present two classes of program transformations designed to reduce this additional overhead, while preserving the operational semantics of the original programs, modulo ordering of literals woken at the same time. The first class of transformations simplifies the delay conditions while the second class moves delayed literals later in the rule body. Application of the program transformations can be automated using information provided by compile-time analysis. We provide experimental results obtained from an implementation of the proposed techniques using the CIAO prototype compiler. Our results show that the techniques can lead to substantial performance improvement.

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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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Time series are proficiently converted into graphs via the horizontal visibility (HV) algorithm, which prompts interest in its capability for capturing the nature of different classes of series in a network context. We have recently shown [B. Luque et al., PLoS ONE 6, 9 (2011)] that dynamical systems can be studied from a novel perspective via the use of this method. Specifically, the period-doubling and band-splitting attractor cascades that characterize unimodal maps transform into families of graphs that turn out to be independent of map nonlinearity or other particulars. Here, we provide an in depth description of the HV treatment of the Feigenbaum scenario, together with analytical derivations that relate to the degree distributions, mean distances, clustering coefficients, etc., associated to the bifurcation cascades and their accumulation points. We describe how the resultant families of graphs can be framed into a renormalization group scheme in which fixed-point graphs reveal their scaling properties. These fixed points are then re-derived from an entropy optimization process defined for the graph sets, confirming a suggested connection between renormalization group and entropy optimization. Finally, we provide analytical and numerical results for the graph entropy and show that it emulates the Lyapunov exponent of the map independently of its sign.

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The present research is focused on the application of hyperspectral images for the supervision of quality deterioration in ready to use leafy spinach during storage (Spinacia oleracea). Two sets of samples of packed leafy spinach were considered: (a) a first set of samples was stored at 20 °C (E-20) in order to accelerate the degradation process, and these samples were measured the day of reception in the laboratory and after 2 days of storage; (b) a second set of samples was kept at 10 °C (E-10), and the measurements were taken throughout storage, beginning the day of reception and repeating the acquisition of Images 3, 6 and 9 days later. Twenty leaves per test were analyzed. Hyperspectral images were acquired with a push-broom CCD camera equipped with a spectrograph VNIR (400–1000 nm). Calibration set of spectra was extracted from E-20 samples, containing three classes of degradation: class A (optimal quality), class B and class C (maximum deterioration). Reference average spectra were defined for each class. Three models, computed on the calibration set, with a decreasing degree of complexity were compared, according to their ability for segregating leaves at different quality stages (fresh, with incipient and non-visible symptoms of degradation, and degraded): spectral angle mapper distance (SAM), partial least squares discriminant analysis models (PLS-DA), and a non linear index (Leafy Vegetable Evolution, LEVE) combining five wavelengths were included among the previously selected by CovSel procedure. In sets E-10 and E-20, artificial images of the membership degree according to the distance of each pixel to the reference classes, were computed assigning each pixel to the closest reference class. The three methods were able to show the degradation of the leaves with storage time.

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How easy is it to reproduce the results found in a typical computational biology paper? Either through experience or intuition the reader will already know that the answer is with difficulty or not at all. In this paper we attempt to quantify this difficulty by reproducing a previously published paper for different classes of users (ranging from users with little expertise to domain experts) and suggest ways in which the situation might be improved. Quantification is achieved by estimating the time required to reproduce each of the steps in the method described in the original paper and make them part of an explicit workflow that reproduces the original results. Reproducing the method took several months of effort, and required using new versions and new software that posed challenges to reconstructing and validating the results. The quantification leads to “reproducibility maps” that reveal that novice researchers would only be able to reproduce a few of the steps in the method, and that only expert researchers with advance knowledge of the domain would be able to reproduce the method in its entirety. The workflow itself is published as an online resource together with supporting software and data. The paper concludes with a brief discussion of the complexities of requiring reproducibility in terms of cost versus benefit, and a desiderata with our observations and guidelines for improving reproducibility. This has implications not only in reproducing the work of others from published papers, but reproducing work from one’s own laboratory.

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This article provides a new methodology for estimating fuel consumption and emissions by enabling a correct comparison between freight transportation modes. The approach is developed and integrated as a part of an intelligent transportation system dealing with goods movement. A key issue is related to energy consumption ratios and consequent CO2 emissions. Energy consumption ratios are often used based on transport demand. However, including other ratios based on transport supply can be useful. Furthermore, it is important to indicate which factors are associated with variations in energy consumption and emissions; especially of interest are parameters that have a higher incidence and order of magnitude, in order to fairly compare and understand the difference between transport modes and sub-modes. The study finds that the use of an energy consumption equation can improve the quality of the estimates. The study proposes that coefficients that define the energy consumption equation should be tested to determine market niches and sources of improvement in energy consumption according to the category of vehicles, fuel types used, and classes of products transported.

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Lacunarity as a means of quantifying textural properties of spatial distributions suggests a classification into three main classes of the most abundant soils that cover 92% of Europe. Soils with a well-defined self-similar structure of the linear class are related to widespread spatial patterns that are nondominant but ubiquitous at continental scale. Fractal techniques have been increasingly and successfully applied to identify and describe spatial patterns in natural sciences. However, objects with the same fractal dimension can show very different optical properties because of their spatial arrangement. This work focuses primary attention on the geometrical structure of the geographical patterns of soils in Europe. We made use of the European Soil Database to estimate lacunarity indexes of the most abundant soils that cover 92% of the surface of Europe and investigated textural properties of their spatial distribution. We observed three main classes corresponding to three different patterns that displayed the graphs of lacunarity functions, that is, linear, convex, and mixed. They correspond respectively to homogeneous or self-similar, heterogeneous or clustered and those in which behavior can change at different ranges of scales. Finally, we discuss the pedological implications of that classification.

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Auxin is associated with the regulation of virtually every aspect of plant growth and development. Many previous genetic and biochemical studies revealed that, among the proposed routes for the production of auxin, the so-called indole-3-pyruvic acid (IPA) pathway is the main source for indole-3-acetic acid (IAA) in plants. The IPA pathway involves the action of 2 classes of enzymes, tryptophan-pyruvate aminotransferases (TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS 1(TAA1)/TRYPTOPHAN AMINOTRANSFERASE RELATED (TAR)) and flavin monooxygenases (YUCCA). Both enzyme classes appear to be encoded by small gene families in Arabidopsis consisting of 5 and 11 members, respectively. We recently showed that it is possible to induce transcript accumulation of 2 YUCCA genes, YUC8 and YUC9, by methyl jasmonate treatment. Both gene products were demonstrated to contribute to auxin biosynthesis in planta.1 Here we report that the overexpression of YUC8 as well as YUC9 led to strong lignification of plant aerial tissues. Furthermore, new evidence indicates that this abnormally strong secondary growth is linked to increased levels of ethylene production.

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Sight distance plays an important role in road traffic safety. Two types of Digital Elevation Models (DEMs) are utilized for the estimation of available sight distance in roads: Digital Terrain Models (DTMs) and Digital Surface Models (DSMs). DTMs, which represent the bare ground surface, are commonly used to determine available sight distance at the design stage. Additionally, the use of DSMs provides further information about elements by the roadsides such as trees, buildings, walls or even traffic signals which may reduce available sight distance. This document analyses the influence of three classes of DEMs in available sight distance estimation. For this purpose, diverse roads within the Region of Madrid (Spain) have been studied using software based on geographic information systems. The study evidences the influence of using each DEM in the outcome as well as the pros and cons of using each model.

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This paper presents an approach to compare two types of data, subjective data (Polarity of Pan American Games 2011 event by country) and objective data (the number of medals won by each participating country), based on the Pearson corre- lation. When dealing with events described by people, knowledge acquisition is difficult because their structure is heterogeneous and subjective. A first step towards knowing the polarity of the information provided by people consists in automatically classifying the posts into clusters according to their polarity. The authors carried out a set of experiments using a corpus that consists of 5600 posts extracted from 168 Internet resources related to a specific event: the 2011 Pan American games. The approach is based on four components: a crawler, a filter, a synthesizer and a polarity analyzer. The PanAmerican approach automatically classifies the polarity of the event into clusters with the following results: 588 positive, 336 neutral, and 76 negative. Our work found out that the polarity of the content produced was strongly influenced by the results of the event with a correlation of .74. Thus, it is possible to conclude that the polarity of content is strongly affected by the results of the event. Finally, the accuracy of the PanAmerican approach is: .87, .90, and .80 according to the precision of the three classes of polarity evaluated.