873 resultados para Análise de desempenho


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This paper presents the validation of the Performance Indicator System for Projects under Construction - SIDECC. The goal was to develop a system of performance indicators from the macroergonômica approach, considering criteria of usefulness, practicality and applicability and the concept of continuous improvement in the construction industry. The validation process SIDECC consisted of three distinct models. Modeling I corresponded to the theoretical development and validation of a system of indicators. Modeling II concerns the development and validation of multi- indicator system. For this modeling, we used the Mother of Use and Importance and Multivariate Analysis. Modeling III corresponded to the validation situated, which consisted of a case study of a work of construction of buildings, which were applied and analyzed the results of modeling II. This work resulted in the development of an applied and tested for the construction of an integrated system of performance indicators methodology, involving aspects of production, quality, environmental, health and safety. It is inferred that the SIDECC can be applied, in full or in part, the construction companies as a whole, as well as in other economic sectors

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This work treats of a field research in restaurants of Natal. The principal objective of the research was to verify the companies they would be using some type of acting evaluation with base in no-financial perspectives, that if they assimilated to Balanced Scorecard proposal, in the dimension of the Learning and Growth. In the statistical treatment, the descriptive analysis was accomplished with part of the Descriptive Statistics. The crossed analysis was made with Cluster Analysis employment. It was reached the conclusion that would not be careful to affirm the exact percentile of the ones that they use them referred practices, because there is not an uniform use on the part of the establishments. It is admitted that, even in an informal way, intentionally or not, partly, the companies are been worth of some investigated methods. It is also concluded that the adoption of instruments of that nature can take the companies they advance her/it in competitiveness, strengthening to your continuity possibilities and of growth. The word-key of this healthy work Balanced Scorecard, Knowledge Organizacional, Evaluation of Acting, Strategy and Competitiveness

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This Thesis deals with the performance improvement on hotels that have adopted the ISO 9000 Quality Management Systems. It is researched the Brazilian hotels that have an ISO 9001 registration with an assessment form based on the Balanced Scorecard approach. The main findings are that ISO 9000 provided improvement on the performance of the hotels in general and also in all the BSC perspectives, and that are different perception on managers and directors, what suggests a need for a tool like BSC to register the performance improvements on the same basis. The Thesis contributes to provide information on the performance improvement in hotels, one of the claimed regarding the low ISO 9000 adoption rate in Brazilian hotels

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The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries

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This work addresses issues related to analysis and development of multivariable predictive controllers based on bilinear multi-models. Linear Generalized Predictive Control (GPC) monovariable and multivariable is shown, and highlighted its properties, key features and applications in industry. Bilinear GPC, the basis for the development of this thesis, is presented by the time-step quasilinearization approach. Some results are presented using this controller in order to show its best performance when compared to linear GPC, since the bilinear models represent better the dynamics of certain processes. Time-step quasilinearization, due to the fact that it is an approximation, causes a prediction error, which limits the performance of this controller when prediction horizon increases. Due to its prediction error, Bilinear GPC with iterative compensation is shown in order to minimize this error, seeking a better performance than the classic Bilinear GPC. Results of iterative compensation algorithm are shown. The use of multi-model is discussed in this thesis, in order to correct the deficiency of controllers based on single model, when they are applied in cases with large operation ranges. Methods of measuring the distance between models, also called metrics, are the main contribution of this thesis. Several application results in simulated distillation columns, which are close enough to actual behaviour of them, are made, and the results have shown satisfactory

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The bidimensional periodic structures called frequency selective surfaces have been well investigated because of their filtering properties. Similar to the filters that work at the traditional radiofrequency band, such structures can behave as band-stop or pass-band filters, depending on the elements of the array (patch or aperture, respectively) and can be used for a variety of applications, such as: radomes, dichroic reflectors, waveguide filters, artificial magnetic conductors, microwave absorbers etc. To provide high-performance filtering properties at microwave bands, electromagnetic engineers have investigated various types of periodic structures: reconfigurable frequency selective screens, multilayered selective filters, as well as periodic arrays printed on anisotropic dielectric substrates and composed by fractal elements. In general, there is no closed form solution directly from a given desired frequency response to a corresponding device; thus, the analysis of its scattering characteristics requires the application of rigorous full-wave techniques. Besides that, due to the computational complexity of using a full-wave simulator to evaluate the frequency selective surface scattering variables, many electromagnetic engineers still use trial-and-error process until to achieve a given design criterion. As this procedure is very laborious and human dependent, optimization techniques are required to design practical periodic structures with desired filter specifications. Some authors have been employed neural networks and natural optimization algorithms, such as the genetic algorithms and the particle swarm optimization for the frequency selective surface design and optimization. This work has as objective the accomplishment of a rigorous study about the electromagnetic behavior of the periodic structures, enabling the design of efficient devices applied to microwave band. For this, artificial neural networks are used together with natural optimization techniques, allowing the accurate and efficient investigation of various types of frequency selective surfaces, in a simple and fast manner, becoming a powerful tool for the design and optimization of such structures

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This work presents a study of implementation procedures for multiband microstrip patch antennas characterization, using on wireless communication systems. An artificial neural network multilayer perceptron is used to locate the bands of operational frequencies of the antenna for different geometrics configurations. The antenna is projected, simulated and tested in laboratory. The results obtained are compared in order to validate the performance of archetypes that resulted in a good one agreement in metric terms. The neurocomputationals procedures developed can be extended to other electromagnetic structures of wireless communications systems

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Avaliaram-se consumo, desempenho, parâmetros plasmáticos e características de carcaça de 24 novilhos, 3/4 Simental 1/4 Nelore, com peso médio inicial de 370 kg. As dietas foram compostas por 55% de silagem de milho e diferentes fontes energéticas: milho (MI) e substituição parcial do milho pela casca de soja (CS) ou pelo farelo de gérmen de milho (FGM), tendo como fonte de proteína o farelo de girassol. O período de avaliação de consumo e ganho de peso foi de 49 dias. Foram realizadas amostragens de sangue para mensuração dos parâmetros plasmáticos: glicose, uréia, proteína total e albumina. As meia-carcaças direitas resfriadas foram utilizadas para medir a área de olho de lombo (AOL), a espessura de gordura (EG) e o comprimento de carcaça. As dietas não influenciaram os parâmetros plasmáticos. A média obtida para uréia plasmática foi elevada (26,1 mg/dL). As diferentes fontes energéticas não afetaram o ganho de peso e a conversão alimentar, com médias de 1,15 kg/dia e 9,17 kg de MS ingerida/kg de ganho. Não houve efeito sobre o rendimento de carcaça (52,8% peso final e 63,11% PCV), AOL (63,6 cm²) e EG (4,7 mm). O grão de milho pode ser substituído parcialmente pela casca de soja e pelo farelo de gérmen de milho, em dietas para novilhos em confinamento, sem afetar o desempenho e as características de carcaça, permitindo que a escolha entre esses ingredientes seja realizada pela análise econômica.

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Currently, one of the biggest challenges for the field of data mining is to perform cluster analysis on complex data. Several techniques have been proposed but, in general, they can only achieve good results within specific areas providing no consensus of what would be the best way to group this kind of data. In general, these techniques fail due to non-realistic assumptions about the true probability distribution of the data. Based on this, this thesis proposes a new measure based on Cross Information Potential that uses representative points of the dataset and statistics extracted directly from data to measure the interaction between groups. The proposed approach allows us to use all advantages of this information-theoretic descriptor and solves the limitations imposed on it by its own nature. From this, two cost functions and three algorithms have been proposed to perform cluster analysis. As the use of Information Theory captures the relationship between different patterns, regardless of assumptions about the nature of this relationship, the proposed approach was able to achieve a better performance than the main algorithms in literature. These results apply to the context of synthetic data designed to test the algorithms in specific situations and to real data extracted from problems of different fields

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In this thesis, a frequency selective surface (FSS) consists of a two-dimensional periodic structure mounted on a dielectric substrate, which is capable of selecting signals in one or more frequency bands of interest. In search of better performance, more compact dimensions, low cost manufacturing, among other characteristics, these periodic structures have been continually optimized over time. Due to its spectral characteristics, which are similar to band-stop or band-pass filters, the FSSs have been studied and used in several applications for more than four decades. The design of an FSS with a periodic structure composed by pre-fractal elements facilitates the tuning of these spatial filters and the adjustment of its electromagnetic parameters, enabling a compact design which generally has a stable frequency response and superior performance relative to its euclidean counterpart. The unique properties of geometric fractals have shown to be useful, mainly in the production of antennas and frequency selective surfaces, enabling innovative solutions and commercial applications in microwave range. In recent applications, the FSSs modify the indoor propagation environments (emerging concept called wireless building ). In this context, the use of pre-fractal elements has also shown promising results, allowing a more effective filtering of more than one frequency band with a single-layer structure. This thesis approaches the design of FSSs using pre-fractal elements based on Vicsek, Peano and teragons geometries, which act as band-stop spatial filters. The transmission properties of the periodic surfaces are analyzed to design compact and efficient devices with stable frequency responses, applicable to microwave frequency range and suitable for use in indoor communications. The results are discussed in terms of the electromagnetic effect resulting from the variation of parameters such as: fractal iteration number (or fractal level), scale factor, fractal dimension and periodicity of FSS, according the pre-fractal element applied on the surface. The analysis of the fractal dimension s influence on the resonant properties of a FSS is a new contribution in relation to researches about microwave devices that use fractal geometry. Due to its own characteristics and the geometric shape of the Peano pre-fractal elements, the reconfiguration possibility of these structures is also investigated and discussed. This thesis also approaches, the construction of efficient selective filters with new configurations of teragons pre-fractal patches, proposed to control the WLAN coverage in indoor environments by rejecting the signals in the bands of 2.4~2.5 GHz (IEEE 802.11 b) and 5.0~6.0 GHz (IEEE 802.11a). The FSSs are initially analyzed through simulations performed by commercial software s: Ansoft DesignerTM and HFSSTM. The fractal design methodology is validated by experimental characterization of the built prototypes, using alternatively, different measurement setups, with commercial horn antennas and microstrip monopoles fabricated for low cost measurements

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Ceramic substrates have been investigated by researchers around the world and has achieved a high interest in the scientific community, because they had high dielectric constants and excellent performance in the structures employed. Such ceramics result in miniaturized structures with dimensions well reduced and high radiation efficiency. In this work, we have used a new ceramic material called lead zinc titanate in the form of Zn0,8Pb0,2TiO3, capable of being used as a dielectric substrate in the construction of various structures of antennas. The method used in constructing the ceramic combustion synthesis was Self- Sustained High Temperature (SHS - "Self-Propagating High-Temperature Synthesis") which is defined as a process that uses highly exothermic reactions to produce various materials. Once initiated the reaction area in the reaction mixture, the heat generated is sufficient to become self-sustaining combustion in the form of a wave that propagates converting the reaction mixture into the product of interest. Were analyzed aspects of the formation of the composite Zn0,8Pb0,2TiO3 by SHS powders and characterized. The analysis consisted of determining the parameters of the reaction for the formation of the composite, as the ignition temperature and reaction mechanisms. The production of composite Zn0,8Pb0,2TiO3 by SHS performed in the laboratory, was the result of a total control of combustion temperature and after obtaining the powder began the development of ceramics. The product was obtained in the form of regular, alternating layers of porous ceramics and was obtained by uniaxial pressing. 10 The product was characterized by analysis of dilatometry, X-ray diffraction analysis and scanning electron microscopy. One of the contributions typically defined in this work is the development of a new dielectric material, nevertheless presented previously in the literature. Therefore, the structures of the antennas presented in this work consisted of new dielectric ceramics based Zn0,8Pb0,2TiO3 usually used as dielectric substrate. The materials produced were characterized in the microwave range. These are dielectrics with high relative permittivity and low loss tangent. The Ansoft HFSS, commercial program employee, using the finite element method, and was used for analysis of antennas studied in this work

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In this work, the Markov chain will be the tool used in the modeling and analysis of convergence of the genetic algorithm, both the standard version as for the other versions that allows the genetic algorithm. In addition, we intend to compare the performance of the standard version with the fuzzy version, believing that this version gives the genetic algorithm a great ability to find a global optimum, own the global optimization algorithms. The choice of this algorithm is due to the fact that it has become, over the past thirty yares, one of the more importan tool used to find a solution of de optimization problem. This choice is due to its effectiveness in finding a good quality solution to the problem, considering that the knowledge of a good quality solution becomes acceptable given that there may not be another algorithm able to get the optimal solution for many of these problems. However, this algorithm can be set, taking into account, that it is not only dependent on how the problem is represented as but also some of the operators are defined, to the standard version of this, when the parameters are kept fixed, to their versions with variables parameters. Therefore to achieve good performance with the aforementioned algorithm is necessary that it has an adequate criterion in the choice of its parameters, especially the rate of mutation and crossover rate or even the size of the population. It is important to remember that those implementations in which parameters are kept fixed throughout the execution, the modeling algorithm by Markov chain results in a homogeneous chain and when it allows the variation of parameters during the execution, the Markov chain that models becomes be non - homogeneous. Therefore, in an attempt to improve the algorithm performance, few studies have tried to make the setting of the parameters through strategies that capture the intrinsic characteristics of the problem. These characteristics are extracted from the present state of execution, in order to identify and preserve a pattern related to a solution of good quality and at the same time that standard discarding of low quality. Strategies for feature extraction can either use precise techniques as fuzzy techniques, in the latter case being made through a fuzzy controller. A Markov chain is used for modeling and convergence analysis of the algorithm, both in its standard version as for the other. In order to evaluate the performance of a non-homogeneous algorithm tests will be applied to compare the standard fuzzy algorithm with the genetic algorithm, and the rate of change adjusted by a fuzzy controller. To do so, pick up optimization problems whose number of solutions varies exponentially with the number of variables

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This work presents a theoretical and numerical analysis of Frequency Selective Surfaces (FSS) with elements as rectangular patch, thin dipole and crossed dipole mounted on uniaxial anisotropic dielectric substrate layers for orientations of the optical axis along x, y and z directions. The analysis of these structures is accomplished by combination of the Hertz vector potentials method and the Galerkin's technique, in the Fourier transform-domain, using entire¬domain basis functions. This study consists in the use of one more technique for analysis of FSS on anisotropic dielectric substrate. And presents as the main contribution the introduction of one more project parameter to determinate the transmission and reflection characteristics of periodic structures, from the use of anisotropic dielectric with orientations of the crystal optical axis along x, y and z directions. To validate this analysis, the numerical results of this work are compared to those obtained by other authors, for FSS structures on anisotropic and isotropic dielectric substrates. Also are compared experimental results and the numerical correspondent ones for the FSS isotropic case. The technique proposed in this work is accurate and efficient. ln a second moment, curves are presented for the transmission and reflection characteristics of the FSS structures using conducting patch elements mounted on uniaxial anisotropic dielectric substrate layers with optical axis oriented along x, y and z directions. From analysis of these curves, the performance of the considered FSS structures as function of the optical axis orientation is described

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Com o propósito de avaliar a colhedora Penha CLM-350, visando fornecer subsídios aos projetos e usuários, realizou-se o presente trabalho, onde foi estudada a eficácia do sistema espigador, determinando-se a porcentagem de milho colhido para os diversos tratamentos estudados. Definiu-se um parâmetro adimensional U, que é a relação entre a velocidade periférica dos roletes e a velocidade de deslocamento da colhedora. Procurou-se relacionar as diversos tratamentos U, com os valores percentuais de grãos de milho colhidos e perdidos no solo. Os resultados foram estudados através da análise de variância, empregando-se o teste F, aos níveis de 1% e 5% de probabilidade e o teste Tukey para a comparação estatística entre as médias.

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Blind Source Separation (BSS) refers to the problem of estimate original signals from observed linear mixtures with no knowledge about the sources or the mixing process. Independent Component Analysis (ICA) is a technique mainly applied to BSS problem and from the algorithms that implement this technique, FastICA is a high performance iterative algorithm of low computacional cost that uses nongaussianity measures based on high order statistics to estimate the original sources. The great number of applications where ICA has been found useful reects the need of the implementation of this technique in hardware and the natural paralelism of FastICA favors the implementation of this algorithm on digital hardware. This work proposes the implementation of FastICA on a reconfigurable hardware platform for the viability of it's use in blind source separation problems, more specifically in a hardware prototype embedded in a Field Programmable Gate Array (FPGA) board for the monitoring of beds in hospital environments. The implementations will be carried out by Simulink models and it's synthesizing will be done through the DSP Builder software from Altera Corporation.