67 resultados para Colapso de dados


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Last century Six Sigma Strategy has been the focus of study for many scientists, between the discoveries we have the importance of data process for the free of error product manufactory. So, this work focuses on data quality importance in an enterprise. For this, a descriptive-exploratory study of seventeen pharmacies of manipulations from Rio Grande do Norte was undertaken with the objective to be able to create a base structure model to classify enterprises according to their data bases. Therefore, statistical methods such as cluster and discriminant analyses were used applied to a questionnaire built for this specific study. Data collection identified four group showing strong and weak characteristics for each group and that are differentiated from each other

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This Master of Science Thesis deals with applying DEA (Data Envelopment Analysis) to the academic performance evaluation of graduate programs in Brazil, exploring it on a Mechanical and Production Engineering Program 2001-2003 data. The data used is that of the national assessment carried by CAPES, the governmental body in charge for graduate program assessment and certification. It is used the CCR output oriented DEA model, the CCR-Output with Assurance Region, and Window Analysis. The main findings are first that the CCR has the concerning problem of zero values of weights of outputs that is not appropriate in a sense that a graduate program has the higher efficiency score zeroing some output (e.g., number of academic papers published). Secondly, the Assurance Region method proved useful. Third, the Window Analysis also gave some light to the consistency of the performance in the time frame analysed. Also, the analysis results in the understanding that the Mechanics and Production Engineering should not be assessed jointly like currently applied by CAPES and rather should be assessed in its own field separately. Finally, the result of the DEA analysis showed some serious inconsistencies with the CAPES method. Graduate programs considered excellent has got low performance score and vice versa. This Thesis provides a strong argument in order to use DEA at least as a complimentary methodology for graduate program performance evaluation in Brazil

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The objective of this thesis is proposes a method for a mobile robot to build a hybrid map of an indoor, semi-structured environment. The topological part of this map deals with spatial relationships among rooms and corridors. It is a topology-based map, where the edges of the graph are rooms or corridors, and each link between two distinct edges represents a door. The metric part of the map consists in a set of parameters. These parameters describe a geometric figure which adapts to the free space of the local environment. This figure is calculated by a set of points which sample the boundaries of the local free space. These points are obtained with range sensors and with knowledge about the robot s pose. A method based on generalized Hough transform is applied to this set of points in order to obtain the geomtric figure. The building of the hybrid map is an incremental procedure. It is accomplished while the robot explores the environment. Each room is associated with a metric local map and, consequently, with an edge of the topo-logical map. During the mapping procedure, the robot may use recent metric information of the environment to improve its global or relative pose

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This graduate thesis proposes a model to asynchronously replicate heterogeneous databases. This model singularly combines -in a systematic way and in a single project -different concepts, techniques and paradigms related to the areas of database replication and management of heterogeneous databases. One of the main advantages of the replication is to allow applications to continue to process information, during time intervals when they are off the network and to trigger the database synchronization, as soon as the network connection is reestablished. Therefore, the model introduces a communication and update protocol that takes in consideration the environment of asynchronous characteristics used. As part of the work, a tool was developed in Java language, based on the model s premises in order to process, test, simulate and validate the proposed model

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In recent decades, changes have been occurring in the telecommunications industry, allied to competition driven by the policies of privatization and concessions, have fomented the world market irrefutably causing the emergence of a new reality. The reflections in Brazil have become evident due to the appearance of significant growth rates, getting in 2012 to provide a net operating income of 128 billion dollars, placing the country among the five major powers in the world in mobile communications. In this context, an issue of increasing importance to the financial health of companies is their ability to retain their customers, as well as turn them into loyal customers. The appearance of infidelity from customer operators has been generating monthly rates shutdowns about two to four percent per month accounting for business management one of its biggest challenges, since capturing a new customer has meant an expenditure greater than five times to retention. For this purpose, models have been developed by means of structural equation modeling to identify the relationships between the various determinants of customer loyalty in the context of services. The original contribution of this thesis is to develop a model for loyalty from the identification of relationships between determinants of satisfaction (latent variables) and the inclusion of attributes that determine the perceptions of service quality for the mobile communications industry, such as quality, satisfaction, value, trust, expectation and loyalty. It is a qualitative research which will be conducted with customers of operators through simple random sampling technique, using structured questionnaires. As a result, the proposed model and statistical evaluations should enable operators to conclude that customer loyalty is directly influenced by technical and operational quality of the services offered, as well as provide a satisfaction index for the mobile communication segment

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This work presents simulation results of an identification platform compatible with the INPE Brazilian Data Collection System, modeled with SystemC-AMS. SystemC-AMS that is a library of C++ classes dedicated to the simulation of heterogeneous systems, offering a powerful resource to describe models in digital, analog and RF domains, as well as mechanical and optic. The designed model was divided in four parts. The first block takes into account the satellite s orbit, necessary to correctly model the propagation channel, including Doppler effect, attenuation and thermal noise. The identification block detects the satellite presence. It is composed by low noise amplifier, band pass filter, power detector and logic comparator. The controller block is responsible for enabling the RF transmitter when the presence of the satellite is detected. The controller was modeled as a Petri net, due to the asynchronous nature of the system. The fourth block is the RF transmitter unit, which performs the modulation of the information in BPSK ±60o. This block is composed by oscillator, mixer, adder and amplifier. The whole system was simulated simultaneously. The results are being used to specify system components and to elaborate testbenchs for design verification

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We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results

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Digital signal processing (DSP) aims to extract specific information from digital signals. Digital signals are, by definition, physical quantities represented by a sequence of discrete values and from these sequences it is possible to extract and analyze the desired information. The unevenly sampled data can not be properly analyzed using standard techniques of digital signal processing. This work aimed to adapt a technique of DSP, the multiresolution analysis, to analyze unevenly smapled data, to aid the studies in the CoRoT laboratory at UFRN. The process is based on re-indexing the wavelet transform to handle unevenly sampled data properly. The was efective presenting satisfactory results

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The last years have presented an increase in the acceptance and adoption of the parallel processing, as much for scientific computation of high performance as for applications of general intention. This acceptance has been favored mainly for the development of environments with massive parallel processing (MPP - Massively Parallel Processing) and of the distributed computation. A common point between distributed systems and MPPs architectures is the notion of message exchange, that allows the communication between processes. An environment of message exchange consists basically of a communication library that, acting as an extension of the programming languages that allow to the elaboration of applications parallel, such as C, C++ and Fortran. In the development of applications parallel, a basic aspect is on to the analysis of performance of the same ones. Several can be the metric ones used in this analysis: time of execution, efficiency in the use of the processing elements, scalability of the application with respect to the increase in the number of processors or to the increase of the instance of the treat problem. The establishment of models or mechanisms that allow this analysis can be a task sufficiently complicated considering parameters and involved degrees of freedom in the implementation of the parallel application. An joined alternative has been the use of collection tools and visualization of performance data, that allow the user to identify to points of strangulation and sources of inefficiency in an application. For an efficient visualization one becomes necessary to identify and to collect given relative to the execution of the application, stage this called instrumentation. In this work it is presented, initially, a study of the main techniques used in the collection of the performance data, and after that a detailed analysis of the main available tools is made that can be used in architectures parallel of the type to cluster Beowulf with Linux on X86 platform being used libraries of communication based in applications MPI - Message Passing Interface, such as LAM and MPICH. This analysis is validated on applications parallel bars that deal with the problems of the training of neural nets of the type perceptrons using retro-propagation. The gotten conclusions show to the potentiality and easinesses of the analyzed tools.

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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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The control of industrial processes has become increasingly complex due to variety of factory devices, quality requirement and market competition. Such complexity requires a large amount of data to be treated by the three levels of process control: field devices, control systems and management softwares. To use data effectively in each one of these levels is extremely important to industry. Many of today s industrial computer systems consist of distributed software systems written in a wide variety of programming languages and developed for specific platforms, so, even more companies apply a significant investment to maintain or even re-write their systems for different platforms. Furthermore, it is rare that a software system works in complete isolation. In industrial automation is common that, software had to interact with other systems on different machines and even written in different languages. Thus, interoperability is not just a long-term challenge, but also a current context requirement of industrial software production. This work aims to propose a middleware solution for communication over web service and presents an user case applying the solution developed to an integrated system for industrial data capture , allowing such data to be available simplified and platformindependent across the network

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Crude oil is a complex liquid mixture of organic and inorganic compounds that are dominated by hydrocarbons. It is a mixture of alkanes from the simplest to more complex aromatic compounds that are present derivatives such as gasoline, diesel, alcohol, kerosene, naphtha, etc.. These derivatives are extracted from any oil, however, only with a very high quality, in other words, when the content of hydrocarbons of low molecular weight is high means that production of these compounds is feasible. The American Petroleum Institute (API) developed a classification system for the various types of oil. In Brazil, the quality of most of the oil taken from wells is very low, so it is necessary to generate new technology to develop best practices for refining in order to produce petroleum products of higher commercial value. Therefore, it is necessary to study the thermodynamic equilibrium properties of its derivative compounds of interest. This dissertation aims to determine vapor-liquid equilibrium (VLE) data for the systems Phenilcyclohexane - CO2, and Cyclohexane - Phenilcyclohexane - CO2 at high pressure and temperatures between 30 to 70oC. Furthermore, comparisons between measured VLE experimental data from this work and from the literature in relation to the Peng- Robinson molecular thermodynamic model, using a simulation program SPECS IVCSEP v5.60 and two adjustable interaction parameters, have been performed for modeling and simulation purposes. Finally, the developed apparatus for determination of phase equilibrium data at high pressures is presented

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The objective of this work was the development and improvement of the mathematical models based on mass and heat balances, representing the drying transient process fruit pulp in spouted bed dryer with intermittent feeding. Mass and energy balance for drying, represented by a system of differential equations, were developed in Fortran language and adapted to the condition of intermittent feeding and mass accumulation. Were used the DASSL routine (Differential Algebraic System Solver) for solving the differential equation system and used a heuristic optimization algorithm in parameter estimation, the Particle Swarm algorithm. From the experimental data food drying, the differential models were used to determine the quantity of water and the drying air temperature at the exit of a spouted bed and accumulated mass of powder in the dryer. The models were validated using the experimental data of drying whose operating conditions, air temperature, flow rate and time intermittency, varied within the limits studied. In reviewing the results predicted, it was found that these models represent the experimental data of the kinetics of production and accumulation of powder and humidity and air temperature at the outlet of the dryer

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In the present work are established initially the fundamental relationships of thermodynamics that govern the equilibrium between phases, the models used for the description of the behavior non ideal of the liquid and vapor phases in conditions of low pressures. This work seeks the determination of vapor-liquid equilibrium (VLE) data for a series of multicomponents mixtures of saturated aliphatic hydrocarbons, prepared synthetically starting from substances with analytical degree and the development of a new dynamic cell with circulation of the vapor phase. The apparatus and experimental procedures developed are described and applied for the determination of VLE data. VLE isobarics data were obtained through a Fischer s ebulliometer of circulation of both phases, for the systems pentane + dodecane, heptane + dodecane and decane + dodecane. Using the two new dynamic cells especially projected, of easy operation and low cost, with circulation of the vapor phase, data for the systems heptane + decane + dodecane, acetone + water, tween 20 + dodecane, phenol + water and distillation curves of a gasoline without addictive were measured. Compositions of the equilibrium phases were found by densimetry, chromatography, and total organic carbon analyzer. Calibration curves of density versus composition were prepared from synthetic mixtures and the behavior excess volumes were evaluated. The VLE data obtained experimentally for the hydrocarbon and aqueous systems were submitted to the test of thermodynamic consistency, as well as the obtained from the literature data for another binary systems, mainly in the bank DDB (Dortmund Data Bank), where the Gibbs-Duhem equation is used obtaining a satisfactory data base. The results of the thermodynamic consistency tests for the binary and ternary systems were evaluated in terms of deviations for applications such as model development. Later, those groups of data (tested and approved) were used in the KijPoly program for the determination of the binary kij parameters of the cubic equations of state original Peng-Robinson and with the expanded alpha function. These obtained parameters can be applied for simulation of the reservoirs petroleum conditions and of the several distillation processes found in the petrochemistry industry, through simulators. The two designed dynamic cells used equipments of national technology for the determination of VLE data were well succeed, demonstrating efficiency and low cost. Multicomponents systems, mixtures of components of different molecular weights and also diluted solutions may be studied in these developed VLE cells