Modelagem estocástica do índice de radiação ultravioleta na costa leste do nordeste do Brasil

The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (João Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

Determinação de parâmetros (sólidos solúveis, pH e acidez titulável) em ameixas intactas usando espectroscopia no infravermelho próximo e seleção de comprimento de onda

The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive method to determine the soluble solid content (SSC), pH and titratable acidity of intact plums. Samples of plum with a total solids content ranging from 5.7 to 15%, pH from 2.72 to 3.84 and titratable acidity from 0.88 a 3.6% were collected from supermarkets in Natal-Brazil, and NIR spectra were acquired in the 714 2500 nm range. A comparison of several multivariate calibration techniques with respect to several pre-processing data and variable selection algorithms, such as interval Partial Least Squares (iPLS), genetic algorithm (GA), successive projections algorithm (SPA) and ordered predictors selection (OPS), was performed. Validation models for SSC, pH and titratable acidity had a coefficient of correlation (R) of 0.95 0.90 and 0.80, as well as a root mean square error of prediction (RMSEP) of 0.45ºBrix, 0.07 and 0.40%, respectively. From these results, it can be concluded that NIR spectroscopy can be used as a non-destructive alternative for measuring the SSC, pH and titratable acidity in plums

Método híbrido para detecção e diagnóstico de falhas baseado em resíduos

The detection and diagnosis of faults, ie., find out how , where and why failures occur is an important area of study since man came to be replaced by machines. However, no technique studied to date can solve definitively the problem. Differences in dynamic systems, whether linear, nonlinear, variant or invariant in time, with physical or analytical redundancy, hamper research in order to obtain a unique solution . In this paper, a technique for fault detection and diagnosis (FDD) will be presented in dynamic systems using state observers in conjunction with other tools in order to create a hybrid FDD. A modified state observer is used to create a residue that allows also the detection and diagnosis of faults. A bank of faults signatures will be created using statistical tools and finally an approach using mean squared error ( MSE ) will assist in the study of the behavior of fault diagnosis even in the presence of noise . This methodology is then applied to an educational plant with coupled tanks and other with industrial instrumentation to validate the system.

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

Estimação e previsão no processo INARCH(2)

In the last decades the study of integer-valued time series has gained notoriety due to its broad applicability (modeling the number of car accidents in a given highway, or the number of people infected by a virus are two examples). One of the main interests of this area of study is to make forecasts, and for this reason it is very important to propose methods to make such forecasts, which consist of nonnegative integer values, due to the discrete nature of the data. In this work, we focus on the study and proposal of forecasts one, two and h steps ahead for integer-valued second-order autoregressive conditional heteroskedasticity processes [INARCH (2)], and in determining some theoretical properties of this model, such as the ordinary moments of its marginal distribution and the asymptotic distribution of its conditional least squares estimators. In addition, we study, via Monte Carlo simulation, the behavior of the estimators for the parameters of INARCH(2) processes obtained using three di erent methods (Yule- Walker, conditional least squares, and conditional maximum likelihood), in terms of mean squared error, mean absolute error and bias. We present some forecast proposals for INARCH(2) processes, which are compared again via Monte Carlo simulation. As an application of this proposed theory, we model a dataset related to the number of live male births of mothers living at Riachuelo city, in the state of Rio Grande do Norte, Brazil.

Estimação e previsão no processo INARCH(2)

In the last decades the study of integer-valued time series has gained notoriety due to its broad applicability (modeling the number of car accidents in a given highway, or the number of people infected by a virus are two examples). One of the main interests of this area of study is to make forecasts, and for this reason it is very important to propose methods to make such forecasts, which consist of nonnegative integer values, due to the discrete nature of the data. In this work, we focus on the study and proposal of forecasts one, two and h steps ahead for integer-valued second-order autoregressive conditional heteroskedasticity processes [INARCH (2)], and in determining some theoretical properties of this model, such as the ordinary moments of its marginal distribution and the asymptotic distribution of its conditional least squares estimators. In addition, we study, via Monte Carlo simulation, the behavior of the estimators for the parameters of INARCH(2) processes obtained using three di erent methods (Yule- Walker, conditional least squares, and conditional maximum likelihood), in terms of mean squared error, mean absolute error and bias. We present some forecast proposals for INARCH(2) processes, which are compared again via Monte Carlo simulation. As an application of this proposed theory, we model a dataset related to the number of live male births of mothers living at Riachuelo city, in the state of Rio Grande do Norte, Brazil.

Influência da fadiga no comportamento neuromuscular do quadríceps femoral, após reconstrução do ligamento cruzado anterior

Muscle fatigue is a phenomenon that promotes physiological and biomechanical disorders and their changes in healthy subjects have been widely studied and have significant importance for care in preventing injuries, but we do not have many information about its effects in patients after ACL reconstruction. Thus, this study is to analyze the effects of fatigue on neuromuscular behavior of quadriceps after ACL reconstruction. To reach this objective, participants were forty men, twenty healthy (26,90 ± 6,29 years) and twenty after ACL reconstruction (29,75 ± 7,01 years) with a graft of semitendinosus and gracilis tendons, between four to six months after surgery. At first, there was an assessment of joint position sense (JPS) at the isokinetic dynamometer at a speed of 5°/s and target angle of 45° to analyze the absolute error of JPS. Next, we applied the a muscle fatigue protocol, running 100 repetitions of isokinetic knee flexion-extension at 90°/s. Concurrently with this protocol, there was the assessment of muscle performance, as the peak torque (PT) and fatigue index, and electromyographic activity (RMS and median frequency). Finally, we repeated the assessment of JPS. The statistical analysis showed that patients after ACL reconstruction have, even under normal conditions, the amended JPS compared with healthy subjects and that after fatigue, both have disturbances in the JPS, but this alteration is significantly exacerbated in patients after ACL reconstruction. About muscle performance, we could notice that these patients have a lower PT, although there are no differences between the dynamometric and EMG fatigue index. These findings show the necessity about the cares of pacients with ACL reconstruction in respect of the risks of articulate instability and overload in ligamentar graft

Algoritmo SOM com estrutura hierárquica e dinâmica aplicado a compressão de imagens

ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural network is presented in the form of hierarchical structures, applied to the compression of images. The main objective of this approach is to develop an Hierarchical SOM algorithm with static structure and another one with dynamic structure to generate codebooks (books of codes) in the process of the image Vector Quantization (VQ), reducing the time of processing and obtaining a good rate of compression of images with a minimum degradation of the quality in relation to the original image. Both self-organizing neural networks developed here, were denominated HSOM, for static case, and DHSOM, for the dynamic case. ln the first form, the hierarchical structure is previously defined and in the later this structure grows in an automatic way in agreement with heuristic rules that explore the data of the training group without use of external parameters. For the network, the heuristic mIes determine the dynamics of growth, the pruning of ramifications criteria, the flexibility and the size of children maps. The LBO (Linde-Buzo-Oray) algorithm or K-means, one ofthe more used algorithms to develop codebook for Vector Quantization, was used together with the algorithm of Kohonen in its basic form, that is, not hierarchical, as a reference to compare the performance of the algorithms here proposed. A performance analysis between the two hierarchical structures is also accomplished in this work. The efficiency of the proposed processing is verified by the reduction in the complexity computational compared to the traditional algorithms, as well as, through the quantitative analysis of the images reconstructed in function of the parameters: (PSNR) peak signal-to-noise ratio and (MSE) medium squared error

Previsão do módulo de elasticidade transversal de compósitos unidirecionais através de redes neurais mistas

The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halpín-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed

Desenvolvimento de perfis aerodinâmicos a partir de suas características utilizando redes neurais artificiais

One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoil

Efeito imediato da estimulação elétrica neuromuscular seletiva do músculo VMO em pacientes com síndrome da dor femoropatelar

Patellofemoral pain syndrome (PFPS) is described as anterior or retropatellar pain knee in the absence of other pathologies and is frequently associated with dysfunction of the vastus medialis oblique (VMO). However, several studies have demonstrated the inability to selectively activate this muscle through exercise. To evaluate the effect of Neuromuscular Electrical Stimulation (NMES) selective VMO in women with syndrome. We evaluated thirty-eight women: twenty in the control group (24.15 ± 2.60 years) and eighteen diagnosed with PFPS (25.56 ± 3.55 years). Both groups were evaluated before and after a protocol of electro stimulation. To measure for comparing groups before and after treatment, we assessed the extensor torque concentric and eccentric knee through an isokinetic dynamometer, the intensity (Root Mean Square - RMS) and the onset of activation (onset) of VMO compared to the vastus lateralis (VL) in two types of exercise: open and closed kinetic chain. . Statistical analysis was performed using SPSS 15.0, with a significance level of 5%. Results: Our data showed an increase in the intensity of activation (RMS) of the VMO muscle after NMES in both study groups. During concentric contraction the RMS of the VMO before the NMES was 105.69 ± 32.26 μV and after a single intervention was 122.10 ± 39.62 μV (p = 0.048) for the control group. In the group with PPS, we found a similar behavior, with RMS of the VMO before NMES of 96.25 ± 18.83 μV and 139.80 ± 65.88 μV after the intervention (p = 0.0001). However, there was no evidence in the RMS value of VL muscle. The onset was calculated by subtracting the onset of VL by the onset of VMO. For the group with PFPS, the onset before the intervention was -0.007 ± 0.14 ms, indicating a delay of the VMO relative to VL, and after NMES was 0.074 ± 0.09 ms (p = 0.016), showing an activation previous VMO to VL. The same occurred for the control group. We also observed that NMES increased knee extensor power during the concentric contraction in both groups. Before the intervention the mean power was 28.97 ± 9.01 W for the PPS group and after NMES was 34.38 ± 7.61 W (p = 0.0001). Conclusion: We observed an increase in electromyographic activity of the VMO and also an anticipatory effect of this muscle

Influência do método pilates na força e atividade elétrica dos músculos respiratórios de idosas - ensaio clínico controlado randomizado

The reduction of physiological capacity present in the process of aging causes a marked decline in lung function. The exercise does promote several positive changes in the physical health of people and protect the cardiorespiratory function. The aim of this study was to investigate the effects of a program of Pilates exercices on the strengh and electrical activity of respiratory muscles of elderly. This is a randomized, controlled clinical trial, evaluating 33 elderly aged 65 and 80 (70.88 ± 4.32), healthy, sedentary, without cognitive impairment and able the practice physical activity. The sample was divided into two groups, one experimental group with 16 elderly women who did Pilates exercises and a control group (17) that was not submitted to the exercises, but received educational booklets on aging and health care. The elderly were evaluated initially and after a period of three months, taking into account the Maximal Inspiratory Pressure (MIP) and Maximal Expiratory Pressure (MEP), obtained by Manovacuometry and intensity of EMG activity was measured using the values of Root Mean Square (RMS) for the diaphragm and rectus abdominis muscles, during the course of diaphragmatic breathing and MIP maneuver. Data were analyzed using SPSS version 17.0. For all tests, we used a significance level or p value < 0.05 and confidence interval 95%. RMS in diaphragm and rectus abdominis muscles in both tests increased, but the data were significant for the rectus abdominis during diaphragmatic breathing (p = 0.03) and the diaphragm during the MIP maneuver (p = 0.01). There was no significant variation of the MIP and MEP. Pilates exercises were responsible for increasing the electrical activation of the diaphragm and rectus abdominis muscles in a group of healthy elderly, but had no influence on changes in strength of respiratory muscles

Efeito da crioterapia e da laserterapia na resposta ao dano muscular induzido pelo exercício excêntrico: ensaio clínico e randomizado

Exercise-induced muscle damage mainly affects individuals who returned to physical activity after a time without practicing it or had some kind of exhaustive exercise, particularly eccentric exercise. To evaluate the effect of cryotherapy and laser therapy in response to muscle damage induced by eccentric exercise on the biceps muscle. This was a randomized clinical trial consisting of 60 female subjects. All subjects initially underwent an evaluation consisting of perimetry, measurement of pain sensation (via algometry and visual analogue scale), electromyography and dynamometry. Then the subjects performed an exercise protocol on the isokinetic dynamometer consisting of 2 sets of 10 eccentric elbow flexors contraction at 60 °/s. Completed this protocol, an intervention was held according to a previously random group distribution: control group (no intervention), cryotherapy group and laser therapy group. Finally, subjects were re-evaluated immediately and 48 hours after the intervention protocol, except for Visual Analogue Scale (VAS), which was also evaluated 24 hours after exercise. The circumference of the limb, the pain sensation (VAS and algometry), the muscle activation amplitude (via Root Mean Square - RMS), median frequency, peak torque normalized per body weight, average peak torque, power and work were analyzed. The median frequency immediately after the intervention protocol on the cryotherapy group was the only variable that showed inter and intra-group differences; the remaining variables showed only intragroup differences. The perimetry values did not change immediately after the protocol on the groups which underwent cryotherapy and laser therapy, however, there was an increase after 48 hours; algometry values decreased in all groups for 48 hours and the VAS values increased 24 and 48 hours also for all groups. Regarding RMS no significant change was observed. For dynamometry, peak torque normalized per body weight and average peak torque had a similar behavior, with a reduction in the post protocol that has remained after 48 hours. For the power and work, a decrease was observed immediately after the protocol with a further reduction after 48 hours. Cryotherapy and laser therapy does not alter the muscle damage response, except for the perimetry values immediately after exercise.