108 resultados para Satelites artificiais em agrimensura
Resumo:
Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature
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Nowadays, optic fiber is one of the most used communication methods, mainly due to the fact that the data transmission rates of those systems exceed all of the other means of digital communication. Despite the great advantage, there are problems that prevent full utilization of the optical channel: by increasing the transmission speed and the distances involved, the data is subjected to non-linear inter symbolic interference caused by the dispersion phenomena in the fiber. Adaptive equalizers can be used to solve this problem, they compensate non-ideal responses of the channel in order to restore the signal that was transmitted. This work proposes an equalizer based on artificial neural networks and evaluates its performance in optical communication systems. The proposal is validated through a simulated optic channel and the comparison with other adaptive equalization techniques
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The petroleum industry, in consequence of an intense activity of exploration and production, is responsible by great part of the generation of residues, which are considered toxic and pollutants to the environment. Among these, the oil sludge is found produced during the production, transportation and refine phases. This work had the purpose to develop a process to recovery the oil present in oil sludge, in order to use the recovered oil as fuel or return it to the refining plant. From the preliminary tests, were identified the most important independent variables, like: temperature, contact time, solvents and acid volumes. Initially, a series of parameters to characterize the oil sludge was determined to characterize its. A special extractor was projected to work with oily waste. Two experimental designs were applied: fractional factorial and Doehlert. The tests were carried out in batch process to the conditions of the experimental designs applied. The efficiency obtained in the oil extraction process was 70%, in average. Oil sludge is composed of 36,2% of oil, 16,8% of ash, 40% of water and 7% of volatile constituents. However, the statistical analysis showed that the quadratic model was not well fitted to the process with a relative low determination coefficient (60,6%). This occurred due to the complexity of the oil sludge. To obtain a model able to represent the experiments, the mathematical model was used, the so called artificial neural networks (RNA), which was generated, initially, with 2, 4, 5, 6, 7 and 8 neurons in the hidden layer, 64 experimental results and 10000 presentations (interactions). Lesser dispersions were verified between the experimental and calculated values using 4 neurons, regarding the proportion of experimental points and estimated parameters. The analysis of the average deviations of the test divided by the respective training showed up that 2150 presentations resulted in the best value parameters. For the new model, the determination coefficient was 87,5%, which is quite satisfactory for the studied system
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Photo-oxidation processes of toxic organic compounds have been widely studied. This work seeks the application of the photo-Fenton process for the degradation of hydrocarbons in water. The gasoline found in the refinery, without additives and alcohol, was used as the model pollutant. The effects of the concentration of the following substances have been properly evaluated: hydrogen peroxide (100-200 mM), iron ions (0.5-1 mM) and sodium chloride (200 2000 ppm). The experiments were accomplished in reactor with UV lamp and in a falling film solar reactor. The photo-oxidation process was monitored by measurements of the absorption spectra, total organic carbon (TOC) and chemical oxygen demand (COD). Experimental results demonstrated that the photo-Fenton process is feasible for the treatment of wastewaters containing aliphatic hydrocarbons, inclusive in the presence of salts. These conditions are similar to the water produced by the petroleum fields, generated in the extraction and production of petroleum. A neural network model of process correlated well the observed data for the photooxidation process of hydrocarbons
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Expanded Bed Adsorption (EBA) is an integrative process that combines concepts of chromatography and fluidization of solids. The many parameters involved and their synergistic effects complicate the optimization of the process. Fortunately, some mathematical tools have been developed in order to guide the investigation of the EBA system. In this work the application of experimental design, phenomenological modeling and artificial neural networks (ANN) in understanding chitosanases adsorption on ion exchange resin Streamline® DEAE have been investigated. The strain Paenibacillus ehimensis NRRL B-23118 was used for chitosanase production. EBA experiments were carried out using a column of 2.6 cm inner diameter with 30.0 cm in height that was coupled to a peristaltic pump. At the bottom of the column there was a distributor of glass beads having a height of 3.0 cm. Assays for residence time distribution (RTD) revelead a high degree of mixing, however, the Richardson-Zaki coefficients showed that the column was on the threshold of stability. Isotherm models fitted the adsorption equilibrium data in the presence of lyotropic salts. The results of experiment design indicated that the ionic strength and superficial velocity are important to the recovery and purity of chitosanases. The molecular mass of the two chitosanases were approximately 23 kDa and 52 kDa as estimated by SDS-PAGE. The phenomenological modeling was aimed to describe the operations in batch and column chromatography. The simulations were performed in Microsoft Visual Studio. The kinetic rate constant model set to kinetic curves efficiently under conditions of initial enzyme activity 0.232, 0.142 e 0.079 UA/mL. The simulated breakthrough curves showed some differences with experimental data, especially regarding the slope. Sensitivity tests of the model on the surface velocity, axial dispersion and initial concentration showed agreement with the literature. The neural network was constructed in MATLAB and Neural Network Toolbox. The cross-validation was used to improve the ability of generalization. The parameters of ANN were improved to obtain the settings 6-6 (enzyme activity) and 9-6 (total protein), as well as tansig transfer function and Levenberg-Marquardt training algorithm. The neural Carlos Eduardo de Araújo Padilha dezembro/2013 9 networks simulations, including all the steps of cycle, showed good agreement with experimental data, with a correlation coefficient of approximately 0.974. The effects of input variables on profiles of the stages of loading, washing and elution were consistent with the literature
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There is presently a worldwide interest in artificial magnetic systems which guide research activities in universities and companies. Thin films and multilayers have a central role, revealing new magnetic phases which often lead to breakthroughs and new technology standards, never thought otherwise. Surface and confinement effects cause large impact in the magnetic phases of magnetic materials with bulk spatially periodic patterns. New magnetic phases are expected to form in thin film thicknesses comparable to the length of the intrinsic bulk magnetic unit cell. Helimagnetic materials are prototypes in this respect, since the bulk magnetic phases consist in periodic patterns with the length of the helical pitch. In this thesis we study the magnetic phases of thin rare-earth films, with surfaces oriented along the (002) direction. The thesis includes the investigation of the magnetic phases of thin Dy and Ho films, as well as the thermal hysteresis cycles of Dy thin films. The investigation of the thermal hysteresis cycles of thin Dy films has been done in collaboration with the Laboratory of Magnetic Materials of the University of Texas, at Arlington. The theoretical modeling is based on a self-consistent theory developed by the Group of Magnetism of UFRN. Contributions from the first and second neighbors exchange energy, from the anisotropy energy and the Zeeman energy are calculated in a set of nonequivalent magnetic ions, and the equilibrium magnetic phases, from the Curie temperature up to the Nèel temperature, are determined in a self-consistent manner, resulting in a vanishing torque in the magnetic ions at all planes across the thin film. Our results reproduce the known isothermal and iso-field curves of bulk Dy and Ho, and the known spin-slip phases of Ho, and indicate that: (i) the confinement in thin films leads to a new magnetic phase, with alternate helicity, which leads to the measured thermal hysteresis of Dy ultrathin films, with thicknesses ranging from 4 nm to 16 nm; (ii) thin Dy films have anisotropy dominated surface lock-in phases, with alignment of surface spins along the anisotropy easy axis directions, similar to the known spin-slip phases of Ho ( which form in the bulk and are commensurate to the crystal lattice); and (iii) the confinement in thin films change considerably the spin-slip patterns of Ho.
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The physical properties and the excitations spectrum in oxides and semiconductors materials are presented in this work, whose the first part presents a study on the confinement of optical phonons in artificial systems based on III-V nitrides, grown in periodic and quasiperiodic forms. The second part of this work describes the Ab initio calculations which were carried out to obtain the optoeletronic properties of Calcium Oxide (CaO) and Calcium Carbonate (CaCO3) crystals. For periodic and quasi-periodic superlattices, we present some dynamical properties related to confined optical phonons (bulk and surface), obtained through simple theories, such as the dielectric continuous model, and using techniques such as the transfer-matrix method. The localization character of confined optical phonon modes, the magnitude of the bands in the spectrum and the power laws of these structures are presented as functions of the generation number of sequence. The ab initio calculations have been carried out using the CASTEP software (Cambridge Total Sequential Energy Package), and they were based on ultrasoft-like pseudopotentials and Density Functional Theory (DFT). Two di®erent geometry optimizations have been e®ectuated for CaO crystals and CaCO3 polymorphs, according to LDA (local density approximation) and GGA (generalized gradient approximation) approaches, determining several properties, e. g. lattice parameters, bond length, electrons density, energy band structures, electrons density of states, e®ective masses and optical properties, such as dielectric constant, absorption, re°ectivity, conductivity and refractive index. Those results were employed to investigate the confinement of excitons in spherical Si@CaCO3 and CaCO3@SiO2 quantum dots and in calcium carbonate nanoparticles, and were also employed in investigations of the photoluminescence spectra of CaCO3 crystal
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The objective of this work is to identify, to chart and to explain the evolution of the soil occupation and the envirionment vulnerability of the areas of Canto do Amaro and Alto da Pedra, in the city of Mossoró-RN, having as base analyzes it multiweather of images of orbital remote sensors, the accomplishment of extensive integrated works of field to a Geographic Information System (GIS). With the use of inserted techniques of it analyzes space inserted in a (GIS), and related with the interpretation and analyzes of products that comes from the Remote Sensoriamento (RS.), make possible resulted significant to reach the objectives of this works. Having as support for the management of the information, the data set gotten of the most varied sources and stored in digital environment, it comes to constitute the geographic data base of this research. The previous knowledge of the spectral behavior of the natural or artificial targets, and the use of algorithms of Processing of Digital images (DIP), it facilitates the interpretation task sufficiently and searchs of new information on the spectral level. Use as background these data, was generated a varied thematic cartography was: Maps of Geology, Geomorfológicals Units soils, Vegetation and Use and Occupation of the soil. The crossing in environment SIG, of the above-mentioned maps, generated the maps of Natural and Vulnerability envirionmental of the petroliferous fields of I Canto do Amaro and Alto da Pedra-RN, working in an ambient centered in the management of waters and solid residuos, as well as the analysis of the spatial data, making possible then a more complex analysis of the studied area
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The use of non-human primates in scientific research has contributed significantly to the biomedical area and, in the case of Callithrix jacchus, has provided important evidence on physiological mechanisms that help explain its biology, making the species a valuable experimental model in different pathologies. However, raising non-human primates in captivity for long periods of time is accompanied by behavioral disorders and chronic diseases, as well as progressive weight loss in most of the animals. The Primatology Center of the Universidade Federal do Rio Grande do Norte (UFRN) has housed a colony of C. jacchus for nearly 30 years and during this period these animals have been weighed systematically to detect possible alterations in their clinical conditions. This procedure has generated a volume of data on the weight of animals at different age ranges. These data are of great importance in the study of this variable from different perspectives. Accordingly, this paper presents three studies using weight data collected over 15 years (1985-2000) as a way of verifying the health status and development of the animals. The first study produced the first article, which describes the histopathological findings of animals with probable diagnosis of permanent wasting marmoset syndrome (WMS). All the animals were carriers of trematode parasites (Platynosomum spp) and had obstruction in the hepatobiliary system; it is suggested that this agent is one of the etiological factors of the syndrome. In the second article, the analysis focused on comparing environmental profile and cortisol levels between the animals with normal weight curve evolution and those with WMS. We observed a marked decrease in locomotion, increased use of lower cage extracts and hypocortisolemia. The latter is likely associated to an adaptation of the mechanisms that make up the hypothalamus-hypophysis-adrenal axis, as observed in other mammals under conditions of chronic malnutrition. Finally, in the third study, the animals with weight alterations were excluded from the sample and, using computational tools (K-means and SOM) in a non-supervised way, we suggest found new ontogenetic development classes for C. jacchus. These were redimensioned from five to eight classes: infant I, infant II, infant III, juvenile I, juvenile II, sub-adult, young adult and elderly adult, in order to provide a more suitable classification for more detailed studies that require better control over the animal development
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This study aimed at exploring and describing children s perceptions in threatened natural settings, specifically, the Rain Forest in Brazil. Several studies point to the significance of perceptions for people s pro-environmental attitudes and actions. We try to understand the person-environment interaction from an ecological perspective, and we present theoretical references for the understanding of how crucial nature is for psychological development and well-being. The children s drawings, individual interviews, discussion groups, photographies and informal and indirect sources, as teachers, brought material for the analysis. Participated in our study, carried on through a multi-method strategy, 209 children from six to eleven years old, living in the neighborhood of the Biological Reserve of Una, State of Bahia, created to protect Rain Forest fragments. The Rain Forest landscape is well portrayed in children s drawings, the vegetal elements prevailing over artificial and human elements. The figured plants and trees, however, are pointed with no precision as to their species. Most of the defined species are eatable. The children seem to be aware of the environment degradation, and of the importance of its conservation, but they describe episodes of hunting and feeding wild threatened animals. Our results indicate a utilitarian trend in the perception of living beings, in terms of their immediate usefulness for people. The multimethod approach seems to be appropriate to the complexity of the theme; the methodological strategies were well accepted by the children, offering them opportunities to express themselves. We observed how children, in different life phases, organize natural elements and processes in their drawings, and how these images relate to the local landscape. We discuss the results in the light of theoretical references of personenvironment studies and from previous investigations about children s perceptions of natural environment
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In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma
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This study investigates the chemical species produced water from the reservoir areas of oil production in the field of Monte Alegre (onshore production) with a proposal of developing a model applied to the identification of the water produced in different zones or groups of zones.Starting from the concentrations of anions and cátions from water produced as input parameters in Linear Discriminate Analysis, it was possible to estimate and compare the model predictions respecting the particularities of their methods in order to ascertain which one would be most appropriate. The methods Resubstitution, Holdout Method and Lachenbruch were used for adjustment and general evaluation of the built models. Of the estimated models for Wells producing water for a single production area, the most suitable method was the "Holdout Method and had a hit rate of 90%. Discriminant functions (CV1, CV2 and CV3) estimated in this model were used to modeling new functions for samples ofartificial mixtures of produced water (producedin our laboratory) and samples of mixtures actualproduced water (water collected inwellsproducingmore thanonezone).The experiment with these mixtures was carried out according to a schedule experimental mixtures simplex type-centroid also was simulated in which the presence of water from steam injectionin these tanks fora part of amostras. Using graphs of two and three dimensions was possible to estimate the proportion of water in the production area
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There is a lack of clinical studies evaluating techniques of functional impression for partially edentulous arches. The aim of this double-blind non-randomized controlled clinical trial was to compare the efficacy of altered cast impression (ACI) and direct functional impression (DFI) techniques. The efficacy was evaluated regarding the number of occlusal units on denture teeth, mucosa integrity at 24-hour follow-up and denture base extension. The sample included 51 patients (female and male) with mean age of 58.96 years treated at Dental Department of UFRN. The patients, exhibiting edentulous maxilla and mandibular Kennedy class I, were divided into two groups (group ACI, n=29; group DFI, n=22). Clinical evaluation was based on the number of occlusal units on natural and/or artificial teeth, mucosa integrity at 24-hour follow-up, and denture base extension. Statistical analysis was conducted using the software SPSS 17.0® (SPSS Inc., Chicago, Illinois). Student T-test was used to reveal association between number of occlusal units and impression technique while chi-square test showed association between mucosa integrity and impression technique. Fischer s exact test was applied for association between denture base extension and impression technique at 95% level of significance. No significant difference was observed between the groups regarding number of occlusal units, mucosa integrity and denture base extension. The altered cast technique did not provide significant improvement in comparison to the direct technique when the number of occlusal units, mucosa integrity and denture base extension
Falhas e complicações com o uso de prótese parcial removível inferior de extremidade livre bilateral
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Aim: To determine the frequency and type of complications related to removable partial denture (RPD) less, Kennedy Class I, over time . Materials and Methods: This observational study consisted of a sample of 65 users PPR lower arches in Kennedy Class I and dentures, rehabilitated in the Department of Dentistry, Federal University of Rio Grande do Norte (UFRN). Patients were followed through periodic controls during periods of 60 days, 6 months and 1 year from installation. After the first year of control had other returns annually. The occurrence of complications or prosthetic failure was observed and recorded in a specific clinical record over 39 months. The patterns of failures observed were classified in the following situations: occurrence of traumatic ulcers after 2 months of installation, lack of retention, fracture or caries in the rest, fracture or dislocation of the artificial teeth, the larger connector fracture, fracture clip fracture support, poor support (need to reline the denture) and prosthesis fracture. Results: The incidence of complications was low frequency, being higher in the second year of use of the prosthesis. Among the complications that occurred more is the loss of retention (31.57%). Failures more severe and difficult to solve as the fracture elements of the metal structure of the PPR had low occurrence and were represented by only one case of the larger connector (5.3%) fractures. Conclusion: Removable partial dentures mandibular free end opposing of the conventional dentures have a low complication rate after 39 months of use when subjected to periodic controls
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RePART (Reward/Punishment ART) is a neural model that constitutes a variation of the Fuzzy Artmap model. This network was proposed in order to minimize the inherent problems in the Artmap-based model, such as the proliferation of categories and misclassification. RePART makes use of additional mechanisms, such as an instance counting parameter, a reward/punishment process and a variable vigilance parameter. The instance counting parameter, for instance, aims to minimize the misclassification problem, which is a consequence of the sensitivity to the noises, frequently presents in Artmap-based models. On the other hand, the use of the variable vigilance parameter tries to smoouth out the category proliferation problem, which is inherent of Artmap-based models, decreasing the complexity of the net. RePART was originally proposed in order to minimize the aforementioned problems and it was shown to have better performance (higer accuracy and lower complexity) than Artmap-based models. This work proposes an investigation of the performance of the RePART model in classifier ensembles. Different sizes, learning strategies and structures will be used in this investigation. As a result of this investigation, it is aimed to define the main advantages and drawbacks of this model, when used as a component in classifier ensembles. This can provide a broader foundation for the use of RePART in other pattern recognition applications