909 resultados para estimador Kernel


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Este PFM se enmarca dentro del trabajo a realizar por el proyecto IRATI. IRATI es un proyecto STReP (Specific Targeted Research Project) financiado por la Unión Europea dentro del programa FP7 (Seventh Framework Programme for Research and Technological Development). El objetivo general de IRATI es conseguir una mayor compresión y exploración de RINA. El trabajo que se reportará en este PFM es (aproximadamente) la primera fase del diseño y desarrollo de un prototipo de RINA sobre Ethernet en el seno del Kernel (Linux), basándose y generando software libre.

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O objetivo deste trabalho foi desenvolver metodologia que integre sensoriamento remoto e sistema de informações geográficas (SIG) para criar um painel amostral e alocar segmentos regulares por meio de um sistema de amostragem aleatória estratificada. Diferentes estratos foram obtidos por meio da classificação de imagens de satélite. Em cada estrato foi realizado sorteio para a seleção dos segmentos amostrais, os quais foram visitados para delimitar as diversas culturas e estimar a área. Na estimativa da área plantada por cultura, para toda a região, utilizou-se o estimador por expansão direta por meio de um procedimento semi-automático. A metodologia reduziu tanto a subjetividade do percentual da área agrícola estimada no estrato, quanto o tempo de construção do painel amostral.

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The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

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This letter presents advanced classification methods for very high resolution images. Efficient multisource information, both spectral and spatial, is exploited through the use of composite kernels in support vector machines. Weighted summations of kernels accounting for separate sources of spectral and spatial information are analyzed and compared to classical approaches such as pure spectral classification or stacked approaches using all the features in a single vector. Model selection problems are addressed, as well as the importance of the different kernels in the weighted summation.

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On the domain of general assignment games (with possible reservation prices) the core is axiomatized as the unique solution satisfying two consistency principles: projection consistency and derived consistency. Also, an axiomatic characterization of the nucleolus is given as the unique solution that satisfies derived consistency and equal maximum complaint between groups. As a consequence, we obtain a geometric characterization of the nucleolus. Maschler et al. (1979) provide a geometrical characterization for the intersection of the kernel and the core of a coalitional game, showing that those allocations that lie in both sets are always the midpoint of certain bargaining range between each pair of players. In the case of the assignment game, this means that the kernel can be determined as those core allocations where the maximum amount, that can be transferred without getting outside the core, from one agent to his / her optimally matched partner equals the maximum amount that he / she can receive from this partner, also remaining inside the core. We now prove that the nucleolus of the assignment game can be characterized by requiring this bisection property be satisfied not only for optimally matched pairs but also for optimally matched coalitions. Key words: cooperative games, assignment game, core, nucleolus

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In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

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Yhteisön langaton palvelualusta on konsepti langattomien yhteisöllisten verkkopalveluiden tarjoamiseen.Konsepti perustuu langattomaan WLAN-reititinlaitteeseen sekä Linux-käyttöjärjestelmäpohjaiseen laiteohjelmistoon, joiden avulla voidaan tarjota paikallisia, erilaisten pienten yhteisöjen käyttöön tarkoitettuja langattomia verkkopalveluita.Soveltuvia käyttökohteita voivat olla esimerkiksi asuntoyhteisöjen välinen tiedotuskanava tai perheen sisäinen viihdekeskus, jonka kautta voidaan tarjota yhteisön toimintaa helpottavia ja tavoitteita edistäviä palveluita. Yhteisön langattomat palvelut perustuvat vapaisiin ohjelmistoihin, jotka mahdollistavat monipuolisen palveluvalikoiman luomisen. Langattoman palvelualustan avulla pienten yhteisöjen tarvitsemat langattomat palvelut voidaan luoda helposti, edullisesti ja joustavasti, ilman kaupallisten palveluoperaattoreiden asettamia rajoituksia.

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Diplomityön tarkoituksena oli luoda menetelmä Symbian-käyttöjärjestelmää käyttävien älypuhelinten suorituskyvyn määrittämiseen, jotta laitteiden välisiä eroja voitaisiin mitata. Aluksi Symbian-käyttöjärjestelmää ja älypuhelinlaitteistoja tutkittiin suorituskykyyn ja sen vaihteluun vaikuttavien tekijöiden ja osien löytämiseksi. Tämän jälkeen kehitettiin useita testitapauksia sisältävä testikirjasto, jolla voitiin mitata joidenkin suorituskykyyn vaikuttavien käyttöjärjestelmän rajapintojen suoritusaikoja. Testikirjaston testit ajettiin kolmella eri älypuhelinmallilla, jotta testien toimivuutta voitiin arvioida. Lopuksi testituloksia analysoitiin mahdollisten pullonkaulojen havaitsemiseksi suorituskyvystä. Testikirjaston pystyttiin havaitsemaan eroja laitteiden suorituskyvyssä. Viimeisin, uudella Symbianin EKA2-ytimellä varustettu älypuhelin, Nokia E70, jäi mittauksissa viimeiseksi, koska se pärjäsi huonosti muistinvarauksia ja TRAP-poikkeuksia testaavissa tapauksissa. Muilla mitatuilla osa-alueilla se kuitenkin päihitti selvästi muut testatut puhelimet, Nokia N90:n ja Nokia 6630:n. Näiden kahden muun laitteen tulosten skaalan tasaisuus osoittaa, että kehitetyn testikirjaston avulla saadaan johdonmukaisia ja uskottavia mittaustuloksia.

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This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

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We propose robust estimators of the generalized log-gamma distribution and, more generally, of location-shape-scale families of distributions. A (weighted) Q tau estimator minimizes a tau scale of the differences between empirical and theoretical quantiles. It is n(1/2) consistent; unfortunately, it is not asymptotically normal and, therefore, inconvenient for inference. However, it is a convenient starting point for a one-step weighted likelihood estimator, where the weights are based on a disparity measure between the model density and a kernel density estimate. The one-step weighted likelihood estimator is asymptotically normal and fully efficient under the model. It is also highly robust under outlier contamination. Supplementary materials are available online.

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El present treball es centra en la fusta en roll per a ús estructural de savina turífera (Juniperus thurifera L.) de Castella i Lleó. En ell s'ha caracteritzat mecànicament aquest material, determinant la resistència a flexió, el mòdul d'elasticitat i la densitat. En funció d'aquests tres paràmetres s'ha assignat una classe resistent al material. S'han avaluat diferents classificacions visuals per agrupar la població en subgrups en funció de les seves singularitats visuals, caracteritzant mecànicament cada un d'aquests subgrups. Així mateix s'ha avaluat el mètode de freqüència de ressonància com a estimador dels paràmetres mecànics. Aquesta metodologia està basada en la lectura de la freqüència sonora del material, a partir d'aquesta freqüència s'han proposat models per a estimar el mòdul d'elasticitat i la resistència a flexió del roll de savina.

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The relationship between yield, carbon isotope discrimination and ash content in mature kernels was examined for a set of 13 barley (Hordeum vulgare) cultivars. Plants were grown under rainfed and well-irrigated conditions in a Mediterranean area. Water deficit caused a decrease in both grain yield and carbon isotope discrimination (Δ). The yield was positively related to Δ and negatively related to ash content, across genotypes within each treatment. However, whereas the correlation between yield and Δ was higher for the set of genotypes under well-irrigated (r=0.70, P<0.01) than under rainfed (r=0.42) conditions, the opposite occurred when yield and ash content were related, ie r=-0.38 under well-irrigated and r=-0.73, (P<0.01) under rainfed conditions. Carbon isotope discrimination and ash content together account for almost 60% of the variation in yield, in both conditions. There was no significant relationship (r=-0.15) between carbon isotope discrimination and ash content in well-irrigated plants, whereas in rainfed plants, this relationship, although significant (r=-0.54, P< 0.05), was weakly negative. The concentration of several mineral elements was measured in the same kernels. The mineral that correlated best with ash content, yield and A, was K. For yield and Δ, although the relationship with K followed the same pattern as the relationhip with ash content, the correlation coefficients were lower. Thus, mineral accumulation in mature kernels seems to be independent of transpiration efficiency. In fact, filling of grains takes place through the phloem pathway. The ash content in kernels is proposed as a complementary criterion, in addition to kernel Δ, to assess genotype differences in barley grain yield under rainfed conditions.

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The kernel of the cutia nut (castanha-de-cutia, Couepia edulis (Prance) Prance) of the western Amazon, which is consumed by the local population, has traditionally been extracted from the nut with a machete, a dangerous procedure that only produces kernels cut in half. A shelling off machine prototype, which produces whole kernels without serious risks to its operator, is described and tested. The machine makes a circular cut in the central part of the fruit shell, perpendicular to its main axis. Three ways of conditioning the fruits before cutting were compared: (1) control; (2) oven drying immediately prior to cutting; (3) oven drying, followed by a 24-hour interval before cutting. The time needed to extract and separate the kernel from the endocarp and testa was measured. Treatment 3 produced the highest output: 63 kernels per hour, the highest percentage of whole kernels (90%), and the best kernel taste. Kernel extraction with treatment 3 required 50% less time than treatment 1, while treatment 2 needed 38% less time than treatment 1. The proportion of kernels attached to the testa was 93%, 47%, and 8% for treatments 1, 2, and 3, respectively, and was the main reason for extraction time differences.

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In this work, we present an integral scheduling system for non-dedicated clusters, termed CISNE-P, which ensures the performance required by the local applications, while simultaneously allocating cluster resources to parallel jobs. Our approach solves the problem efficiently by using a social contract technique. This kind of technique is based on reserving computational resources, preserving a predetermined response time to local users. CISNE-P is a middleware which includes both a previously developed space-sharing job scheduler and a dynamic coscheduling system, a time sharing scheduling component. The experimentation performed in a Linux cluster shows that these two scheduler components are complementary and a good coordination improves global performance significantly. We also compare two different CISNE-P implementations: one developed inside the kernel, and the other entirely implemented in the user space.

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Given an elliptic curve E and a finite subgroup G, V ́lu’s formulae concern to a separable isogeny IG : E → E ′ with kernel G. In particular, for a point P ∈ E these formulae express the first elementary symmetric polynomial on the abscissas of the points in the set P + G as the difference between the abscissa of IG (P ) and the first elementary symmetric polynomial on the abscissas of the nontrivial points of the kernel G. On the other hand, they express Weierstraß coefficients of E ′ as polynomials in the coefficients of E and two additional parameters: w0 = t and w1 = w. We generalize this by defining parameters wn for all n ≥ 0 and giving analogous formulae for all the elementary symmetric polynomials and the power sums on the abscissas of the points in P +G. Simultaneously, we obtain an efficient way of performing computations concerning the isogeny when G is a rational group.