Conceptual model for adaptable and extensible visual data exploration

Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

Morphometric analysis of a population of diplopods of the genus Rhinocricus Karsch, 1881

Diplopods belonging to the subclass Helminthomorpha may present one or both leg pairs of the seventh diplosegment modified into structures that aid copulation, called gonopods. These structures are used as a taxonomic trait for the description of most species. In the genus Rhinocricus these structures are closely similar, so that it is difficult to distinguish species only on the basis of this trait. Two species, R. padbergi and R. varians, are found in the same habitat and present gonopods practically identical in shape; together they present a broad colour gradient, ranging from dark brown to light beige. Morphometric data for individuals of the experimental group were submitted to ANOVA and MANOVA, using Hotelling-Lawley Trace and generalized Mahalanobis distances (D 2) tests. The results demonstrated a relationship between size and colour, with darker individuals being larger. On the basis of this preliminary analysis, we may suggest that the two species are distinct since dark individuals are distant from medium- and light-coloured individuals according to the D 2 values. This seems to indicate a possible polymorphism of individuals belonging to R. padbergi which present close proximity in the values obtained. In all analyses, we observed that the main variables were diameter, length and telson size.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Stress analysis in bone tissue around single implants with different diameters and veneering materials: A 3-D finite element study

The aimof this study was to evaluate the stress distribution on bone tissue with a single prosthesis supported by implants of large and conventional diameter and presenting different veneering materials using the 3-D finite elementmethod. Sixteenmodels were fabricated to reproduce a bone block with implants, using two diameters (3.75 × 10 mmand 5.00 × 10 mm), four different veneering materials (composite resin, acrylic resin, porcelain, and NiCr crown), and two loads (axial (200 N) and oblique (100 N)). For data analysis, the maximum principal stress and vonMises criterion were used. For the axial load, the cortical bone in allmodels did not exhibit significant differences, and the trabecular bone presented higher tensile stresswith reduced implant diameter. For the oblique load, the cortical bone presented a significant increase in tensile stress on the same side as the loading for smaller implant diameters. The trabecular bone showed a similar but more discreet trend. There was no difference in bone tissue with different veneering materials. The veneering material did not influence the stress distribution in the supporting tissues of single implant-supported prostheses. The large-diameter implants improved the transference of occlusal loads to bone tissue and decreased stress mainly under oblique loads.Oblique loading was more detrimental to distribution stresses than axial loading. © 2013 Elsevier B.V. All rights reserved.

Transdisciplinaridade em saúde: uma análise integrativa da literatura

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Autocura metafisica: revisão integrativa

Pós-graduação em Saúde Coletiva - FMB

Ambiente data cleaning: suporte extensível, semântico e automático para análise e transformação de dados

Pós-graduação em Ciência da Computação - IBILCE

Dimensões e limites da supervisão acadêmica de estágio em Serviço Social

Pós-graduação em Serviço Social - FCHS

Analysis of 25 mutual eclipses and occultations between the Galilean satellites observed from Brazil in 2009

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Singular Value Decomposition and Ligand Binding Analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Metabolic profiling by ultra-performance liquid chromatography-mass spectrometry and parallel factor analysis for the determination of disease biomarkers in Eucalyptus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Implementation of an F-statistic all-sky search for continuous gravitational waves in Virgo VSR1 data

We present an implementation of the F-statistic to carry out the first search in data from the Virgo laser interferometric gravitational wave detector for periodic gravitational waves from a priori unknown, isolated rotating neutron stars. We searched a frequency f(0) range from 100 Hz to 1 kHz and the frequency dependent spindown f(1) range from -1.6(f(0)/100 Hz) x 10(-9) Hz s(-1) to zero. A large part of this frequency-spindown space was unexplored by any of the all-sky searches published so far. Our method consisted of a coherent search over two-day periods using the F-statistic, followed by a search for coincidences among the candidates from the two-day segments. We have introduced a number of novel techniques and algorithms that allow the use of the fast Fourier transform (FFT) algorithm in the coherent part of the search resulting in a fifty-fold speed-up in computation of the F-statistic with respect to the algorithm used in the other pipelines. No significant gravitational wave signal was found. The sensitivity of the search was estimated by injecting signals into the data. In the most sensitive parts of the detector band more than 90% of signals would have been detected with dimensionless gravitational-wave amplitude greater than 5 x 10(-24).

Data collection on bone density of mandibular alveolar bone on a Hounsfield scale of the dental apex of the cranial root of the first inferior molar in dogs using computed tomography at FMVZ-UNESP

The head is the most important and specialized region in the body because it contains a range of specialized organs and, because it has interconnections between specialized organs, there is a great overlap of images. Thus, computed tomography (CT) helps in diagnosing diseases in this region, such as oral conditions, as they provide millimetric slices or cuts and demonstrate the relationship between the various anatomical structures involved, in volume and depth. Within dentistry, CT helps in the identification of pathological processes such as infection, tumors, visualization of embedded teeth and bone bed. This study aimed to assess the density of the mandibular alveolar bone at a determined point to later predict how periodontal disease is involved in bone resorption. For this, we performed a blind retrospective study (n = 124) of the CT scan files of dog skulls at FMVZ-UNESP in order to determine the density of the jaw bone using a Hounsfield scale, in the region of the dental apex of the cranial root of the first molar tooth in dogs. The results obtained were evaluated using mean and standard deviation (27.28 +/- 9.53 HU) in order to predict the normal density of the mandibular alveolar bone in the studied region. Thus, this data analysis allows a more concise evaluation of bone resorption of mandibular alveolar bone and, therefore, provides an adequate surgical planning in cases of osteosynthesis given mainly by the presence of installed periodontal disease.

Estimation of a preference map of new consumers for spatial load forecasting simulation methods using a spatial analysis of points

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Analysis of simple hardware efficiency for temperature measurement in agriculture and environment

This work focuses basically on the design and analysis of simple and low cost hardware systems efficiency for temperature measurement in agricultural area. The main objective is to prove quantitatively, through statistical data analysis, to what extent a simple hardware designed with inexpensive components can be used safely in the indoor temperature measurement in farm buildings, such as greenhouses, warehouse or silos. To verify the of simple hardware efficiency, its data were compared with data from measurements with a high performance LabVIEW platform. This work proved that a simple hardware based on a microcontroller and the LM35 sensor can perform well. It presented a good accuracy but a relatively low precision that can be improved when performed some consecutive signal sampling and then used its average value. Although there are many papers that explain these components, this work has the distinction of presenting a data analysis in numerical form and using high performance systems to ensure critical data comparison.