8 resultados para Information Requirements: Data Availability
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.
Resumo:
Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra computational effort is necessary to compute the needed distances, making multidimensional projection prohibitive in applications dealing with interactivity and massive data. The novel multidimensional projection technique proposed in this work, called Part-Linear Multidimensional Projection (PLMP), has been tailored to handle multivariate data represented in Cartesian high-dimensional spaces, requiring only distance information between pairs of representative samples. This characteristic renders PLMP faster than previous methods when processing large data sets while still being competitive in terms of precision. Moreover, knowing the range of variation for data instances in the high-dimensional space, we can make PLMP a truly streaming data projection technique, a trait absent in previous methods.
Resumo:
For many learning tasks the duration of the data collection can be greater than the time scale for changes of the underlying data distribution. The question we ask is how to include the information that data are aging. Ad hoc methods to achieve this include the use of validity windows that prevent the learning machine from making inferences based on old data. This introduces the problem of how to define the size of validity windows. In this brief, a new adaptive Bayesian inspired algorithm is presented for learning drifting concepts. It uses the analogy of validity windows in an adaptive Bayesian way to incorporate changes in the data distribution over time. We apply a theoretical approach based on information geometry to the classification problem and measure its performance in simulations. The uncertainty about the appropriate size of the memory windows is dealt with in a Bayesian manner by integrating over the distribution of the adaptive window size. Thus, the posterior distribution of the weights may develop algebraic tails. The learning algorithm results from tracking the mean and variance of the posterior distribution of the weights. It was found that the algebraic tails of this posterior distribution give the learning algorithm the ability to cope with an evolving environment by permitting the escape from local traps.
Resumo:
Diapoma is reviewed and four species are recognized: (1) Diapoma thauma, new species, from streams of the rio Jacuí basin, state of Rio Grande do Sul; (2) D. pyrrhopteryx, new species collected from the rio Canoas and streams flowing into this basin in the states of Rio Grande do Sul and Santa Catarina, Brazil; (3) Diapoma terofali, from streams flowing into rio Uruguay in Uruguay and Rio Grande do Sul, Brazil and streams flowing into rio de la Plata, Argentina; and (4) Diapoma speculiferum, from lowland coastal streams in Rio Grande do Sul, Brazil and Uruguay. Diapoma pyrrhopteryx possess the posteroventral opercular elongation typical of D. speculiferum, type species of the genus, but which is absent in D. thauma and D. terofali. Nonetheless, all the diapomin species have the caudal pouch organ about equally developed in both sexes and the dorsal portion of the pouch opening bordered by a series of 3 to 8 elongated scales, the two derived features that characterize the group. The two previously described species, D. speculiferum and D. terofali, are redescribed. Previous hypotheses of relationships among the diapomin genera Planaltina, Diapoma and Acrobrycon are discussed on the basis of preliminary morphological information. It is proposed that the Diapomini is a monophyletic group. An identification key, information on sexual dimorphism, gonad anatomy, reproductive mode and distribution of the species of Diapoma are provided.
Resumo:
A catalogue is provided with the type material of four superfamilies of "Acalyptrate" (Conopoidea, Diopsoidea, Nerioidea and Tephritoidea) held in the collection of the Museu de Zoologia da Universidade de São Paulo (MZUSP), São Paulo, Brazil. Concerning the taxa dealt with herein, the Diptera collection of MZUSP held 77 holotypes, 4 "allotypes" and 194 paratypes. In this paper, information about data labels, preservation and missing structures of the type specimens is given.
Resumo:
To investigate stress intensity and coping style in older people with mild Alzheimer`s disease. The potential risk assessment of a stress event and the devising of coping strategies are dependent on cognitive function. Although older individuals with Alzheimer`s disease present significant cognitive impairment, little is known about how these individuals experience stress events and select coping strategies in stress situations. Survey. A convenient sample of 30 cognitively healthy older people and 30 individuals with mild Alzheimer`s disease were given an assessment battery of stress indicators (Symptom Stress List, Cornell Scale for Depression in Dementia, State-Trait Anxiety Inventory), coping style (Jalowiec Coping Scale) and cognitive performance (mini-mental state exam) were applied in both groups. Statistical analysis of the data employed the Mann-Whitney test to compare medians of stress indicators and coping style, Fischer`s exact test to compare proportions when expected frequencies were lower than five, and Spearman`s correlation coefficient to verify correlation between coping style and cognitive performance. Both groups suffered from the same stress intensity (p = 0.254). Regarding coping styles, although differences were not statistically significant (p = 0.124), emotion-oriented coping was predominant in the patients with Alzheimer`s disease. However, those individuals displaying better cognitive performance in the Alzheimer`s disease group had selected coping strategies focused on problem solving (p = 0.0074). Despite a tendency for older people with Alzheimer`s disease to select escape strategies and emotional control, rather than attempting to resolve or lesser the consequences arising from a problem, coping ultimately depends on cognitive performance of the individual. The findings of this study provide information and data to assist planning of appropriate support care for individuals with Alzheimer`s disease who experience stress situations, based on their cognitive performance.
Resumo:
Since the 1990s several large companies have been publishing nonfinancial performance reports. Focusing initially on the physical environment, these reports evolved to consider social relations, as well as data on the firm`s economic performance. A few mining companies pioneered this trend, and in the last years some of them incorporated the three dimensions of sustainable development, publishing so-called sustainability reports. This article reviews 31 reports published between 2001 and 2006 by four major mining companies. A set of 62 assessment items organized in six categories (namely context and commitment, management, environmental, social and economic performance, and accessibility and assurance) were selected to guide the review. The items were derived from international literature and recommended best practices, including the Global Reporting Initiative G3 framework. A content analysis was performed using the report as a sampling unit, and using phrases, graphics, or tables containing certain information as data collection units. A basic rating scale (0 or 1) was used for noting the presence or absence of information and a final percentage score was obtained for each report. Results show that there is a clear evolution in report`s comprehensiveness and depth. Categories ""accessibility and assurance"" and ""economic performance"" featured the lowest scores and do not present a clear evolution trend in the period, whereas categories ""context and commitment"" and ""social performance"" presented the best results and regular improvement; the category ""environmental performance,"" despite it not reaching the biggest scores, also featured constant evolution. Description of data measurement techniques, besides more comprehensive third-party verification are the items most in need of improvement.
Resumo:
Much information on flavonoid content of Brazilian foods has already been obtained; however, this information is spread in scientific publications and non-published data. The objectives of this work were to compile and evaluate the quality of national flavonoid data according to the United States Department of Agriculture`s Data Quality Evaluation System (USDA-DQES) with few modifications, for future dissemination in the TBCA-USP (Brazilian Food Composition Database). For the compilation, the most abundant compounds in the flavonoid subclasses were considered (flavonols, flavones, isoflavones, flavanones, flavan-3-ols, and anthocyanidins) and the analysis of the compounds by HPLC was adopted as criteria for data inclusion. The evaluation system considers five categories, and the maximum score assigned to each category is 20. For each data, a confidence code (CC) was attributed (A, B, C and D), indicating the quality and reliability of the information. Flavonoid data (773) present in 197 Brazilian foods were evaluated. The CC ""C"" (as average) was attributed to 99% of the data and ""B"" (above average) to 1%. The main categories assigned low average scores were: number of samples; sampling plan and analytical quality control (average scores 2, 5 and 4, respectively). The analytical method category received an average score of 9. The category assigned the highest score was the sample handling (20 average). These results show that researchers need to be conscious about the importance of the number and plan of evaluated samples and the complete description and documentation of all the processes of methodology execution and analytical quality control. (C) 2010 Elsevier Inc. All rights reserved.