991 resultados para Linear variable filters


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Groundwater systems of different densities are often mathematically modeled to understand and predict environmental behavior such as seawater intrusion or submarine groundwater discharge. Additional data collection may be justified if it will cost-effectively aid in reducing the uncertainty of a model's prediction. The collection of salinity, as well as, temperature data could aid in reducing predictive uncertainty in a variable-density model. However, before numerical models can be created, rigorous testing of the modeling code needs to be completed. This research documents the benchmark testing of a new modeling code, SEAWAT Version 4. The benchmark problems include various combinations of density-dependent flow resulting from variations in concentration and temperature. The verified code, SEAWAT, was then applied to two different hydrological analyses to explore the capacity of a variable-density model to guide data collection. ^ The first analysis tested a linear method to guide data collection by quantifying the contribution of different data types and locations toward reducing predictive uncertainty in a nonlinear variable-density flow and transport model. The relative contributions of temperature and concentration measurements, at different locations within a simulated carbonate platform, for predicting movement of the saltwater interface were assessed. Results from the method showed that concentration data had greater worth than temperature data in reducing predictive uncertainty in this case. Results also indicated that a linear method could be used to quantify data worth in a nonlinear model. ^ The second hydrological analysis utilized a model to identify the transient response of the salinity, temperature, age, and amount of submarine groundwater discharge to changes in tidal ocean stage, seasonal temperature variations, and different types of geology. The model was compared to multiple kinds of data to (1) calibrate and verify the model, and (2) explore the potential for the model to be used to guide the collection of data using techniques such as electromagnetic resistivity, thermal imagery, and seepage meters. Results indicated that the model can be used to give insight to submarine groundwater discharge and be used to guide data collection. ^

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Mixtures of Zellner's g-priors have been studied extensively in linear models and have been shown to have numerous desirable properties for Bayesian variable selection and model averaging. Several extensions of g-priors to Generalized Linear Models (GLMs) have been proposed in the literature; however, the choice of prior distribution of g and resulting properties for inference have received considerably less attention. In this paper, we extend mixtures of g-priors to GLMs by assigning the truncated Compound Confluent Hypergeometric (tCCH) distribution to 1/(1+g) and illustrate how this prior distribution encompasses several special cases of mixtures of g-priors in the literature, such as the Hyper-g, truncated Gamma, Beta-prime, and the Robust prior. Under an integrated Laplace approximation to the likelihood, the posterior distribution of 1/(1+g) is in turn a tCCH distribution, and approximate marginal likelihoods are thus available analytically. We discuss the local geometric properties of the g-prior in GLMs and show that specific choices of the hyper-parameters satisfy the various desiderata for model selection proposed by Bayarri et al, such as asymptotic model selection consistency, information consistency, intrinsic consistency, and measurement invariance. We also illustrate inference using these priors and contrast them to others in the literature via simulation and real examples.

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In this thesis, novel analog-to-digital and digital-to-analog generalized time-interleaved variable bandpass sigma-delta modulators are designed, analysed, evaluated and implemented that are suitable for high performance data conversion for a broad-spectrum of applications. These generalized time-interleaved variable bandpass sigma-delta modulators can perform noise-shaping for any centre frequency from DC to Nyquist. The proposed topologies are well-suited for Butterworth, Chebyshev, inverse-Chebyshev and elliptical filters, where designers have the flexibility of specifying the centre frequency, bandwidth as well as the passband and stopband attenuation parameters. The application of the time-interleaving approach, in combination with these bandpass loop-filters, not only overcomes the limitations that are associated with conventional and mid-band resonator-based bandpass sigma-delta modulators, but also offers an elegant means to increase the conversion bandwidth, thereby relaxing the need to use faster or higher-order sigma-delta modulators. A step-by-step design technique has been developed for the design of time-interleaved variable bandpass sigma-delta modulators. Using this technique, an assortment of lower- and higher-order single- and multi-path generalized A/D variable bandpass sigma-delta modulators were designed, evaluated and compared in terms of their signal-to-noise ratios, hardware complexity, stability, tonality and sensitivity for ideal and non-ideal topologies. Extensive behavioural-level simulations verified that one of the proposed topologies not only used fewer coefficients but also exhibited greater robustness to non-idealties. Furthermore, second-, fourth- and sixth-order single- and multi-path digital variable bandpass digital sigma-delta modulators are designed using this technique. The mathematical modelling and evaluation of tones caused by the finite wordlengths of these digital multi-path sigmadelta modulators, when excited by sinusoidal input signals, are also derived from first principles and verified using simulation and experimental results. The fourth-order digital variable-band sigma-delta modulator topologies are implemented in VHDL and synthesized on Xilinx® SpartanTM-3 Development Kit using fixed-point arithmetic. Circuit outputs were taken via RS232 connection provided on the FPGA board and evaluated using MATLAB routines developed by the author. These routines included the decimation process as well. The experiments undertaken by the author further validated the design methodology presented in the work. In addition, a novel tunable and reconfigurable second-order variable bandpass sigma-delta modulator has been designed and evaluated at the behavioural-level. This topology offers a flexible set of choices for designers and can operate either in single- or dual-mode enabling multi-band implementations on a single digital variable bandpass sigma-delta modulator. This work is also supported by a novel user-friendly design and evaluation tool that has been developed in MATLAB/Simulink that can speed-up the design, evaluation and comparison of analog and digital single-stage and time-interleaved variable bandpass sigma-delta modulators. This tool enables the user to specify the conversion type, topology, loop-filter type, path number and oversampling ratio.

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In this work the split-field finite-difference time-domain method (SF-FDTD) has been extended for the analysis of two-dimensionally periodic structures with third-order nonlinear media. The accuracy of the method is verified by comparisons with the nonlinear Fourier Modal Method (FMM). Once the formalism has been validated, examples of one- and two-dimensional nonlinear gratings are analysed. Regarding the 2D case, the shifting in resonant waveguides is corroborated. Here, not only the scalar Kerr effect is considered, the tensorial nature of the third-order nonlinear susceptibility is also included. The consideration of nonlinear materials in this kind of devices permits to design tunable devices such as variable band filters. However, the third-order nonlinear susceptibility is usually small and high intensities are needed in order to trigger the nonlinear effect. Here, a one-dimensional CBG is analysed in both linear and nonlinear regime and the shifting of the resonance peaks in both TE and TM are achieved numerically. The application of a numerical method based on the finite- difference time-domain method permits to analyse this issue from the time domain, thus bistability curves are also computed by means of the numerical method. These curves show how the nonlinear effect modifies the properties of the structure as a function of variable input pump field. When taking the nonlinear behaviour into account, the estimation of the electric field components becomes more challenging. In this paper, we present a set of acceleration strategies based on parallel software and hardware solutions.

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The aims of this thesis were evaluation the type of wave channel, wave current, and effect of some parameters on them and identification and comparison between types of wave maker in laboratory situations. In this study, designing and making of two dimension channels (flume) and wave maker for experiment son the marine buoy, marine building and energy conversion systems were also investigated. In current research, the physical relation between pump and pumpage and the designing of current making in flume were evaluated. The related calculation for steel building, channels beside glasses and also equations of wave maker plate movement, power of motor and absorb wave(co astal slope) were calculated. In continue of this study, the servo motor was designed and applied for moving of wave maker’s plate. One Ball Screw Leaner was used for having better movement mechanisms of equipment and convert of the around movement to linear movement. The Programmable Logic Controller (PLC) was also used for control of wave maker system. The studies were explained type of ocean energies and energy conversion systems. In another part of this research, the systems of energy resistance in special way of Oscillating Water Column (OWC) were explained and one sample model was designed and applied in hydrolic channel at the Sheikh Bahaii building in Azad University, Science and Research Branch. The dimensions of designed flume was considered at 16 1.98 0. 57 m which had ability to provide regular waves as well as irregular waves with little changing on the control system. The ability of making waves was evaluated in our designed channel and the results were showed that all of the calculation in designed flume was correct. The mean of error between our results and theory calculation was conducted 7%, which was showed the well result in this situation. With evaluating of designed OWC model and considering of changes in the some part of system, one bigger sample of this model can be used for designing the energy conversion system model. The obtained results showed that the best form for chamber in exit position of system, were zero degree (0) in angle for moving below part, forty and five (45) degree in front wall of system and the moving forward of front wall keep in two times of height of wave.

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We propose a positive, accurate moment closure for linear kinetic transport equations based on a filtered spherical harmonic (FP_N) expansion in the angular variable. The FP_N moment equations are accurate approximations to linear kinetic equations, but they are known to suffer from the occurrence of unphysical, negative particle concentrations. The new positive filtered P_N (FP_N+) closure is developed to address this issue. The FP_N+ closure approximates the kinetic distribution by a spherical harmonic expansion that is non-negative on a finite, predetermined set of quadrature points. With an appropriate numerical PDE solver, the FP_N+ closure generates particle concentrations that are guaranteed to be non-negative. Under an additional, mild regularity assumption, we prove that as the moment order tends to infinity, the FP_N+ approximation converges, in the L2 sense, at the same rate as the FP_N approximation; numerical tests suggest that this assumption may not be necessary. By numerical experiments on the challenging line source benchmark problem, we confirm that the FP_N+ method indeed produces accurate and non-negative solutions. To apply the FP_N+ closure on problems at large temporal-spatial scales, we develop a positive asymptotic preserving (AP) numerical PDE solver. We prove that the propose AP scheme maintains stability and accuracy with standard mesh sizes at large temporal-spatial scales, while, for generic numerical schemes, excessive refinements on temporal-spatial meshes are required. We also show that the proposed scheme preserves positivity of the particle concentration, under some time step restriction. Numerical results confirm that the proposed AP scheme is capable for solving linear transport equations at large temporal-spatial scales, for which a generic scheme could fail. Constrained optimization problems are involved in the formulation of the FP_N+ closure to enforce non-negativity of the FP_N+ approximation on the set of quadrature points. These optimization problems can be written as strictly convex quadratic programs (CQPs) with a large number of inequality constraints. To efficiently solve the CQPs, we propose a constraint-reduced variant of a Mehrotra-predictor-corrector algorithm, with a novel constraint selection rule. We prove that, under appropriate assumptions, the proposed optimization algorithm converges globally to the solution at a locally q-quadratic rate. We test the algorithm on randomly generated problems, and the numerical results indicate that the combination of the proposed algorithm and the constraint selection rule outperforms other compared constraint-reduced algorithms, especially for problems with many more inequality constraints than variables.

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To know how marketing variables affect customer value is essential for a company in order to be market and customer oriented, and to improve investment efficiency in both attracting and retaining customers. Thus, the assessment of the influence of marketing variables in customer value is of prime importance. This is recognized in many empirical studies of these variables, which address the impact of a single variable (or sets of a few variables) on customer value. A comprehensive, integrated assessment of all marketing variables and their interdependencies is an arduous and complex task for researchers and marketing managers. This research proposes a theoretical model of customer value that takes into account all significant marketing variables that have been partially addressed in empirical investigations of other researchers. These marketing variables include brand and reputation, point of sale, employees, price, termination fee commitment, discounts, complementarity of products, experiences, emotions, perceived value, quality, satisfaction, switching costs, and loyalty. The model incorporates the relationship between each variable with retention and with customer value as well as the relationships between them. A special focus is placed on the empirical analysis of the termination fee commitment and its relationship with customer value. This variable is widely used in the telecommunication’s industry for its influence on customer retention from the moment of purchase. However, there is strikingly little research in this topic. A large customer database of a telecommunications company containing five years information about 63.165 customers is used for this purpose. Multivariate linear regression and ANOVA method are applied...

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In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

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In recent years, vehicle acoustics have gained significant importance in new car development: increasingly advanced infotainment systems for spatial audio and sound enhancement algorithms have become the norm in modern vehicles. In the past, car manufacturers had to build numerous prototypes to study the sound behaviour inside the car cabin or the effect of new algorithms under development. Nowadays, advanced simulation techniques can reduce development costs and time. In this work, after selecting the reference test vehicle, a modern luxury sedan equipped with a high-end sound system, two independent tools were developed: a simulation tool created in the Comsol Multiphysics environment and an auralization tool developed in the Cycling ‘74 MAX environment. The simulation tool can calculate the impulse response and acoustic spectrum at a specific position inside the cockpit. Its input data are the vehicle’s geometry, acoustic absorption parameters of materials, the acoustic characteristics and position of loudspeakers, and the type and position of virtual microphones (or microphone arrays). The simulation tool can also provide binaural impulse responses thanks to Head Related Transfer Functions (HRTFs) and an innovative algorithm able to compute the HRTF at any distance and angle from the head. Impulse responses from simulations or acoustic measurements inside the car cabin are processed and fed into the auralization tool, enabling real-time interaction by applying filters, changing the channels gain or displaying the acoustic spectrum. Since the acoustic simulation of a vehicle involves multiple topics, the focus of this work has not only been the development of two tools but also the study and application of new techniques for acoustic characterization of the materials that compose the cockpit and the loudspeaker simulation. Specifically, three different methods have been applied for material characterization through the use of a pressure-velocity probe, a Laser Doppler Vibrometer (LDV), and a microphone array.

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This study investigated the effect of simulated microwave disinfection (SMD) on the linear dimensional changes, hardness and impact strength of acrylic resins under different polymerization cycles. Metal dies with referential points were embedded in flasks with dental stone. Samples of Classico and Vipi acrylic resins were made following the manufacturers' recommendations. The assessed polymerization cycles were: A-- water bath at 74ºC for 9 h; B-- water bath at 74ºC for 8 h and temperature increased to 100ºC for 1 h; C-- water bath at 74ºC for 2 h and temperature increased to 100ºC for 1 h;; and D-- water bath at 120ºC and pressure of 60 pounds. Linear dimensional distances in length and width were measured after SMD and water storage at 37ºC for 7 and 30 days using an optical microscope. SMD was carried out with the samples immersed in 150 mL of water in an oven (650 W for 3 min). A load of 25 gf for 10 sec was used in the hardness test. Charpy impact test was performed with 40 kpcm. Data were submitted to ANOVA and Tukey's test (5%). The Classico resin was dimensionally steady in length in the A and D cycles for all periods, while the Vipi resin was steady in the A, B and C cycles for all periods. The Classico resin was dimensionally steady in width in the C and D cycles for all periods, and the Vipi resin was steady in all cycles and periods. The hardness values for Classico resin were steady in all cycles and periods, while the Vipi resin was steady only in the C cycle for all periods. Impact strength values for Classico resin were steady in the A, C and D cycles for all periods, while Vipi resin was steady in all cycles and periods. SMD promoted different effects on the linear dimensional changes, hardness and impact strength of acrylic resins submitted to different polymerization cycles when after SMD and water storage were considered.

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This study investigated the effect of simulated microwave disinfection (SMD) on the linear dimensional changes, hardness and impact strength of acrylic resins under different polymerization cycles. Metal dies with referential points were embedded in flasks with dental stone. Samples of Classico and Vipi acrylic resins were made following the manufacturers' recommendations. The assessed polymerization cycles were: A) water bath at 74 ºC for 9 h; B) water bath at 74 ºC for 8 h and temperature increased to 100 ºC for 1 h; C) water bath at 74 ºC for 2 h and temperature increased to 100 ºC for 1 h; and D) water bath at 120 ºC and pressure of 60 pounds. Linear dimensional distances in length and width were measured after SMD and water storage at 37 ºC for 7 and 30 days using an optical microscope. SMD was carried out with the samples immersed in 150 mL of water in an oven (650 W for 3 min). A load of 25 gf for 10 s was used in the hardness test. Charpy impact test was performed with 40 kpcm. Data were submitted to ANOVA and Tukey's test (5%). The Classico resin was dimensionally steady in length in the A and D cycles for all periods, while the Vipi resin was steady in the A, B and C cycles for all periods. The Classico resin was dimensionally steady in width in the C and D cycles for all periods, and the Vipi resin was steady in all cycles and periods. The hardness values for Classico resin were steady in all cycles and periods, while the Vipi resin was steady only in the C cycle for all periods. Impact strength values for Classico resin were steady in the A, C and D cycles for all periods, while Vipi resin was steady in all cycles and periods. SMD promoted different effects on the linear dimensional changes, hardness and impact strength of acrylic resins submitted to different polymerization cycles when after SMD and water storage were considered.

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Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

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In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

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This study examined the influence of three polymerization cycles (1: heat cure - long cycle; 2: heat cure - short cycle; and 3: microwave activation) on the linear dimensions of three denture base resins, immediately after deflasking, and 30 days after storage in distilled water at 37± 2ºC. The acrylic resins used were: Clássico, Lucitone 550 and Acron MC. The first two resins were submitted to all three polymerization cycles, and the Acron MC resin was cured by microwave activation only. The samples had three marks, and dimensions of 65 mm in length, 10 mm in width and 3 mm in thickness. Twenty-one test specimens were fabricated for each combination of resin and cure cycle, and they were submitted to three linear dimensional evaluations for two positions (A and B). The changes were evaluated using a microscope. The results indicated that all acrylic resins, regardless of the cure cycle, showed increased linear dimension after 30 days of storage in water. The composition of the acrylic resin affected the results more than the cure cycles, and the conventional acrylic resin (Lucitone 550 and Clássico) cured by microwave activation presented similar results when compared with the resin specific for microwave activation.

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BACKGROUND: Changes in heart rate during rest-exercise transition can be characterized by the application of mathematical calculations, such as deltas 0-10 and 0-30 seconds to infer on the parasympathetic nervous system and linear regression and delta applied to data range from 60 to 240 seconds to infer on the sympathetic nervous system. The objective of this study was to test the hypothesis that young and middle-aged subjects have different heart rate responses in exercise of moderate and intense intensity, with different mathematical calculations. METHODS: Seven middle-aged men and ten young men apparently healthy were subject to constant load tests (intense and moderate) in cycle ergometer. The heart rate data were submitted to analysis of deltas (0-10, 0-30 and 60-240 seconds) and simple linear regression (60-240 seconds). The parameters obtained from simple linear regression analysis were: intercept and slope angle. We used the Shapiro-Wilk test to check the distribution of data and the t test for unpaired comparisons between groups. The level of statistical significance was 5%. RESULTS: The value of the intercept and delta 0-10 seconds was lower in middle age in two loads tested and the inclination angle was lower in moderate exercise in middle age. CONCLUSION: The young subjects present greater magnitude of vagal withdrawal in the initial stage of the HR response during constant load exercise and higher speed of adjustment of sympathetic response in moderate exercise.