955 resultados para Open Library Environment
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A longitudinal study of three discrete online public access catalog (OPAC) design enhancements examined the possible effects such changes may have on circulation and resource sharing within the automated library consortium environment. Statistical comparisons were made of both circulation and interlibrary loan (ILL) figures from the year before enhancement to the year after implementation. Data from sixteen libraries covering a seven-year period were studied in order to determine the degree to which patrons may or may not utilize increasingly broader OPAC ILL options over time. Results indicated that while ILL totals increased significantly after each OPAC enhancement, such gains did not result in significant corresponding changes in total circulation.
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Manufactured housing has been found to have substantial levels of formaldehyde in the indoor air. Because mobile homes are more affordable than conventional housing, there has been a large increase in their use in the U.S. This increase in mobile home use has been substantial in the sunbelt regions such as Texas, where high temperatures and humidities may enhance out-gassing of formaldehyde and other volatile organic compounds from construction and furnishing materials and increase any potential health hazards.^ The influences of environmental, architectural and temporal factors on the presence of indoor formaldehyde and other organic compounds were investigated in conjunction with the Texas Indoor Air Quality Study of manufactured housing. A matched pair of mobile homes, one with electric heating and cooking utilities and the other with propane gas utilities, were used for a series of controlled experiments over a fourteen month period from October, 1982 through November, 1983.^ Over this fourteen month period formaldehyde levels decreased approximately 33%. Daily fluctuations of 20% to 40% were observed even with a constant indoor temperature. An increase in indoor temperature of 8(DEGREES)C doubled the measured formaldehyde concentration. Opening windows resulted in decreases of indoor formaldehyde levels of up to 50%. Studies of the impact of propane as a cooking source showed no increase in formaldehyde levels with stove use.^ The presence and concentration of selected volatile organic compounds is influenced greatest by occupancy. Occupants continually open and close windows and doors, vary the operation and settings (temperature) of air control systems, and vary in their selection of furnishings and use of consumer products, which may act as sources of indoor air contaminants. ^
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Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.
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Machine vision is an important subject in computer science and engineering degrees. For laboratory experimentation, it is desirable to have a complete and easy-to-use tool. In this work we present a Java library, oriented to teaching computer vision. We have designed and built the library from the scratch with enfasis on readability and understanding rather than on efficiency. However, the library can also be used for research purposes. JavaVis is an open source Java library, oriented to the teaching of Computer Vision. It consists of a framework with several features that meet its demands. It has been designed to be easy to use: the user does not have to deal with internal structures or graphical interface, and should the student need to add a new algorithm it can be done simply enough. Once we sketch the library, we focus on the experience the student gets using this library in several computer vision courses. Our main goal is to find out whether the students understand what they are doing, that is, find out how much the library helps the student in grasping the basic concepts of computer vision. In the last four years we have conducted surveys to assess how much the students have improved their skills by using this library.
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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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Projet de recherche réalisé en 2014-2015 avec l'appui du Fonds de recherche du Québec – Société et culture.
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Inman E. Page Library participated in the ARCL's Assessment in Action project led by Academic Librarian kYmberly Keeton. This is the final project poster presented by Ms. Keeton at ALA's 2016 Annual at Orlando, Florida. The poster shows how one faculty library group comes together to explore assessing students’ writing intensive projects in three academic semesters within a scholarly learning space at a Historically Black College University.
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Projet de recherche réalisé en 2014-2015 avec l'appui du Fonds de recherche du Québec – Société et culture.
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Title from cover.
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Mode of access: Internet.
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Includes bibliographical references.
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"Serial no. 96-H58."
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Mode of access: Internet.