92 resultados para Search image
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Laser diffraction (LD) and static image analysis (SIA) of rectangular particles [United States Pharmacopeia, USP30-NF25, General Chapter <776>, Optical Miroscopy.] have been systematically studied. To rule out sample dispersion and particle orientation as the root cause of differences in size distribution profiles, we immobilize powder samples on a glass plate by means of a dry disperser. For a defined region of the glass plate, we measure the diffraction pattern as induced by the dispersed particles, and the 2D dimensions of the individual particles using LD and optical microscopy, respectively. We demonstrate a correlation between LD and SIA, with the scattering intensity of the individual particles as the dominant factor. In theory, the scattering intensity is related to the square of the projected area of both spherical and rectangular particles. In traditional LD the size distribution profile is dominated by the maximum projected area of the particles (A). The diffraction diameters of a rectangular particle with length L and breadth B as measured by the LD instrument approximately correspond to spheres of diameter ØL and ØB respectively. Differences in the scattering intensity between spherical and rectangular particles suggest that the contribution made to the overall LD volume probability distribution by each rectangular particle is proportional to A2/L and A2/B. Accordingly, for rectangular particles the scattering intensity weighted diffraction diameter (SIWDD) explains an overestimation of their shortest dimension and an underestimation of their longest dimension. This study analyzes various samples of particles whose length ranges from approximately 10 to 1000 μm. The correlation we demonstrate between LD and SIA can be used to improve validation of LD methods based on SIA data for a variety of pharmaceutical powders all with a different rectangular particle size and shape.
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We consider the numerical treatment of the optical flow problem by evaluating the performance of the trust region method versus the line search method. To the best of our knowledge, the trust region method is studied here for the first time for variational optical flow computation. Four different optical flow models are used to test the performance of the proposed algorithm combining linear and nonlinear data terms with quadratic and TV regularization. We show that trust region often performs better than line search; especially in the presence of non-linearity and non-convexity in the model.
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The aim of this article was to study the effect of virtual-reality exposure to situations that are emotionally significant for patients with eating disorders (ED) on the stability of body-image distortion and body-image dissatisfaction. A total of 85 ED patients and 108 non-ED students were randomly exposed to four experimental virtual environments: a kitchen with low-calorie food, a kitchen with high-calorie food, a restaurant with low-calorie food, and a restaurant with high-calorie food. In the interval between the presentation of each situation, body-image distortion and body-image dissatisfaction were assessed. Several 2 x 2 x 2 repeated measures analyses of variance (high-calorie vs. low-calorie food x presence vs. absence of people x ED group vs. control group) showed that ED participants had significantly higher levels of body-image distortion and body dissatisfaction after eating high-calorie food than after eating low-calorie food, while control participants reported a similar body image in all situations. The results suggest that body-image distortion and body-image dissatisfaction show both trait and state features. On the one hand, ED patients show a general predisposition to overestimate their body size and to feel more dissatisfied with their body image than controls. On the other hand, these body-image disturbances fluctuate when participants are exposed to virtual situations that are emotionally relevant for them.
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This paper describes Question Waves, an algorithm that can be applied to social search protocols, such as Asknext or Sixearch. In this model, the queries are propagated through the social network, with faster propagation through more trustable acquaintances. Question Waves uses local information to make decisions and obtain an answer ranking. With Question Waves, the answers that arrive first are the most likely to be relevant, and we computed the correlation of answer relevance with the order of arrival to demonstrate this result. We obtained correlations equivalent to the heuristics that use global knowledge, such as profile similarity among users or the expertise value of an agent. Because Question Waves is compatible with the social search protocol Asknext, it is possible to stop a search when enough relevant answers have been found; additionally, stopping the search early only introduces a minimal risk of not obtaining the best possible answer. Furthermore, Question Waves does not require a re-ranking algorithm because the results arrive sorted
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The tourism image is an element that conditions the competitiveness of tourism destinations by making them stand out in the minds of tourists. In this context, marketers of tourism destinations endeavour to create an induced image based on their identity and distinctive characteristics.A number of authors have also recognized the complexity of tourism destinations and the need for coordination and cooperation among all tourism agents, in order to supply a satisfactory tourist product and be competitive in the tourism market. Therefore, tourism agents at the destination need to develop and integrate strategic marketing plans.The aim of this paper is to determine how cities of similar cultures use their resources with the purpose of developing a distinctive induced tourism image to attract tourists and the extent of coordination and cooperation among the various tourism agents of a destination in the process of induced image creation.In order to accomplish these aims, a comparative analysis of the induced image of two cultural cities is presented, Girona (Spain) and Perpignan (France). The induced image is assessed through the content analysis of promotional brochures and the extent of cooperation with in-depth interviews of the main tourism agents of these destinations.Despite the similarities of both cities in terms of tourism resources, results show the use of different attributes to configure the induced image of each destination, as well as a different configuration of the network of tourism agents that participate in the process of induced image creation
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Open educational resources (OER) promise increased access, participation, quality, and relevance, in addition to cost reduction. These seemingly fantastic promises are based on the supposition that educators and learners will discover existing resources, improve them, and share the results, resulting in a virtuous cycle of improvement and re-use. By anecdotal metrics, existing web scale search is not working for OER. This situation impairs the cycle underlying the promise of OER, endangering long term growth and sustainability. While the scope of the problem is vast, targeted improvements in areas of curation, indexing, and data exchange can improve the situation, and create opportunities for further scale. I explore the way the system is currently inadequate, discuss areas for targeted improvement, and describe a prototype system built to test these ideas. I conclude with suggestions for further exploration and development.
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Postprint (published version)
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The vast majority of users don’t seek results beyond the second page offered by the search engine, so if a site fails to be among the top 20 (second page), it says that this page does not have good SEO and, therefore, is not visible to the user. The overall objective of this project is to conduct a study to discover the factors that determine (or not) the positioning of websites in a search engine.
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An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method
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Why Bernardo Bertolucci, when adapting as a film Alberto Moravia’s novel Il conformista, introduced into its homonymous The Conformist the Platonic image of the cave? The article is to give an answer to this question by analysing Moravia’s work in search of “cave images”, which would justify Bertolucci’s decision.
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[spa] ¿Por qué Bernardo Bertolucci, al adaptar cinematográficamente la novela de Alberto Moravia Il conformista, introdujo en The Conformist la imagen platónica de la caverna? Este artículo preende dar respuesta a esta pregunta mediante el análisis de una parte considerable de la obra de Moravia.
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[cat] Per què Bernardo Bertolucci, en fer l’adaptació cinematogràfica de la novel·la d’Alberto Moravia Il conformista, introduí a The Conformist la imatge platònica de la caverna? Hom pretén donar resposta a aquesta pregunta mitjançant l’anàlisi de bona part de l’obra de Moravia.
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In image processing, segmentation algorithms constitute one of the main focuses of research. In this paper, new image segmentation algorithms based on a hard version of the information bottleneck method are presented. The objective of this method is to extract a compact representation of a variable, considered the input, with minimal loss of mutual information with respect to another variable, considered the output. First, we introduce a split-and-merge algorithm based on the definition of an information channel between a set of regions (input) of the image and the intensity histogram bins (output). From this channel, the maximization of the mutual information gain is used to optimize the image partitioning. Then, the merging process of the regions obtained in the previous phase is carried out by minimizing the loss of mutual information. From the inversion of the above channel, we also present a new histogram clustering algorithm based on the minimization of the mutual information loss, where now the input variable represents the histogram bins and the output is given by the set of regions obtained from the above split-and-merge algorithm. Finally, we introduce two new clustering algorithms which show how the information bottleneck method can be applied to the registration channel obtained when two multimodal images are correctly aligned. Different experiments on 2-D and 3-D images show the behavior of the proposed algorithms
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Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping
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Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.