937 resultados para energy auto-correlation function


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This work presents a set of intelligent algorithms with the purpose of correcting calibration errors in sensors and reducting the periodicity of their calibrations. Such algorithms were designed using Artificial Neural Networks due to its great capacity of learning, adaptation and function approximation. Two approaches willbe shown, the firstone uses Multilayer Perceptron Networks to approximate the many shapes of the calibration curve of a sensor which discalibrates in different time points. This approach requires the knowledge of the sensor s functioning time, but this information is not always available. To overcome this need, another approach using Recurrent Neural Networks was proposed. The Recurrent Neural Networks have a great capacity of learning the dynamics of a system to which it was trained, so they can learn the dynamics of a sensor s discalibration. Knowingthe sensor s functioning time or its discalibration dynamics, it is possible to determine how much a sensor is discalibrated and correct its measured value, providing then, a more exact measurement. The algorithms proposed in this work can be implemented in a Foundation Fieldbus industrial network environment, which has a good capacity of device programming through its function blocks, making it possible to have them applied to the measurement process

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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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Background: It was reported that autonomic nervous system function is altered in subjects with chronic obstructive pulmonary disease (COPD). We evaluated short-and long-term fractal exponents of heart rate variability (HRV) in COPD subjects.Patients and methods: We analyzed data from 30 volunteers, who were divided into two groups according to spirometric values: COPD (n = 15) and control (n = 15). For analysis of HRV indices, HRV was recorded beat by beat with the volunteers in the supine position for 30 minutes. We analyzed the linear indices in the time (SDNN [standard deviation of normal to normal] and RMSSD [root-mean square of differences]) and frequency domains (low frequency [LF], high frequency [HF], and LF/HF), and the short-and long-term fractal exponents were obtained by detrended fluctuation analysis. We considered P < 0.05 to be a significant difference.Results: COPD patients presented reduced levels of all linear exponents and decreased short-term fractal exponent (alpha-1: 0.899 +/- 0.18 versus 1.025 +/- 0.09, P = 0.026). There was no significant difference between COPD and control groups in alpha-2 and alpha-1/alpha-2 ratio.Conclusion: COPD subjects present reduced short-term fractal correlation properties of HRV, which indicates that this index can be used for risk stratification, assessment of systemic disease manifestations, and therapeutic procedures to monitor those patients.

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The great majority of analytical models for extragalactic radio sources suppose self-similarity and can be classified into three types: I, II and III. We have developed a model that represents a generalization of most models found in the literature and showed that these three types are particular cases. The model assumes that the area of the head of the jet varies with the jet size according to a power law and the jet luminosity is a function of time. As it is usually done, the basic hypothesis is that there is an equilibrium between the pressure exerted both by the head of the jet and the cocoon walls and the ram pressure of the ambient medium. The equilibrium equations and energy conservation equation allow us to express the size and width of the source and the pressure in the cocoon as a power law and find the respective exponents. All these assumptions can be used to calculate the evolution of the source size, width and radio luminosity. This can then be compared with the observed width-size relation for radio lobes and the power-size (P-D) diagram of both compact (GPS and CSS) and extended sources from the 3CR catalogue. In this work we introduce two important improvement as compared with a previous work: (1)We have put together a larger sample of both compact and extended radio sources

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The effect of finite size on the magnetic properties of ferromagnetic particles systems is a recurrent subject. One of the aspects wide investigated is the superparamagnetic limit where the temperature destroys the magnetic order of ferromagnetic small particles. Above the block temperature the thermal value of the magnetic moment of the particle vanishes, due to thermal fluctuations. The value of the blocking temperature diminishes when the size of the particle is reduced, reflecting the reduction of the anisotropy energy barrier between the uniform states along the uniaxial axis. The increasing demand for high density magnetic media has recently attracted great research interest in periodic arrangements of nanometric ferromagnetics particles, approach in the superparamagnetic limit. An interesting conjecture is the possibility of stabilization of the magnetic order of small ferromagnetic particles (F) by interface coupling with antiferromagnetic (AF) substrate. These F/AF systems may also help to elucidate some details of the effect of exchange bias, because the effect of interface roughness and the paper of domain walls, either in the substrate or the particle, are significantly reduced. We investigate the magnetic phases of small ferromagnetic particles on a antiferromagnetic substrate. We use a self-consistent local field method, incorporating the interface field and the dipole interaction between the spins of the ferromagnetic particle. Our results indicate that increasing the area of the interface favors the formation of the uniform state. Howere above a critical height value appears a state non-uniform is formed where the spins of in the particle s free surface are rotated with respect to the interface spins direction. We discuss the impact of the competition between the dipolar and interface field on the magnetic charge, that controls the field of flux leakage of the particle, and on the format of the hysteresis curves. Our results indicate that the liquid magnetic charge is not a monotonically increasing function of the height of the particle. The exchange bias may display anomalous features, induced for the dipolar field of the spins near the F/AF interface

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Backgroud: Obesity is a major public health problem and is related to the low physical capacity when obese are compared to no-obese people, however the cause of this limitation is not completely understood. The measurement associated of physiological response to the telemetric 6MWT adds information of metabolic and respiratory system for diagnose of the functional limitation. Objective: Analyze physiological, metabolic and ventilatory responses in women with different body fat during the 6MWT. Methods: 32 women (8 non-obese, 8 Overweight, 8 Obese and 8 morbidly obese) were evaluated for anthropometry, lung function and exercise capacity. Results: Morbidly obese walked the shortest distance (400.2±38.7m), had lower VO2/Kg (12.75±3.20l/Kg/min) and lower R (0.74± 0.11) in the 6MWT compared to other groups. Analyses of metabolic (VO2 and VCO2) and respiratory (VE, VT and BF) during the test did not identify differences between groups. The evaluation of cardiac function (O2 pulse) found higher values in the OM (12.3 ± 4.9ml/bat). Conclusion: The OM had worse performance in the 6MWT compared to other groups. The physical performance may be reduced in this population related to a protocol-dependent response because the speed of 6MWT is self-adjusted allows the individual himself select the intensity of the test, making it set at a speed where there is energy saving

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The aging process modifies various systems in the body, leading to changes in mobility, balance and muscle strength. This can cause a drop in the elderly, or not changing the perceived self-efficacy in preventing falls. Objective: To compare the mobility, body balance and muscle performance according to self-efficacy for falls in community-dwelling elderly. Methods: A cross-sectional comparative study with 63 older (65-80 years) community. Were evaluated for identification data and sociodemographic, cognitive screening using the Mini Mental State Examination (MMSE), effective for the fall of Falls Efficacy Scale International Brazil (FES-I-BRAZIL), Mobility through the Timed Up and Go Test , the balance Berg Balance Scale (BBS) and the Modified Clinical Test tests of Sensory Interaction on Balance (mCTSIB), tandem walk (TW) and Sit to Stand (STS) of the Balance Master® System. Finally, muscle performance by using isokinetic dynamometry. Statistical analysis was performed Student t test for comparison between groups, with p value ≤ 0.05. Results: Comparing the elderly with low-efficacy for falls with high-efficacy for falls, we found significant differences only for the variable Timed Up and Go Test (p = 0.04). With regard to data on balance tests were significant differences in the speed of oscillation firm surface eyes open modified Clinical Test of Sensory Interaction on Test of Balance (p = 0.01). Variables to isokinetic dynamometry were no significant differences in movement knee extension, as regards the variables peak torque (p = 0.04) and power (p = 0.03). Conclusion: The results suggest that, compared to older community with low-and high-efficacy for falls, we observed differences in variables related to mobility, balance and muscle function

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The term fatigability concerns the degree of fatigue associated with performing an activity of any type (physical, mental, emotional and / or social). Recently scales for assessing fatigue in the English language were created, however, gaps exist regarding the validity of these scales in relation to oxygen consumption and levels of perceived fatigue. Objective: To investigate the validity of perceived fatigability scale in older women frail and non-frail by the expired gases kinetics. Methods: This is a study of type validation, where were evaluated 48 elderly. The evaluation was conducted at two different sessions. In the first, data were collected demographic partners, as well as assessment of cognitive function, physical health, and the phenotype of frailty. The second was composed by the test 6-minute walk (6MWT) associated the expired gases kinects and assessment of perceived fatigability. Statistical analysis was performed a descriptive analysis and then we used the Pearson correlation test to evaluate the relationship between the measure of perceived fatigue and variables oxygen consumption (VO2), carbon dioxide production (VCO2), respiratory exchange ratio (RER)before and after 6MWT. We used a linear regression model initially considering the following explanatory variable: age, Body Mass Index (BMI), presence of frailty, comorbidities, level of physical activity, distance covered in the 6MWT , the energy cost of walking and severity of fatigability on performance. Results: The final sample consisted of 44 elderly women, 4 elderly were excluded because they didn t complete all phases of this study. The mean age obtained was 75 years (± 7.2 years). There was no significant correlation between fatigability measures and the values of VO2 ( r = .09 , p = .56 ) , VCO2 ( r = .173 , p = .26 ) , RER ( r = - .121 , p = .43 ). The final linear regression model showed that the energy cost of walking, the usual level of physical activity and the performance severity of fatigability explained 83.5 % (R2 = 0.835, p < 0.01) of the variation in the perceived fatigability. Conclusion: Our findings indicate a relationship between greater severity of fatigability and lower levels of physical activity and increased energy cost in walking, suggesting that the fatigability analyses using a simple numeric scale is valid and viable for assessment of fatigue in older women

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A mathematical model was developed in order to study the behavior of thermal stratification of liquid in a typical storage tank with porous medium. The model employs a transient stream function-vorticity formulation to predict the development of stream function and temperature fields in a charging process. Parameters analyzed include Biot, Darcy, Reynolds and Richardson numbers, position, and the thickness of the porous medium. The results show the influence of these physical parameters that should be considered for a good design of storage tanks with thermal stratification.

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Diamond-like carbon (DLC) films were grown from radiofrequency plasmas of acetylene-argon mixtures, at different excitation powers, P. The effects of this parameter on the plasma potential, electron density, electron temperature, and plasma activity were investigated using a Langmuir probe. The mean electron temperature increased from about 0.5 to about 7.0 eV while the mean electron density decreased from about 1.2x10(9) to about 0.2x10(9) cm(-3) as P was increased from 25 to 150 W. Both the plasma potential and the plasma activity were found to increase with increasing P. Through actinometric optical emission spectrometry, the relative concentrations of CH, [CH], and H, [H], in the discharge were mapped as a function of the applied power. A rise in [H] and a fall in [CH] with increasing P were observed and are discussed in relation to the plasma characteristics and the subimplantation model. The optical properties of the films were calculated from ultraviolet-visible spectroscopic data; the surface resistivity was measured by the two-point probe method. The optical gap, E(G), and the surface resistivity, rho(s), fall with increasing P. E(G) and rho(s) are in the ranges of about 2.0-1.3 eV and 10(14)-10(16) Omega/square, respectively. The plasma power also influences the film self-bias, V(b), via a linear dependence, and the effect of V(b) on ion bombardment during growth is addressed together with variation in the relative densities of sp(2) and sp(3) bonds in the films as determined by Raman spectroscopy.

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This paper presents a pole placement method using both the augmented Jacobian and the corresponding system transfer function matrices. From the manipulation of these matrices a straightforward approach results to get the coefficients of a non-linear system, whose solution gives the parameters of the stabilizers that can provide a pre-specified minimum damping to the system. (C) 2001 Elsevier B.V. Ltd. All rights reserved.

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Topics of research related to energy and environment have significantly grown in recent years, with the need of its own energy as hydrogen. More particularly, numerous researches have been focused on hydrogen as energy vector. The main portion of hydrogen is presently obtained by reforming of methane or light hydrocarbons (steam, oxy, dry or auto reforming). During the methane steam reforming process the formation of CO2 undesirable (the main contributor to the greenhouse effect) is observed. Thus, an oxide material (sorbent) can be used to capture the CO2 generated during the process and simultaneously shifting the equilibrium of water gas shift towards thermodynamically more favorable production of pure hydrogen. The aim of this study is to develop a material with dual function (catalyst/sorbent) in the reaction of steam reforming of methane. CaO is well known as CO2 sorbent due to its high efficiency in reactions of carbonation and easy regeneration through calcination. However the kinetic of carbonation decreases quickly with time and carbonation/calcination cycles. A calcium aluminate (Ca12Al14O33) should be used to avoid sintering and increase the stability of CaO sorbents for several cycles. Nickel, the industrial catalyst choice for steam reforming has been added to the support from different manners. These bi-functional materials (sorbent/catalyst) in different molar ratios CaO.Ca12Al14O33 (48:52, 65:35, 75:25, 90:10) were prepared by different synthesis methodologies, among them, especially the method of microwave assisted self-combustion. Synthesis, structure and catalytic performances of Ni- CaO.Ca12Al14O33 synthesized by the novel method (microwave assisted selfcombustion) proposed in this work has not being reported yet in literature. The results indicate that CO2 capture time depends both on the CaO excess and on operating conditions (eg., temperature and H2O/CH4 ratio). To be efficient for CO2 sorption, temperature of steam reforming needs to be lower than 700 °C. An optimized percentage corresponding to 75% of CaO and a ratio H2O/CH4 = 1 provides the most promising results since a smaller amount of water avoids competition between water and CO2 to form carbonate and hydroxide. If this competition is most effective (H2O/CH4 = 3) and would have a smaller amount of CaO available for absorption possibly due to the formation of Ca(OH)2. Therefore, the capture time was higher (16h) for the ratio H2O/CH4 = 1 than H2O/CH4 = 3 (7h) using as catalyst one prepared by impregnating the support obtained by microwave assisted self-combustion. Therefore, it was demonstrated that, with these catalysts, the CO2 sorption on CaO modifies the balance of the water gas-shift reaction. Consequently, steam reforming of CH4 is optimized, producing pure H2, complete conversion of methane and negligible concentration of CO2 and CO during the time of capture even at low temperature (650 °C). This validates the concept of the sorption of CO2 together with methane steam reforming

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Background: Cerebral palsy (CP) presents changes in posture and movement as a core characteristic, which requires therapeutic monitoring during the habilitation or rehabilitation of children. Besides clinical treatment, it is fundamental that professionals use systems of evaluation to quantify the difficulties presented to the individual and assist in the organization of a therapeutic program. The aim of this study was to quantitatively verify the performance of children with spastic di-paresia type CP.Methods: The Pediatric Evaluation of Disability Inventory (PEDI) and Gross Motor Function Classification System (GMFM) tests were used and classification made through the GMFCS in the assessment of 7 patients with CP, 4 females and 3 males, average age of 9 years old.Results: According to GMFCS scales, 17% (n=1) were level II and 83% (n=6) were level III. The PEDI test and 88 GMFM items were used in the area of mobility. We observed that there was high correlation between mobility and gross motor function with Pearson's correlation coefficient =0.929) showing the likely impact of these areas in the functional skills and the quality of life of these patients.Conclusion: We suggest the impact of the limitation of the areas in functional skills and quality of life of these patients.

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In this work, we propose a two-stage algorithm for real-time fault detection and identification of industrial plants. Our proposal is based on the analysis of selected features using recursive density estimation and a new evolving classifier algorithm. More specifically, the proposed approach for the detection stage is based on the concept of density in the data space, which is not the same as probability density function, but is a very useful measure for abnormality/outliers detection. This density can be expressed by a Cauchy function and can be calculated recursively, which makes it memory and computational power efficient and, therefore, suitable for on-line applications. The identification/diagnosis stage is based on a self-developing (evolving) fuzzy rule-based classifier system proposed in this work, called AutoClass. An important property of AutoClass is that it can start learning from scratch". Not only do the fuzzy rules not need to be prespecified, but neither do the number of classes for AutoClass (the number may grow, with new class labels being added by the on-line learning process), in a fully unsupervised manner. In the event that an initial rule base exists, AutoClass can evolve/develop it further based on the newly arrived faulty state data. In order to validate our proposal, we present experimental results from a level control didactic process, where control and error signals are used as features for the fault detection and identification systems, but the approach is generic and the number of features can be significant due to the computationally lean methodology, since covariance or more complex calculations, as well as storage of old data, are not required. The obtained results are significantly better than the traditional approaches used for comparison