982 resultados para Numbered Information Spaces
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Virtual reality (VR) techniques to understand and obtain conclusions of data in an easy way are being used by the scientific community. However, these techniques are not used frequently for analyzing large amounts of data in life sciences, particularly in genomics, due to the high complexity of data (curse of dimensionality). Nevertheless, new approaches that allow to bring out the real important data characteristics, arise the possibility of constructing VR spaces to visually understand the intrinsic nature of data. It is well known the benefits of representing high dimensional data in tridimensional spaces by means of dimensionality reduction and transformation techniques, complemented with a strong component of interaction methods. Thus, a novel framework, designed for helping to visualize and interact with data about diseases, is presented. In this paper, the framework is applied to the Van't Veer breast cancer dataset is used, while oncologists from La Paz Hospital (Madrid) are interacting with the obtained results. That is to say a first attempt to generate a visually tangible model of breast cancer disease in order to support the experience of oncologists is presented.
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Recent advances in non-destructive imaging techniques, such as X-ray computed tomography (CT), make it possible to analyse pore space features from the direct visualisation from soil structures. A quantitative characterisation of the three-dimensional solid-pore architecture is important to understand soil mechanics, as they relate to the control of biological, chemical, and physical processes across scales. This analysis technique therefore offers an opportunity to better interpret soil strata, as new and relevant information can be obtained. In this work, we propose an approach to automatically identify the pore structure of a set of 200-2D images that represent slices of an original 3D CT image of a soil sample, which can be accomplished through non-linear enhancement of the pixel grey levels and an image segmentation based on a PFCM (Possibilistic Fuzzy C-Means) algorithm. Once the solids and pore spaces have been identified, the set of 200-2D images is then used to reconstruct an approximation of the soil sample by projecting only the pore spaces. This reconstruction shows the structure of the soil and its pores, which become more bounded, less bounded, or unbounded with changes in depth. If the soil sample image quality is sufficiently favourable in terms of contrast, noise and sharpness, the pore identification is less complicated, and the PFCM clustering algorithm can be used without additional processing; otherwise, images require pre-processing before using this algorithm. Promising results were obtained with four soil samples, the first of which was used to show the algorithm validity and the additional three were used to demonstrate the robustness of our proposal. The methodology we present here can better detect the solid soil and pore spaces on CT images, enabling the generation of better 2D?3D representations of pore structures from segmented 2D images.
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In the setting of noncooperative game theory, strategic negligibility of individual agents, or diffuseness of information, has been modeled as a nonatomic measure space, typically the unit interval endowed with Lebesgue measure. However, recent work has shown that with uncountable action sets, for example the unit interval, there do not exist pure-strategy Nash equilibria in such nonatomic games. In this brief announcement, we show that there is a perfectly satisfactory existence theory for nonatomic games provided this nonatomicity is formulated on the basis of a particular class of measure spaces, hyperfinite Loeb spaces. We also emphasize other desirable properties of games on hyperfinite Loeb spaces, and present a synthetic treatment, embracing both large games as well as those with incomplete information.
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In the first part of this work, we show how certain techniques from quantum information theory can be used in order to obtain very sharp embeddings between noncommutative Lp-spaces. Then, we use these estimates to study the classical capacity with restricted assisted entanglement of the quantum erasure channel and the quantum depolarizing channel. In particular, we exactly compute the capacity of the first one and we show that certain nonmultiplicative results hold for the second one.
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This layer is a georeferenced raster image of the historic paper map entitled: Base map of the District of Columbia showing public and zoning areas, base prepared in the Office of the Surveyor, D.C., by direction of the Engineer Commissioner, D.C. It was published by Engineer Commissioner in 1936. Scale [ca. 1:19,200]. Base map "complete to June 13, 1933." The image inside the map neatline is georeferenced to the surface of the earth and fit to the Maryland State Plane Coordinate System Meters NAD83 (Fipszone 1900). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as residential areas, open spaces, commercial and industrial areas, alley dwelling areas, roads, block numbers, railroads and stations, drainage, selected public buildings and points of interest, parks, cemeteries, and more. This layer is part of a selection of digitally scanned and georeferenced historic maps from The Harvard Map Collection as part of the Imaging the Urban Environment project. Maps selected for this project represent major urban areas and cities of the world, at various time periods. These maps typically portray both natural and manmade features at a large scale. The selection represents a range of regions, originators, ground condition dates, scales, and purposes.
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Advertisement for Fred. Lundberg Florist on p. [1] at end.
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[1] Committee on Types of Dwellings.--[2] Committee on Fundamental Equipment.--[3] Committee on Kitchens and Other Work Centers.--[4] Committee on Utilities for Houses.--[5] Committee on Subdivision Layout.--[6] Tentative report of the Committee on Business and Housing.--[7] Committee on Industrial Decentralization and Housing.--[8] Committee on Blighted Areas and Slums.--[9] Committee on Reconditioning, Remodeling and Modernizing.--[10] Committee on Construction.--[11] Committee on Design.--[12] Committee on City Planning and Zoning.--[13] Committee on Finance.--[14] Committee on Taxation.--[15] Committee on Home Ownership and Leasing.--[16] Committee on Home Furnishing and Decoration.--[17] Committee on Landscape Planning and Planting.--[18] Committee on Household Management.[19] Committee on Housing and the Community.--[20] Committee on Farm and Village Housing.--[21] Committee on Negro Housing.--[22] Committee on Home Information Services and Centers.[23] Committee on Homemaking - Housing and Family Life.--[24] Committee on Large-scale Operations.--[25] Committee on Relationship of Income and the Home.
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List of active members in some volumes.
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No. 36/37 & 50, sect. 1-3. Queensboro subway.--No. 39, sect. 2. Broadway - Fourth avenue (New Utrecht avenue) - No. 43, 4/38, see no. 4/38, 43.--No. 48, sect. 1-2. Seventh avenue - Lexington avenue.--No. 50. Queensboro subway (Hunters Point avenue station
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Purpose: The physical environment plays an important role in influencing participation in physical activity, although the specific factors that are correlated with different patterns of walking remain to be determined We examined correlations between physical environmental factors and self-reported walking for recreation and transport near home. Methods: The local neighborhood environments (defined as a 400-m radius from the respondent's home) of 1678 adults were assessed for their suitability for walking. The environmental data were collected during 2000 using the Systematic Pedestrian and Cycling Environmental Scan (SPACES) instrument together with information from other sources. We used logistic regression modeling to examine the relationship between the attributes of the physical environment and the self-reported walking behavior undertaken near home. Results: Functional features were correlated with both walking for recreation (odds ratio (OR) 1.62; 95% confidence interval (Cl): 1.20-2.19) and for transport (OR 1.30; 95% Cl: 0.97-1.73). A well-maintained walking surface was the main functional factor associated with walking for recreation (OR 2.04; 95% Cl: 1.43-2.91) and for transport (OR 2.13; 95% Cl: 1.53-2.96). Destination factors, such as shops and public transport, were significantly correlated with walking for transport (OR 1.80; 95% Cl: 1.33-2.44), but not recreation. Conclusion: The findings suggest that neighborhoods with pedestrian facilities that are attractive and comfortable and where there are local destinations (such as shops and public transport) are associated with walking near home.