952 resultados para Square Root Model
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This raster layer represents surface elevation and bathymetry data for the Boston Region, Massachusetts. It was created by merging portions of MassGIS Digital Elevation Model 1:5,000 (2005) data with NOAA Estuarine Bathymetric Digital Elevation Models (30 m.) (1998). DEM data was derived from the digital terrain models that were produced as part of the MassGIS 1:5,000 Black and White Digital Orthophoto imagery project. Cellsize is 5 meters by 5 meters. Each cell has a floating point value, in meters, which represents its elevation above or below sea level.
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"29 November 1967."
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Structure from Motion (SfM) is a new form of photogrammetry that automates the rendering of georeferenced 3D models of objects using digital photographs and independently surveyed Ground Control Points (GCPs). This project seeks to quantify the error found in Digital Elevation Models (DEMs) produced using SfM. I modeled a rockslide found at the Cadman Quarry (Monroe, Washington) because the surface is vegetation-free, which is ideal for SfM and Terrestrial LiDAR Scanner (TLS) surveys. By using SfM, TLS, and GPS positioning at the same time, I attempted to find the deviation in the SfM model from the TLS model and GPS points. Using the deviation, I found the Root-Mean-Square Error (RMSE) between the SfM DEM and GPS positions. The RMSE of the SfM model when compared to surveyed GPS points is 17cm. I propagated the uncertainty of the GPS points with the RMSE of the SfM model to find the uncertainty of the SfM model compared to the NAD 1984 datum. The uncertainty of the SfM model compared to the NAD 1984 is 27cm. This study did not produce a model from the TLS that had sufficient resolution on horizontal surfaces to compare to surveyed GPS points.
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Purpose: To evaluate the effects of instrument realignment and angular misalignment during the clinical determination of wavefront aberrations by simulation in model eyes. Setting: Aston Academy of Life Sciences, Aston University, Birmingham, United Kingdom. Methods: Six model eyes were examined with wavefront-aberration-supported cornea ablation (WASCA) (Carl Zeiss Meditec) in 4 sessions of 10 measurements each: sessions 1 and 2, consecutive repeated measures without realignment; session 3, realignment of the instrument between readings; session 4, measurements without realignment but with the model eye shifted 6 degrees angularly. Intersession repeatability and the effects of realignment and misalignment were obtained by comparing the measurements in the various sessions for coma, spherical aberration, and higher-order aberrations (HOAs). Results: The mean differences between the 2 sessions without realignment of the instrument were 0.020 μm ± 0.076 (SD) for Z3 - 1(P = .551), 0.009 ± 0.139 μm for Z3 1(P = .877), 0.004 ± 0.037 μm for Z4 0 (P = .820), and 0.005 ± 0.01 μm for HO root mean square (RMS) (P = .301). Differences between the nonrealigned and realigned instruments were -0.017 ± 0.026 μm for Z3 - 1(P = .159), 0.009 ± 0.028 μm for Z3 1 (P = .475), 0.007 ± 0.014 μm for Z4 0(P = .296), and 0.002 ± 0.007 μm for HO RMS (P = 0.529; differences between centered and misaligned instruments were -0.355 ± 0.149 μm for Z3 - 1 (P = .002), 0.007 ± 0.034 μm for Z3 1(P = .620), -0.005 ± 0.081 μm for Z4 0(P = .885), and 0.012 ± 0.020 μm for HO RMS (P = .195). Realignment increased the standard deviation by a factor of 3 compared with the first session without realignment. Conclusions: Repeatability of the WASCA was excellent in all situations tested. Realignment substantially increased the variance of the measurements. Angular misalignment can result in significant errors, particularly in the determination of coma. These findings are important when assessing highly aberrated eyes during follow-up or before surgery. © 2007 ASCRS and ESCRS.
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In this paper, we present syllable-based duration modelling in the context of a prosody model for Standard Yorùbá (SY) text-to-speech (TTS) synthesis applications. Our prosody model is conceptualised around a modular holistic framework. This framework is implemented using the Relational Tree (R-Tree) techniques. An important feature of our R-Tree framework is its flexibility in that it facilitates the independent implementation of the different dimensions of prosody, i.e. duration, intonation, and intensity, using different techniques and their subsequent integration. We applied the Fuzzy Decision Tree (FDT) technique to model the duration dimension. In order to evaluate the effectiveness of FDT in duration modelling, we have also developed a Classification And Regression Tree (CART) based duration model using the same speech data. Each of these models was integrated into our R-Tree based prosody model. We performed both quantitative (i.e. Root Mean Square Error (RMSE) and Correlation (Corr)) and qualitative (i.e. intelligibility and naturalness) evaluations on the two duration models. The results show that CART models the training data more accurately than FDT. The FDT model, however, shows a better ability to extrapolate from the training data since it achieved a better accuracy for the test data set. Our qualitative evaluation results show that our FDT model produces synthesised speech that is perceived to be more natural than our CART model. In addition, we also observed that the expressiveness of FDT is much better than that of CART. That is because the representation in FDT is not restricted to a set of piece-wise or discrete constant approximation. We, therefore, conclude that the FDT approach is a practical approach for duration modelling in SY TTS applications. © 2006 Elsevier Ltd. All rights reserved.
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Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.
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Surface quality is important in engineering and a vital aspect of it is surface roughness, since it plays an important role in wear resistance, ductility, tensile, and fatigue strength for machined parts. This paper reports on a research study on the development of a geometrical model for surface roughness prediction when face milling with square inserts. The model is based on a geometrical analysis of the recreation of the tool trail left on the machined surface. The model has been validated with experimental data obtained for high speed milling of aluminum alloy (Al 7075-T7351) when using a wide range of cutting speed, feed per tooth, axial depth of cut and different values of tool nose radius (0.8. mm and 2.5. mm), using the Taguchi method as the design of experiments. The experimental roughness was obtained by measuring the surface roughness of the milled surfaces with a non-contact profilometer. The developed model can be used for any combination of material workpiece and tool, when tool flank wear is not considered and is suitable for using any tool diameter with any number of teeth and tool nose radius. The results show that the developed model achieved an excellent performance with almost 98% accuracy in terms of predicting the surface roughness when compared to the experimental data. © 2014 The Society of Manufacturing Engineers.
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Measurements of area summation for luminance-modulated stimuli are typically confounded by variations in sensitivity across the retina. Recently we conducted a detailed analysis of sensitivity across the visual field (Baldwin et al, 2012) and found it to be well-described by a bilinear “witch’s hat” function: sensitivity declines rapidly over the first 8 cycles or so, more gently thereafter. Here we multiplied luminance-modulated stimuli (4 c/deg gratings and “Swiss cheeses”) by the inverse of the witch’s hat function to compensate for the inhomogeneity. This revealed summation functions that were straight lines (on double log axes) with a slope of -1/4 extending to ≥33 cycles, demonstrating fourth-root summation of contrast over a wider area than has previously been reported for the central retina. Fourth-root summation is typically attributed to probability summation, but recent studies have rejected that interpretation in favour of a noisy energy model that performs local square-law transduction of the signal, adds noise at each location of the target and then sums over signal area. Modelling shows our results to be consistent with a wide field application of such a contrast integrator. We reject a probability summation model, a quadratic model and a matched template model of our results under the assumptions of signal detection theory. We also reject the high threshold theory of contrast detection under the assumption of probability summation over area.
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Setting out from the database of Operophtera brumata, L. in between 1973 and 2000 due to the Light Trap Network in Hungary, we introduce a simple theta-logistic population dynamical model based on endogenous and exogenous factors, only. We create an indicator set from which we can choose some elements with which we can improve the fitting results the most effectively. Than we extend the basic simple model with additive climatic factors. The parameter optimization is based on the minimized root mean square error. The best model is chosen according to the Akaike Information Criterion. Finally we run the calibrated extended model with daily outputs of the regional climate model RegCM3.1, regarding 1961-1990 as reference period and 2021-2050 with 2071-2100 as future predictions. The results of the three time intervals are fitted with Beta distributions and compared statistically. The expected changes are discussed.
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This paper presents a new tuning methodology of the main controller of an internal model control structure for n×n stable multivariable processes with multiple time delays based on the centralized inverted decoupling structure. Independently of the system size, very simple general expressions for the controller elements are obtained. The realizability conditions are provided and the specification of the closed-loop requirements is explained. A diagonal filter is added to the proposed control structure in order to improve the disturbance rejection without modifying the nominal set-point response. The effectiveness of the method is illustrated through different simulation examples in comparison with other works.
Root cause analysis applied to a finite element model's refinement of a negative stiffness structure
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Negative Stiffness Structures are mechanical systems that require a decrease in the applied force to generate an increase in displacement. They are structures that possess special characteristics such as snap-through and bi-stability. All of these features make them particularly suitable for different applications, such as shock-absorption, vibration isolation and damping. From this point of view, they have risen awareness of their characteristics and, in order to match them to the application needed, a numerical simulation is of great interest. In this regard, this thesis is a continuation of previous studies in a circular negative stiffness structure and aims at refine the numerical model by presenting a new solution. To that end, an investigation procedure is needed. Amongst all of the methods available, root cause analysis was the chosen one to perform the investigation since it provides a clear view of the problem under analysis and a categorization of all the causes behind it. As a result of the cause-effect analysis, the main causes that have influence on the numerical results were obtained. Once all of the causes were listed, solutions to them were proposed and it led to a new numerical model. The numerical model proposed was of nonlinear type of analysis with hexagonal elements and a hyperelastic material model. The results were analyzed through force-displacement curves, allowing for the visualization of the structure’s energy recovery. When compared to the results obtained from the experimental part, it is evident that the trend is similar and the negative stiffness behaviour is present.
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The aim of this study was to evaluate the differential sensitivity of sugarcane genotypes to H2O2 in root medium. As a hypothesis, the drought tolerant genotype would be able to minimize the oxidative damage and maintain the water transport from roots to shoots, reducing the negative effects on photosynthesis. The sugarcane genotypes IACSP94-2094 (drought tolerant) and IACSP94-2101 (drought sensitive) were grown in a growth chamber and exposed to three levels of H2O2 in nutrient solution: control; 3mmolL(-1) and 80mmolL(-1). Leaf gas exchange, photochemical activity, root hydraulic conductance (Lr) and antioxidant metabolism in both roots and leaves were evaluated after 15min of treatment with H2O2. Although, root hydraulic conductance, stomatal aperture, apparent electron transport rate and instantaneous carboxylation efficiency have been reduced by H2O2 in both genotypes, IACSP94-2094 presented higher values of those variables as compared to IACSP94-2101. There was a significant genotypic variation in relation to the physiological responses of sugarcane to increasing H2O2 in root tissues, being root changes associated with modifications in plant shoots. IACSP94-2094 presented a root antioxidant system more effective against H2O2 in root medium, regardless H2O2 concentration. Under low H2O2 concentration, water transport and leaf gas exchange of IACSP94-2094 were less affected as compared to IACSP94-2101. Under high H2O2 concentration, the lower sensitivity of IACSP94-2094 was associated with increases in superoxide dismutase activity in roots and leaves and increases in catalase activity in roots. In conclusion, we propose a general model of sugarcane reaction to H2O2, linking root and shoot physiological responses.
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Universidade Estadual de Campinas . Faculdade de Educação Física