Kinetic energy classification and smoothing for compact B-spline basis sets in quantum Monte Carlo

Science.gov (United States)

Krogel, Jaron T.; Reboredo, Fernando A.

2018-01-01

Quantum Monte Carlo calculations of defect properties of transition metal oxides have become feasible in recent years due to increases in computing power. As the system size has grown, availability of on-node memory has become a limiting factor. Saving memory while minimizing computational cost is now a priority. The main growth in memory demand stems from the B-spline representation of the single particle orbitals, especially for heavier elements such as transition metals where semi-core states are present. Despite the associated memory costs, splines are computationally efficient. In this work, we explore alternatives to reduce the memory usage of splined orbitals without significantly affecting numerical fidelity or computational efficiency. We make use of the kinetic energy operator to both classify and smooth the occupied set of orbitals prior to splining. By using a partitioning scheme based on the per-orbital kinetic energy distributions, we show that memory savings of about 50% is possible for select transition metal oxide systems. For production supercells of practical interest, our scheme incurs a performance penalty of less than 5%.

Image edges detection through B-Spline filters

International Nuclear Information System (INIS)

Mastropiero, D.G.

1997-01-01

B-Spline signal processing was used to detect the edges of a digital image. This technique is based upon processing the image in the Spline transform domain, instead of doing so in the space domain (classical processing). The transformation to the Spline transform domain means finding out the real coefficients that makes it possible to interpolate the grey levels of the original image, with a B-Spline polynomial. There exist basically two methods of carrying out this interpolation, which produces the existence of two different Spline transforms: an exact interpolation of the grey values (direct Spline transform), and an approximated interpolation (smoothing Spline transform). The latter results in a higher smoothness of the gray distribution function defined by the Spline transform coefficients, and is carried out with the aim of obtaining an edge detection algorithm which higher immunity to noise. Finally the transformed image was processed in order to detect the edges of the original image (the gradient method was used), and the results of the three methods (classical, direct Spline transform and smoothing Spline transform) were compared. The results were that, as expected, the smoothing Spline transform technique produced a detection algorithm more immune to external noise. On the other hand the direct Spline transform technique, emphasizes more the edges, even more than the classical method. As far as the consuming time is concerned, the classical method is clearly the fastest one, and may be applied whenever the presence of noise is not important, and whenever edges with high detail are not required in the final image. (author). 9 refs., 17 figs., 1 tab

Deconvolution using thin-plate splines

International Nuclear Information System (INIS)

Toussaint, Udo v.; Gori, Silvio

2007-01-01

The ubiquitous problem of estimating 2-dimensional profile information from a set of line integrated measurements is tackled with Bayesian probability theory by exploiting prior information about local smoothness. For this purpose thin-plate-splines (the 2-D minimal curvature analogue of cubic-splines in 1-D) are employed. The optimal number of support points required for inversion of 2-D tomographic problems is determined using model comparison. Properties of this approach are discussed and the question of suitable priors is addressed. Finally, we illustrated the properties of this approach with 2-D inversion results using data from line-integrated measurements from fusion experiments

LOCALLY REFINED SPLINES REPRESENTATION FOR GEOSPATIAL BIG DATA

Directory of Open Access Journals (Sweden)

T. Dokken

2015-08-01

Full Text Available When viewed from distance, large parts of the topography of landmasses and the bathymetry of the sea and ocean floor can be regarded as a smooth background with local features. Consequently a digital elevation model combining a compact smooth representation of the background with locally added features has the potential of providing a compact and accurate representation for topography and bathymetry. The recent introduction of Locally Refined B-Splines (LR B-splines allows the granularity of spline representations to be locally adapted to the complexity of the smooth shape approximated. This allows few degrees of freedom to be used in areas with little variation, while adding extra degrees of freedom in areas in need of more modelling flexibility. In the EU fp7 Integrating Project IQmulus we exploit LR B-splines for approximating large point clouds representing bathymetry of the smooth sea and ocean floor. A drastic reduction is demonstrated in the bulk of the data representation compared to the size of input point clouds. The representation is very well suited for exploiting the power of GPUs for visualization as the spline format is transferred to the GPU and the triangulation needed for the visualization is generated on the GPU according to the viewing parameters. The LR B-splines are interoperable with other elevation model representations such as LIDAR data, raster representations and triangulated irregular networks as these can be used as input to the LR B-spline approximation algorithms. Output to these formats can be generated from the LR B-spline applications according to the resolution criteria required. The spline models are well suited for change detection as new sensor data can efficiently be compared to the compact LR B-spline representation.

Schwarz and multilevel methods for quadratic spline collocation

Energy Technology Data Exchange (ETDEWEB)

Christara, C.C. [Univ. of Toronto, Ontario (Canada); Smith, B. [Univ. of California, Los Angeles, CA (United States)

1994-12-31

Smooth spline collocation methods offer an alternative to Galerkin finite element methods, as well as to Hermite spline collocation methods, for the solution of linear elliptic Partial Differential Equations (PDEs). Recently, optimal order of convergence spline collocation methods have been developed for certain degree splines. Convergence proofs for smooth spline collocation methods are generally more difficult than for Galerkin finite elements or Hermite spline collocation, and they require stronger assumptions and more restrictions. However, numerical tests indicate that spline collocation methods are applicable to a wider class of problems, than the analysis requires, and are very competitive to finite element methods, with respect to efficiency. The authors will discuss Schwarz and multilevel methods for the solution of elliptic PDEs using quadratic spline collocation, and compare these with domain decomposition methods using substructuring. Numerical tests on a variety of parallel machines will also be presented. In addition, preliminary convergence analysis using Schwarz and/or maximum principle techniques will be presented.

Smoothing data series by means of cubic splines: quality of approximation and introduction of a repeating spline approach

Science.gov (United States)

Wüst, Sabine; Wendt, Verena; Linz, Ricarda; Bittner, Michael

2017-09-01

Cubic splines with equidistant spline sampling points are a common method in atmospheric science, used for the approximation of background conditions by means of filtering superimposed fluctuations from a data series. What is defined as background or superimposed fluctuation depends on the specific research question. The latter also determines whether the spline or the residuals - the subtraction of the spline from the original time series - are further analysed.Based on test data sets, we show that the quality of approximation of the background state does not increase continuously with an increasing number of spline sampling points and/or decreasing distance between two spline sampling points. Splines can generate considerable artificial oscillations in the background and the residuals.We introduce a repeating spline approach which is able to significantly reduce this phenomenon. We apply it not only to the test data but also to TIMED-SABER temperature data and choose the distance between two spline sampling points in a way that is sensitive for a large spectrum of gravity waves.

Piecewise linear regression splines with hyperbolic covariates

International Nuclear Information System (INIS)

Cologne, John B.; Sposto, Richard

1992-09-01

Consider the problem of fitting a curve to data that exhibit a multiphase linear response with smooth transitions between phases. We propose substituting hyperbolas as covariates in piecewise linear regression splines to obtain curves that are smoothly joined. The method provides an intuitive and easy way to extend the two-phase linear hyperbolic response model of Griffiths and Miller and Watts and Bacon to accommodate more than two linear segments. The resulting regression spline with hyperbolic covariates may be fit by nonlinear regression methods to estimate the degree of curvature between adjoining linear segments. The added complexity of fitting nonlinear, as opposed to linear, regression models is not great. The extra effort is particularly worthwhile when investigators are unwilling to assume that the slope of the response changes abruptly at the join points. We can also estimate the join points (the values of the abscissas where the linear segments would intersect if extrapolated) if their number and approximate locations may be presumed known. An example using data on changing age at menarche in a cohort of Japanese women illustrates the use of the method for exploratory data analysis. (author)

MRI non-uniformity correction through interleaved bias estimation and B-spline deformation with a template.

Science.gov (United States)

Fletcher, E; Carmichael, O; Decarli, C

2012-01-01

We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain. At each algorithm iteration, the update of a B-spline deformation between an unbiased template image and the subject image is interleaved with estimation of a bias field based on the current template-to-image alignment. The bias field is modeled using a spatially smooth thin-plate spline interpolation based on ratios of local image patch intensity means between the deformed template and subject images. This is used to iteratively correct subject image intensities which are then used to improve the template-to-image deformation. Experiments on synthetic and real data sets of images with and without Alzheimer's disease suggest that the approach may have advantages over the popular N3 technique for modeling bias fields and narrowing intensity ranges of gray matter, white matter, and cerebrospinal fluid. This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions.

MRI Non-Uniformity Correction Through Interleaved Bias Estimation and B-Spline Deformation with a Template*

Science.gov (United States)

Fletcher, E.; Carmichael, O.; DeCarli, C.

2013-01-01

We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain. At each algorithm iteration, the update of a B-spline deformation between an unbiased template image and the subject image is interleaved with estimation of a bias field based on the current template-to-image alignment. The bias field is modeled using a spatially smooth thin-plate spline interpolation based on ratios of local image patch intensity means between the deformed template and subject images. This is used to iteratively correct subject image intensities which are then used to improve the template-to-image deformation. Experiments on synthetic and real data sets of images with and without Alzheimer’s disease suggest that the approach may have advantages over the popular N3 technique for modeling bias fields and narrowing intensity ranges of gray matter, white matter, and cerebrospinal fluid. This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions. PMID:23365843

Smooth extrapolation of unknown anatomy via statistical shape models

Science.gov (United States)

Grupp, R. B.; Chiang, H.; Otake, Y.; Murphy, R. J.; Gordon, C. R.; Armand, M.; Taylor, R. H.

2015-03-01

Several methods to perform extrapolation of unknown anatomy were evaluated. The primary application is to enhance surgical procedures that may use partial medical images or medical images of incomplete anatomy. Le Fort-based, face-jaw-teeth transplant is one such procedure. From CT data of 36 skulls and 21 mandibles separate Statistical Shape Models of the anatomical surfaces were created. Using the Statistical Shape Models, incomplete surfaces were projected to obtain complete surface estimates. The surface estimates exhibit non-zero error in regions where the true surface is known; it is desirable to keep the true surface and seamlessly merge the estimated unknown surface. Existing extrapolation techniques produce non-smooth transitions from the true surface to the estimated surface, resulting in additional error and a less aesthetically pleasing result. The three extrapolation techniques evaluated were: copying and pasting of the surface estimate (non-smooth baseline), a feathering between the patient surface and surface estimate, and an estimate generated via a Thin Plate Spline trained from displacements between the surface estimate and corresponding vertices of the known patient surface. Feathering and Thin Plate Spline approaches both yielded smooth transitions. However, feathering corrupted known vertex values. Leave-one-out analyses were conducted, with 5% to 50% of known anatomy removed from the left-out patient and estimated via the proposed approaches. The Thin Plate Spline approach yielded smaller errors than the other two approaches, with an average vertex error improvement of 1.46 mm and 1.38 mm for the skull and mandible respectively, over the baseline approach.

Color management with a hammer: the B-spline fitter

Science.gov (United States)

Bell, Ian E.; Liu, Bonny H. P.

2003-01-01

To paraphrase Abraham Maslow: If the only tool you have is a hammer, every problem looks like a nail. We have a B-spline fitter customized for 3D color data, and many problems in color management can be solved with this tool. Whereas color devices were once modeled with extensive measurement, look-up tables and trilinear interpolation, recent improvements in hardware have made B-spline models an affordable alternative. Such device characterizations require fewer color measurements than piecewise linear models, and have uses beyond simple interpolation. A B-spline fitter, for example, can act as a filter to remove noise from measurements, leaving a model with guaranteed smoothness. Inversion of the device model can then be carried out consistently and efficiently, as the spline model is well behaved and its derivatives easily computed. Spline-based algorithms also exist for gamut mapping, the composition of maps, and the extrapolation of a gamut. Trilinear interpolation---a degree-one spline---can still be used after nonlinear spline smoothing for high-speed evaluation with robust convergence. Using data from several color devices, this paper examines the use of B-splines as a generic tool for modeling devices and mapping one gamut to another, and concludes with applications to high-dimensional and spectral data.

Radial Basis Function Based Quadrature over Smooth Surfaces

Science.gov (United States)

2016-03-24

Radial Basis Functions φ(r) Piecewise Smooth (Conditionally Positive Definite) MN Monomial |r|2m+1 TPS thin plate spline |r|2mln|r| Infinitely Smooth...smooth surfaces using polynomial interpolants, while [27] couples Thin - Plate Spline interpolation (see table 1) with Green’s integral formula [29

Sequential bayes estimation algorithm with cubic splines on uniform meshes

International Nuclear Information System (INIS)

Hossfeld, F.; Mika, K.; Plesser-Walk, E.

1975-11-01

After outlining the principles of some recent developments in parameter estimation, a sequential numerical algorithm for generalized curve-fitting applications is presented combining results from statistical estimation concepts and spline analysis. Due to its recursive nature, the algorithm can be used most efficiently in online experimentation. Using computer-sumulated and experimental data, the efficiency and the flexibility of this sequential estimation procedure is extensively demonstrated. (orig.) [de

Spline smoothing of histograms by linear programming

Science.gov (United States)

Bennett, J. O.

1972-01-01

An algorithm for an approximating function to the frequency distribution is obtained from a sample of size n. To obtain the approximating function a histogram is made from the data. Next, Euclidean space approximations to the graph of the histogram using central B-splines as basis elements are obtained by linear programming. The approximating function has area one and is nonnegative.

P-Splines Using Derivative Information

KAUST Repository

Calderon, Christopher P.

2010-01-01

Time series associated with single-molecule experiments and/or simulations contain a wealth of multiscale information about complex biomolecular systems. We demonstrate how a collection of Penalized-splines (P-splines) can be useful in quantitatively summarizing such data. In this work, functions estimated using P-splines are associated with stochastic differential equations (SDEs). It is shown how quantities estimated in a single SDE summarize fast-scale phenomena, whereas variation between curves associated with different SDEs partially reflects noise induced by motion evolving on a slower time scale. P-splines assist in "semiparametrically" estimating nonlinear SDEs in situations where a time-dependent external force is applied to a single-molecule system. The P-splines introduced simultaneously use function and derivative scatterplot information to refine curve estimates. We refer to the approach as the PuDI (P-splines using Derivative Information) method. It is shown how generalized least squares ideas fit seamlessly into the PuDI method. Applications demonstrating how utilizing uncertainty information/approximations along with generalized least squares techniques improve PuDI fits are presented. Although the primary application here is in estimating nonlinear SDEs, the PuDI method is applicable to situations where both unbiased function and derivative estimates are available.

Improving mouse controlling and movement for people with Parkinson's disease and involuntary tremor using adaptive path smoothing technique via B-spline.

Science.gov (United States)

Hashem, Seyed Yashar Bani; Zin, Nor Azan Mat; Yatim, Noor Faezah Mohd; Ibrahim, Norlinah Mohamed

2014-01-01

Many input devices are available for interacting with computers, but the computer mouse is still the most popular device for interaction. People who suffer from involuntary tremor have difficulty using the mouse in the normal way. The target participants of this research were individuals who suffer from Parkinson's disease. Tremor in limbs makes accurate mouse movements impossible or difficult without any assistive technologies to help. This study explores a new assistive technique-adaptive path smoothing via B-spline (APSS)-to enhance mouse controlling based on user's tremor level and type. APSS uses Mean filtering and B-spline to provide a smoothed mouse trajectory. Seven participants who have unwanted tremor evaluated APSS. Results show that APSS is very promising and greatly increases their control of the computer mouse. Result of user acceptance test also shows that user perceived APSS as easy to use. They also believe it to be a useful tool and intend to use it once it is available. Future studies could explore the possibility of integrating APSS with one assistive pointing technique, such as the Bubble cursor or the Sticky target technique, to provide an all in one solution for motor disabled users.

Mathematical modelling for the drying method and smoothing drying rate using cubic spline for seaweed Kappaphycus Striatum variety Durian in a solar dryer

Energy Technology Data Exchange (ETDEWEB)

M Ali, M. K., E-mail: majidkhankhan@ymail.com, E-mail: eutoco@gmail.com; Ruslan, M. H., E-mail: majidkhankhan@ymail.com, E-mail: eutoco@gmail.com [Solar Energy Research Institute (SERI), Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor (Malaysia); Muthuvalu, M. S., E-mail: sudaram-@yahoo.com, E-mail: jumat@ums.edu.my; Wong, J., E-mail: sudaram-@yahoo.com, E-mail: jumat@ums.edu.my [Unit Penyelidikan Rumpai Laut (UPRL), Sekolah Sains dan Teknologi, Universiti Malaysia Sabah, 88400 Kota Kinabalu, Sabah (Malaysia); Sulaiman, J., E-mail: ysuhaimi@ums.edu.my, E-mail: hafidzruslan@eng.ukm.my; Yasir, S. Md., E-mail: ysuhaimi@ums.edu.my, E-mail: hafidzruslan@eng.ukm.my [Program Matematik dengan Ekonomi, Sekolah Sains dan Teknologi, Universiti Malaysia Sabah, 88400 Kota Kinabalu, Sabah (Malaysia)

2014-06-19

The solar drying experiment of seaweed using Green V-Roof Hybrid Solar Drier (GVRHSD) was conducted in Semporna, Sabah under the metrological condition in Malaysia. Drying of sample seaweed in GVRHSD reduced the moisture content from about 93.4% to 8.2% in 4 days at average solar radiation of about 600W/m{sup 2} and mass flow rate about 0.5 kg/s. Generally the plots of drying rate need more smoothing compared moisture content data. Special cares is needed at low drying rates and moisture contents. It is shown the cubic spline (CS) have been found to be effective for moisture-time curves. The idea of this method consists of an approximation of data by a CS regression having first and second derivatives. The analytical differentiation of the spline regression permits the determination of instantaneous rate. The method of minimization of the functional of average risk was used successfully to solve the problem. This method permits to obtain the instantaneous rate to be obtained directly from the experimental data. The drying kinetics was fitted with six published exponential thin layer drying models. The models were fitted using the coefficient of determination (R{sup 2}), and root mean square error (RMSE). The modeling of models using raw data tested with the possible of exponential drying method. The result showed that the model from Two Term was found to be the best models describe the drying behavior. Besides that, the drying rate smoothed using CS shows to be effective method for moisture-time curves good estimators as well as for the missing moisture content data of seaweed Kappaphycus Striatum Variety Durian in Solar Dryer under the condition tested.

Mathematical modelling for the drying method and smoothing drying rate using cubic spline for seaweed Kappaphycus Striatum variety Durian in a solar dryer

International Nuclear Information System (INIS)

M Ali, M. K.; Ruslan, M. H.; Muthuvalu, M. S.; Wong, J.; Sulaiman, J.; Yasir, S. Md.

2014-01-01

The solar drying experiment of seaweed using Green V-Roof Hybrid Solar Drier (GVRHSD) was conducted in Semporna, Sabah under the metrological condition in Malaysia. Drying of sample seaweed in GVRHSD reduced the moisture content from about 93.4% to 8.2% in 4 days at average solar radiation of about 600W/m 2 and mass flow rate about 0.5 kg/s. Generally the plots of drying rate need more smoothing compared moisture content data. Special cares is needed at low drying rates and moisture contents. It is shown the cubic spline (CS) have been found to be effective for moisture-time curves. The idea of this method consists of an approximation of data by a CS regression having first and second derivatives. The analytical differentiation of the spline regression permits the determination of instantaneous rate. The method of minimization of the functional of average risk was used successfully to solve the problem. This method permits to obtain the instantaneous rate to be obtained directly from the experimental data. The drying kinetics was fitted with six published exponential thin layer drying models. The models were fitted using the coefficient of determination (R 2 ), and root mean square error (RMSE). The modeling of models using raw data tested with the possible of exponential drying method. The result showed that the model from Two Term was found to be the best models describe the drying behavior. Besides that, the drying rate smoothed using CS shows to be effective method for moisture-time curves good estimators as well as for the missing moisture content data of seaweed Kappaphycus Striatum Variety Durian in Solar Dryer under the condition tested

Mathematical modelling for the drying method and smoothing drying rate using cubic spline for seaweed Kappaphycus Striatum variety Durian in a solar dryer

Science.gov (United States)

M Ali, M. K.; Ruslan, M. H.; Muthuvalu, M. S.; Wong, J.; Sulaiman, J.; Yasir, S. Md.

2014-06-01

The solar drying experiment of seaweed using Green V-Roof Hybrid Solar Drier (GVRHSD) was conducted in Semporna, Sabah under the metrological condition in Malaysia. Drying of sample seaweed in GVRHSD reduced the moisture content from about 93.4% to 8.2% in 4 days at average solar radiation of about 600W/m2 and mass flow rate about 0.5 kg/s. Generally the plots of drying rate need more smoothing compared moisture content data. Special cares is needed at low drying rates and moisture contents. It is shown the cubic spline (CS) have been found to be effective for moisture-time curves. The idea of this method consists of an approximation of data by a CS regression having first and second derivatives. The analytical differentiation of the spline regression permits the determination of instantaneous rate. The method of minimization of the functional of average risk was used successfully to solve the problem. This method permits to obtain the instantaneous rate to be obtained directly from the experimental data. The drying kinetics was fitted with six published exponential thin layer drying models. The models were fitted using the coefficient of determination (R2), and root mean square error (RMSE). The modeling of models using raw data tested with the possible of exponential drying method. The result showed that the model from Two Term was found to be the best models describe the drying behavior. Besides that, the drying rate smoothed using CS shows to be effective method for moisture-time curves good estimators as well as for the missing moisture content data of seaweed Kappaphycus Striatum Variety Durian in Solar Dryer under the condition tested.

Numerical discretization-based estimation methods for ordinary differential equation models via penalized spline smoothing with applications in biomedical research.

Science.gov (United States)

Wu, Hulin; Xue, Hongqi; Kumar, Arun

2012-06-01

Differential equations are extensively used for modeling dynamics of physical processes in many scientific fields such as engineering, physics, and biomedical sciences. Parameter estimation of differential equation models is a challenging problem because of high computational cost and high-dimensional parameter space. In this article, we propose a novel class of methods for estimating parameters in ordinary differential equation (ODE) models, which is motivated by HIV dynamics modeling. The new methods exploit the form of numerical discretization algorithms for an ODE solver to formulate estimating equations. First, a penalized-spline approach is employed to estimate the state variables and the estimated state variables are then plugged in a discretization formula of an ODE solver to obtain the ODE parameter estimates via a regression approach. We consider three different order of discretization methods, Euler's method, trapezoidal rule, and Runge-Kutta method. A higher-order numerical algorithm reduces numerical error in the approximation of the derivative, which produces a more accurate estimate, but its computational cost is higher. To balance the computational cost and estimation accuracy, we demonstrate, via simulation studies, that the trapezoidal discretization-based estimate is the best and is recommended for practical use. The asymptotic properties for the proposed numerical discretization-based estimators are established. Comparisons between the proposed methods and existing methods show a clear benefit of the proposed methods in regards to the trade-off between computational cost and estimation accuracy. We apply the proposed methods t an HIV study to further illustrate the usefulness of the proposed approaches. © 2012, The International Biometric Society.

A new class of interpolatory $L$-splines with adjoint end conditions

OpenAIRE

Bejancu, Aurelian; Al-Sahli, Reyouf S.

2014-01-01

A thin plate spline surface for interpolation of smooth transfinite data prescribed along concentric circles was recently proposed by Bejancu, using Kounchev's polyspline method. The construction of the new `Beppo Levi polyspline' surface reduces, via separation of variables, to that of a countable family of univariate $L$-splines, indexed by the frequency integer $k$. This paper establishes the existence, uniqueness and variational properties of the `Beppo Levi $L$-spline' schemes correspond...

The estimation of branching curves in the presence of subject-specific random effects.

Science.gov (United States)

Elmi, Angelo; Ratcliffe, Sarah J; Guo, Wensheng

2014-12-20

Branching curves are a technique for modeling curves that change trajectory at a change (branching) point. Currently, the estimation framework is limited to independent data, and smoothing splines are used for estimation. This article aims to extend the branching curve framework to the longitudinal data setting where the branching point varies by subject. If the branching point is modeled as a random effect, then the longitudinal branching curve framework is a semiparametric nonlinear mixed effects model. Given existing issues with using random effects within a smoothing spline, we express the model as a B-spline based semiparametric nonlinear mixed effects model. Simple, clever smoothness constraints are enforced on the B-splines at the change point. The method is applied to Women's Health data where we model the shape of the labor curve (cervical dilation measured longitudinally) before and after treatment with oxytocin (a labor stimulant). Copyright © 2014 John Wiley & Sons, Ltd.

Spline Trajectory Algorithm Development: Bezier Curve Control Point Generation for UAVs

Science.gov (United States)

Howell, Lauren R.; Allen, B. Danette

2016-01-01

A greater need for sophisticated autonomous piloting systems has risen in direct correlation with the ubiquity of Unmanned Aerial Vehicle (UAV) technology. Whether surveying unknown or unexplored areas of the world, collecting scientific data from regions in which humans are typically incapable of entering, locating lost or wanted persons, or delivering emergency supplies, an unmanned vehicle moving in close proximity to people and other vehicles, should fly smoothly and predictably. The mathematical application of spline interpolation can play an important role in autopilots' on-board trajectory planning. Spline interpolation allows for the connection of Three-Dimensional Euclidean Space coordinates through a continuous set of smooth curves. This paper explores the motivation, application, and methodology used to compute the spline control points, which shape the curves in such a way that the autopilot trajectory is able to meet vehicle-dynamics limitations. The spline algorithms developed used to generate these curves supply autopilots with the information necessary to compute vehicle paths through a set of coordinate waypoints.

[Medical image elastic registration smoothed by unconstrained optimized thin-plate spline].

Science.gov (United States)

Zhang, Yu; Li, Shuxiang; Chen, Wufan; Liu, Zhexing

2003-12-01

Elastic registration of medical image is an important subject in medical image processing. Previous work has concentrated on selecting the corresponding landmarks manually and then using thin-plate spline interpolating to gain the elastic transformation. However, the landmarks extraction is always prone to error, which will influence the registration results. Localizing the landmarks manually is also difficult and time-consuming. We the optimization theory to improve the thin-plate spline interpolation, and based on it, used an automatic method to extract the landmarks. Combining these two steps, we have proposed an automatic, exact and robust registration method and have gained satisfactory registration results.

Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows

Directory of Open Access Journals (Sweden)

Makram J. Geha

2011-01-01

Full Text Available Milk yield records (305d, 2X, actual milk yield of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β0 + β1X + e ,quadratic regression, (y = β0 + β1X + β2X2 + e cubic regression (y = β0 + β1X + β2X2 + β3X3 + e and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc. The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as "traditional", AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared to results from fitting inbreeding as a linear covariate or as a fixed factor with seven levels. Estimates of inbreeding effects were not significantly different between the cubic-spline model and the fixed factor model, but were significantly different from the linear regression model. Milk yield decreased significantly at inbreeding levels greater than 9%. Variance component estimates were similar for the three models. Ranking of the top 100 sires with daughter records remained unaffected by the model used.

Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique

Science.gov (United States)

Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad

2015-11-01

One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.

Bayesian Analysis for Penalized Spline Regression Using WinBUGS

Directory of Open Access Journals (Sweden)

Ciprian M. Crainiceanu

2005-09-01

Full Text Available Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in WinBUGS. Good mixing properties of the MCMC chains are obtained by using low-rank thin-plate splines, while simulation times per iteration are reduced employing WinBUGS specific computational tricks.

Tomographic reconstruction with B-splines surfaces

International Nuclear Information System (INIS)

Oliveira, Eric F.; Dantas, Carlos C.; Melo, Silvio B.; Mota, Icaro V.; Lira, Mailson

2011-01-01

Algebraic reconstruction techniques when applied to a limited number of data usually suffer from noise caused by the process of correction or by inconsistencies in the data coming from the stochastic process of radioactive emission and oscillation equipment. The post - processing of the reconstructed image with the application of filters can be done to mitigate the presence of noise. In general these processes also attenuate the discontinuities present in edges that distinguish objects or artifacts, causing excessive blurring in the reconstructed image. This paper proposes a built-in noise reduction at the same time that it ensures adequate smoothness level in the reconstructed surface, representing the unknowns as linear combinations of elements of a piecewise polynomial basis, i.e. a B-splines basis. For that, the algebraic technique ART is modified to accommodate the first, second and third degree bases, ensuring C 0 , C 1 and C 2 smoothness levels, respectively. For comparisons, three methodologies are applied: ART, ART post-processed with regular B-splines filters (ART*) and the proposed method with the built-in B-splines filter (BsART). Simulations with input data produced from common mathematical phantoms were conducted. For the phantoms used the BsART method consistently presented the smallest errors, among the three methods. This study has shown the superiority of the change made to embed the filter in the ART when compared to the post-filtered ART. (author)

Computer simulation comparison of tripolar, bipolar, and spline Laplacian electrocadiogram estimators.

Science.gov (United States)

Chen, T; Besio, W; Dai, W

2009-01-01

A comparison of the performance of the tripolar and bipolar concentric as well as spline Laplacian electrocardiograms (LECGs) and body surface Laplacian mappings (BSLMs) for localizing and imaging the cardiac electrical activation has been investigated based on computer simulation. In the simulation a simplified eccentric heart-torso sphere-cylinder homogeneous volume conductor model were developed. Multiple dipoles with different orientations were used to simulate the underlying cardiac electrical activities. Results show that the tripolar concentric ring electrodes produce the most accurate LECG and BSLM estimation among the three estimators with the best performance in spatial resolution.

Adaptive B-spline volume representation of measured BRDF data for photorealistic rendering

Directory of Open Access Journals (Sweden)

Hyungjun Park

2015-01-01

Full Text Available Measured bidirectional reflectance distribution function (BRDF data have been used to represent complex interaction between lights and surface materials for photorealistic rendering. However, their massive size makes it hard to adopt them in practical rendering applications. In this paper, we propose an adaptive method for B-spline volume representation of measured BRDF data. It basically performs approximate B-spline volume lofting, which decomposes the problem into three sub-problems of multiple B-spline curve fitting along u-, v-, and w-parametric directions. Especially, it makes the efficient use of knots in the multiple B-spline curve fitting and thereby accomplishes adaptive knot placement along each parametric direction of a resulting B-spline volume. The proposed method is quite useful to realize efficient data reduction while smoothing out the noises and keeping the overall features of BRDF data well. By applying the B-spline volume models of real materials for rendering, we show that the B-spline volume models are effective in preserving the features of material appearance and are suitable for representing BRDF data.

Kernel PLS Estimation of Single-trial Event-related Potentials

Science.gov (United States)

Rosipal, Roman; Trejo, Leonard J.

2004-01-01

Nonlinear kernel partial least squaes (KPLS) regressior, is a novel smoothing approach to nonparametric regression curve fitting. We have developed a KPLS approach to the estimation of single-trial event related potentials (ERPs). For improved accuracy of estimation, we also developed a local KPLS method for situations in which there exists prior knowledge about the approximate latency of individual ERP components. To assess the utility of the KPLS approach, we compared non-local KPLS and local KPLS smoothing with other nonparametric signal processing and smoothing methods. In particular, we examined wavelet denoising, smoothing splines, and localized smoothing splines. We applied these methods to the estimation of simulated mixtures of human ERPs and ongoing electroencephalogram (EEG) activity using a dipole simulator (BESA). In this scenario we considered ongoing EEG to represent spatially and temporally correlated noise added to the ERPs. This simulation provided a reasonable but simplified model of real-world ERP measurements. For estimation of the simulated single-trial ERPs, local KPLS provided a level of accuracy that was comparable with or better than the other methods. We also applied the local KPLS method to the estimation of human ERPs recorded in an experiment on co,onitive fatigue. For these data, the local KPLS method provided a clear improvement in visualization of single-trial ERPs as well as their averages. The local KPLS method may serve as a new alternative to the estimation of single-trial ERPs and improvement of ERP averages.

Spline-procedures

International Nuclear Information System (INIS)

Schmidt, R.

1976-12-01

This report contains a short introduction to spline functions as well as a complete description of the spline procedures presently available in the HMI-library. These include polynomial splines (using either B-splines or one-sided basis representations) and natural splines, as well as their application to interpolation, quasiinterpolation, L 2 -, and Tchebycheff approximation. Special procedures are included for the case of cubic splines. Complete test examples with input and output are provided for each of the procedures. (orig.) [de

Estimating trajectories of energy intake through childhood and adolescence using linear-spline multilevel models.

Science.gov (United States)

Anderson, Emma L; Tilling, Kate; Fraser, Abigail; Macdonald-Wallis, Corrie; Emmett, Pauline; Cribb, Victoria; Northstone, Kate; Lawlor, Debbie A; Howe, Laura D

2013-07-01

Methods for the assessment of changes in dietary intake across the life course are underdeveloped. We demonstrate the use of linear-spline multilevel models to summarize energy-intake trajectories through childhood and adolescence and their application as exposures, outcomes, or mediators. The Avon Longitudinal Study of Parents and Children assessed children's dietary intake several times between ages 3 and 13 years, using both food frequency questionnaires (FFQs) and 3-day food diaries. We estimated energy-intake trajectories for 12,032 children using linear-spline multilevel models. We then assessed the associations of these trajectories with maternal body mass index (BMI), and later offspring BMI, and also their role in mediating the relation between maternal and offspring BMIs. Models estimated average and individual energy intake at 3 years, and linear changes in energy intake from age 3 to 7 years and from age 7 to 13 years. By including the exposure (in this example, maternal BMI) in the multilevel model, we were able to estimate the average energy-intake trajectories across levels of the exposure. When energy-intake trajectories are the exposure for a later outcome (in this case offspring BMI) or a mediator (between maternal and offspring BMI), results were similar, whether using a two-step process (exporting individual-level intercepts and slopes from multilevel models and using these in linear regression/path analysis), or a single-step process (multivariate multilevel models). Trajectories were similar when FFQs and food diaries were assessed either separately, or when combined into one model. Linear-spline multilevel models provide useful summaries of trajectories of dietary intake that can be used as an exposure, outcome, or mediator.

The estimation of time-varying risks in asset pricing modelling using B-Spline method

Science.gov (United States)

Nurjannah; Solimun; Rinaldo, Adji

2017-12-01

Asset pricing modelling has been extensively studied in the past few decades to explore the risk-return relationship. The asset pricing literature typically assumed a static risk-return relationship. However, several studies found few anomalies in the asset pricing modelling which captured the presence of the risk instability. The dynamic model is proposed to offer a better model. The main problem highlighted in the dynamic model literature is that the set of conditioning information is unobservable and therefore some assumptions have to be made. Hence, the estimation requires additional assumptions about the dynamics of risk. To overcome this problem, the nonparametric estimators can also be used as an alternative for estimating risk. The flexibility of the nonparametric setting avoids the problem of misspecification derived from selecting a functional form. This paper investigates the estimation of time-varying asset pricing model using B-Spline, as one of nonparametric approach. The advantages of spline method is its computational speed and simplicity, as well as the clarity of controlling curvature directly. The three popular asset pricing models will be investigated namely CAPM (Capital Asset Pricing Model), Fama-French 3-factors model and Carhart 4-factors model. The results suggest that the estimated risks are time-varying and not stable overtime which confirms the risk instability anomaly. The results is more pronounced in Carhart’s 4-factors model.

B-Spline potential function for maximum a-posteriori image reconstruction in fluorescence microscopy

Directory of Open Access Journals (Sweden)

Shilpa Dilipkumar

2015-03-01

Full Text Available An iterative image reconstruction technique employing B-Spline potential function in a Bayesian framework is proposed for fluorescence microscopy images. B-splines are piecewise polynomials with smooth transition, compact support and are the shortest polynomial splines. Incorporation of the B-spline potential function in the maximum-a-posteriori reconstruction technique resulted in improved contrast, enhanced resolution and substantial background reduction. The proposed technique is validated on simulated data as well as on the images acquired from fluorescence microscopes (widefield, confocal laser scanning fluorescence and super-resolution 4Pi microscopy. A comparative study of the proposed technique with the state-of-art maximum likelihood (ML and maximum-a-posteriori (MAP with quadratic potential function shows its superiority over the others. B-Spline MAP technique can find applications in several imaging modalities of fluorescence microscopy like selective plane illumination microscopy, localization microscopy and STED.

Recursive B-spline approximation using the Kalman filter

Directory of Open Access Journals (Sweden)

Jens Jauch

2017-02-01

Full Text Available This paper proposes a novel recursive B-spline approximation (RBA algorithm which approximates an unbounded number of data points with a B-spline function and achieves lower computational effort compared with previous algorithms. Conventional recursive algorithms based on the Kalman filter (KF restrict the approximation to a bounded and predefined interval. Conversely RBA includes a novel shift operation that enables to shift estimated B-spline coefficients in the state vector of a KF. This allows to adapt the interval in which the B-spline function can approximate data points during run-time.

P-Splines Using Derivative Information

KAUST Repository

Calderon, Christopher P.; Martinez, Josue G.; Carroll, Raymond J.; Sorensen, Danny C.

2010-01-01

in quantitatively summarizing such data. In this work, functions estimated using P-splines are associated with stochastic differential equations (SDEs). It is shown how quantities estimated in a single SDE summarize fast-scale phenomena, whereas variation between

Space cutter compensation method for five-axis nonuniform rational basis spline machining

Directory of Open Access Journals (Sweden)

Yanyu Ding

2015-07-01

Full Text Available In view of the good machining performance of traditional three-axis nonuniform rational basis spline interpolation and the space cutter compensation issue in multi-axis machining, this article presents a triple nonuniform rational basis spline five-axis interpolation method, which uses three nonuniform rational basis spline curves to describe cutter center location, cutter axis vector, and cutter contact point trajectory, respectively. The relative position of the cutter and workpiece is calculated under the workpiece coordinate system, and the cutter machining trajectory can be described precisely and smoothly using this method. The three nonuniform rational basis spline curves are transformed into a 12-dimentional Bézier curve to carry out discretization during the discrete process. With the cutter contact point trajectory as the precision control condition, the discretization is fast. As for different cutters and corners, the complete description method of space cutter compensation vector is presented in this article. Finally, the five-axis nonuniform rational basis spline machining method is further verified in a two-turntable five-axis machine.

Data approximation using a blending type spline construction

International Nuclear Information System (INIS)

Dalmo, Rune; Bratlie, Jostein

2014-01-01

Generalized expo-rational B-splines (GERBS) is a blending type spline construction where local functions at each knot are blended together by C k -smooth basis functions. One way of approximating discrete regular data using GERBS is by partitioning the data set into subsets and fit a local function to each subset. Partitioning and fitting strategies can be devised such that important or interesting data points are interpolated in order to preserve certain features. We present a method for fitting discrete data using a tensor product GERBS construction. The method is based on detection of feature points using differential geometry. Derivatives, which are necessary for feature point detection and used to construct local surface patches, are approximated from the discrete data using finite differences

Shape Preserving Interpolation Using C2 Rational Cubic Spline

Directory of Open Access Journals (Sweden)

Samsul Ariffin Abdul Karim

2016-01-01

Full Text Available This paper discusses the construction of new C2 rational cubic spline interpolant with cubic numerator and quadratic denominator. The idea has been extended to shape preserving interpolation for positive data using the constructed rational cubic spline interpolation. The rational cubic spline has three parameters αi, βi, and γi. The sufficient conditions for the positivity are derived on one parameter γi while the other two parameters αi and βi are free parameters that can be used to change the final shape of the resulting interpolating curves. This will enable the user to produce many varieties of the positive interpolating curves. Cubic spline interpolation with C2 continuity is not able to preserve the shape of the positive data. Notably our scheme is easy to use and does not require knots insertion and C2 continuity can be achieved by solving tridiagonal systems of linear equations for the unknown first derivatives di, i=1,…,n-1. Comparisons with existing schemes also have been done in detail. From all presented numerical results the new C2 rational cubic spline gives very smooth interpolating curves compared to some established rational cubic schemes. An error analysis when the function to be interpolated is ft∈C3t0,tn is also investigated in detail.

Trajectory control of an articulated robot with a parallel drive arm based on splines under tension

Science.gov (United States)

Yi, Seung-Jong

Today's industrial robots controlled by mini/micro computers are basically simple positioning devices. The positioning accuracy depends on the mathematical description of the robot configuration to place the end-effector at the desired position and orientation within the workspace and on following the specified path which requires the trajectory planner. In addition, the consideration of joint velocity, acceleration, and jerk trajectories are essential for trajectory planning of industrial robots to obtain smooth operation. The newly designed 6 DOF articulated robot with a parallel drive arm mechanism which permits the joint actuators to be placed in the same horizontal line to reduce the arm inertia and to increase load capacity and stiffness is selected. First, the forward kinematic and inverse kinematic problems are examined. The forward kinematic equations are successfully derived based on Denavit-Hartenberg notation with independent joint angle constraints. The inverse kinematic problems are solved using the arm-wrist partitioned approach with independent joint angle constraints. Three types of curve fitting methods used in trajectory planning, i.e., certain degree polynomial functions, cubic spline functions, and cubic spline functions under tension, are compared to select the best possible method to satisfy both smooth joint trajectories and positioning accuracy for a robot trajectory planner. Cubic spline functions under tension is the method selected for the new trajectory planner. This method is implemented for a 6 DOF articulated robot with a parallel drive arm mechanism to improve the smoothness of the joint trajectories and the positioning accuracy of the manipulator. Also, this approach is compared with existing trajectory planners, 4-3-4 polynomials and cubic spline functions, via circular arc motion simulations. The new trajectory planner using cubic spline functions under tension is implemented into the microprocessor based robot controller and

A direct method to solve optimal knots of B-spline curves: An application for non-uniform B-spline curves fitting.

Directory of Open Access Journals (Sweden)

Van Than Dung

Full Text Available B-spline functions are widely used in many industrial applications such as computer graphic representations, computer aided design, computer aided manufacturing, computer numerical control, etc. Recently, there exist some demands, e.g. in reverse engineering (RE area, to employ B-spline curves for non-trivial cases that include curves with discontinuous points, cusps or turning points from the sampled data. The most challenging task in these cases is in the identification of the number of knots and their respective locations in non-uniform space in the most efficient computational cost. This paper presents a new strategy for fitting any forms of curve by B-spline functions via local algorithm. A new two-step method for fast knot calculation is proposed. In the first step, the data is split using a bisecting method with predetermined allowable error to obtain coarse knots. Secondly, the knots are optimized, for both locations and continuity levels, by employing a non-linear least squares technique. The B-spline function is, therefore, obtained by solving the ordinary least squares problem. The performance of the proposed method is validated by using various numerical experimental data, with and without simulated noise, which were generated by a B-spline function and deterministic parametric functions. This paper also discusses the benchmarking of the proposed method to the existing methods in literature. The proposed method is shown to be able to reconstruct B-spline functions from sampled data within acceptable tolerance. It is also shown that, the proposed method can be applied for fitting any types of curves ranging from smooth ones to discontinuous ones. In addition, the method does not require excessive computational cost, which allows it to be used in automatic reverse engineering applications.

An Adaptive B-Spline Method for Low-order Image Reconstruction Problems - Final Report - 09/24/1997 - 09/24/2000

Energy Technology Data Exchange (ETDEWEB)

Li, Xin; Miller, Eric L.; Rappaport, Carey; Silevich, Michael

2000-04-11

A common problem in signal processing is to estimate the structure of an object from noisy measurements linearly related to the desired image. These problems are broadly known as inverse problems. A key feature which complicates the solution to such problems is their ill-posedness. That is, small perturbations in the data arising e.g. from noise can and do lead to severe, non-physical artifacts in the recovered image. The process of stabilizing these problems is known as regularization of which Tikhonov regularization is one of the most common. While this approach leads to a simple linear least squares problem to solve for generating the reconstruction, it has the unfortunate side effect of producing smooth images thereby obscuring important features such as edges. Therefore, over the past decade there has been much work in the development of edge-preserving regularizers. This technique leads to image estimates in which the important features are retained, but computationally the y require the solution of a nonlinear least squares problem, a daunting task in many practical multi-dimensional applications. In this thesis we explore low-order models for reducing the complexity of the re-construction process. Specifically, B-Splines are used to approximate the object. If a ''proper'' collection B-Splines are chosen that the object can be efficiently represented using a few basis functions, the dimensionality of the underlying problem will be significantly decreased. Consequently, an optimum distribution of splines needs to be determined. Here, an adaptive refining and pruning algorithm is developed to solve the problem. The refining part is based on curvature information, in which the intuition is that a relatively dense set of fine scale basis elements should cluster near regions of high curvature while a spares collection of basis vectors are required to adequately represent the object over spatially smooth areas. The pruning part is a greedy

Adaptive estimation of multivariate functions using conditionally Gaussian tensor-product spline priors

NARCIS (Netherlands)

Jonge, de R.; Zanten, van J.H.

2012-01-01

We investigate posterior contraction rates for priors on multivariate functions that are constructed using tensor-product B-spline expansions. We prove that using a hierarchical prior with an appropriate prior distribution on the partition size and Gaussian prior weights on the B-spline

Correcting bias in the rational polynomial coefficients of satellite imagery using thin-plate smoothing splines

Science.gov (United States)

Shen, Xiang; Liu, Bin; Li, Qing-Quan

2017-03-01

The Rational Function Model (RFM) has proven to be a viable alternative to the rigorous sensor models used for geo-processing of high-resolution satellite imagery. Because of various errors in the satellite ephemeris and instrument calibration, the Rational Polynomial Coefficients (RPCs) supplied by image vendors are often not sufficiently accurate, and there is therefore a clear need to correct the systematic biases in order to meet the requirements of high-precision topographic mapping. In this paper, we propose a new RPC bias-correction method using the thin-plate spline modeling technique. Benefiting from its excellent performance and high flexibility in data fitting, the thin-plate spline model has the potential to remove complex distortions in vendor-provided RPCs, such as the errors caused by short-period orbital perturbations. The performance of the new method was evaluated by using Ziyuan-3 satellite images and was compared against the recently developed least-squares collocation approach, as well as the classical affine-transformation and quadratic-polynomial based methods. The results show that the accuracies of the thin-plate spline and the least-squares collocation approaches were better than the other two methods, which indicates that strong non-rigid deformations exist in the test data because they cannot be adequately modeled by simple polynomial-based methods. The performance of the thin-plate spline method was close to that of the least-squares collocation approach when only a few Ground Control Points (GCPs) were used, and it improved more rapidly with an increase in the number of redundant observations. In the test scenario using 21 GCPs (some of them located at the four corners of the scene), the correction residuals of the thin-plate spline method were about 36%, 37%, and 19% smaller than those of the affine transformation method, the quadratic polynomial method, and the least-squares collocation algorithm, respectively, which demonstrates

Optimal Smoothing in Adaptive Location Estimation

OpenAIRE

Mammen, Enno; Park, Byeong U.

1997-01-01

In this paper higher order performance of kernel basedadaptive location estimators are considered. Optimalchoice of smoothing parameters is discussed and it isshown how much is lossed in efficiency by not knowingthe underlying translation density.

Spline and spline wavelet methods with applications to signal and image processing

CERN Document Server

Averbuch, Amir Z; Zheludev, Valery A

This volume provides universal methodologies accompanied by Matlab software to manipulate numerous signal and image processing applications. It is done with discrete and polynomial periodic splines. Various contributions of splines to signal and image processing from a unified perspective are presented. This presentation is based on Zak transform and on Spline Harmonic Analysis (SHA) methodology. SHA combines approximation capabilities of splines with the computational efficiency of the Fast Fourier transform. SHA reduces the design of different spline types such as splines, spline wavelets (SW), wavelet frames (SWF) and wavelet packets (SWP) and their manipulations by simple operations. Digital filters, produced by wavelets design process, give birth to subdivision schemes. Subdivision schemes enable to perform fast explicit computation of splines' values at dyadic and triadic rational points. This is used for signals and images upsampling. In addition to the design of a diverse library of splines, SW, SWP a...

Landmark-based elastic registration using approximating thin-plate splines.

Science.gov (United States)

Rohr, K; Stiehl, H S; Sprengel, R; Buzug, T M; Weese, J; Kuhn, M H

2001-06-01

We consider elastic image registration based on a set of corresponding anatomical point landmarks and approximating thin-plate splines. This approach is an extension of the original interpolating thin-plate spline approach and allows to take into account landmark localization errors. The extension is important for clinical applications since landmark extraction is always prone to error. Our approach is based on a minimizing functional and can cope with isotropic as well as anisotropic landmark errors. In particular, in the latter case it is possible to include different types of landmarks, e.g., unique point landmarks as well as arbitrary edge points. Also, the scheme is general with respect to the image dimension and the order of smoothness of the underlying functional. Optimal affine transformations as well as interpolating thin-plate splines are special cases of this scheme. To localize landmarks we use a semi-automatic approach which is based on three-dimensional (3-D) differential operators. Experimental results are presented for two-dimensional as well as 3-D tomographic images of the human brain.

Approximation and geomatric modeling with simplex B-splines associates with irregular triangular

NARCIS (Netherlands)

Auerbach, S.; Gmelig Meyling, R.H.J.; Neamtu, M.; Neamtu, M.; Schaeben, H.

1991-01-01

Bivariate quadratic simplical B-splines defined by their corresponding set of knots derived from a (suboptimal) constrained Delaunay triangulation of the domain are employed to obtain a C1-smooth surface. The generation of triangle vertices is adjusted to the areal distribution of the data in the

SPLPKG WFCMPR WFAPPX, Wilson-Fowler Spline Generator for Computer Aided Design And Manufacturing (CAD/CAM) Systems

International Nuclear Information System (INIS)

Fletcher, S.K.

2002-01-01

1 - Description of program or function: The three programs SPLPKG, WFCMPR, and WFAPPX provide the capability for interactively generating, comparing and approximating Wilson-Fowler Splines. The Wilson-Fowler spline is widely used in Computer Aided Design and Manufacturing (CAD/CAM) systems. It is favored for many applications because it produces a smooth, low curvature fit to planar data points. Program SPLPKG generates a Wilson-Fowler spline passing through given nodes (with given end conditions) and also generates a piecewise linear approximation to that spline within a user-defined tolerance. The program may be used to generate a 'desired' spline against which to compare other Splines generated by CAD/CAM systems. It may also be used to generate an acceptable approximation to a desired spline in the event that an acceptable spline cannot be generated by the receiving CAD/CAM system. SPLPKG writes an IGES file of points evaluated on the spline and/or a file containing the spline description. Program WFCMPR computes the maximum difference between two Wilson-Fowler Splines and may be used to verify the spline recomputed by a receiving system. It compares two Wilson-Fowler Splines with common nodes and reports the maximum distance between curves (measured perpendicular to segments) and the maximum difference of their tangents (or normals), both computed along the entire length of the Splines. Program WFAPPX computes the maximum difference between a Wilson- Fowler spline and a piecewise linear curve. It may be used to accept or reject a proposed approximation to a desired Wilson-Fowler spline, even if the origin of the approximation is unknown. The maximum deviation between these two curves, and the parameter value on the spline where it occurs are reported. 2 - Restrictions on the complexity of the problem - Maxima of: 1600 evaluation points (SPLPKG), 1000 evaluation points (WFAPPX), 1000 linear curve breakpoints (WFAPPX), 100 spline Nodes

A scalable block-preconditioning strategy for divergence-conforming B-spline discretizations of the Stokes problem

KAUST Repository

Cortes, Adriano Mauricio; Dalcin, Lisandro; Sarmiento, Adel; Collier, N.; Calo, Victor M.

2016-01-01

The recently introduced divergence-conforming B-spline discretizations allow the construction of smooth discrete velocity-pressure pairs for viscous incompressible flows that are at the same time inf−supinf−sup stable and pointwise divergence

Smoothed Spectra, Ogives, and Error Estimates for Atmospheric Turbulence Data

Science.gov (United States)

Dias, Nelson Luís

2018-01-01

A systematic evaluation is conducted of the smoothed spectrum, which is a spectral estimate obtained by averaging over a window of contiguous frequencies. The technique is extended to the ogive, as well as to the cross-spectrum. It is shown that, combined with existing variance estimates for the periodogram, the variance—and therefore the random error—associated with these estimates can be calculated in a straightforward way. The smoothed spectra and ogives are biased estimates; with simple power-law analytical models, correction procedures are devised, as well as a global constraint that enforces Parseval's identity. Several new results are thus obtained: (1) The analytical variance estimates compare well with the sample variance calculated for the Bartlett spectrum and the variance of the inertial subrange of the cospectrum is shown to be relatively much larger than that of the spectrum. (2) Ogives and spectra estimates with reduced bias are calculated. (3) The bias of the smoothed spectrum and ogive is shown to be negligible at the higher frequencies. (4) The ogives and spectra thus calculated have better frequency resolution than the Bartlett spectrum, with (5) gradually increasing variance and relative error towards the low frequencies. (6) Power-law identification and extraction of the rate of dissipation of turbulence kinetic energy are possible directly from the ogive. (7) The smoothed cross-spectrum is a valid inner product and therefore an acceptable candidate for coherence and spectral correlation coefficient estimation by means of the Cauchy-Schwarz inequality. The quadrature, phase function, coherence function and spectral correlation function obtained from the smoothed spectral estimates compare well with the classical ones derived from the Bartlett spectrum.

A robust method of thin plate spline and its application to DEM construction

Science.gov (United States)

Chen, Chuanfa; Li, Yanyan

2012-11-01

In order to avoid the ill-conditioning problem of thin plate spline (TPS), the orthogonal least squares (OLS) method was introduced, and a modified OLS (MOLS) was developed. The MOLS of TPS (TPS-M) can not only select significant points, termed knots, from large and dense sampling data sets, but also easily compute the weights of the knots in terms of back-substitution. For interpolating large sampling points, we developed a local TPS-M, where some neighbor sampling points around the point being estimated are selected for computation. Numerical tests indicate that irrespective of sampling noise level, the average performance of TPS-M can advantage with smoothing TPS. Under the same simulation accuracy, the computational time of TPS-M decreases with the increase of the number of sampling points. The smooth fitting results on lidar-derived noise data indicate that TPS-M has an obvious smoothing effect, which is on par with smoothing TPS. The example of constructing a series of large scale DEMs, located in Shandong province, China, was employed to comparatively analyze the estimation accuracies of the two versions of TPS and the classical interpolation methods including inverse distance weighting (IDW), ordinary kriging (OK) and universal kriging with the second-order drift function (UK). Results show that regardless of sampling interval and spatial resolution, TPS-M is more accurate than the classical interpolation methods, except for the smoothing TPS at the finest sampling interval of 20 m, and the two versions of kriging at the spatial resolution of 15 m. In conclusion, TPS-M, which avoids the ill-conditioning problem, is considered as a robust method for DEM construction.

Statistical analysis of sediment toxicity by additive monotone regression splines

NARCIS (Netherlands)

Boer, de W.J.; Besten, den P.J.; Braak, ter C.J.F.

2002-01-01

Modeling nonlinearity and thresholds in dose-effect relations is a major challenge, particularly in noisy data sets. Here we show the utility of nonlinear regression with additive monotone regression splines. These splines lead almost automatically to the estimation of thresholds. We applied this

Gamma Splines and Wavelets

Directory of Open Access Journals (Sweden)

Hannu Olkkonen

2013-01-01

Full Text Available In this work we introduce a new family of splines termed as gamma splines for continuous signal approximation and multiresolution analysis. The gamma splines are born by -times convolution of the exponential by itself. We study the properties of the discrete gamma splines in signal interpolation and approximation. We prove that the gamma splines obey the two-scale equation based on the polyphase decomposition. to introduce the shift invariant gamma spline wavelet transform for tree structured subscale analysis of asymmetric signal waveforms and for systems with asymmetric impulse response. Especially we consider the applications in biomedical signal analysis (EEG, ECG, and EMG. Finally, we discuss the suitability of the gamma spline signal processing in embedded VLSI environment.

Smooth time-dependent receiver operating characteristic curve estimators.

Science.gov (United States)

Martínez-Camblor, Pablo; Pardo-Fernández, Juan Carlos

2018-03-01

The receiver operating characteristic curve is a popular graphical method often used to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, two main extensions have been proposed: the cumulative/dynamic receiver operating characteristic curve and the incident/dynamic receiver operating characteristic curve. In both cases, the main problem for developing appropriate estimators is the estimation of the joint distribution of the variables time-to-event and marker. As usual, different approximations lead to different estimators. In this article, the authors explore the use of a bivariate kernel density estimator which accounts for censored observations in the sample and produces smooth estimators of the time-dependent receiver operating characteristic curves. The performance of the resulting cumulative/dynamic and incident/dynamic receiver operating characteristic curves is studied by means of Monte Carlo simulations. Additionally, the influence of the choice of the required smoothing parameters is explored. Finally, two real-applications are considered. An R package is also provided as a complement to this article.

The smoothing and fast Fourier transformation of experimental X-ray and neutron data from amorphous materials

International Nuclear Information System (INIS)

Dixon, M.; Wright, A.C.; Hutchinson, P.

1977-01-01

The application of fast Fourier transformation techniques to the analysis of experimental X-ray and neutron diffraction patterns from amorphous materials is discussed and compared with conventional techniques using Filon's quadrature. The fast Fourier transform package described also includes cubic spline smoothing and has been extensively tested, using model data to which statistical errors have been added by means of a pseudo-random number generator with Gaussian shaper. Neither cubic spline nor hand smoothing has much effect on the resulting transform since the noise removed is of too high a frequency. (Auth.)

Smoothed Conditional Scale Function Estimation in AR(1-ARCH(1 Processes

Directory of Open Access Journals (Sweden)

Lema Logamou Seknewna

2018-01-01

Full Text Available The estimation of the Smoothed Conditional Scale Function for time series was taken out under the conditional heteroscedastic innovations by imitating the kernel smoothing in nonparametric QAR-QARCH scheme. The estimation was taken out based on the quantile regression methodology proposed by Koenker and Bassett. And the proof of the asymptotic properties of the Conditional Scale Function estimator for this type of process was given and its consistency was shown.

A method for fitting regression splines with varying polynomial order in the linear mixed model.

Science.gov (United States)

Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

2006-02-15

The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

Designing interactively with elastic splines

DEFF Research Database (Denmark)

Brander, David; Bærentzen, Jakob Andreas; Fisker, Ann-Sofie

2018-01-01

We present an algorithm for designing interactively with C1 elastic splines. The idea is to design the elastic spline using a C1 cubic polynomial spline where each polynomial segment is so close to satisfying the Euler-Lagrange equation for elastic curves that the visual difference becomes neglig...... negligible. Using a database of cubic Bézier curves we are able to interactively modify the cubic spline such that it remains visually close to an elastic spline....

Smooth individual level covariates adjustment in disease mapping.

Science.gov (United States)

Huque, Md Hamidul; Anderson, Craig; Walton, Richard; Woolford, Samuel; Ryan, Louise

2018-05-01

Spatial models for disease mapping should ideally account for covariates measured both at individual and area levels. The newly available "indiCAR" model fits the popular conditional autoregresssive (CAR) model by accommodating both individual and group level covariates while adjusting for spatial correlation in the disease rates. This algorithm has been shown to be effective but assumes log-linear associations between individual level covariates and outcome. In many studies, the relationship between individual level covariates and the outcome may be non-log-linear, and methods to track such nonlinearity between individual level covariate and outcome in spatial regression modeling are not well developed. In this paper, we propose a new algorithm, smooth-indiCAR, to fit an extension to the popular conditional autoregresssive model that can accommodate both linear and nonlinear individual level covariate effects while adjusting for group level covariates and spatial correlation in the disease rates. In this formulation, the effect of a continuous individual level covariate is accommodated via penalized splines. We describe a two-step estimation procedure to obtain reliable estimates of individual and group level covariate effects where both individual and group level covariate effects are estimated separately. This distributed computing framework enhances its application in the Big Data domain with a large number of individual/group level covariates. We evaluate the performance of smooth-indiCAR through simulation. Our results indicate that the smooth-indiCAR method provides reliable estimates of all regression and random effect parameters. We illustrate our proposed methodology with an analysis of data on neutropenia admissions in New South Wales (NSW), Australia. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spline techniques for magnetic fields

International Nuclear Information System (INIS)

Aspinall, J.G.

1984-01-01

This report is an overview of B-spline techniques, oriented toward magnetic field computation. These techniques form a powerful mathematical approximating method for many physics and engineering calculations. In section 1, the concept of a polynomial spline is introduced. Section 2 shows how a particular spline with well chosen properties, the B-spline, can be used to build any spline. In section 3, the description of how to solve a simple spline approximation problem is completed, and some practical examples of using splines are shown. All these sections deal exclusively in scalar functions of one variable for simplicity. Section 4 is partly digression. Techniques that are not B-spline techniques, but are closely related, are covered. These methods are not needed for what follows, until the last section on errors. Sections 5, 6, and 7 form a second group which work toward the final goal of using B-splines to approximate a magnetic field. Section 5 demonstrates how to approximate a scalar function of many variables. The necessary mathematics is completed in section 6, where the problems of approximating a vector function in general, and a magnetic field in particular, are examined. Finally some algorithms and data organization are shown in section 7. Section 8 deals with error analysis

ESTIMATION OF GENETIC PARAMETERS IN TROPICARNE CATTLE WITH RANDOM REGRESSION MODELS USING B-SPLINES

Directory of Open Access Journals (Sweden)

Joel Domínguez Viveros

2015-04-01

Full Text Available The objectives were to estimate variance components, and direct (h2 and maternal (m2 heritability in the growth of Tropicarne cattle based on a random regression model using B-Splines for random effects modeling. Information from 12 890 monthly weightings of 1787 calves, from birth to 24 months old, was analyzed. The pedigree included 2504 animals. The random effects model included genetic and permanent environmental (direct and maternal of cubic order, and residuals. The fixed effects included contemporaneous groups (year – season of weighed, sex and the covariate age of the cow (linear and quadratic. The B-Splines were defined in four knots through the growth period analyzed. Analyses were performed with the software Wombat. The variances (phenotypic and residual presented a similar behavior; of 7 to 12 months of age had a negative trend; from birth to 6 months and 13 to 18 months had positive trend; after 19 months were maintained constant. The m2 were low and near to zero, with an average of 0.06 in an interval of 0.04 to 0.11; the h2 also were close to zero, with an average of 0.10 in an interval of 0.03 to 0.23.

Selected Aspects of Wear Affecting Keyed Joints and Spline Connections During Operation of Aircrafts

Directory of Open Access Journals (Sweden)

Gębura Andrzej

2014-12-01

Full Text Available The paper deals with selected deficiencies of spline connections, such as angular or parallel misalignment (eccentricity and excessive play. It is emphasized how important these deficiencies are for smooth operation of the entire driving units. The aim of the study is to provide a kind of a reference list with such deficiencies with visual symptoms of wear, specification of mechanical measurements for mating surfaces, mathematical description of waveforms for dynamic variability of motion in such connections and visualizations of the connection behaviour acquired with the use of the FAM-C and FDM-A. Attention is paid to hazards to flight safety when excessively worn spline connections are operated for long periods of time

B-Spline Active Contour with Handling of Topology Changes for Fast Video Segmentation

Directory of Open Access Journals (Sweden)

Frederic Precioso

2002-06-01

Full Text Available This paper deals with video segmentation for MPEG-4 and MPEG-7 applications. Region-based active contour is a powerful technique for segmentation. However most of these methods are implemented using level sets. Although level-set methods provide accurate segmentation, they suffer from large computational cost. We propose to use a regular B-spline parametric method to provide a fast and accurate segmentation. Our B-spline interpolation is based on a fixed number of points 2j depending on the level of the desired details. Through this spatial multiresolution approach, the computational cost of the segmentation is reduced. We introduce a length penalty. This results in improving both smoothness and accuracy. Then we show some experiments on real-video sequences.

Spline approximation, Part 1: Basic methodology

Science.gov (United States)

Ezhov, Nikolaj; Neitzel, Frank; Petrovic, Svetozar

2018-04-01

In engineering geodesy point clouds derived from terrestrial laser scanning or from photogrammetric approaches are almost never used as final results. For further processing and analysis a curve or surface approximation with a continuous mathematical function is required. In this paper the approximation of 2D curves by means of splines is treated. Splines offer quite flexible and elegant solutions for interpolation or approximation of "irregularly" distributed data. Depending on the problem they can be expressed as a function or as a set of equations that depend on some parameter. Many different types of splines can be used for spline approximation and all of them have certain advantages and disadvantages depending on the approximation problem. In a series of three articles spline approximation is presented from a geodetic point of view. In this paper (Part 1) the basic methodology of spline approximation is demonstrated using splines constructed from ordinary polynomials and splines constructed from truncated polynomials. In the forthcoming Part 2 the notion of B-spline will be explained in a unique way, namely by using the concept of convex combinations. The numerical stability of all spline approximation approaches as well as the utilization of splines for deformation detection will be investigated on numerical examples in Part 3.

Spline Interpolation of Image

OpenAIRE

I. Kuba; J. Zavacky; J. Mihalik

1995-01-01

This paper presents the use of B spline functions in various digital signal processing applications. The theory of one-dimensional B spline interpolation is briefly reviewed, followed by its extending to two dimensions. After presenting of one and two dimensional spline interpolation, the algorithms of image interpolation and resolution increasing were proposed. Finally, experimental results of computer simulations are presented.

Isogeometric analysis using T-splines

KAUST Repository

Bazilevs, Yuri

2010-01-01

We explore T-splines, a generalization of NURBS enabling local refinement, as a basis for isogeometric analysis. We review T-splines as a surface design methodology and then develop it for engineering analysis applications. We test T-splines on some elementary two-dimensional and three-dimensional fluid and structural analysis problems and attain good results in all cases. We summarize the current status of T-splines, their limitations, and future possibilities. © 2009 Elsevier B.V.

Maximum profile likelihood estimation of differential equation parameters through model based smoothing state estimates.

Science.gov (United States)

Campbell, D A; Chkrebtii, O

2013-12-01

Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

Efectivity of Additive Spline for Partial Least Square Method in Regression Model Estimation

Directory of Open Access Journals (Sweden)

Ahmad Bilfarsah

2005-04-01

Full Text Available Additive Spline of Partial Least Square method (ASPL as one generalization of Partial Least Square (PLS method. ASPLS method can be acommodation to non linear and multicollinearity case of predictor variables. As a principle, The ASPLS method approach is cahracterized by two idea. The first is to used parametric transformations of predictors by spline function; the second is to make ASPLS components mutually uncorrelated, to preserve properties of the linear PLS components. The performance of ASPLS compared with other PLS method is illustrated with the fisher economic application especially the tuna fish production.

Hilbertian kernels and spline functions

CERN Document Server

Atteia, M

1992-01-01

In this monograph, which is an extensive study of Hilbertian approximation, the emphasis is placed on spline functions theory. The origin of the book was an effort to show that spline theory parallels Hilbertian Kernel theory, not only for splines derived from minimization of a quadratic functional but more generally for splines considered as piecewise functions type. Being as far as possible self-contained, the book may be used as a reference, with information about developments in linear approximation, convex optimization, mechanics and partial differential equations.

Symmetric, discrete fractional splines and Gabor systems

DEFF Research Database (Denmark)

Søndergaard, Peter Lempel

2006-01-01

In this paper we consider fractional splines as windows for Gabor frames. We introduce two new types of symmetric, fractional splines in addition to one found by Unser and Blu. For the finite, discrete case we present two families of splines: One is created by sampling and periodizing the continu......In this paper we consider fractional splines as windows for Gabor frames. We introduce two new types of symmetric, fractional splines in addition to one found by Unser and Blu. For the finite, discrete case we present two families of splines: One is created by sampling and periodizing...... the continuous splines, and one is a truly finite, discrete construction. We discuss the properties of these splines and their usefulness as windows for Gabor frames and Wilson bases....

Interpolation of natural cubic spline

Directory of Open Access Journals (Sweden)

Arun Kumar

1992-01-01

Full Text Available From the result in [1] it follows that there is a unique quadratic spline which bounds the same area as that of the function. The matching of the area for the cubic spline does not follow from the corresponding result proved in [2]. We obtain cubic splines which preserve the area of the function.

A Bayesian-optimized spline representation of the electrocardiogram

International Nuclear Information System (INIS)

Guilak, F G; McNames, J

2013-01-01

We introduce an implementation of a novel spline framework for parametrically representing electrocardiogram (ECG) waveforms. This implementation enables a flexible means to study ECG structure in large databases. Our algorithm allows researchers to identify key points in the waveform and optimally locate them in long-term recordings with minimal manual effort, thereby permitting analysis of trends in the points themselves or in metrics derived from their locations. In the work described here we estimate the location of a number of commonly-used characteristic points of the ECG signal, defined as the onsets, peaks, and offsets of the P, QRS, T, and R′ waves. The algorithm applies Bayesian optimization to a linear spline representation of the ECG waveform. The location of the knots—which are the endpoints of the piecewise linear segments used in the spline representation of the signal—serve as the estimate of the waveform’s characteristic points. We obtained prior information of knot times, amplitudes, and curvature from a large manually-annotated training dataset and used the priors to optimize a Bayesian figure of merit based on estimated knot locations. In cases where morphologies vary or are subject to noise, the algorithm relies more heavily on the estimated priors for its estimate of knot locations. We compared optimized knot locations from our algorithm to two sets of manual annotations on a prospective test data set comprising 200 beats from 20 subjects not in the training set. Mean errors of characteristic point locations were less than four milliseconds, and standard deviations of errors compared favorably against reference values. This framework can easily be adapted to include additional points of interest in the ECG signal or for other biomedical detection problems on quasi-periodic signals. (paper)

Smoothing of, and parameter estimation from, noisy biophysical recordings.

Directory of Open Access Journals (Sweden)

Quentin J M Huys

2009-05-01

Full Text Available Biophysically detailed models of single cells are difficult to fit to real data. Recent advances in imaging techniques allow simultaneous access to various intracellular variables, and these data can be used to significantly facilitate the modelling task. These data, however, are noisy, and current approaches to building biophysically detailed models are not designed to deal with this. We extend previous techniques to take the noisy nature of the measurements into account. Sequential Monte Carlo ("particle filtering" methods, in combination with a detailed biophysical description of a cell, are used for principled, model-based smoothing of noisy recording data. We also provide an alternative formulation of smoothing where the neural nonlinearities are estimated in a non-parametric manner. Biophysically important parameters of detailed models (such as channel densities, intercompartmental conductances, input resistances, and observation noise are inferred automatically from noisy data via expectation-maximization. Overall, we find that model-based smoothing is a powerful, robust technique for smoothing of noisy biophysical data and for inference of biophysical parameters in the face of recording noise.

Final report on Production Test No. 105-245-P -- Effectiveness of cadmium coated splines

Energy Technology Data Exchange (ETDEWEB)

Carson, A.B.

1949-05-19

This report discussed cadmium coated splines which have been developed to supplement the regular control rod systems under emergency shutdown conditions from higher power levels. The objective of this test was to determine the effectiveness of one such spline placed in a tube in the central zone of a pile, and of two splines in the same tube. In addition, the process control group of the P Division asked that probable spline requirements for safe operation at various power levels be estimated, and the details included in this report. The results of the test indicated a reactivity value of 10.5 {plus_minus} 1.0 ih for a single spline, and 19.0 ih {plus_minus} 1.0 ihfor two splines in tube 1674-B under the loading conditions of 4-27-49, the date of the test. The temperature rise of the cooling water for this tube under these conditions was found to be 37.2{degrees}C for 275 MW operation.

Smoothing internal migration age profiles for comparative research

Directory of Open Access Journals (Sweden)

Aude Bernard

2015-05-01

Full Text Available Background: Age patterns are a key dimension to compare migration between countries and over time. Comparative metrics can be reliably computed only if data capture the underlying age distribution of migration. Model schedules, the prevailing smoothing method, fit a composite exponential function, but are sensitive to function selection and initial parameter setting. Although non-parametric alternatives exist, their performance is yet to be established. Objective: We compare cubic splines and kernel regressions against model schedules by assessingwhich method provides an accurate representation of the age profile and best performs on metrics for comparing aggregate age patterns. Methods: We use full population microdata for Chile to perform 1,000 Monte-Carlo simulations for nine sample sizes and two spatial scales. We use residual and graphic analysis to assess model performance on the age and intensity at which migration peaks and the evolution of migration age patterns. Results: Model schedules generate a better fit when (1 the expected distribution of the age profile is known a priori, (2 the pre-determined shape of the model schedule adequately describes the true age distribution, and (3 the component curves and initial parameter values can be correctly set. When any of these conditions is not met, kernel regressions and cubic splines offer more reliable alternatives. Conclusions: Smoothing models should be selected according to research aims, age profile characteristics, and sample size. Kernel regressions and cubic splines enable a precise representation of aggregate migration age profiles for most sample sizes, without requiring parameter setting or imposing a pre-determined distribution, and therefore facilitate objective comparison.

Geometric and computer-aided spline hob modeling

Science.gov (United States)

Brailov, I. G.; Myasoedova, T. M.; Panchuk, K. L.; Krysova, I. V.; Rogoza, YU A.

2018-03-01

The paper considers acquiring the spline hob geometric model. The objective of the research is the development of a mathematical model of spline hob for spline shaft machining. The structure of the spline hob is described taking into consideration the motion in parameters of the machine tool system of cutting edge positioning and orientation. Computer-aided study is performed with the use of CAD and on the basis of 3D modeling methods. Vector representation of cutting edge geometry is accepted as the principal method of spline hob mathematical model development. The paper defines the correlations described by parametric vector functions representing helical cutting edges designed for spline shaft machining with consideration for helical movement in two dimensions. An application for acquiring the 3D model of spline hob is developed on the basis of AutoLISP for AutoCAD environment. The application presents the opportunity for the use of the acquired model for milling process imitation. An example of evaluation, analytical representation and computer modeling of the proposed geometrical model is reviewed. In the mentioned example, a calculation of key spline hob parameters assuring the capability of hobbing a spline shaft of standard design is performed. The polygonal and solid spline hob 3D models are acquired by the use of imitational computer modeling.

Fingerprint Matching by Thin-plate Spline Modelling of Elastic Deformations

NARCIS (Netherlands)

Bazen, A.M.; Gerez, Sabih H.

2003-01-01

This paper presents a novel minutiae matching method that describes elastic distortions in fingerprints by means of a thin-plate spline model, which is estimated using a local and a global matching stage. After registration of the fingerprints according to the estimated model, the number of matching

Straight-sided Spline Optimization

DEFF Research Database (Denmark)

Pedersen, Niels Leergaard

2011-01-01

and the subject of improving the design. The present paper concentrates on the optimization of splines and the predictions of stress concentrations, which are determined by finite element analysis (FEA). Using design modifications, that do not change the spline load carrying capacity, it is shown that large...

A Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Data

KAUST Repository

Gazioglu, Suzan

2013-05-25

Primary analysis of case-control studies focuses on the relationship between disease (D) and a set of covariates of interest (Y, X). A secondary application of the case-control study, often invoked in modern genetic epidemiologic association studies, is to investigate the interrelationship between the covariates themselves. The task is complicated due to the case-control sampling, and to avoid the biased sampling that arises from the design, it is typical to use the control data only. In this paper, we develop penalized regression spline methodology that uses all the data, and improves precision of estimation compared to using only the controls. A simulation study and an empirical example are used to illustrate the methodology.

A Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Data

KAUST Repository

Gazioglu, Suzan; Wei, Jiawei; Jennings, Elizabeth M.; Carroll, Raymond J.

2013-01-01

Primary analysis of case-control studies focuses on the relationship between disease (D) and a set of covariates of interest (Y, X). A secondary application of the case-control study, often invoked in modern genetic epidemiologic association studies, is to investigate the interrelationship between the covariates themselves. The task is complicated due to the case-control sampling, and to avoid the biased sampling that arises from the design, it is typical to use the control data only. In this paper, we develop penalized regression spline methodology that uses all the data, and improves precision of estimation compared to using only the controls. A simulation study and an empirical example are used to illustrate the methodology.

On Characterization of Quadratic Splines

DEFF Research Database (Denmark)

Chen, B. T.; Madsen, Kaj; Zhang, Shuzhong

2005-01-01

that the representation can be refined in a neighborhood of a non-degenerate point and a set of non-degenerate minimizers. Based on these characterizations, many existing algorithms for specific convex quadratic splines are also finite convergent for a general convex quadratic spline. Finally, we study the relationship...... between the convexity of a quadratic spline function and the monotonicity of the corresponding LCP problem. It is shown that, although both conditions lead to easy solvability of the problem, they are different in general....

B-splines and Faddeev equations

International Nuclear Information System (INIS)

Huizing, A.J.

1990-01-01

Two numerical methods for solving the three-body equations describing relativistic pion deuteron scattering have been investigated. For separable two body interactions these equations form a set of coupled one-dimensional integral equations. They are plagued by singularities which occur in the kernel of the integral equations as well as in the solution. The methods to solve these equations differ in the way they treat the singularities. First the Fuda-Stuivenberg method is discussed. The basic idea of this method is an one time iteration of the set of integral equations to treat the logarithmic singularities. In the second method, the spline method, the unknown solution is approximated by splines. Cubic splines have been used with cubic B-splines as basis. If the solution is approximated by a linear combination of basis functions, an integral equation can be transformed into a set of linear equations for the expansion coefficients. This set of linear equations is solved by standard means. Splines are determined by points called knots. A proper choice of splines to approach the solution stands for a proper choice of the knots. The solution of the three-body scattering equations has a square root behaviour at a certain point. Hence it was investigated how the knots should be chosen to approximate the square root function by cubic B-splines in an optimal way. Before applying this method to solve numerically the three-body equations describing pion-deuteron scattering, an analytically solvable example has been constructed with a singularity structure of both kernel and solution comparable to those of the three-body equations. The accuracy of the numerical solution was determined to a large extent by the accuracy of the approximation of the square root part. The results for a pion laboratory energy of 47.4 MeV agree very well with those from literature. In a complete calculation for 47.7 MeV the spline method turned out to be a factor thousand faster than the Fuda

4D-PET reconstruction using a spline-residue model with spatial and temporal roughness penalties

Science.gov (United States)

Ralli, George P.; Chappell, Michael A.; McGowan, Daniel R.; Sharma, Ricky A.; Higgins, Geoff S.; Fenwick, John D.

2018-05-01

4D reconstruction of dynamic positron emission tomography (dPET) data can improve the signal-to-noise ratio in reconstructed image sequences by fitting smooth temporal functions to the voxel time-activity-curves (TACs) during the reconstruction, though the optimal choice of function remains an open question. We propose a spline-residue model, which describes TACs as weighted sums of convolutions of the arterial input function with cubic B-spline basis functions. Convolution with the input function constrains the spline-residue model at early time-points, potentially enhancing noise suppression in early time-frames, while still allowing a wide range of TAC descriptions over the entire imaged time-course, thus limiting bias. Spline-residue based 4D-reconstruction is compared to that of a conventional (non-4D) maximum a posteriori (MAP) algorithm, and to 4D-reconstructions based on adaptive-knot cubic B-splines, the spectral model and an irreversible two-tissue compartment (‘2C3K’) model. 4D reconstructions were carried out using a nested-MAP algorithm including spatial and temporal roughness penalties. The algorithms were tested using Monte-Carlo simulated scanner data, generated for a digital thoracic phantom with uptake kinetics based on a dynamic [18F]-Fluromisonidazole scan of a non-small cell lung cancer patient. For every algorithm, parametric maps were calculated by fitting each voxel TAC within a sub-region of the reconstructed images with the 2C3K model. Compared to conventional MAP reconstruction, spline-residue-based 4D reconstruction achieved  >50% improvements for five of the eight combinations of the four kinetics parameters for which parametric maps were created with the bias and noise measures used to analyse them, and produced better results for 5/8 combinations than any of the other reconstruction algorithms studied, while spectral model-based 4D reconstruction produced the best results for 2/8. 2C3K model-based 4D reconstruction generated

Differential constraints for bounded recursive identification with multivariate splines

NARCIS (Netherlands)

De Visser, C.C.; Chu, Q.P.; Mulder, J.A.

2011-01-01

The ability to perform online model identification for nonlinear systems with unknown dynamics is essential to any adaptive model-based control system. In this paper, a new differential equality constrained recursive least squares estimator for multivariate simplex splines is presented that is able

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

Science.gov (United States)

Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19

Gaussian quadrature for splines via homotopy continuation: Rules for C2 cubic splines

KAUST Repository

Barton, Michael

2015-10-24

We introduce a new concept for generating optimal quadrature rules for splines. To generate an optimal quadrature rule in a given (target) spline space, we build an associated source space with known optimal quadrature and transfer the rule from the source space to the target one, while preserving the number of quadrature points and therefore optimality. The quadrature nodes and weights are, considered as a higher-dimensional point, a zero of a particular system of polynomial equations. As the space is continuously deformed by changing the source knot vector, the quadrature rule gets updated using polynomial homotopy continuation. For example, starting with C1C1 cubic splines with uniform knot sequences, we demonstrate the methodology by deriving the optimal rules for uniform C2C2 cubic spline spaces where the rule was only conjectured to date. We validate our algorithm by showing that the resulting quadrature rule is independent of the path chosen between the target and the source knot vectors as well as the source rule chosen.

Gaussian quadrature for splines via homotopy continuation: Rules for C2 cubic splines

KAUST Repository

Barton, Michael; Calo, Victor M.

2015-01-01

We introduce a new concept for generating optimal quadrature rules for splines. To generate an optimal quadrature rule in a given (target) spline space, we build an associated source space with known optimal quadrature and transfer the rule from the source space to the target one, while preserving the number of quadrature points and therefore optimality. The quadrature nodes and weights are, considered as a higher-dimensional point, a zero of a particular system of polynomial equations. As the space is continuously deformed by changing the source knot vector, the quadrature rule gets updated using polynomial homotopy continuation. For example, starting with C1C1 cubic splines with uniform knot sequences, we demonstrate the methodology by deriving the optimal rules for uniform C2C2 cubic spline spaces where the rule was only conjectured to date. We validate our algorithm by showing that the resulting quadrature rule is independent of the path chosen between the target and the source knot vectors as well as the source rule chosen.

Multivariate Hermite interpolation on scattered point sets using tensor-product expo-rational B-splines

Science.gov (United States)

Dechevsky, Lubomir T.; Bang, Børre; Laksa˚, Arne; Zanaty, Peter

2011-12-01

At the Seventh International Conference on Mathematical Methods for Curves and Surfaces, To/nsberg, Norway, in 2008, several new constructions for Hermite interpolation on scattered point sets in domains in Rn,n∈N, combined with smooth convex partition of unity for several general types of partitions of these domains were proposed in [1]. All of these constructions were based on a new type of B-splines, proposed by some of the authors several years earlier: expo-rational B-splines (ERBS) [3]. In the present communication we shall provide more details about one of these constructions: the one for the most general class of domain partitions considered. This construction is based on the use of two separate families of basis functions: one which has all the necessary Hermite interpolation properties, and another which has the necessary properties of a smooth convex partition of unity. The constructions of both of these two bases are well-known; the new part of the construction is the combined use of these bases for the derivation of a new basis which enjoys having all above-said interpolation and unity partition properties simultaneously. In [1] the emphasis was put on the use of radial basis functions in the definitions of the two initial bases in the construction; now we shall put the main emphasis on the case when these bases consist of tensor-product B-splines. This selection provides two useful advantages: (A) it is easier to compute higher-order derivatives while working in Cartesian coordinates; (B) it becomes clear that this construction becomes a far-going extension of tensor-product constructions. We shall provide 3-dimensional visualization of the resulting bivariate bases, using tensor-product ERBS. In the main tensor-product variant, we shall consider also replacement of ERBS with simpler generalized ERBS (GERBS) [2], namely, their simplified polynomial modifications: the Euler Beta-function B-splines (BFBS). One advantage of using BFBS instead of ERBS

Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models

DEFF Research Database (Denmark)

Gørgens, Tue; Skeels, Christopher L.; Wurtz, Allan

This paper explores estimation of a class of non-linear dynamic panel data models with additive unobserved individual-specific effects. The models are specified by moment restrictions. The class includes the panel data AR(p) model and panel smooth transition models. We derive an efficient set...... of moment restrictions for estimation and apply the results to estimation of panel smooth transition models with fixed effects, where the transition may be determined endogenously. The performance of the GMM estimator, both in terms of estimation precision and forecasting performance, is examined in a Monte...

Influence of smoothing of X-ray spectra on parameters of calibration model

International Nuclear Information System (INIS)

Antoniak, W.; Urbanski, P.; Kowalska, E.

1998-01-01

Parameters of the calibration model before and after smoothing of X-ray spectra have been investigated. The calibration model was calculated using multivariate procedure - namely the partial least square regression (PLS). Investigations have been performed on an example of six sets of various standards used for calibration of some instruments based on X-ray fluorescence principle. The smoothing methods were compared: regression splines, Savitzky-Golay and Discrete Fourier Transform. The calculations were performed using a software package MATLAB and some home-made programs. (author)

Surface Estimation, Variable Selection, and the Nonparametric Oracle Property.

Science.gov (United States)

Storlie, Curtis B; Bondell, Howard D; Reich, Brian J; Zhang, Hao Helen

2011-04-01

Variable selection for multivariate nonparametric regression is an important, yet challenging, problem due, in part, to the infinite dimensionality of the function space. An ideal selection procedure should be automatic, stable, easy to use, and have desirable asymptotic properties. In particular, we define a selection procedure to be nonparametric oracle (np-oracle) if it consistently selects the correct subset of predictors and at the same time estimates the smooth surface at the optimal nonparametric rate, as the sample size goes to infinity. In this paper, we propose a model selection procedure for nonparametric models, and explore the conditions under which the new method enjoys the aforementioned properties. Developed in the framework of smoothing spline ANOVA, our estimator is obtained via solving a regularization problem with a novel adaptive penalty on the sum of functional component norms. Theoretical properties of the new estimator are established. Additionally, numerous simulated and real examples further demonstrate that the new approach substantially outperforms other existing methods in the finite sample setting.

Estimation and variable selection for generalized additive partial linear models

KAUST Repository

Wang, Li

2011-08-01

We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.

B-spline Collocation with Domain Decomposition Method

International Nuclear Information System (INIS)

Hidayat, M I P; Parman, S; Ariwahjoedi, B

2013-01-01

A global B-spline collocation method has been previously developed and successfully implemented by the present authors for solving elliptic partial differential equations in arbitrary complex domains. However, the global B-spline approximation, which is simply reduced to Bezier approximation of any degree p with C 0 continuity, has led to the use of B-spline basis of high order in order to achieve high accuracy. The need for B-spline bases of high order in the global method would be more prominent in domains of large dimension. For the increased collocation points, it may also lead to the ill-conditioning problem. In this study, overlapping domain decomposition of multiplicative Schwarz algorithm is combined with the global method. Our objective is two-fold that improving the accuracy with the combination technique, and also investigating influence of the combination technique to the employed B-spline basis orders with respect to the obtained accuracy. It was shown that the combination method produced higher accuracy with the B-spline basis of much lower order than that needed in implementation of the initial method. Hence, the approximation stability of the B-spline collocation method was also increased.

Comparison of volatility function technique for risk-neutral densities estimation

Science.gov (United States)

Bahaludin, Hafizah; Abdullah, Mimi Hafizah

2017-08-01

Volatility function technique by using interpolation approach plays an important role in extracting the risk-neutral density (RND) of options. The aim of this study is to compare the performances of two interpolation approaches namely smoothing spline and fourth order polynomial in extracting the RND. The implied volatility of options with respect to strike prices/delta are interpolated to obtain a well behaved density. The statistical analysis and forecast accuracy are tested using moments of distribution. The difference between the first moment of distribution and the price of underlying asset at maturity is used as an input to analyze forecast accuracy. RNDs are extracted from the Dow Jones Industrial Average (DJIA) index options with a one month constant maturity for the period from January 2011 until December 2015. The empirical results suggest that the estimation of RND using a fourth order polynomial is more appropriate to be used compared to a smoothing spline in which the fourth order polynomial gives the lowest mean square error (MSE). The results can be used to help market participants capture market expectations of the future developments of the underlying asset.

Applications of the spline filter for areal filtration

International Nuclear Information System (INIS)

Tong, Mingsi; Zhang, Hao; Ott, Daniel; Chu, Wei; Song, John

2015-01-01

This paper proposes a general use isotropic areal spline filter. This new areal spline filter can achieve isotropy by approximating the transmission characteristic of the Gaussian filter. It can also eliminate the effect of void areas using a weighting factor, and resolve end-effect issues by applying new boundary conditions, which replace the first order finite difference in the traditional spline formulation. These improvements make the spline filter widely applicable to 3D surfaces and extend the applications of the spline filter in areal filtration. (technical note)

Construction of local integro quintic splines

Directory of Open Access Journals (Sweden)

T. Zhanlav

2016-06-01

Full Text Available In this paper, we show that the integro quintic splines can locally be constructed without solving any systems of equations. The new construction does not require any additional end conditions. By virtue of these advantages the proposed algorithm is easy to implement and effective. At the same time, the local integro quintic splines possess as good approximation properties as the integro quintic splines. In this paper, we have proved that our local integro quintic spline has superconvergence properties at the knots for the first and third derivatives. The orders of convergence at the knots are six (not five for the first derivative and four (not three for the third derivative.

Nonlinear bias compensation of ZiYuan-3 satellite imagery with cubic splines

Science.gov (United States)

Cao, Jinshan; Fu, Jianhong; Yuan, Xiuxiao; Gong, Jianya

2017-11-01

Like many high-resolution satellites such as the ALOS, MOMS-2P, QuickBird, and ZiYuan1-02C satellites, the ZiYuan-3 satellite suffers from different levels of attitude oscillations. As a result of such oscillations, the rational polynomial coefficients (RPCs) obtained using a terrain-independent scenario often have nonlinear biases. In the sensor orientation of ZiYuan-3 imagery based on a rational function model (RFM), these nonlinear biases cannot be effectively compensated by an affine transformation. The sensor orientation accuracy is thereby worse than expected. In order to eliminate the influence of attitude oscillations on the RFM-based sensor orientation, a feasible nonlinear bias compensation approach for ZiYuan-3 imagery with cubic splines is proposed. In this approach, no actual ground control points (GCPs) are required to determine the cubic splines. First, the RPCs are calculated using a three-dimensional virtual control grid generated based on a physical sensor model. Second, one cubic spline is used to model the residual errors of the virtual control points in the row direction and another cubic spline is used to model the residual errors in the column direction. Then, the estimated cubic splines are used to compensate the nonlinear biases in the RPCs. Finally, the affine transformation parameters are used to compensate the residual biases in the RPCs. Three ZiYuan-3 images were tested. The experimental results showed that before the nonlinear bias compensation, the residual errors of the independent check points were nonlinearly biased. Even if the number of GCPs used to determine the affine transformation parameters was increased from 4 to 16, these nonlinear biases could not be effectively compensated. After the nonlinear bias compensation with the estimated cubic splines, the influence of the attitude oscillations could be eliminated. The RFM-based sensor orientation accuracies of the three ZiYuan-3 images reached 0.981 pixels, 0.890 pixels, and 1

Multivariate Epi-splines and Evolving Function Identification Problems

Science.gov (United States)

2015-04-15

such extrinsic information as well as observed function and subgradient values often evolve in applications, we establish conditions under which the...previous study [30] dealt with compact intervals of IR. Splines are intimately tied to optimization problems through their variational theory pioneered...approxima- tion. Motivated by applications in curve fitting, regression, probability density estimation, variogram computation, financial curve construction

Polarization Smoothing Generalized MUSIC Algorithm with Polarization Sensitive Array for Low Angle Estimation.

Science.gov (United States)

Tan, Jun; Nie, Zaiping

2018-05-12

Direction of Arrival (DOA) estimation of low-altitude targets is difficult due to the multipath coherent interference from the ground reflection image of the targets, especially for very high frequency (VHF) radars, which have antennae that are severely restricted in terms of aperture and height. The polarization smoothing generalized multiple signal classification (MUSIC) algorithm, which combines polarization smoothing and generalized MUSIC algorithm for polarization sensitive arrays (PSAs), was proposed to solve this problem in this paper. Firstly, the polarization smoothing pre-processing was exploited to eliminate the coherence between the direct and the specular signals. Secondly, we constructed the generalized MUSIC algorithm for low angle estimation. Finally, based on the geometry information of the symmetry multipath model, the proposed algorithm was introduced to convert the two-dimensional searching into one-dimensional searching, thus reducing the computational burden. Numerical results were provided to verify the effectiveness of the proposed method, showing that the proposed algorithm has significantly improved angle estimation performance in the low-angle area compared with the available methods, especially when the grazing angle is near zero.

Multidimensional splines for modeling FET nonlinearities

Energy Technology Data Exchange (ETDEWEB)

Barby, J A

1986-01-01

Circuit simulators like SPICE and timing simulators like MOTIS are used extensively for critical path verification of integrated circuits. MOSFET model evaluation dominates the run time of these simulators. Changes in technology results in costly updates, since modifications require reprogramming of the functions and their derivatives. The computational cost of MOSFET models can be reduced by using multidimensional polynomial splines. Since simulators based on the Newton Raphson algorithm require the function and first derivative, quadratic splines are sufficient for this purpose. The cost of updating the MOSFET model due to technology changes is greatly reduced since splines are derived from a set of points. Crucial for convergence speed of simulators is the fact that MOSFET characteristic equations are monotonic. This must be maintained by any simulation model. The splines the author designed do maintain monotonicity.

Compare diagnostic tests using transformation-invariant smoothed ROC curves⋆

Science.gov (United States)

Tang, Liansheng; Du, Pang; Wu, Chengqing

2012-01-01

Receiver operating characteristic (ROC) curve, plotting true positive rates against false positive rates as threshold varies, is an important tool for evaluating biomarkers in diagnostic medicine studies. By definition, ROC curve is monotone increasing from 0 to 1 and is invariant to any monotone transformation of test results. And it is often a curve with certain level of smoothness when test results from the diseased and non-diseased subjects follow continuous distributions. Most existing ROC curve estimation methods do not guarantee all of these properties. One of the exceptions is Du and Tang (2009) which applies certain monotone spline regression procedure to empirical ROC estimates. However, their method does not consider the inherent correlations between empirical ROC estimates. This makes the derivation of the asymptotic properties very difficult. In this paper we propose a penalized weighted least square estimation method, which incorporates the covariance between empirical ROC estimates as a weight matrix. The resulting estimator satisfies all the aforementioned properties, and we show that it is also consistent. Then a resampling approach is used to extend our method for comparisons of two or more diagnostic tests. Our simulations show a significantly improved performance over the existing method, especially for steep ROC curves. We then apply the proposed method to a cancer diagnostic study that compares several newly developed diagnostic biomarkers to a traditional one. PMID:22639484

Pseudo-cubic thin-plate type Spline method for analyzing experimental data

Energy Technology Data Exchange (ETDEWEB)

Crecy, F de

1994-12-31

A mathematical tool, using pseudo-cubic thin-plate type Spline, has been developed for analysis of experimental data points. The main purpose is to obtain, without any a priori given model, a mathematical predictor with related uncertainties, usable at any point in the multidimensional parameter space. The smoothing parameter is determined by a generalized cross validation method. The residual standard deviation obtained is significantly smaller than that of a least square regression. An example of use is given with critical heat flux data, showing a significant decrease of the conception criterion (minimum allowable value of the DNB ratio). (author) 4 figs., 1 tab., 7 refs.

Pseudo-cubic thin-plate type Spline method for analyzing experimental data

International Nuclear Information System (INIS)

Crecy, F. de.

1993-01-01

A mathematical tool, using pseudo-cubic thin-plate type Spline, has been developed for analysis of experimental data points. The main purpose is to obtain, without any a priori given model, a mathematical predictor with related uncertainties, usable at any point in the multidimensional parameter space. The smoothing parameter is determined by a generalized cross validation method. The residual standard deviation obtained is significantly smaller than that of a least square regression. An example of use is given with critical heat flux data, showing a significant decrease of the conception criterion (minimum allowable value of the DNB ratio). (author) 4 figs., 1 tab., 7 refs

Marginal longitudinal semiparametric regression via penalized splines

KAUST Repository

Al Kadiri, M.

2010-08-01

We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

Marginal longitudinal semiparametric regression via penalized splines

KAUST Repository

Al Kadiri, M.; Carroll, R.J.; Wand, M.P.

2010-01-01

We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

Automatic lung lobe segmentation using particles, thin plate splines, and maximum a posteriori estimation.

Science.gov (United States)

Ross, James C; San José Estépar, Rail; Kindlmann, Gordon; Díaz, Alejandro; Westin, Carl-Fredrik; Silverman, Edwin K; Washko, George R

2010-01-01

We present a fully automatic lung lobe segmentation algorithm that is effective in high resolution computed tomography (CT) datasets in the presence of confounding factors such as incomplete fissures (anatomical structures indicating lobe boundaries), advanced disease states, high body mass index (BMI), and low-dose scanning protocols. In contrast to other algorithms that leverage segmentations of auxiliary structures (esp. vessels and airways), we rely only upon image features indicating fissure locations. We employ a particle system that samples the image domain and provides a set of candidate fissure locations. We follow this stage with maximum a posteriori (MAP) estimation to eliminate poor candidates and then perform a post-processing operation to remove remaining noise particles. We then fit a thin plate spline (TPS) interpolating surface to the fissure particles to form the final lung lobe segmentation. Results indicate that our algorithm performs comparably to pulmonologist-generated lung lobe segmentations on a set of challenging cases.

Using Spline Regression in Semi-Parametric Stochastic Frontier Analysis: An Application to Polish Dairy Farms

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

of specifying an unsuitable functional form and thus, model misspecification and biased parameter estimates. Given these problems of the DEA and the SFA, Fan, Li and Weersink (1996) proposed a semi-parametric stochastic frontier model that estimates the production function (frontier) by non......), Kumbhakar et al. (2007), and Henningsen and Kumbhakar (2009). The aim of this paper and its main contribution to the existing literature is the estimation semi-parametric stochastic frontier models using a different non-parametric estimation technique: spline regression (Ma et al. 2011). We apply...... efficiency of Polish dairy farms contributes to the insight into this dynamic process. Furthermore, we compare and evaluate the results of this spline-based semi-parametric stochastic frontier model with results of other semi-parametric stochastic frontier models and of traditional parametric stochastic...

Evaluating the impact of spatio-temporal smoothness constraints on the BOLD hemodynamic response function estimation: an analysis based on Tikhonov regularization

International Nuclear Information System (INIS)

Casanova, R; Yang, L; Hairston, W D; Laurienti, P J; Maldjian, J A

2009-01-01

Recently we have proposed the use of Tikhonov regularization with temporal smoothness constraints to estimate the BOLD fMRI hemodynamic response function (HRF). The temporal smoothness constraint was imposed on the estimates by using second derivative information while the regularization parameter was selected based on the generalized cross-validation function (GCV). Using one-dimensional simulations, we previously found this method to produce reliable estimates of the HRF time course, especially its time to peak (TTP), being at the same time fast and robust to over-sampling in the HRF estimation. Here, we extend the method to include simultaneous temporal and spatial smoothness constraints. This method does not need Gaussian smoothing as a pre-processing step as usually done in fMRI data analysis. We carried out two-dimensional simulations to compare the two methods: Tikhonov regularization with temporal (Tik-GCV-T) and spatio-temporal (Tik-GCV-ST) smoothness constraints on the estimated HRF. We focus our attention on quantifying the influence of the Gaussian data smoothing and the presence of edges on the performance of these techniques. Our results suggest that the spatial smoothing introduced by regularization is less severe than that produced by Gaussian smoothing. This allows more accurate estimates of the response amplitudes while producing similar estimates of the TTP. We illustrate these ideas using real data. (note)

Signal-to-noise ratio enhancement on SEM images using a cubic spline interpolation with Savitzky-Golay filters and weighted least squares error.

Science.gov (United States)

Kiani, M A; Sim, K S; Nia, M E; Tso, C P

2015-05-01

A new technique based on cubic spline interpolation with Savitzky-Golay smoothing using weighted least squares error filter is enhanced for scanning electron microscope (SEM) images. A diversity of sample images is captured and the performance is found to be better when compared with the moving average and the standard median filters, with respect to eliminating noise. This technique can be implemented efficiently on real-time SEM images, with all mandatory data for processing obtained from a single image. Noise in images, and particularly in SEM images, are undesirable. A new noise reduction technique, based on cubic spline interpolation with Savitzky-Golay and weighted least squares error method, is developed. We apply the combined technique to single image signal-to-noise ratio estimation and noise reduction for SEM imaging system. This autocorrelation-based technique requires image details to be correlated over a few pixels, whereas the noise is assumed to be uncorrelated from pixel to pixel. The noise component is derived from the difference between the image autocorrelation at zero offset, and the estimation of the corresponding original autocorrelation. In the few test cases involving different images, the efficiency of the developed noise reduction filter is proved to be significantly better than those obtained from the other methods. Noise can be reduced efficiently with appropriate choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

IRT Item Parameter Recovery with Marginal Maximum Likelihood Estimation Using Loglinear Smoothing Models

Science.gov (United States)

Casabianca, Jodi M.; Lewis, Charles

2015-01-01

Loglinear smoothing (LLS) estimates the latent trait distribution while making fewer assumptions about its form and maintaining parsimony, thus leading to more precise item response theory (IRT) item parameter estimates than standard marginal maximum likelihood (MML). This article provides the expectation-maximization algorithm for MML estimation…

Optimization of straight-sided spline design

DEFF Research Database (Denmark)

Pedersen, Niels Leergaard

2011-01-01

and the subject of improving the design. The present paper concentrates on the optimization of splines and the predictions of stress concentrations, which are determined by finite element analysis (FEA). Using different design modifications, that do not change the spline load carrying capacity, it is shown...

Spline models of contemporary, 2030, 2060, and 2090 climates for Mexico and their use in understanding climate-change impacts on the vegetation

Science.gov (United States)

Cuauhtemoc Saenz-Romero; Gerald E. Rehfeldt; Nicholas L. Crookston; Pierre Duval; Remi St-Amant; Jean Beaulieu; Bryce A. Richardson

2010-01-01

Spatial climate models were developed for Mexico and its periphery (southern USA, Cuba, Belize and Guatemala) for monthly normals (1961-1990) of average, maximum and minimum temperature and precipitation using thin plate smoothing splines of ANUSPLIN software on ca. 3,800 observations. The fit of the model was generally good: the signal was considerably less than one-...

Nonrigid registration of dynamic medical imaging data using nD + t B-splines and a groupwise optimization approach.

Science.gov (United States)

Metz, C T; Klein, S; Schaap, M; van Walsum, T; Niessen, W J

2011-04-01

A registration method for motion estimation in dynamic medical imaging data is proposed. Registration is performed directly on the dynamic image, thus avoiding a bias towards a specifically chosen reference time point. Both spatial and temporal smoothness of the transformations are taken into account. Optionally, cyclic motion can be imposed, which can be useful for visualization (viewing the segmentation sequentially) or model building purposes. The method is based on a 3D (2D+time) or 4D (3D+time) free-form B-spline deformation model, a similarity metric that minimizes the intensity variances over time and constrained optimization using a stochastic gradient descent method with adaptive step size estimation. The method was quantitatively compared with existing registration techniques on synthetic data and 3D+t computed tomography data of the lungs. This showed subvoxel accuracy while delivering smooth transformations, and high consistency of the registration results. Furthermore, the accuracy of semi-automatic derivation of left ventricular volume curves from 3D+t computed tomography angiography data of the heart was evaluated. On average, the deviation from the curves derived from the manual annotations was approximately 3%. The potential of the method for other imaging modalities was shown on 2D+t ultrasound and 2D+t magnetic resonance images. The software is publicly available as an extension to the registration package elastix. Copyright © 2010 Elsevier B.V. All rights reserved.

Joint surface modeling with thin-plate splines.

Science.gov (United States)

Boyd, S K; Ronsky, J L; Lichti, D D; Salkauskas, K; Chapman, M A; Salkauskas, D

1999-10-01

Mathematical joint surface models based on experimentally determined data points can be used to investigate joint characteristics such as curvature, congruency, cartilage thickness, joint contact areas, as well as to provide geometric information well suited for finite element analysis. Commonly, surface modeling methods are based on B-splines, which involve tensor products. These methods have had success; however, they are limited due to the complex organizational aspect of working with surface patches, and modeling unordered, scattered experimental data points. An alternative method for mathematical joint surface modeling is presented based on the thin-plate spline (TPS). It has the advantage that it does not involve surface patches, and can model scattered data points without experimental data preparation. An analytical surface was developed and modeled with the TPS to quantify its interpolating and smoothing characteristics. Some limitations of the TPS include discontinuity of curvature at exactly the experimental surface data points, and numerical problems dealing with data sets in excess of 2000 points. However, suggestions for overcoming these limitations are presented. Testing the TPS with real experimental data, the patellofemoral joint of a cat was measured with multistation digital photogrammetry and modeled using the TPS to determine cartilage thicknesses and surface curvature. The cartilage thickness distribution ranged between 100 to 550 microns on the patella, and 100 to 300 microns on the femur. It was found that the TPS was an effective tool for modeling joint surfaces because no preparation of the experimental data points was necessary, and the resulting unique function representing the entire surface does not involve surface patches. A detailed algorithm is presented for implementation of the TPS.

Smooth semi-nonparametric (SNP) estimation of the cumulative incidence function.

Science.gov (United States)

Duc, Anh Nguyen; Wolbers, Marcel

2017-08-15

This paper presents a novel approach to estimation of the cumulative incidence function in the presence of competing risks. The underlying statistical model is specified via a mixture factorization of the joint distribution of the event type and the time to the event. The time to event distributions conditional on the event type are modeled using smooth semi-nonparametric densities. One strength of this approach is that it can handle arbitrary censoring and truncation while relying on mild parametric assumptions. A stepwise forward algorithm for model estimation and adaptive selection of smooth semi-nonparametric polynomial degrees is presented, implemented in the statistical software R, evaluated in a sequence of simulation studies, and applied to data from a clinical trial in cryptococcal meningitis. The simulations demonstrate that the proposed method frequently outperforms both parametric and nonparametric alternatives. They also support the use of 'ad hoc' asymptotic inference to derive confidence intervals. An extension to regression modeling is also presented, and its potential and challenges are discussed. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

A 156 kyr smoothed history of the atmospheric greenhouse gases CO2, CH4, and N2O and their radiative forcing

Science.gov (United States)

Köhler, Peter; Nehrbass-Ahles, Christoph; Schmitt, Jochen; Stocker, Thomas F.; Fischer, Hubertus

2017-06-01

Continuous records of the atmospheric greenhouse gases (GHGs) CO2, CH4, and N2O are necessary input data for transient climate simulations, and their associated radiative forcing represents important components in analyses of climate sensitivity and feedbacks. Since the available data from ice cores are discontinuous and partly ambiguous, a well-documented decision process during data compilation followed by some interpolating post-processing is necessary to obtain those desired time series. Here, we document our best possible data compilation of published ice core records and recent measurements on firn air and atmospheric samples spanning the interval from the penultimate glacial maximum ( ˜ 156 kyr BP) to the beginning of the year 2016 CE. We use the most recent age scales for the ice core data and apply a smoothing spline method to translate the discrete and irregularly spaced data points into continuous time series. These splines are then used to compute the radiative forcing for each GHG using well-established, simple formulations. We compile only a Southern Hemisphere record of CH4 and discuss how much larger a Northern Hemisphere or global CH4 record might have been due to its interpolar difference. The uncertainties of the individual data points are considered in the spline procedure. Based on the given data resolution, time-dependent cutoff periods of the spline, defining the degree of smoothing, are prescribed, ranging from 5000 years for the less resolved older parts of the records to 4 years for the densely sampled recent years. The computed splines seamlessly describe the GHG evolution on orbital and millennial timescales for glacial and glacial-interglacial variations and on centennial and decadal timescales for anthropogenic times. Data connected with this paper, including raw data and final splines, are available at PANGAEA.871273" target="_blank">doi:10.1594/PANGAEA.871273.

Limit Stress Spline Models for GRP Composites | Ihueze | Nigerian ...

African Journals Online (AJOL)

Spline functions were established on the assumption of three intervals and fitting of quadratic and cubic splines to critical stress-strain responses data. Quadratic ... of data points. Spline model is therefore recommended as it evaluates the function at subintervals, eliminating the error associated with wide range interpolation.

Data assimilation using Bayesian filters and B-spline geological models

KAUST Repository

Duan, Lian

2011-04-01

This paper proposes a new approach to problems of data assimilation, also known as history matching, of oilfield production data by adjustment of the location and sharpness of patterns of geological facies. Traditionally, this problem has been addressed using gradient based approaches with a level set parameterization of the geology. Gradient-based methods are robust, but computationally demanding with real-world reservoir problems and insufficient for reservoir management uncertainty assessment. Recently, the ensemble filter approach has been used to tackle this problem because of its high efficiency from the standpoint of implementation, computational cost, and performance. Incorporation of level set parameterization in this approach could further deal with the lack of differentiability with respect to facies type, but its practical implementation is based on some assumptions that are not easily satisfied in real problems. In this work, we propose to describe the geometry of the permeability field using B-spline curves. This transforms history matching of the discrete facies type to the estimation of continuous B-spline control points. As filtering scheme, we use the ensemble square-root filter (EnSRF). The efficacy of the EnSRF with the B-spline parameterization is investigated through three numerical experiments, in which the reservoir contains a curved channel, a disconnected channel or a 2-dimensional closed feature. It is found that the application of the proposed method to the problem of adjusting facies edges to match production data is relatively straightforward and provides statistical estimates of the distribution of geological facies and of the state of the reservoir.

Data assimilation using Bayesian filters and B-spline geological models

International Nuclear Information System (INIS)

Duan Lian; Farmer, Chris; Hoteit, Ibrahim; Luo Xiaodong; Moroz, Irene

2011-01-01

This paper proposes a new approach to problems of data assimilation, also known as history matching, of oilfield production data by adjustment of the location and sharpness of patterns of geological facies. Traditionally, this problem has been addressed using gradient based approaches with a level set parameterization of the geology. Gradient-based methods are robust, but computationally demanding with real-world reservoir problems and insufficient for reservoir management uncertainty assessment. Recently, the ensemble filter approach has been used to tackle this problem because of its high efficiency from the standpoint of implementation, computational cost, and performance. Incorporation of level set parameterization in this approach could further deal with the lack of differentiability with respect to facies type, but its practical implementation is based on some assumptions that are not easily satisfied in real problems. In this work, we propose to describe the geometry of the permeability field using B-spline curves. This transforms history matching of the discrete facies type to the estimation of continuous B-spline control points. As filtering scheme, we use the ensemble square-root filter (EnSRF). The efficacy of the EnSRF with the B-spline parameterization is investigated through three numerical experiments, in which the reservoir contains a curved channel, a disconnected channel or a 2-dimensional closed feature. It is found that the application of the proposed method to the problem of adjusting facies edges to match production data is relatively straightforward and provides statistical estimates of the distribution of geological facies and of the state of the reservoir.

A 156 kyr smoothed history of the atmospheric greenhouse gases CO2, CH4, and N2O and their radiative forcing

Directory of Open Access Journals (Sweden)

P. Köhler

2017-06-01

Full Text Available Continuous records of the atmospheric greenhouse gases (GHGs CO2, CH4, and N2O are necessary input data for transient climate simulations, and their associated radiative forcing represents important components in analyses of climate sensitivity and feedbacks. Since the available data from ice cores are discontinuous and partly ambiguous, a well-documented decision process during data compilation followed by some interpolating post-processing is necessary to obtain those desired time series. Here, we document our best possible data compilation of published ice core records and recent measurements on firn air and atmospheric samples spanning the interval from the penultimate glacial maximum ( ∼  156 kyr BP to the beginning of the year 2016 CE. We use the most recent age scales for the ice core data and apply a smoothing spline method to translate the discrete and irregularly spaced data points into continuous time series. These splines are then used to compute the radiative forcing for each GHG using well-established, simple formulations. We compile only a Southern Hemisphere record of CH4 and discuss how much larger a Northern Hemisphere or global CH4 record might have been due to its interpolar difference. The uncertainties of the individual data points are considered in the spline procedure. Based on the given data resolution, time-dependent cutoff periods of the spline, defining the degree of smoothing, are prescribed, ranging from 5000 years for the less resolved older parts of the records to 4 years for the densely sampled recent years. The computed splines seamlessly describe the GHG evolution on orbital and millennial timescales for glacial and glacial–interglacial variations and on centennial and decadal timescales for anthropogenic times. Data connected with this paper, including raw data and final splines, are available at doi:10.1594/PANGAEA.871273.

A scalable block-preconditioning strategy for divergence-conforming B-spline discretizations of the Stokes problem

KAUST Repository

Cortes, Adriano Mauricio

2016-10-01

The recently introduced divergence-conforming B-spline discretizations allow the construction of smooth discrete velocity-pressure pairs for viscous incompressible flows that are at the same time inf−supinf−sup stable and pointwise divergence-free. When applied to the discretized Stokes problem, these spaces generate a symmetric and indefinite saddle-point linear system. The iterative method of choice to solve such system is the Generalized Minimum Residual Method. This method lacks robustness, and one remedy is to use preconditioners. For linear systems of saddle-point type, a large family of preconditioners can be obtained by using a block factorization of the system. In this paper, we show how the nesting of “black-box” solvers and preconditioners can be put together in a block triangular strategy to build a scalable block preconditioner for the Stokes system discretized by divergence-conforming B-splines. Besides the known cavity flow problem, we used for benchmark flows defined on complex geometries: an eccentric annulus and hollow torus of an eccentric annular cross-section.

Positivity Preserving Interpolation Using Rational Bicubic Spline

Directory of Open Access Journals (Sweden)

Samsul Ariffin Abdul Karim

2015-01-01

Full Text Available This paper discusses the positivity preserving interpolation for positive surfaces data by extending the C1 rational cubic spline interpolant of Karim and Kong to the bivariate cases. The partially blended rational bicubic spline has 12 parameters in the descriptions where 8 of them are free parameters. The sufficient conditions for the positivity are derived on every four boundary curves network on the rectangular patch. Numerical comparison with existing schemes also has been done in detail. Based on Root Mean Square Error (RMSE, our partially blended rational bicubic spline is on a par with the established methods.

A spline-based regression parameter set for creating customized DARTEL MRI brain templates from infancy to old age

Directory of Open Access Journals (Sweden)

Marko Wilke

2018-02-01

Full Text Available This dataset contains the regression parameters derived by analyzing segmented brain MRI images (gray matter and white matter from a large population of healthy subjects, using a multivariate adaptive regression splines approach. A total of 1919 MRI datasets ranging in age from 1–75 years from four publicly available datasets (NIH, C-MIND, fCONN, and IXI were segmented using the CAT12 segmentation framework, writing out gray matter and white matter images normalized using an affine-only spatial normalization approach. These images were then subjected to a six-step DARTEL procedure, employing an iterative non-linear registration approach and yielding increasingly crisp intermediate images. The resulting six datasets per tissue class were then analyzed using multivariate adaptive regression splines, using the CerebroMatic toolbox. This approach allows for flexibly modelling smoothly varying trajectories while taking into account demographic (age, gender as well as technical (field strength, data quality predictors. The resulting regression parameters described here can be used to generate matched DARTEL or SHOOT templates for a given population under study, from infancy to old age. The dataset and the algorithm used to generate it are publicly available at https://irc.cchmc.org/software/cerebromatic.php. Keywords: MRI template creation, Multivariate adaptive regression splines, DARTEL, Structural MRI

Near real-time estimation of ionosphere vertical total electron content from GNSS satellites using B-splines in a Kalman filter

Science.gov (United States)

Erdogan, Eren; Schmidt, Michael; Seitz, Florian; Durmaz, Murat

2017-02-01

Although the number of terrestrial global navigation satellite system (GNSS) receivers supported by the International GNSS Service (IGS) is rapidly growing, the worldwide rather inhomogeneously distributed observation sites do not allow the generation of high-resolution global ionosphere products. Conversely, with the regionally enormous increase in highly precise GNSS data, the demands on (near) real-time ionosphere products, necessary in many applications such as navigation, are growing very fast. Consequently, many analysis centers accepted the responsibility of generating such products. In this regard, the primary objective of our work is to develop a near real-time processing framework for the estimation of the vertical total electron content (VTEC) of the ionosphere using proper models that are capable of a global representation adapted to the real data distribution. The global VTEC representation developed in this work is based on a series expansion in terms of compactly supported B-spline functions, which allow for an appropriate handling of the heterogeneous data distribution, including data gaps. The corresponding series coefficients and additional parameters such as differential code biases of the GNSS satellites and receivers constitute the set of unknown parameters. The Kalman filter (KF), as a popular recursive estimator, allows processing of the data immediately after acquisition and paves the way of sequential (near) real-time estimation of the unknown parameters. To exploit the advantages of the chosen data representation and the estimation procedure, the B-spline model is incorporated into the KF under the consideration of necessary constraints. Based on a preprocessing strategy, the developed approach utilizes hourly batches of GPS and GLONASS observations provided by the IGS data centers with a latency of 1 h in its current realization. Two methods for validation of the results are performed, namely the self consistency analysis and a comparison

Ensuring dynamic load smoothness in problem of controlling Atomic Electric Power Stations exclusive mechanisms

International Nuclear Information System (INIS)

Shumilov, V.F.

2003-01-01

New methods for the investigation of automatic systems based on the inverse tasks of dynamics with the use of rational, trigonometric and polynomial spline functions are discussed. By means of SH function the technological regimes: start-up, steadiness, racing, braking, reverse, stop were determined. Procedure for the provision of dynamic load smoothness is suggested, and example of control over the transport systems for fuel load is considered [ru

Higher order multipoles and splines in plasma simulations

International Nuclear Information System (INIS)

Okuda, H.; Cheng, C.Z.

1978-01-01

The reduction of spatial grid effects in plasma simulations has been studied numerically using higher order multipole expansions and the spline method in one dimension. It is found that, while keeping the higher order moments such as quadrupole and octopole moments substantially reduces the grid effects, quadratic and cubic splines in general have better stability properties for numerical plasma simulations when the Debye length is much smaller than the grid size. In particular the spline method may be useful in three-dimensional simulations for plasma confinement where the grid size in the axial direction is much greater than the Debye length. (Auth.)

Higher-order multipoles and splines in plasma simulations

International Nuclear Information System (INIS)

Okuda, H.; Cheng, C.Z.

1977-12-01

Reduction of spatial grid effects in plasma simulations has been studied numerically using higher order multipole expansions and spline method in one dimension. It is found that, while keeping the higher order moments such as quadrupole and octopole moments substantially reduces the grid effects, quadratic and cubic splines in general have better stability properties for numerical plasma simulations when the Debye length is much smaller than the grid size. In particular, spline method may be useful in three dimensional simulations for plasma confinement where the grid size in the axial direction is much greater than the Debye length

Automatic Shape Control of Triangular B-Splines of Arbitrary Topology

Institute of Scientific and Technical Information of China (English)

Ying He; Xian-Feng Gu; Hong Qin

2006-01-01

Triangular B-splines are powerful and flexible in modeling a broader class of geometric objects defined over arbitrary, non-rectangular domains. Despite their great potential and advantages in theory, practical techniques and computational tools with triangular B-splines are less-developed. This is mainly because users have to handle a large number of irregularly distributed control points over arbitrary triangulation. In this paper, an automatic and efficient method is proposed to generate visually pleasing, high-quality triangular B-splines of arbitrary topology. The experimental results on several real datasets show that triangular B-splines are powerful and effective in both theory and practice.

USING SPLINE FUNCTIONS FOR THE SUBSTANTIATION OF TAX POLICIES BY LOCAL AUTHORITIES

Directory of Open Access Journals (Sweden)

Otgon Cristian

2011-07-01

Full Text Available The paper aims to approach innovative financial instruments for the management of public resources. In the category of these innovative tools have been included polynomial spline functions used for budgetary sizing in the substantiating of fiscal and budgetary policies. In order to use polynomial spline functions there have been made a number of steps consisted in the establishment of nodes, the calculation of specific coefficients corresponding to the spline functions, development and determination of errors of approximation. Also in this paper was done extrapolation of series of property tax data using polynomial spline functions of order I. For spline impelementation were taken two series of data, one reffering to property tax as a resultative variable and the second one reffering to building tax, resulting a correlation indicator R=0,95. Moreover the calculation of spline functions are easy to solve and due to small errors of approximation have a great power of predictibility, much better than using ordinary least squares method. In order to realise the research there have been used as methods of research several steps, namely observation, series of data construction and processing the data with spline functions. The data construction is a daily series gathered from the budget account, reffering to building tax and property tax. The added value of this paper is given by the possibility of avoiding deficits by using spline functions as innovative instruments in the publlic finance, the original contribution is made by the average of splines resulted from the series of data. The research results lead to conclusion that the polynomial spline functions are recommended to form the elaboration of fiscal and budgetary policies, due to relatively small errors obtained in the extrapolation of economic processes and phenomena. Future research directions are taking in consideration to study the polynomial spline functions of second-order, third

Thin-plate spline quadrature of geodetic integrals

Science.gov (United States)

Vangysen, Herman

1989-01-01

Thin-plate spline functions (known for their flexibility and fidelity in representing experimental data) are especially well-suited for the numerical integration of geodetic integrals in the area where the integration is most sensitive to the data, i.e., in the immediate vicinity of the evaluation point. Spline quadrature rules are derived for the contribution of a circular innermost zone to Stoke's formula, to the formulae of Vening Meinesz, and to the recursively evaluated operator L(n) in the analytical continuation solution of Molodensky's problem. These rules are exact for interpolating thin-plate splines. In cases where the integration data are distributed irregularly, a system of linear equations needs to be solved for the quadrature coefficients. Formulae are given for the terms appearing in these equations. In case the data are regularly distributed, the coefficients may be determined once-and-for-all. Examples are given of some fixed-point rules. With such rules successive evaluation, within a circular disk, of the terms in Molodensky's series becomes relatively easy. The spline quadrature technique presented complements other techniques such as ring integration for intermediate integration zones.

Quasi interpolation with Voronoi splines.

Science.gov (United States)

Mirzargar, Mahsa; Entezari, Alireza

2011-12-01

We present a quasi interpolation framework that attains the optimal approximation-order of Voronoi splines for reconstruction of volumetric data sampled on general lattices. The quasi interpolation framework of Voronoi splines provides an unbiased reconstruction method across various lattices. Therefore this framework allows us to analyze and contrast the sampling-theoretic performance of general lattices, using signal reconstruction, in an unbiased manner. Our quasi interpolation methodology is implemented as an efficient FIR filter that can be applied online or as a preprocessing step. We present visual and numerical experiments that demonstrate the improved accuracy of reconstruction across lattices, using the quasi interpolation framework. © 2011 IEEE

PEMODELAN REGRESI SPLINE (Studi Kasus: Herpindo Jaya Cabang Ngaliyan

Directory of Open Access Journals (Sweden)

I MADE BUDIANTARA PUTRA

2015-06-01

Full Text Available Regression analysis is a method of data analysis to describe the relationship between response variables and predictor variables. There are two approaches to estimating the regression function. They are parametric and nonparametric approaches. The parametric approach is used when the relationship between the predictor variables and the response variables are known or the shape of the regression curve is known. Meanwhile, the nonparametric approach is used when the form of the relationship between the response and predictor variables is unknown or no information about the form of the regression function. The aim of this study are to determine the best spline nonparametric regression model on data of quality of the product, price, and advertising on purchasing decisions of Yamaha motorcycle with optimal knots point and to compare it with the multiple regression linear based on the coefficient of determination (R2 and mean square error (MSE. Optimal knot points are defined by two point knots. The result of this analysis is that for this data multiple regression linear is better than the spline regression one.

An adaptive spatio-temporal smoothing model for estimating trends and step changes in disease risk

OpenAIRE

Rushworth, Alastair; Lee, Duncan; Sarran, Christophe

2014-01-01

Statistical models used to estimate the spatio-temporal pattern in disease\\ud risk from areal unit data represent the risk surface for each time period with known\\ud covariates and a set of spatially smooth random effects. The latter act as a proxy\\ud for unmeasured spatial confounding, whose spatial structure is often characterised by\\ud a spatially smooth evolution between some pairs of adjacent areal units while other\\ud pairs exhibit large step changes. This spatial heterogeneity is not c...

Detrending of non-stationary noise data by spline techniques

International Nuclear Information System (INIS)

Behringer, K.

1989-11-01

An off-line method for detrending non-stationary noise data has been investigated. It uses a least squares spline approximation of the noise data with equally spaced breakpoints. Subtraction of the spline approximation from the noise signal at each data point gives a residual noise signal. The method acts as a high-pass filter with very sharp frequency cutoff. The cutoff frequency is determined by the breakpoint distance. The steepness of the cutoff is controlled by the spline order. (author) 12 figs., 1 tab., 5 refs

The modeling of quadratic B-splines surfaces for the tomographic reconstruction in the FCC- type-riser

International Nuclear Information System (INIS)

Vasconcelos, Geovane Vitor; Dantas, Carlos Costa; Melo, Silvio de Barros; Pires, Renan Ferraz

2009-01-01

The 3D tomography reconstruction has been a profitable alternative in the analysis of the FCC-type- riser (Fluid Catalytic Cracking), for appropriately keeping track of the sectional catalyst concentration distribution in the process of oil refining. The method of tomography reconstruction proposed by M. Azzi and colleagues (1991) uses a relatively small amount of trajectories (from 3 to 5) and projections (from 5 to 7) of gamma rays, a desirable feature in the industrial process tomography. Compared to more popular methods, such as the FBP (Filtered Back Projection), which demands a much higher amount of gamma rays projections, the method by Azzi et al. is more appropriate for the industrial process, where the physical limitations and the cost of the process require more economical arrangements. The use of few projections and trajectories facilitates the diagnosis in the flow dynamical process. This article proposes an improvement in the basis functions introduced by Azzi et al., through the use of quadratic B-splines functions. The use of B-splines functions makes possible a smoother surface reconstruction of the density distribution, since the functions are continuous and smooth. This work describes how the modeling can be done. (author)

About some properties of bivariate splines with shape parameters

Science.gov (United States)

Caliò, F.; Marchetti, E.

2017-07-01

The paper presents and proves geometrical properties of a particular bivariate function spline, built and algorithmically implemented in previous papers. The properties typical of this family of splines impact the field of computer graphics in particular that of the reverse engineering.

Meshing Force of Misaligned Spline Coupling and the Influence on Rotor System

Directory of Open Access Journals (Sweden)

Guang Zhao

2008-01-01

Full Text Available Meshing force of misaligned spline coupling is derived, dynamic equation of rotor-spline coupling system is established based on finite element analysis, the influence of meshing force on rotor-spline coupling system is simulated by numerical integral method. According to the theoretical analysis, meshing force of spline coupling is related to coupling parameters, misalignment, transmitting torque, static misalignment, dynamic vibration displacement, and so on. The meshing force increases nonlinearly with increasing the spline thickness and static misalignment or decreasing alignment meshing distance (AMD. Stiffness of coupling relates to dynamic vibration displacement, and static misalignment is not a constant. Dynamic behaviors of rotor-spline coupling system reveal the following: 1X-rotating speed is the main response frequency of system when there is no misalignment; while 2X-rotating speed appears when misalignment is present. Moreover, when misalignment increases, vibration of the system gets intricate; shaft orbit departs from origin, and magnitudes of all frequencies increase. Research results can provide important criterions on both optimization design of spline coupling and trouble shooting of rotor systems.

Point Set Denoising Using Bootstrap-Based Radial Basis Function.

Science.gov (United States)

Liew, Khang Jie; Ramli, Ahmad; Abd Majid, Ahmad

2016-01-01

This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.

Efficient GPU-based texture interpolation using uniform B-splines

NARCIS (Netherlands)

Ruijters, D.; Haar Romenij, ter B.M.; Suetens, P.

2008-01-01

This article presents uniform B-spline interpolation, completely contained on the graphics processing unit (GPU). This implies that the CPU does not need to compute any lookup tables or B-spline basis functions. The cubic interpolation can be decomposed into several linear interpolations [Sigg and

Causal Mediation Analysis for the Cox Proportional Hazards Model with a Smooth Baseline Hazard Estimator.

Science.gov (United States)

Wang, Wei; Albert, Jeffrey M

2017-08-01

An important problem within the social, behavioral, and health sciences is how to partition an exposure effect (e.g. treatment or risk factor) among specific pathway effects and to quantify the importance of each pathway. Mediation analysis based on the potential outcomes framework is an important tool to address this problem and we consider the estimation of mediation effects for the proportional hazards model in this paper. We give precise definitions of the total effect, natural indirect effect, and natural direct effect in terms of the survival probability, hazard function, and restricted mean survival time within the standard two-stage mediation framework. To estimate the mediation effects on different scales, we propose a mediation formula approach in which simple parametric models (fractional polynomials or restricted cubic splines) are utilized to approximate the baseline log cumulative hazard function. Simulation study results demonstrate low bias of the mediation effect estimators and close-to-nominal coverage probability of the confidence intervals for a wide range of complex hazard shapes. We apply this method to the Jackson Heart Study data and conduct sensitivity analysis to assess the impact on the mediation effects inference when the no unmeasured mediator-outcome confounding assumption is violated.

DOĞRUSAL KARMA ETKİLİ MODELLERDE TAHMİN VE ÇIKARSAMALAR: BİR KARŞILAŞTIRMALI ÇALIŞMA

Directory of Open Access Journals (Sweden)

Özlem AKSOY

2015-05-01

Full Text Available Smoothing methods that use basis functions with penalization can be formulated as fits in formlinear mixed effects models. This allows s uch models to be fitted using sta ndard mixed models structures. In this paper we provide an estimation and inference for linear mixed models using restrict- ed maximum likelihood and penalized spline smoothing, and describe the connection between the two. To this end, a real data example is considered and model is fitted in R using diff erent package. We see that penalized spline smoothing expressed in form of linear mixed model gives the better results than standard mixed effects model.

Non-stationary hydrologic frequency analysis using B-spline quantile regression

Science.gov (United States)

Nasri, B.; Bouezmarni, T.; St-Hilaire, A.; Ouarda, T. B. M. J.

2017-11-01

Hydrologic frequency analysis is commonly used by engineers and hydrologists to provide the basic information on planning, design and management of hydraulic and water resources systems under the assumption of stationarity. However, with increasing evidence of climate change, it is possible that the assumption of stationarity, which is prerequisite for traditional frequency analysis and hence, the results of conventional analysis would become questionable. In this study, we consider a framework for frequency analysis of extremes based on B-Spline quantile regression which allows to model data in the presence of non-stationarity and/or dependence on covariates with linear and non-linear dependence. A Markov Chain Monte Carlo (MCMC) algorithm was used to estimate quantiles and their posterior distributions. A coefficient of determination and Bayesian information criterion (BIC) for quantile regression are used in order to select the best model, i.e. for each quantile, we choose the degree and number of knots of the adequate B-spline quantile regression model. The method is applied to annual maximum and minimum streamflow records in Ontario, Canada. Climate indices are considered to describe the non-stationarity in the variable of interest and to estimate the quantiles in this case. The results show large differences between the non-stationary quantiles and their stationary equivalents for an annual maximum and minimum discharge with high annual non-exceedance probabilities.

Exponential B-splines and the partition of unity property

DEFF Research Database (Denmark)

Christensen, Ole; Massopust, Peter

2012-01-01

We provide an explicit formula for a large class of exponential B-splines. Also, we characterize the cases where the integer-translates of an exponential B-spline form a partition of unity up to a multiplicative constant. As an application of this result we construct explicitly given pairs of dual...

Point Set Denoising Using Bootstrap-Based Radial Basis Function.

Directory of Open Access Journals (Sweden)

Khang Jie Liew

Full Text Available This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.

Comparison Between Polynomial, Euler Beta-Function and Expo-Rational B-Spline Bases

Science.gov (United States)

Kristoffersen, Arnt R.; Dechevsky, Lubomir T.; Laksa˚, Arne; Bang, Børre

2011-12-01

Euler Beta-function B-splines (BFBS) are the practically most important instance of generalized expo-rational B-splines (GERBS) which are not true expo-rational B-splines (ERBS). BFBS do not enjoy the full range of the superproperties of ERBS but, while ERBS are special functions computable by a very rapidly converging yet approximate numerical quadrature algorithms, BFBS are explicitly computable piecewise polynomial (for integer multiplicities), similar to classical Schoenberg B-splines. In the present communication we define, compute and visualize for the first time all possible BFBS of degree up to 3 which provide Hermite interpolation in three consecutive knots of multiplicity up to 3, i.e., the function is being interpolated together with its derivatives of order up to 2. We compare the BFBS obtained for different degrees and multiplicities among themselves and versus the classical Schoenberg polynomial B-splines and the true ERBS for the considered knots. The results of the graphical comparison are discussed from analytical point of view. For the numerical computation and visualization of the new B-splines we have used Maple 12.

Design Evaluation of Wind Turbine Spline Couplings Using an Analytical Model: Preprint

Energy Technology Data Exchange (ETDEWEB)

Guo, Y.; Keller, J.; Wallen, R.; Errichello, R.; Halse, C.; Lambert, S.

2015-02-01

Articulated splines are commonly used in the planetary stage of wind turbine gearboxes for transmitting the driving torque and improving load sharing. Direct measurement of spline loads and performance is extremely challenging because of limited accessibility. This paper presents an analytical model for the analysis of articulated spline coupling designs. For a given torque and shaft misalignment, this analytical model quickly yields insights into relationships between the spline design parameters and resulting loads; bending, contact, and shear stresses; and safety factors considering various heat treatment methods. Comparisons of this analytical model against previously published computational approaches are also presented.

Smooth incidence maps give valuable insight into Q fever outbreaks in The Netherlands

Directory of Open Access Journals (Sweden)

Wim van der Hoek

2012-11-01

Full Text Available From 2007 through 2009, The Netherlands faced large outbreaks of human Q fever. Control measures focused primarily on dairy goat farms because these were implicated as the main source of infection for the surrounding population. However, in other countries, outbreaks have mainly been associated with non-dairy sheep and The Netherlands has many more sheep than goats. Therefore, a public discussion arose about the possible role of non-dairy (meat sheep in the outbreaks. To inform decision makers about the relative importance of different infection sources, we developed accurate and high-resolution incidence maps for detection of Q fever hot spots. In the high incidence area in the south of the country, full postal codes of notified Q fever patients with onset of illness in 2009, were georeferenced. Q fever cases (n = 1,740 were treated as a spatial point process. A 500 x 500 m grid was imposed over the area of interest. The number of cases and the population number were counted in each cell. The number of cases was modelled as an inhomogeneous Poisson process where the underlying incidence was estimated by 2-dimensional P-spline smoothing. Modelling of numbers of Q fever cases based on residential addresses and population size produced smooth incidence maps that clearly showed Q fever hotspots around infected dairy goat farms. No such increased incidence was noted around infected meat sheep farms. We conclude that smooth incidence maps of human notifications give valuable information about the Q fever epidemic and are a promising method to provide decision support for the control of other infectious diseases with an environmental source.

A spline-based regression parameter set for creating customized DARTEL MRI brain templates from infancy to old age.

Science.gov (United States)

Wilke, Marko

2018-02-01

This dataset contains the regression parameters derived by analyzing segmented brain MRI images (gray matter and white matter) from a large population of healthy subjects, using a multivariate adaptive regression splines approach. A total of 1919 MRI datasets ranging in age from 1-75 years from four publicly available datasets (NIH, C-MIND, fCONN, and IXI) were segmented using the CAT12 segmentation framework, writing out gray matter and white matter images normalized using an affine-only spatial normalization approach. These images were then subjected to a six-step DARTEL procedure, employing an iterative non-linear registration approach and yielding increasingly crisp intermediate images. The resulting six datasets per tissue class were then analyzed using multivariate adaptive regression splines, using the CerebroMatic toolbox. This approach allows for flexibly modelling smoothly varying trajectories while taking into account demographic (age, gender) as well as technical (field strength, data quality) predictors. The resulting regression parameters described here can be used to generate matched DARTEL or SHOOT templates for a given population under study, from infancy to old age. The dataset and the algorithm used to generate it are publicly available at https://irc.cchmc.org/software/cerebromatic.php.

Preprocessor with spline interpolation for converting stereolithography into cutter location source data

Science.gov (United States)

Nagata, Fusaomi; Okada, Yudai; Sakamoto, Tatsuhiko; Kusano, Takamasa; Habib, Maki K.; Watanabe, Keigo

2017-06-01

The authors have developed earlier an industrial machining robotic system for foamed polystyrene materials. The developed robotic CAM system provided a simple and effective interface without the need to use any robot language between operators and the machining robot. In this paper, a preprocessor for generating Cutter Location Source data (CLS data) from Stereolithography (STL data) is first proposed for robotic machining. The preprocessor enables to control the machining robot directly using STL data without using any commercially provided CAM system. The STL deals with a triangular representation for a curved surface geometry. The preprocessor allows machining robots to be controlled through a zigzag or spiral path directly calculated from STL data. Then, a smart spline interpolation method is proposed and implemented for smoothing coarse CLS data. The effectiveness and potential of the developed approaches are demonstrated through experiments on actual machining and interpolation.

Nonparametric estimation of age-specific reference percentile curves with radial smoothing.

Science.gov (United States)

Wan, Xiaohai; Qu, Yongming; Huang, Yao; Zhang, Xiao; Song, Hanping; Jiang, Honghua

2012-01-01

Reference percentile curves represent the covariate-dependent distribution of a quantitative measurement and are often used to summarize and monitor dynamic processes such as human growth. We propose a new nonparametric method based on a radial smoothing (RS) technique to estimate age-specific reference percentile curves assuming the underlying distribution is relatively close to normal. We compared the RS method with both the LMS and the generalized additive models for location, scale and shape (GAMLSS) methods using simulated data and found that our method has smaller estimation error than the two existing methods. We also applied the new method to analyze height growth data from children being followed in a clinical observational study of growth hormone treatment, and compared the growth curves between those with growth disorders and the general population. Copyright © 2011 Elsevier Inc. All rights reserved.

Curve fitting and modeling with splines using statistical variable selection techniques

Science.gov (United States)

Smith, P. L.

1982-01-01

The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Smooth Phase Interpolated Keying

Science.gov (United States)

Borah, Deva K.

2007-01-01

that result in equal numbers of clockwise and counter-clockwise phase rotations for equally likely symbols. The purpose served by assigning phase values in this way is to prevent unnecessary generation of spectral lines and prevent net shifts of the carrier signal. In the phase-interpolation step, the smooth phase values are interpolated over a number, n, of consecutive symbols (including the present symbol) by means of an unconventional spline curve fit.

Splines and their reciprocal-bases in volume-integral equations

International Nuclear Information System (INIS)

Sabbagh, H.A.

1993-01-01

The authors briefly outline the use of higher-order splines and their reciprocal-bases in discretizing the volume-integral equations of electromagnetics. The discretization is carried out by means of the method of moments, in which the expansion functions are the higher-order splines, and the testing functions are the corresponding reciprocal-basis functions. These functions satisfy an orthogonality condition with respect to the spline expansion functions. Thus, the method is not Galerkin, but the structure of the resulting equations is quite regular, nevertheless. The theory is applied to the volume-integral equations for the unknown current density, or unknown electric field, within a scattering body, and to the equations for eddy-current nondestructive evaluation. Numerical techniques for computing the matrix elements are also given

Point based interactive image segmentation using multiquadrics splines

Science.gov (United States)

Meena, Sachin; Duraisamy, Prakash; Palniappan, Kannappan; Seetharaman, Guna

2017-05-01

Multiquadrics (MQ) are radial basis spline function that can provide an efficient interpolation of data points located in a high dimensional space. MQ were developed by Hardy to approximate geographical surfaces and terrain modelling. In this paper we frame the task of interactive image segmentation as a semi-supervised interpolation where an interpolating function learned from the user provided seed points is used to predict the labels of unlabeled pixel and the spline function used in the semi-supervised interpolation is MQ. This semi-supervised interpolation framework has a nice closed form solution which along with the fact that MQ is a radial basis spline function lead to a very fast interactive image segmentation process. Quantitative and qualitative results on the standard datasets show that MQ outperforms other regression based methods, GEBS, Ridge Regression and Logistic Regression, and popular methods like Graph Cut,4 Random Walk and Random Forest.6

Doubly robust estimation of generalized partial linear models for longitudinal data with dropouts.

Science.gov (United States)

Lin, Huiming; Fu, Bo; Qin, Guoyou; Zhu, Zhongyi

2017-12-01

We develop a doubly robust estimation of generalized partial linear models for longitudinal data with dropouts. Our method extends the highly efficient aggregate unbiased estimating function approach proposed in Qu et al. (2010) to a doubly robust one in the sense that under missing at random (MAR), our estimator is consistent when either the linear conditional mean condition is satisfied or a model for the dropout process is correctly specified. We begin with a generalized linear model for the marginal mean, and then move forward to a generalized partial linear model, allowing for nonparametric covariate effect by using the regression spline smoothing approximation. We establish the asymptotic theory for the proposed method and use simulation studies to compare its finite sample performance with that of Qu's method, the complete-case generalized estimating equation (GEE) and the inverse-probability weighted GEE. The proposed method is finally illustrated using data from a longitudinal cohort study. © 2017, The International Biometric Society.

Transmit/Receive Spatial Smoothing with Improved Effective Array Aperture for Angle and Mutual Coupling Estimation in Bistatic MIMO Radar

Directory of Open Access Journals (Sweden)

Haomiao Liu

2016-01-01

Full Text Available We proposed a transmit/receive spatial smoothing with improved effective aperture approach for angle and mutual coupling estimation in bistatic MIMO radar. Firstly, the noise in each channel is restrained, by exploiting its independency, in both the spatial domain and temporal domain. Then the augmented transmit and receive spatial smoothing matrices with improved effective aperture are obtained, by exploiting the Vandermonde structure of steering vector with uniform linear array. The DOD and DOA can be estimated by utilizing the unitary ESPRIT algorithm. Finally, the mutual coupling coefficients of both the transmitter and the receiver can be figured out with the estimated angles of DOD and DOA. Numerical examples are presented to verify the effectiveness of the proposed method.

Fine-granularity inference and estimations to network traffic for SDN.

Directory of Open Access Journals (Sweden)

Dingde Jiang

Full Text Available An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN. However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective.

Fine-granularity inference and estimations to network traffic for SDN.

Science.gov (United States)

Jiang, Dingde; Huo, Liuwei; Li, Ya

2018-01-01

An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective.

Smoothing and projecting age-specific probabilities of death by TOPALS

Directory of Open Access Journals (Sweden)

Joop de Beer

2012-10-01

Full Text Available BACKGROUND TOPALS is a new relational model for smoothing and projecting age schedules. The model is operationally simple, flexible, and transparent. OBJECTIVE This article demonstrates how TOPALS can be used for both smoothing and projecting age-specific mortality for 26 European countries and compares the results of TOPALS with those of other smoothing and projection methods. METHODS TOPALS uses a linear spline to describe the ratios between the age-specific death probabilities of a given country and a standard age schedule. For smoothing purposes I use the average of death probabilities over 15 Western European countries as standard, whereas for projection purposes I use an age schedule of 'best practice' mortality. A partial adjustment model projects how quickly the death probabilities move in the direction of the best-practice level of mortality. RESULTS On average, TOPALS performs better than the Heligman-Pollard model and the Brass relational method in smoothing mortality age schedules. TOPALS can produce projections that are similar to those of the Lee-Carter method, but can easily be used to produce alternative scenarios as well. This article presents three projections of life expectancy at birth for the year 2060 for 26 European countries. The Baseline scenario assumes a continuation of the past trend in each country, the Convergence scenario assumes that there is a common trend across European countries, and the Acceleration scenario assumes that the future decline of death probabilities will exceed that in the past. The Baseline scenario projects that average European life expectancy at birth will increase to 80 years for men and 87 years for women in 2060, whereas the Acceleration scenario projects an increase to 90 and 93 years respectively. CONCLUSIONS TOPALS is a useful new tool for demographers for both smoothing age schedules and making scenarios.

Gearbox Reliability Collaborative Analytic Formulation for the Evaluation of Spline Couplings

Energy Technology Data Exchange (ETDEWEB)

Guo, Yi [National Renewable Energy Lab. (NREL), Golden, CO (United States); Keller, Jonathan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Errichello, Robert [GEARTECH, Houston, TX (United States); Halse, Chris [Romax Technology, Nottingham (United Kingdom)

2013-12-01

Gearboxes in wind turbines have not been achieving their expected design life; however, they commonly meet and exceed the design criteria specified in current standards in the gear, bearing, and wind turbine industry as well as third-party certification criteria. The cost of gearbox replacements and rebuilds, as well as the down time associated with these failures, has elevated the cost of wind energy. The National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC) was established by the U.S. Department of Energy in 2006; its key goal is to understand the root causes of premature gearbox failures and improve their reliability using a combined approach of dynamometer testing, field testing, and modeling. As part of the GRC program, this paper investigates the design of the spline coupling often used in modern wind turbine gearboxes to connect the planetary and helical gear stages. Aside from transmitting the driving torque, another common function of the spline coupling is to allow the sun to float between the planets. The amount the sun can float is determined by the spline design and the sun shaft flexibility subject to the operational loads. Current standards address spline coupling design requirements in varying detail. This report provides additional insight beyond these current standards to quickly evaluate spline coupling designs.

Acoustic Emission Signatures of Fatigue Damage in Idealized Bevel Gear Spline for Localized Sensing

Directory of Open Access Journals (Sweden)

Lu Zhang

2017-06-01

Full Text Available In many rotating machinery applications, such as helicopters, the splines of an externally-splined steel shaft that emerges from the gearbox engage with the reverse geometry of an internally splined driven shaft for the delivery of power. The splined section of the shaft is a critical and non-redundant element which is prone to cracking due to complex loading conditions. Thus, early detection of flaws is required to prevent catastrophic failures. The acoustic emission (AE method is a direct way of detecting such active flaws, but its application to detect flaws in a splined shaft in a gearbox is difficult due to the interference of background noise and uncertainty about the effects of the wave propagation path on the received AE signature. Here, to model how AE may detect fault propagation in a hollow cylindrical splined shaft, the splined section is essentially unrolled into a metal plate of the same thickness as the cylinder wall. Spline ridges are cut into this plate, a through-notch is cut perpendicular to the spline to model fatigue crack initiation, and tensile cyclic loading is applied parallel to the spline to propagate the crack. In this paper, the new piezoelectric sensor array is introduced with the purpose of placing them within the gearbox to minimize the wave propagation path. The fatigue crack growth of a notched and flattened gearbox spline component is monitored using a new piezoelectric sensor array and conventional sensors in a laboratory environment with the purpose of developing source models and testing the new sensor performance. The AE data is continuously collected together with strain gauges strategically positioned on the structure. A significant amount of continuous emission due to the plastic deformation accompanied with the crack growth is observed. The frequency spectra of continuous emissions and burst emissions are compared to understand the differences of plastic deformation and sudden crack jump. The

Modeling the dispersion of atmospheric pollution using cubic splines and chapeau functions

Energy Technology Data Exchange (ETDEWEB)

Pepper, D W; Kern, C D; Long, P E

1979-01-01

Two methods that can be used to solve complex, three-dimensional, advection-diffusion transport equations are investigated. A quasi-Lagrangian cubic spline method and a chapeau function method are compared in advecting a passive scalar. The methods are simple to use, computationally fast, and reasonably accurate. Little numerical dissipation is manifested by the schemes. In simple advection tests with equal mesh spacing, the chapeau function method maintains slightly more accurate peak values than the cubic spline method. In tests with unequal mesh spacing, the cubic spline method has less noise, but slightly more damping than the standard chapeau method has. Both cubic splines and chapeau functions can be used to solve the three-dimensional problem of gaseous emissions dispersion without excessive programing complexity or storage requirements. (10 diagrams, 39 references, 2 tables)

Integration by cell algorithm for Slater integrals in a spline basis

International Nuclear Information System (INIS)

Qiu, Y.; Fischer, C.F.

1999-01-01

An algorithm for evaluating Slater integrals in a B-spline basis is introduced. Based on the piecewise property of the B-splines, the algorithm divides the two-dimensional (r 1 , r 2 ) region into a number of rectangular cells according to the chosen grid and implements the two-dimensional integration over each individual cell using Gaussian quadrature. Over the off-diagonal cells, the integrands are separable so that each two-dimensional cell-integral is reduced to a product of two one-dimensional integrals. Furthermore, the scaling invariance of the B-splines in the logarithmic region of the chosen grid is fully exploited such that only some of the cell integrations need to be implemented. The values of given Slater integrals are obtained by assembling the cell integrals. This algorithm significantly improves the efficiency and accuracy of the traditional method that relies on the solution of differential equations and renders the B-spline method more effective when applied to multi-electron atomic systems

About the Modeling of Radio Source Time Series as Linear Splines

Science.gov (United States)

Karbon, Maria; Heinkelmann, Robert; Mora-Diaz, Julian; Xu, Minghui; Nilsson, Tobias; Schuh, Harald

2016-12-01

Many of the time series of radio sources observed in geodetic VLBI show variations, caused mainly by changes in source structure. However, until now it has been common practice to consider source positions as invariant, or to exclude known misbehaving sources from the datum conditions. This may lead to a degradation of the estimated parameters, as unmodeled apparent source position variations can propagate to the other parameters through the least squares adjustment. In this paper we will introduce an automated algorithm capable of parameterizing the radio source coordinates as linear splines.

Numerical Solutions for Convection-Diffusion Equation through Non-Polynomial Spline

Directory of Open Access Journals (Sweden)

Ravi Kanth A.S.V.

2016-01-01

Full Text Available In this paper, numerical solutions for convection-diffusion equation via non-polynomial splines are studied. We purpose an implicit method based on non-polynomial spline functions for solving the convection-diffusion equation. The method is proven to be unconditionally stable by using Von Neumann technique. Numerical results are illustrated to demonstrate the efficiency and stability of the purposed method.

[Multimodal medical image registration using cubic spline interpolation method].

Science.gov (United States)

He, Yuanlie; Tian, Lianfang; Chen, Ping; Wang, Lifei; Ye, Guangchun; Mao, Zongyuan

2007-12-01

Based on the characteristic of the PET-CT multimodal image series, a novel image registration and fusion method is proposed, in which the cubic spline interpolation method is applied to realize the interpolation of PET-CT image series, then registration is carried out by using mutual information algorithm and finally the improved principal component analysis method is used for the fusion of PET-CT multimodal images to enhance the visual effect of PET image, thus satisfied registration and fusion results are obtained. The cubic spline interpolation method is used for reconstruction to restore the missed information between image slices, which can compensate for the shortage of previous registration methods, improve the accuracy of the registration, and make the fused multimodal images more similar to the real image. Finally, the cubic spline interpolation method has been successfully applied in developing 3D-CRT (3D Conformal Radiation Therapy) system.

Estimation of Posterior Probabilities Using Multivariate Smoothing Splines and Generalized Cross-Validation.

Science.gov (United States)

1983-09-01

Ciencia y Tecnologia -Mexico, by ONR under Contract No. N00014-77-C-0675, and by ARO under Contract No. DAAG29-80-K-0042. LUJ THE VIE~W, rTIJ. ’~v ’’~c...Department of Statis- tics. For financial support I thank the Consejo Nacional de Ciencia y Tecnologia - Mexico, and the Department of Statistics of the...from the context of the expression what they should be. The ia element (covariate) of an observations y will be denoted by ",(4) and all vectors will be

Explicit Gaussian quadrature rules for C^1 cubic splines with symmetrically stretched knot sequence

KAUST Repository

Ait-Haddou, Rachid

2015-06-19

We provide explicit expressions for quadrature rules on the space of C^1 cubic splines with non-uniform, symmetrically stretched knot sequences. The quadrature nodes and weights are derived via an explicit recursion that avoids an intervention of any numerical solver and the rule is optimal, that is, it requires minimal number of nodes. Numerical experiments validating the theoretical results and the error estimates of the quadrature rules are also presented.

Estimation of airway smooth muscle stiffness changes due to length oscillation using artificial neural network.

Science.gov (United States)

Al-Jumaily, Ahmed; Chen, Leizhi

2012-10-07

This paper presents a novel approach to estimate stiffness changes in airway smooth muscles due to external oscillation. Artificial neural networks are used to model the stiffness changes due to cyclic stretches of the smooth muscles. The nonlinear relationship between stiffness ratios and oscillation frequencies is modeled by a feed-forward neural network (FNN) model. The structure of the FNN is selected through the training and validation using literature data from 11 experiments with different muscle lengths, muscle masses, oscillation frequencies and amplitudes. Data pre-processing methods are used to improve the robustness of the neural network model to match the non-linearity. The validation results show that the FNN model can predict the stiffness ratio changes with a mean square error of 0.0042. Copyright © 2012 Elsevier Ltd. All rights reserved.

Smooth Approximation l 0-Norm Constrained Affine Projection Algorithm and Its Applications in Sparse Channel Estimation

Science.gov (United States)

2014-01-01

We propose a smooth approximation l 0-norm constrained affine projection algorithm (SL0-APA) to improve the convergence speed and the steady-state error of affine projection algorithm (APA) for sparse channel estimation. The proposed algorithm ensures improved performance in terms of the convergence speed and the steady-state error via the combination of a smooth approximation l 0-norm (SL0) penalty on the coefficients into the standard APA cost function, which gives rise to a zero attractor that promotes the sparsity of the channel taps in the channel estimation and hence accelerates the convergence speed and reduces the steady-state error when the channel is sparse. The simulation results demonstrate that our proposed SL0-APA is superior to the standard APA and its sparsity-aware algorithms in terms of both the convergence speed and the steady-state behavior in a designated sparse channel. Furthermore, SL0-APA is shown to have smaller steady-state error than the previously proposed sparsity-aware algorithms when the number of nonzero taps in the sparse channel increases. PMID:24790588

On convexity and Schoenberg's variation diminishing splines

International Nuclear Information System (INIS)

Feng, Yuyu; Kozak, J.

1992-11-01

In the paper we characterize a convex function by the monotonicity of a particular variation diminishing spline sequence. The result extends the property known for the Bernstein polynomial sequence. (author). 4 refs

An adaptive segment method for smoothing lidar signal based on noise estimation

Science.gov (United States)

Wang, Yuzhao; Luo, Pingping

2014-10-01

An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

A One-Step-Ahead Smoothing-Based Joint Ensemble Kalman Filter for State-Parameter Estimation of Hydrological Models

KAUST Repository

El Gharamti, Mohamad

2015-11-26

The ensemble Kalman filter (EnKF) recursively integrates field data into simulation models to obtain a better characterization of the model’s state and parameters. These are generally estimated following a state-parameters joint augmentation strategy. In this study, we introduce a new smoothing-based joint EnKF scheme, in which we introduce a one-step-ahead smoothing of the state before updating the parameters. Numerical experiments are performed with a two-dimensional synthetic subsurface contaminant transport model. The improved performance of the proposed joint EnKF scheme compared to the standard joint EnKF compensates for the modest increase in the computational cost.

Stabilized Discretization in Spline Element Method for Solution of Two-Dimensional Navier-Stokes Problems

Directory of Open Access Journals (Sweden)

Neng Wan

2014-01-01

Full Text Available In terms of the poor geometric adaptability of spline element method, a geometric precision spline method, which uses the rational Bezier patches to indicate the solution domain, is proposed for two-dimensional viscous uncompressed Navier-Stokes equation. Besides fewer pending unknowns, higher accuracy, and computation efficiency, it possesses such advantages as accurate representation of isogeometric analysis for object boundary and the unity of geometry and analysis modeling. Meanwhile, the selection of B-spline basis functions and the grid definition is studied and a stable discretization format satisfying inf-sup conditions is proposed. The degree of spline functions approaching the velocity field is one order higher than that approaching pressure field, and these functions are defined on one-time refined grid. The Dirichlet boundary conditions are imposed through the Nitsche variational principle in weak form due to the lack of interpolation properties of the B-splines functions. Finally, the validity of the proposed method is verified with some examples.

Application of thin plate splines for accurate regional ionosphere modeling with multi-GNSS data

Science.gov (United States)

Krypiak-Gregorczyk, Anna; Wielgosz, Pawel; Borkowski, Andrzej

2016-04-01

GNSS-derived regional ionosphere models are widely used in both precise positioning, ionosphere and space weather studies. However, their accuracy is often not sufficient to support precise positioning, RTK in particular. In this paper, we presented new approach that uses solely carrier phase multi-GNSS observables and thin plate splines (TPS) for accurate ionospheric TEC modeling. TPS is a closed solution of a variational problem minimizing both the sum of squared second derivatives of a smoothing function and the deviation between data points and this function. This approach is used in UWM-rt1 regional ionosphere model developed at UWM in Olsztyn. The model allows for providing ionospheric TEC maps with high spatial and temporal resolutions - 0.2x0.2 degrees and 2.5 minutes, respectively. For TEC estimation, EPN and EUPOS reference station data is used. The maps are available with delay of 15-60 minutes. In this paper we compare the performance of UWM-rt1 model with IGS global and CODE regional ionosphere maps during ionospheric storm that took place on March 17th, 2015. During this storm, the TEC level over Europe doubled comparing to earlier quiet days. The performance of the UWM-rt1 model was validated by (a) comparison to reference double-differenced ionospheric corrections over selected baselines, and (b) analysis of post-fit residuals to calibrated carrier phase geometry-free observational arcs at selected test stations. The results show a very good performance of UWM-rt1 model. The obtained post-fit residuals in case of UWM maps are lower by one order of magnitude comparing to IGS maps. The accuracy of UWM-rt1 -derived TEC maps is estimated at 0.5 TECU. This may be directly translated to the user positioning domain.

Scripted Bodies and Spline Driven Animation

DEFF Research Database (Denmark)

Erleben, Kenny; Henriksen, Knud

2002-01-01

In this paper we will take a close look at the details and technicalities in applying spline driven animation to scripted bodies in the context of dynamic simulation. The main contributions presented in this paper are methods for computing velocities and accelerations in the time domain...

Numerical solution of system of boundary value problems using B-spline with free parameter

Science.gov (United States)

Gupta, Yogesh

2017-01-01

This paper deals with method of B-spline solution for a system of boundary value problems. The differential equations are useful in various fields of science and engineering. Some interesting real life problems involve more than one unknown function. These result in system of simultaneous differential equations. Such systems have been applied to many problems in mathematics, physics, engineering etc. In present paper, B-spline and B-spline with free parameter methods for the solution of a linear system of second-order boundary value problems are presented. The methods utilize the values of cubic B-spline and its derivatives at nodal points together with the equations of the given system and boundary conditions, ensuing into the linear matrix equation.

Development of quadrilateral spline thin plate elements using the B-net method

Science.gov (United States)

Chen, Juan; Li, Chong-Jun

2013-08-01

The quadrilateral discrete Kirchhoff thin plate bending element DKQ is based on the isoparametric element Q8, however, the accuracy of the isoparametric quadrilateral elements will drop significantly due to mesh distortions. In a previouswork, we constructed an 8-node quadrilateral spline element L8 using the triangular area coordinates and the B-net method, which can be insensitive to mesh distortions and possess the second order completeness in the Cartesian coordinates. In this paper, a thin plate spline element is developed based on the spline element L8 and the refined technique. Numerical examples show that the present element indeed possesses higher accuracy than the DKQ element for distorted meshes.

Smoothing-based compressed state Kalman filter for joint state-parameter estimation: Applications in reservoir characterization and CO2 storage monitoring

Science.gov (United States)

Li, Y. J.; Kokkinaki, Amalia; Darve, Eric F.; Kitanidis, Peter K.

2017-08-01

The operation of most engineered hydrogeological systems relies on simulating physical processes using numerical models with uncertain parameters and initial conditions. Predictions by such uncertain models can be greatly improved by Kalman-filter techniques that sequentially assimilate monitoring data. Each assimilation constitutes a nonlinear optimization, which is solved by linearizing an objective function about the model prediction and applying a linear correction to this prediction. However, if model parameters and initial conditions are uncertain, the optimization problem becomes strongly nonlinear and a linear correction may yield unphysical results. In this paper, we investigate the utility of one-step ahead smoothing, a variant of the traditional filtering process, to eliminate nonphysical results and reduce estimation artifacts caused by nonlinearities. We present the smoothing-based compressed state Kalman filter (sCSKF), an algorithm that combines one step ahead smoothing, in which current observations are used to correct the state and parameters one step back in time, with a nonensemble covariance compression scheme, that reduces the computational cost by efficiently exploring the high-dimensional state and parameter space. Numerical experiments show that when model parameters are uncertain and the states exhibit hyperbolic behavior with sharp fronts, as in CO2 storage applications, one-step ahead smoothing reduces overshooting errors and, by design, gives physically consistent state and parameter estimates. We compared sCSKF with commonly used data assimilation methods and showed that for the same computational cost, combining one step ahead smoothing and nonensemble compression is advantageous for real-time characterization and monitoring of large-scale hydrogeological systems with sharp moving fronts.

MHD stability analysis using higher order spline functions

Energy Technology Data Exchange (ETDEWEB)

Ida, Akihiro [Department of Energy Engineering and Science, Graduate School of Engineering, Nagoya University, Nagoya, Aichi (Japan); Todoroki, Jiro; Sanuki, Heiji

1999-04-01

The eigenvalue problem of the linearized magnetohydrodynamic (MHD) equation is formulated by using higher order spline functions as the base functions of Ritz-Galerkin approximation. When the displacement vector normal to the magnetic surface (in the magnetic surface) is interpolated by B-spline functions of degree p{sub 1} (degree p{sub 2}), which is continuously c{sub 1}-th (c{sub 2}-th) differentiable on neighboring finite elements, the sufficient conditions for the good approximation is given by p{sub 1}{>=}p{sub 2}+1, c{sub 1}{<=}c{sub 2}+1, (c{sub 1}{>=}1, p{sub 2}{>=}c{sub 2}{>=}0). The influence of the numerical integration upon the convergence of calculated eigenvalues is discussed. (author)

Dynamic metabolic flux analysis using B-splines to study the effects of temperature shift on CHO cell metabolism

Directory of Open Access Journals (Sweden)

Verónica S. Martínez

2015-12-01

Full Text Available Metabolic flux analysis (MFA is widely used to estimate intracellular fluxes. Conventional MFA, however, is limited to continuous cultures and the mid-exponential growth phase of batch cultures. Dynamic MFA (DMFA has emerged to characterize time-resolved metabolic fluxes for the entire culture period. Here, the linear DMFA approach was extended using B-spline fitting (B-DMFA to estimate mass balanced fluxes. Smoother fits were achieved using reduced number of knots and parameters. Additionally, computation time was greatly reduced using a new heuristic algorithm for knot placement. B-DMFA revealed that Chinese hamster ovary cells shifted from 37 °C to 32 °C maintained a constant IgG volume-specific productivity, whereas the productivity for the controls peaked during mid-exponential growth phase and declined afterward. The observed 42% increase in product titer at 32 °C was explained by a prolonged cell growth with high cell viability, a larger cell volume and a more stable volume-specific productivity. Keywords: Dynamic, Metabolism, Flux analysis, CHO cells, Temperature shift, B-spline curve fitting

Estimation of time-varying growth, uptake and excretion rates from dynamic metabolomics data.

Science.gov (United States)

Cinquemani, Eugenio; Laroute, Valérie; Cocaign-Bousquet, Muriel; de Jong, Hidde; Ropers, Delphine

2017-07-15

Technological advances in metabolomics have made it possible to monitor the concentration of extracellular metabolites over time. From these data, it is possible to compute the rates of uptake and excretion of the metabolites by a growing cell population, providing precious information on the functioning of intracellular metabolism. The computation of the rate of these exchange reactions, however, is difficult to achieve in practice for a number of reasons, notably noisy measurements, correlations between the concentration profiles of the different extracellular metabolites, and discontinuties in the profiles due to sudden changes in metabolic regime. We present a method for precisely estimating time-varying uptake and excretion rates from time-series measurements of extracellular metabolite concentrations, specifically addressing all of the above issues. The estimation problem is formulated in a regularized Bayesian framework and solved by a combination of extended Kalman filtering and smoothing. The method is shown to improve upon methods based on spline smoothing of the data. Moreover, when applied to two actual datasets, the method recovers known features of overflow metabolism in Escherichia coli and Lactococcus lactis , and provides evidence for acetate uptake by L. lactis after glucose exhaustion. The results raise interesting perspectives for further work on rate estimation from measurements of intracellular metabolites. The Matlab code for the estimation method is available for download at https://team.inria.fr/ibis/rate-estimation-software/ , together with the datasets. eugenio.cinquemani@inria.fr. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Practical aspects of estimating energy components in rodents

Directory of Open Access Journals (Sweden)

Jan Bert evan Klinken

2013-05-01

Full Text Available Recently there has been an increasing interest in exploiting computational and statistical techniques for the purpose of component analysis of indirect calorimetry data. Using these methods it becomes possible to dissect daily energy expenditure into its components and to assess the dynamic response of the resting metabolic rate to nutritional and pharmacological manipulations. To perform robust component analysis, however, is not straightforward and typically requires the tuning of parameters and the preprocessing of data. Moreover the degree of accuracy that can be attained by these methods depends on the configuration of the system, which must be properly taken into account when setting up experimental studies. Here, we review the methods of Kalman filtering, linear and penalised spline regression, and minimal energy expenditure estimation in the context of component analysis and discuss their results on high resolution datasets from mice and rats. In addition, we investigate the effect of the sample time, the accuracy of the activity sensor, and the washout time of the chamber on the estimation accuracy. We found that on the high resolution data there was a strong correlation between the results of Kalman filtering and P-spline regression, except for the activity respiratory quotient. For low resolution data the basal metabolic rate and resting respiratory quotient could still be estimated accurately with P-spline regression, having a strong correlation with the high resolution estimate (R2 > 0.997; sample time of 9 min. In contrast, the thermic effect of food and activity related energy expenditure were more sensitive to a reduction in the sample rate (R2 > 0.97.In conclusion, for component analysis on data generated by single channel systems with continuous data acquisition both Kalman filtering and P-spline regression can be used, while for low resolution data from multichannel systems P-spline regression gives more robust results.

Application of Cubic Box Spline Wavelets in the Analysis of Signal Singularities

Directory of Open Access Journals (Sweden)

Rakowski Waldemar

2015-12-01

Full Text Available In the subject literature, wavelets such as the Mexican hat (the second derivative of a Gaussian or the quadratic box spline are commonly used for the task of singularity detection. The disadvantage of the Mexican hat, however, is its unlimited support; the disadvantage of the quadratic box spline is a phase shift introduced by the wavelet, making it difficult to locate singular points. The paper deals with the construction and properties of wavelets in the form of cubic box splines which have compact and short support and which do not introduce a phase shift. The digital filters associated with cubic box wavelets that are applied in implementing the discrete dyadic wavelet transform are defined. The filters and the algorithme à trous of the discrete dyadic wavelet transform are used in detecting signal singularities and in calculating the measures of signal singularities in the form of a Lipschitz exponent. The article presents examples illustrating the use of cubic box spline wavelets in the analysis of signal singularities.

Splines and variational methods

CERN Document Server

Prenter, P M

2008-01-01

One of the clearest available introductions to variational methods, this text requires only a minimal background in calculus and linear algebra. Its self-contained treatment explains the application of theoretic notions to the kinds of physical problems that engineers regularly encounter. The text's first half concerns approximation theoretic notions, exploring the theory and computation of one- and two-dimensional polynomial and other spline functions. Later chapters examine variational methods in the solution of operator equations, focusing on boundary value problems in one and two dimension

An isogeometric boundary element method for electromagnetic scattering with compatible B-spline discretizations

Science.gov (United States)

Simpson, R. N.; Liu, Z.; Vázquez, R.; Evans, J. A.

2018-06-01

We outline the construction of compatible B-splines on 3D surfaces that satisfy the continuity requirements for electromagnetic scattering analysis with the boundary element method (method of moments). Our approach makes use of Non-Uniform Rational B-splines to represent model geometry and compatible B-splines to approximate the surface current, and adopts the isogeometric concept in which the basis for analysis is taken directly from CAD (geometry) data. The approach allows for high-order approximations and crucially provides a direct link with CAD data structures that allows for efficient design workflows. After outlining the construction of div- and curl-conforming B-splines defined over 3D surfaces we describe their use with the electric and magnetic field integral equations using a Galerkin formulation. We use Bézier extraction to accelerate the computation of NURBS and B-spline terms and employ H-matrices to provide accelerated computations and memory reduction for the dense matrices that result from the boundary integral discretization. The method is verified using the well known Mie scattering problem posed over a perfectly electrically conducting sphere and the classic NASA almond problem. Finally, we demonstrate the ability of the approach to handle models with complex geometry directly from CAD without mesh generation.

StarSmasher: Smoothed Particle Hydrodynamics code for smashing stars and planets

Science.gov (United States)

Gaburov, Evghenii; Lombardi, James C., Jr.; Portegies Zwart, Simon; Rasio, F. A.

2018-05-01

Smoothed Particle Hydrodynamics (SPH) is a Lagrangian particle method that approximates a continuous fluid as discrete nodes, each carrying various parameters such as mass, position, velocity, pressure, and temperature. In an SPH simulation the resolution scales with the particle density; StarSmasher is able to handle both equal-mass and equal number-density particle models. StarSmasher solves for hydro forces by calculating the pressure for each particle as a function of the particle's properties - density, internal energy, and internal properties (e.g. temperature and mean molecular weight). The code implements variational equations of motion and libraries to calculate the gravitational forces between particles using direct summation on NVIDIA graphics cards. Using a direct summation instead of a tree-based algorithm for gravity increases the accuracy of the gravity calculations at the cost of speed. The code uses a cubic spline for the smoothing kernel and an artificial viscosity prescription coupled with a Balsara Switch to prevent unphysical interparticle penetration. The code also implements an artificial relaxation force to the equations of motion to add a drag term to the calculated accelerations during relaxation integrations. Initially called StarCrash, StarSmasher was developed originally by Rasio.

Modeling terminal ballistics using blending-type spline surfaces

Science.gov (United States)

Pedersen, Aleksander; Bratlie, Jostein; Dalmo, Rune

2014-12-01

We explore using GERBS, a blending-type spline construction, to represent deform able thin-plates and model terminal ballistics. Strategies to construct geometry for different scenarios of terminal ballistics are proposed.

Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems.

Science.gov (United States)

Bhadra, Anindya; Carroll, Raymond J

2016-07-01

In truncated polynomial spline or B-spline models where the covariates are measured with error, a fully Bayesian approach to model fitting requires the covariates and model parameters to be sampled at every Markov chain Monte Carlo iteration. Sampling the unobserved covariates poses a major computational problem and usually Gibbs sampling is not possible. This forces the practitioner to use a Metropolis-Hastings step which might suffer from unacceptable performance due to poor mixing and might require careful tuning. In this article we show for the cases of truncated polynomial spline or B-spline models of degree equal to one, the complete conditional distribution of the covariates measured with error is available explicitly as a mixture of double-truncated normals, thereby enabling a Gibbs sampling scheme. We demonstrate via a simulation study that our technique performs favorably in terms of computational efficiency and statistical performance. Our results indicate up to 62 and 54 % increase in mean integrated squared error efficiency when compared to existing alternatives while using truncated polynomial splines and B-splines respectively. Furthermore, there is evidence that the gain in efficiency increases with the measurement error variance, indicating the proposed method is a particularly valuable tool for challenging applications that present high measurement error. We conclude with a demonstration on a nutritional epidemiology data set from the NIH-AARP study and by pointing out some possible extensions of the current work.

Collective estimation of multiple bivariate density functions with application to angular-sampling-based protein loop modeling

KAUST Repository

Maadooliat, Mehdi

2015-10-21

This paper develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed method was used to estimate neighbor-dependent distributions of protein backbone dihedral angles (i.e., Ramachandran distributions). The estimated distributions were applied to protein loop modeling, one of the most challenging open problems in protein structure prediction, by feeding them into an angular-sampling-based loop structure prediction framework. Our estimated distributions compared favorably to the Ramachandran distributions estimated by fitting a hierarchical Dirichlet process model; and in particular, our distributions showed significant improvements on the hard cases where existing methods do not work well.

Collective estimation of multiple bivariate density functions with application to angular-sampling-based protein loop modeling

KAUST Repository

Maadooliat, Mehdi; Zhou, Lan; Najibi, Seyed Morteza; Gao, Xin; Huang, Jianhua Z.

2015-01-01

This paper develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed method was used to estimate neighbor-dependent distributions of protein backbone dihedral angles (i.e., Ramachandran distributions). The estimated distributions were applied to protein loop modeling, one of the most challenging open problems in protein structure prediction, by feeding them into an angular-sampling-based loop structure prediction framework. Our estimated distributions compared favorably to the Ramachandran distributions estimated by fitting a hierarchical Dirichlet process model; and in particular, our distributions showed significant improvements on the hard cases where existing methods do not work well.

On the accurate fast evaluation of finite Fourier integrals using cubic splines

International Nuclear Information System (INIS)

Morishima, N.

1993-01-01

Finite Fourier integrals based on a cubic-splines fit to equidistant data are shown to be evaluated fast and accurately. Good performance, especially on computational speed, is achieved by the optimization of the spline fit and the internal use of the fast Fourier transform (FFT) algorithm for complex data. The present procedure provides high accuracy with much shorter CPU time than a trapezoidal FFT. (author)

Integration of association statistics over genomic regions using Bayesian adaptive regression splines

Directory of Open Access Journals (Sweden)

Zhang Xiaohua

2003-11-01

Full Text Available Abstract In the search for genetic determinants of complex disease, two approaches to association analysis are most often employed, testing single loci or testing a small group of loci jointly via haplotypes for their relationship to disease status. It is still debatable which of these approaches is more favourable, and under what conditions. The former has the advantage of simplicity but suffers severely when alleles at the tested loci are not in linkage disequilibrium (LD with liability alleles; the latter should capture more of the signal encoded in LD, but is far from simple. The complexity of haplotype analysis could be especially troublesome for association scans over large genomic regions, which, in fact, is becoming the standard design. For these reasons, the authors have been evaluating statistical methods that bridge the gap between single-locus and haplotype-based tests. In this article, they present one such method, which uses non-parametric regression techniques embodied by Bayesian adaptive regression splines (BARS. For a set of markers falling within a common genomic region and a corresponding set of single-locus association statistics, the BARS procedure integrates these results into a single test by examining the class of smooth curves consistent with the data. The non-parametric BARS procedure generally finds no signal when no liability allele exists in the tested region (ie it achieves the specified size of the test and it is sensitive enough to pick up signals when a liability allele is present. The BARS procedure provides a robust and potentially powerful alternative to classical tests of association, diminishes the multiple testing problem inherent in those tests and can be applied to a wide range of data types, including genotype frequencies estimated from pooled samples.

Regional Densification of a Global VTEC Model Based on B-Spline Representations

Science.gov (United States)

Erdogan, Eren; Schmidt, Michael; Dettmering, Denise; Goss, Andreas; Seitz, Florian; Börger, Klaus; Brandert, Sylvia; Görres, Barbara; Kersten, Wilhelm F.; Bothmer, Volker; Hinrichs, Johannes; Mrotzek, Niclas

2017-04-01

both directions. The spectral resolution of both model parts is defined by the number of B-spline basis functions introduced for longitude and latitude directions related to appropriate coordinate systems. Furthermore, the TLVM has to be developed under the postulation that the global model part will be computed continuously in near real-time (NRT) and routinely predicted into the future by an algorithm based on deterministic and statistical forecast models. Thus, the additional regional densification model part, which will be computed also in NRT, but possibly only for a specified time duration, must be estimated independently from the global one. For that purpose a data separation procedure has to be developed in order to estimate the unknown series coefficients of both model parts independently. This procedure must also consider additional technique-dependent unknowns such as the Differential Code Biases (DCBs) within GNSS and intersystem biases. In this contribution we will present the concept to set up the TLVM including the data combination and the Kalman filtering procedure; first numerical results will be presented.

Analytic regularization of uniform cubic B-spline deformation fields.

Science.gov (United States)

Shackleford, James A; Yang, Qi; Lourenço, Ana M; Shusharina, Nadya; Kandasamy, Nagarajan; Sharp, Gregory C

2012-01-01

Image registration is inherently ill-posed, and lacks a unique solution. In the context of medical applications, it is desirable to avoid solutions that describe physically unsound deformations within the patient anatomy. Among the accepted methods of regularizing non-rigid image registration to provide solutions applicable to medical practice is the penalty of thin-plate bending energy. In this paper, we develop an exact, analytic method for computing the bending energy of a three-dimensional B-spline deformation field as a quadratic matrix operation on the spline coefficient values. Results presented on ten thoracic case studies indicate the analytic solution is between 61-1371x faster than a numerical central differencing solution.

A comparison of tripolar concentric ring electrode and spline Laplacians on a four-layer concentric spherical model.

Science.gov (United States)

Liu, Xiang; Makeyev, Oleksandr; Besio, Walter

2011-01-01

We have simulated a four-layer concentric spherical head model. We calculated the spline and tripolar Laplacian estimates and compared them to the analytical Laplacian on the spherical surface. In the simulations we used five different dipole groups and two electrode configurations. The comparison shows that the tripolar Laplacian has higher correlation coefficient to the analytical Laplacian in the electrode configurations tested (19, standard 10/20 locations and 64 electrodes).

B-spline solution of a singularly perturbed boundary value problem arising in biology

International Nuclear Information System (INIS)

Lin Bin; Li Kaitai; Cheng Zhengxing

2009-01-01

We use B-spline functions to develop a numerical method for solving a singularly perturbed boundary value problem associated with biology science. We use B-spline collocation method, which leads to a tridiagonal linear system. The accuracy of the proposed method is demonstrated by test problems. The numerical result is found in good agreement with exact solution.

A baseline correction algorithm for Raman spectroscopy by adaptive knots B-spline

International Nuclear Information System (INIS)

Wang, Xin; Fan, Xian-guang; Xu, Ying-jie; Wang, Xiu-fen; He, Hao; Zuo, Yong

2015-01-01

The Raman spectroscopy technique is a powerful and non-invasive technique for molecular fingerprint detection which has been widely used in many areas, such as food safety, drug safety, and environmental testing. But Raman signals can be easily corrupted by a fluorescent background, therefore we presented a baseline correction algorithm to suppress the fluorescent background in this paper. In this algorithm, the background of the Raman signal was suppressed by fitting a curve called a baseline using a cyclic approximation method. Instead of the traditional polynomial fitting, we used the B-spline as the fitting algorithm due to its advantages of low-order and smoothness, which can avoid under-fitting and over-fitting effectively. In addition, we also presented an automatic adaptive knot generation method to replace traditional uniform knots. This algorithm can obtain the desired performance for most Raman spectra with varying baselines without any user input or preprocessing step. In the simulation, three kinds of fluorescent background lines were introduced to test the effectiveness of the proposed method. We showed that two real Raman spectra (parathion-methyl and colza oil) can be detected and their baselines were also corrected by the proposed method. (paper)

Effects of slope smoothing in river channel modeling

Science.gov (United States)

Kim, Kyungmin; Liu, Frank; Hodges, Ben R.

2017-04-01

In extending dynamic river modeling with the 1D Saint-Venant equations from a single reach to a large watershed there are critical questions as to how much bathymetric knowledge is necessary and how it should be represented parsimoniously. The ideal model will include the detail necessary to provide realism, but not include extraneous detail that should not exert a control on a 1D (cross-section averaged) solution. In a Saint-Venant model, the overall complexity of the river channel morphometry is typically abstracted into metrics for the channel slope, cross-sectional area, hydraulic radius, and roughness. In stream segments where cross-section surveys are closely spaced, it is not uncommon to have sharp changes in slope or even negative values (where a positive slope is the downstream direction). However, solving river flow with the Saint-Venant equations requires a degree of smoothness in the equation parameters or the equation set with the directly measured channel slopes may not be Lipschitz continuous. The results of non-smoothness are typically extended computational time to converge solutions (or complete failure to converge) and/or numerical instabilities under transient conditions. We have investigated using cubic splines to smooth the bottom slope and ensure always positive reference slopes within a 1D model. This method has been implemented in the Simulation Program for River Networks (SPRNT) and is compared to the standard HEC-RAS river solver. It is shown that the reformulation of the reference slope is both in keeping with the underlying derivation of the Saint-Venant equations and provides practical numerical stability without altering the realism of the simulation. This research was supported in part by the National Science Foundation under grant number CCF-1331610.

TPS-HAMMER: improving HAMMER registration algorithm by soft correspondence matching and thin-plate splines based deformation interpolation.

Science.gov (United States)

Wu, Guorong; Yap, Pew-Thian; Kim, Minjeong; Shen, Dinggang

2010-02-01

We present an improved MR brain image registration algorithm, called TPS-HAMMER, which is based on the concepts of attribute vectors and hierarchical landmark selection scheme proposed in the highly successful HAMMER registration algorithm. We demonstrate that TPS-HAMMER algorithm yields better registration accuracy, robustness, and speed over HAMMER owing to (1) the employment of soft correspondence matching and (2) the utilization of thin-plate splines (TPS) for sparse-to-dense deformation field generation. These two aspects can be integrated into a unified framework to refine the registration iteratively by alternating between soft correspondence matching and dense deformation field estimation. Compared with HAMMER, TPS-HAMMER affords several advantages: (1) unlike the Gaussian propagation mechanism employed in HAMMER, which can be slow and often leaves unreached blotches in the deformation field, the deformation interpolation in the non-landmark points can be obtained immediately with TPS in our algorithm; (2) the smoothness of deformation field is preserved due to the nice properties of TPS; (3) possible misalignments can be alleviated by allowing the matching of the landmarks with a number of possible candidate points and enforcing more exact matches in the final stages of the registration. Extensive experiments have been conducted, using the original HAMMER as a comparison baseline, to validate the merits of TPS-HAMMER. The results show that TPS-HAMMER yields significant improvement in both accuracy and speed, indicating high applicability for the clinical scenario. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Carrier tracking by smoothing filter improves symbol SNR

Science.gov (United States)

Pomalaza-Raez, Carlos A.; Hurd, William J.

1986-01-01

The potential benefit of using a smoothing filter to estimate carrier phase over use of phase locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of the deep space network advanced receiver. These are residual carrier PLL, sideband aided residual carrier PLL, and finally sideband aiding with a Kalman smoother. The average symbol signal to noise ratio (SNR) after losses due to carrier phase estimation error is computed for different total power SNRs, symbol rates and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.4 dB over a sideband aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to a residual carrier loop is often in excess of 1 dB.

Sequential and simultaneous SLAR block adjustment. [spline function analysis for mapping

Science.gov (United States)

Leberl, F.

1975-01-01

Two sequential methods of planimetric SLAR (Side Looking Airborne Radar) block adjustment, with and without splines, and three simultaneous methods based on the principles of least squares are evaluated. A limited experiment with simulated SLAR images indicates that sequential block formation with splines followed by external interpolative adjustment is superior to the simultaneous methods such as planimetric block adjustment with similarity transformations. The use of the sequential block formation is recommended, since it represents an inexpensive tool for satisfactory point determination from SLAR images.

An Investigation into Conversion from Non-Uniform Rational B-Spline Boundary Representation Geometry to Constructive Solid Geometry

Science.gov (United States)

2015-12-01

ARL-SR-0347 ● DEC 2015 US Army Research Laboratory An Investigation into Conversion from Non-Uniform Rational B-Spline Boundary...US Army Research Laboratory An Investigation into Conversion from Non-Uniform Rational B-Spline Boundary Representation Geometry to...from Non-Uniform Rational B-Spline Boundary Representation Geometry to Constructive Solid Geometry 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Space-Time Smoothing of Complex Survey Data: Small Area Estimation for Child Mortality.

Science.gov (United States)

Mercer, Laina D; Wakefield, Jon; Pantazis, Athena; Lutambi, Angelina M; Masanja, Honorati; Clark, Samuel

2015-12-01

Many people living in low and middle-income countries are not covered by civil registration and vital statistics systems. Consequently, a wide variety of other types of data including many household sample surveys are used to estimate health and population indicators. In this paper we combine data from sample surveys and demographic surveillance systems to produce small area estimates of child mortality through time. Small area estimates are necessary to understand geographical heterogeneity in health indicators when full-coverage vital statistics are not available. For this endeavor spatio-temporal smoothing is beneficial to alleviate problems of data sparsity. The use of conventional hierarchical models requires careful thought since the survey weights may need to be considered to alleviate bias due to non-random sampling and non-response. The application that motivated this work is estimation of child mortality rates in five-year time intervals in regions of Tanzania. Data come from Demographic and Health Surveys conducted over the period 1991-2010 and two demographic surveillance system sites. We derive a variance estimator of under five years child mortality that accounts for the complex survey weighting. For our application, the hierarchical models we consider include random effects for area, time and survey and we compare models using a variety of measures including the conditional predictive ordinate (CPO). The method we propose is implemented via the fast and accurate integrated nested Laplace approximation (INLA).

Impact of spectral smoothing on gamma radiation portal alarm probabilities

International Nuclear Information System (INIS)

Burr, T.; Hamada, M.; Hengartner, N.

2011-01-01

Gamma detector counts are included in radiation portal monitors (RPM) to screen for illicit nuclear material. Gamma counts are sometimes smoothed to reduce variance in the estimated underlying true mean count rate, which is the 'signal' in our context. Smoothing reduces total error variance in the estimated signal if the bias that smoothing introduces is more than offset by the variance reduction. An empirical RPM study for vehicle screening applications is presented for unsmoothed and smoothed gamma counts in low-resolution plastic scintillator detectors and in medium-resolution NaI detectors. - Highlights: → We evaluate options for smoothing counts from gamma detectors deployed for portal monitoring. → A new multiplicative bias correction (MBC) is shown to reduce bias in peak and valley regions. → Performance is measured using mean squared error and detection probabilities for sources. → Smoothing with the MBC improves detection probabilities and the mean squared error.

Estimate of K-functionals and modulus of smoothness constructed ...

Indian Academy of Sciences (India)

2016-08-26

functional and a modulus of smoothness for the Dunkl transform on Rd. Author Affiliations. M El Hamma1 R Daher1. Department of Mathematics, Faculty of Sciences Aïn Chock, University of Hassan II, Casablanca, Morocco. Dates.

A spline-based non-linear diffeomorphism for multimodal prostate registration.

Science.gov (United States)

Mitra, Jhimli; Kato, Zoltan; Martí, Robert; Oliver, Arnau; Lladó, Xavier; Sidibé, Désiré; Ghose, Soumya; Vilanova, Joan C; Comet, Josep; Meriaudeau, Fabrice

2012-08-01

This paper presents a novel method for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape representations is used to find the point correspondences between the 2D fixed and moving images. The registration method involves parametric estimation of the non-linear diffeomorphism between the multimodal images and has its basis in solving a set of non-linear equations of thin-plate splines. The solution is obtained as the least-squares solution of an over-determined system of non-linear equations constructed by integrating a set of non-linear functions over the fixed and moving images. However, this may not result in clinically acceptable transformations of the anatomical targets. Therefore, the regularized bending energy of the thin-plate splines along with the localization error of established correspondences should be included in the system of equations. The registration accuracies of the proposed method are evaluated in 20 pairs of prostate mid-gland ultrasound and magnetic resonance images. The results obtained in terms of Dice similarity coefficient show an average of 0.980±0.004, average 95% Hausdorff distance of 1.63±0.48 mm and mean target registration and target localization errors of 1.60±1.17 mm and 0.15±0.12 mm respectively. Copyright © 2012 Elsevier B.V. All rights reserved.

B-Spline Approximations of the Gaussian, their Gabor Frame Properties, and Approximately Dual Frames

DEFF Research Database (Denmark)

Christensen, Ole; Kim, Hong Oh; Kim, Rae Young

2017-01-01

We prove that Gabor systems generated by certain scaled B-splines can be considered as perturbations of the Gabor systems generated by the Gaussian, with a deviation within an arbitrary small tolerance whenever the order N of the B-spline is sufficiently large. As a consequence we show that for a...

On developing B-spline registration algorithms for multi-core processors

International Nuclear Information System (INIS)

Shackleford, J A; Kandasamy, N; Sharp, G C

2010-01-01

Spline-based deformable registration methods are quite popular within the medical-imaging community due to their flexibility and robustness. However, they require a large amount of computing time to obtain adequate results. This paper makes two contributions towards accelerating B-spline-based registration. First, we propose a grid-alignment scheme and associated data structures that greatly reduce the complexity of the registration algorithm. Based on this grid-alignment scheme, we then develop highly data parallel designs for B-spline registration within the stream-processing model, suitable for implementation on multi-core processors such as graphics processing units (GPUs). Particular attention is focused on an optimal method for performing analytic gradient computations in a data parallel fashion. CPU and GPU versions are validated for execution time and registration quality. Performance results on large images show that our GPU algorithm achieves a speedup of 15 times over the single-threaded CPU implementation whereas our multi-core CPU algorithm achieves a speedup of 8 times over the single-threaded implementation. The CPU and GPU versions achieve near-identical registration quality in terms of RMS differences between the generated vector fields.

Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression

Science.gov (United States)

Ndiaye, Eugene; Fercoq, Olivier; Gramfort, Alexandre; Leclère, Vincent; Salmon, Joseph

2017-10-01

In high dimensional settings, sparse structures are crucial for efficiency, both in term of memory, computation and performance. It is customary to consider ℓ 1 penalty to enforce sparsity in such scenarios. Sparsity enforcing methods, the Lasso being a canonical example, are popular candidates to address high dimension. For efficiency, they rely on tuning a parameter trading data fitting versus sparsity. For the Lasso theory to hold this tuning parameter should be proportional to the noise level, yet the latter is often unknown in practice. A possible remedy is to jointly optimize over the regression parameter as well as over the noise level. This has been considered under several names in the literature: Scaled-Lasso, Square-root Lasso, Concomitant Lasso estimation for instance, and could be of interest for uncertainty quantification. In this work, after illustrating numerical difficulties for the Concomitant Lasso formulation, we propose a modification we coined Smoothed Concomitant Lasso, aimed at increasing numerical stability. We propose an efficient and accurate solver leading to a computational cost no more expensive than the one for the Lasso. We leverage on standard ingredients behind the success of fast Lasso solvers: a coordinate descent algorithm, combined with safe screening rules to achieve speed efficiency, by eliminating early irrelevant features.

Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates

Science.gov (United States)

Garcin, Matthieu

2017-10-01

Hurst exponents depict the long memory of a time series. For human-dependent phenomena, as in finance, this feature may vary in the time. It justifies modelling dynamics by multifractional Brownian motions, which are consistent with time-dependent Hurst exponents. We improve the existing literature on estimating time-dependent Hurst exponents by proposing a smooth estimate obtained by variational calculus. This method is very general and not restricted to the sole Hurst framework. It is globally more accurate and easier than other existing non-parametric estimation techniques. Besides, in the field of Hurst exponents, it makes it possible to make forecasts based on the estimated multifractional Brownian motion. The application to high-frequency foreign exchange markets (GBP, CHF, SEK, USD, CAD, AUD, JPY, CNY and SGD, all against EUR) shows significantly good forecasts. When the Hurst exponent is higher than 0.5, what depicts a long-memory feature, the accuracy is higher.

Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach

Science.gov (United States)

Michael S. Balshi; A. David McGuire; Paul Duffy; Mike Flannigan; John Walsh; Jerry Melillo

2009-01-01

We developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5o (latitude x longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was...

Usando splines cúbicas na modelagem matemática da evolução populacional de Pirapora/MG

Directory of Open Access Journals (Sweden)

José Sérgio Domingues

2014-08-01

, then, it is used as sample, years apart with step h of 10 years. The values initially dropped and population estimates for this city, described by Fundação João Pinheiro, served to validate the constructed model, and to estimate the percentage differences of prediction, which did not exceed 2.21%. Considering that the pattern of population evolution from 2000 to 2010 will remain until 2020, it is estimated the population of the city from 2011 to 2020, whose average percentage difference was only 0.49%. The conclusion is that the model fits well to the data, and population estimates in any year from 1970 to 2020 are trustfull. Beyond, the model allows practical visualization of an application of this technique in population modeling, and therefore, it can also be used for teaching purposes.Keywords: Cubic splines. Interpolation. Mathematical modeling. Population Evolution. Pirapora.

Implementation of exterior complex scaling in B-splines to solve atomic and molecular collision problems

International Nuclear Information System (INIS)

McCurdy, C William; MartIn, Fernando

2004-01-01

B-spline methods are now well established as widely applicable tools for the evaluation of atomic and molecular continuum states. The mathematical technique of exterior complex scaling has been shown, in a variety of other implementations, to be a powerful method with which to solve atomic and molecular scattering problems, because it allows the correct imposition of continuum boundary conditions without their explicit analytic application. In this paper, an implementation of exterior complex scaling in B-splines is described that can bring the well-developed technology of B-splines to bear on new problems, including multiple ionization and breakup problems, in a straightforward way. The approach is demonstrated for examples involving the continuum motion of nuclei in diatomic molecules as well as electronic continua. For problems involving electrons, a method based on Poisson's equation is presented for computing two-electron integrals over B-splines under exterior complex scaling

Thin-plate spline analysis of mandibular growth.

Science.gov (United States)

Franchi, L; Baccetti, T; McNamara, J A

2001-04-01

The analysis of mandibular growth changes around the pubertal spurt in humans has several important implications for the diagnosis and orthopedic correction of skeletal disharmonies. The purpose of this study was to evaluate mandibular shape and size growth changes around the pubertal spurt in a longitudinal sample of subjects with normal occlusion by means of an appropriate morphometric technique (thin-plate spline analysis). Ten mandibular landmarks were identified on lateral cephalograms of 29 subjects at 6 different developmental phases. The 6 phases corresponded to 6 different maturational stages in cervical vertebrae during accelerative and decelerative phases of the pubertal growth curve of the mandible. Differences in shape between average mandibular configurations at the 6 developmental stages were visualized by means of thin-plate spline analysis and subjected to permutation test. Centroid size was used as the measure of the geometric size of each mandibular specimen. Differences in size at the 6 developmental phases were tested statistically. The results of graphical analysis indicated a statistically significant change in mandibular shape only for the growth interval from stage 3 to stage 4 in cervical vertebral maturation. Significant increases in centroid size were found at all developmental phases, with evidence of a prepubertal minimum and of a pubertal maximum. The existence of a pubertal peak in human mandibular growth, therefore, is confirmed by thin-plate spline analysis. Significant morphological changes in the mandible during the growth interval from stage 3 to stage 4 in cervical vertebral maturation may be described as an upward-forward direction of condylar growth determining an overall "shrinkage" of the mandibular configuration along the measurement of total mandibular length. This biological mechanism is particularly efficient in compensating for major increments in mandibular size at the adolescent spurt.

Prostate multimodality image registration based on B-splines and quadrature local energy.

Science.gov (United States)

Mitra, Jhimli; Martí, Robert; Oliver, Arnau; Lladó, Xavier; Ghose, Soumya; Vilanova, Joan C; Meriaudeau, Fabrice

2012-05-01

Needle biopsy of the prostate is guided by Transrectal Ultrasound (TRUS) imaging. The TRUS images do not provide proper spatial localization of malignant tissues due to the poor sensitivity of TRUS to visualize early malignancy. Magnetic Resonance Imaging (MRI) has been shown to be sensitive for the detection of early stage malignancy, and therefore, a novel 2D deformable registration method that overlays pre-biopsy MRI onto TRUS images has been proposed. The registration method involves B-spline deformations with Normalized Mutual Information (NMI) as the similarity measure computed from the texture images obtained from the amplitude responses of the directional quadrature filter pairs. Registration accuracy of the proposed method is evaluated by computing the Dice Similarity coefficient (DSC) and 95% Hausdorff Distance (HD) values for 20 patients prostate mid-gland slices and Target Registration Error (TRE) for 18 patients only where homologous structures are visible in both the TRUS and transformed MR images. The proposed method and B-splines using NMI computed from intensities provide average TRE values of 2.64 ± 1.37 and 4.43 ± 2.77 mm respectively. Our method shows statistically significant improvement in TRE when compared with B-spline using NMI computed from intensities with Student's t test p = 0.02. The proposed method shows 1.18 times improvement over thin-plate splines registration with average TRE of 3.11 ± 2.18 mm. The mean DSC and the mean 95% HD values obtained with the proposed method of B-spline with NMI computed from texture are 0.943 ± 0.039 and 4.75 ± 2.40 mm respectively. The texture energy computed from the quadrature filter pairs provides better registration accuracy for multimodal images than raw intensities. Low TRE values of the proposed registration method add to the feasibility of it being used during TRUS-guided biopsy.

A chord error conforming tool path B-spline fitting method for NC machining based on energy minimization and LSPIA

OpenAIRE

He, Shanshan; Ou, Daojiang; Yan, Changya; Lee, Chen-Han

2015-01-01

Piecewise linear (G01-based) tool paths generated by CAM systems lack G1 and G2 continuity. The discontinuity causes vibration and unnecessary hesitation during machining. To ensure efficient high-speed machining, a method to improve the continuity of the tool paths is required, such as B-spline fitting that approximates G01 paths with B-spline curves. Conventional B-spline fitting approaches cannot be directly used for tool path B-spline fitting, because they have shortages such as numerical...

Nonlinear time series theory, methods and applications with R examples

CERN Document Server

Douc, Randal; Stoffer, David

2014-01-01

FOUNDATIONSLinear ModelsStochastic Processes The Covariance World Linear Processes The Multivariate Cases Numerical Examples ExercisesLinear Gaussian State Space Models Model Basics Filtering, Smoothing, and Forecasting Maximum Likelihood Estimation Smoothing Splines and the Kalman Smoother Asymptotic Distribution of the MLE Missing Data Modifications Structural Component Models State-Space Models with Correlated Errors Exercises Beyond Linear ModelsNonlinear Non-Gaussian Data Volterra Series Expansion Cumulants and Higher-Order Spectra Bilinear Models Conditionally Heteroscedastic Models Thre

Spline Approximation-Based Optimization of Multi-component Disperse Reinforced Composites

Directory of Open Access Journals (Sweden)

Yu. I. Dimitrienko

2015-01-01

Full Text Available The paper suggests an algorithm for solving the problems of optimal design of multicomponent disperse-reinforced composite materials, which properties are defined by filler concentrations and are independent of their shape. It formulates the problem of conditional optimization of a composite with restrictions on its effective parameters - the elasticity modulus, tension and compression strengths, and heat-conductivity coefficient with minimized composite density. The effective characteristics of a composite were computed by finite-element solving the auxiliary local problems of elasticity and heat-conductivity theories appearing when the asymptotic averaging method is applied.The algorithm suggested to solve the optimization problem includes the following main stages:1 finding a set of solutions for direct problem to calculate the effective characteristics;2 constructing the curves of effective characteristics versus filler concentrations by means of approximating functions, which are offered for use as a thin plate spline with smoothing;3 constructing a set of points to satisfy restrictions and a boundary of the point set to satisfy restrictions obtaining, as a result, a contour which can be parameterized;4 defining a global density minimum over the contour through psi-transformation.A numerical example of solving the optimization problem was given for a dispersereinforced composite with two types of fillers being hollow microspheres: glass and phenolic. It was shown that the suggested algorithm allows us to find optimal filler concentrations efficiently enough.

A Piecewise Acceleration-Optimal and Smooth-Jerk Trajectory Planning Method for Robot Manipulator along a Predefined Path

Directory of Open Access Journals (Sweden)

Yuan Chen

2011-09-01

Full Text Available This paper proposes a piecewise acceleration-optimal and smooth-jerk trajectory planning method of robot manipulator. The optimal objective function is given by the weighted sum of two terms having opposite effects: the maximal acceleration and the minimal jerk. Some computing techniques are proposed to determine the optimal solution. These techniques take both the time intervals between two interpolation points and the control points of B-spline function as optimal variables, redefine the kinematic constraints as the constraints of optimal variables, and reformulate the objective function in matrix form. The feasibility of the optimal method is illustrated by simulation and experimental results with pan mechanism for cooking robot.

Quantification of smoothing requirement for 3D optic flow calculation of volumetric images

DEFF Research Database (Denmark)

Bab-Hadiashar, Alireza; Tennakoon, Ruwan B.; de Bruijne, Marleen

2013-01-01

Complexities of dynamic volumetric imaging challenge the available computer vision techniques on a number of different fronts. This paper examines the relationship between the estimation accuracy and required amount of smoothness for a general solution from a robust statistics perspective. We show...... that a (surprisingly) small amount of local smoothing is required to satisfy both the necessary and sufficient conditions for accurate optic flow estimation. This notion is called 'just enough' smoothing, and its proper implementation has a profound effect on the preservation of local information in processing 3D...... dynamic scans. To demonstrate the effect of 'just enough' smoothing, a robust 3D optic flow method with quantized local smoothing is presented, and the effect of local smoothing on the accuracy of motion estimation in dynamic lung CT images is examined using both synthetic and real image sequences...

Median regression spline modeling of longitudinal FEV1 measurements in cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) patients.

Science.gov (United States)

Conrad, Douglas J; Bailey, Barbara A; Hardie, Jon A; Bakke, Per S; Eagan, Tomas M L; Aarli, Bernt B

2017-01-01

Clinical phenotyping, therapeutic investigations as well as genomic, airway secretion metabolomic and metagenomic investigations can benefit from robust, nonlinear modeling of FEV1 in individual subjects. We demonstrate the utility of measuring FEV1 dynamics in representative cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) populations. Individual FEV1 data from CF and COPD subjects were modeled by estimating median regression splines and their predicted first and second derivatives. Classes were created from variables that capture the dynamics of these curves in both cohorts. Nine FEV1 dynamic variables were identified from the splines and their predicted derivatives in individuals with CF (n = 177) and COPD (n = 374). Three FEV1 dynamic classes (i.e. stable, intermediate and hypervariable) were generated and described using these variables from both cohorts. In the CF cohort, the FEV1 hypervariable class (HV) was associated with a clinically unstable, female-dominated phenotypes while stable FEV1 class (S) individuals were highly associated with the male-dominated milder clinical phenotype. In the COPD cohort, associations were found between the FEV1 dynamic classes, the COPD GOLD grades, with exacerbation frequency and symptoms. Nonlinear modeling of FEV1 with splines provides new insights and is useful in characterizing CF and COPD clinical phenotypes.

A Well-Designed Parameter Estimation Method for Lifetime Prediction of Deteriorating Systems with Both Smooth Degradation and Abrupt Damage

Directory of Open Access Journals (Sweden)

Chuanqiang Yu

2015-01-01

Full Text Available Deteriorating systems, which are subject to both continuous smooth degradation and additional abrupt damages due to a shock process, can be often encountered in engineering. Modeling the degradation evolution and predicting the lifetime of this kind of systems are both interesting and challenging in practice. In this paper, we model the degradation trajectory of the deteriorating system by a random coefficient regression (RCR model with positive jumps, where the RCR part is used to model the continuous smooth degradation of the system and the jump part is used to characterize the abrupt damages due to random shocks. Based on a specified threshold level, the probability density function (PDF and cumulative distribution function (CDF of the lifetime can be derived analytically. The unknown parameters associated with the derived lifetime distributions can be estimated via a well-designed parameter estimation procedure on the basis of the available degradation recordings of the deteriorating systems. An illustrative example is finally provided to demonstrate the implementation and superiority of the newly proposed lifetime prediction method. The experimental results reveal that our proposed lifetime prediction method with the dedicated parameter estimation strategy can get more accurate lifetime predictions than the rival model in literature.

Spline methods for conversation equations

International Nuclear Information System (INIS)

Bottcher, C.; Strayer, M.R.

1991-01-01

The consider the numerical solution of physical theories, in particular hydrodynamics, which can be formulated as systems of conservation laws. To this end we briefly describe the Basis Spline and collocation methods, paying particular attention to representation theory, which provides discrete analogues of the continuum conservation and dispersion relations, and hence a rigorous understanding of errors and instabilities. On this foundation we propose an algorithm for hydrodynamic problems in which most linear and nonlinear instabilities are brought under control. Numerical examples are presented from one-dimensional relativistic hydrodynamics. 9 refs., 10 figs

A User Guide for Smoothing Air Traffic Radar Data

Science.gov (United States)

Bach, Ralph E.; Paielli, Russell A.

2014-01-01

Matlab software was written to provide smoothing of radar tracking data to simulate ADS-B (Automatic Dependent Surveillance-Broadcast) data in order to test a tactical conflict probe. The probe, called TSAFE (Tactical Separation-Assured Flight Environment), is designed to handle air-traffic conflicts left undetected or unresolved when loss-of-separation is predicted to occur within approximately two minutes. The data stream that is down-linked from an aircraft equipped with an ADS-B system would include accurate GPS-derived position and velocity information at sample rates of 1 Hz. Nation-wide ADS-B equipage (mandated by 2020) should improve surveillance accuracy and TSAFE performance. Currently, position data are provided by Center radar (nominal 12-sec samples) and Terminal radar (nominal 4.8-sec samples). Aircraft ground speed and ground track are estimated using real-time filtering, causing lags up to 60 sec, compromising performance of a tactical resolution tool. Offline smoothing of radar data reduces wild-point errors, provides a sample rate as high as 1 Hz, and yields more accurate and lag-free estimates of ground speed, ground track, and climb rate. Until full ADS-B implementation is available, smoothed radar data should provide reasonable track estimates for testing TSAFE in an ADS-B-like environment. An example illustrates the smoothing of radar data and shows a comparison of smoothed-radar and ADS-B tracking. This document is intended to serve as a guide for using the smoothing software.

PySpline: A Modern, Cross-Platform Program for the Processing of Raw Averaged XAS Edge and EXAFS Data

International Nuclear Information System (INIS)

Tenderholt, Adam; Hedman, Britt; Hodgson, Keith O.

2007-01-01

PySpline is a modern computer program for processing raw averaged XAS and EXAFS data using an intuitive approach which allows the user to see the immediate effect of various processing parameters on the resulting k- and R-space data. The Python scripting language and Qt and Qwt widget libraries were chosen to meet the design requirement that it be cross-platform (i.e. versions for Windows, Mac OS X, and Linux). PySpline supports polynomial pre- and post-edge background subtraction, splining of the EXAFS region with a multi-segment polynomial spline, and Fast Fourier Transform (FFT) of the resulting k3-weighted EXAFS data

Parametric inference for stochastic differential equations: a smooth and match approach

NARCIS (Netherlands)

Gugushvili, S.; Spreij, P.

2012-01-01

We study the problem of parameter estimation for a univariate discretely observed ergodic diffusion process given as a solution to a stochastic differential equation. The estimation procedure we propose consists of two steps. In the first step, which is referred to as a smoothing step, we smooth the

Carrier tracking by smoothing filter can improve symbol SNR

Science.gov (United States)

Hurd, W. J.; Pomalaza-Raez, C. A.

1985-01-01

The potential benefit of using a smoothing filter to estimate carrier phase over use of phase locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of the deep space network advanced receiver. These are residual carrier PLL, sideband aided residual carrier PLL, and finally sideband aiding with a Kalman smoother. The average symbol signal to noise ratio (CNR) after losses due to carrier phase estimation error is computed for different total power SNRs, symbol rates and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.4 dB over a sideband aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to a residual carrier loop is often in excess of 1 dB.

C2-rational cubic spline involving tension parameters

Indian Academy of Sciences (India)

preferred which preserves some of the characteristics of the function to be interpolated. In order to tackle such ... Shape preserving properties of the rational (cubic/quadratic) spline interpolant have been studied ... tension parameters which is used to interpolate the given monotonic data is described in. [6]. Shape preserving ...

Intensity-based hierarchical elastic registration using approximating splines.

Science.gov (United States)

Serifovic-Trbalic, Amira; Demirovic, Damir; Cattin, Philippe C

2014-01-01

We introduce a new hierarchical approach for elastic medical image registration using approximating splines. In order to obtain the dense deformation field, we employ Gaussian elastic body splines (GEBS) that incorporate anisotropic landmark errors and rotation information. Since the GEBS approach is based on a physical model in form of analytical solutions of the Navier equation, it can very well cope with the local as well as global deformations present in the images by varying the standard deviation of the Gaussian forces. The proposed GEBS approximating model is integrated into the elastic hierarchical image registration framework, which decomposes a nonrigid registration problem into numerous local rigid transformations. The approximating GEBS registration scheme incorporates anisotropic landmark errors as well as rotation information. The anisotropic landmark localization uncertainties can be estimated directly from the image data, and in this case, they represent the minimal stochastic localization error, i.e., the Cramér-Rao bound. The rotation information of each landmark obtained from the hierarchical procedure is transposed in an additional angular landmark, doubling the number of landmarks in the GEBS model. The modified hierarchical registration using the approximating GEBS model is applied to register 161 image pairs from a digital mammogram database. The obtained results are very encouraging, and the proposed approach significantly improved all registrations comparing the mean-square error in relation to approximating TPS with the rotation information. On artificially deformed breast images, the newly proposed method performed better than the state-of-the-art registration algorithm introduced by Rueckert et al. (IEEE Trans Med Imaging 18:712-721, 1999). The average error per breast tissue pixel was less than 2.23 pixels compared to 2.46 pixels for Rueckert's method. The proposed hierarchical elastic image registration approach incorporates the GEBS

An enhanced computational method for age-at-death estimation based on the pubic symphysis using 3D laser scans and thin plate splines.

Science.gov (United States)

Stoyanova, Detelina; Algee-Hewitt, Bridget F B; Slice, Dennis E

2015-11-01

The pubic symphysis is frequently used to estimate age-at-death from the adult skeleton. Assessment methods require the visual comparison of the bone morphology against age-informative characteristics that represent a series of phases. Age-at-death is then estimated from the age-range previously associated with the chosen phase. While easily executed, the "morphoscopic" process of feature-scoring and bone-to-phase-matching is known to be subjective. Studies of method and practitioner error demonstrate a need for alternative tools to quantify age-progressive change in the pubic symphysis. This article proposes a more objective, quantitative method that analyzes three-dimensional (3D) surface scans of the pubic symphysis using a thin plate spline algorithm (TPS). This algorithm models the bending of a flat plane to approximately match the surface of the bone and minimizes the bending energy required for this transformation. Known age-at-death and bending energy were used to construct a linear model to predict age from observed bending energy. This approach is tested with scans from 44 documented white male skeletons and 12 casts. The results of the surface analysis show a significant association (regression p-value = 0.0002 and coefficient of determination = 0.2270) between the minimum bending energy and age-at-death, with a root mean square error of ≈19 years. This TPS method yields estimates comparable to established methods but offers a fully integrated, objective and quantitative framework of analysis and has potential for use in archaeological and forensic casework. © 2015 Wiley Periodicals, Inc.

Quantum key distribution with finite resources: Smooth Min entropy vs. Smooth Renyi entropy

Energy Technology Data Exchange (ETDEWEB)

Mertz, Markus; Abruzzo, Silvestre; Bratzik, Sylvia; Kampermann, Hermann; Bruss, Dagmar [Institut fuer Theoretische Physik III, Duesseldorf (Germany)

2010-07-01

We consider different entropy measures that play an important role in the analysis of the security of QKD with finite resources. The smooth min entropy leads to an optimal bound for the length of a secure key. Another bound on the secure key length was derived by using Renyi entropies. Unfortunately, it is very hard or even impossible to calculate these entropies for realistic QKD scenarios. To estimate the security rate it becomes important to find computable bounds on these entropies. Here, we compare a lower bound for the smooth min entropy with a bound using Renyi entropies. We compare these entropies for the six-state protocol with symmetric attacks.

Spline function fit for multi-sets of correlative data

International Nuclear Information System (INIS)

Liu Tingjin; Zhou Hongmo

1992-01-01

The Spline fit method for multi-sets of correlative data is developed. The properties of correlative data fit are investigated. The data of 23 Na(n, 2n) cross section are fitted in the cases with and without correlation

A fractional spline collocation-Galerkin method for the time-fractional diffusion equation

Directory of Open Access Journals (Sweden)

Pezza L.

2018-03-01

Full Text Available The aim of this paper is to numerically solve a diffusion differential problem having time derivative of fractional order. To this end we propose a collocation-Galerkin method that uses the fractional splines as approximating functions. The main advantage is in that the derivatives of integer and fractional order of the fractional splines can be expressed in a closed form that involves just the generalized finite difference operator. This allows us to construct an accurate and efficient numerical method. Several numerical tests showing the effectiveness of the proposed method are presented.

Preconditioning cubic spline collocation method by FEM and FDM for elliptic equations

Energy Technology Data Exchange (ETDEWEB)

Kim, Sang Dong [KyungPook National Univ., Taegu (Korea, Republic of)

1996-12-31

In this talk we discuss the finite element and finite difference technique for the cubic spline collocation method. For this purpose, we consider the uniformly elliptic operator A defined by Au := -{Delta}u + a{sub 1}u{sub x} + a{sub 2}u{sub y} + a{sub 0}u in {Omega} (the unit square) with Dirichlet or Neumann boundary conditions and its discretization based on Hermite cubic spline spaces and collocation at the Gauss points. Using an interpolatory basis with support on the Gauss points one obtains the matrix A{sub N} (h = 1/N).

Validation of CMIP5 multimodel ensembles through the smoothness of climate variables

KAUST Repository

Lee, Myoungji

2015-05-14

Smoothness is an important characteristic of a spatial process that measures local variability. If climate model outputs are realistic, then not only the values at each grid pixel but also the relative variation over nearby pixels should represent the true climate. We estimate the smoothness of long-term averages for land surface temperature anomalies in the Coupled Model Intercomparison Project Phase 5 (CMIP5), and compare them by climate regions and seasons. We also compare the estimated smoothness of the climate outputs in CMIP5 with those of reanalysis data. The estimation is done through the composite likelihood approach for locally self-similar processes. The composite likelihood that we consider is a product of conditional likelihoods of neighbouring observations. We find that the smoothness of the surface temperature anomalies in CMIP5 depends primarily on the modelling institution and on the climate region. The seasonal difference in the smoothness is generally small, except for some climate regions where the average temperature is extremely high or low.

The basis spline method and associated techniques

International Nuclear Information System (INIS)

Bottcher, C.; Strayer, M.R.

1989-01-01

We outline the Basis Spline and Collocation methods for the solution of Partial Differential Equations. Particular attention is paid to the theory of errors, and the handling of non-self-adjoint problems which are generated by the collocation method. We discuss applications to Poisson's equation, the Dirac equation, and the calculation of bound and continuum states of atomic and nuclear systems. 12 refs., 6 figs

Estimate of K-functionals and modulus of smoothness constructed ...

Indian Academy of Sciences (India)

... and -functionals. The main result of the paper is the proof of the equivalence theorem for a -functional and a modulus of smoothness for the Dunkl transform on R d . Author Affiliations. M El Hamma1 R Daher1. Department of Mathematics, Faculty of Sciences Aïn Chock, University of Hassan II, Casablanca, Morocco ...

Estimate of K-functionals and modulus of smoothness constructed ...

Indian Academy of Sciences (India)

Casablanca, Morocco. E-mail: m_elhamma@yahoo.fr. MS received 17 January 2013. Abstract. Using a generalized spherical mean operator, we define generalized modu- lus of smoothness in the space L2 k. (Rd). Based on the Dunkl operator we define. Sobolev-type space and K-functionals. The main result of the paper ...

Comparative Performance of Complex-Valued B-Spline and Polynomial Models Applied to Iterative Frequency-Domain Decision Feedback Equalization of Hammerstein Channels.

Science.gov (United States)

Chen, Sheng; Hong, Xia; Khalaf, Emad F; Alsaadi, Fuad E; Harris, Chris J

2017-12-01

Complex-valued (CV) B-spline neural network approach offers a highly effective means for identifying and inverting practical Hammerstein systems. Compared with its conventional CV polynomial-based counterpart, a CV B-spline neural network has superior performance in identifying and inverting CV Hammerstein systems, while imposing a similar complexity. This paper reviews the optimality of the CV B-spline neural network approach. Advantages of B-spline neural network approach as compared with the polynomial based modeling approach are extensively discussed, and the effectiveness of the CV neural network-based approach is demonstrated in a real-world application. More specifically, we evaluate the comparative performance of the CV B-spline and polynomial-based approaches for the nonlinear iterative frequency-domain decision feedback equalization (NIFDDFE) of single-carrier Hammerstein channels. Our results confirm the superior performance of the CV B-spline-based NIFDDFE over its CV polynomial-based counterpart.

Spline-based high-accuracy piecewise-polynomial phase-to-sinusoid amplitude converters.

Science.gov (United States)

Petrinović, Davor; Brezović, Marko

2011-04-01

We propose a method for direct digital frequency synthesis (DDS) using a cubic spline piecewise-polynomial model for a phase-to-sinusoid amplitude converter (PSAC). This method offers maximum smoothness of the output signal. Closed-form expressions for the cubic polynomial coefficients are derived in the spectral domain and the performance analysis of the model is given in the time and frequency domains. We derive the closed-form performance bounds of such DDS using conventional metrics: rms and maximum absolute errors (MAE) and maximum spurious free dynamic range (SFDR) measured in the discrete time domain. The main advantages of the proposed PSAC are its simplicity, analytical tractability, and inherent numerical stability for high table resolutions. Detailed guidelines for a fixed-point implementation are given, based on the algebraic analysis of all quantization effects. The results are verified on 81 PSAC configurations with the output resolutions from 5 to 41 bits by using a bit-exact simulation. The VHDL implementation of a high-accuracy DDS based on the proposed PSAC with 28-bit input phase word and 32-bit output value achieves SFDR of its digital output signal between 180 and 207 dB, with a signal-to-noise ratio of 192 dB. Its implementation requires only one 18 kB block RAM and three 18-bit embedded multipliers in a typical field-programmable gate array (FPGA) device. © 2011 IEEE

A theoretical formulation of the electrophysiological inverse problem on the sphere.

Science.gov (United States)

Riera, Jorge J; Valdés, Pedro A; Tanabe, Kunio; Kawashima, Ryuta

2006-04-07

The construction of three-dimensional images of the primary current density (PCD) produced by neuronal activity is a problem of great current interest in the neuroimaging community, though being initially formulated in the 1970s. There exist even now enthusiastic debates about the authenticity of most of the inverse solutions proposed in the literature, in which low resolution electrical tomography (LORETA) is a focus of attention. However, in our opinion, the capabilities and limitations of the electro and magneto encephalographic techniques to determine PCD configurations have not been extensively explored from a theoretical framework, even for simple volume conductor models of the head. In this paper, the electrophysiological inverse problem for the spherical head model is cast in terms of reproducing kernel Hilbert spaces (RKHS) formalism, which allows us to identify the null spaces of the implicated linear integral operators and also to define their representers. The PCD are described in terms of a continuous basis for the RKHS, which explicitly separates the harmonic and non-harmonic components. The RKHS concept permits us to bring LORETA into the scope of the general smoothing splines theory. A particular way of calculating the general smoothing splines is illustrated, avoiding a brute force discretization prematurely. The Bayes information criterion is used to handle dissimilarities in the signal/noise ratios and physical dimensions of the measurement modalities, which could affect the estimation of the amount of smoothness required for that class of inverse solution to be well specified. In order to validate the proposed method, we have estimated the 3D spherical smoothing splines from two data sets: electric potentials obtained from a skull phantom and magnetic fields recorded from subjects performing an experiment of human faces recognition.

Enhanced spatio-temporal alignment of plantar pressure image sequences using B-splines.

Science.gov (United States)

Oliveira, Francisco P M; Tavares, João Manuel R S

2013-03-01

This article presents an enhanced methodology to align plantar pressure image sequences simultaneously in time and space. The temporal alignment of the sequences is accomplished using B-splines in the time modeling, and the spatial alignment can be attained using several geometric transformation models. The methodology was tested on a dataset of 156 real plantar pressure image sequences (3 sequences for each foot of the 26 subjects) that was acquired using a common commercial plate during barefoot walking. In the alignment of image sequences that were synthetically deformed both in time and space, an outstanding accuracy was achieved with the cubic B-splines. This accuracy was significantly better (p align real image sequences with unknown transformation involved, the alignment based on cubic B-splines also achieved superior results than our previous methodology (p alignment on the dynamic center of pressure (COP) displacement was also assessed by computing the intraclass correlation coefficients (ICC) before and after the temporal alignment of the three image sequence trials of each foot of the associated subject at six time instants. The results showed that, generally, the ICCs related to the medio-lateral COP displacement were greater when the sequences were temporally aligned than the ICCs of the original sequences. Based on the experimental findings, one can conclude that the cubic B-splines are a remarkable solution for the temporal alignment of plantar pressure image sequences. These findings also show that the temporal alignment can increase the consistency of the COP displacement on related acquired plantar pressure image sequences.

B-spline tight frame based force matching method

Science.gov (United States)

Yang, Jianbin; Zhu, Guanhua; Tong, Dudu; Lu, Lanyuan; Shen, Zuowei

2018-06-01

In molecular dynamics simulations, compared with popular all-atom force field approaches, coarse-grained (CG) methods are frequently used for the rapid investigations of long time- and length-scale processes in many important biological and soft matter studies. The typical task in coarse-graining is to derive interaction force functions between different CG site types in terms of their distance, bond angle or dihedral angle. In this paper, an ℓ1-regularized least squares model is applied to form the force functions, which makes additional use of the B-spline wavelet frame transform in order to preserve the important features of force functions. The B-spline tight frames system has a simple explicit expression which is useful for representing our force functions. Moreover, the redundancy of the system offers more resilience to the effects of noise and is useful in the case of lossy data. Numerical results for molecular systems involving pairwise non-bonded, three and four-body bonded interactions are obtained to demonstrate the effectiveness of our approach.

Choosing the Optimal Number of B-spline Control Points (Part 1: Methodology and Approximation of Curves)

Science.gov (United States)

Harmening, Corinna; Neuner, Hans

2016-09-01

Due to the establishment of terrestrial laser scanner, the analysis strategies in engineering geodesy change from pointwise approaches to areal ones. These areal analysis strategies are commonly built on the modelling of the acquired point clouds. Freeform curves and surfaces like B-spline curves/surfaces are one possible approach to obtain space continuous information. A variety of parameters determines the B-spline's appearance; the B-spline's complexity is mostly determined by the number of control points. Usually, this number of control points is chosen quite arbitrarily by intuitive trial-and-error-procedures. In this paper, the Akaike Information Criterion and the Bayesian Information Criterion are investigated with regard to a justified and reproducible choice of the optimal number of control points of B-spline curves. Additionally, we develop a method which is based on the structural risk minimization of the statistical learning theory. Unlike the Akaike and the Bayesian Information Criteria this method doesn't use the number of parameters as complexity measure of the approximating functions but their Vapnik-Chervonenkis-dimension. Furthermore, it is also valid for non-linear models. Thus, the three methods differ in their target function to be minimized and consequently in their definition of optimality. The present paper will be continued by a second paper dealing with the choice of the optimal number of control points of B-spline surfaces.

PM10 modeling in the Oviedo urban area (Northern Spain) by using multivariate adaptive regression splines

Science.gov (United States)

Nieto, Paulino José García; Antón, Juan Carlos Álvarez; Vilán, José Antonio Vilán; García-Gonzalo, Esperanza

2014-10-01

The aim of this research work is to build a regression model of the particulate matter up to 10 micrometers in size (PM10) by using the multivariate adaptive regression splines (MARS) technique in the Oviedo urban area (Northern Spain) at local scale. This research work explores the use of a nonparametric regression algorithm known as multivariate adaptive regression splines (MARS) which has the ability to approximate the relationship between the inputs and outputs, and express the relationship mathematically. In this sense, hazardous air pollutants or toxic air contaminants refer to any substance that may cause or contribute to an increase in mortality or serious illness, or that may pose a present or potential hazard to human health. To accomplish the objective of this study, the experimental dataset of nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3) and dust (PM10) were collected over 3 years (2006-2008) and they are used to create a highly nonlinear model of the PM10 in the Oviedo urban nucleus (Northern Spain) based on the MARS technique. One main objective of this model is to obtain a preliminary estimate of the dependence between PM10 pollutant in the Oviedo urban area at local scale. A second aim is to determine the factors with the greatest bearing on air quality with a view to proposing health and lifestyle improvements. The United States National Ambient Air Quality Standards (NAAQS) establishes the limit values of the main pollutants in the atmosphere in order to ensure the health of healthy people. Firstly, this MARS regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the main pollutants in the Oviedo urban area. Secondly, the main advantages of MARS are its capacity to produce simple, easy-to-interpret models, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, on the basis of

Splines under tension for gridding three-dimensional data

International Nuclear Information System (INIS)

Brand, H.R.; Frazer, J.W.

1982-01-01

By use of the splines-under-tension concept, a simple algorithm has been developed for the three-dimensional representation of nonuniformly spaced data. The representations provide useful information to the experimentalist when he is attempting to understand the results obtained in a self-adaptive experiment. The shortcomings of the algorithm are discussed as well as the advantages

Effects of early activator treatment in patients with class II malocclusion evaluated by thin-plate spline analysis.

Science.gov (United States)

Lux, C J; Rübel, J; Starke, J; Conradt, C; Stellzig, P A; Komposch, P G

2001-04-01

The aim of the present longitudinal cephalometric study was to evaluate the dentofacial shape changes induced by activator treatment between 9.5 and 11.5 years in male Class II patients. For a rigorous morphometric analysis, a thin-plate spline analysis was performed to assess and visualize dental and skeletal craniofacial changes. Twenty male patients with a skeletal Class II malrelationship and increased overjet who had been treated at the University of Heidelberg with a modified Andresen-Häupl-type activator were compared with a control group of 15 untreated male subjects of the Belfast Growth Study. The shape changes for each group were visualized on thin-plate splines with one spline comprising all 13 landmarks to show all the craniofacial shape changes, including skeletal and dento-alveolar reactions, and a second spline based on 7 landmarks to visualize only the skeletal changes. In the activator group, the grid deformation of the total spline pointed to a strong activator-induced reduction of the overjet that was caused both by a tipping of the incisors and by a moderation of sagittal discrepancies, particularly a slight advancement of the mandible. In contrast with this, in the control group, only slight localized shape changes could be detected. Both in the 7- and 13-landmark configurations, the shape changes between the groups differed significantly at P thin-plate spline analysis turned out to be a useful morphometric supplement to conventional cephalometrics because the complex patterns of shape change could be suggestively visualized.

SPLINE-FUNCTIONS IN THE TASK OF THE FLOW AIRFOIL PROFILE

Directory of Open Access Journals (Sweden)

Mikhail Lopatjuk

2013-12-01

Full Text Available The method and the algorithm of solving the problem of streamlining are presented. Neumann boundary problem is reduced to the solution of integral equations with given boundary conditions using the cubic spline-functions

Covariances of smoothed observational data

Czech Academy of Sciences Publication Activity Database

Vondrák, Jan; Čepek, A.

2000-01-01

Roč. 40, 5-6 (2000), s. 42-44 ISSN 1210-2709 R&D Projects: GA ČR GA205/98/1104 Institutional research plan: CEZ:AV0Z1003909 Keywords : digital filter * smoothing * estimation of uncertainties Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics

Quintic hyperbolic nonpolynomial spline and finite difference method for nonlinear second order differential equations and its application

Directory of Open Access Journals (Sweden)

Navnit Jha

2014-04-01

Full Text Available An efficient numerical method based on quintic nonpolynomial spline basis and high order finite difference approximations has been presented. The scheme deals with the space containing hyperbolic and polynomial functions as spline basis. With the help of spline functions we derive consistency conditions and high order discretizations of the differential equation with the significant first order derivative. The error analysis of the new method is discussed briefly. The new method is analyzed for its efficiency using the physical problems. The order and accuracy of the proposed method have been analyzed in terms of maximum errors and root mean square errors.

T-Spline Based Unifying Registration Procedure for Free-Form Surface Workpieces in Intelligent CMM

Directory of Open Access Journals (Sweden)

Zhenhua Han

2017-10-01

Full Text Available With the development of the modern manufacturing industry, the free-form surface is widely used in various fields, and the automatic detection of a free-form surface is an important function of future intelligent three-coordinate measuring machines (CMMs. To improve the intelligence of CMMs, a new visual system is designed based on the characteristics of CMMs. A unified model of the free-form surface is proposed based on T-splines. A discretization method of the T-spline surface formula model is proposed. Under this discretization, the position and orientation of the workpiece would be recognized by point cloud registration. A high accuracy evaluation method is proposed between the measured point cloud and the T-spline surface formula. The experimental results demonstrate that the proposed method has the potential to realize the automatic detection of different free-form surfaces and improve the intelligence of CMMs.

Application of multivariate splines to discrete mathematics

OpenAIRE

Xu, Zhiqiang

2005-01-01

Using methods developed in multivariate splines, we present an explicit formula for discrete truncated powers, which are defined as the number of non-negative integer solutions of linear Diophantine equations. We further use the formula to study some classical problems in discrete mathematics as follows. First, we extend the partition function of integers in number theory. Second, we exploit the relation between the relative volume of convex polytopes and multivariate truncated powers and giv...

Using LMS Method in Smoothing Reference Centile Curves for Lipid Profile of Iranian Children and Adolescents: A CASPIAN Study

Directory of Open Access Journals (Sweden)

M Hoseini

2012-05-01

Full Text Available

Background and Objectives: LMS is a general monitoring method for fitting smooth reference centile curves in medical sciences. They provide the distribution of a measurement as it changes according to some covariates like age or time. This method describes the distribution of changes by three parameters; Mean, Coefficient of variation and Cox-Box power (skewness. Applying maximum penalized likelihood and spline function, the three curves are estimated and fitted and optimum smoothness is expressed by three curves. This study was conducted to provide the percentiles of lipid profile of Iranian children and adolescents by LMS.

Methods: Smoothed reference centile curves of four groups of lipids (triglycerides, total-LDL- and HDL-cholesterol were developed from the data of 4824 Iranian school students, aged 6-18 years, living in six cities (Tabriz, Rasht, Gorgan, Mashad, Yazd and Tehran-Firouzkouh in Iran. Demographic and laboratory data were taken from the national study of the surveillance and prevention of non-communicable diseases from childhood (CASPIAN Study. After data management, data of 4824 students were included in the statistical analysis, which was conducted by the modified LMS method proposed by Cole. The curves were developed with a degree of freedom of four to ten with some tools such as deviance, Q tests, and detrended Q-Q plot were used for monitoring goodness of fit models.

Results: All tools confirmed the model, and the LMS method was used as an appropriate method in smoothing reference centile. This method revealed the distributing features of variables serving as an objective tool to determine their relative importance.

Conclusion: This study showed that the triglycerides level is higher and

Study on signal processing in Eddy current testing for defects in spline gear

International Nuclear Information System (INIS)

Lee, Jae Ho; Park, Tae Sug; Park, Ik Keun

2016-01-01

Eddy current testing (ECT) is commonly applied for the inspection of automated production lines of metallic products, because it has a high inspection speed and a reasonable price. When ECT is applied for the inspection of a metallic object having an uneven target surface, such as the spline gear of a spline shaft, it is difficult to distinguish between the original signal obtained from the sensor and the signal generated by a defect because of the relatively large surface signals having similar frequency distributions. To facilitate the detection of defect signals from the spline gear, implementation of high-order filters is essential, so that the fault signals can be distinguished from the surrounding noise signals, and simultaneously, the pass-band of the filter can be adjusted according to the status of each production line and the object to be inspected. We will examine the infinite impulse filters (IIR filters) available for implementing an advanced filter for ECT, and attempt to detect the flaw signals through optimization of system design parameters for detecting the signals at the system level

Performance evaluation of block-diagonal preconditioners for the divergence-conforming B-spline discretization of the Stokes system

KAUST Repository

Cô rtes, A.M.A.; Coutinho, A.L.G.A.; Dalcin, L.; Calo, Victor M.

2015-01-01

The recently introduced divergence-conforming B-spline discretizations allow the construction of smooth discrete velocity–pressure pairs for viscous incompressible flows that are at the same time inf-sup stable and pointwise divergence-free. When applied to discretized Stokes equations, these spaces generate a symmetric and indefinite saddle-point linear system. Krylov subspace methods are usually the most efficient procedures to solve such systems. One of such methods, for symmetric systems, is the Minimum Residual Method (MINRES). However, the efficiency and robustness of Krylov subspace methods is closely tied to appropriate preconditioning strategies. For the discrete Stokes system, in particular, block-diagonal strategies provide efficient preconditioners. In this article, we compare the performance of block-diagonal preconditioners for several block choices. We verify how the eigenvalue clustering promoted by the preconditioning strategies affects MINRES convergence. We also compare the number of iterations and wall-clock timings. We conclude that among the building blocks we tested, the strategy with relaxed inner conjugate gradients preconditioned with incomplete Cholesky provided the best results.

Performance evaluation of block-diagonal preconditioners for the divergence-conforming B-spline discretization of the Stokes system

KAUST Repository

Côrtes, A.M.A.

2015-02-20

The recently introduced divergence-conforming B-spline discretizations allow the construction of smooth discrete velocity–pressure pairs for viscous incompressible flows that are at the same time inf-sup stable and pointwise divergence-free. When applied to discretized Stokes equations, these spaces generate a symmetric and indefinite saddle-point linear system. Krylov subspace methods are usually the most efficient procedures to solve such systems. One of such methods, for symmetric systems, is the Minimum Residual Method (MINRES). However, the efficiency and robustness of Krylov subspace methods is closely tied to appropriate preconditioning strategies. For the discrete Stokes system, in particular, block-diagonal strategies provide efficient preconditioners. In this article, we compare the performance of block-diagonal preconditioners for several block choices. We verify how the eigenvalue clustering promoted by the preconditioning strategies affects MINRES convergence. We also compare the number of iterations and wall-clock timings. We conclude that among the building blocks we tested, the strategy with relaxed inner conjugate gradients preconditioned with incomplete Cholesky provided the best results.

A thin-plate spline analysis of the face and tongue in obstructive sleep apnea patients.

Science.gov (United States)

Pae, E K; Lowe, A A; Fleetham, J A

1997-12-01

The shape characteristics of the face and tongue in obstructive sleep apnea (OSA) patients were investigated using thin-plate (TP) splines. A relatively new analytic tool, the TP spline method, provides a means of size normalization and image analysis. When shape is one's main concern, various sizes of a biologic structure may be a source of statistical noise. More seriously, the strong size effect could mask underlying, actual attributes of the disease. A set of size normalized data in the form of coordinates was generated from cephalograms of 80 male subjects. The TP spline method envisioned the differences in the shape of the face and tongue between OSA patients and nonapneic subjects and those between the upright and supine body positions. In accordance with OSA severity, the hyoid bone and the submental region positioned inferiorly and the fourth vertebra relocated posteriorly with respect to the mandible. This caused a fanlike configuration of the lower part of the face and neck in the sagittal plane in both upright and supine body positions. TP splines revealed tongue deformations caused by a body position change. Overall, the new morphometric tool adopted here was found to be viable in the analysis of morphologic changes.

Spatiotemporal reconstruction of list-mode PET data

International Nuclear Information System (INIS)

Nichols, Thomas E.; Qi, Jinyi; Asma, Evren; Leahy, Richard M.

2002-01-01

We describe a method for computing a continuous time estimate of tracer density using list-mode positron emission tomography data. The rate function in each voxel is modeled as an inhomogeneous Poisson process whose rate function can be represented using a cubic B-spline basis. The rate functions are estimated by maximizing the likelihood of the arrival times of detected photon pairs over the control vertices of the spline, modified by quadratic spatial and temporal smoothness penalties and a penalty term to enforce non-negativity. Randoms rate functions are estimated by assuming independence between the spatial and temporal randoms distributions. Similarly, scatter rate functions are estimated by assuming spatiotemporal independence and that the temporal distribution of the scatter is proportional to the temporal distribution of the trues. A quantitative evaluation was performed using simulated data and the method is also demonstrated in a human study using 11C-raclopride

Spatiotemporal reconstruction of list-mode PET data

CERN Document Server

Nichols, T E; Asma, E; Leahy, R M

2002-01-01

We describe a method for computing a continuous time estimate of tracer density using list-mode positron emission tomography data. The rate function in each voxel is modeled as an inhomogeneous Poisson process whose rate function can be represented using a cubic B-spline basis. The rate functions are estimated by maximizing the likelihood of the arrival times of detected photon pairs over the control vertices of the spline, modified by quadratic spatial and temporal smoothness penalties and a penalty term to enforce non-negativity. Randoms rate functions are estimated by assuming independence between the spatial and temporal randoms distributions. Similarly, scatter rate functions are estimated by assuming spatiotemporal independence and that the temporal distribution of the scatter is proportional to the temporal distribution of the trues. A quantitative evaluation was performed using simulated data and the method is also demonstrated in a human study using 11C-raclopride.

Data smoothing techniques applied to proton microprobe scans of teleost hard parts

International Nuclear Information System (INIS)

West, I.F.; Gauldie, R.W.; Coote, G.E.

1992-01-01

We use a proton microprobe to examine the distribution of elements in otoliths and scales of teleost (bony) fish. The elements of principal interest are calcium and strontium in otoliths and calcium and fluorine in scales. Changes in the distribution of these elements across hard structures may allow inferences about the life histories of fish. Otoliths and scales of interest are up to a centimeter in linear dimension and to reveal the structures of interest up to 200 sampling points are required in each dimension. The time needed to accumulate high X-ray counts at each sampling point can be large, particularly for strontium. To reduce microprobe usage we use data smoothing techniques to reveal changing patterns with modest X-ray count accumulations at individual data points. In this paper we review performance for revealing pattern at modest levels of X-ray count accumulations of a selection of digital filters (moving average smoothers), running median filters, robust locally weighted regression filters and adaptive spline filters. (author)

Comparison of density estimators. [Estimation of probability density functions

Energy Technology Data Exchange (ETDEWEB)

Kao, S.; Monahan, J.F.

1977-09-01

Recent work in the field of probability density estimation has included the introduction of some new methods, such as the polynomial and spline methods and the nearest neighbor method, and the study of asymptotic properties in depth. This earlier work is summarized here. In addition, the computational complexity of the various algorithms is analyzed, as are some simulations. The object is to compare the performance of the various methods in small samples and their sensitivity to change in their parameters, and to attempt to discover at what point a sample is so small that density estimation can no longer be worthwhile. (RWR)

Comparison of parametric, orthogonal, and spline functions to model individual lactation curves for milk yield in Canadian Holsteins

Directory of Open Access Journals (Sweden)

Corrado Dimauro

2010-11-01

Full Text Available Test day records for milk yield of 57,390 first lactation Canadian Holsteins were analyzed with a linear model that included the fixed effects of herd-test date and days in milk (DIM interval nested within age and calving season. Residuals from this model were analyzed as a new variable and fitted with a five parameter model, fourth-order Legendre polynomials, with linear, quadratic and cubic spline models with three knots. The fit of the models was rather poor, with about 30-40% of the curves showing an adjusted R-square lower than 0.20 across all models. Results underline a great difficulty in modelling individual deviations around the mean curve for milk yield. However, the Ali and Schaeffer (5 parameter model and the fourth-order Legendre polynomials were able to detect two basic shapes of individual deviations among the mean curve. Quadratic and, especially, cubic spline functions had better fitting performances but a poor predictive ability due to their great flexibility that results in an abrupt change of the estimated curve when data are missing. Parametric and orthogonal polynomials seem to be robust and affordable under this standpoint.

Asymptotic theory for regressions with smoothly changing parameters

DEFF Research Database (Denmark)

Hillebrand, Eric; Medeiros, Marcelo; Xu, Junyue

2013-01-01

We derive asymptotic properties of the quasi maximum likelihood estimator of smooth transition regressions when time is the transition variable. The consistency of the estimator and its asymptotic distribution are examined. It is shown that the estimator converges at the usual pT-rate and has...... an asymptotically normal distribution. Finite sample properties of the estimator are explored in simulations. We illustrate with an application to US inflation and output data....

Counterexamples to the B-spline Conjecture for Gabor Frames

DEFF Research Database (Denmark)

Lemvig, Jakob; Nielsen, Kamilla Haahr

2016-01-01

The frame set conjecture for B-splines Bn, n≥2, states that the frame set is the maximal set that avoids the known obstructions. We show that any hyperbola of the form ab=r, where r is a rational number smaller than one and a and b denote the sampling and modulation rates, respectively, has infin...

An Iterative Ensemble Kalman Filter with One-Step-Ahead Smoothing for State-Parameters Estimation of Contaminant Transport Models

KAUST Repository

Gharamti, M. E.

2015-05-11

The ensemble Kalman filter (EnKF) is a popular method for state-parameters estimation of subsurface flow and transport models based on field measurements. The common filtering procedure is to directly update the state and parameters as one single vector, which is known as the Joint-EnKF. In this study, we follow the one-step-ahead smoothing formulation of the filtering problem, to derive a new joint-based EnKF which involves a smoothing step of the state between two successive analysis steps. The new state-parameters estimation scheme is derived in a consistent Bayesian filtering framework and results in separate update steps for the state and the parameters. This new algorithm bears strong resemblance with the Dual-EnKF, but unlike the latter which first propagates the state with the model then updates it with the new observation, the proposed scheme starts by an update step, followed by a model integration step. We exploit this new formulation of the joint filtering problem and propose an efficient model-integration-free iterative procedure on the update step of the parameters only for further improved performances. Numerical experiments are conducted with a two-dimensional synthetic subsurface transport model simulating the migration of a contaminant plume in a heterogenous aquifer domain. Contaminant concentration data are assimilated to estimate both the contaminant state and the hydraulic conductivity field. Assimilation runs are performed under imperfect modeling conditions and various observational scenarios. Simulation results suggest that the proposed scheme efficiently recovers both the contaminant state and the aquifer conductivity, providing more accurate estimates than the standard Joint and Dual EnKFs in all tested scenarios. Iterating on the update step of the new scheme further enhances the proposed filter’s behavior. In term of computational cost, the new Joint-EnKF is almost equivalent to that of the Dual-EnKF, but requires twice more model

Motion characteristic between die and workpiece in spline rolling process with round dies

Directory of Open Access Journals (Sweden)

Da-Wei Zhang

2016-06-01

Full Text Available In the spline rolling process with round dies, additional kinematic compensation is an essential mechanism for improving the division of teeth and pitch accuracy as well as surface quality. The motion characteristic between the die and workpiece under varied center distance in the spline rolling process was investigated. Mathematical models of the instantaneous center of rotation, transmission ratio, and centrodes in the rolling process were established. The models were used to analyze the rolling process of the involute spline with circular dedendum, and the results indicated that (1 with the reduction in the center distance, the instantaneous center moves toward workpiece, and the transmission ratio increases at first and then decreases; (2 the variations in the instantaneous center and transmission ratio are discontinuous, presenting an interruption when the involute flank begins to be formed; (3 the change in transmission ratio at the forming stage of the workpiece with the involute flank can be negligible; and (4 the centrode of the workpiece is an Archimedes line whose polar radius reduces, and the centrode of the rolling die is similar to Archimedes line when the workpiece is with the involute flank.

Curvelet-domain multiple matching method combined with cubic B-spline function

Science.gov (United States)

Wang, Tong; Wang, Deli; Tian, Mi; Hu, Bin; Liu, Chengming

2018-05-01

Since the large amount of surface-related multiple existed in the marine data would influence the results of data processing and interpretation seriously, many researchers had attempted to develop effective methods to remove them. The most successful surface-related multiple elimination method was proposed based on data-driven theory. However, the elimination effect was unsatisfactory due to the existence of amplitude and phase errors. Although the subsequent curvelet-domain multiple-primary separation method achieved better results, poor computational efficiency prevented its application. In this paper, we adopt the cubic B-spline function to improve the traditional curvelet multiple matching method. First, select a little number of unknowns as the basis points of the matching coefficient; second, apply the cubic B-spline function on these basis points to reconstruct the matching array; third, build constraint solving equation based on the relationships of predicted multiple, matching coefficients, and actual data; finally, use the BFGS algorithm to iterate and realize the fast-solving sparse constraint of multiple matching algorithm. Moreover, the soft-threshold method is used to make the method perform better. With the cubic B-spline function, the differences between predicted multiple and original data diminish, which results in less processing time to obtain optimal solutions and fewer iterative loops in the solving procedure based on the L1 norm constraint. The applications to synthetic and field-derived data both validate the practicability and validity of the method.

Asymptotic Theory for Regressions with Smoothly Changing Parameters

DEFF Research Database (Denmark)

Hillebrand, Eric Tobias; Medeiros, Marcelo C.; Xu, Junyue

We derive asymptotic properties of the quasi maximum likelihood estimator of smooth transition regressions when time is the transition variable. The consistency of the estimator and its asymptotic distribution are examined. It is shown that the estimator converges at the usual square-root-of-T rate...... and has an asymptotically normal distribution. Finite sample properties of the estimator are explored in simulations. We illustrate with an application to US inflation and output data....

Multilevel summation with B-spline interpolation for pairwise interactions in molecular dynamics simulations

International Nuclear Information System (INIS)

Hardy, David J.; Schulten, Klaus; Wolff, Matthew A.; Skeel, Robert D.; Xia, Jianlin

2016-01-01

The multilevel summation method for calculating electrostatic interactions in molecular dynamics simulations constructs an approximation to a pairwise interaction kernel and its gradient, which can be evaluated at a cost that scales linearly with the number of atoms. The method smoothly splits the kernel into a sum of partial kernels of increasing range and decreasing variability with the longer-range parts interpolated from grids of increasing coarseness. Multilevel summation is especially appropriate in the context of dynamics and minimization, because it can produce continuous gradients. This article explores the use of B-splines to increase the accuracy of the multilevel summation method (for nonperiodic boundaries) without incurring additional computation other than a preprocessing step (whose cost also scales linearly). To obtain accurate results efficiently involves technical difficulties, which are overcome by a novel preprocessing algorithm. Numerical experiments demonstrate that the resulting method offers substantial improvements in accuracy and that its performance is competitive with an implementation of the fast multipole method in general and markedly better for Hamiltonian formulations of molecular dynamics. The improvement is great enough to establish multilevel summation as a serious contender for calculating pairwise interactions in molecular dynamics simulations. In particular, the method appears to be uniquely capable for molecular dynamics in two situations, nonperiodic boundary conditions and massively parallel computation, where the fast Fourier transform employed in the particle–mesh Ewald method falls short.

Vibration Analysis of Rectangular Plates with One or More Guided Edges via Bicubic B-Spline Method

Directory of Open Access Journals (Sweden)

W.J. Si

2005-01-01

Full Text Available A simple and accurate method is proposed for the vibration analysis of rectangular plates with one or more guided edges, in which bicubic B-spline interpolation in combination with a new type of basis cubic B-spline functions is used to approximate the plate deflection. This type of basis cubic B-spline functions can satisfy simply supported, clamped, free, and guided edge conditions with easy numerical manipulation. The frequency characteristic equation is formulated based on classical thin plate theory by performing Hamilton's principle. The present solutions are verified with the analytical ones. Fast convergence, high accuracy and computational efficiency have been demonstrated from the comparisons. Frequency parameters for 13 cases of rectangular plates with at least one guided edge, which are possible by approximate or numerical methods only, are presented. These results are new in literature.

Mandibular transformations in prepubertal patients following treatment for craniofacial microsomia: thin-plate spline analysis.

Science.gov (United States)

Hay, A D; Singh, G D

2000-01-01

To analyze correction of mandibular deformity using an inverted L osteotomy and autogenous bone graft in patients exhibiting unilateral craniofacial microsomia (CFM), thin-plate spline analysis was undertaken. Preoperative, early postoperative, and approximately 3.5-year postoperative posteroanterior cephalographs of 15 children (age 10+/-3 years) with CFM were scanned, and eight homologous mandibular landmarks digitized. Average mandibular geometries, scaled to an equivalent size, were generated using Procrustes superimposition. Results indicated that the mean pre- and postoperative mandibular configurations differed statistically (PThin-plate spline analysis indicated that the total spline (Cartesian transformation grid) of the pre- to early postoperative configuration showed mandibular body elongation on the treated side and inferior symphyseal displacement. The affine component of the total spline revealed a clockwise rotation of the preoperative configuration, whereas the nonaffine component was responsible for ramus, body, and symphyseal displacements. The transformation grid for the early and late postoperative comparison showed bilateral ramus elongation. A superior symphyseal displacement contrasted with its earlier inferior displacement, the affine component had translocated the symphyseal landmarks towards the midline. The nonaffine component demonstrated bilateral ramus lengthening, and partial warps suggested that these elongations were slightly greater on the nontreated side. The affine component of the pre- and late postoperative comparison also demonstrated a clockwise rotation. The nonaffine component produced the bilateral ramus elongations-the nontreated side ramus lengthening slightly more than the treated side. It is concluded that an inverted L osteotomy improves mandibular morphology significantly in CFM patients and permits continued bilateral ramus growth. Copyright 2000 Wiley-Liss, Inc.

Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts.

Science.gov (United States)

Howe, Laura D; Tilling, Kate; Matijasevich, Alicia; Petherick, Emily S; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S; Barros, Aluísio Jd; Martin, Richard M; Kramer, Michael S; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A

2016-10-01

Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models. © The Author(s) 2013.

Value of the New Spline QTc Formula in Adjusting for Pacing-Induced Changes in Heart Rate

Directory of Open Access Journals (Sweden)

Hirmand Nouraei

2018-01-01

Full Text Available Aims. To determine whether a new QTc calculation based on a Spline fit model derived and validated from a large population remained stable in the same individual across a range of heart rates (HRs. Second, to determine whether this formula incorporating QRS duration can be of value in QT measurement, compared to direct measurement of the JT interval, during ventricular pacing. Methods. Individuals (N=30; 14 males aged 51.9 ± 14.3 years were paced with decremental atrial followed by decremental ventricular pacing. Results. The new QTc changed minimally with shorter RR intervals, poorly fit even a linear relationship, and did not fit a second-order polynomial. In contrast, the Bazett formula (QTcBZT showed a steep and marked increase in QTc with shorter RR intervals. For atrial pacing data, QTcBZT was fit best by a second-order polynomial and demonstrated a dramatic increase in QTc with progressively shorter RR intervals. For ventricular pacing, the new QTc minus QRS duration did not meaningfully change with HR in contrast to the HR dependency of QTcBZT and JT interval. Conclusion. The new QT correction formula is minimally impacted by HR acceleration induced by atrial or ventricular pacing. The Spline QTc minus QRS duration is an excellent method to estimate QTc in ventricular paced complexes.

SPLINE LINEAR REGRESSION USED FOR EVALUATING FINANCIAL ASSETS 1

Directory of Open Access Journals (Sweden)

Liviu GEAMBAŞU

2010-12-01

Full Text Available One of the most important preoccupations of financial markets participants was and still is the problem of determining more precise the trend of financial assets prices. For solving this problem there were written many scientific papers and were developed many mathematical and statistical models in order to better determine the financial assets price trend. If until recently the simple linear models were largely used due to their facile utilization, the financial crises that affected the world economy starting with 2008 highlight the necessity of adapting the mathematical models to variation of economy. A simple to use model but adapted to economic life realities is the spline linear regression. This type of regression keeps the continuity of regression function, but split the studied data in intervals with homogenous characteristics. The characteristics of each interval are highlighted and also the evolution of market over all the intervals, resulting reduced standard errors. The first objective of the article is the theoretical presentation of the spline linear regression, also referring to scientific national and international papers related to this subject. The second objective is applying the theoretical model to data from the Bucharest Stock Exchange

Topology optimization based on spline-based meshfree method using topological derivatives

International Nuclear Information System (INIS)

Hur, Junyoung; Youn, Sung-Kie; Kang, Pilseong

2017-01-01

Spline-based meshfree method (SBMFM) is originated from the Isogeometric analysis (IGA) which integrates design and analysis through Non-uniform rational B-spline (NURBS) basis functions. SBMFM utilizes trimming technique of CAD system by representing the domain using NURBS curves. In this work, an explicit boundary topology optimization using SBMFM is presented with an effective boundary update scheme. There have been similar works in this subject. However unlike the previous works where semi-analytic method for calculating design sensitivities is employed, the design update is done by using topological derivatives. In this research, the topological derivative is used to derive the sensitivity of boundary curves and for the creation of new holes. Based on the values of topological derivatives, the shape of boundary curves is updated. Also, the topological change is achieved by insertion and removal of the inner holes. The presented approach is validated through several compliance minimization problems.

Topology optimization based on spline-based meshfree method using topological derivatives

Energy Technology Data Exchange (ETDEWEB)

Hur, Junyoung; Youn, Sung-Kie [KAIST, Daejeon (Korea, Republic of); Kang, Pilseong [Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of)

2017-05-15

Spline-based meshfree method (SBMFM) is originated from the Isogeometric analysis (IGA) which integrates design and analysis through Non-uniform rational B-spline (NURBS) basis functions. SBMFM utilizes trimming technique of CAD system by representing the domain using NURBS curves. In this work, an explicit boundary topology optimization using SBMFM is presented with an effective boundary update scheme. There have been similar works in this subject. However unlike the previous works where semi-analytic method for calculating design sensitivities is employed, the design update is done by using topological derivatives. In this research, the topological derivative is used to derive the sensitivity of boundary curves and for the creation of new holes. Based on the values of topological derivatives, the shape of boundary curves is updated. Also, the topological change is achieved by insertion and removal of the inner holes. The presented approach is validated through several compliance minimization problems.

Penalized Nonlinear Least Squares Estimation of Time-Varying Parameters in Ordinary Differential Equations

KAUST Repository

Cao, Jiguo; Huang, Jianhua Z.; Wu, Hulin

2012-01-01

Ordinary differential equations (ODEs) are widely used in biomedical research and other scientific areas to model complex dynamic systems. It is an important statistical problem to estimate parameters in ODEs from noisy observations. In this article we propose a method for estimating the time-varying coefficients in an ODE. Our method is a variation of the nonlinear least squares where penalized splines are used to model the functional parameters and the ODE solutions are approximated also using splines. We resort to the implicit function theorem to deal with the nonlinear least squares objective function that is only defined implicitly. The proposed penalized nonlinear least squares method is applied to estimate a HIV dynamic model from a real dataset. Monte Carlo simulations show that the new method can provide much more accurate estimates of functional parameters than the existing two-step local polynomial method which relies on estimation of the derivatives of the state function. Supplemental materials for the article are available online.

A Smooth Transition Logit Model of the Effects of Deregulation in the Electricity Market

DEFF Research Database (Denmark)

Hurn, A.S.; Silvennoinen, Annastiina; Teräsvirta, Timo

We consider a nonlinear vector model called the logistic vector smooth transition autoregressive model. The bivariate single-transition vector smooth transition regression model of Camacho (2004) is generalised to a multivariate and multitransition one. A modelling strategy consisting of specific......We consider a nonlinear vector model called the logistic vector smooth transition autoregressive model. The bivariate single-transition vector smooth transition regression model of Camacho (2004) is generalised to a multivariate and multitransition one. A modelling strategy consisting...... of specification, including testing linearity, estimation and evaluation of these models is constructed. Nonlinear least squares estimation of the parameters of the model is discussed. Evaluation by misspecification tests is carried out using tests derived in a companion paper. The use of the modelling strategy...

Combined visualization for noise mapping of industrial facilities based on ray-tracing and thin plate splines

Science.gov (United States)

Ovsiannikov, Mikhail; Ovsiannikov, Sergei

2017-01-01

The paper presents the combined approach to noise mapping and visualizing of industrial facilities sound pollution using forward ray tracing method and thin-plate spline interpolation. It is suggested to cauterize industrial area in separate zones with similar sound levels. Equivalent local source is defined for range computation of sanitary zones based on ray tracing algorithm. Computation of sound pressure levels within clustered zones are based on two-dimension spline interpolation of measured data on perimeter and inside the zone.

Local smoothness for global optical flow

DEFF Research Database (Denmark)

Rakêt, Lars Lau

2012-01-01

by this technique and work on local-global optical flow we propose a simple method for fusing optical flow estimates of different smoothness by evaluating interpolation quality locally by means of L1 block match on the corresponding set of gradient images. We illustrate the method in a setting where optical flows...

Estimation of delays and other parameters in nonlinear functional differential equations

Science.gov (United States)

Banks, H. T.; Lamm, P. K. D.

1983-01-01

A spline-based approximation scheme for nonlinear nonautonomous delay differential equations is discussed. Convergence results (using dissipative type estimates on the underlying nonlinear operators) are given in the context of parameter estimation problems which include estimation of multiple delays and initial data as well as the usual coefficient-type parameters. A brief summary of some of the related numerical findings is also given.

The core spline method for solution of quantum-mechanical systems of differential equations for bound states

International Nuclear Information System (INIS)

Aleksandrov, L.; Drenska, M.; Karadzhov, D.

1986-01-01

A generalization of the core spline method is given in the case of solution of the general bound state problem for a system of M linear differential equations with coefficients depending on the spectral parameter. The recursion scheme for construction of basic splines is described. The wave functions are expressed as linear combinations of basic splines, which are approximate partial solutions of the system. The spectral parameter (the eigenvalue) is determined from the condition for existence of a nontrivial solution of a (MxM) linear algebraic system at the last collocation point. The nontrivial solutions of this system determine (M - 1) coefficients of the linear spans, expressing the wave functions. The last unknown coefficient is determined from a boundary (or normalization) condition for the system. The computational aspects of the method are discussed, in particular, its concrete algorithmic realization used in the RODSOL program. The numerical solution of the Dirac system for the bound states of a hydrogen atom is given is an example

Improvement of the Cubic Spline Function Sets for a Synthesis of the Axial Power Distribution of a Core Protection System

International Nuclear Information System (INIS)

Koo, Bon-Seung; Lee, Chung-Chan; Zee, Sung-Quun

2006-01-01

Online digital core protection system(SCOPS) for a system-integrated modular reactor is being developed as a part of a plant protection system at KAERI. SCOPS calculates the minimum CHFR and maximum LPD based on several online measured system parameters including 3-level ex-core detector signals. In conventional ABB-CE digital power plants, cubic spline synthesis technique has been used in online calculations of the core axial power distributions using ex-core detector signals once every 1 second in CPC. In CPC, pre-determined cubic spline function sets are used depending on the characteristics of the ex-core detector responses. But this method shows an unnegligible power distribution error for the extremely skewed axial shapes by using restrictive function sets. Therefore, this paper describes the cubic spline method for the synthesis of an axial power distribution and it generates several new cubic spline function sets for the application of the core protection system, especially for the severely distorted power shapes needed reactor type

Accurate e/sup -/-He cross sections below 19 eV

Energy Technology Data Exchange (ETDEWEB)

Nesbet, R K [International Business Machines Corp., San Jose, CA (USA). Research Lab.

1979-04-14

Variational calculations of e/sup -/-He s- and p-wave phaseshifts, together with the Born formula for higher partial waves, are used to give the scattering amplitude to within one per cent estimated accuracy for energies less than 19 eV. Coefficients are given of cubic spline fits to auxiliary functions that provide smooth interpolation of the estimated accurate phaseshifts. Data given here make it possible to obtain the differential scattering cross section over the energy range considered from simple formulae.

Comments on the comparison of global methods for linear two-point boundary value problems

International Nuclear Information System (INIS)

de Boor, C.; Swartz, B.

1977-01-01

A more careful count of the operations involved in solving the linear system associated with collocation of a two-point boundary value problem using a rough splines reverses results recently reported by others in this journal. In addition, it is observed that the use of the technique of ''condensation of parameters'' can decrease the computer storage required. Furthermore, the use of a particular highly localized basis can also reduce the setup time when the mesh is irregular. Finally, operation counts are roughly estimated for the solution of certain linear system associated with two competing collocation methods; namely, collocation with smooth splines and collocation of the equivalent first order system with continuous piecewise polynomials

Surface quality monitoring for process control by on-line vibration analysis using an adaptive spline wavelet algorithm

Science.gov (United States)

Luo, G. Y.; Osypiw, D.; Irle, M.

2003-05-01

The dynamic behaviour of wood machining processes affects the surface finish quality of machined workpieces. In order to meet the requirements of increased production efficiency and improved product quality, surface quality information is needed for enhanced process control. However, current methods using high price devices or sophisticated designs, may not be suitable for industrial real-time application. This paper presents a novel approach of surface quality evaluation by on-line vibration analysis using an adaptive spline wavelet algorithm, which is based on the excellent time-frequency localization of B-spline wavelets. A series of experiments have been performed to extract the feature, which is the correlation between the relevant frequency band(s) of vibration with the change of the amplitude and the surface quality. The graphs of the experimental results demonstrate that the change of the amplitude in the selective frequency bands with variable resolution (linear and non-linear) reflects the quality of surface finish, and the root sum square of wavelet power spectrum is a good indication of surface quality. Thus, surface quality can be estimated and quantified at an average level in real time. The results can be used to regulate and optimize the machine's feed speed, maintaining a constant spindle motor speed during cutting. This will lead to higher level control and machining rates while keeping dimensional integrity and surface finish within specification.

Regularization by fractional filter methods and data smoothing

International Nuclear Information System (INIS)

Klann, E; Ramlau, R

2008-01-01

This paper is concerned with the regularization of linear ill-posed problems by a combination of data smoothing and fractional filter methods. For the data smoothing, a wavelet shrinkage denoising is applied to the noisy data with known error level δ. For the reconstruction, an approximation to the solution of the operator equation is computed from the data estimate by fractional filter methods. These fractional methods are based on the classical Tikhonov and Landweber method, but avoid, at least partially, the well-known drawback of oversmoothing. Convergence rates as well as numerical examples are presented

Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous response.

Science.gov (United States)

Binder, Harald; Sauerbrei, Willi; Royston, Patrick

2013-06-15

In observational studies, many continuous or categorical covariates may be related to an outcome. Various spline-based procedures or the multivariable fractional polynomial (MFP) procedure can be used to identify important variables and functional forms for continuous covariates. This is the main aim of an explanatory model, as opposed to a model only for prediction. The type of analysis often guides the complexity of the final model. Spline-based procedures and MFP have tuning parameters for choosing the required complexity. To compare model selection approaches, we perform a simulation study in the linear regression context based on a data structure intended to reflect realistic biomedical data. We vary the sample size, variance explained and complexity parameters for model selection. We consider 15 variables. A sample size of 200 (1000) and R(2)  = 0.2 (0.8) is the scenario with the smallest (largest) amount of information. For assessing performance, we consider prediction error, correct and incorrect inclusion of covariates, qualitative measures for judging selected functional forms and further novel criteria. From limited information, a suitable explanatory model cannot be obtained. Prediction performance from all types of models is similar. With a medium amount of information, MFP performs better than splines on several criteria. MFP better recovers simpler functions, whereas splines better recover more complex functions. For a large amount of information and no local structure, MFP and the spline procedures often select similar explanatory models. Copyright © 2012 John Wiley & Sons, Ltd.

Interpolating Spline Curve-Based Perceptual Encryption for 3D Printing Models

Directory of Open Access Journals (Sweden)

Giao N. Pham

2018-02-01

Full Text Available With the development of 3D printing technology, 3D printing has recently been applied to many areas of life including healthcare and the automotive industry. Due to the benefit of 3D printing, 3D printing models are often attacked by hackers and distributed without agreement from the original providers. Furthermore, certain special models and anti-weapon models in 3D printing must be protected against unauthorized users. Therefore, in order to prevent attacks and illegal copying and to ensure that all access is authorized, 3D printing models should be encrypted before being transmitted and stored. A novel perceptual encryption algorithm for 3D printing models for secure storage and transmission is presented in this paper. A facet of 3D printing model is extracted to interpolate a spline curve of degree 2 in three-dimensional space that is determined by three control points, the curvature coefficients of degree 2, and an interpolating vector. Three control points, the curvature coefficients, and interpolating vector of the spline curve of degree 2 are encrypted by a secret key. The encrypted features of the spline curve are then used to obtain the encrypted 3D printing model by inverse interpolation and geometric distortion. The results of experiments and evaluations prove that the entire 3D triangle model is altered and deformed after the perceptual encryption process. The proposed algorithm is responsive to the various formats of 3D printing models. The results of the perceptual encryption process is superior to those of previous methods. The proposed algorithm also provides a better method and more security than previous methods.

Applying Emax model and bivariate thin plate splines to assess drug interactions.

Science.gov (United States)

Kong, Maiying; Lee, J Jack

2010-01-01

We review the semiparametric approach previously proposed by Kong and Lee and extend it to a case in which the dose-effect curves follow the Emax model instead of the median effect equation. When the maximum effects for the investigated drugs are different, we provide a procedure to obtain the additive effect based on the Loewe additivity model. Then, we apply a bivariate thin plate spline approach to estimate the effect beyond additivity along with its 95 per cent point-wise confidence interval as well as its 95 per cent simultaneous confidence interval for any combination dose. Thus, synergy, additivity, and antagonism can be identified. The advantages of the method are that it provides an overall assessment of the combination effect on the entire two-dimensional dose space spanned by the experimental doses, and it enables us to identify complex patterns of drug interaction in combination studies. In addition, this approach is robust to outliers. To illustrate this procedure, we analyzed data from two case studies.

A simple mathematical procedure to estimate heat flux in machining using measured surface temperature with infrared laser

Directory of Open Access Journals (Sweden)

Hocine Mzad

2015-09-01

Full Text Available Several techniques have been developed over time for the measurement of heat and the temperatures generated in various manufacturing processes and tribological applications. Each technique has its own advantages and disadvantages. The appropriate technique for temperature measurement depends on the application under consideration as well as the available tools for measurement. This paper presents a procedure for a simple and accurate determination of the time-varying heat flux at the workpiece–tool interface of three different metals under known cutting conditions. A portable infrared thermometer is used for surface temperature measurements. A spline smoothing interpolation of the surface temperature history enables to determine the local heat flux produced during stock removal. The measured temperature is represented by a third-order spline approximation. Nonetheless, the accuracy of polynomial interpolation depends on how close are the interpolated points; an increase in degree cannot be used to increase the accuracy. Although the data analysis is relatively complicated, the computing time is very small.

A novel knot selection method for the error-bounded B-spline curve fitting of sampling points in the measuring process

International Nuclear Information System (INIS)

Liang, Fusheng; Zhao, Ji; Ji, Shijun; Zhang, Bing; Fan, Cheng

2017-01-01

The B-spline curve has been widely used in the reconstruction of measurement data. The error-bounded sampling points reconstruction can be achieved by the knot addition method (KAM) based B-spline curve fitting. In KAM, the selection pattern of initial knot vector has been associated with the ultimate necessary number of knots. This paper provides a novel initial knots selection method to condense the knot vector required for the error-bounded B-spline curve fitting. The initial knots are determined by the distribution of features which include the chord length (arc length) and bending degree (curvature) contained in the discrete sampling points. Firstly, the sampling points are fitted into an approximate B-spline curve Gs with intensively uniform knot vector to substitute the description of the feature of the sampling points. The feature integral of Gs is built as a monotone increasing function in an analytic form. Then, the initial knots are selected according to the constant increment of the feature integral. After that, an iterative knot insertion (IKI) process starting from the initial knots is introduced to improve the fitting precision, and the ultimate knot vector for the error-bounded B-spline curve fitting is achieved. Lastly, two simulations and the measurement experiment are provided, and the results indicate that the proposed knot selection method can reduce the number of ultimate knots available. (paper)

Correction of Sample-Time Error for Time-Interleaved Sampling System Using Cubic Spline Interpolation

Directory of Open Access Journals (Sweden)

Qin Guo-jie

2014-08-01

Full Text Available Sample-time errors can greatly degrade the dynamic range of a time-interleaved sampling system. In this paper, a novel correction technique employing a cubic spline interpolation is proposed for inter-channel sample-time error compensation. The cubic spline interpolation compensation filter is developed in the form of a finite-impulse response (FIR filter structure. The correction method of the interpolation compensation filter coefficients is deduced. A 4GS/s two-channel, time-interleaved ADC prototype system has been implemented to evaluate the performance of the technique. The experimental results showed that the correction technique is effective to attenuate the spurious spurs and improve the dynamic performance of the system.

Valid and efficient manual estimates of intracranial volume from magnetic resonance images

International Nuclear Information System (INIS)

Klasson, Niklas; Olsson, Erik; Rudemo, Mats; Eckerström, Carl; Malmgren, Helge; Wallin, Anders

2015-01-01

Manual segmentations of the whole intracranial vault in high-resolution magnetic resonance images are often regarded as very time-consuming. Therefore it is common to only segment a few linearly spaced intracranial areas to estimate the whole volume. The purpose of the present study was to evaluate how the validity of intracranial volume estimates is affected by the chosen interpolation method, orientation of the intracranial areas and the linear spacing between them. Intracranial volumes were manually segmented on 62 participants from the Gothenburg MCI study using 1.5 T, T 1 -weighted magnetic resonance images. Estimates of the intracranial volumes were then derived using subsamples of linearly spaced coronal, sagittal or transversal intracranial areas from the same volumes. The subsamples of intracranial areas were interpolated into volume estimates by three different interpolation methods. The linear spacing between the intracranial areas ranged from 2 to 50 mm and the validity of the estimates was determined by comparison with the entire intracranial volumes. A progressive decrease in intra-class correlation and an increase in percentage error could be seen with increased linear spacing between intracranial areas. With small linear spacing (≤15 mm), orientation of the intracranial areas and interpolation method had negligible effects on the validity. With larger linear spacing, the best validity was achieved using cubic spline interpolation with either coronal or sagittal intracranial areas. Even at a linear spacing of 50 mm, cubic spline interpolation on either coronal or sagittal intracranial areas had a mean absolute agreement intra-class correlation with the entire intracranial volumes above 0.97. Cubic spline interpolation in combination with linearly spaced sagittal or coronal intracranial areas overall resulted in the most valid and robust estimates of intracranial volume. Using this method, valid ICV estimates could be obtained in less than five

Using biased image analysis for improving unbiased stereological number estimation - a pilot simulation study of the smooth fractionator

DEFF Research Database (Denmark)

Gardi, Jonathan Eyal; Nyengaard, Jens Randel; Gundersen, Hans Jørgen Gottlieb

2006-01-01

uniformly random sampling design and the ordinary simple random sampling design. The smooth protocol is performed using biased information from crude (but fully automatic) image analysis of the fields of view. The different design paradigms are compared using simulation in three different cell distributions......The smooth fractionator was introduced in 2002. The combination of a smoothing protocol with a computer-aided stereology tool provides better precision and a lighter workload. This study uses simulation to compare fractionator sampling based on the smooth design, the commonly used systematic...

Estimates of gradient Richardson numbers from vertically smoothed data in the Gulf Stream region

Directory of Open Access Journals (Sweden)

Paul van Gastel

2004-12-01

Full Text Available We use several hydrographic and velocity sections crossing the Gulf Stream to examine how the gradient Richardson number, Ri, is modified due to both vertical smoothing of the hydrographic and/or velocity fields and the assumption of parallel or geostrophic flow. Vertical smoothing of the original (25 m interval velocity field leads to a substantial increase in the Ri mean value, of the same order as the smoothing factor, while its standard deviation remains approximately constant. This contrasts with very minor changes in the distribution of the Ri values due to vertical smoothing of the density field over similar lengths. Mean geostrophic Ri values remain always above the actual unsmoothed Ri values, commonly one to two orders of magnitude larger, but the standard deviation is typically a factor of five larger in geostrophic than in actual Ri values. At high vertical wavenumbers (length scales below 3 m the geostrophic shear only leads to near critical conditions in already rather mixed regions. At these scales, hence, the major contributor to shear mixing is likely to come from the interaction of the background flow with internal waves. At low vertical wavenumbers (scales above 25 m the ageostrophic motions provide the main source for shear, with cross-stream movements having a minor but non-negligible contribution. These large-scale motions may be associated with local accelerations taking place during frontogenetic phases of meanders.

Investigation of confined hydrogen atom in spherical cavity, using B-splines basis set

Directory of Open Access Journals (Sweden)

M Barezi

2011-03-01

Full Text Available Studying confined quantum systems (CQS is very important in nano technology. One of the basic CQS is a hydrogen atom confined in spherical cavity. In this article, eigenenergies and eigenfunctions of hydrogen atom in spherical cavity are calculated, using linear variational method. B-splines are used as basis functions, which can easily construct the trial wave functions with appropriate boundary conditions. The main characteristics of B-spline are its high localization and its flexibility. Besides, these functions have numerical stability and are able to spend high volume of calculation with good accuracy. The energy levels as function of cavity radius are analyzed. To check the validity and efficiency of the proposed method, extensive convergence test of eigenenergies in different cavity sizes has been carried out.

Interval Forecast for Smooth Transition Autoregressive Model ...

African Journals Online (AJOL)

In this paper, we propose a simple method for constructing interval forecast for smooth transition autoregressive (STAR) model. This interval forecast is based on bootstrapping the residual error of the estimated STAR model for each forecast horizon and computing various Akaike information criterion (AIC) function. This new ...

La obtención y proyección de tablas de mortalidad empleando curvas. Spline

Directory of Open Access Journals (Sweden)

Alejandro MINA-VALDÉS

2011-01-01

Full Text Available Una de las herramientas del análisis numérico es el uso de polinomios de n-ésimo orden para interpolar entre n + 1 puntos, teniéndose casos en donde estas funciones polinómicas pueden llevar a resultados erróneos. Una alternativa es la de aplicar polinomios de orden inferior a subconjuntos de datos. Estos polinomios conectados se llaman funciones de interpolación segmentaria (spline functions. En este artículo se presenta la herramienta que el análisis numérico proporciona como instrumento técnico necesario para llevar a cabo todos los procedimientos matemáticos existentes con base a algoritmos que permitan su simulación o cálculo, en especial, las funciones splines definidas a trozos (por tramos, con interpolación mediante ellas, dando lugar a el ajuste de curvas spline con base en la serie de sobrevivientes lx de una tabla abreviada de mortalidad mexicana, con el fin de desagregarla por edad desplegada, respetando las concavidades que por el efecto de la mortalidad en las primeras edades y en las siguientes se tienen en la experiencia mexicana. También empleando las curvas splines se presentan las simulaciones que permiten obtener escenarios futuros de las series de sobrevivientes lx, que dan lugar a las proyecciones de la mortalidad mexicana para los años 2010-2050, las que generan las tablas completas de mortalidad para hombres y mujeres de dicho periodo, resaltando las diferencias entre sexos y edades de sus probabilidades de supervivencia y las ganancias en las esperanzas de vida.

Ethnicity and skeletal Class III morphology: a pubertal growth analysis using thin-plate spline analysis.

Science.gov (United States)

Alkhamrah, B; Terada, K; Yamaki, M; Ali, I M; Hanada, K

2001-01-01

A longitudinal retrospective study using thin-plate spline analysis was used to investigate skeletal Class III etiology in Japanese female adolescents. Headfilms of 40 subjects were chosen from the archives of the Orthodontic department at Niigata University Dental Hospital, and were traced at IIIB and IVA Hellman dental ages. Twenty-eight homologous landmarks, representing hard and soft tissue, were digitized. These were used to reproduce a consensus for the profilogram, craniomaxillary complex, mandible, and soft tissue for each age and skeletal group. Generalized least-square analysis revealed a significant shape difference between age-matched groups (P spline and partial warps (PW)3 and 2 showed a maxillary retrusion at stage IIIB opposite an acute cranial base at stage IVA. Mandibular total spline and PW4, 5 showed changes affecting most landmarks and their spatial interrelationship, especially a stretch along the articulare-pogonion axis. In soft tissue analysis, PW8 showed large and local changes which paralleled the underlying hard tissue components. Allometry of the mandible and anisotropy of the cranial base, the maxilla, and the mandible asserted the complexity of craniofacial growth and the difficulty of predicting its outcome.

RANCANG BANGUN PROGRAM PENGEDITAN KURVA B-SPLINE MULTIRESOLUSI BERBASIS WAVELETS

Directory of Open Access Journals (Sweden)

Nanik Suciati

2002-07-01

Full Text Available Penelitian ini menyusun representasi multiresolusi untuk kurva B-spline kubik yang menginterpolasi titik-titik ujung dengan basis wavelets. Representasi multiresolusi ini digunakan untuk mendukung beberapa tipe pengeditan kurva, yaitu penghalusan kurva dengan tingkat resolusi kontinyu untuk menghilangkan detail-detail kurva yang tidak diinginkan, pengeditan bentuk keseluruhan kurva dengan tetap mempertahankan detaildetailnya, perubahan detail-detail kurva tanpa mempengaruhi bentuk keseluruhannya, dan pengeditan satubagian tertentu dari kurva melalui manipulasi secara langsung terhadap titik-titik kontrolnya. Untuk menguji kemampuan representasi multiresolusi dalam mendukung empat tipe manipulasi kurva tersebut, disusun program pengeditan kurva dengan menggunakan bahasa pemrograman Visual C++ pada komputer Pentium 133 MHz, memori 16 Mbyte, sistem operasi Windows 95, lingkungan pengembangan Microsoft DevelopmentStudio 97 dan pustaka Microsoft Foundation Class. Dari hasil uji coba program diketahui bahwa representasi multiresolusi memberikan dukungan yang sangat baik terhadap tipe-tipe pengeditan seperti yang disebutkan di atas. Representasi multiresolusi tidak membutuhkan memori penyimpan ekstra selain dari yang digunakan untuk menyimpan titik kontrol. Dari hasil uji coba program menggunakan ratusan titik kontrol, algoritma berjalan cukup cepat dan memadai berkaitan dengan tuntutan komunikasi interaktif antara user dan program.Kata kunci: B-Spline, Wavelet, Multiresolusi

Hybrid B-Spline Collocation Method for Solving the Generalized Burgers-Fisher and Burgers-Huxley Equations

Directory of Open Access Journals (Sweden)

Imtiaz Wasim

2018-01-01

Full Text Available In this study, we introduce a new numerical technique for solving nonlinear generalized Burgers-Fisher and Burgers-Huxley equations using hybrid B-spline collocation method. This technique is based on usual finite difference scheme and Crank-Nicolson method which are used to discretize the time derivative and spatial derivatives, respectively. Furthermore, hybrid B-spline function is utilized as interpolating functions in spatial dimension. The scheme is verified unconditionally stable using the Von Neumann (Fourier method. Several test problems are considered to check the accuracy of the proposed scheme. The numerical results are in good agreement with known exact solutions and the existing schemes in literature.

A chord error conforming tool path B-spline fitting method for NC machining based on energy minimization and LSPIA

Directory of Open Access Journals (Sweden)

Shanshan He

2015-10-01

Full Text Available Piecewise linear (G01-based tool paths generated by CAM systems lack G1 and G2 continuity. The discontinuity causes vibration and unnecessary hesitation during machining. To ensure efficient high-speed machining, a method to improve the continuity of the tool paths is required, such as B-spline fitting that approximates G01 paths with B-spline curves. Conventional B-spline fitting approaches cannot be directly used for tool path B-spline fitting, because they have shortages such as numerical instability, lack of chord error constraint, and lack of assurance of a usable result. Progressive and Iterative Approximation for Least Squares (LSPIA is an efficient method for data fitting that solves the numerical instability problem. However, it does not consider chord errors and needs more work to ensure ironclad results for commercial applications. In this paper, we use LSPIA method incorporating Energy term (ELSPIA to avoid the numerical instability, and lower chord errors by using stretching energy term. We implement several algorithm improvements, including (1 an improved technique for initial control point determination over Dominant Point Method, (2 an algorithm that updates foot point parameters as needed, (3 analysis of the degrees of freedom of control points to insert new control points only when needed, (4 chord error refinement using a similar ELSPIA method with the above enhancements. The proposed approach can generate a shape-preserving B-spline curve. Experiments with data analysis and machining tests are presented for verification of quality and efficiency. Comparisons with other known solutions are included to evaluate the worthiness of the proposed solution.

NeuroMap: A spline-based interactive open-source software for spatiotemporal mapping of 2D and 3D MEA data

Directory of Open Access Journals (Sweden)

Oussama eAbdoun

2011-01-01

Full Text Available A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA technology. Indeed, high-density MEAs provide large-scale covering (several mm² of whole neural structures combined with microscopic resolution (about 50µm of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid deformation based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License (GPL and available at http://sites.google.com/site/neuromapsoftware.

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data.

Science.gov (United States)

Abdoun, Oussama; Joucla, Sébastien; Mazzocco, Claire; Yvert, Blaise

2011-01-01

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware.

On splice site prediction using weight array models: a comparison of smoothing techniques

International Nuclear Information System (INIS)

Taher, Leila; Meinicke, Peter; Morgenstern, Burkhard

2007-01-01

In most eukaryotic genes, protein-coding exons are separated by non-coding introns which are removed from the primary transcript by a process called 'splicing'. The positions where introns are cut and exons are spliced together are called 'splice sites'. Thus, computational prediction of splice sites is crucial for gene finding in eukaryotes. Weight array models are a powerful probabilistic approach to splice site detection. Parameters for these models are usually derived from m-tuple frequencies in trusted training data and subsequently smoothed to avoid zero probabilities. In this study we compare three different ways of parameter estimation for m-tuple frequencies, namely (a) non-smoothed probability estimation, (b) standard pseudo counts and (c) a Gaussian smoothing procedure that we recently developed

Spline Collocation Method for Nonlinear Multi-Term Fractional Differential Equation

OpenAIRE

Choe, Hui-Chol; Kang, Yong-Suk

2013-01-01

We study an approximation method to solve nonlinear multi-term fractional differential equations with initial conditions or boundary conditions. First, we transform the nonlinear multi-term fractional differential equations with initial conditions and boundary conditions to nonlinear fractional integral equations and consider the relations between them. We present a Spline Collocation Method and prove the existence, uniqueness and convergence of approximate solution as well as error estimatio...

Estimating continuous floodplain and major river bed topography mixing ordinal coutour lines and topographic points

Science.gov (United States)

Bailly, J. S.; Dartevelle, M.; Delenne, C.; Rousseau, A.

2017-12-01

Floodplain and major river bed topography govern many river biophysical processes during floods. Despite the grow of direct topographic measurements from LiDARS on riverine systems, it still room to develop methods for large (e.g. deltas) or very local (e.g. ponds) riverine systems that take advantage of information coming from simple SAR or optical image processing on floodplain, resulting from waterbodies delineation during flood up or down, and producing ordered coutour lines. The next challenge is thus to exploit such data in order to estimate continuous topography on the floodplain combining heterogeneous data: a topographic points dataset and a located but unknown and ordered contourline dataset. This article is comparing two methods designed to estimate continuous topography on the floodplain mixing ordinal coutour lines and continuous topographic points. For both methods a first estimation step is to value each contourline with elevation and a second step is next to estimate the continuous field from both topographic points and valued contourlines. The first proposed method is a stochastic method starting from multigaussian random-fields and conditional simualtion. The second is a deterministic method based on radial spline fonction for thin layers used for approximated bivariate surface construction. Results are first shown and discussed from a set of synoptic case studies presenting various topographic points density and topographic smoothness. Next, results are shown and discuss on an actual case study in the Montagua laguna, located in the north of Valparaiso, Chile.

Adaptive estimation of a time-varying phase with coherent states: Smoothing can give an unbounded improvement over filtering

Science.gov (United States)

Laverick, Kiarn T.; Wiseman, Howard M.; Dinani, Hossein T.; Berry, Dominic W.

2018-04-01

The problem of measuring a time-varying phase, even when the statistics of the variation is known, is considerably harder than that of measuring a constant phase. In particular, the usual bounds on accuracy, such as the 1 /(4 n ¯) standard quantum limit with coherent states, do not apply. Here, by restricting to coherent states, we are able to analytically obtain the achievable accuracy, the equivalent of the standard quantum limit, for a wide class of phase variation. In particular, we consider the case where the phase has Gaussian statistics and a power-law spectrum equal to κp -1/|ω| p for large ω , for some p >1 . For coherent states with mean photon flux N , we give the quantum Cramér-Rao bound on the mean-square phase error as [psin(π /p ) ] -1(4N /κ ) -(p -1 )/p . Next, we consider whether the bound can be achieved by an adaptive homodyne measurement in the limit N /κ ≫1 , which allows the photocurrent to be linearized. Applying the optimal filtering for the resultant linear Gaussian system, we find the same scaling with N , but with a prefactor larger by a factor of p . By contrast, if we employ optimal smoothing we can exactly obtain the quantum Cramér-Rao bound. That is, contrary to previously considered (p =2 ) cases of phase estimation, here the improvement offered by smoothing over filtering is not limited to a factor of 2 but rather can be unbounded by a factor of p . We also study numerically the performance of these estimators for an adaptive measurement in the limit where N /κ is not large and find a more complicated picture.

Adaptive Nonparametric Variance Estimation for a Ratio Estimator ...

African Journals Online (AJOL)

Kernel estimators for smooth curves require modifications when estimating near end points of the support, both for practical and asymptotic reasons. The construction of such boundary kernels as solutions of variational problem is a difficult exercise. For estimating the error variance of a ratio estimator, we suggest an ...

Modeling Fetal Weight for Gestational Age: A Comparison of a Flexible Multi-level Spline-based Model with Other Approaches

Science.gov (United States)

Villandré, Luc; Hutcheon, Jennifer A; Perez Trejo, Maria Esther; Abenhaim, Haim; Jacobsen, Geir; Platt, Robert W

2011-01-01

We present a model for longitudinal measures of fetal weight as a function of gestational age. We use a linear mixed model, with a Box-Cox transformation of fetal weight values, and restricted cubic splines, in order to flexibly but parsimoniously model median fetal weight. We systematically compare our model to other proposed approaches. All proposed methods are shown to yield similar median estimates, as evidenced by overlapping pointwise confidence bands, except after 40 completed weeks, where our method seems to produce estimates more consistent with observed data. Sex-based stratification affects the estimates of the random effects variance-covariance structure, without significantly changing sex-specific fitted median values. We illustrate the benefits of including sex-gestational age interaction terms in the model over stratification. The comparison leads to the conclusion that the selection of a model for fetal weight for gestational age can be based on the specific goals and configuration of a given study without affecting the precision or value of median estimates for most gestational ages of interest. PMID:21931571

Optimization and parallelization of B-spline based orbital evaluations in QMC on multi/many-core shared memory processors

OpenAIRE

Mathuriya, Amrita; Luo, Ye; Benali, Anouar; Shulenburger, Luke; Kim, Jeongnim

2016-01-01

B-spline based orbital representations are widely used in Quantum Monte Carlo (QMC) simulations of solids, historically taking as much as 50% of the total run time. Random accesses to a large four-dimensional array make it challenging to efficiently utilize caches and wide vector units of modern CPUs. We present node-level optimizations of B-spline evaluations on multi/many-core shared memory processors. To increase SIMD efficiency and bandwidth utilization, we first apply data layout transfo...

A graph-based method for fitting planar B-spline curves with intersections

Directory of Open Access Journals (Sweden)

Pengbo Bo

2016-01-01

Full Text Available The problem of fitting B-spline curves to planar point clouds is studied in this paper. A novel method is proposed to deal with the most challenging case where multiple intersecting curves or curves with self-intersection are necessary for shape representation. A method based on Delauney Triangulation of data points is developed to identify connected components which is also capable of removing outliers. A skeleton representation is utilized to represent the topological structure which is further used to create a weighted graph for deciding the merging of curve segments. Different to existing approaches which utilize local shape information near intersections, our method considers shape characteristics of curve segments in a larger scope and is thus capable of giving more satisfactory results. By fitting each group of data points with a B-spline curve, we solve the problems of curve structure reconstruction from point clouds, as well as the vectorization of simple line drawing images by drawing lines reconstruction.

Local and Global Path Generation for Autonomous Vehicles Using SplinesGeneración Local y Global de Trayectorias para Vehículo Autónomos Usando Splines

Directory of Open Access Journals (Sweden)

Randerson Lemos

2016-05-01

Full Text Available Abstract Context: Before autonomous vehicles being a reality in daily situations, outstanding issues regarding the techniques of autonomous mobility must be solved. Hence, relevant aspects of a path planning for terrestrial vehicles are shown. Method: The approached path planning technique uses splines to generate the global route. For this goal, waypoints obtained from online map services are used. With the global route parametrized in the arc-length, candidate local paths are computed and the optimal one is selected by cost functions. Results: Different routes are used to show that the number and distribution of waypoints are highly correlated to a satisfactory arc-length parameterization of the global route, which is essential to the proper behavior of the path planning technique. Conclusions: The cubic splines approach to the path planning problem successfully generates the global and local paths. Nevertheless, the use of raw data from the online map services showed to be unfeasible due the consistency of the data. Hence, a preprocessing stage of the raw data is proposed to guarantee the well behavior and robustness of the technique.

A modified linear algebraic approach to electron scattering using cubic splines

International Nuclear Information System (INIS)

Kinney, R.A.

1986-01-01

A modified linear algebraic approach to the solution of the Schrodiner equation for low-energy electron scattering is presented. The method uses a piecewise cubic-spline approximation of the wavefunction. Results in the static-potential and the static-exchange approximations for e - +H s-wave scattering are compared with unmodified linear algebraic and variational linear algebraic methods. (author)

Simulating water hammer with corrective smoothed particle method

NARCIS (Netherlands)

Hou, Q.; Kruisbrink, A.C.H.; Tijsseling, A.S.; Keramat, A.

2012-01-01

The corrective smoothed particle method (CSPM) is used to simulate water hammer. The spatial derivatives in the water-hammer equations are approximated by a corrective kernel estimate. For the temporal derivatives, the Euler-forward time integration algorithm is employed. The CSPM results are in

Smooth manifolds

CERN Document Server

Sinha, Rajnikant

2014-01-01

This book offers an introduction to the theory of smooth manifolds, helping students to familiarize themselves with the tools they will need for mathematical research on smooth manifolds and differential geometry. The book primarily focuses on topics concerning differential manifolds, tangent spaces, multivariable differential calculus, topological properties of smooth manifolds, embedded submanifolds, Sard’s theorem and Whitney embedding theorem. It is clearly structured, amply illustrated and includes solved examples for all concepts discussed. Several difficult theorems have been broken into many lemmas and notes (equivalent to sub-lemmas) to enhance the readability of the book. Further, once a concept has been introduced, it reoccurs throughout the book to ensure comprehension. Rank theorem, a vital aspect of smooth manifolds theory, occurs in many manifestations, including rank theorem for Euclidean space and global rank theorem. Though primarily intended for graduate students of mathematics, the book ...

XRLINE, a program to evaluate the crystallite size of supported metal catalysts by single X-ray profile Fourier analysis

International Nuclear Information System (INIS)

Aldea, N.; Indrea, E.

1990-01-01

The computer program presented is based on the Fourier analysis of a singel X-ray diffraction profile. An X-ray diffraction method is presented which is capable of determining the average particle size, microstrain, stacking fault probability as well as the particle size distribution function in crystalline materials. The main numerical methods used are: (i) Smoothing and interpolation by 3rd-order piecewise polynomial functions or by cubic splines with the least squares method; (ii) numerical integration by successive five points formulae and numerical derivative by cubic splines with the least squares method; (iii) estimation of parameters by the weighted least squares method. The results for supported platinum catalysts used in the H/D isotopic exchange reaction are illustrated. (orig.)

Estimation of time- and state-dependent delays and other parameters in functional differential equations

Science.gov (United States)

Murphy, K. A.

1990-01-01

A parameter estimation algorithm is developed which can be used to estimate unknown time- or state-dependent delays and other parameters (e.g., initial condition) appearing within a nonlinear nonautonomous functional differential equation. The original infinite dimensional differential equation is approximated using linear splines, which are allowed to move with the variable delay. The variable delays are approximated using linear splines as well. The approximation scheme produces a system of ordinary differential equations with nice computational properties. The unknown parameters are estimated within the approximating systems by minimizing a least-squares fit-to-data criterion. Convergence theorems are proved for time-dependent delays and state-dependent delays within two classes, which say essentially that fitting the data by using approximations will, in the limit, provide a fit to the data using the original system. Numerical test examples are presented which illustrate the method for all types of delay.

Modeling the dispersion effects of contractile fibers in smooth muscles

Science.gov (United States)

Murtada, Sae-Il; Kroon, Martin; Holzapfel, Gerhard A.

2010-12-01

Micro-structurally based models for smooth muscle contraction are crucial for a better understanding of pathological conditions such as atherosclerosis, incontinence and asthma. It is meaningful that models consider the underlying mechanical structure and the biochemical activation. Hence, a simple mechanochemical model is proposed that includes the dispersion of the orientation of smooth muscle myofilaments and that is capable to capture available experimental data on smooth muscle contraction. This allows a refined study of the effects of myofilament dispersion on the smooth muscle contraction. A classical biochemical model is used to describe the cross-bridge interactions with the thin filament in smooth muscles in which calcium-dependent myosin phosphorylation is the only regulatory mechanism. A novel mechanical model considers the dispersion of the contractile fiber orientations in smooth muscle cells by means of a strain-energy function in terms of one dispersion parameter. All model parameters have a biophysical meaning and may be estimated through comparisons with experimental data. The contraction of the middle layer of a carotid artery is studied numerically. Using a tube the relationships between the internal pressure and the stretches are investigated as functions of the dispersion parameter, which implies a strong influence of the orientation of smooth muscle myofilaments on the contraction response. It is straightforward to implement this model in a finite element code to better analyze more complex boundary-value problems.

Smoothing-Based Relative Navigation and Coded Aperture Imaging

Science.gov (United States)

Saenz-Otero, Alvar; Liebe, Carl Christian; Hunter, Roger C.; Baker, Christopher

2017-01-01

This project will develop an efficient smoothing software for incremental estimation of the relative poses and velocities between multiple, small spacecraft in a formation, and a small, long range depth sensor based on coded aperture imaging that is capable of identifying other spacecraft in the formation. The smoothing algorithm will obtain the maximum a posteriori estimate of the relative poses between the spacecraft by using all available sensor information in the spacecraft formation.This algorithm will be portable between different satellite platforms that possess different sensor suites and computational capabilities, and will be adaptable in the case that one or more satellites in the formation become inoperable. It will obtain a solution that will approach an exact solution, as opposed to one with linearization approximation that is typical of filtering algorithms. Thus, the algorithms developed and demonstrated as part of this program will enhance the applicability of small spacecraft to multi-platform operations, such as precisely aligned constellations and fractionated satellite systems.

Finite nucleus Dirac mean field theory and random phase approximation using finite B splines

International Nuclear Information System (INIS)

McNeil, J.A.; Furnstahl, R.J.; Rost, E.; Shepard, J.R.; Department of Physics, University of Maryland, College Park, Maryland 20742; Department of Physics, University of Colorado, Boulder, Colorado 80309)

1989-01-01

We calculate the finite nucleus Dirac mean field spectrum in a Galerkin approach using finite basis splines. We review the method and present results for the relativistic σ-ω model for the closed-shell nuclei 16 O and 40 Ca. We study the convergence of the method as a function of the size of the basis and the closure properties of the spectrum using an energy-weighted dipole sum rule. We apply the method to the Dirac random-phase-approximation response and present results for the isoscalar 1/sup -/ and 3/sup -/ longitudinal form factors of 16 O and 40 Ca. We also use a B-spline spectral representation of the positive-energy projector to evaluate partial energy-weighted sum rules and compare with nonrelativistic sum rule results

Thin-plate spline analysis of the effects of face mask treatment in children with maxillary retrognathism.

Science.gov (United States)

Chang, Jenny Zwei-Chieng; Liu, Pao-Hsin; Chen, Yi-Jane; Yao, Jane Chung-Chen; Chang, Hong-Po; Chang, Chih-Han; Chang, Frank Hsin-Fu

2006-02-01

Face mask therapy is indicated for growing patients who suffer from maxillary retrognathia. Most previous studies used conventional cephalometric analysis to evaluate the effects of face mask treatment. Cephalometric analysis has been shown to be insufficient for complex craniofacial configurations. The purpose of this study was to investigate changes in the craniofacial structure of children with maxillary retrognathism following face mask treatment by means of thin-plate spline analysis. Thirty children with skeletal Class III malocclusions who had been treated with face masks were compared with a group of 30 untreated gender-matched, age-matched, observation period-matched, and craniofacial configuration-matched subjects. Average geometries, scaled to an equivalent size, were generated by means of Procrustes analysis. Thin-plate spline analysis was then performed for localization of the shape changes. Face mask treatment induced a forward displacement of the maxilla, a counterclockwise rotation of the palatal plane, a horizontal compression of the anterior border of the symphysis and the condylar region, and a downward deformation of the menton. The cranial base exhibited a counterclockwise deformation as a whole. We conclude that thin-plate spline analysis is a valuable supplement to conventional cephalometric analysis.

Alignment of large image series using cubic B-splines tessellation: application to transmission electron microscopy data.

Science.gov (United States)

Dauguet, Julien; Bock, Davi; Reid, R Clay; Warfield, Simon K

2007-01-01

3D reconstruction from serial 2D microscopy images depends on non-linear alignment of serial sections. For some structures, such as the neuronal circuitry of the brain, very large images at very high resolution are necessary to permit reconstruction. These very large images prevent the direct use of classical registration methods. We propose in this work a method to deal with the non-linear alignment of arbitrarily large 2D images using the finite support properties of cubic B-splines. After initial affine alignment, each large image is split into a grid of smaller overlapping sub-images, which are individually registered using cubic B-splines transformations. Inside the overlapping regions between neighboring sub-images, the coefficients of the knots controlling the B-splines deformations are blended, to create a virtual large grid of knots for the whole image. The sub-images are resampled individually, using the new coefficients, and assembled together into a final large aligned image. We evaluated the method on a series of large transmission electron microscopy images and our results indicate significant improvements compared to both manual and affine alignment.

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor

Directory of Open Access Journals (Sweden)

Xin Li

2018-02-01

Full Text Available Dynamic thermal management (DTM mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE by 1.2 ∘ C and increase the signal-to-noise ratio (SNR by 15.8 dB (with a very small average runtime overhead compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times.

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor.

Science.gov (United States)

Li, Xin; Ou, Xingtao; Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

2018-02-02

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘ C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times.

Spline based iterative phase retrieval algorithm for X-ray differential phase contrast radiography.

Science.gov (United States)

Nilchian, Masih; Wang, Zhentian; Thuering, Thomas; Unser, Michael; Stampanoni, Marco

2015-04-20

Differential phase contrast imaging using grating interferometer is a promising alternative to conventional X-ray radiographic methods. It provides the absorption, differential phase and scattering information of the underlying sample simultaneously. Phase retrieval from the differential phase signal is an essential problem for quantitative analysis in medical imaging. In this paper, we formalize the phase retrieval as a regularized inverse problem, and propose a novel discretization scheme for the derivative operator based on B-spline calculus. The inverse problem is then solved by a constrained regularized weighted-norm algorithm (CRWN) which adopts the properties of B-spline and ensures a fast implementation. The method is evaluated with a tomographic dataset and differential phase contrast mammography data. We demonstrate that the proposed method is able to produce phase image with enhanced and higher soft tissue contrast compared to conventional absorption-based approach, which can potentially provide useful information to mammographic investigations.

[Non-rigid medical image registration based on mutual information and thin-plate spline].

Science.gov (United States)

Cao, Guo-gang; Luo, Li-min

2009-01-01

To get precise and complete details, the contrast in different images is needed in medical diagnosis and computer assisted treatment. The image registration is the basis of contrast, but the regular rigid registration does not satisfy the clinic requirements. A non-rigid medical image registration method based on mutual information and thin-plate spline was present. Firstly, registering two images globally based on mutual information; secondly, dividing reference image and global-registered image into blocks and registering them; then getting the thin-plate spline transformation according to the shift of blocks' center; finally, applying the transformation to the global-registered image. The results show that the method is more precise than the global rigid registration based on mutual information and it reduces the complexity of getting control points and satisfy the clinic requirements better by getting control points of the thin-plate transformation automatically.

Robust neural network with applications to credit portfolio data analysis.

Science.gov (United States)

Feng, Yijia; Li, Runze; Sudjianto, Agus; Zhang, Yiyun

2010-01-01

In this article, we study nonparametric conditional quantile estimation via neural network structure. We proposed an estimation method that combines quantile regression and neural network (robust neural network, RNN). It provides good smoothing performance in the presence of outliers and can be used to construct prediction bands. A Majorization-Minimization (MM) algorithm was developed for optimization. Monte Carlo simulation study is conducted to assess the performance of RNN. Comparison with other nonparametric regression methods (e.g., local linear regression and regression splines) in real data application demonstrate the advantage of the newly proposed procedure.

Semiparametric Bernstein–von Mises for the error standard deviation

OpenAIRE

Jonge, de, R.; Zanten, van, J.H.

2013-01-01

We study Bayes procedures for nonparametric regression problems with Gaussian errors, giving conditions under which a Bernstein–von Mises result holds for the marginal posterior distribution of the error standard deviation. We apply our general results to show that a single Bayes procedure using a hierarchical spline-based prior on the regression function and an independent prior on the error variance, can simultaneously achieve adaptive, rate-optimal estimation of a smooth, multivariate regr...

Preference learning with evolutionary Multivariate Adaptive Regression Spline model

DEFF Research Database (Denmark)

Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

2015-01-01

This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

Spline Truncated Multivariabel pada Permodelan Nilai Ujian Nasional di Kabupaten Lombok Barat

Directory of Open Access Journals (Sweden)

Nurul Fitriyani

2017-12-01

Full Text Available Regression model is used to analyze the relationship between dependent variable and independent variable. If the regression curve form is not known, then the regression curve estimation can be done by nonparametric regression approach. This study aimed to investigate the relationship between the value resulted by National Examination and the factors that influence it. The statistical analysis used was multivariable truncated spline, in order to analyze the relationship between variables. The research that has been done showed that the best model obtained by using three knot points. This model produced a minimum GCV value of 44.46 and the value of determination coefficient of 58.627%. The parameter test showed that all factors used were significantly influence the National Examination Score for Senior High School students in West Lombok Regency year 2017. The variables were as follows: National Examination Score of Junior High School; School or Madrasah Examination Score; the value of Student’s Report Card; Student’s House Distance to School; and Number of Student’s Siblings.

Nonlinear Multivariate Spline-Based Control Allocation for High-Performance Aircraft

OpenAIRE

Tol, H.J.; De Visser, C.C.; Van Kampen, E.; Chu, Q.P.

2014-01-01

High performance flight control systems based on the nonlinear dynamic inversion (NDI) principle require highly accurate models of aircraft aerodynamics. In general, the accuracy of the internal model determines to what degree the system nonlinearities can be canceled; the more accurate the model, the better the cancellation, and with that, the higher the performance of the controller. In this paper a new control system is presented that combines NDI with multivariate simplex spline based con...

A Combination of TsHARP and Thin Plate Spline Interpolation for Spatial Sharpening of Thermal Imagery

Directory of Open Access Journals (Sweden)

Xuehong Chen

2014-03-01

Full Text Available There have been many studies and much attention paid to spatial sharpening for thermal imagery. Among them, TsHARP, based on the good correlation between vegetation index and land surface temperature (LST, is regarded as a standard technique because of its operational simplicity and effectiveness. However, as LST is affected by other factors (e.g., soil moisture in the areas with low vegetation cover, these areas cannot be well sharpened by TsHARP. Thin plate spline (TPS is another popular downscaling technique for surface data. It has been shown to be accurate and robust for different datasets; however, it has not yet been attempted in thermal sharpening. This paper proposes to combine the TsHARP and TPS methods to enhance the advantages of each. The spatially explicit errors of these two methods were firstly estimated in theory, and then the results of TPS and TsHARP were combined with the estimation of their errors. The experiments performed across various landscapes and data showed that the proposed combined method performs more robustly and accurately than TsHARP.

Explicit Gaussian quadrature rules for C^1 cubic splines with symmetrically stretched knot sequence

KAUST Repository

Ait-Haddou, Rachid; Barton, Michael; Calo, Victor M.

2015-01-01

We provide explicit expressions for quadrature rules on the space of C^1 cubic splines with non-uniform, symmetrically stretched knot sequences. The quadrature nodes and weights are derived via an explicit recursion that avoids an intervention

Smooth polyhedral surfaces

KAUST Repository

Gü nther, Felix; Jiang, Caigui; Pottmann, Helmut

2017-01-01

Polyhedral surfaces are fundamental objects in architectural geometry and industrial design. Whereas closeness of a given mesh to a smooth reference surface and its suitability for numerical simulations were already studied extensively, the aim of our work is to find and to discuss suitable assessments of smoothness of polyhedral surfaces that only take the geometry of the polyhedral surface itself into account. Motivated by analogies to classical differential geometry, we propose a theory of smoothness of polyhedral surfaces including suitable notions of normal vectors, tangent planes, asymptotic directions, and parabolic curves that are invariant under projective transformations. It is remarkable that seemingly mild conditions significantly limit the shapes of faces of a smooth polyhedral surface. Besides being of theoretical interest, we believe that smoothness of polyhedral surfaces is of interest in the architectural context, where vertices and edges of polyhedral surfaces are highly visible.

Smooth polyhedral surfaces

KAUST Repository

Günther, Felix

2017-03-15

Polyhedral surfaces are fundamental objects in architectural geometry and industrial design. Whereas closeness of a given mesh to a smooth reference surface and its suitability for numerical simulations were already studied extensively, the aim of our work is to find and to discuss suitable assessments of smoothness of polyhedral surfaces that only take the geometry of the polyhedral surface itself into account. Motivated by analogies to classical differential geometry, we propose a theory of smoothness of polyhedral surfaces including suitable notions of normal vectors, tangent planes, asymptotic directions, and parabolic curves that are invariant under projective transformations. It is remarkable that seemingly mild conditions significantly limit the shapes of faces of a smooth polyhedral surface. Besides being of theoretical interest, we believe that smoothness of polyhedral surfaces is of interest in the architectural context, where vertices and edges of polyhedral surfaces are highly visible.

Comparing the accuracy and precision of three techniques used for estimating missing landmarks when reconstructing fossil hominin crania.

Science.gov (United States)

Neeser, Rudolph; Ackermann, Rebecca Rogers; Gain, James

2009-09-01

Various methodological approaches have been used for reconstructing fossil hominin remains in order to increase sample sizes and to better understand morphological variation. Among these, morphometric quantitative techniques for reconstruction are increasingly common. Here we compare the accuracy of three approaches--mean substitution, thin plate splines, and multiple linear regression--for estimating missing landmarks of damaged fossil specimens. Comparisons are made varying the number of missing landmarks, sample sizes, and the reference species of the population used to perform the estimation. The testing is performed on landmark data from individuals of Homo sapiens, Pan troglodytes and Gorilla gorilla, and nine hominin fossil specimens. Results suggest that when a small, same-species fossil reference sample is available to guide reconstructions, thin plate spline approaches perform best. However, if no such sample is available (or if the species of the damaged individual is uncertain), estimates of missing morphology based on a single individual (or even a small sample) of close taxonomic affinity are less accurate than those based on a large sample of individuals drawn from more distantly related extant populations using a technique (such as a regression method) able to leverage the information (e.g., variation/covariation patterning) contained in this large sample. Thin plate splines also show an unexpectedly large amount of error in estimating landmarks, especially over large areas. Recommendations are made for estimating missing landmarks under various scenarios. Copyright 2009 Wiley-Liss, Inc.

Quiet Clean Short-haul Experimental Engine (QCSEE). Ball spline pitch change mechanism design report

Science.gov (United States)

1978-01-01

Detailed design parameters are presented for a variable-pitch change mechanism. The mechanism is a mechanical system containing a ball screw/spline driving two counteracting master bevel gears meshing pinion gears attached to each of 18 fan blades.

SmoothMoves : Smooth pursuits head movements for augmented reality

NARCIS (Netherlands)

Esteves, Augusto; Verweij, David; Suraiya, Liza; Islam, Rasel; Lee, Youryang; Oakley, Ian

2017-01-01

SmoothMoves is an interaction technique for augmented reality (AR) based on smooth pursuits head movements. It works by computing correlations between the movements of on-screen targets and the user's head while tracking those targets. The paper presents three studies. The first suggests that head

Microscopic Model of Automobile Lane-changing Virtual Desire Trajectory by Spline Curves

Directory of Open Access Journals (Sweden)

Yulong Pei

2010-05-01

Full Text Available With the development of microscopic traffic simulation models, they have increasingly become an important tool for transport system analysis and management, which assist the traffic engineer to investigate and evaluate the performance of transport network systems. Lane-changing model is a vital component in any traffic simulation model, which could improve road capacity and reduce vehicles delay so as to reduce the likelihood of congestion occurrence. Therefore, this paper addresses the virtual desire trajectory, a vital part to investigate the behaviour divided into four phases. Based on the boundary conditions, β-spline curves and the corresponding reverse algorithm are introduced firstly. Thus, the relation between the velocity and length of lane-changing is constructed, restricted by the curvature, steering velocity and driving behaviour. Then the virtual desire trajectory curves are presented by Matlab and the error analysis results prove that this proposed description model has higher precision in automobile lane-changing process reconstruction, compared with the surveyed result. KEY WORDS: traffic simulation, lane-changing model, virtual desire trajectory, β-spline curves, driving behaviour

Smoothing a Piecewise-Smooth: An Example from Plankton Population Dynamics

DEFF Research Database (Denmark)

Piltz, Sofia Helena

2016-01-01

In this work we discuss a piecewise-smooth dynamical system inspired by plankton observations and constructed for one predator switching its diet between two different types of prey. We then discuss two smooth formulations of the piecewise-smooth model obtained by using a hyperbolic tangent funct...... function and adding a dimension to the system. We compare model behaviour of the three systems and show an example case where the steepness of the switch is determined from a comparison with data on freshwater plankton....

Fuzzy topological digital space and digital fuzzy spline of electroencephalography during epileptic seizures

Science.gov (United States)

Shah, Mazlina Muzafar; Wahab, Abdul Fatah

2017-08-01

Epilepsy disease occurs because of there is a temporary electrical disturbance in a group of brain cells (nurons). The recording of electrical signals come from the human brain which can be collected from the scalp of the head is called Electroencephalography (EEG). EEG then considered in digital format and in fuzzy form makes it a fuzzy digital space data form. The purpose of research is to identify the area (curve and surface) in fuzzy digital space affected by inside epilepsy seizure in epileptic patient's brain. The main focus for this research is to generalize fuzzy topological digital space, definition and basic operation also the properties by using digital fuzzy set and the operations. By using fuzzy digital space, the theory of digital fuzzy spline can be introduced to replace grid data that has been use previously to get better result. As a result, the flat of EEG can be fuzzy topological digital space and this type of data can be use to interpolate the digital fuzzy spline.

Isogeometric finite element data structures based on Bézier extraction of T-splines

NARCIS (Netherlands)

Scott, M.A.; Borden, M.J.; Verhoosel, C.V.; Sederberg, T.W.; Hughes, T.J.R.

2011-01-01

We develop finite element data structures for T-splines based on Bézier extraction generalizing our previous work for NURBS. As in traditional finite element analysis, the extracted Bézier elements are defined in terms of a fixed set of polynomial basis functions, the so-called Bernstein basis. The

Estimating a Smooth Common Transfer Function with a Panel of Time Series - Inflow of Larvae Cod as an Example

Directory of Open Access Journals (Sweden)

Elizabeth Hansen

2012-07-01

Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} The annual response variable in an ecological monitoring study often relates linearly to the weighted cumulative effect of some daily covariate, after adjusting for other annual covariates. Here we consider the problem of non-parametrically estimating the weights involved in computing the aforementioned cumulative effect, with a panel of short and contemporaneously correlated time series whose responses share the common cumulative effect of a daily covariate. The sequence of (unknown daily weights constitutes the so-called transfer function. Specifically, we consider the problem of estimating a smooth common transfer function shared by a panel of short time series that are contemporaneously correlated. We propose an estimation scheme using a likelihood approach that penalizes the roughness of the common transfer function. We illustrate the proposed method with a simulation study and a biological example of indirectly estimating the spawning date distribution of North Sea cod.

Iteratively re-weighted bi-cubic spline representation of corneal topography and its comparison to the standard methods.

Science.gov (United States)

Zhu, Zhongxia; Janunts, Edgar; Eppig, Timo; Sauer, Tomas; Langenbucher, Achim

2010-01-01

The aim of this study is to represent the corneal anterior surface by utilizing radius and height data extracted from a TMS-2N topographic system with three different mathematical approaches and to simulate the visual performance. An iteratively re-weighted bi-cubic spline method is introduced for the local representation of the corneal surface. For comparison, two standard mathematical global representation approaches are used: the general quadratic function and the higher order Taylor polynomial approach. First, these methods were applied in simulations using three corneal models. Then, two real eye examples were investigated: one eye with regular astigmatism, and one eye which had undergone refractive surgery. A ray-tracing program was developed to evaluate the imaging performance of these examples with each surface representation strategy at the best focus plane. A 6 mm pupil size was chosen for the simulation. The fitting error (deviation) of the presented methods was compared. It was found that the accuracy of the topography representation was worst using the quadratic function and best with bicubic spline. The quadratic function cannot precisely describe the irregular corneal shape. In order to achieve a sub-micron fitting precision, the Taylor polynomial's order selection behaves adaptive to the corneal shape. The bi-cubic spline shows more stable performance. Considering the visual performance, the more precise the cornea representation is, the worse the visual performance is. The re-weighted bi-cubic spline method is a reasonable and stable method for representing the anterior corneal surface in measurements using a Placido-ring-pattern-based corneal topographer. Copyright © 2010. Published by Elsevier GmbH.

Optimal quadrature rules for odd-degree spline spaces and their application to tensor-product-based isogeometric analysis

KAUST Repository

Barton, Michael

2016-03-14

We introduce optimal quadrature rules for spline spaces that are frequently used in Galerkin discretizations to build mass and stiffness matrices. Using the homotopy continuation concept (Bartoň and Calo, 2016) that transforms optimal quadrature rules from source spaces to target spaces, we derive optimal rules for splines defined on finite domains. Starting with the classical Gaussian quadrature for polynomials, which is an optimal rule for a discontinuous odd-degree space, we derive rules for target spaces of higher continuity. We further show how the homotopy methodology handles cases where the source and target rules require different numbers of optimal quadrature points. We demonstrate it by deriving optimal rules for various odd-degree spline spaces, particularly with non-uniform knot sequences and non-uniform multiplicities. We also discuss convergence of our rules to their asymptotic counterparts, that is, the analogues of the midpoint rule of Hughes et al. (2010), that are exact and optimal for infinite domains. For spaces of low continuities, we numerically show that the derived rules quickly converge to their asymptotic counterparts as the weights and nodes of a few boundary elements differ from the asymptotic values.

Optimal quadrature rules for odd-degree spline spaces and their application to tensor-product-based isogeometric analysis

KAUST Repository

Barton, Michael; Calo, Victor M.

2016-01-01

We introduce optimal quadrature rules for spline spaces that are frequently used in Galerkin discretizations to build mass and stiffness matrices. Using the homotopy continuation concept (Bartoň and Calo, 2016) that transforms optimal quadrature rules from source spaces to target spaces, we derive optimal rules for splines defined on finite domains. Starting with the classical Gaussian quadrature for polynomials, which is an optimal rule for a discontinuous odd-degree space, we derive rules for target spaces of higher continuity. We further show how the homotopy methodology handles cases where the source and target rules require different numbers of optimal quadrature points. We demonstrate it by deriving optimal rules for various odd-degree spline spaces, particularly with non-uniform knot sequences and non-uniform multiplicities. We also discuss convergence of our rules to their asymptotic counterparts, that is, the analogues of the midpoint rule of Hughes et al. (2010), that are exact and optimal for infinite domains. For spaces of low continuities, we numerically show that the derived rules quickly converge to their asymptotic counterparts as the weights and nodes of a few boundary elements differ from the asymptotic values.

Discrete quintic spline for boundary value problem in plate deflation theory

Science.gov (United States)

Wong, Patricia J. Y.

2017-07-01

We propose a numerical scheme for a fourth-order boundary value problem arising from plate deflation theory. The scheme involves a discrete quintic spline, and it is of order 4 if a parameter takes a specific value, else it is of order 2. We also present a well known numerical example to illustrate the efficiency of our method as well as to compare with other numerical methods proposed in the literature.

An inductive algorithm for smooth approximation of functions

International Nuclear Information System (INIS)

Kupenova, T.N.

2011-01-01

An inductive algorithm is presented for smooth approximation of functions, based on the Tikhonov regularization method and applied to a specific kind of the Tikhonov parametric functional. The discrepancy principle is used for estimation of the regularization parameter. The principle of heuristic self-organization is applied for assessment of some parameters of the approximating function

Smooth random change point models.

Science.gov (United States)

van den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E

2011-03-15

Change point models are used to describe processes over time that show a change in direction. An example of such a process is cognitive ability, where a decline a few years before death is sometimes observed. A broken-stick model consists of two linear parts and a breakpoint where the two lines intersect. Alternatively, models can be formulated that imply a smooth change between the two linear parts. Change point models can be extended by adding random effects to account for variability between subjects. A new smooth change point model is introduced and examples are presented that show how change point models can be estimated using functions in R for mixed-effects models. The Bayesian inference using WinBUGS is also discussed. The methods are illustrated using data from a population-based longitudinal study of ageing, the Cambridge City over 75 Cohort Study. The aim is to identify how many years before death individuals experience a change in the rate of decline of their cognitive ability. Copyright © 2010 John Wiley & Sons, Ltd.

Numerical simulation of reaction-diffusion systems by modified cubic B-spline differential quadrature method

International Nuclear Information System (INIS)

Mittal, R.C.; Rohila, Rajni

2016-01-01

In this paper, we have applied modified cubic B-spline based differential quadrature method to get numerical solutions of one dimensional reaction-diffusion systems such as linear reaction-diffusion system, Brusselator system, Isothermal system and Gray-Scott system. The models represented by these systems have important applications in different areas of science and engineering. The most striking and interesting part of the work is the solution patterns obtained for Gray Scott model, reminiscent of which are often seen in nature. We have used cubic B-spline functions for space discretization to get a system of ordinary differential equations. This system of ODE’s is solved by highly stable SSP-RK43 method to get solution at the knots. The computed results are very accurate and shown to be better than those available in the literature. Method is easy and simple to apply and gives solutions with less computational efforts.

Thin-plate spline analysis of allometry and sexual dimorphism in the human craniofacial complex.

Science.gov (United States)

Rosas, Antonio; Bastir, Markus

2002-03-01

The relationship between allometry and sexual dimorphism in the human craniofacial complex was analyzed using geometric morphometric methods. Thin-plate splines (TPS) analysis has been applied to investigate the lateral profile of complete adult skulls of known sex. Twenty-nine three-dimensional (3D) craniofacial and mandibular landmark coordinates were recorded from a sample of 52 adult females and 52 adult males of known age and sex. No difference in the influence of size on shape was detected between sexes. Both size and sex had significant influences on shape. As expected, the influence of centroid size on shape (allometry) revealed a shift in the proportions of the neurocranium and the viscerocranium, with a marked allometric variation of the lower face. Adjusted for centroid size, males presented a relatively larger size of the nasopharyngeal space than females. A mean-male TPS transformation revealed a larger piriform aperture, achieved by an increase of the angulation of the nasal bones and a downward rotation of the anterior nasal floor. Male pharynx expansion was also reflected by larger choanae and a more posteriorly inclined basilar part of the occipital clivus. Male muscle attachment sites appeared more pronounced. In contrast, the mean-female TPS transformation was characterized by a relatively small nasal aperture. The occipital clivus inclined anteriorly, and muscle insertion areas became smoothed. Besides these variations, both maxillary and mandibular alveolar regions became prognathic. The sex-specific TPS deformation patterns are hypothesized to be associated with sexual differences in body composition and energetic requirements. Copyright 2002 Wiley-Liss, Inc.

Thin-plate spline analysis of the cranial base in subjects with Class III malocclusion.

Science.gov (United States)

Singh, G D; McNamara, J A; Lozanoff, S

1997-08-01

The role of the cranial base in the emergence of Class III malocclusion is not fully understood. This study determines deformations that contribute to a Class III cranial base morphology, employing thin-plate spline analysis on lateral cephalographs. A total of 73 children of European-American descent aged between 5 and 11 years of age with Class III malocclusion were compared with an equivalent group of subjects with a normal, untreated, Class I molar occlusion. The cephalographs were traced, checked and subdivided into seven age- and sex-matched groups. Thirteen points on the cranial base were identified and digitized. The datasets were scaled to an equivalent size, and statistical analysis indicated significant differences between average Class I and Class III cranial base morphologies for each group. Thin-plate spline analysis indicated that both affine (uniform) and non-affine transformations contribute toward the total spline for each average cranial base morphology at each age group analysed. For non-affine transformations, Partial warps 10, 8 and 7 had high magnitudes, indicating large-scale deformations affecting Bolton point, basion, pterygo-maxillare, Ricketts' point and articulare. In contrast, high eigenvalues associated with Partial warps 1-3, indicating localized shape changes, were found at tuberculum sellae, sella, and the frontonasomaxillary suture. It is concluded that large spatial-scale deformations affect the occipital complex of the cranial base and sphenoidal region, in combination with localized distortions at the frontonasal suture. These deformations may contribute to reduced orthocephalization or deficient flattening of the cranial base antero-posteriorly that, in turn, leads to the formation of a Class III malocclusion.

Water Residence Time estimation by 1D deconvolution in the form of a l2 -regularized inverse problem with smoothness, positivity and causality constraints

Science.gov (United States)

Meresescu, Alina G.; Kowalski, Matthieu; Schmidt, Frédéric; Landais, François

2018-06-01

The Water Residence Time distribution is the equivalent of the impulse response of a linear system allowing the propagation of water through a medium, e.g. the propagation of rain water from the top of the mountain towards the aquifers. We consider the output aquifer levels as the convolution between the input rain levels and the Water Residence Time, starting with an initial aquifer base level. The estimation of Water Residence Time is important for a better understanding of hydro-bio-geochemical processes and mixing properties of wetlands used as filters in ecological applications, as well as protecting fresh water sources for wells from pollutants. Common methods of estimating the Water Residence Time focus on cross-correlation, parameter fitting and non-parametric deconvolution methods. Here we propose a 1D full-deconvolution, regularized, non-parametric inverse problem algorithm that enforces smoothness and uses constraints of causality and positivity to estimate the Water Residence Time curve. Compared to Bayesian non-parametric deconvolution approaches, it has a fast runtime per test case; compared to the popular and fast cross-correlation method, it produces a more precise Water Residence Time curve even in the case of noisy measurements. The algorithm needs only one regularization parameter to balance between smoothness of the Water Residence Time and accuracy of the reconstruction. We propose an approach on how to automatically find a suitable value of the regularization parameter from the input data only. Tests on real data illustrate the potential of this method to analyze hydrological datasets.

Hierarchical and successive approximate registration of the non-rigid medical image based on thin-plate splines

Science.gov (United States)

Hu, Jinyan; Li, Li; Yang, Yunfeng

2017-06-01

The hierarchical and successive approximate registration method of non-rigid medical image based on the thin-plate splines is proposed in the paper. There are two major novelties in the proposed method. First, the hierarchical registration based on Wavelet transform is used. The approximate image of Wavelet transform is selected as the registered object. Second, the successive approximation registration method is used to accomplish the non-rigid medical images registration, i.e. the local regions of the couple images are registered roughly based on the thin-plate splines, then, the current rough registration result is selected as the object to be registered in the following registration procedure. Experiments show that the proposed method is effective in the registration process of the non-rigid medical images.

A Method for Low-Delay Pitch Tracking and Smoothing

DEFF Research Database (Denmark)

Christensen, Mads Græsbøll

2012-01-01

. In the second step, a Kalman filter is used to smooth the estimates and separate the pitch into a slowly varying component and a rapidly varying component. The former represents the mean pitch while the latter represents vibrato, slides and other fast changes. The method is intended for use in applica- tions...... that require fast and sample-by-sample estimates, like tuners for musical instruments, transcription tasks requiring details like vi- brato, and real-time tracking of voiced speech....

Two-component mixture cure rate model with spline estimated nonparametric components.

Science.gov (United States)

Wang, Lu; Du, Pang; Liang, Hua

2012-09-01

In some survival analysis of medical studies, there are often long-term survivors who can be considered as permanently cured. The goals in these studies are to estimate the noncured probability of the whole population and the hazard rate of the susceptible subpopulation. When covariates are present as often happens in practice, to understand covariate effects on the noncured probability and hazard rate is of equal importance. The existing methods are limited to parametric and semiparametric models. We propose a two-component mixture cure rate model with nonparametric forms for both the cure probability and the hazard rate function. Identifiability of the model is guaranteed by an additive assumption that allows no time-covariate interactions in the logarithm of hazard rate. Estimation is carried out by an expectation-maximization algorithm on maximizing a penalized likelihood. For inferential purpose, we apply the Louis formula to obtain point-wise confidence intervals for noncured probability and hazard rate. Asymptotic convergence rates of our function estimates are established. We then evaluate the proposed method by extensive simulations. We analyze the survival data from a melanoma study and find interesting patterns for this study. © 2011, The International Biometric Society.

Examination of influential observations in penalized spline regression

Science.gov (United States)

Türkan, Semra

2013-10-01

In parametric or nonparametric regression models, the results of regression analysis are affected by some anomalous observations in the data set. Thus, detection of these observations is one of the major steps in regression analysis. These observations are precisely detected by well-known influence measures. Pena's statistic is one of them. In this study, Pena's approach is formulated for penalized spline regression in terms of ordinary residuals and leverages. The real data and artificial data are used to see illustrate the effectiveness of Pena's statistic as to Cook's distance on detecting influential observations. The results of the study clearly reveal that the proposed measure is superior to Cook's Distance to detect these observations in large data set.

Accurate B-spline-based 3-D interpolation scheme for digital volume correlation

Science.gov (United States)

Ren, Maodong; Liang, Jin; Wei, Bin

2016-12-01

An accurate and efficient 3-D interpolation scheme, based on sampling theorem and Fourier transform technique, is proposed to reduce the sub-voxel matching error caused by intensity interpolation bias in digital volume correlation. First, the influence factors of the interpolation bias are investigated theoretically using the transfer function of an interpolation filter (henceforth filter) in the Fourier domain. A law that the positional error of a filter can be expressed as a function of fractional position and wave number is found. Then, considering the above factors, an optimized B-spline-based recursive filter, combining B-spline transforms and least squares optimization method, is designed to virtually eliminate the interpolation bias in the process of sub-voxel matching. Besides, given each volumetric image containing different wave number ranges, a Gaussian weighting function is constructed to emphasize or suppress certain of wave number ranges based on the Fourier spectrum analysis. Finally, a novel software is developed and series of validation experiments were carried out to verify the proposed scheme. Experimental results show that the proposed scheme can reduce the interpolation bias to an acceptable level.

Contrast and assimilation in motion perception and smooth pursuit eye movements.

Science.gov (United States)

Spering, Miriam; Gegenfurtner, Karl R

2007-09-01

The analysis of visual motion serves many different functions ranging from object motion perception to the control of self-motion. The perception of visual motion and the oculomotor tracking of a moving object are known to be closely related and are assumed to be controlled by shared brain areas. We compared perceived velocity and the velocity of smooth pursuit eye movements in human observers in a paradigm that required the segmentation of target object motion from context motion. In each trial, a pursuit target and a visual context were independently perturbed simultaneously to briefly increase or decrease in speed. Observers had to accurately track the target and estimate target speed during the perturbation interval. Here we show that the same motion signals are processed in fundamentally different ways for perception and steady-state smooth pursuit eye movements. For the computation of perceived velocity, motion of the context was subtracted from target motion (motion contrast), whereas pursuit velocity was determined by the motion average (motion assimilation). We conclude that the human motion system uses these computations to optimally accomplish different functions: image segmentation for object motion perception and velocity estimation for the control of smooth pursuit eye movements.

Gradient approach to quantify the gradation smoothness for output media

Science.gov (United States)

Kim, Youn Jin; Bang, Yousun; Choh, Heui-Keun

2010-01-01

We aim to quantify the perception of color gradation smoothness using objectively measurable properties. We propose a model to compute the smoothness of hardcopy color-to-color gradations. It is a gradient-based method that can be determined as a function of the 95th percentile of second derivative for the tone-jump estimator and the fifth percentile of first derivative for the tone-clipping estimator. Performance of the model and a previously suggested method were psychophysically appreciated, and their prediction accuracies were compared to each other. Our model showed a stronger Pearson correlation to the corresponding visual data, and the magnitude of the Pearson correlation reached up to 0.87. Its statistical significance was verified through analysis of variance. Color variations of the representative memory colors-blue sky, green grass and Caucasian skin-were rendered as gradational scales and utilized as the test stimuli.

Splines and polynomial tools for flatness-based constrained motion planning

Science.gov (United States)

Suryawan, Fajar; De Doná, José; Seron, María

2012-08-01

This article addresses the problem of trajectory planning for flat systems with constraints. Flat systems have the useful property that the input and the state can be completely characterised by the so-called flat output. We propose a spline parametrisation for the flat output, the performance output, the states and the inputs. Using this parametrisation the problem of constrained trajectory planning can be cast into a simple quadratic programming problem. An important result is that the B-spline parametrisation used gives exact results for constrained linear continuous-time system. The result is exact in the sense that the constrained signal can be made arbitrarily close to the boundary without having intersampling issues (as one would have in sampled-data systems). Simulation examples are presented, involving the generation of rest-to-rest trajectories. In addition, an experimental result of the method is also presented, where two methods to generate trajectories for a magnetic-levitation (maglev) system in the presence of constraints are compared and each method's performance is discussed. The first method uses the nonlinear model of the plant, which turns out to belong to the class of flat systems. The second method uses a linearised version of the plant model around an operating point. In every case, a continuous-time description is used. The experimental results on a real maglev system reported here show that, in most scenarios, the nonlinear and linearised models produce almost similar, indistinguishable trajectories.

Mass transfer from smooth alabaster surfaces in turbulent flows

Science.gov (United States)

Opdyke, Bradley N.; Gust, Giselher; Ledwell, James R.

1987-11-01

The mass transfer velocity for alabaster plates in smooth-wall turbulent flow is found to vary with the friction velocity according to an analytic solution of the advective diffusion equation. Deployment of alabaster plates on the sea floor can perhaps be used to estimate the viscous stress, and transfer velocities for other species.

A fourth order spline collocation approach for a business cycle model

Science.gov (United States)

Sayfy, A.; Khoury, S.; Ibdah, H.

2013-10-01

A collocation approach, based on a fourth order cubic B-splines is presented for the numerical solution of a Kaleckian business cycle model formulated by a nonlinear delay differential equation. The equation is approximated and the nonlinearity is handled by employing an iterative scheme arising from Newton's method. It is shown that the model exhibits a conditionally dynamical stable cycle. The fourth-order rate of convergence of the scheme is verified numerically for different special cases.

Estimating monthly temperature using point based interpolation techniques

Science.gov (United States)

Saaban, Azizan; Mah Hashim, Noridayu; Murat, Rusdi Indra Zuhdi

2013-04-01

This paper discusses the use of point based interpolation to estimate the value of temperature at an unallocated meteorology stations in Peninsular Malaysia using data of year 2010 collected from the Malaysian Meteorology Department. Two point based interpolation methods which are Inverse Distance Weighted (IDW) and Radial Basis Function (RBF) are considered. The accuracy of the methods is evaluated using Root Mean Square Error (RMSE). The results show that RBF with thin plate spline model is suitable to be used as temperature estimator for the months of January and December, while RBF with multiquadric model is suitable to estimate the temperature for the rest of the months.

The Asymptotic Behavior of Particle Size Distribution Undergoing Brownian Coagulation Based on the Spline-Based Method and TEMOM Model

Directory of Open Access Journals (Sweden)

Qing He

2018-01-01

Full Text Available In this paper, the particle size distribution is reconstructed using finite moments based on a converted spline-based method, in which the number of linear system of equations to be solved reduced from 4m × 4m to (m + 3 × (m + 3 for (m + 1 nodes by using cubic spline compared to the original method. The results are verified by comparing with the reference firstly. Then coupling with the Taylor-series expansion moment method, the evolution of particle size distribution undergoing Brownian coagulation and its asymptotic behavior are investigated.

Classification of smooth Fano polytopes

DEFF Research Database (Denmark)

Øbro, Mikkel

A simplicial lattice polytope containing the origin in the interior is called a smooth Fano polytope, if the vertices of every facet is a basis of the lattice. The study of smooth Fano polytopes is motivated by their connection to toric varieties. The thesis concerns the classification of smooth...... Fano polytopes up to isomorphism. A smooth Fano -polytope can have at most vertices. In case of vertices an explicit classification is known. The thesis contains the classification in case of vertices. Classifications of smooth Fano -polytopes for fixed exist only for . In the thesis an algorithm...... for the classification of smooth Fano -polytopes for any given is presented. The algorithm has been implemented and used to obtain the complete classification for ....

Optimal HRF and smoothing parameters for fMRI time series within an autoregressive modeling framework.

Science.gov (United States)

Galka, Andreas; Siniatchkin, Michael; Stephani, Ulrich; Groening, Kristina; Wolff, Stephan; Bosch-Bayard, Jorge; Ozaki, Tohru

2010-12-01

The analysis of time series obtained by functional magnetic resonance imaging (fMRI) may be approached by fitting predictive parametric models, such as nearest-neighbor autoregressive models with exogeneous input (NNARX). As a part of the modeling procedure, it is possible to apply instantaneous linear transformations to the data. Spatial smoothing, a common preprocessing step, may be interpreted as such a transformation. The autoregressive parameters may be constrained, such that they provide a response behavior that corresponds to the canonical haemodynamic response function (HRF). We present an algorithm for estimating the parameters of the linear transformations and of the HRF within a rigorous maximum-likelihood framework. Using this approach, an optimal amount of both the spatial smoothing and the HRF can be estimated simultaneously for a given fMRI data set. An example from a motor-task experiment is discussed. It is found that, for this data set, weak, but non-zero, spatial smoothing is optimal. Furthermore, it is demonstrated that activated regions can be estimated within the maximum-likelihood framework.

On Improving Density Estimators which are not Bona Fide Functions

OpenAIRE

Gajek, Leslaw

1986-01-01

In order to improve the rate of decrease of the IMSE for nonparametric kernel density estimators with nonrandom bandwidth beyond $O(n^{-4/5})$ all current methods must relax the constraint that the density estimate be a bona fide function, that is, be nonnegative and integrate to one. In this paper we show how to achieve similar improvement without relaxing any of these constraints. The method can also be applied for orthogonal series, adaptive orthogonal series, spline, jackknife, and other ...

B-spline goal-oriented error estimators for geometrically nonlinear rods

Science.gov (United States)

2011-04-01

respectively, for the output functionals q2–q4 (linear and nonlinear with the trigonometric functions sine and cosine) in all the tests considered...of the errors resulting from the linear, quadratic and nonlinear (with trigonometric functions sine and cosine) outputs and for p = 1, 2. If the... Portugal . References [1] A.T. Adams. Sobolev Spaces. Academic Press, Boston, 1975. [2] M. Ainsworth and J.T. Oden. A posteriori error estimation in

A meshless scheme for partial differential equations based on multiquadric trigonometric B-spline quasi-interpolation

International Nuclear Information System (INIS)

Gao Wen-Wu; Wang Zhi-Gang

2014-01-01

Based on the multiquadric trigonometric B-spline quasi-interpolant, this paper proposes a meshless scheme for some partial differential equations whose solutions are periodic with respect to the spatial variable. This scheme takes into account the periodicity of the analytic solution by using derivatives of a periodic quasi-interpolant (multiquadric trigonometric B-spline quasi-interpolant) to approximate the spatial derivatives of the equations. Thus, it overcomes the difficulties of the previous schemes based on quasi-interpolation (requiring some additional boundary conditions and yielding unwanted high-order discontinuous points at the boundaries in the spatial domain). Moreover, the scheme also overcomes the difficulty of the meshless collocation methods (i.e., yielding a notorious ill-conditioned linear system of equations for large collocation points). The numerical examples that are presented at the end of the paper show that the scheme provides excellent approximations to the analytic solutions. (general)

Inverting travel times with a triplication. [spline fitting technique applied to lunar seismic data reduction

Science.gov (United States)

Jarosch, H. S.

1982-01-01

A method based on the use of constrained spline fits is used to overcome the difficulties arising when body-wave data in the form of T-delta are reduced to the tau-p form in the presence of cusps. In comparison with unconstrained spline fits, the method proposed here tends to produce much smoother models which lie approximately in the middle of the bounds produced by the extremal method. The method is noniterative and, therefore, computationally efficient. The method is applied to the lunar seismic data, where at least one triplication is presumed to occur in the P-wave travel-time curve. It is shown, however, that because of an insufficient number of data points for events close to the antipode of the center of the lunar network, the present analysis is not accurate enough to resolve the problem of a possible lunar core.

Gauss-Galerkin quadrature rules for quadratic and cubic spline spaces and their application to isogeometric analysis

KAUST Repository

Barton, Michael; Calo, Victor M.

2016-01-01

We introduce Gaussian quadrature rules for spline spaces that are frequently used in Galerkin discretizations to build mass and stiffness matrices. By definition, these spaces are of even degrees. The optimal quadrature rules we recently derived

Application of Data Smoothing Method in Signal Processing for Vortex Flow Meters

Directory of Open Access Journals (Sweden)

Zhang Jun

2017-01-01

Full Text Available Vortex flow meter is typical flow measure equipment. Its measurement output signals can easily be impaired by environmental conditions. In order to obtain an improved estimate of the time-averaged velocity from the vortex flow meter, a signal filter method is applied in this paper. The method is based on a simple Savitzky-Golay smoothing filter algorithm. According with the algorithm, a numerical program is developed in Python with the scientific library numerical Numpy. Two sample data sets are processed through the program. The results demonstrate that the processed data is available accepted compared with the original data. The improved data of the time-averaged velocity is obtained within smoothing curves. Finally the simple data smoothing program is useable and stable for this filter.

PetIGA-MF: a multi-field high-performance toolbox for structure-preserving B-splines spaces

KAUST Repository

Sarmiento, Adel; Cô rtes, A.M.A.; Garcia, D.A.; Dalcin, Lisandro; Collier, N.; Calo, V.M.

2016-01-01

We describe a high-performance solution framework for isogeometric discrete differential forms based on B-splines: PetIGA-MF. Built on top of PetIGA, an open-source library we have built and developed over the last decade, PetIGA-MF is a general

Evaluation of optimization methods for nonrigid medical image registration using mutual information and B-splines

NARCIS (Netherlands)

Klein, S.; Staring, M.; Pluim, J.P.W.

2007-01-01

A popular technique for nonrigid registration of medical images is based on the maximization of their mutual information, in combination with a deformation field parameterized by cubic B-splines. The coordinate mapping that relates the two images is found using an iterative optimization procedure.

Robust estimation of the expected survival probabilities from high-dimensional Cox models with biomarker-by-treatment interactions in randomized clinical trials

Directory of Open Access Journals (Sweden)

Nils Ternès

2017-05-01

Full Text Available Abstract Background Thanks to the advances in genomics and targeted treatments, more and more prediction models based on biomarkers are being developed to predict potential benefit from treatments in a randomized clinical trial. Despite the methodological framework for the development and validation of prediction models in a high-dimensional setting is getting more and more established, no clear guidance exists yet on how to estimate expected survival probabilities in a penalized model with biomarker-by-treatment interactions. Methods Based on a parsimonious biomarker selection in a penalized high-dimensional Cox model (lasso or adaptive lasso, we propose a unified framework to: estimate internally the predictive accuracy metrics of the developed model (using double cross-validation; estimate the individual survival probabilities at a given timepoint; construct confidence intervals thereof (analytical or bootstrap; and visualize them graphically (pointwise or smoothed with spline. We compared these strategies through a simulation study covering scenarios with or without biomarker effects. We applied the strategies to a large randomized phase III clinical trial that evaluated the effect of adding trastuzumab to chemotherapy in 1574 early breast cancer patients, for which the expression of 462 genes was measured. Results In our simulations, penalized regression models using the adaptive lasso estimated the survival probability of new patients with low bias and standard error; bootstrapped confidence intervals had empirical coverage probability close to the nominal level across very different scenarios. The double cross-validation performed on the training data set closely mimicked the predictive accuracy of the selected models in external validation data. We also propose a useful visual representation of the expected survival probabilities using splines. In the breast cancer trial, the adaptive lasso penalty selected a prediction model with 4

Numerical Solution of the Blasius Viscous Flow Problem by Quartic B-Spline Method

Directory of Open Access Journals (Sweden)

Hossein Aminikhah

2016-01-01

Full Text Available A numerical method is proposed to study the laminar boundary layer about a flat plate in a uniform stream of fluid. The presented method is based on the quartic B-spline approximations with minimizing the error L2-norm. Theoretical considerations are discussed. The computed results are compared with some numerical results to show the efficiency of the proposed approach.

Estimation of arterial arrival time and cerebral blood flow from QUASAR arterial spin labeling using stable spline.

Science.gov (United States)

Castellaro, Marco; Peruzzo, Denis; Mehndiratta, Amit; Pillonetto, Gianluigi; Petersen, Esben Thade; Golay, Xavier; Chappell, Michael A; Bertoldo, Alessandra

2015-12-01

QUASAR arterial spin labeling (ASL) permits the application of deconvolution approaches for the absolute quantification of cerebral perfusion. Currently, oscillation index regularized singular value decomposition (oSVD) combined with edge-detection (ED) is the most commonly used method. Its major drawbacks are nonphysiological oscillations in the impulse response function and underestimation of perfusion. The aim of this work is to introduce a novel method to overcome these limitations. A system identification method, stable spline (SS), was extended to address ASL peculiarities such as the delay in arrival of the arterial blood in the tissue. The proposed framework was compared with oSVD + ED in both simulated and real data. SS was used to investigate the validity of using a voxel-wise tissue T1 value instead of using a single global value (of blood T1 ). SS outperformed oSVD + ED in 79.9% of simulations. When applied to real data, SS exhibited a physiologically realistic range for perfusion and a higher mean value with respect to oSVD + ED (55.5 ± 9.5 SS, 34.9 ± 5.2 oSVD + ED mL/100 g/min). SS can represent an alternative to oSVD + ED for the quantification of QUASAR ASL data. Analysis of the retrieved impulse response function revealed that using a voxel wise tissue T1 might be suboptimal. © 2014 Wiley Periodicals, Inc.

PEMODELAN B-SPLINE DAN MARS PADA NILAI UJIAN MASUK TERHADAP IPK MAHASISWA JURUSAN DISAIN KOMUNIKASI VISUAL UK. PETRA SURABAYA

Directory of Open Access Journals (Sweden)

I Nyoman Budiantara

2006-01-01

Full Text Available Regression analysis is constructed for capturing the influences of independent variables to dependent ones. It can be done by looking at the relationship between those variables. This task of approximating the mean function can be done essentially in two ways. The quiet often use parametric approach is to assume that the mean curve has some prespecified functional forms. Alternatively, nonparametric approach, .i.e., without reference to a specific form, is used when there is no information of the regression function form (Haerdle, 1990. Therefore nonparametric approach has more flexibilities than the parametric one. The aim of this research is to find the best fit model that captures relationship between admission test score to the GPA. This particular data was taken from the Department of Design Communication and Visual, Petra Christian University, Surabaya for year 1999. Those two approaches were used here. In the parametric approach, we use simple linear, quadric cubic regression, and in the nonparametric ones, we use B-Spline and Multivariate Adaptive Regression Splines (MARS. Overall, the best model was chosen based on the maximum determinant coefficient. However, for MARS, the best model was chosen based on the GCV, minimum MSE, maximum determinant coefficient. Abstract in Bahasa Indonesia : Analisa regresi digunakan untuk melihat pengaruh variabel independen terhadap variabel dependent dengan terlebih dulu melihat pola hubungan variabel tersebut. Hal ini dapat dilakukan dengan melalui dua pendekatan. Pendekatan yang paling umum dan seringkali digunakan adalah pendekatan parametrik. Pendekatan parametrik mengasumsikan bentuk model sudah ditentukan. Apabila tidak ada informasi apapun tentang bentuk dari fungsi regresi, maka pendekatan yang digunakan adalah pendekatan nonparametrik. (Haerdle, 1990. Karena pendekatan tidak tergantung pada asumsi bentuk kurva tertentu, sehingga memberikan fleksibelitas yang lebih besar. Tujuan penelitian ini

Smooth Bézier surfaces over unstructured quadrilateral meshes

CERN Document Server

Bercovier, Michel

2017-01-01

Using an elegant mixture of geometry, graph theory and linear analysis, this monograph completely solves a problem lying at the interface of Isogeometric Analysis (IgA) and Finite Element Methods (FEM). The recent explosion of IgA, strongly tying Computer Aided Geometry Design to Analysis, does not easily apply to the rich variety of complex shapes that engineers have to design and analyse. Therefore new developments have studied the extension of IgA to unstructured unions of meshes, similar to those one can find in FEM. The following problem arises: given an unstructured planar quadrilateral mesh, construct a C1-surface, by piecewise Bézier or B-Spline patches defined over this mesh. This problem is solved for C1-surfaces defined over plane bilinear Bézier patches, the corresponding results for B-Splines then being simple consequences. The method can be extended to higher-order quadrilaterals and even to three dimensions, and the most recent developments in this direction are also mentioned here.

A New Image Processing Procedure Integrating PCI-RPC and ArcGIS-Spline Tools to Improve the Orthorectification Accuracy of High-Resolution Satellite Imagery

Directory of Open Access Journals (Sweden)

Hongying Zhang

2016-10-01

Full Text Available Given the low accuracy of the traditional remote sensing image processing software when orthorectifying satellite images that cover mountainous areas, and in order to make a full use of mutually compatible and complementary characteristics of the remote sensing image processing software PCI-RPC (Rational Polynomial Coefficients and ArcGIS-Spline, this study puts forward a new operational and effective image processing procedure to improve the accuracy of image orthorectification. The new procedure first processes raw image data into an orthorectified image using PCI with RPC model (PCI-RPC, and then the orthorectified image is further processed using ArcGIS with the Spline tool (ArcGIS-Spline. We used the high-resolution CBERS-02C satellite images (HR1 and HR2 scenes with a pixel size of 2 m acquired from Yangyuan County in Hebei Province of China to test the procedure. In this study, when separately using PCI-RPC and ArcGIS-Spline tools directly to process the HR1/HR2 raw images, the orthorectification accuracies (root mean square errors, RMSEs for HR1/HR2 images were 2.94 m/2.81 m and 4.65 m/4.41 m, respectively. However, when using our newly proposed procedure, the corresponding RMSEs could be reduced to 1.10 m/1.07 m. The experimental results demonstrated that the new image processing procedure which integrates PCI-RPC and ArcGIS-Spline tools could significantly improve image orthorectification accuracy. Therefore, in terms of practice, the new procedure has the potential to use existing software products to easily improve image orthorectification accuracy.

A spectral/B-spline method for the Navier-Stokes equations in unbounded domains

International Nuclear Information System (INIS)

Dufresne, L.; Dumas, G.

2003-01-01

The numerical method presented in this paper aims at solving the incompressible Navier-Stokes equations in unbounded domains. The problem is formulated in cylindrical coordinates and the method is based on a Galerkin approximation scheme that makes use of vector expansions that exactly satisfy the continuity constraint. More specifically, the divergence-free basis vector functions are constructed with Fourier expansions in the θ and z directions while mapped B-splines are used in the semi-infinite radial direction. Special care has been taken to account for the particular analytical behaviors at both end points r=0 and r→∞. A modal reduction algorithm has also been implemented in the azimuthal direction, allowing for a relaxation of the CFL constraint on the timestep size and a possibly significant reduction of the number of DOF. The time marching is carried out using a mixed quasi-third order scheme. Besides the advantages of a divergence-free formulation and a quasi-spectral convergence, the local character of the B-splines allows for a great flexibility in node positioning while keeping narrow bandwidth matrices. Numerical tests show that the present method compares advantageously with other similar methodologies using purely global expansions

APPROX, 1-D and 2-D Function Approximation by Polynomials, Splines, Finite Elements Method

International Nuclear Information System (INIS)

Tollander, Bengt

1975-01-01

1 - Nature of physical problem solved: Approximates one- and two- dimensional functions using different forms of the approximating function, as polynomials, rational functions, Splines and (or) the finite element method. Different kinds of transformations of the dependent and (or) the independent variables can easily be made by data cards using a FORTRAN-like language. 2 - Method of solution: Approximations by polynomials, Splines and (or) the finite element method are made in L2 norm using the least square method by which the answer is directly given. For rational functions in one dimension the result given in L(infinite) norm is achieved by iterations moving the zero points of the error curve. For rational functions in two dimensions, the norm is L2 and the result is achieved by iteratively changing the coefficients of the denominator and then solving the coefficients of the numerator by the least square method. The transformation of the dependent and (or) independent variables is made by compiling the given transform data card(s) to an array of integers from which the transformation can be made

The high-level error bound for shifted surface spline interpolation

OpenAIRE

Luh, Lin-Tian

2006-01-01

Radial function interpolation of scattered data is a frequently used method for multivariate data fitting. One of the most frequently used radial functions is called shifted surface spline, introduced by Dyn, Levin and Rippa in \\cite{Dy1} for $R^{2}$. Then it's extended to $R^{n}$ for $n\\geq 1$. Many articles have studied its properties, as can be seen in \\cite{Bu,Du,Dy2,Po,Ri,Yo1,Yo2,Yo3,Yo4}. When dealing with this function, the most commonly used error bounds are the one raised by Wu and S...

C1 Rational Quadratic Trigonometric Interpolation Spline for Data Visualization

Directory of Open Access Journals (Sweden)

Shengjun Liu

2015-01-01

Full Text Available A new C1 piecewise rational quadratic trigonometric spline with four local positive shape parameters in each subinterval is constructed to visualize the given planar data. Constraints are derived on these free shape parameters to generate shape preserving interpolation curves for positive and/or monotonic data sets. Two of these shape parameters are constrained while the other two can be set free to interactively control the shape of the curves. Moreover, the order of approximation of developed interpolant is investigated as O(h3. Numeric experiments demonstrate that our method can construct nice shape preserving interpolation curves efficiently.

Bayesian Exponential Smoothing.

OpenAIRE

Forbes, C.S.; Snyder, R.D.; Shami, R.S.

2000-01-01

In this paper, a Bayesian version of the exponential smoothing method of forecasting is proposed. The approach is based on a state space model containing only a single source of error for each time interval. This model allows us to improve current practices surrounding exponential smoothing by providing both point predictions and measures of the uncertainty surrounding them.

Reproducción espectral de valores triestímulo mediante descripciones B-Spline: evaluación del error en el color

OpenAIRE

Pizarro Bondia, Carlos; Arasa Marti, Jose; de Lasarte, Marta; Pujol Ramo, Jaume; Arjona Carbonell, Mª Montserrat; Vilaseca Ricart, Meritxell

2008-01-01

La principal motivación de este trabajo es la búsqueda de una única expresión matemática que permita reproducir distribuciones espectrales de forma general. Para ello se consideran polinomios B-Spline rotacionales de segundo orden como expresión matemática base para dicha reproducción. El objetivo fundamental de este trabajo es, por tanto, la determinación de los coeficientes de los polinomios B-Spline que permitan reproducir distribuciones espectrales, así como la evaluación de la exactit...

Improving the resolution for Lamb wave testing via a smoothed Capon algorithm

Science.gov (United States)

Cao, Xuwei; Zeng, Liang; Lin, Jing; Hua, Jiadong

2018-04-01

Lamb wave testing is promising for damage detection and evaluation in large-area structures. The dispersion of Lamb waves is often unavoidable, restricting testing resolution and making the signal hard to interpret. A smoothed Capon algorithm is proposed in this paper to estimate the accurate path length of each wave packet. In the algorithm, frequency domain whitening is firstly used to obtain the transfer function in the bandwidth of the excitation pulse. Subsequently, wavenumber domain smoothing is employed to reduce the correlation between wave packets. Finally, the path lengths are determined by distance domain searching based on the Capon algorithm. Simulations are applied to optimize the number of smoothing times. Experiments are performed on an aluminum plate consisting of two simulated defects. The results demonstrate that spatial resolution is improved significantly by the proposed algorithm.

Spline-based automatic path generation of welding robot

Institute of Scientific and Technical Information of China (English)

Niu Xuejuan; Li Liangyu

2007-01-01

This paper presents a flexible method for the representation of welded seam based on spline interpolation. In this method, the tool path of welding robot can be generated automatically from a 3D CAD model. This technique has been implemented and demonstrated in the FANUC Arc Welding Robot Workstation. According to the method, a software system is developed using VBA of SolidWorks 2006. It offers an interface between SolidWorks and ROBOGUIDE, the off-line programming software of FANUC robot. It combines the strong modeling function of the former and the simulating function of the latter. It also has the capability of communication with on-line robot. The result data have shown its high accuracy and strong reliability in experiments. This method will improve the intelligence and the flexibility of the welding robot workstation.

Anti-smooth muscle antibody

Science.gov (United States)

... gov/ency/article/003531.htm Anti-smooth muscle antibody To use the sharing features on this page, please enable JavaScript. Anti-smooth muscle antibody is a blood test that detects the presence ...

Smooth functors vs. differential forms

NARCIS (Netherlands)

Schreiber, U.; Waldorf, K.

2011-01-01

We establish a relation between smooth 2-functors defined on the path 2-groupoid of a smooth manifold and differential forms on this manifold. This relation can be understood as a part of a dictionary between fundamental notions from category theory and differential geometry. We show that smooth

Internal Friction And Instabilities Of Rotors

Science.gov (United States)

Walton, J.; Artiles, A.; Lund, J.; Dill, J.; Zorzi, E.

1992-01-01

Report describes study of effects of internal friction on dynamics of rotors prompted by concern over instabilities in rotors of turbomachines. Theoretical and experimental studies described. Theoretical involved development of nonlinear mathematical models of internal friction in three joints found in turbomachinery - axial splines, Curvic(TM) splines, and interference fits between smooth cylindrical surfaces. Experimental included traction tests to determine the coefficients of friction of rotor alloys at various temperatures, bending-mode-vibration tests of shafts equipped with various joints and rotordynamic tests of shafts with axial-spline and interference-fit joints.

Effects of Tightening Torque on Dynamic Characteristics of Low Pressure Rotors Connected by a Spline Coupling

Institute of Scientific and Technical Information of China (English)

Chen Xi; Liao M ingfu; Li Quankun

2017-01-01

A rotor dynamic model is built up for investigating the effects of tightening torque on dynamic character-istics of low pressure rotors connected by a spline coupling .The experimental rotor system is established using a fluted disk and a speed sensor which is applied in an actual aero engine for speed measurement .Through simulating calculation and experiments ,the effects of tightening torque on the dynamic characteristics of the rotor system con-nected by a spline coupling including critical speeds ,vibration modes and unbalance responses are analyzed .The results show that when increasing the tightening torque ,the first two critical speeds and the amplitudes of unbal-ance response gradually increase in varying degrees while the vibration modes are essentially unchanged .In addi-tion ,changing axial and circumferential positions of the mass unbalance can lead to various amplitudes of unbalance response and even the rates of change .

Application of thin-plate spline transformations to finite element models, or, how to turn a bog turtle into a spotted turtle to analyze both.

Science.gov (United States)

Stayton, C Tristan

2009-05-01

Finite element (FE) models are popular tools that allow biologists to analyze the biomechanical behavior of complex anatomical structures. However, the expense and time required to create models from specimens has prevented comparative studies from involving large numbers of species. A new method is presented for transforming existing FE models using geometric morphometric methods. Homologous landmark coordinates are digitized on the FE model and on a target specimen into which the FE model is being transformed. These coordinates are used to create a thin-plate spline function and coefficients, which are then applied to every node in the FE model. This function smoothly interpolates the location of points between landmarks, transforming the geometry of the original model to match the target. This new FE model is then used as input in FE analyses. This procedure is demonstrated with turtle shells: a Glyptemys muhlenbergii model is transformed into Clemmys guttata and Actinemys marmorata models. Models are loaded and the resulting stresses are compared. The validity of the models is tested by crushing actual turtle shells in a materials testing machine and comparing those results to predictions from FE models. General guidelines, cautions, and possibilities for this procedure are also presented.

Cubic spline numerical solution of an ablation problem with convective backface cooling

Science.gov (United States)

Lin, S.; Wang, P.; Kahawita, R.

1984-08-01

An implicit numerical technique using cubic splines is presented for solving an ablation problem on a thin wall with convective cooling. A non-uniform computational mesh with 6 grid points has been used for the numerical integration. The method has been found to be computationally efficient, providing for the care under consideration of an overall error of about 1 percent. The results obtained indicate that the convective cooling is an important factor in reducing the ablation thickness.

Thin-plate spline (TPS) graphical analysis of the mandible on cephalometric radiographs.

Science.gov (United States)

Chang, H P; Liu, P H; Chang, H F; Chang, C H

2002-03-01

We describe two cases of Class III malocclusion with and without orthodontic treatment. A thin-plate spline (TPS) analysis of lateral cephalometric radiographs was used to visualize transformations of the mandible. The actual sites of mandibular skeletal change are not detectable with conventional cephalometric analysis. These case analyses indicate that specific patterns of mandibular transformation are associated with Class III malocclusion with or without orthopaedic therapy, and visualization of these deformations is feasible using TPS graphical analysis.

Quiet Clean Short-Haul Experimental Engine (QCSEE) ball spline pitch-change mechanism whirligig test report

Science.gov (United States)

1978-01-01

The component testing of a ball spline variable pitch mechanism is described including a whirligig test. The variable pitch actuator successfully completed all planned whirligig tests including a fifty cycle endurance test at actuation rates up to 125 deg per second at up to 102 percent fan speed (3400 rpm).

Smoothness in Binomial Edge Ideals

Directory of Open Access Journals (Sweden)

Hamid Damadi

2016-06-01

Full Text Available In this paper we study some geometric properties of the algebraic set associated to the binomial edge ideal of a graph. We study the singularity and smoothness of the algebraic set associated to the binomial edge ideal of a graph. Some of these algebraic sets are irreducible and some of them are reducible. If every irreducible component of the algebraic set is smooth we call the graph an edge smooth graph, otherwise it is called an edge singular graph. We show that complete graphs are edge smooth and introduce two conditions such that the graph G is edge singular if and only if it satisfies these conditions. Then, it is shown that cycles and most of trees are edge singular. In addition, it is proved that complete bipartite graphs are edge smooth.

Ensemble Kalman filtering with one-step-ahead smoothing

KAUST Repository

Raboudi, Naila F.

2018-01-11

The ensemble Kalman filter (EnKF) is widely used for sequential data assimilation. It operates as a succession of forecast and analysis steps. In realistic large-scale applications, EnKFs are implemented with small ensembles and poorly known model error statistics. This limits their representativeness of the background error covariances and, thus, their performance. This work explores the efficiency of the one-step-ahead (OSA) smoothing formulation of the Bayesian filtering problem to enhance the data assimilation performance of EnKFs. Filtering with OSA smoothing introduces an updated step with future observations, conditioning the ensemble sampling with more information. This should provide an improved background ensemble in the analysis step, which may help to mitigate the suboptimal character of EnKF-based methods. Here, the authors demonstrate the efficiency of a stochastic EnKF with OSA smoothing for state estimation. They then introduce a deterministic-like EnKF-OSA based on the singular evolutive interpolated ensemble Kalman (SEIK) filter. The authors show that the proposed SEIK-OSA outperforms both SEIK, as it efficiently exploits the data twice, and the stochastic EnKF-OSA, as it avoids observational error undersampling. They present extensive assimilation results from numerical experiments conducted with the Lorenz-96 model to demonstrate SEIK-OSA’s capabilities.

Is Middle-Upper Arm Circumference "normally" distributed? Secondary data analysis of 852 nutrition surveys.

Science.gov (United States)

Frison, Severine; Checchi, Francesco; Kerac, Marko; Nicholas, Jennifer

2016-01-01

Wasting is a major public health issue throughout the developing world. Out of the 6.9 million estimated deaths among children under five annually, over 800,000 deaths (11.6 %) are attributed to wasting. Wasting is quantified as low Weight-For-Height (WFH) and/or low Mid-Upper Arm Circumference (MUAC) (since 2005). Many statistical procedures are based on the assumption that the data used are normally distributed. Analyses have been conducted on the distribution of WFH but there are no equivalent studies on the distribution of MUAC. This secondary data analysis assesses the normality of the MUAC distributions of 852 nutrition cross-sectional survey datasets of children from 6 to 59 months old and examines different approaches to normalise "non-normal" distributions. The distribution of MUAC showed no departure from a normal distribution in 319 (37.7 %) distributions using the Shapiro-Wilk test. Out of the 533 surveys showing departure from a normal distribution, 183 (34.3 %) were skewed (D'Agostino test) and 196 (36.8 %) had a kurtosis different to the one observed in the normal distribution (Anscombe-Glynn test). Testing for normality can be sensitive to data quality, design effect and sample size. Out of the 533 surveys showing departure from a normal distribution, 294 (55.2 %) showed high digit preference, 164 (30.8 %) had a large design effect, and 204 (38.3 %) a large sample size. Spline and LOESS smoothing techniques were explored and both techniques work well. After Spline smoothing, 56.7 % of the MUAC distributions showing departure from normality were "normalised" and 59.7 % after LOESS. Box-Cox power transformation had similar results on distributions showing departure from normality with 57 % of distributions approximating "normal" after transformation. Applying Box-Cox transformation after Spline or Loess smoothing techniques increased that proportion to 82.4 and 82.7 % respectively. This suggests that statistical approaches relying on the

Is Middle-Upper Arm Circumference “normally” distributed? Secondary data analysis of 852 nutrition surveys

Directory of Open Access Journals (Sweden)

Severine Frison

2016-05-01

Full Text Available Abstract Background Wasting is a major public health issue throughout the developing world. Out of the 6.9 million estimated deaths among children under five annually, over 800,000 deaths (11.6 % are attributed to wasting. Wasting is quantified as low Weight-For-Height (WFH and/or low Mid-Upper Arm Circumference (MUAC (since 2005. Many statistical procedures are based on the assumption that the data used are normally distributed. Analyses have been conducted on the distribution of WFH but there are no equivalent studies on the distribution of MUAC. Methods This secondary data analysis assesses the normality of the MUAC distributions of 852 nutrition cross-sectional survey datasets of children from 6 to 59 months old and examines different approaches to normalise “non-normal” distributions. Results The distribution of MUAC showed no departure from a normal distribution in 319 (37.7 % distributions using the Shapiro–Wilk test. Out of the 533 surveys showing departure from a normal distribution, 183 (34.3 % were skewed (D’Agostino test and 196 (36.8 % had a kurtosis different to the one observed in the normal distribution (Anscombe–Glynn test. Testing for normality can be sensitive to data quality, design effect and sample size. Out of the 533 surveys showing departure from a normal distribution, 294 (55.2 % showed high digit preference, 164 (30.8 % had a large design effect, and 204 (38.3 % a large sample size. Spline and LOESS smoothing techniques were explored and both techniques work well. After Spline smoothing, 56.7 % of the MUAC distributions showing departure from normality were “normalised” and 59.7 % after LOESS. Box-Cox power transformation had similar results on distributions showing departure from normality with 57 % of distributions approximating “normal” after transformation. Applying Box-Cox transformation after Spline or Loess smoothing techniques increased that proportion to 82.4 and 82.7�

Modelling free surface flows with smoothed particle hydrodynamics

Directory of Open Access Journals (Sweden)

L.Di G.Sigalotti

2006-01-01

Full Text Available In this paper the method of Smoothed Particle Hydrodynamics (SPH is extended to include an adaptive density kernel estimation (ADKE procedure. It is shown that for a van der Waals (vdW fluid, this method can be used to deal with free-surface phenomena without difficulties. In particular, arbitrary moving boundaries can be easily handled because surface tension is effectively simulated by the cohesive pressure forces. Moreover, the ADKE method is seen to increase both the accuracy and stability of SPH since it allows the width of the kernel interpolant to vary locally in a way that only the minimum necessary smoothing is applied at and near free surfaces and sharp fluid-fluid interfaces. The method is robust and easy to implement. Examples of its resolving power are given for both the formation of a circular liquid drop under surface tension and the nonlinear oscillation of excited drops.

Nonlinear Analysis for the Crack Control of SMA Smart Concrete Beam Based on a Bidirectional B-Spline QR Method

Directory of Open Access Journals (Sweden)

Yan Li

2018-01-01

Full Text Available A bidirectional B-spline QR method (BB-sQRM for the study on the crack control of the reinforced concrete (RC beam embedded with shape memory alloy (SMA wires is presented. In the proposed method, the discretization is performed with a set of spline nodes in two directions of the plane model, and structural displacement fields are constructed by the linear combination of the products of cubic B-spline interpolation functions. To derive the elastoplastic stiffness equation of the RC beam, an explicit form is utilized to express the elastoplastic constitutive law of concrete materials. The proposed model is compared with the ANSYS model in several numerical examples. The results not only show that the solutions given by the BB-sQRM are very close to those given by the finite element method (FEM but also prove the high efficiency and low computational cost of the BB-sQRM. Meanwhile, the five parameters, such as depth-span ratio, thickness of concrete cover, reinforcement ratio, prestrain, and eccentricity of SMA wires, are investigated to learn their effects on the crack control. The results show that depth-span ratio of RC beams and prestrain and eccentricity of SMA wires have a significant influence on the control performance of beam cracks.

Localisation of deformations of the midfacial complex in subjects with class III malocclusions employing thin-plate spline analysis.

Science.gov (United States)

Singh, G D; McNamara, J A; Lozanoff, S

1997-11-01

This study determines deformations of the midface that contribute to a class III appearance, employing thinplate spline analysis. A total of 135 lateral cephalographs of prepubertal children of European-American descent with either class III malocclusions or a class I molar occlusion were compared. The cephalographs were traced and checked, and 7 homologous landmarks of the midface were identified and digitised. The data sets were scaled to an equivalent size and subjected to Procrustes analysis. These statistical tests indicated significant differences (P spline analysis indicated that both affine and nonaffine transformations contribute towards the total spline for the averaged midfacial configuration. For nonaffine transformations, partial warp 3 had the highest magnitude, indicating the large scale deformations of the midfacial configuration. These deformations affected the palatal landmarks, and were associated with compression of the midfacial complex in the anteroposterior plane predominantly. Partial warp 4 produced some vertical compression of the posterior aspect of the midfacial complex whereas partial warps 1 and 2 indicated localised shape changes of the maxillary alveolus region. large spatial-scale deformations therefore affect the midfacial complex in an anteroposterior axis, in combination with vertical compression and localised distortions. These deformations may represent a developmental diminution of the palatal complex anteroposteriorly that, allied with vertical shortening of midfacial height posteriorly, results in class III malocclusions with a retrusive midfacial profile.

Density estimation by maximum quantum entropy

International Nuclear Information System (INIS)

Silver, R.N.; Wallstrom, T.; Martz, H.F.

1993-01-01

A new Bayesian method for non-parametric density estimation is proposed, based on a mathematical analogy to quantum statistical physics. The mathematical procedure is related to maximum entropy methods for inverse problems and image reconstruction. The information divergence enforces global smoothing toward default models, convexity, positivity, extensivity and normalization. The novel feature is the replacement of classical entropy by quantum entropy, so that local smoothing is enforced by constraints on differential operators. The linear response of the estimate is proportional to the covariance. The hyperparameters are estimated by type-II maximum likelihood (evidence). The method is demonstrated on textbook data sets

Smooth halos in the cosmic web

Energy Technology Data Exchange (ETDEWEB)

Gaite, José, E-mail: jose.gaite@upm.es [Physics Dept., ETSIAE, IDR, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, E-28040 Madrid (Spain)

2015-04-01

Dark matter halos can be defined as smooth distributions of dark matter placed in a non-smooth cosmic web structure. This definition of halos demands a precise definition of smoothness and a characterization of the manner in which the transition from smooth halos to the cosmic web takes place. We introduce entropic measures of smoothness, related to measures of inequality previously used in economy and with the advantage of being connected with standard methods of multifractal analysis already used for characterizing the cosmic web structure in cold dark matter N-body simulations. These entropic measures provide us with a quantitative description of the transition from the small scales portrayed as a distribution of halos to the larger scales portrayed as a cosmic web and, therefore, allow us to assign definite sizes to halos. However, these ''smoothness sizes'' have no direct relation to the virial radii. Finally, we discuss the influence of N-body discreteness parameters on smoothness.

Smooth halos in the cosmic web

International Nuclear Information System (INIS)

Gaite, José

2015-01-01

Dark matter halos can be defined as smooth distributions of dark matter placed in a non-smooth cosmic web structure. This definition of halos demands a precise definition of smoothness and a characterization of the manner in which the transition from smooth halos to the cosmic web takes place. We introduce entropic measures of smoothness, related to measures of inequality previously used in economy and with the advantage of being connected with standard methods of multifractal analysis already used for characterizing the cosmic web structure in cold dark matter N-body simulations. These entropic measures provide us with a quantitative description of the transition from the small scales portrayed as a distribution of halos to the larger scales portrayed as a cosmic web and, therefore, allow us to assign definite sizes to halos. However, these ''smoothness sizes'' have no direct relation to the virial radii. Finally, we discuss the influence of N-body discreteness parameters on smoothness

Ecological ranges for the pH and NO3 of syntaxa: a new basis for the estimation of critical loads for acid and nitrogen deposition

NARCIS (Netherlands)

Wamelink, G.W.W.; Goedhart, P.W.; Malinowska, A.H.; Frissel, J.Y.; Wegman, R.M.A.; Slim, P.A.; Dobben, van H.F.

2011-01-01

Question: Can the abiotic ranges of syntaxonomic units (associations) in terms of pH and nitrate concentration be estimated and then in principle be used to estimate critical loads for acid and nitrogen deposition? Location: Europe. Methods: Using splines, abiotic ranges of syntaxonomic units were

Complex wavenumber Fourier analysis of the B-spline based finite element method

Czech Academy of Sciences Publication Activity Database

Kolman, Radek; Plešek, Jiří; Okrouhlík, Miloslav

2014-01-01

Roč. 51, č. 2 (2014), s. 348-359 ISSN 0165-2125 R&D Projects: GA ČR(CZ) GAP101/11/0288; GA ČR(CZ) GAP101/12/2315; GA ČR GPP101/10/P376; GA ČR GA101/09/1630 Institutional support: RVO:61388998 Keywords : elastic wave propagation * dispersion errors * B-spline * finite element method * isogeometric analysis Subject RIV: JR - Other Machinery Impact factor: 1.513, year: 2014 http://www.sciencedirect.com/science/article/pii/S0165212513001479

Gauss-Galerkin quadrature rules for quadratic and cubic spline spaces and their application to isogeometric analysis

KAUST Repository

Barton, Michael

2016-07-21

We introduce Gaussian quadrature rules for spline spaces that are frequently used in Galerkin discretizations to build mass and stiffness matrices. By definition, these spaces are of even degrees. The optimal quadrature rules we recently derived (Bartoň and Calo, 2016) act on spaces of the smallest odd degrees and, therefore, are still slightly sub-optimal. In this work, we derive optimal rules directly for even-degree spaces and therefore further improve our recent result. We use optimal quadrature rules for spaces over two elements as elementary building blocks and use recursively the homotopy continuation concept described in Bartoň and Calo (2016) to derive optimal rules for arbitrary admissible numbers of elements.We demonstrate the proposed methodology on relevant examples, where we derive optimal rules for various even-degree spline spaces. We also discuss convergence of our rules to their asymptotic counterparts, these are the analogues of the midpoint rule of Hughes et al. (2010), that are exact and optimal for infinite domains.

Comparison of some nonlinear smoothing methods

International Nuclear Information System (INIS)

Bell, P.R.; Dillon, R.S.

1977-01-01

Due to the poor quality of many nuclear medicine images, computer-driven smoothing procedures are frequently employed to enhance the diagnostic utility of these images. While linear methods were first tried, it was discovered that nonlinear techniques produced superior smoothing with little detail suppression. We have compared four methods: Gaussian smoothing (linear), two-dimensional least-squares smoothing (linear), two-dimensional least-squares bounding (nonlinear), and two-dimensional median smoothing (nonlinear). The two dimensional least-squares procedures have yielded the most satisfactorily enhanced images, with the median smoothers providing quite good images, even in the presence of widely aberrant points

Splines employment for inverse problem of nonstationary thermal conduction

International Nuclear Information System (INIS)

Nikonov, S.P.; Spolitak, S.I.

1985-01-01

An analytical solution has been obtained for an inverse problem of nonstationary thermal conduction which is faced in nonstationary heat transfer data processing when the rewetting in channels with uniform annular fuel element imitators is investigated. In solving the problem both boundary conditions and power density within the imitator are regularized via cubic splines constructed with the use of Reinsch algorithm. The solution can be applied for calculation of temperature distribution in the imitator and the heat flux in two-dimensional approximation (r-z geometry) under the condition that the rewetting front velocity is known, and in one-dimensional r-approximation in cases with negligible axial transport or when there is a lack of data about the temperature disturbance source velocity along the channel

The Public Health and Air Pollution in Asia (PAPA) Project: estimating the mortality effects of particulate matter in Bangkok, Thailand.

Science.gov (United States)

Vichit-Vadakan, Nuntavarn; Vajanapoom, Nitaya; Ostro, Bart

2008-09-01

Air pollution data in Bangkok, Thailand, indicate that levels of particulate matter with aerodynamic diameter air pollution in Bangkok, Thailand. The study period extended from 1999 to 2003, for which the Ministry of Public Health provided the mortality data. Measures of air pollution were derived from air monitoring stations, and information on temperature and relative humidity was obtained from the weather station in central Bangkok. The statistical analysis followed the common protocol for the multicity PAPA (Public Health and Air Pollution Project in Asia) project in using a natural cubic spline model with smooths of time and weather. The excess risk for non-accidental mortality was 1.3% [95% confidence interval (CI), 0.8-1.7] per 10 microg/m(3) of PM(10), with higher excess risks for cardiovascular and above age 65 mortality of 1.9% (95% CI, 0.8-3.0) and 1.5% (95% CI, 0.9-2.1), respectively. In addition, the effects from PM(10) appear to be consistent in multipollutant models. The results suggest strong associations between several different mortality outcomes and PM(10). In many cases, the effect estimates were higher than those typically reported in Western industrialized nations.

Dynamic MRI Using SmooThness Regularization on Manifolds (SToRM).

Science.gov (United States)

Poddar, Sunrita; Jacob, Mathews

2016-04-01

We introduce a novel algorithm to recover real time dynamic MR images from highly under-sampled k- t space measurements. The proposed scheme models the images in the dynamic dataset as points on a smooth, low dimensional manifold in high dimensional space. We propose to exploit the non-linear and non-local redundancies in the dataset by posing its recovery as a manifold smoothness regularized optimization problem. A navigator acquisition scheme is used to determine the structure of the manifold, or equivalently the associated graph Laplacian matrix. The estimated Laplacian matrix is used to recover the dataset from undersampled measurements. The utility of the proposed scheme is demonstrated by comparisons with state of the art methods in multi-slice real-time cardiac and speech imaging applications.

Growth curve analysis for plasma profiles using smoothing splines. Final report, January 1993--January 1995

International Nuclear Information System (INIS)

Imre, K.

1995-07-01

In this project, we parameterize the shape and magnitude of the temperature and density profiles on JET and the temperature profiles on TFTR. The key control variables for the profiles were tabulated and the response functions were estimated. A sophisticated statistical analysis code was developed to fit the plasma profiles. Our analysis indicate that the JET density shape depends primarily on bar n/B t for Ohmic heating, bar n for L-mode and I p for H-mode. The temperature profiles for JET are mainly determined by q 95 for the case of Ohmic heating, and by B t and P/bar n for the L-mode. For the H-mode the shape depends on the type of auxiliary heating, Z eff , N bar n, q 95 , and P

From symplectic integrator to Poincare map: Spline expansion of a map generator in Cartesian coordinates

International Nuclear Information System (INIS)

Warnock, R.L.; Ellison, J.A.; Univ. of New Mexico, Albuquerque, NM

1997-08-01

Data from orbits of a symplectic integrator can be interpolated so as to construct an approximation to the generating function of a Poincare map. The time required to compute an orbit of the symplectic map induced by the generator can be much less than the time to follow the same orbit by symplectic integration. The construction has been carried out previously for full-turn maps of large particle accelerators, and a big saving in time (for instance a factor of 60) has been demonstrated. A shortcoming of the work to date arose from the use of canonical polar coordinates, which precluded map construction in small regions of phase space near coordinate singularities. This paper shows that Cartesian coordinates can also be used, thus avoiding singularities. The generator is represented in a basis of tensor product B-splines. Under weak conditions the spline expansion converges uniformly as the mesh is refined, approaching the exact generator of the Poincare map as defined by the symplectic integrator, in some parallelepiped of phase space centered at the origin

Estimating the Competitive Storage Model with Trending Commodity Prices

OpenAIRE

Gouel , Christophe; LEGRAND , Nicolas

2017-01-01

We present a method to estimate jointly the parameters of a standard commodity storage model and the parameters characterizing the trend in commodity prices. This procedure allows the influence of a possible trend to be removed without restricting the model specification, and allows model and trend selection based on statistical criteria. The trend is modeled deterministically using linear or cubic spline functions of time. The results show that storage models with trend are always preferred ...

Smooth conditional distribution function and quantiles under random censorship.

Science.gov (United States)

Leconte, Eve; Poiraud-Casanova, Sandrine; Thomas-Agnan, Christine

2002-09-01

We consider a nonparametric random design regression model in which the response variable is possibly right censored. The aim of this paper is to estimate the conditional distribution function and the conditional alpha-quantile of the response variable. We restrict attention to the case where the response variable as well as the explanatory variable are unidimensional and continuous. We propose and discuss two classes of estimators which are smooth with respect to the response variable as well as to the covariate. Some simulations demonstrate that the new methods have better mean square error performances than the generalized Kaplan-Meier estimator introduced by Beran (1981) and considered in the literature by Dabrowska (1989, 1992) and Gonzalez-Manteiga and Cadarso-Suarez (1994).

A splitting algorithm for the wavelet transform of cubic splines on a nonuniform grid

Science.gov (United States)

Sulaimanov, Z. M.; Shumilov, B. M.

2017-10-01

For cubic splines with nonuniform nodes, splitting with respect to the even and odd nodes is used to obtain a wavelet expansion algorithm in the form of the solution to a three-diagonal system of linear algebraic equations for the coefficients. Computations by hand are used to investigate the application of this algorithm for numerical differentiation. The results are illustrated by solving a prediction problem.

Least square fitting of low resolution gamma ray spectra with cubic B-spline basis functions

International Nuclear Information System (INIS)

Zhu Menghua; Liu Lianggang; Qi Dongxu; You Zhong; Xu Aoao

2009-01-01

In this paper, the least square fitting method with the cubic B-spline basis functions is derived to reduce the influence of statistical fluctuations in the gamma ray spectra. The derived procedure is simple and automatic. The results show that this method is better than the convolution method with a sufficient reduction of statistical fluctuation. (authors)

Numerical solution of the controlled Duffing oscillator by semi-orthogonal spline wavelets

International Nuclear Information System (INIS)

Lakestani, M; Razzaghi, M; Dehghan, M

2006-01-01

This paper presents a numerical method for solving the controlled Duffing oscillator. The method can be extended to nonlinear calculus of variations and optimal control problems. The method is based upon compactly supported linear semi-orthogonal B-spline wavelets. The differential and integral expressions which arise in the system dynamics, the performance index and the boundary conditions are converted into some algebraic equations which can be solved for the unknown coefficients. Illustrative examples are included to demonstrate the validity and applicability of the technique

A New Method to Solve Numeric Solution of Nonlinear Dynamic System

Directory of Open Access Journals (Sweden)

Min Hu

2016-01-01

Full Text Available It is well known that the cubic spline function has advantages of simple forms, good convergence, approximation, and second-order smoothness. A particular class of cubic spline function is constructed and an effective method to solve the numerical solution of nonlinear dynamic system is proposed based on the cubic spline function. Compared with existing methods, this method not only has high approximation precision, but also avoids the Runge phenomenon. The error analysis of several methods is given via two numeric examples, which turned out that the proposed method is a much more feasible tool applied to the engineering practice.

Smooth and non-smooth travelling waves in a nonlinearly dispersive Boussinesq equation

International Nuclear Information System (INIS)

Shen Jianwei; Xu Wei; Lei Youming

2005-01-01

The dynamical behavior and special exact solutions of nonlinear dispersive Boussinesq equation (B(m,n) equation), u tt -u xx -a(u n ) xx +b(u m ) xxxx =0, is studied by using bifurcation theory of dynamical system. As a result, all possible phase portraits in the parametric space for the travelling wave system, solitary wave, kink and anti-kink wave solutions and uncountably infinite many smooth and non-smooth periodic wave solutions are obtained. It can be shown that the existence of singular straight line in the travelling wave system is the reason why smooth waves converge to cusp waves, finally. When parameter are varied, under different parametric conditions, various sufficient conditions guarantee the existence of the above solutions are given

Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure

DEFF Research Database (Denmark)

Amado, Christina; Teräsvirta, Timo

multiplier type misspecification tests. Finite-sample properties of these procedures and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns illustrate the functioning and properties of our modelling strategy in practice......In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the conditional variance to have a smooth time-varying structure of either ad- ditive or multiplicative type. The suggested parameterizations describe both nonlinearity and structural change...... in the conditional and unconditional variances where the transition between regimes over time is smooth. A modelling strategy for these new time-varying parameter GARCH models is developed. It relies on a sequence of Lagrange multiplier tests, and the adequacy of the estimated models is investigated by Lagrange...

Mediators on human airway smooth muscle.

Science.gov (United States)

Armour, C; Johnson, P; Anticevich, S; Ammit, A; McKay, K; Hughes, M; Black, J

1997-01-01

1. Bronchial hyperresponsiveness in asthma may be due to several abnormalities, but must include alterations in the airway smooth muscle responsiveness and/or volume. 2. Increased responsiveness of airway smooth muscle in vitro can be induced by certain inflammatory cell products and by induction of sensitization (atopy). 3. Increased airway smooth muscle growth can also be induced by inflammatory cell products and atopic serum. 4. Mast cell numbers are increased in the airways of asthmatics and, in our studies, in airway smooth muscle that is sensitized and hyperresponsive. 5. We propose that there is a relationship between mast cells and airway smooth muscle cells which, once an allergic process has been initiated, results in the development of critical features in the lungs in asthma.

Nuclear fusion-independent smooth muscle differentiation of human adipose-derived stem cells induced by a smooth muscle environment.

Science.gov (United States)

Zhang, Rong; Jack, Gregory S; Rao, Nagesh; Zuk, Patricia; Ignarro, Louis J; Wu, Benjamin; Rodríguez, Larissa V

2012-03-01

Human adipose-derived stem cells hASC have been isolated and were shown to have multilineage differentiation capacity. Although both plasticity and cell fusion have been suggested as mechanisms for cell differentiation in vivo, the effect of the local in vivo environment on the differentiation of adipose-derived stem cells has not been evaluated. We previously reported the in vitro capacity of smooth muscle differentiation of these cells. In this study, we evaluate the effect of an in vivo smooth muscle environment in the differentiation of hASC. We studied this by two experimental designs: (a) in vivo evaluation of smooth muscle differentiation of hASC injected into a smooth muscle environment and (b) in vitro evaluation of smooth muscle differentiation capacity of hASC exposed to bladder smooth muscle cells. Our results indicate a time-dependent differentiation of hASC into mature smooth muscle cells when these cells are injected into the smooth musculature of the urinary bladder. Similar findings were seen when the cells were cocultured in vitro with primary bladder smooth muscle cells. Chromosomal analysis demonstrated that microenvironment cues rather than nuclear fusion are responsible for this differentiation. We conclude that cell plasticity is present in hASCs, and their differentiation is accomplished in the absence of nuclear fusion. Copyright © 2011 AlphaMed Press.

Tikhonov regularization method for the numerical inversion of Mellin transforms using splines

International Nuclear Information System (INIS)

Iqbal, M.

2005-01-01

Mellin transform is an ill-posed problem. These problems arise in many branches of science and engineering. In the typical situation one is interested in recovering the original function, given a finite number of noisy measurements of data. In this paper, we shall convert Mellin transform to Laplace transform and then an integral equation of the first kind of convolution type. We solve the integral equation using Tikhonov regularization with splines as basis function. The method is applied to various test examples in the literature and results are shown in the table

Expectile smoothing: new perspectives on asymmetric least squares. An application to life expectancy

NARCIS (Netherlands)

Schnabel, S.K.

2011-01-01

While initially motivated from a demographic application, this thesis develops methodology for expectile estimation. To this end first the basic model for expectile curves using least asymmetrically weighted squares (LAWS) was introduced as well as methods for smoothing in this context. The simple

3D craniofacial registration using thin-plate spline transform and cylindrical surface projection.

Science.gov (United States)

Chen, Yucong; Zhao, Junli; Deng, Qingqiong; Duan, Fuqing

2017-01-01

Craniofacial registration is used to establish the point-to-point correspondence in a unified coordinate system among human craniofacial models. It is the foundation of craniofacial reconstruction and other craniofacial statistical analysis research. In this paper, a non-rigid 3D craniofacial registration method using thin-plate spline transform and cylindrical surface projection is proposed. First, the gradient descent optimization is utilized to improve a cylindrical surface fitting (CSF) for the reference craniofacial model. Second, the thin-plate spline transform (TPST) is applied to deform a target craniofacial model to the reference model. Finally, the cylindrical surface projection (CSP) is used to derive the point correspondence between the reference and deformed target models. To accelerate the procedure, the iterative closest point ICP algorithm is used to obtain a rough correspondence, which can provide a possible intersection area of the CSP. Finally, the inverse TPST is used to map the obtained corresponding points from the deformed target craniofacial model to the original model, and it can be realized directly by the correspondence between the original target model and the deformed target model. Three types of registration, namely, reflexive, involutive and transitive registration, are carried out to verify the effectiveness of the proposed craniofacial registration algorithm. Comparison with the methods in the literature shows that the proposed method is more accurate.

3D craniofacial registration using thin-plate spline transform and cylindrical surface projection.

Directory of Open Access Journals (Sweden)

Yucong Chen

Full Text Available Craniofacial registration is used to establish the point-to-point correspondence in a unified coordinate system among human craniofacial models. It is the foundation of craniofacial reconstruction and other craniofacial statistical analysis research. In this paper, a non-rigid 3D craniofacial registration method using thin-plate spline transform and cylindrical surface projection is proposed. First, the gradient descent optimization is utilized to improve a cylindrical surface fitting (CSF for the reference craniofacial model. Second, the thin-plate spline transform (TPST is applied to deform a target craniofacial model to the reference model. Finally, the cylindrical surface projection (CSP is used to derive the point correspondence between the reference and deformed target models. To accelerate the procedure, the iterative closest point ICP algorithm is used to obtain a rough correspondence, which can provide a possible intersection area of the CSP. Finally, the inverse TPST is used to map the obtained corresponding points from the deformed target craniofacial model to the original model, and it can be realized directly by the correspondence between the original target model and the deformed target model. Three types of registration, namely, reflexive, involutive and transitive registration, are carried out to verify the effectiveness of the proposed craniofacial registration algorithm. Comparison with the methods in the literature shows that the proposed method is more accurate.

A comparison of spatial analysis methods for the construction of topographic maps of retinal cell density.

Directory of Open Access Journals (Sweden)

Eduardo Garza-Gisholt

Full Text Available Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed 'by eye'. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation 'respects' the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the 'noise' caused by artefacts and permits a clearer representation of the dominant, 'real' distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect

A comparison of spatial analysis methods for the construction of topographic maps of retinal cell density.

Science.gov (United States)

Garza-Gisholt, Eduardo; Hemmi, Jan M; Hart, Nathan S; Collin, Shaun P

2014-01-01

Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation) and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed 'by eye'. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation 'respects' the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the 'noise' caused by artefacts and permits a clearer representation of the dominant, 'real' distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect the outcome.

multiscale smoothing in supervised statistical learning

Indian Academy of Sciences (India)

Optimum level of smoothing is chosen based on the entire training sample, while a good choice of smoothing parameter may also depend on the observation to be classified. One may like to assess the strength of evidence in favor of different competing class at different scale of smoothing. In allows only one single ...

Smoothness of limit functors

Indian Academy of Sciences (India)

Abstract. Let S be a scheme. Assume that we are given an action of the one dimen- sional split torus Gm,S on a smooth affine S-scheme X. We consider the limit (also called attractor) subfunctor Xλ consisting of points whose orbit under the given action. 'admits a limit at 0'. We show that Xλ is representable by a smooth ...

A gradient estimate for solutions to parabolic equations with discontinuous coefficients

Directory of Open Access Journals (Sweden)

Jishan Fan

2013-04-01

Full Text Available Li-Vogelius and Li-Nirenberg gave a gradient estimate for solutions of strongly elliptic equations and systems of divergence forms with piecewise smooth coefficients, respectively. The discontinuities of the coefficients are assumed to be given by manifolds of codimension 1, which we called them emph{manifolds of discontinuities}. Their gradient estimate is independent of the distances between manifolds of discontinuities. In this paper, we gave a parabolic version of their results. That is, we gave a gradient estimate for parabolic equations of divergence forms with piecewise smooth coefficients. The coefficients are assumed to be independent of time and their discontinuities are likewise the previous elliptic equations. As an application of this estimate, we also gave a pointwise gradient estimate for the fundamental solution of a parabolic operator with piecewise smooth coefficients. Both gradient estimates are independent of the distances between manifolds of discontinuities.

Efficient estimation of semiparametric copula models for bivariate survival data

KAUST Repository

Cheng, Guang

2014-01-01

A semiparametric copula model for bivariate survival data is characterized by a parametric copula model of dependence and nonparametric models of two marginal survival functions. Efficient estimation for the semiparametric copula model has been recently studied for the complete data case. When the survival data are censored, semiparametric efficient estimation has only been considered for some specific copula models such as the Gaussian copulas. In this paper, we obtain the semiparametric efficiency bound and efficient estimation for general semiparametric copula models for possibly censored data. We construct an approximate maximum likelihood estimator by approximating the log baseline hazard functions with spline functions. We show that our estimates of the copula dependence parameter and the survival functions are asymptotically normal and efficient. Simple consistent covariance estimators are also provided. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2013 Elsevier Inc.

The Norwegian Healthier Goats program--modeling lactation curves using a multilevel cubic spline regression model.

Science.gov (United States)

Nagel-Alne, G E; Krontveit, R; Bohlin, J; Valle, P S; Skjerve, E; Sølverød, L S

2014-07-01

In 2001, the Norwegian Goat Health Service initiated the Healthier Goats program (HG), with the aim of eradicating caprine arthritis encephalitis, caseous lymphadenitis, and Johne's disease (caprine paratuberculosis) in Norwegian goat herds. The aim of the present study was to explore how control and eradication of the above-mentioned diseases by enrolling in HG affected milk yield by comparison with herds not enrolled in HG. Lactation curves were modeled using a multilevel cubic spline regression model where farm, goat, and lactation were included as random effect parameters. The data material contained 135,446 registrations of daily milk yield from 28,829 lactations in 43 herds. The multilevel cubic spline regression model was applied to 4 categories of data: enrolled early, control early, enrolled late, and control late. For enrolled herds, the early and late notations refer to the situation before and after enrolling in HG; for nonenrolled herds (controls), they refer to development over time, independent of HG. Total milk yield increased in the enrolled herds after eradication: the total milk yields in the fourth lactation were 634.2 and 873.3 kg in enrolled early and enrolled late herds, respectively, and 613.2 and 701.4 kg in the control early and control late herds, respectively. Day of peak yield differed between enrolled and control herds. The day of peak yield came on d 6 of lactation for the control early category for parities 2, 3, and 4, indicating an inability of the goats to further increase their milk yield from the initial level. For enrolled herds, on the other hand, peak yield came between d 49 and 56, indicating a gradual increase in milk yield after kidding. Our results indicate that enrollment in the HG disease eradication program improved the milk yield of dairy goats considerably, and that the multilevel cubic spline regression was a suitable model for exploring effects of disease control and eradication on milk yield. Copyright © 2014

ESTIMATION OF CONSTANT AND TIME-VARYING DYNAMIC PARAMETERS OF HIV INFECTION IN A NONLINEAR DIFFERENTIAL EQUATION MODEL.

Science.gov (United States)

Liang, Hua; Miao, Hongyu; Wu, Hulin

2010-03-01

Modeling viral dynamics in HIV/AIDS studies has resulted in deep understanding of pathogenesis of HIV infection from which novel antiviral treatment guidance and strategies have been derived. Viral dynamics models based on nonlinear differential equations have been proposed and well developed over the past few decades. However, it is quite challenging to use experimental or clinical data to estimate the unknown parameters (both constant and time-varying parameters) in complex nonlinear differential equation models. Therefore, investigators usually fix some parameter values, from the literature or by experience, to obtain only parameter estimates of interest from clinical or experimental data. However, when such prior information is not available, it is desirable to determine all the parameter estimates from data. In this paper, we intend to combine the newly developed approaches, a multi-stage smoothing-based (MSSB) method and the spline-enhanced nonlinear least squares (SNLS) approach, to estimate all HIV viral dynamic parameters in a nonlinear differential equation model. In particular, to the best of our knowledge, this is the first attempt to propose a comparatively thorough procedure, accounting for both efficiency and accuracy, to rigorously estimate all key kinetic parameters in a nonlinear differential equation model of HIV dynamics from clinical data. These parameters include the proliferation rate and death rate of uninfected HIV-targeted cells, the average number of virions produced by an infected cell, and the infection rate which is related to the antiviral treatment effect and is time-varying. To validate the estimation methods, we verified the identifiability of the HIV viral dynamic model and performed simulation studies. We applied the proposed techniques to estimate the key HIV viral dynamic parameters for two individual AIDS patients treated with antiretroviral therapies. We demonstrate that HIV viral dynamics can be well characterized and

Calcium dynamics in vascular smooth muscle

OpenAIRE

Amberg, Gregory C.; Navedo, Manuel F.

2013-01-01

Smooth muscle cells are ultimately responsible for determining vascular luminal diameter and blood flow. Dynamic changes in intracellular calcium are a critical mechanism regulating vascular smooth muscle contractility. Processes influencing intracellular calcium are therefore important regulators of vascular function with physiological and pathophysiological consequences. In this review we discuss the major dynamic calcium signals identified and characterized in vascular smooth muscle cells....

From cardinal spline wavelet bases to highly coherent dictionaries

International Nuclear Information System (INIS)

Andrle, Miroslav; Rebollo-Neira, Laura

2008-01-01

Wavelet families arise by scaling and translations of a prototype function, called the mother wavelet. The construction of wavelet bases for cardinal spline spaces is generally carried out within the multi-resolution analysis scheme. Thus, the usual way of increasing the dimension of the multi-resolution subspaces is by augmenting the scaling factor. We show here that, when working on a compact interval, the identical effect can be achieved without changing the wavelet scale but reducing the translation parameter. By such a procedure we generate a redundant frame, called a dictionary, spanning the same spaces as a wavelet basis but with wavelets of broader support. We characterize the correlation of the dictionary elements by measuring their 'coherence' and produce examples illustrating the relevance of highly coherent dictionaries to problems of sparse signal representation. (fast track communication)

Subpixel Snow Cover Mapping from MODIS Data by Nonparametric Regression Splines

Science.gov (United States)

Akyurek, Z.; Kuter, S.; Weber, G. W.

2016-12-01

Spatial extent of snow cover is often considered as one of the key parameters in climatological, hydrological and ecological modeling due to its energy storage, high reflectance in the visible and NIR regions of the electromagnetic spectrum, significant heat capacity and insulating properties. A significant challenge in snow mapping by remote sensing (RS) is the trade-off between the temporal and spatial resolution of satellite imageries. In order to tackle this issue, machine learning-based subpixel snow mapping methods, like Artificial Neural Networks (ANNs), from low or moderate resolution images have been proposed. Multivariate Adaptive Regression Splines (MARS) is a nonparametric regression tool that can build flexible models for high dimensional and complex nonlinear data. Although MARS is not often employed in RS, it has various successful implementations such as estimation of vertical total electron content in ionosphere, atmospheric correction and classification of satellite images. This study is the first attempt in RS to evaluate the applicability of MARS for subpixel snow cover mapping from MODIS data. Total 16 MODIS-Landsat ETM+ image pairs taken over European Alps between March 2000 and April 2003 were used in the study. MODIS top-of-atmospheric reflectance, NDSI, NDVI and land cover classes were used as predictor variables. Cloud-covered, cloud shadow, water and bad-quality pixels were excluded from further analysis by a spatial mask. MARS models were trained and validated by using reference fractional snow cover (FSC) maps generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also developed. The mutual comparison of obtained MARS and ANN models was accomplished on independent test areas. The MARS model performed better than the ANN model with an average RMSE of 0.1288 over the independent test areas; whereas the average RMSE of the ANN model

Registration of segmented histological images using thin plate splines and belief propagation

Science.gov (United States)

Kybic, Jan

2014-03-01

We register images based on their multiclass segmentations, for cases when correspondence of local features cannot be established. A discrete mutual information is used as a similarity criterion. It is evaluated at a sparse set of location on the interfaces between classes. A thin-plate spline regularization is approximated by pairwise interactions. The problem is cast into a discrete setting and solved efficiently by belief propagation. Further speedup and robustness is provided by a multiresolution framework. Preliminary experiments suggest that our method can provide similar registration quality to standard methods at a fraction of the computational cost.

Autonomous Integrated Navigation for Indoor Robots Utilizing On-Line Iterated Extended Rauch-Tung-Striebel Smoothing

Directory of Open Access Journals (Sweden)

Yuan Xu

2013-11-01

Full Text Available In order to reduce the estimated errors of the inertial navigation system (INS/Wireless sensor network (WSN-integrated navigation for mobile robots indoors, this work proposes an on-line iterated extended Rauch-Tung-Striebel smoothing (IERTSS utilizing inertial measuring units (IMUs and an ultrasonic positioning system. In this mode, an iterated Extended Kalman filter (IEKF is used in forward data processing of the Extended Rauch-Tung-Striebel smoothing (ERTSS to improve the accuracy of the filtering output for the smoother. Furthermore, in order to achieve the on-line smoothing, IERTSS is embedded into the average filter. For verification, a real indoor test has been done to assess the performance of the proposed method. The results show that the proposed method is effective in reducing the errors compared with the conventional schemes.

Effect of smoothing on robust chaos.

Science.gov (United States)

Deshpande, Amogh; Chen, Qingfei; Wang, Yan; Lai, Ying-Cheng; Do, Younghae

2010-08-01

In piecewise-smooth dynamical systems, situations can arise where the asymptotic attractors of the system in an open parameter interval are all chaotic (e.g., no periodic windows). This is the phenomenon of robust chaos. Previous works have established that robust chaos can occur through the mechanism of border-collision bifurcation, where border is the phase-space region where discontinuities in the derivatives of the dynamical equations occur. We investigate the effect of smoothing on robust chaos and find that periodic windows can arise when a small amount of smoothness is present. We introduce a parameter of smoothing and find that the measure of the periodic windows in the parameter space scales linearly with the parameter, regardless of the details of the smoothing function. Numerical support and a heuristic theory are provided to establish the scaling relation. Experimental evidence of periodic windows in a supposedly piecewise linear dynamical system, which has been implemented as an electronic circuit, is also provided.

CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation.

Science.gov (United States)

Wilke, Marko; Altaye, Mekibib; Holland, Scott K

2017-01-01

Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps. Appropriately selecting these tissue maps becomes particularly important when investigating "unusual" populations, such as young children or elderly subjects. When creating such priors, the disadvantage of applying more deformation must be weighed against the benefit of achieving a crisper image. We have previously suggested that statistically modeling demographic variables, instead of simply averaging images, is advantageous. Both aspects (more vs. less deformation and modeling vs. averaging) were explored here. We used imaging data from 1914 subjects, aged 13 months to 75 years, and employed multivariate adaptive regression splines to model the effects of age, field strength, gender, and data quality. Within the spm/cat12 framework, we compared an affine-only with a low- and a high-dimensional warping approach. As expected, more deformation on the individual level results in lower group dissimilarity. Consequently, effects of age in particular are less apparent in the resulting tissue maps when using a more extensive deformation scheme. Using statistically-described parameters, high-quality tissue probability maps could be generated for the whole age range; they are consistently closer to a gold standard than conventionally-generated priors based on 25, 50, or 100 subjects. Distinct effects of field strength, gender, and data quality were seen. We conclude that an extensive matching for generating tissue priors may model much of the variability inherent in the dataset which is then not contained in the resulting priors. Further, the statistical description of relevant parameters (using regression splines) allows for the generation of high-quality tissue probability maps while controlling for known confounds. The resulting CerebroMatic toolbox is available for download at http://irc.cchmc.org/software/cerebromatic.php.

Curve fitting for RHB Islamic Bank annual net profit

Science.gov (United States)

Nadarajan, Dineswary; Noor, Noor Fadiya Mohd

2015-05-01

The RHB Islamic Bank net profit data are obtained from 2004 to 2012. Curve fitting is done by assuming the data are exact or experimental due to smoothing process. Higher order Lagrange polynomial and cubic spline with curve fitting procedure are constructed using Maple software. Normality test is performed to check the data adequacy. Regression analysis with curve estimation is conducted in SPSS environment. All the eleven models are found to be acceptable at 10% significant level of ANOVA. Residual error and absolute relative true error are calculated and compared. The optimal model based on the minimum average error is proposed.

Smooth surfaces from rational bilinear patches

KAUST Repository

Shi, Ling

2014-01-01

Smooth freeform skins from simple panels constitute a challenging topic arising in contemporary architecture. We contribute to this problem area by showing how to approximate a negatively curved surface by smoothly joined rational bilinear patches. The approximation problem is solved with help of a new computational approach to the hyperbolic nets of Huhnen-Venedey and Rörig and optimization algorithms based on it. We also discuss its limits which lie in the topology of the input surface. Finally, freeform deformations based on Darboux transformations are used to generate smooth surfaces from smoothly joined Darboux cyclide patches; in this way we eliminate the restriction to surfaces with negative Gaussian curvature. © 2013 Elsevier B.V.

Surface smoothing: a way back in early brain morphogenesis

Science.gov (United States)

Lefèvre, Julien; Intwali, Victor; Hertz-Pannier, Lucie; Hüppi, Petra S.; Mangin, Jean-Francois; Dubois, Jessica; Germanaud, David

2013-01-01

In this article we propose to investigate the analogy between early cortical folding process and cortical smoothing by mean curvature flow. First, we introduce a one-parameter model that is able to fit a developmental trajectory as represented in a Volume-Area plot and we propose an efficient optimization strategy for parameter estimation. Second, we validate the model on forty cortical surfaces of preterm newborns by comparing global geometrical indices and trajectories of central sulcus along developmental and simulation time. PMID:24505715

StreamMap: Smooth Dynamic Visualization of High-Density Streaming Points.

Science.gov (United States)

Li, Chenhui; Baciu, George; Han, Yu

2018-03-01

Interactive visualization of streaming points for real-time scatterplots and linear blending of correlation patterns is increasingly becoming the dominant mode of visual analytics for both big data and streaming data from active sensors and broadcasting media. To better visualize and interact with inter-stream patterns, it is generally necessary to smooth out gaps or distortions in the streaming data. Previous approaches either animate the points directly or present a sampled static heat-map. We propose a new approach, called StreamMap, to smoothly blend high-density streaming points and create a visual flow that emphasizes the density pattern distributions. In essence, we present three new contributions for the visualization of high-density streaming points. The first contribution is a density-based method called super kernel density estimation that aggregates streaming points using an adaptive kernel to solve the overlapping problem. The second contribution is a robust density morphing algorithm that generates several smooth intermediate frames for a given pair of frames. The third contribution is a trend representation design that can help convey the flow directions of the streaming points. The experimental results on three datasets demonstrate the effectiveness of StreamMap when dynamic visualization and visual analysis of trend patterns on streaming points are required.

Fuzzy B-spline optimization for urban slum three-dimensional reconstruction using ENVISAT satellite data

International Nuclear Information System (INIS)

Marghany, Maged

2014-01-01

A critical challenges in urban aeras is slums. In fact, they are considered a source of crime and disease due to poor-quality housing, unsanitary conditions, poor infrastructures and occupancy security. The poor in the dense urban slums are the most vulnerable to infection due to (i) inadequate and restricted access to safety, drinking water and sufficient quantities of water for personal hygiene; (ii) the lack of removal and treatment of excreta; and (iii) the lack of removal of solid waste. This study aims to investigate the capability of ENVISAT ASAR satellite and Google Earth data for three-dimensional (3-D) slum urban reconstruction in developed countries such as Egypt. The main objective of this work is to utilize some 3-D automatic detection algorithm for urban slum in ENVISAT ASAR and Google Erath images were acquired in Cairo, Egypt using Fuzzy B-spline algorithm. The results show that the fuzzy algorithm is the best indicator for chaotic urban slum as it can discriminate between them from its surrounding environment. The combination of Fuzzy and B-spline then used to reconstruct 3-D of urban slum. The results show that urban slums, road network, and infrastructures are perfectly discriminated. It can therefore be concluded that the fuzzy algorithm is an appropriate algorithm for chaotic urban slum automatic detection in ENVSIAT ASAR and Google Earth data

Fuzzy B-spline optimization for urban slum three-dimensional reconstruction using ENVISAT satellite data

Science.gov (United States)

Marghany, Maged

2014-06-01

A critical challenges in urban aeras is slums. In fact, they are considered a source of crime and disease due to poor-quality housing, unsanitary conditions, poor infrastructures and occupancy security. The poor in the dense urban slums are the most vulnerable to infection due to (i) inadequate and restricted access to safety, drinking water and sufficient quantities of water for personal hygiene; (ii) the lack of removal and treatment of excreta; and (iii) the lack of removal of solid waste. This study aims to investigate the capability of ENVISAT ASAR satellite and Google Earth data for three-dimensional (3-D) slum urban reconstruction in developed countries such as Egypt. The main objective of this work is to utilize some 3-D automatic detection algorithm for urban slum in ENVISAT ASAR and Google Erath images were acquired in Cairo, Egypt using Fuzzy B-spline algorithm. The results show that the fuzzy algorithm is the best indicator for chaotic urban slum as it can discriminate between them from its surrounding environment. The combination of Fuzzy and B-spline then used to reconstruct 3-D of urban slum. The results show that urban slums, road network, and infrastructures are perfectly discriminated. It can therefore be concluded that the fuzzy algorithm is an appropriate algorithm for chaotic urban slum automatic detection in ENVSIAT ASAR and Google Earth data.

Numerical solution of the Black-Scholes equation using cubic spline wavelets

Science.gov (United States)

Černá, Dana

2016-12-01

The Black-Scholes equation is used in financial mathematics for computation of market values of options at a given time. We use the θ-scheme for time discretization and an adaptive scheme based on wavelets for discretization on the given time level. Advantages of the proposed method are small number of degrees of freedom, high-order accuracy with respect to variables representing prices and relatively small number of iterations needed to resolve the problem with a desired accuracy. We use several cubic spline wavelet and multi-wavelet bases and discuss their advantages and disadvantages. We also compare an isotropic and anisotropic approach. Numerical experiments are presented for the two-dimensional Black-Scholes equation.

Perbaikan Metode Penghitungan Debit Sungai Menggunakan Cubic Spline Interpolation

Directory of Open Access Journals (Sweden)

Budi I. Setiawan

2007-09-01

Full Text Available Makalah ini menyajikan perbaikan metode pengukuran debit sungai menggunakan fungsi cubic spline interpolation. Fungi ini digunakan untuk menggambarkan profil sungai secara kontinyu yang terbentuk atas hasil pengukuran jarak dan kedalaman sungai. Dengan metoda baru ini, luas dan perimeter sungai lebih mudah, cepat dan tepat dihitung. Demikian pula, fungsi kebalikannnya (inverse function tersedia menggunakan metode. Newton-Raphson sehingga memudahkan dalam perhitungan luas dan perimeter bila tinggi air sungai diketahui. Metode baru ini dapat langsung menghitung debit sungaimenggunakan formula Manning, dan menghasilkan kurva debit (rating curve. Dalam makalah ini dikemukaan satu canton pengukuran debit sungai Rudeng Aceh. Sungai ini mempunyai lebar sekitar 120 m dan kedalaman 7 m, dan pada saat pengukuran mempunyai debit 41 .3 m3/s, serta kurva debitnya mengikuti formula: Q= 0.1649 x H 2.884 , dimana Q debit (m3/s dan H tinggi air dari dasar sungai (m.

Bifurcations of non-smooth systems

Science.gov (United States)

Angulo, Fabiola; Olivar, Gerard; Osorio, Gustavo A.; Escobar, Carlos M.; Ferreira, Jocirei D.; Redondo, Johan M.

2012-12-01

Non-smooth systems (namely piecewise-smooth systems) have received much attention in the last decade. Many contributions in this area show that theory and applications (to electronic circuits, mechanical systems, …) are relevant to problems in science and engineering. Specially, new bifurcations have been reported in the literature, and this was the topic of this minisymposium. Thus both bifurcation theory and its applications were included. Several contributions from different fields show that non-smooth bifurcations are a hot topic in research. Thus in this paper the reader can find contributions from electronics, energy markets and population dynamics. Also, a carefully-written specific algebraic software tool is presented.

Transforming wealth: using the inverse hyperbolic sine (IHS) and splines to predict youth's math achievement.

Science.gov (United States)

Friedline, Terri; Masa, Rainier D; Chowa, Gina A N

2015-01-01

The natural log and categorical transformations commonly applied to wealth for meeting the statistical assumptions of research may not always be appropriate for adjusting for skewness given wealth's unique properties. Finding and applying appropriate transformations is becoming increasingly important as researchers consider wealth as a predictor of well-being. We present an alternative transformation-the inverse hyperbolic sine (IHS)-for simultaneously dealing with skewness and accounting for wealth's unique properties. Using the relationship between household wealth and youth's math achievement as an example, we apply the IHS transformation to wealth data from US and Ghanaian households. We also explore non-linearity and accumulation thresholds by combining IHS transformed wealth with splines. IHS transformed wealth relates to youth's math achievement similarly when compared to categorical and natural log transformations, indicating that it is a viable alternative to other transformations commonly used in research. Non-linear relationships and accumulation thresholds emerge that predict youth's math achievement when splines are incorporated. In US households, accumulating debt relates to decreases in math achievement whereas accumulating assets relates to increases in math achievement. In Ghanaian households, accumulating assets between the 25th and 50th percentiles relates to increases in youth's math achievement. Copyright © 2014 Elsevier Inc. All rights reserved.

RGB color calibration for quantitative image analysis: the "3D thin-plate spline" warping approach.

Science.gov (United States)

Menesatti, Paolo; Angelini, Claudio; Pallottino, Federico; Antonucci, Francesca; Aguzzi, Jacopo; Costa, Corrado

2012-01-01

In the last years the need to numerically define color by its coordinates in n-dimensional space has increased strongly. Colorimetric calibration is fundamental in food processing and other biological disciplines to quantitatively compare samples' color during workflow with many devices. Several software programmes are available to perform standardized colorimetric procedures, but they are often too imprecise for scientific purposes. In this study, we applied the Thin-Plate Spline interpolation algorithm to calibrate colours in sRGB space (the corresponding Matlab code is reported in the Appendix). This was compared with other two approaches. The first is based on a commercial calibration system (ProfileMaker) and the second on a Partial Least Square analysis. Moreover, to explore device variability and resolution two different cameras were adopted and for each sensor, three consecutive pictures were acquired under four different light conditions. According to our results, the Thin-Plate Spline approach reported a very high efficiency of calibration allowing the possibility to create a revolution in the in-field applicative context of colour quantification not only in food sciences, but also in other biological disciplines. These results are of great importance for scientific color evaluation when lighting conditions are not controlled. Moreover, it allows the use of low cost instruments while still returning scientifically sound quantitative data.

A SAS IML Macro for Loglinear Smoothing

Science.gov (United States)

Moses, Tim; von Davier, Alina

2011-01-01

Polynomial loglinear models for one-, two-, and higher-way contingency tables have important applications to measurement and assessment. They are essentially regarded as a smoothing technique, which is commonly referred to as loglinear smoothing. A SAS IML (SAS Institute, 2002a) macro was created to implement loglinear smoothing according to…

Investigation of electron and hydrogenic-donor states confined in a permeable spherical box using B-splines

Directory of Open Access Journals (Sweden)

T Nikbakht

2012-12-01

Full Text Available   Effects of quantum size and potential shape on the spectra of an electron and a hydrogenic-donor at the center of a permeable spherical cavity have been calculated, using linear variational method. B-splines have been used as basis functions. By extensive convergence tests and comparing with other results given in the literature, the validity and efficiency of the method were confirmed.

Functional Mixed Effects Model for Small Area Estimation.

Science.gov (United States)

Maiti, Tapabrata; Sinha, Samiran; Zhong, Ping-Shou

2016-09-01

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fit a varying coefficient linear mixed effect model where the varying coefficients are semi-parametrically modeled via B-splines. We propose a method of estimating the fixed effect parameters and consider prediction of random effects that can be implemented using a standard software. For measuring prediction uncertainties, we derive an analytical expression for the mean squared errors, and propose a method of estimating the mean squared errors. The procedure is illustrated via a real data example, and operating characteristics of the method are judged using finite sample simulation studies.

ESTIMACIÓN ROBUSTA DE MODELOS ADITIVOS MEDIANTE EL ALGORITMO DE BACKFITTING

Directory of Open Access Journals (Sweden)

Luis P. Yapu Quispe

2012-07-01

Full Text Available En este trabajo se presenta un método de estimación y simulación de un modelo aditivo a dos variables mediante splines robustos, el método general puede ser aplicado con varias variables. El software utilizado para las simulaciones es S+ y se utiliza explícitamente la función smooth.splineRob en una implementación del algoritmo de backfitting. La función smooth.splineRob ha sido escrita en base al trabajo de Cantoni y Ronchetti [3], en el cual se pone énfasis en la selección robusta del parámetro de suavizamiento utilizando una versión robusta del Cp de Mallows, RCp, y de la validación cruzada, RCV. La existencia de datos extremos o no-normales en la parte estocástica de un modelo aditivo puede provocar una mala estimación del parámetro de suavizamiento, lo que tendrá influencia global en la estimación por splines. Para la etapa de simulación se realizan las estimaciones por splines clásicos y robustos (con estimación robusta del parámetro. La estimación obtenida es muy convincente pero el tiempo de ejecución del programa es relativamente elevado tanto para RCp y RCV, aun cuando, en ciertos casos, con pocas iteraciones robustas se obtienen ya resultados más útiles que la estimación clásica.

Path Planning for Unmanned Underwater Vehicle in 3D Space with Obstacles Using Spline-Imperialist Competitive Algorithm and Optimal Interval Type-2 Fuzzy Logic Controller

Directory of Open Access Journals (Sweden)

Ehsan Zakeri

Full Text Available Abstract In this research, generation of a short and smooth path in three-dimensional space with obstacles for guiding an Unmanned Underwater Vehicle (UUV without collision is investigated. This is done by utilizing spline technique, in which the spline control points positions are determined by Imperialist Competitive Algorithm (ICA in three-dimensional space such that the shortest possible path from the starting point to the target point without colliding with obstacles is achieved. Furthermore, for guiding the UUV in the generated path, an Interval Type-2 Fuzzy Logic Controller (IT2FLC, the coefficients of which are optimized by considering an objective function that includes quadratic terms of the input forces and state error of the system, is used. Selecting such objective function reduces the control error and also the force applied to the UUV, which consequently leads to reduction of energy consumption. Therefore, by using a special method, desired signals of UUV state are obtained from generated three-dimensional optimal path such that tracking these signals by the controller leads to the tracking of this path by UUV. In this paper, the dynamical model of the UUV, entitled as "mUUV-WJ-1" , is derived and its hydrodynamic coefficients are calculated by CFD in order to be used in the simulations. For simulation by the method presented in this study, three environments with different obstacles are intended in order to check the performance of the IT2FLC controller in generating optimal paths for guiding the UUV. In this article, in addition to ICA, Particle Swarm Optimization (PSO and Artificial Bee Colony (ABC are also used for generation of the paths and the results are compared with each other. The results show the appropriate performance of ICA rather than ABC and PSO. Moreover, to evaluate the performance of the IT2FLC, optimal Type-1 Fuzzy Logic Controller (T1FLC and Proportional Integrator Differentiator (PID controller are designed

Income and Consumption Smoothing among US States

DEFF Research Database (Denmark)

Sørensen, Bent; Yosha, Oved

within regions but not between regions. This suggests that capital markets transcend regional barriers while credit markets are regional in their nature. Smoothing within the club of rich states is accomplished mainly via capital markets whereas consumption smoothing is dominant within the club of poor...... states. The fraction of a shock to gross state products smoothed by the federal tax-transfer system is the same for various regions and other clubs of states. We calculate the scope for consumption smoothing within various regions and clubs, finding that most gains from risk sharing can be achieved...

Asymmetric free vibrations of laminated annular cross-ply circular plates including the effects of shear deformation and rotary inertia. Spline method

Energy Technology Data Exchange (ETDEWEB)

Viswanathan, K.K.; Kim, Kyung Su; Lee, Jang Hyun [Inha Univ., Incheon (Korea). Dept. of Naval Architecture and Ocean Engineering

2009-12-15

Asymmetric free vibrations of annular cross-ply circular plates are studied using spline function approximation. The governing equations are formulated including the effects of shear deformation and rotary inertia. Assumptions are made to study the cross-ply layered plates. A system of coupled differential equations are obtained in terms of displacement functions and rotational functions. These functions are approximated using Bickley- type spline functions of suitable order. Then the system is converted into the eigenvalue problem by applying the point collocation technique and suitable boundary conditions. Parametric studies have been made to investigate the effect of transverse shear deformation and rotary inertia on frequency parameter with respect to the circumferential node number, radii ratio and thickness to radius ratio for both symmetric and anti-symmetric cross-ply plates using various types of material properties. (orig.)

Assessment of smoothed spectra using autocorrelation function

International Nuclear Information System (INIS)

Urbanski, P.; Kowalska, E.

2006-01-01

Recently, data and signal smoothing became almost standard procedures in the spectrometric and chromatographic methods. In radiometry, the main purpose to apply smoothing is minimisation of the statistical fluctuation and avoid distortion. The aim of the work was to find a qualitative parameter, which could be used, as a figure of merit for detecting distortion of the smoothed spectra, based on the linear model. It is assumed that as long as the part of the raw spectrum removed by the smoothing procedure (v s ) will be of random nature, the smoothed spectrum can be considered as undistorted. Thanks to this feature of the autocorrelation function, drifts of the mean value in the removed noise vs as well as its periodicity can be more easily detected from the autocorrelogram than from the original data

Probabilistic fatigue life prediction methodology for notched components based on simple smooth fatigue tests