892 resultados para estimating conditional probabilities


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Effective static analyses have been proposed which allow inferring functions which bound the number of resolutions or reductions. These have the advantage of being independent from the platform on which the programs are executed and such bounds have been shown useful in a number of applications, such as granularity control in parallel execution. On the other hand, in certain distributed computation scenarios where different platforms come into play, with each platform having different capabilities, it is more interesting to express costs in metrics that include the characteristics of the platform. In particular, it is specially interesting to be able to infer upper and lower bounds on actual execution time. With this objective in mind, we propose a method which allows inferring upper and lower bounds on the execution times of procedures of a program in a given execution platform. The approach combines compile-time cost bounds analysis with a one-time profiling of the platform in order to determine the values of certain constants for that platform. These constants calibrate a cost model which from then on is able to compute statically time bound functions for procedures and to predict with a significant degree of accuracy the execution times of such procedures in the given platform. The approach has been implemented and integrated in the CiaoPP system.

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This paper presents a conditional parallelization process for and-parallelism based on the notion of non-strict independence, a more relaxed notion than the traditional of strict independence. By using this notion, a parallelism annotator can extract more parallelism from programs. On the other hand, the intrinsic complexity of non-strict independence poses new challenges to this task. We report here on the implementation we have accomplished of an annotator for non-strict independence, capable of producing both static and dynamic execution graphs. This implementation, along with the also implemented independence checker and their integration in our system, have resulted what is, to the best of our knowledge, the first parallelizing compiler based on nonstrict independence which produces dynamic execution graphs. The paper also presents a preliminary assessment of the implemented tools, comparing them with the existing ones for strict independence, which shows encouraging results.

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Current trends in the fields of artifical intelligence and expert systems are moving towards the exciting possibility of reproducing and simulating human expertise and expert behaviour into a knowledge base, coupled with an appropriate, partially ‘intelligent’, computer code. This paper deals with the quality level prediction in concrete structures using the helpful assistance of an expert system, QL-CONST1, which is able to reason about this specific field of structural engineering. Evidence, hypotheses and factors related to this human knowledge field have been codified into a knowledge base. This knowledge base has been prepared in terms of probabilities of the presence of either hypotheses or evidence and the conditional presence of both. Human experts in the fields of structural engineering and the safety of structures gave their invaluable knowledge and assistance to the construction of the knowledge base. Some illustrative examples for, the validation of the expert system behaviour are included.

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Natural regeneration is an ecological key-process that makes plant persistence possible and, consequently, it constitutes an essential element of sustainable forest management. In this respect, natural regeneration in even-aged stands of Pinus pinea L. located in the Spanish Northern Plateau has not always been successfully achieved despite over a century of pine nut-based management. As a result, natural regeneration has recently become a major concern for forest managers when we are living a moment of rationalization of investment in silviculture. The present dissertation is addressed to provide answers to forest managers on this topic through the development of an integral regeneration multistage model for P. pinea stands in the region. From this model, recommendations for natural regeneration-based silviculture can be derived under present and future climate scenarios. Also, the model structure makes it possible to detect the likely bottlenecks affecting the process. The integral model consists of five submodels corresponding to each of the subprocesses linking the stages involved in natural regeneration (seed production, seed dispersal, seed germination, seed predation and seedling survival). The outputs of the submodels represent the transitional probabilities between these stages as a function of climatic and stand variables, which in turn are representative of the ecological factors driving regeneration. At subprocess level, the findings of this dissertation should be interpreted as follows. The scheduling of the shelterwood system currently conducted over low density stands leads to situations of dispersal limitation since the initial stages of the regeneration period. Concerning predation, predator activity appears to be only limited by the occurrence of severe summer droughts and masting events, the summer resulting in a favourable period for seed survival. Out of this time interval, predators were found to almost totally deplete seed crops. Given that P. pinea dissemination occurs in summer (i.e. the safe period against predation), the likelihood of a seed to not be destroyed is conditional to germination occurrence prior to the intensification of predator activity. However, the optimal conditions for germination seldom take place, restraining emergence to few days during the fall. Thus, the window to reach the seedling stage is narrow. In addition, the seedling survival submodel predicts extremely high seedling mortality rates and therefore only some individuals from large cohorts will be able to persist. These facts, along with the strong climate-mediated masting habit exhibited by P. pinea, reveal that viii the overall probability of establishment is low. Given this background, current management –low final stand densities resulting from intense thinning and strict felling schedules– conditions the occurrence of enough favourable events to achieve natural regeneration during the current rotation time. Stochastic simulation and optimisation computed through the integral model confirm this circumstance, suggesting that more flexible and progressive regeneration fellings should be conducted. From an ecological standpoint, these results inform a reproductive strategy leading to uneven-aged stand structures, in full accordance with the medium shade-tolerant behaviour of the species. As a final remark, stochastic simulations performed under a climate-change scenario show that regeneration in the species will not be strongly hampered in the future. This resilient behaviour highlights the fundamental ecological role played by P. pinea in demanding areas where other tree species fail to persist.

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This work deals with quality level prediction in concrete structures through the helpful assistance of an expert system wich is able to apply reasoning to this field of structural engineering. Evidences, hypotheses and factors related to this human knowledge field have been codified into a Knowledge Base in terms of probabilities for the presence of either hypotheses or evidences,and conditional presence of both. Human experts in structural engineering and safety of structures gave their invaluable knowledge and assistance necessary when constructing the "computer knowledge body".

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This work investigates to what degree speakers with different verbal intelligence may adapt to each other. The work is based on a corpus consisting of 100 descriptions of a short film (monologues), 56 discussions about the same topic (dialogues), and verbal intelligence scores of the test participants. Adaptation between two dialogue partners was measured using cross-referencing, proportion of "I", "You" and "We" words, between-subject correlation and similarity of texts. It was shown that lower verbal intelligence speakers repeated more nouns and adjectives from the other and used the same linguistic categories more often than higher verbal intelligence speakers. In dialogues between strangers, participants with higher verbal intelligence showed a greater level of adaptation.

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We have determined matrix elements for all experimental configurations of Ca III, including the 3s3p63d configuration. These values have been obtained using intermediate coupling (IC). For these IC calculations, we have used the standard method of least-squares fitting from the experimental energy levels, using the computer code developed by Robert Cowan. In this paper, using these matrix elements, we report the calculated values of the Ca III Stark widths and shifts for 148 spectral lines, of 56 Ca III spectral line transition probabilities and of eight radiative lifetimes of Ca III levels. The Stark widths and shifts, calculated using the Griem semi-empirical approach, correspond to the spectral lines of Ca III and are presented for an electron density of 1017 cm?3 and temperatures T = 1.0?10.0 (×104 K). The theoretical trends of the Stark broadening parameter versus the temperature are presented for transitions that are of astrophysical interest. There is good agreement between our calculations, for transition probabilities and radiative lifetimes, and the experimental values presented in the literature. We have not been able to find any values for the Stark parameters in the references.

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We present improved experimental transition probabilities for the optical Ca I 4s4p-4s4d and 4s4p-4p2multiplets. The values were determined with an absolute uncertainty of 10%. Transition probabilities have been determined by the branching ratios from the measurement of relative line intensities emitted by laser-induced plasma (LIP). The line intensities were obtained with the target (leadcalcium) placed in argon atmosphere at 6 Torr, recorded at a 2.5 µs delay from the laser pulse, which provides appropriate measurement conditions, and analysed between 350.0 and 550.0 nm. They are measured when the plasma reaches local thermodynamic equilibrium (LTE). The plasma is characterized by electron temperature (T) of 11400 K and an electron number density (Ne) of 1.1 x 1016 cm-3. The influence self-absorption has been estimated for every line, and plasma homogeneity has been checked. The values obtained were compared with previous experimental values in the literature. The method for measurement of transition probabilities using laser-induced plasma as spectroscopic source has been checked.

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Computing the modal parameters of structural systems often requires processing data from multiple non-simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors, which are fixed for all measurements, while the other sensors change their position from one setup to the next. One possibility is to process the setups separately resulting in different modal parameter estimates for each setup. Then, the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global mode shapes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a new state space model that processes all setups at once. The result is that the global mode shapes are obtained automatically, and only a value for the natural frequency and damping ratio of each mode is estimated. We also investigate the estimation of this model using maximum likelihood and the Expectation Maximization algorithm, and apply this technique to simulated and measured data corresponding to different structures.

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The research that is summarized in this article, resultant of diverse studies realized in the CEDEX, has for object a comparative analysis of methods of overtopping rates developed by different authors. For that, the summary was realized first and the analysis of the existing formulations to estimate the rate of overtopping on rubble mound and vertical breakwaters. Later, there was carried out the contrast of the above mentioned formulations by the results obtained in a serie of hydraulic model tests of the Hydraulic Research Laboratory (the Center of Studies of Ports and Coasts of the CEDEX, Madrid, Spain).

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Los factores de transcripción (FTs) son reguladores clave de la expresión génica en todos los organismos. En eucariotas los FTs con frecuencia están representados por miembros funcionalmente redundantes de familias génicas de gran tamaño. La sobreexpresión de FTs puede representar una herramienta para revelar las funciones biológicas de FTs redundantes en plantas; sin embargo, la sobreexpresión constitutiva de FTs con frecuencia conlleva diversos defectos en el desarrollo, impidiendo su caracterización funcional. Sin embargo, aproximaciones de sobreexpresión condicional podrían ayudar a solventar este problema. En el consorcio TRANSPLANTA, en el que participan varios laboratorios del CBGP, hemos generado una colección de líneas transgénicas de Arabidopsis, cada una de las cuales expresa un FT bajo el control de un promotor inducible por ?estradiol. Hasta el momento se han generado 1636 líneas homocigotas independientes que corresponden a 634 FTs diferentes, lo que representa una media de 2,6 líneas por cada FT. Como confirmación de la utilidad de esta herramienta, el tratamiento con ?estradiol de líneas que expresaban condicionalmente FTs provoca alteraciones fenotípicas tales como proliferación de pelos radiculares, senescencia inducida por oscuridad, acumulación de antocianinas y enanismo, y que corroboran fenotipos previamente descritos debidos a la sobreexpresión de dichos FTs. Rastreos realizados posteriormente con otras líneas TRANSPLANTA han permitido la identificación de FTs implicados en diferentes procesos biológicos de plantas, confirmando que la colección es una herramienta valiosa para la caracterización funcional de FTs. Las semillas de las líneas TRANSPLANTA han sido depositadas en el Nottingham Arabidopsis Stock Centre para su distribución posterior.

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Neurological Diseases (ND) are affecting larger segments of aging population every year. Treatment is dependent on expensive accurate and frequent monitoring. It is well known that ND leave correlates in speech and phonation. The present work shows a method to detect alterations in vocal fold tension during phonation. These may appear either as hypertension or as cyclical tremor. Estimations of tremor may be produced by auto-regressive modeling of the vocal fold tension series in sustained phonation. The correlates obtained are a set of cyclicality coefficients, the frequency and the root mean square amplitude of the tremor. Statistical distributions of these correlates obtained from a set of male and female subjects are presented. Results from five study cases of female voice are also given.

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Building integrated photovoltaic (BIPV) systems are a relevant application of photovoltaics. In countries belonging to the International Energy Agency countries, 24% of total installed PV power corresponds to BIPV systems. Electricity losses caused by shadows over the PV generator have a significant impact on the performance of BIPV systems, being the major source of electricity losses. This paper presents a methodology to estimate electricity produced by BIPV systems which incorporates a model for shading losses. The proposed methodology has been validated on a one year study with real data from two similar PV systems placed on the south façade of a building belonging to the Technical University of Madrid. This study has covered all weather conditions: clear, partially overcast and fully overcast sky. Results of this study are shown at different time scales, resulting that the errors committed by the best performing model are below 1% and 3% in annual and daily electricity estimation. The use of models which account for the reduced performance at low irradiance levels also improves the estimation of generated electricity.

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Mixtures of polynomials (MoPs) are a non-parametric density estimation technique especially designed for hybrid Bayesian networks with continuous and discrete variables. Algorithms to learn one- and multi-dimensional (marginal) MoPs from data have recently been proposed. In this paper we introduce two methods for learning MoP approximations of conditional densities from data. Both approaches are based on learning MoP approximations of the joint density and the marginal density of the conditioning variables, but they differ as to how the MoP approximation of the quotient of the two densities is found. We illustrate and study the methods using data sampled from known parametric distributions, and we demonstrate their applicability by learning models based on real neuroscience data. Finally, we compare the performance of the proposed methods with an approach for learning mixtures of truncated basis functions (MoTBFs). The empirical results show that the proposed methods generally yield models that are comparable to or significantly better than those found using the MoTBF-based method.

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The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.