55 resultados para System analysis - Data processing


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Cassava starch has been shown to make transparent and colorless flexible films without any previous chemical treatment. The functional properties of edible films are influenced by starch properties, including chain conformation, molecular bonding, crystallinity, and water content. Fourier-transform infrared (FTIR) spectroscopy in combination with attenuated total reflectance (ATR) has been applied for the elucidation of the structure and conformation of carbohydrates. This technique associated with chemometric data processing could indicate the relationship between the structural parameters and the functional properties of cassava starch-based edible films. Successful prediction of the functional properties values of the starch-based films was achieved by partial least squares regression data. The results showed that presence of the hydroxyl group on carbon 6 of the cyclic part of glucose is directly correlated with the functional properties of cassava starch films.

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Apert Syndrome, also called acrocephalosyndactylia type 1, is characterized by craniostenosis with early fusion of sutures of the vault and/ or cranial base, associated to mid-face hypoplasia, symmetric syndactylia of the hands and feet and other systemic malformations. CNS malformations and intracranial hypertension are frequently observed in these patients. Early surgical treatment aims to minimize the deleterious effects of intracranial hypertension. Fronto-orbital advancement, the usual surgical technique, increases the intracranial volume and improves the disposition of encephalic structures previously deformed by a short skull. This study analyzes CNS alterations revealed by magnetic resonance in 18 patients presenting Apert Syndrome, and the conformational alterations in the encephalic structures after surgical treatment. The patients' age in February 2001 ranged from 14 to 322 months (m=107). Image study included brain magnetic resonance showing ventricular enlargement in five cases (27.8%), corpus callosum hypoplasia in five cases (27.8%), septum pellucidum hypoplasia in five cases (27.8%), cavum vergae in two cases (11.1%) and, arachnoid cyst in the posterior fossa in two cases (11.1%). Absence of CNS alterations was noted in 44.4% of cases. A corpus callosum morphologic index was established by dividing its height by its length, which revealed values that ranged from 0.4409 to 1.0237. The values of this index were correlated to the occurrence or absence of surgical treatment (p=0.012; t=2.83). Data analysis allowed the conclusion that the corpus callosum morphologic measure quantified the conformational alterations of the cerebral structures determined by the surgical treatment.

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This paper describes a data mining environment for knowledge discovery in bioinformatics applications. The system has a generic kernel that implements the mining functions to be applied to input primary databases, with a warehouse architecture, of biomedical information. Both supervised and unsupervised classification can be implemented within the kernel and applied to data extracted from the primary database, with the results being suitably stored in a complex object database for knowledge discovery. The kernel also includes a specific high-performance library that allows designing and applying the mining functions in parallel machines. The experimental results obtained by the application of the kernel functions are reported. © 2003 Elsevier Ltd. All rights reserved.

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Until mid 2006, SCIAMACHY data processors for the operational retrieval of nitrogen dioxide (NO2) column data were based on the historical version 2 of the GOME Data Processor (GDP). On top of known problems inherent to GDP 2, ground-based validations of SCIAMACHY NO2 data revealed issues specific to SCIAMACHY, like a large cloud-dependent offset occurring at Northern latitudes. In 2006, the GDOAS prototype algorithm of the improved GDP version 4 was transferred to the off-line SCIAMACHY Ground Processor (SGP) version 3.0. In parallel, the calibration of SCIAMACHY radiometric data was upgraded. Before operational switch-on of SGP 3.0 and public release of upgraded SCIAMACHY NO2 data, we have investigated the accuracy of the algorithm transfer: (a) by checking the consistency of SGP 3.0 with prototype algorithms; and (b) by comparing SGP 3.0 NO2 data with ground-based observations reported by the WMO/GAW NDACC network of UV-visible DOAS/SAOZ spectrometers. This delta-validation study concludes that SGP 3.0 is a significant improvement with respect to the previous processor IPF 5.04. For three particular SCIAMACHY states, the study reveals unexplained features in the slant columns and air mass factors, although the quantitative impact on SGP 3.0 vertical columns is not significant.

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The present study aimed to show the spatial distribution of the Rochas watershed (Avaré-SP, Brazil) soil use capacity using the Idrisi geographical information system in order to contribute to a better territorial organization and the planning of the appropriate soil occupation. The obtained results using this methodology showed that most of the Rocha watershed areas are from the following groups: dystrophic yellow-red latosol (36.64%), eutroferric and distroferric red latosol (30.30%) with sandy texture. There was a predominance of areas with slope classes of 0-12%, plain to wavy relief (61.37% of the watershed area) showing that these areas are appropriate for annual culture plantations with wide use of machinery. Most of these areas were classified as class IV (73.79%) as to use capacity. In the studied area the following subclasses of land use capacity were found: IIe, s; IIIe; IVe; IVs; IVe,s; VIe and VIIe. Capacity subclasses IVe; IVe,s; IVs and Vie were the most significant because they are areas that can be used for agriculture but subject to severe soil impoverishment if there are no special care mainly for annual cultures. The Idrisi geographical information system was efficient to determine soil use capacity of the Rocha's watershed showing that the use of geoprocessing tools makes data analysis easier and faster, allowing digital data storage for future analysis uses mainly for territorial planning and environmental studies.

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In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of São Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation. © 2011 by the Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved.

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Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the search for consumers that cause great frauds. In this context, a electric power company may be interested in to go deeper a specific profile of illegal consumer. In this paper, we introduce the Optimum-Path Forest (OPF) clustering technique to this task, and we evaluate the behavior of a dataset provided by a brazilian electric power company with different values of an OPF parameter. © 2011 IEEE.

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This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.

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Sixty female Wistar rats were submitted to a daily intake of ration doped with uranium from weaning to adulthood. Uranium in bone was quantified by the SSNTD (solid state nuclear track detection) technique, and bone mineral density (BMD) analysis performed. Uranium concentration as a function of age exhibited a sharp rise during the first week of the experiment and a drastic drop of 70% in the following weeks. Data interpretation indicates that uranium mimics calcium. Results from BMD suggest that radiation emitted by the incorporated Uranium could induce death of bone cells. © 2013 Elsevier Ltd.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciência da Computação - IBILCE

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Engenharia Mecânica - FEG

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

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The X-ray fluorescence analysis (XRF) is an important technique for the qualitative and quantitative determination of chemical components in a sample. It is based on measurement of the intensity of the emitted characteristic radiation by the elements of the sample, after being properly excited. One of the modalities of this technique is the total reflection x-ray fluorescence (TXRF). In TXRF, the angle of refraction of the incident beam tends to zero and the refracted beam is tangent to the sample-support interface. Thus, there is a minimum angle of incidence that there is no refracted beam and all the incident radiation undergoes total reflection. As it is implemented in very small samples, in a film format, self-absorption effects should not very relevant. In this study, we evaluated the feasibility of using code MCNPX (Monte Carlo N - Particle eXtended), to simulate a measure implemented by the TXRF technique. In this way, it was verified the quality of response of a system by TXRF spectroscopy using synchrotron radiation as excitation beam for a simple setup, by retrieving the characteristic energies and the concentrations of the elements in the sample. The steps of data processing, after obtaining the excitation spectra, were the same as in a real experiment and included the obtaining of the sensitivity curve for the simulated system. The agreement between the theoretical and simulated values of Ka characteristic energies for different elements was lower than 1 % .The obtained concentration of the elements of the sample had high relatively errors ( between 6 and 60 % ) due mainly to lack of knowing about some realistic physical parameters of the sample , such as density . In this way, this result does not preclude the use of MCNPX code for this type of application