Otimização do processo de aprendizagem da estrutura gráfica de Redes Bayesianas em BigData

A automação na gestão e análise de dados tem sido um fator crucial para as empresas que necessitam de soluções eficientes em um mundo corporativo cada vez mais competitivo. A explosão do volume de informações, que vem se mantendo crescente nos últimos anos, tem exigido cada vez mais empenho em buscar estratégias para gerenciar e, principalmente, extrair informações estratégicas valiosas a partir do uso de algoritmos de Mineração de Dados, que comumente necessitam realizar buscas exaustivas na base de dados a fim de obter estatísticas que solucionem ou otimizem os parâmetros do modelo de extração do conhecimento utilizado; processo que requer computação intensiva para a execução de cálculos e acesso frequente à base de dados. Dada a eficiência no tratamento de incerteza, Redes Bayesianas têm sido amplamente utilizadas neste processo, entretanto, à medida que o volume de dados (registros e/ou atributos) aumenta, torna-se ainda mais custoso e demorado extrair informações relevantes em uma base de conhecimento. O foco deste trabalho é propor uma nova abordagem para otimização do aprendizado da estrutura da Rede Bayesiana no contexto de BigData, por meio do uso do processo de MapReduce, com vista na melhora do tempo de processamento. Para tanto, foi gerada uma nova metodologia que inclui a criação de uma Base de Dados Intermediária contendo todas as probabilidades necessárias para a realização dos cálculos da estrutura da rede. Por meio das análises apresentadas neste estudo, mostra-se que a combinação da metodologia proposta com o processo de MapReduce é uma boa alternativa para resolver o problema de escalabilidade nas etapas de busca em frequência do algoritmo K2 e, consequentemente, reduzir o tempo de resposta na geração da rede.

Análise ambiental e morfométrica da bacia hidrográfica do Córrego Santo Antônio - São Francisco Xavier (SP)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Inteligência cibernética e uso de recursos semânticos na detecção de perfis falsos no contexto do Big Data

Pós-graduação em Ciência da Informação - FFC

Inteligência cibernética e uso de recursos semânticos na detecção de perfis falsos no contexto do Big Data

Pós-graduação em Ciência da Informação - FFC

Two modes of Gulf Stream variability revealed in two decades of Satellite Altimeter Data

[ES]Charla divulgativa impartida en el Postdoctoal symposium de la Woods Hole oceanographic Institution. Artículo original pulicado en  Journal of Geophysical Research-Oceans

Digital processing and data compilation approach for using remotely sensed imagery to identify geological lineaments in hard-rock terrains : an application for groundwater explorations in Nicaragua

Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

Quantitative proteome analysis in cardiovascular physiology and pathology. I. Data processing

Methodological evaluation of the proteomic analysis of cardiovascular-tissue material has been performed with a special emphasis on establishing examinations that allow reliable quantitative analysis of silver-stained readouts. Reliability, reproducibility, robustness and linearity were addressed and clarified. In addition, several types of normalization procedures were evaluated and new approaches are proposed. It has been found that the silver-stained readout offers a convenient approach for quantitation if a linear range for gel loading is defined. In addition, a broad range of a 10-fold input (loading 20-200 microg per gel) fulfills the linearity criteria, although at the lowest input (20 microg) a portion of protein species will remain undetected. The method is reliable and reproducible within a range of 65-200 microg input. The normalization procedure using the sum of all spot intensities from a silver-stained 2D pattern has been shown to be less reliable than other approaches, namely, normalization through median or through involvement of interquartile range. A special refinement of the normalization through virtual segmentation of pattern, and calculation of normalization factor for each stratum provides highly satisfactory results. The presented results not only provide evidence for the usefulness of silver-stained gels for quantitative evaluation, but they are directly applicable to the research endeavor of monitoring alterations in cardiovascular pathophysiology.

Integrated data acquisition and processing to determine metabolite contents, relaxation times, and macromolecule baseline in single examinations of individual subjects

Absolute quantitation of clinical (1)H-MR spectra is virtually always incomplete for single subjects because the separate determination of spectrum, baseline, and transverse and longitudinal relaxation times in single subjects is prohibitively long. Integrated Processing and Acquisition of Data (IPAD) based on a combined 2-dimensional experimental and fitting strategy is suggested to substantially improve the information content from a given measurement time. A series of localized saturation-recovery spectra was recorded and combined with 2-dimensional prior-knowledge fitting to simultaneously determine metabolite T(1) (from analysis of the saturation-recovery time course), metabolite T(2) (from lineshape analysis based on metabolite and water peak shapes), macromolecular baseline (based on T(1) differences and analysis of the saturation-recovery time course), and metabolite concentrations (using prior knowledge fitting and conventional procedures of absolute standardization). The procedure was tested on metabolite solutions and applied in 25 subjects (15-78 years old). Metabolite content was comparable to previously found values. Interindividual variation was larger than intraindividual variation in repeated spectra for metabolite content as well as for some relaxation times. Relaxation times were different for various metabolite groups. Parts of the interindividual variation could be explained by significant age dependence of relaxation times.

Air-Sea Interactions During the Passage of a Winter Storm Over the Gulf Stream: A Three-Dimensional Coupled Atmosphere-Ocean Model Study

A three-dimensional, regional coupled atmosphere-ocean model with full physics is developed to study air-sea interactions during winter storms off the U. S. east coast. Because of the scarcity of open ocean observations, models such as this offer valuable opportunities to investigate how oceanic forcing drives atmospheric circulation and vice versa. The study presented here considers conditions of strong atmospheric forcing (high wind speeds) and strong oceanic forcing (significant sea surface temperature (SST) gradients). A simulated atmospheric cyclone evolves in a manner consistent with Eta reanalysis, and the simulated air-sea heat and momentum exchanges strongly affect the circulations in both the atmosphere and the ocean. For the simulated cyclone of 19-20 January 1998, maximum ocean-to-atmosphere heat fluxes first appear over the Gulf Stream in the South Atlantic Bight, and this results in rapid deepening of the cyclone off the Carolina coast. As the cyclone moves eastward, the heat flux maximum shifts into the region near Cape Hatteras and later northeast of Hatteras, where it enhances the wind locally. The oceanic response to the atmospheric forcing is closely related to the wind direction. Southerly and southwesterly winds tend to strengthen surface currents in the Gulf Stream, whereas northeasterly winds weaken the surface currents in the Gulf Stream and generate southwestward flows on the shelf. The oceanic feedback to the atmosphere moderates the cyclone strength. Compared with a simulation in which the oceanic model always passes the initial SST to the atmospheric model, the coupled simulation in which the oceanic model passes the evolving SST to the atmospheric model produces higher ocean-to-atmosphere heat flux near Gulf Stream meander troughs. This is due to wind-driven lateral shifts of the stream, which in turn enhance the local northeasterly winds. Away from the Gulf Stream the coupled simulation produces surface winds that are 5 similar to 10% weaker. Differences in the surface ocean currents between these two experiments are significant on the shelf and in the open ocean.