881 resultados para Of the image Lula


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The main contribution of this project is the study of collections of valuable documents related to the image of India in Bulgaria. Digital repositories of selected samples are constructed using modern information technologies. The results are presented in a virtual exhibition ‘The Image of India in Bulgaria: from the late 19th to the late 20th century’.

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How are the image statistics of global image contrast computed? We answered this by using a contrast-matching task for checkerboard configurations of ‘battenberg’ micro-patterns where the contrasts and spatial spreads of interdigitated pairs of micro-patterns were adjusted independently. Test stimuli were 20 × 20 arrays with various sized cluster widths, matched to standard patterns of uniform contrast. When one of the test patterns contained a pattern with much higher contrast than the other, that determined global pattern contrast, as in a max() operation. Crucially, however, the full matching functions had a curious intermediate region where low contrast additions for one pattern to intermediate contrasts of the other caused a paradoxical reduction in perceived global contrast. None of the following models predicted this: RMS, energy, linear sum, max, Legge and Foley. However, a gain control model incorporating wide-field integration and suppression of nonlinear contrast responses predicted the results with no free parameters. This model was derived from experiments on summation of contrast at threshold, and masking and summation effects in dipper functions. Those experiments were also inconsistent with the failed models above. Thus, we conclude that our contrast gain control model (Meese & Summers, 2007) describes a fundamental operation in human contrast vision.

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Social issues are assessed from different perspectives. The purpose here is to evaluate one short article in terms of interpretive social theory and then briefly assess it in terms of functionalism, conflic theory and critical theory.

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Aerial observations of light pollution can fill an important gap between ground based surveys and nighttime satellite data. Terrestrially bound surveys are labor intensive and are generally limited to a small spatial extent, and while existing satellite data cover the whole world, they are limited to coarse resolution. This paper describes the production of a high resolution (1 m) mosaic image of the city of Berlin, Germany at night. The dataset is spatially analyzed to identify themajor sources of light pollution in the city based on urban land use data. An area-independent 'brightness factor' is introduced that allows direct comparison of the light emission from differently sized land use classes, and the percentage area with values above average brightness is calculated for each class. Using this methodology, lighting associated with streets has been found to be the dominant source of zenith directed light pollution (31.6%), although other land use classes have much higher average brightness. These results are compared with other urban light pollution quantification studies. The minimum resolution required for an analysis of this type is found to be near 10 m. Future applications of high resolution datasets such as this one could include: studies of the efficacy of light pollution mitigation measures, improved light pollution simulations, economic and energy use, the relationship between artificial light and ecological parameters (e.g. circadian rhythm, fitness, mate selection, species distributions, migration barriers and seasonal behavior), or the management of nightscapes. To encourage further scientific inquiry, the mosaic data is freely available at Pangaea.

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The aim of art, as transformer of the individual, has numerous sides which give the human beings a sense of enhancement and growth. It is considered by university the need for our students to take part of this process of social transformation in which they feel the need of helping the community when its members are at risk of social exclusion. Art is considered to be a means, a tool and a purpose for an artis-pedagogue to be used as a guide for the renewal. And the university is also considered as a focus of commitment by means of the development of good practices as well as adopting an open and innovative attitude to any changes aimed at living harmoniously within a more just society.

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With the rise of smart phones, lifelogging devices (e.g. Google Glass) and popularity of image sharing websites (e.g. Flickr), users are capturing and sharing every aspect of their life online producing a wealth of visual content. Of these uploaded images, the majority are poorly annotated or exist in complete semantic isolation making the process of building retrieval systems difficult as one must firstly understand the meaning of an image in order to retrieve it. To alleviate this problem, many image sharing websites offer manual annotation tools which allow the user to “tag” their photos, however, these techniques are laborious and as a result have been poorly adopted; Sigurbjörnsson and van Zwol (2008) showed that 64% of images uploaded to Flickr are annotated with < 4 tags. Due to this, an entire body of research has focused on the automatic annotation of images (Hanbury, 2008; Smeulders et al., 2000; Zhang et al., 2012a) where one attempts to bridge the semantic gap between an image’s appearance and meaning e.g. the objects present. Despite two decades of research the semantic gap still largely exists and as a result automatic annotation models often offer unsatisfactory performance for industrial implementation. Further, these techniques can only annotate what they see, thus ignoring the “bigger picture” surrounding an image (e.g. its location, the event, the people present etc). Much work has therefore focused on building photo tag recommendation (PTR) methods which aid the user in the annotation process by suggesting tags related to those already present. These works have mainly focused on computing relationships between tags based on historical images e.g. that NY and timessquare co-exist in many images and are therefore highly correlated. However, tags are inherently noisy, sparse and ill-defined often resulting in poor PTR accuracy e.g. does NY refer to New York or New Year? This thesis proposes the exploitation of an image’s context which, unlike textual evidences, is always present, in order to alleviate this ambiguity in the tag recommendation process. Specifically we exploit the “what, who, where, when and how” of the image capture process in order to complement textual evidences in various photo tag recommendation and retrieval scenarios. In part II, we combine text, content-based (e.g. # of faces present) and contextual (e.g. day-of-the-week taken) signals for tag recommendation purposes, achieving up to a 75% improvement to precision@5 in comparison to a text-only TF-IDF baseline. We then consider external knowledge sources (i.e. Wikipedia & Twitter) as an alternative to (slower moving) Flickr in order to build recommendation models on, showing that similar accuracy could be achieved on these faster moving, yet entirely textual, datasets. In part II, we also highlight the merits of diversifying tag recommendation lists before discussing at length various problems with existing automatic image annotation and photo tag recommendation evaluation collections. In part III, we propose three new image retrieval scenarios, namely “visual event summarisation”, “image popularity prediction” and “lifelog summarisation”. In the first scenario, we attempt to produce a rank of relevant and diverse images for various news events by (i) removing irrelevant images such memes and visual duplicates (ii) before semantically clustering images based on the tweets in which they were originally posted. Using this approach, we were able to achieve over 50% precision for images in the top 5 ranks. In the second retrieval scenario, we show that by combining contextual and content-based features from images, we are able to predict if it will become “popular” (or not) with 74% accuracy, using an SVM classifier. Finally, in chapter 9 we employ blur detection and perceptual-hash clustering in order to remove noisy images from lifelogs, before combining visual and geo-temporal signals in order to capture a user’s “key moments” within their day. We believe that the results of this thesis show an important step towards building effective image retrieval models when there lacks sufficient textual content (i.e. a cold start).

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This document describes each step of the research conducted to understand the factors that may be influencing the low enrollment of freshmen who have experienced the “Escuela de Bibliotecologia, Documentacion e Informacion de la Universidad Nacional” in recent years. It also raises a didactic - multimedia, in response to identified needs, to help improve the problems encountered by making use of technological tools with an educational foundation that fosters reflection of the population to be targeted by the product. Finally, it presents the conclusions and recommendations drawn from the research.

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The purpose of this investigation was to evaluate body image dissatisfaction in relation to low self-esteem due to physical appearance in students of the Faculty of Medicine at the University of Los Andes in Mérida, Venezuela.  It was a non-experimental and correlational study.  The sample included 189 students (27% male and 73% female) with an average age of 19.58 ± 1.57 (men: 19.81 years of age ± 1.74 and women: 20.24 years of age ± 1.76).  Participants were intentionally selected from first-year courses of the Medicine, Nursing and Nutrition programs.  The Body Shape Questionnaire (BSQ) (Cooper and Taylor, 1987) was the instrument used to measure body image dissatisfaction and Graffar’s modified method (Méndez and De Méndez, 1994) was applied to determine the participants’ socioeconomic status.  A descriptive analysis (frequency, percentages, mean) and an inferential analysis (one-way ANOVA) were applied to the data using SPSS (Statistical Package for Social Sciences) version 9.0.  One of the most important findings in this study was the determination of a statistically significant relationship between dissatisfaction and body image and between low self-esteem and gender χ2 (2, N= 189) = 9.686, p=0.008.  Using ANOVA also helped determine that differences in the mean for dissatisfaction and low self-esteem levels with body image and gender are statistically significant, F= 11.236; p=0.008, F=10.23; p=0.002, respectively.  Conclusions: results obtained suggest a relationship between dissatisfaction and low self-esteem due to physical appearance. Consequently, subjects reject their body image because of a distorted or undistorted perception of their physical appearance, which can possibly affect self-esteem.  Moreover, it is observed that the students’ psychological health is more related to their satisfaction with their body-image than to the way their body image is perceived. Consequently, this group of participants must be analyzed regarding their self-esteem due to body image, as an expression in the institutional environment.  It is also important to emphasize that gender may be a risk factor concerning eating disorders.  We believe the foregoing because women showed higher dissatisfaction levels because of their physical appearance being conditioned by a higher dissatisfaction with their perceived body image, which is characterized by an overestimation of the physical dimension of their body image.

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This flyer promotes the event ""Jose Martí: Resisting Melancholia for the Image of the Cuban Hero", Lecture by Emilio Bejel", cosponsored by the Department of Modern Languages at FIU.

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Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

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Sounds of the Suburb was a commissioned public art proposal based upon a brief set by Queensland Rail for the major redevelopment at their Brunswick Street Railway Station, Fortitude Valley, Brisbane. I proposed a large scale, electronic artwork to be distributed across the glass fronted structure of their station’s new concourse building. It was designed as a network of LED based ‘tracking’ - along which would travel electronically animated, ‘trains’ of text synchronised to the actual train timetables. Each message packet moved endlessly through a complex spatial network of ‘tracks’ and ‘stations’ set both inside, outside and via the concourse. The design was underpinned by large scale image of sound waves etched onto the architecture’s glass and was accompanied by two inset monitors each presenting ghosted images of passenger movements within the concourse, time-delay recorded and then cross-combined in realtime to form new composites.----- Each moving, reprogrammable phrase was conceived as a ‘train of thought’ and ostensibly contained an idea or concept about popular cultures surrounding contemporary music – thereby meeting the brief that the work should speak to the diverse musical cultures central to Fortitude Valley’s image as an entertainment hub. These cultural ‘memes’, gathered from both passengers and the music press were situated alongside quotes from philosophies of networking, speed and digital ecologies. These texts would continually propagate, replicate and cross fertlise as they moved throughout the ‘network’, thereby writing a constantly evolving ‘textual soundcape’ of that place. This idea was further cemented through the pace, scale and rhythm of passenger movements continually recorded and re-presented on the smaller screens.

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The requirement to monitor the rapid pace of environmental change due to global warming and to human development is producing large volumes of data but placing much stress on the capacity of ecologists to store, analyse and visualise that data. To date, much of the data has been provided by low level sensors monitoring soil moisture, dissolved nutrients, light intensity, gas composition and the like. However, a significant part of an ecologist’s work is to obtain information about species diversity, distributions and relationships. This task typically requires the physical presence of an ecologist in the field, listening and watching for species of interest. It is an extremely difficult task to automate because of the higher order difficulties in bandwidth, data management and intelligent analysis if one wishes to emulate the highly trained eyes and ears of an ecologist. This paper is concerned with just one part of the bigger challenge of environmental monitoring – the acquisition and analysis of acoustic recordings of the environment. Our intention is to provide helpful tools to ecologists – tools that apply information technologies and computational technologies to all aspects of the acoustic environment. The on-line system which we are building in conjunction with ecologists offers an integrated approach to recording, data management and analysis. The ecologists we work with have different requirements and therefore we have adopted the toolbox approach, that is, we offer a number of different web services that can be concatenated according to need. In particular, one group of ecologists is concerned with identifying the presence or absence of species and their distributions in time and space. Another group, motivated by legislative requirements for measuring habitat condition, are interested in summary indices of environmental health. In both case, the key issues are scalability and automation.

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Introduction: Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (Nmm−1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived froma single 2D radiographic image. Methods: 18 excised human femora had previously been quantitative computed tomography scanned, from which 2D BMD-equivalent radiographic images were derived, and mechanically tested to failure in a stance-loading configuration. A 3D proximal femur shape was generated from each 2D radiographic image and used to construct 3D-FEA models. Results: The coefficient of determination (R2%) to predict failure load was 54.5% for BMD and 80.4% for 3D-FEXI. Conclusions: This ex vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD. This approach may be readily extended to routine clinical BMD images derived by dual energy X-ray absorptiometry. Crown Copyright © 2009 Published by Elsevier Ltd on behalf of IPEM. All rights reserved