112 research outputs found

    Fusion de données dans un système multicapteurs pour l'étude du mouvement d'un objet dans une scène réelle

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    Dans ce papier, nous présentons une nouvelle méthode de détermination des paramètres de rotation d'un objet sans connaissance a priori. Cette méthode exploite le fait que l'état d'une onde réfléchie est fonction de l'orientation de la surface observée. Une mise en correspondance spatio-temporelle fondée sur l'étude des histogrammes procure la valeur de l'angle de rotation autour d'un axe quelconque. Des résultats expérimentaux sur scènes réelles sont présentés

    Histogrammes spatiaux couleur optimisés pour l'indexation d'images par le contenu

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    - Dans cet article, nous présentons une méthode qui augmente l'efficacité et la précision des systèmes d'indexation et de recherche d'images couleur par le contenu basés sur les histogrammes spatiaux. Cette technique consiste essentiellement à extraire les informations spatiales de l'image en la divisant en plusieurs sous-images rectangulaires interférées (grille des histogrammes). La méthodologie proposée optimise, via une combinaison linéaire, le découpage horizontal et vertical de l'image pour le calcul des histogrammes spatiaux. Nous augmentons ainsi la performance de la recherche en réduisant en même temps le coût de stockage et le temps de calcul par rapport aux méthodes classiques dont le choix concernant le découpage reste arbitraire

    Étude de la rotation d'objets dans une scène par analyse polarimétrique et radiométrique de fronts d'ondes

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    Dans ce papier, nous présentons une méthode originale de détermination de paramètres de rotation d'objets fondée sur l'analyse de l'état de polarisation des faisceaux réfléchis par la scène étudiée et une mise en correspondance spatio-temporelle par étude des histogrammes. Des résultats sur scènes réelles sont présentés

    Progression of Wave Breaker Types on a Plane Impermeable Slope, Depending on Experimental Design

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    M. V. Moragues was supported by the research group TEP-209 (Junta de Andalucia) and by the following projects: "Protection of coastal urban fronts against global warming-PROTOCOL" (917PTE0538), "Integrated verification of the hydrodynamic and structural behavior of a breakwater and its implications on the investment project-VIVALDI" (BIA2015-65598-P). This work was funded by the projects PCI2019-103565-SUSME and PID2019-107509GB-I00-ROMPEOLAS (SRA (State Research Agency)/10.13039/501100011033). M. A. Losada was partially funded by the emeritus professorship mentoring program of the University of Granada. We would like to thank the three reviewers for providing helpful comments on earlier drafts of the manuscript.The objective of this research was to analyze the progression of breaker types on plane impermeable slopes. This study used dimensional analysis to demonstrate the relative water depth is a key explanatory quantity. The dominant breaker types depend on the incident wave characteristics at the foot of the slope. Accordingly, it is possible to combine values of H, T, and m. The physical experiments of Galvin, recent numerical results, and new experiments, performed on an impermeable 1:10 slope, were used to verify the result. It was thus possible to obtain the progression of breaker types in different sequences of pairs of combined wave H and T values. Once a sequence is defined, the expected progression of breaker types is predictable, and is well approximated by the log-transform of the alternate similarity parameter. Since the classification of breaker types is discontinuous, the data assigned to each type were placed in horizontal lines, based on the value of log(chi). Given that the breaking of a wave train on a slope should be considered a continuous process, the location of some data was corrected to satisfy this assumption. There is thus a functional relationship between the sets of the experimental space and of the breaker types. This research also derives the non-dimensional energy dissipation on the slope, considering the wave-reflected energy flux on the slope. It is proportional to a dimensionless bulk dissipation coefficient which depends on the breaker type and, therefore, on the value of chi at the toe of the slope.Junta de Andalucia 917PTE0538 BIA2015-65598-Pemeritus professorship mentoring program of the University of GranadaPCI2019-103565-SUSMEPID2019-107509GB-I00-ROMPEOLAS10.13039/50110001103

    An upper limit on hypertriton production in collisions of Ar(1.76 AGeV)+KCl

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    A high-statistic data sample of Ar(1.76 AGeV)+KCl events recorded with HADES is used to search for a hypertriton signal. An upper production limit per centrality-triggered event of 1.041.04 x 10310^{-3} on the 3σ3\sigma level is derived. Comparing this value with the number of successfully reconstructed Λ\Lambda hyperons allows to determine an upper limit on the ratio NΛ3H/NΛN_{_{\Lambda}^3H}/N_{\Lambda}, which is confronted with statistical and coalescence-type model calculations

    Optimized parameter search for large datasets of the regularization parameter and feature selection for ridge regression

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    In this paper we propose mathematical optimizations to select the optimal regularization parameter for ridge regression using cross-validation. The resulting algorithm is suited for large datasets and the computational cost does not depend on the size of the training set. We extend this algorithm to forward or backward feature selection in which the optimal regularization parameter is selected for each possible feature set. These feature selection algorithms yield solutions with a sparse weight matrix using a quadratic cost on the norm of the weights. A naive approach to optimizing the ridge regression parameter has a computational complexity of the order with the number of applied regularization parameters, the number of folds in the validation set, the number of input features and the number of data samples in the training set. Our implementation has a computational complexity of the order . This computational cost is smaller than that of regression without regularization for large datasets and is independent of the number of applied regularization parameters and the size of the training set. Combined with a feature selection algorithm the algorithm is of complexity and for forward and backward feature selection respectively, with the number of selected features and the number of removed features. This is an order faster than and for the naive implementation, with for large datasets. To show the performance and reduction in computational cost, we apply this technique to train recurrent neural networks using the reservoir computing approach, windowed ridge regression, least-squares support vector machines (LS-SVMs) in primal space using the fixed-size LS-SVM approximation and extreme learning machines

    A school-based intervention program in promoting leisure-time physical activity: Trial protocol

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    Background: Regular participation in moderate-to-vigorous physical activity (MVPA) is important to manage obesity. Physical education (PE) is considered to play an important role in promoting lifelong participation in physical activity (PA) because it provides an existing network where cost-effective interventions can be implemented to produce sustainable change in health behavior. However, the association between compulsory school PA (e.g., PE lessons) and body composition levels has received mixed support in the literature. Therefore, the present study aimed to investigate whether a school-based intervention targeting salient PA benefits and barriers grounded on the theory of planned behavior would promote young people's participation in MVPA during leisure time and reduce body mass index (BMI) of overweight students. Methods/design: A total of 171 students from 3 secondary schools in Singapore underwent the control condition followed by the intervention condition. Both the conditions consisted of PE lessons twice per week over 4 weeks. In the control condition, PE teachers encouraged students to participate in PA during leisure time without providing persuasive message. While in the intervention condition, PE teachers delivered persuasive messages that targeted the salient benefits and barriers associated with PA to the students at the last 5 to 10 min of each PE lesson. PA levels over a week were measured objectively with wrist-mounted GENEActiv Original accelerometers and subjectively with self-reporting questionnaires three times (Baseline, Post 1, and Post 2) in each condition. Student's self-reported PA level was measured using the Leisure-Time Physical Activity Participation Questionnaire and the International Physical Activity Questionnaire, and their attitudes, intentions, subjective norms and perceived behavior control towards leisure-time PA were measured with a questionnaire based on the theory of planned behavior. Furthermore, students' intention, determination and willingness to engage in leisure-time PA were compared with the other activity (e.g., doing homework, shopping). Discussion: This study will provide the evidence on the effectiveness of a cost-effective school-based intervention on reducing BMI of overweight students through promoting sustained participation in leisure-time PA. It will also address methodological issues on the gaps between objective and subjective measures of PA. Trial registration: This trial is registered with the ISRCTN registry (ISRCTN73786157, 26/10/2017, retrospectively registered)

    Dynamics of Seed-Borne Rice Endophytes on Early Plant Growth Stages

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    Bacterial endophytes are ubiquitous to virtually all terrestrial plants. With the increasing appreciation of studies that unravel the mutualistic interactions between plant and microbes, we increasingly value the beneficial functions of endophytes that improve plant growth and development. However, still little is known on the source of established endophytes as well as on how plants select specific microbial communities to establish associations. Here, we used cultivation-dependent and -independent approaches to assess the endophytic bacterrial community of surface-sterilized rice seeds, encompassing two consecutive rice generations. We isolated members of nine bacterial genera. In particular, organisms affiliated with Stenotrophomonas maltophilia and Ochrobactrum spp. were isolated from both seed generations. PCR-based denaturing gradient gel electrophoresis (PCR-DGGE) of seed-extracted DNA revealed that approximately 45% of the bacterial community from the first seed generation was found in the second generation as well. In addition, we set up a greenhouse experiment to investigate abiotic and biotic factors influencing the endophytic bacterial community structure. PCR-DGGE profiles performed with DNA extracted from different plant parts showed that soil type is a major effector of the bacterial endophytes. Rice plants cultivated in neutral-pH soil favoured the growth of seed-borne Pseudomonas oryzihabitans and Rhizobium radiobacter, whereas Enterobacter-like and Dyella ginsengisoli were dominant in plants cultivated in low-pH soil. The seed-borne Stenotrophomonas maltophilia was the only conspicuous bacterial endophyte found in plants cultivated in both soils. Several members of the endophytic community originating from seeds were observed in the rhizosphere and surrounding soils. Their impact on the soil community is further discussed
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