974 resultados para math computation


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Interpretability and power of genome-wide association studies can be increased by imputing unobserved genotypes, using a reference panel of individuals genotyped at higher marker density. For many markers, genotypes cannot be imputed with complete certainty, and the uncertainty needs to be taken into account when testing for association with a given phenotype. In this paper, we compare currently available methods for testing association between uncertain genotypes and quantitative traits. We show that some previously described methods offer poor control of the false-positive rate (FPR), and that satisfactory performance of these methods is obtained only by using ad hoc filtering rules or by using a harsh transformation of the trait under study. We propose new methods that are based on exact maximum likelihood estimation and use a mixture model to accommodate nonnormal trait distributions when necessary. The new methods adequately control the FPR and also have equal or better power compared to all previously described methods. We provide a fast software implementation of all the methods studied here; our new method requires computation time of less than one computer-day for a typical genome-wide scan, with 2.5 M single nucleotide polymorphisms and 5000 individuals.

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This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed

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In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible to compute highly-realistic images in a reasonable time. We introduce here a speculation-based parallel solution for a global illumination algorithm in the context of radiosity, in which we have taken advantage of the hierarchical nature of such an algorithm

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In this paper, different recovery methods applied at different network layers and time scales are used in order to enhance the network reliability. Each layer deploys its own fault management methods. However, current recovery methods are applied to only a specific layer. New protection schemes, based on the proposed partial disjoint path algorithm, are defined in order to avoid protection duplications in a multi-layer scenario. The new protection schemes also encompass shared segment backup computation and shared risk link group identification. A complete set of experiments proves the efficiency of the proposed methods in relation with previous ones, in terms of resources used to protect the network, the failure recovery time and the request rejection ratio

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This paper focuses on QoS routing with protection in an MPLS network over an optical layer. In this multi-layer scenario each layer deploys its own fault management methods. A partially protected optical layer is proposed and the rest of the network is protected at the MPLS layer. New protection schemes that avoid protection duplications are proposed. Moreover, this paper also introduces a new traffic classification based on the level of reliability. The failure impact is evaluated in terms of recovery time depending on the traffic class. The proposed schemes also include a novel variation of minimum interference routing and shared segment backup computation. A complete set of experiments proves that the proposed schemes are more efficient as compared to the previous ones, in terms of resources used to protect the network, failure impact and the request rejection ratio

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In this paper, robustness of parametric systems is analyzed using a new approach to interval mathematics called Modal Interval Analysis. Modal Intervals are an interval extension that, instead of classic intervals, recovers some of the properties required by a numerical system. Modal Interval Analysis not only simplifies the computation of interval functions but allows semantic interpretation of their results. Necessary, sufficient and, in some cases, necessary and sufficient conditions for robust performance are presented

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One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram

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This is one of the few studies that have explored the value of baseline symptoms and health-related quality of life (HRQOL) in predicting survival in brain cancer patients. Baseline HRQOL scores (from the EORTC QLQ-C30 and the Brain Cancer Module (BN 20)) were examined in 490 newly diagnosed glioblastoma cancer patients for the relationship with overall survival by using Cox proportional hazards regression models. Refined techniques as the bootstrap re-sampling procedure and the computation of C-indexes and R(2)-coefficients were used to try and validate the model. Classical analysis controlled for major clinical prognostic factors selected cognitive functioning (P=0.0001), global health status (P=0.0055) and social functioning (P<0.0001) as statistically significant prognostic factors of survival. However, several issues question the validity of these findings. C-indexes and R(2)-coefficients, which are measures of the predictive ability of the models, did not exhibit major improvements when adding selected or all HRQOL scores to clinical factors. While classical techniques lead to positive results, more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival. These results may have implications for future use of HRQOL as a prognostic factor in cancer patients.

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La finalitat d'aquest projecte és la realització d'un estudi comparatiu de l'algoritme basat en una colònia artificial d'abelles, Artificial Bee Colony (ABC), comparat amb un conjunt d'algoritmes fonamentats en el paradigma de la computació evolutiva. S'utilitzarà l'eficàcia a l'hora d'optimitzar diverses funcions com a mesura comparativa. Els algoritmes amb els quals es comparara l'algoritme ABC són: algoritmes genètics, evolució diferencial i optimització amb eixam de partícules.

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Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.

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Combining measurements of the monoamine metabolites in the cerebrospinal fluid (CSF) and neuroimaging can increase efficiency of drug discovery for treatment of brain disorders. To address this question, we examined five drug-naïve patients suffering from schizophrenic disorder. Patients were assessed clinically, using the Positive and Negative Syndrome Scale (PANSS): at baseline and then at weekly intervals. Plasma and CSF levels of quetiapine and norquetiapine as well CSF 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), 5-hydroxyindole-acetic acid (5-HIAA) and 3-methoxy-4-hydroxyphenylglycol (MHPG) were obtained at baseline and again after at least a 4 week medication trail with 600 mg/day quetiapine. CSF monoamine metabolites levels were compared with dopamine D(2) receptor occupancy (DA-D(2)) using [(18)F]fallypride and positron emission tomography (PET). Quetiapine produced preferential occupancy of parietal cortex vs. putamenal DA-D(2), 41.4% (p<0.05, corrected for multiple comparisons). DA-D(2) receptor occupancies in the occipital and parietal cortex were correlated with CSF quetiapine and norquetiapine levels (p<0.01 and p<0.05, respectively). CSF monoamine metabolites were significantly increased after treatment and correlated with regional receptor occupancies in the putamen [DOPAC: (p<0.01) and HVA: (p<0.05)], caudate nucleus [HVA: (p<0.01)], thalamus [MHPG: (p<0.05)] and in the temporal cortex [HVA: (p<0.05) and 5-HIAA: (p<0.05)]. This suggests that CSF monoamine metabolites levels reflect the effects of quetiapine treatment on neurotransmitters in vivo and indicates that monitoring plasma and CSF quetiapine and norquetiapine levels may be of clinical relevance.

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TABLE DES MATIERES - Préface - Avant-propos - Architecture des réseaux neuronaux - Développement des réseaux neuronaux du système nerveux central - Microcircuits, plasticité et computation - Réseaux neuronaux en fonctionnement - Vulnérabilité des réseaux neuronaux biologiques et artificiels - Conclusion générale - Glossaire - Bibliographie - Index des notions - Index des noms

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Partint de les definicions usuals de Mesures de Semblança Quàntica (MSQ), es considera la dependència d'aquestes mesures respecte de la superposició molecular. Pel cas particular en qnè els sistemes comparats siguin una molècula i un Àtom i que les mesures es calculin amb l'aproximació EASA, les MSQ esdevenen funcions de les tres coordenades de l'espai. Mantenint fixa una de les tres coordenades, es pot representar fàcilment la variació del valor de semblança en un pla determinat, i obtenir els anomenats mapes de semblança. En aquest article, es comparen els mapes de semblança obtinguts amb diferents MSQ per a sistemes senzills