11 resultados para Subfractals, Subfractal Coding, Model Analysis, Digital Imaging, Pattern Recognition
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
In this study, the methodological procedures involved in digital imaging of collapsed paleocaves in tufa using GPR are presented. These carbonate deposits occur in the Quixeré region, Ceará State (NE Brazil), on the western border of the Potiguar Basin. Collapsed paleocaves are exposed along a state road, which were selected to this study. We chose a portion of the called Quixeré outcrop for making a photomosaic and caring out a GPR test section to compare and parameterize the karst geometries on the geophysical line. The results were satisfactory and led to the adoption of criteria for the interpretation of others GPR sections acquired in the region of the Quixeré outcrop. Two grids of GPR lines were acquired; the first one was wider and more spaced and guided the location of the second grid, denser and located in the southern part of the outcrop. The radargrams of the second grid reveal satisfactorily the collapsed paleocaves geometries. For each grid has been developed a digital solid model of the Quixeré outcrop. The first model allows the recognition of the general distribution and location of collapsed paleocaves in tufa deposits, while the second more detailed digital model provides not only the 3D individualization of the major paleocaves, but also the estimation of their respective volumes. The digital solid models are presented here as a new frontier in the study of analog outcrops to reservoirs (for groundwater and hydrocarbon), in which the volumetric parameterization and characterization of geological bodies become essential for composing the databases, which together with petrophysical properties information, are used in more realistic computer simulations for sedimentary reservoirs.
Resumo:
In this paper we present the methodological procedures involved in the digital imaging in mesoscale of a block of travertines rock of quaternary age, originating from the city of Acquasanta, located in the Apennines, Italy. This rocky block, called T-Block, was stored in the courtyard of the Laboratório Experimental Petróleo "Kelsen Valente" (LabPetro), of Universidade Estadual de Campinas (UNICAMP), so that from it were performed Scientific studies, mainly for research groups universities and research centers working in brazilian areas of reservoir characterization and 3D digital imaging. The purpose of this work is the development of a Model Solid Digital, from the use of non-invasive techniques of digital 3D imaging of internal and external surfaces of the T-Block. For the imaging of the external surfaces technology has been used LIDAR (Light Detection and Range) and the imaging surface Interior was done using Ground Penetrating Radar (GPR), moreover, profiles were obtained with a Gamma Ray Gamae-spectômetro laptop. The goal of 3D digital imaging involved the identification and parameterization of surface geological and sedimentary facies that could represent heterogeneities depositional mesoscale, based on study of a block rocky with dimensions of approximately 1.60 m x 1.60 m x 2.70 m. The data acquired by means of terrestrial laser scanner made available georeferenced spatial information of the surface of the block (X, Y, Z), and varying the intensity values of the return laser beam and high resolution RGB data (3 mm x 3 mm), total points acquired 28,505,106. This information was used as an aid in the interpretation of radargrams and are ready to be displayed in rooms virtual reality. With the GPR was obtained 15 profiles of 2.3 m and 2 3D grids, each with 24 sections horizontal of 1.3 and 14 m vertical sections of 2.3 m, both the Antenna 900 MHz to about 2600 MHz antenna. Finally, the use of GPR associated with Laser Scanner enabled the identification and 3D mapping of 3 different radarfácies which were correlated with three sedimentary facies as had been defined at the outset. The 6 profiles showed gamma a low amplitude variation in the values of radioactivity. This is likely due to the fact of the sedimentary layers profiled have the same mineralogical composition, being composed by carbonate sediments, with no clay in siliciclastic pellitic layers or other mineral carrier elements radioactive
Resumo:
T'his dissertation proposes alternative models to allow the interconnectioin of the data communication networks of COSERN Companhia Energética do Rio Grande do Norte. These networks comprise the oorporative data network, based on TCP/IP architecture, and the automation system linking remote electric energy distribution substations to the main Operatin Centre, based on digital radio links and using the IEC 60870-5-101 protoco1s. The envisaged interconnection aims to provide automation data originated from substations with a contingent route to the Operation Center, in moments of failure or maintenance of the digital radio links. Among the presented models, the one chosen for development consists of a computational prototype based on a standard personal computer, working under LINUX operational system and running na application, developesd in C language, wich functions as a Gateway between the protocols of the TCP/IP stack and the IEC 60870-5-101 suite. So, it is described this model analysis, implementation and tests of functionality and performance. During the test phase it was basically verified the delay introduced by the TCP/IP network when transporting automation data, in order to guarantee that it was cionsistent with the time periods present on the automation network. Besides , additional modules are suggested to the prototype, in order to handle other issues such as security and prioriz\ation of the automation system data, whenever they are travesing the TCP/IP network. Finally, a study hás been done aiming to integrate, in more complete way, the two considered networks. It uses IP platform as a solution of convergence to the communication subsystem of na unified network, as the most recente market tendencies for supervisory and other automation systems indicate
Resumo:
Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification
Resumo:
The aim of this work was to describe the methodological procedures that were mandatory to develop a 3D digital imaging of the external and internal geometry of the analogue outcrops from reservoirs and to build a Virtual Outcrop Model (VOM). The imaging process of the external geometry was acquired by using the Laser Scanner, the Geodesic GPS and the Total Station procedures. On the other hand, the imaging of the internal geometry was evaluated by GPR (Ground Penetrating Radar).The produced VOMs were adapted with much more detailed data with addition of the geological data and the gamma ray and permeability profiles. As a model for the use of the methodological procedures used on this work, the adapted VOM, two outcrops, located at the east part of the Parnaiba Basin, were selected. On the first one, rocks from the aeolian deposit of the Piaui Formation (Neo-carboniferous) and tidal flat deposits from the Pedra de Fogo Formation (Permian), which arises in a large outcrops located between Floriano and Teresina (Piauí), are present. The second area, located at the National Park of Sete Cidades, also at the Piauí, presents rocks from the Cabeças Formation deposited in fluvial-deltaic systems during the Late Devonian. From the data of the adapted VOMs it was possible to identify lines, surfaces and 3D geometry, and therefore, quantify the geometry of interest. Among the found parameterization values, a table containing the thickness and width, obtained in canal and lobes deposits at the outcrop Paredão and Biblioteca were the more relevant ones. In fact, this table can be used as an input for stochastic simulation of reservoirs. An example of the direct use of such table and their predicted radargrams was the identification of the bounding surface at the aeolian sites from the Piauí Formation. In spite of such radargrams supply only bi-dimensional data, the acquired lines followed of a mesh profile were used to add a third dimension to the imaging of the internal geometry. This phenomenon appears to be valid for all studied outcrops. As a conclusion, the tool here presented can became a new methodology in which the advantages of the digital imaging acquired from the Laser Scanner (precision, accuracy and speed of acquisition) were combined with the Total Station procedure (precision) using the classical digital photomosaic technique
Resumo:
The North Paraíba River Estuary, located in the eastern portion of the Paraíba State, Northeast Brazil, on coordinates 34º50 00 -34º57 30 S and 6º55 00 -7º7 30 W, constitutes a fluvio-marine plain formed by the North Paraíba River and its tributaries Sanhauá, Paroeira, Mandacaru, Tiriri, Tambiá, Ribeira and Guia. This estuary comprises an area of about 260 km2. Increasing human demands on the estuary area and inadequate environment managing have generated conflicts. The present work main purpose is to evaluate the geodynamic evolution of the North Paraíba River Estuary in the period from 1969 to 2001, using digital image processing techniques, thematic digital cartography and multitemporal data integration, combined to geological-geophysical field surveys. The SUDENE cartographic database, converted to digital format were, used to obtain occupation and topographic maps from 1969 and to generate a Digital Elevation Model (DEM). Digital Landsat 7 ETM+ and Spot HRVIR-PAN satellite images interpretation allowed the environmental characterization of the estuary. The most important digital processing results were achieved color composites RGB 5-4-3, 5-3-1, 5-2-NDWI and band ratio 7/4-5/3-4/2, 5/7-3/1-5/4). In addition the fusion image technique RGBI was used by the inclusion of the Spot HRVRI and Landsat 7 ETM+ panchromatic band on I layer with RGB triplets 5-4-3, 5-3-1 and 5/7-3/1-5/4. The DEM and digital images integration allowed the identification of seven geomorphological units: coastal tableland, flowing tray, tide plain, fluvial terrace, submerged dune, beach plain and beach). Both Side Scan Sonar and Echosound were used to analyse underwater surface and bedforms of the estuarine channel, sand predominance (fine to very fine) and 2D dune features 5 m wide and 0.5 m height. This investigation characterized the estuary as an environment dominated by regimen of average flow. The channel depth varies between 1 m and 11 m, being this last quota reached in the area of Porto de Cabedelo. The chanel estuary is relatively shallow, with erosion evidences mainly on its superior portion, attested by sand banks exposed during the low tide. Multitemporal digital maps from 1969 and 2001 integration were obtained through geoprocessing techniques, resulting the geodynamic evolution of the estuary based on landuse, DEM geomorphology and bathymetric maps
Resumo:
The IT capability is a organizational ability to perform activities of this role more effectively and an important mechanism in creating value. Its building process (stages of creation and development) occurs through management initiatives for improvement in the performance of their activities, using human resources and IT assets complementary responsible for the evolution of their organizational routines. This research deals with the IT capabilities related to SIG (integrated institutional management systems), built and deployed in UFRN (Universidade Federal do Rio Grande do Norte) to realization and control of administrative, academic and human resources activities. Since 2009, through cooperative agreements with federal and educational institutions of direct administration, UFRN has supported the implementation of these systems, currently involving more than 30 institutions. The present study aims to understand how IT capabilities, relevant in the design, implementation and dissemination of SIG, were built over time. This is a single case study of qualitative and longitudinal nature, performed by capturing, coding and analysis from secondary data and from semi-structured interviews conducted primarily with members of Superintenência de Informática, organizational unit responsible for SIG systems in UFRN. As a result, the technical, of internal relationship and external cooperation capabilities were identified as relevant in the successful trajectory of SIG systems, which have evolved in different ways. The technical capacity, initiated in 2004, toured the stages of creation and development until it reached the stage of stability in 2013, due to technological limits. Regarding the internal relationship capability, begun in 2006, it toured the stages of creation and development, having extended its scope of activities in 2009, being in development since then. Unlike the standard life cycle observed in the literature, the external cooperation capability was initiated by an intensity of initiatives and developments in the routines in 2009, which were decreasing to cease in 2013 in order to stabilize the technological infrastructure already created for cooperative institutions. It was still identified the start of cooperation in 2009 as an important event selection, responsible for changing or creating trajectories of evolution in all three capacities. The most frequent improvements initiatives were of organizational nature and the internal planning activity has been transformed over the routines of the three capabilities. Important resources and complementary assets have been identified as important for the realization of initiatives, such as human resources technical knowledge to the technical capabilities and external cooperation, and business knowledge, for all of them, as well as IT assets: the iproject application for control of development processes, and the document repository wiki. All these resources and complementary assets grew along the capacities, demonstrating its strategic value to SINFO/UFRN
Resumo:
Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's applicability in medical image segmentation. This work treats to implement the following methods: GKA (Genetic K-means Algorithm), GFCMA (Genetic FCM Algorithm), PSOKA (PSO and K-means based Clustering Algorithm) and PSOFCM (PSO and FCM based Clustering Algorithm). Besides, as a way to evaluate the results given by the algorithms, clustering validity indexes are used as quantitative measure. Visual and qualitative evaluations are realized also, mainly using data given by the BrainWeb brain simulator as ground truth
Resumo:
Traditional applications of feature selection in areas such as data mining, machine learning and pattern recognition aim to improve the accuracy and to reduce the computational cost of the model. It is done through the removal of redundant, irrelevant or noisy data, finding a representative subset of data that reduces its dimensionality without loss of performance. With the development of research in ensemble of classifiers and the verification that this type of model has better performance than the individual models, if the base classifiers are diverse, comes a new field of application to the research of feature selection. In this new field, it is desired to find diverse subsets of features for the construction of base classifiers for the ensemble systems. This work proposes an approach that maximizes the diversity of the ensembles by selecting subsets of features using a model independent of the learning algorithm and with low computational cost. This is done using bio-inspired metaheuristics with evaluation filter-based criteria
Resumo:
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
Resumo:
The fundamental senses of the human body are: vision, hearing, touch, taste and smell. These senses are the functions that provide our relationship with the environment. The vision serves as a sensory receptor responsible for obtaining information from the outside world that will be sent to the brain. The gaze reflects its attention, intention and interest. Therefore, the estimation of gaze direction, using computer tools, provides a promising alternative to improve the capacity of human-computer interaction, mainly with respect to those people who suffer from motor deficiencies. Thus, the objective of this work is to present a non-intrusive system that basically uses a personal computer and a low cost webcam, combined with the use of digital image processing techniques, Wavelets transforms and pattern recognition, such as artificial neural network models, resulting in a complete system that performs since the image acquisition (including face detection and eye tracking) to the estimation of gaze direction. The obtained results show the feasibility of the proposed system, as well as several feature advantages.