Métodos numéricos para resolução de equações diferenciais ordinárias lineares baseados em interpolação por spline

In this work we have elaborated a spline-based method of solution of inicial value problems involving ordinary differential equations, with emphasis on linear equations. The method can be seen as an alternative for the traditional solvers such as Runge-Kutta, and avoids root calculations in the linear time invariant case. The method is then applied on a central problem of control theory, namely, the step response problem for linear EDOs with possibly varying coefficients, where root calculations do not apply. We have implemented an efficient algorithm which uses exclusively matrix-vector operations. The working interval (till the settling time) was determined through a calculation of the least stable mode using a modified power method. Several variants of the method have been compared by simulation. For general linear problems with fine grid, the proposed method compares favorably with the Euler method. In the time invariant case, where the alternative is root calculation, we have indications that the proposed method is competitive for equations of sifficiently high order.

Processamento Inteligente de Sinais de Pressão e Temperatura Adquiridos Através de Sensores Permanentes em Poços de Petróleo

Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization

Avaliação citológica em base líquida de fármacos moduladores estrogênicos

Hormone therapy is an important tool in the treatment of breast cancer and tamoxifen represents one of the most important drugs used in this type of treatment. Recently other drugs based on the inhibition of aromatase had been developed, this enzyme is responsible for the synthesis of estrogenic esteroids from the androgenic ones. The objective of this study would be the development of a quantitative cytological model of murine estral analysis that allowed the characterization of different hormone drugs effect over vaginal epithelium. The technique of monochromatic staining with Evans blue (C.I. 23860) showed to be efficient in the qualitative and quantitative classification of the cycle. It had been observed differences in the cytological standard of animals submitted to the studied drugs; tamoxifen presented a widening of phases of lesser maturation (diestrais), while anastrozole and exemestane increased the duration of the phases of larger maturation (estrais). The data were analysed through a cubical non linear regression (spline) which allowed a better characterization of the drugs, suggesting a proper cytological profile to the antagonism of the estrogen receptor (tamoxifen), aromatase competition (anastrozole) and inhibition of the enzyme (exemestane)

Estimativas de mortalidade para a região nordeste do Brasil em 2010: uma associação do método demográfico equação geral de balanceamento, com o estimador bayesiano empírico

One of the greatest challenges of demography, nowadays, is to obtain estimates of mortality, in a consistent manner, mainly in small areas. The lack of this information, hinders public health actions and leads to impairment of quality of classification of deaths, generating concern on the part of demographers and epidemiologists in obtaining reliable statistics of mortality in the country. In this context, the objective of this work is to obtain estimates of deaths adjustment factors for correction of adult mortality, by States, meso-regions and age groups in the northeastern region, in 2010. The proposal is based on two lines of observation: a demographic one and a statistical one, considering also two areas of coverage in the States of the Northeast region, the meso-regions, as larger areas and counties, as small areas. The methodological principle is to use the General Equation and Balancing demographic method or General Growth Balance to correct the observed deaths, in larger areas (meso-regions) of the states, since they are less prone to breakage of methodological assumptions. In the sequence, it will be applied the statistical empirical Bayesian estimator method, considering as sum of deaths in the meso-regions, the death value corrected by the demographic method, and as reference of observation of smaller area, the observed deaths in small areas (counties). As results of this combination, a smoothing effect on the degree of coverage of deaths is obtained, due to the association with the empirical Bayesian Estimator, and the possibility of evaluating the degree of coverage of deaths by age groups at counties, meso-regions and states levels, with the advantage of estimete adjustment factors, according to the desired level of aggregation. The results grouped by State, point to a significant improvement of the degree of coverage of deaths, according to the combination of the methods with values above 80%. Alagoas (0.88), Bahia (0.90), Ceará (0.90), Maranhão (0.84), Paraíba (0.88), Pernambuco (0.93), Piauí (0.85), Rio Grande do Norte (0.89) and Sergipe (0.92). Advances in the control of the registry information in the health system, linked to improvements in socioeconomic conditions and urbanization of the counties, in the last decade, provided a better quality of information registry of deaths in small areas

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

Otimização de forma aplicando B-splines sob critério integral de tensões

This work proposes a computational methodology to solve problems of optimization in structural design. The application develops, implements and integrates methods for structural analysis, geometric modeling, design sensitivity analysis and optimization. So, the optimum design problem is particularized for plane stress case, with the objective to minimize the structural mass subject to a stress criterion. Notice that, these constraints must be evaluated at a series of discrete points, whose distribution should be dense enough in order to minimize the chance of any significant constraint violation between specified points. Therefore, the local stress constraints are transformed into a global stress measure reducing the computational cost in deriving the optimal shape design. The problem is approximated by Finite Element Method using Lagrangian triangular elements with six nodes, and use a automatic mesh generation with a mesh quality criterion of geometric element. The geometric modeling, i.e., the contour is defined by parametric curves of type B-splines, these curves hold suitable characteristics to implement the Shape Optimization Method, that uses the key points like design variables to determine the solution of minimum problem. A reliable tool for design sensitivity analysis is a prerequisite for performing interactive structural design, synthesis and optimization. General expressions for design sensitivity analysis are derived with respect to key points of B-splines. The method of design sensitivity analysis used is the adjoin approach and the analytical method. The formulation of the optimization problem applies the Augmented Lagrangian Method, which convert an optimization problem constrained problem in an unconstrained. The solution of the Augmented Lagrangian function is achieved by determining the analysis of sensitivity. Therefore, the optimization problem reduces to the solution of a sequence of problems with lateral limits constraints, which is solved by the Memoryless Quasi-Newton Method It is demonstrated by several examples that this new approach of analytical design sensitivity analysis of integrated shape design optimization with a global stress criterion purpose is computationally efficient

Planejamento experimental aplicada a um novo separador líquido-líquido utilizado no tratamento de águas residuais contaminadas com petróleo

The present work had as objective to apply an experimental planning aiming at to improve the efficiency of separation of a new type of mixer-settler applied to treat waste water contaminated with oil. An unity in scale of laboratory, was installed in the Post-graduation Program of Chemical Engineering of UFRN. It was constructed in partnership with Petrobras S.A. This called device Misturador-Decantador a Inversão de Fases (MDIF) , possess features of conventional mixer-settler and spray column type. The equipment is composed of three main parts: mixing chamber; chamber of decantation and chamber of separation. The efficiency of separation is evaluated analyzing the oil concentrations in water in the feed and the output of the device. For the analysis one used the gravimetric method of oil and greases analysis (TOG). The system in study is a water of formation emulsified with oil. The used extractant is a mixture of Turpentine spirit hydro-carbons, supplied for Petrobras. It was applied, for otimization of the efficiency of separation of the equipment, an experimental planning of the composite central type, having as factorial portion fractionary factorial planning 2 5-2, with the magnifying of the type star and five replications in the central point. In this work, the following independents variables were studied: contents of oil in the feed of the device; volumetric ratio (O/A); total flowrate ; agitation in the mixing chamber and height of the organic bed. Minimum and maximum limits for the studied variables had been fixed according previous works. The analysis of variance for the equation of the empirical model, revealed statistically significant and useful results for predictions ends. The variance analysis also presented the distribution of the error as a normal distribution and was observed that as the dispersions do not depend on the levels of the factors, the independence assumption can be verified. The variation around the average is explained by 98.98%, or either, equal to the maximum value, being the smoothing of the model in relation to the experimental points of 0,98981. The results present a strong interaction between the variable oil contents in the feed and agitation in the mixing chamber, having great and positive influence in the separation efficiency. Another variable that presented a great positive influence was the height of the organic bed. The best results of separation efficiency had been obtained for high flowrates when associates the high oil concentrations and high agitation. The results of the present work had shown excellent agreement with the results carried out through previous works with the mixer-settler of phase inversion

Monitoramento em tempo real de processos fermentativos por espectroscopia no infravermelho próximo (NIRS)

A chemical process optimization and control is strongly correlated with the quantity of information can be obtained from the system. In biotechnological processes, where the transforming agent is a cell, many variables can interfere in the process, leading to changes in the microorganism metabolism and affecting the quantity and quality of final product. Therefore, the continuously monitoring of the variables that interfere in the bioprocess, is crucial to be able to act on certain variables of the system, keeping it under desirable operational conditions and control. In general, during a fermentation process, the analysis of important parameters such as substrate, product and cells concentration, is done off-line, requiring sampling, pretreatment and analytical procedures. Therefore, this steps require a significant run time and the use of high purity chemical reagents to be done. In order to implement a real time monitoring system for a benchtop bioreactor, these study was conducted in two steps: (i) The development of a software that presents a communication interface between bioreactor and computer based on data acquisition and process variables data recording, that are pH, temperature, dissolved oxygen, level, foam level, agitation frequency and the input setpoints of the operational parameters of the bioreactor control unit; (ii) The development of an analytical method using near-infrared spectroscopy (NIRS) in order to enable substrate, products and cells concentration monitoring during a fermentation process for ethanol production using the yeast Saccharomyces cerevisiae. Three fermentation runs were conducted (F1, F2 and F3) that were monitored by NIRS and subsequent sampling for analytical characterization. The data obtained were used for calibration and validation, where pre-treatments combined or not with smoothing filters were applied to spectrum data. The most satisfactory results were obtained when the calibration models were constructed from real samples of culture medium removed from the fermentation assays F1, F2 and F3, showing that the analytical method based on NIRS can be used as a fast and effective method to quantify cells, substrate and products concentration what enables the implementation of insitu real time monitoring of fermentation processes

Construção de modelos multivariados para determinação de lipídios totais e unidade em leite em pó comercial utilizando espectroscopia no infravermelho próximo

In this work calibration models were constructed to determine the content of total lipids and moisture in powdered milk samples. For this, used the near-infrared spectroscopy by diffuse reflectance, combined with multivariate calibration. Initially, the spectral data were submitted to correction of multiplicative light scattering (MSC) and Savitzsky-Golay smoothing. Then, the samples were divided into subgroups by application of hierarchical clustering analysis of the classes (HCA) and Ward Linkage criterion. Thus, it became possible to build regression models by partial least squares (PLS) that allowed the calibration and prediction of the content total lipid and moisture, based on the values obtained by the reference methods of Soxhlet and 105 ° C, respectively . Therefore, conclude that the NIR had a good performance for the quantification of samples of powdered milk, mainly by minimizing the analysis time, not destruction of the samples and not waste. Prediction models for determination of total lipids correlated (R) of 0.9955, RMSEP of 0.8952, therefore the average error between the Soxhlet and NIR was ± 0.70%, while the model prediction to content moisture correlated (R) of 0.9184, RMSEP, 0.3778 and error of ± 0.76%

Predição de séries temporais de parâmetros de redes HSPA - WCDMA

With the growing demand of data traffic in the networks of third generation (3G), the mobile operators have attempted to focus resources on infrastructure in places where it identifies a greater need. The channeling investments aim to maintain the quality of service especially in dense urban areas. WCDMA - HSPA parameters Rx Power, RSCP (Received Signal Code Power), Ec/Io (Energy per chip/Interference) and transmission rate (throughput) at the physical layer are analyzed. In this work the prediction of time series on HSPA network is performed. The collection of values of the parameters was performed on a fully operational network through a drive test in Natal - RN, a capital city of Brazil northeastern. The models used for prediction of time series were the Simple Exponential Smoothing, Holt, Holt Winters Additive and Holt Winters Multiplicative. The objective of the predictions of the series is to check which model will generate the best predictions of network parameters WCDMA - HSPA.

Utilização da espectroscopia no infravermelho próximo para o controle de qualidade do camarão (Litopenaeus vannamei)

This work was developed with the objective of proposing a simple, fast and versatile methodological routine using near-infrared spectroscopy (NIR) combined with multivariate analysis for the determination of ash content, moisture, protein and total lipids present in the gray shrimp (Litopenaeus vannamei ) which is conventionally performed gravimetrically after ashing at 550 ° C gravimetrically after drying at 105 ° C for the determination of moisture gravimetrically after a Soxhlet extraction using volumetric and after digestion and distillation Kjedhal respectively. Was first collected the spectra of 63 samples processed boiled shrimp Litopenaeus vannamei species. Then, the determinations by conventional standard methods were carried out. The spectra centered average underwent multiplicative scattering correction of light, smoothing Saviztky-Golay 15 points and first derivative, eliminated the noisy region, the working range was from 1100,36 to 2502,37 nm. Thus, the PLS models for predicting ash showed R 0,9471; 0,1017 and RMSEP RMSEC 0,1548; Moisture R was 0,9241; 2,5483 and RMSEP RMSEC 4,1979; R protein to 0,9201; 1,9391 and RMSEP RMSEC 2,7066; for lipids R 0,8801; 0,2827 and RMSEP RMSEC 0,2329 So that the results showed that the relative errors found between the reference method and the NIR were small and satisfactory. These results are an excellent indication that you can use the NIR to these analyzes, which is quite advantageous, since conventional techniques are time consuming, they spend a lot of reagents and involve a number of professionals, which requires a reasonable runtime while after the validation of the methodology execution using NIR reduces all this time to a few minutes, saving reagents, time and without waste generation, and that this is a non-destructive technique.

Processamento Inteligente de Sinais de Pressão e Temperatura Adquiridos Através de Sensores Permanentes em Poços de Petróleo

Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization