944 resultados para fractal segmentation


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The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

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The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

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Defining the limits of an urban agglomeration is essential both for fundamental and applied studies in quantitative and theoretical geography. A simple and consistent way for defining such urban clusters is important for performing different statistical analysis and comparisons. Traditionally, agglomerations are defined using a rather qualitative approach based on various statistical measures. This definition varies generally from one country to another, and the data taken into account are different. In this paper, we explore the use of the City Clustering Algorithm (CCA) for the agglomeration definition in Switzerland. This algorithm provides a systemic and easy way to define an urban area based only on population data. The CCA allows the specification of the spatial resolution for defining the urban clusters. The results from different resolutions are compared and analysed, and the effect of filtering the data investigated. Different scales and parameters allow highlighting different phenomena. The study of Zipf's law using the visual rank-size rule shows that it is valid only for some specific urban clusters, inside a narrow range of the spatial resolution of the CCA. The scale where emergence of one main cluster occurs can also be found in the analysis using Zipf's law. The study of the urban clusters at different scales using the lacunarity measure - a complementary measure to the fractal dimension - allows to highlight the change of scale at a given range.

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Melodic motifs form essential building blocks in Indian Classical music. The motifs, or key phrases, providestrong cues to the identity of the underlying raga in both Hindustani and Carnatic styles of Indian music. Automatic identification and clustering of similar motifs is relevant in this context. The inherent variations in various instances of a characteristic phrase in a bandish (composition)performance make it challenging to identify similar phrases in a performance. A nyas svara (long note)marks the ending of these phrases. The proposed method does segmentation of phrases through identification ofnyas and computes similarity with the reference characteristic phrase.

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Spondylocarpotarsal synostosis syndrome (SCT) (OMIM 272460), originally thought to be a failure of normal spine segmentation, is characterized by progressive fusion of vertebras and associates unsegmented bars, scoliosis, short stature, carpal and tarsal synostosis. Cleft palate, sensorineural or mixed hearing loss, joint limitation, clinodactyly, and dental enamel hypoplasia are variable manifestations. Twenty-five patients have been reported. Thirteen affected individuals were siblings from six families and four of these families were consanguineous. In four of those families, Krakow et al. [Krakow et al. (2004) Nat Genet 36:405-410] found homozygosity or compound heterozygosity for mutations in the gene encoding FLNB. This confirmed autosomal recessive inheritance of the disorder. We report on two new patients (a mother and her son) representing the first case of autosomal dominant inheritance. These patients met the clinical and radiological criteria for SCT and did not present any features which could exclude this diagnosis. Molecular analysis failed to identify mutations in NOG and FLNB. SCT is therefore, genetically heterogeneous. Both dominant and autosomal recessive forms of inheritance should be considered during genetic counseling.

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Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise, e.g., Fundus photography, optical coherence tomography, computed tomography, and magnetic resonance imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The goal of this paper is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI that was not visible before like vessels and the macula. This paper contributions include automatic detection of the optic disc, the fovea, the optic axis, and an automatic segmentation of the vitreous humor of the eye.

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OBJECTIVE: To investigate potential abnormalities in subcortical brain structures in conversion disorder (CD) compared with controls using a region of interest (ROI) approach. METHODS: Fourteen patients with motor CD were compared with 31 healthy controls using high-resolution MRI scans with an ROI approach focusing on the basal ganglia, thalamus and amygdala. Brain volumes were measured using Freesurfer, a validated segmentation algorithm. RESULTS: Significantly smaller left thalamic volumes were found in patients compared with controls when corrected for intracranial volume. These reductions did not vary with handedness, laterality, duration or severity of symptoms. CONCLUSIONS: These differences may reflect a primary disease process in this area or be secondary effects of the disorder, for example, resulting from limb disuse. Larger, longitudinal structural imaging studies will be required to confirm the findings and explore whether they are primary or secondary to CD.

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Dyssegmental dysplasia, Silverman-Handmaker type (DDSH; #MIM 224410) is an autosomal recessive form of lethal dwarfism characterized by a defect in segmentation and fusion of vertebral bodies components ("anisospondyly") and by severe limb shortening. It is caused by mutations in the perlecan gene (HSPG2), but so far, only three molecularly confirmed cases have been reported. We report a novel case of DDSH in a fetus that presented at 15 weeks gestation with encephalocele, severe micromelic dwarfism and narrow thorax. After termination of pregnancy, radiographs showed short ribs, short and bent long bones and anisospondyly of two vertebral bodies. The fetus was homozygous for a previously undescribed null mutation in HSPG2.

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This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

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La segmentació de persones es molt difícil a causa de la variabilitat de les diferents condicions, com la postura que aquestes adoptin, color del fons, etc. Per realitzar aquesta segmentació existeixen diferents tècniques, que a partir d'una imatge ens retornen un etiquetat indicant els diferents objectes presents a la imatge. El propòsit d'aquest projecte és realitzar una comparativa de les tècniques recents que permeten fer segmentació multietiqueta i que son semiautomàtiques, en termes de segmentació de persones. A partir d'un etiquetatge inicial idèntic per a tots els mètodes utilitzats, s'ha realitzat una anàlisi d'aquests, avaluant els seus resultats sobre unes dades publiques, analitzant 2 punts: el nivell de interacció i l'eficiència.

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This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

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In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.

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Résumé : Crise économique et travail féminin : retour à l'ordre. L'offensive contre le travail des femmes dans les services publics en Suisse et en France durant les années 1930 La crise économique mondiale des années 1930 se caractérise par une véritable offensive contre l'activité professionnelle féminine dans les services publics. Dans l'ensemble des pays industrialisés, le travail des femmes fonctionnaires acquiert le statut d'enjeu économique, politique, social, familial et moral. La généralisation du chômage sous l'effet de la crise économique suscite d'âpres discussions sur la répartition des postes de travail et les femmes fonctionnaires endossent le rôle de bouc émissaire. Les gouvernements et autorités publiques des pays industrialisés plébiscitent dès lors, selon des modalités diverses, la « solution » d'une réglementation restrictive du travail des salariées des services publics. Cette thèse met en lumière un épisode de l'histoire de la « ségrégation ordinaire » entre les sexes dans le monde du travail. Elle montre que la segmentation et la hiérarchisation sexuées du travail ne reflètent pas des faits « naturels », mais qu'elles constituent l'aboutissement d'un long processus de différenciation engageant une multitude d'acteurs·trices sociaux·ales. Nous avons opté pour une histoire croisée de l'offensive contre l'activité des salariées de la fonction publique en Suisse et en France, en y intégrant un « détour » par l'analyse de la dimension internationale de cette campagne contre l'emploi féminin. Cette approche permet de revisiter l'histoire politique, sociale, culturelle, économique et financière propre à la Suisse et à la France des années 1930. La sexuation de l'histoire, soit la prise en compte des rapports entre les sexes dans et par le récit historique, l'éclairage novateur de l'histoire d'une nation sur l'autre, ainsi que la prise en considération de l'internationalisation de certaines pratiques (législatives et féministes), permettent de renouveler un cadre d'analyse et de proposer de nouvelles pistes de recherche sur l'histoire du travail et des féminismes. En premier lieu, ce travail analyse les modalités de la reconfiguration des rapports entre les sexes durant les années 1930, sous le prisme de l'activité salariée. Il détermine de quelle manière le travail des femmes fonctionnaires se constitue en « problème » à cette période et quels sont les termes de l'offensive contre les salariées des services publics en Suisse et en France, mais également sur le plan international. En deuxième lieu, le coeur de la recherche porte sur les incidences de l'offensive contre les femmes fonctionnaires en Suisse et en France. Nous montrons de quelle manière les gouvernements et les autorités publiques prennent appui sur les impératifs d'austérité budgétaire pour redessiner des lignes de démarcation entre « travail masculin » et « travail féminin » dans certains domaines bien spécifiques des services publics. En troisième lieu, cette contribution propose une lecture de l'histoire de la mobilisation féministe pour défendre le droit au travail des femmes fonctionnaires, mobilisation encore trop souvent occultée par les récits historiques traditionnels. Pour les sources consultées, l'étude de la manière dont le travail des femmes fonctionnaires se constitue en « problème » sur le plan international (partie I) repose sur les archives et les publications du Bureau international du travail. Quant à l'étude des cas nationaux (parties II et III), pour chaque pays, trois types de sources ont été dépouillés : les archives des associations féministes investies dans la défense du droit au travail féminin ; les sources publiées ayant trait à l'offensive contre le travail féminin (rapports, actes de journées d'étude, organes de presse) ; les sources officielles législatives qui entérinent le processus de ségrégation sexuée dans les emplois publics.