7 resultados para Non-Ideal Duffing System
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
La recherche prend comme point de départ la dimension formative du mémoire de formation, considerée comme constitutive de l´écriture de soi, et cherche à problématiser cette dimension au tour du questionnement suivant: Comment le mémoire de formation devient-il un instrument de recherche-action-formation? Les analyses s´appuient sur les principes théoriques du paradigme anthropoformateur, proposé par Pineau (2005), les études réalisées par Passeggi (2006ª, 2006b, 2007, 2008ª, 2008b) sur les mémoires, les travaux de recherche de Nóvoa (1988, 1995), de Josso (2004), de Souza (2006) et de Fontana (2000), qui conçoivent la formação du point de vue de l´ apprenant. L´univers de la recherche s´est circonscrit à la situation de formation des éducateurs de la zone rurale, étudiants en Pédagogie dans le PROFORMAÇÃO (CAMEAM), à l´Univeristé de l´Etat du Rio Grande du Nord (UERN), pendant le second semestre de 2005. La recherche a croisé diférents types de démarche pour recueillir les données empiriques: l´observation du processus d´élaboration des mémoires; un questionnaire; des entretiens informels avec les enseignants en formation et avec les formateurs; et 09 mémoires, écrits par les participants de la recherche. Les analyses des données empiriques montrent que l´écriture des mémoires, en tant que démarche de recherche-action-formation, révelent que la dimension formative se dédouble en d´autres dimensions: etnosociologique, heuristique, herméneutique, social et afective, autopoiétique et politique. Dans la quête de soi (recherche), mise en oeuvre dans et par l´écriture (action), chaque narrateur construit de nouveaux sens à la vie et (re)signifient les représentations de soi (formation). Les résultats confirment la richesse et les potentialités du mémoire, même dans des conditions non ideal, ce qui permet d´affirmer as valeur travail académique important dans la formation des enseignants
Resumo:
The present work presents the study and implementation of an adaptive bilinear compensated generalized predictive controller. This work uses conventional techniques of predictive control and includes techniques of adaptive control for better results. In order to solve control problems frequently found in the chemical industry, bilinear models are considered to represent the dynamics of the studied systems. Bilinear models are simpler than general nonlinear model, however it can to represent the intrinsic not-linearities of industrial processes. The linearization of the model, by the approach to time step quasilinear , is used to allow the application of the equations of the generalized predictive controller (GPC). Such linearization, however, generates an error of prediction, which is minimized through a compensation term. The term in study is implemented in an adaptive form, due to the nonlinear relationship between the input signal and the prediction error.Simulation results show the efficiency of adaptive predictive bilinear controller in comparison with the conventional.
Resumo:
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
Resumo:
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
Resumo:
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 Humberto Neves Maia de Oliveira Tese de Doutorado PPGEQ/PRH-ANP 14/UFRN 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
Resumo:
Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.
Resumo:
Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.