Comparison of software and human observers in reading images of the CDMAM test object to assess digital mammography systems

NASA Astrophysics Data System (ADS)

Young, Kenneth C.; Cook, James J. H.; Oduko, Jennifer M.; Bosmans, Hilde

2006-03-01

European Guidelines for quality control in digital mammography specify minimum and achievable standards of image quality in terms of threshold contrast, based on readings of images of the CDMAM test object by human observers. However this is time-consuming and has large inter-observer error. To overcome these problems a software program (CDCOM) is available to automatically read CDMAM images, but the optimal method of interpreting the output is not defined. This study evaluates methods of determining threshold contrast from the program, and compares these to human readings for a variety of mammography systems. The methods considered are (A) simple thresholding (B) psychometric curve fitting (C) smoothing and interpolation and (D) smoothing and psychometric curve fitting. Each method leads to similar threshold contrasts but with different reproducibility. Method (A) had relatively poor reproducibility with a standard error in threshold contrast of 18.1 +/- 0.7%. This was reduced to 8.4% by using a contrast-detail curve fitting procedure. Method (D) had the best reproducibility with an error of 6.7%, reducing to 5.1% with curve fitting. A panel of 3 human observers had an error of 4.4% reduced to 2.9 % by curve fitting. All automatic methods led to threshold contrasts that were lower than for humans. The ratio of human to program threshold contrasts varied with detail diameter and was 1.50 +/- .04 (sem) at 0.1mm and 1.82 +/- .06 at 0.25mm for method (D). There were good correlations between the threshold contrast determined by humans and the automated methods.

Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data.

PubMed

Helmer, Markus; Kozyrev, Vladislav; Stephan, Valeska; Treue, Stefan; Geisel, Theo; Battaglia, Demian

2016-01-01

Tuning curves are the functions that relate the responses of sensory neurons to various values within one continuous stimulus dimension (such as the orientation of a bar in the visual domain or the frequency of a tone in the auditory domain). They are commonly determined by fitting a model e.g. a Gaussian or other bell-shaped curves to the measured responses to a small subset of discrete stimuli in the relevant dimension. However, as neuronal responses are irregular and experimental measurements noisy, it is often difficult to determine reliably the appropriate model from the data. We illustrate this general problem by fitting diverse models to representative recordings from area MT in rhesus monkey visual cortex during multiple attentional tasks involving complex composite stimuli. We find that all models can be well-fitted, that the best model generally varies between neurons and that statistical comparisons between neuronal responses across different experimental conditions are affected quantitatively and qualitatively by specific model choices. As a robust alternative to an often arbitrary model selection, we introduce a model-free approach, in which features of interest are extracted directly from the measured response data without the need of fitting any model. In our attentional datasets, we demonstrate that data-driven methods provide descriptions of tuning curve features such as preferred stimulus direction or attentional gain modulations which are in agreement with fit-based approaches when a good fit exists. Furthermore, these methods naturally extend to the frequent cases of uncertain model selection. We show that model-free approaches can identify attentional modulation patterns, such as general alterations of the irregular shape of tuning curves, which cannot be captured by fitting stereotyped conventional models. Finally, by comparing datasets across different conditions, we demonstrate effects of attention that are cell- and even stimulus-specific. Based on these proofs-of-concept, we conclude that our data-driven methods can reliably extract relevant tuning information from neuronal recordings, including cells whose seemingly haphazard response curves defy conventional fitting approaches.

Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data

PubMed Central

Helmer, Markus; Kozyrev, Vladislav; Stephan, Valeska; Treue, Stefan; Geisel, Theo; Battaglia, Demian

2016-01-01

Tuning curves are the functions that relate the responses of sensory neurons to various values within one continuous stimulus dimension (such as the orientation of a bar in the visual domain or the frequency of a tone in the auditory domain). They are commonly determined by fitting a model e.g. a Gaussian or other bell-shaped curves to the measured responses to a small subset of discrete stimuli in the relevant dimension. However, as neuronal responses are irregular and experimental measurements noisy, it is often difficult to determine reliably the appropriate model from the data. We illustrate this general problem by fitting diverse models to representative recordings from area MT in rhesus monkey visual cortex during multiple attentional tasks involving complex composite stimuli. We find that all models can be well-fitted, that the best model generally varies between neurons and that statistical comparisons between neuronal responses across different experimental conditions are affected quantitatively and qualitatively by specific model choices. As a robust alternative to an often arbitrary model selection, we introduce a model-free approach, in which features of interest are extracted directly from the measured response data without the need of fitting any model. In our attentional datasets, we demonstrate that data-driven methods provide descriptions of tuning curve features such as preferred stimulus direction or attentional gain modulations which are in agreement with fit-based approaches when a good fit exists. Furthermore, these methods naturally extend to the frequent cases of uncertain model selection. We show that model-free approaches can identify attentional modulation patterns, such as general alterations of the irregular shape of tuning curves, which cannot be captured by fitting stereotyped conventional models. Finally, by comparing datasets across different conditions, we demonstrate effects of attention that are cell- and even stimulus-specific. Based on these proofs-of-concept, we conclude that our data-driven methods can reliably extract relevant tuning information from neuronal recordings, including cells whose seemingly haphazard response curves defy conventional fitting approaches. PMID:26785378

Toward Continuous GPS Carrier-Phase Time Transfer: Eliminating the Time Discontinuity at an Anomaly

PubMed Central

Yao, Jian; Levine, Judah; Weiss, Marc

2015-01-01

The wide application of Global Positioning System (GPS) carrier-phase (CP) time transfer is limited by the problem of boundary discontinuity (BD). The discontinuity has two categories. One is “day boundary discontinuity,” which has been studied extensively and can be solved by multiple methods [1–8]. The other category of discontinuity, called “anomaly boundary discontinuity (anomaly-BD),” comes from a GPS data anomaly. The anomaly can be a data gap (i.e., missing data), a GPS measurement error (i.e., bad data), or a cycle slip. Initial study of the anomaly-BD shows that we can fix the discontinuity if the anomaly lasts no more than 20 min, using the polynomial curve-fitting strategy to repair the anomaly [9]. However, sometimes, the data anomaly lasts longer than 20 min. Thus, a better curve-fitting strategy is in need. Besides, a cycle slip, as another type of data anomaly, can occur and lead to an anomaly-BD. To solve these problems, this paper proposes a new strategy, i.e., the satellite-clock-aided curve fitting strategy with the function of cycle slip detection. Basically, this new strategy applies the satellite clock correction to the GPS data. After that, we do the polynomial curve fitting for the code and phase data, as before. Our study shows that the phase-data residual is only ~3 mm for all GPS satellites. The new strategy also detects and finds the number of cycle slips by searching the minimum curve-fitting residual. Extensive examples show that this new strategy enables us to repair up to a 40-min GPS data anomaly, regardless of whether the anomaly is due to a data gap, a cycle slip, or a combination of the two. We also find that interference of the GPS signal, known as “jamming”, can possibly lead to a time-transfer error, and that this new strategy can compensate for jamming outages. Thus, the new strategy can eliminate the impact of jamming on time transfer. As a whole, we greatly improve the robustness of the GPS CP time transfer. PMID:26958451

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Tao; Li, Cheng; Huang, Can

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE PAGES

Ding, Tao; Li, Cheng; Huang, Can; ...

2017-01-09

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

Long-term predictive capability of erosion models

NASA Technical Reports Server (NTRS)

Veerabhadra, P.; Buckley, D. H.

1983-01-01

A brief overview of long-term cavitation and liquid impingement erosion and modeling methods proposed by different investigators, including the curve-fit approach is presented. A table was prepared to highlight the number of variables necessary for each model in order to compute the erosion-versus-time curves. A power law relation based on the average erosion rate is suggested which may solve several modeling problems.

A Modified LS+AR Model to Improve the Accuracy of the Short-term Polar Motion Prediction

NASA Astrophysics Data System (ADS)

Wang, Z. W.; Wang, Q. X.; Ding, Y. Q.; Zhang, J. J.; Liu, S. S.

2017-03-01

There are two problems of the LS (Least Squares)+AR (AutoRegressive) model in polar motion forecast: the inner residual value of LS fitting is reasonable, but the residual value of LS extrapolation is poor; and the LS fitting residual sequence is non-linear. It is unsuitable to establish an AR model for the residual sequence to be forecasted, based on the residual sequence before forecast epoch. In this paper, we make solution to those two problems with two steps. First, restrictions are added to the two endpoints of LS fitting data to fix them on the LS fitting curve. Therefore, the fitting values next to the two endpoints are very close to the observation values. Secondly, we select the interpolation residual sequence of an inward LS fitting curve, which has a similar variation trend as the LS extrapolation residual sequence, as the modeling object of AR for the residual forecast. Calculation examples show that this solution can effectively improve the short-term polar motion prediction accuracy by the LS+AR model. In addition, the comparison results of the forecast models of RLS (Robustified Least Squares)+AR, RLS+ARIMA (AutoRegressive Integrated Moving Average), and LS+ANN (Artificial Neural Network) confirm the feasibility and effectiveness of the solution for the polar motion forecast. The results, especially for the polar motion forecast in the 1-10 days, show that the forecast accuracy of the proposed model can reach the world level.

Simplified curve fits for the thermodynamic properties of equilibrium air

NASA Technical Reports Server (NTRS)

Srinivasan, S.; Tannehill, J. C.; Weilmuenster, K. J.

1987-01-01

New, improved curve fits for the thermodynamic properties of equilibrium air have been developed. The curve fits are for pressure, speed of sound, temperature, entropy, enthalpy, density, and internal energy. These curve fits can be readily incorporated into new or existing computational fluid dynamics codes if real gas effects are desired. The curve fits are constructed from Grabau-type transition functions to model the thermodynamic surfaces in a piecewise manner. The accuracies and continuity of these curve fits are substantially improved over those of previous curve fits. These improvements are due to the incorporation of a small number of additional terms in the approximating polynomials and careful choices of the transition functions. The ranges of validity of the new curve fits are temperatures up to 25 000 K and densities from 10 to the -7 to 10 to the 3d power amagats.

Study on efficiency droop in InGaN/GaN light-emitting diodes based on differential carrier lifetime analysis

NASA Astrophysics Data System (ADS)

Meng, Xiao; Wang, Lai; Hao, Zhibiao; Luo, Yi; Sun, Changzheng; Han, Yanjun; Xiong, Bing; Wang, Jian; Li, Hongtao

2016-01-01

Efficiency droop is currently one of the most popular research problems for GaN-based light-emitting diodes (LEDs). In this work, a differential carrier lifetime measurement system is optimized to accurately determine carrier lifetimes (τ) of blue and green LEDs under different injection current (I). By fitting the τ-I curves and the efficiency droop curves of the LEDs according to the ABC carrier rate equation model, the impact of Auger recombination and carrier leakage on efficiency droop can be characterized simultaneously. For the samples used in this work, it is found that the experimental τ-I curves cannot be described by Auger recombination alone. Instead, satisfactory fitting results are obtained by taking both carrier leakage and carriers delocalization into account, which implies carrier leakage plays a more significant role in efficiency droop at high injection level.

Nonlinear Curve-Fitting Program

NASA Technical Reports Server (NTRS)

Everhart, Joel L.; Badavi, Forooz F.

1989-01-01

Nonlinear optimization algorithm helps in finding best-fit curve. Nonlinear Curve Fitting Program, NLINEAR, interactive curve-fitting routine based on description of quadratic expansion of X(sup 2) statistic. Utilizes nonlinear optimization algorithm calculating best statistically weighted values of parameters of fitting function and X(sup 2) minimized. Provides user with such statistical information as goodness of fit and estimated values of parameters producing highest degree of correlation between experimental data and mathematical model. Written in FORTRAN 77.

Simplified curve fits for the thermodynamic properties of equilibrium air

NASA Technical Reports Server (NTRS)

Srinivasan, S.; Tannehill, J. C.; Weilmuenster, K. J.

1986-01-01

New improved curve fits for the thermodynamic properties of equilibrium air were developed. The curve fits are for p = p(e,rho), a = a(e,rho), T = T(e,rho), s = s(e,rho), T = T(p,rho), h = h(p,rho), rho = rho(p,s), e = e(p,s) and a = a(p,s). These curve fits can be readily incorporated into new or existing Computational Fluid Dynamics (CFD) codes if real-gas effects are desired. The curve fits were constructed using Grabau-type transition functions to model the thermodynamic surfaces in a piecewise manner. The accuracies and continuity of these curve fits are substantially improved over those of previous curve fits appearing in NASA CR-2470. These improvements were due to the incorporation of a small number of additional terms in the approximating polynomials and careful choices of the transition functions. The ranges of validity of the new curve fits are temperatures up to 25,000 K and densities from 10 to the minus 7th to 100 amagats (rho/rho sub 0).

Escaping the snare of chronological growth and launching a free curve alternative: general deviance as latent growth model.

PubMed

Wood, Phillip Karl; Jackson, Kristina M

2013-08-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating "protective" or "launch" factors or as "developmental snares." These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of "general deviance" over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the "general deviance" model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of "general deviance" can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the "snares" alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control.

Escaping the snare of chronological growth and launching a free curve alternative: General deviance as latent growth model

PubMed Central

WOOD, PHILLIP KARL; JACKSON, KRISTINA M.

2014-01-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating “protective” or “launch” factors or as “developmental snares.” These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of “general deviance” over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the “general deviance” model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of “general deviance” can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the “snares” alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control. PMID:23880389

Synchronous Phasor-like Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirkham, Harold; Dagle, Jeffery E.

2014-02-14

Phasor measurement units struggle to make acceptable estimates of frequency and rate of change of frequency. The most important cause of the problem is that the quantity being measured is not actually a phasor. The paper substitutes a different equation for the phasor equatin, and obtains its solution by curve-fitting.

Fitting the multitemporal curve: a fourier series approach to the missing data problem in remote sensing analysis

Treesearch

Evan Brooks; Valerie Thomas; Wynne Randolph; John Coulston

2012-01-01

With the advent of free Landsat data stretching back decades, there has been a surge of interest in utilizing remotely sensed data in multitemporal analysis for estimation of biophysical parameters. Such analysis is confounded by cloud cover and other image-specific problems, which result in missing data at various aperiodic times of the year. While there is a wealth...

An interactive user-friendly approach to surface-fitting three-dimensional geometries

NASA Technical Reports Server (NTRS)

Cheatwood, F. Mcneil; Dejarnette, Fred R.

1988-01-01

A surface-fitting technique has been developed which addresses two problems with existing geometry packages: computer storage requirements and the time required of the user for the initial setup of the geometry model. Coordinates of cross sections are fit using segments of general conic sections. The next step is to blend the cross-sectional curve-fits in the longitudinal direction using general conics to fit specific meridional half-planes. Provisions are made to allow the fitting of fuselages and wings so that entire wing-body combinations may be modeled. This report includes the development of the technique along with a User's Guide for the various menus within the program. Results for the modeling of the Space Shuttle and a proposed Aeroassist Flight Experiment geometry are presented.

SORPTION AND DESORPTION BY IDEAL TWO-COMPARTMENT SYSTEMS: UNUSUAL BEHAVIOR AND DATA INTERPRETATION PROBLEMS

EPA Science Inventory

This paper presents an evaluation of the results of fitting curves to isotherm and kinetic data for idealized two-compartment systems of soil or sediment. Data were produced by numerically solving sets of Freundlich isotherm and first-order kinetics equations for mixtures of up ...

Global search in photoelectron diffraction structure determination using genetic algorithms

NASA Astrophysics Data System (ADS)

Viana, M. L.; Díez Muiño, R.; Soares, E. A.; Van Hove, M. A.; de Carvalho, V. E.

2007-11-01

Photoelectron diffraction (PED) is an experimental technique widely used to perform structural determinations of solid surfaces. Similarly to low-energy electron diffraction (LEED), structural determination by PED requires a fitting procedure between the experimental intensities and theoretical results obtained through simulations. Multiple scattering has been shown to be an effective approach for making such simulations. The quality of the fit can be quantified through the so-called R-factor. Therefore, the fitting procedure is, indeed, an R-factor minimization problem. However, the topography of the R-factor as a function of the structural and non-structural surface parameters to be determined is complex, and the task of finding the global minimum becomes tough, particularly for complex structures in which many parameters have to be adjusted. In this work we investigate the applicability of the genetic algorithm (GA) global optimization method to this problem. The GA is based on the evolution of species, and makes use of concepts such as crossover, elitism and mutation to perform the search. We show results of its application in the structural determination of three different systems: the Cu(111) surface through the use of energy-scanned experimental curves; the Ag(110)-c(2 × 2)-Sb system, in which a theory-theory fit was performed; and the Ag(111) surface for which angle-scanned experimental curves were used. We conclude that the GA is a highly efficient method to search for global minima in the optimization of the parameters that best fit the experimental photoelectron diffraction intensities to the theoretical ones.

Using a constrained formulation based on probability summation to fit receiver operating characteristic (ROC) curves

NASA Astrophysics Data System (ADS)

Swensson, Richard G.; King, Jill L.; Good, Walter F.; Gur, David

2000-04-01

A constrained ROC formulation from probability summation is proposed for measuring observer performance in detecting abnormal findings on medical images. This assumes the observer's detection or rating decision on each image is determined by a latent variable that characterizes the specific finding (type and location) considered most likely to be a target abnormality. For positive cases, this 'maximum- suspicion' variable is assumed to be either the value for the actual target or for the most suspicious non-target finding, whichever is the greater (more suspicious). Unlike the usual ROC formulation, this constrained formulation guarantees a 'well-behaved' ROC curve that always equals or exceeds chance- level decisions and cannot exhibit an upward 'hook.' Its estimated parameters specify the accuracy for separating positive from negative cases, and they also predict accuracy in locating or identifying the actual abnormal findings. The present maximum-likelihood procedure (runs on PC with Windows 95 or NT) fits this constrained formulation to rating-ROC data using normal distributions with two free parameters. Fits of the conventional and constrained ROC formulations are compared for continuous and discrete-scale ratings of chest films in a variety of detection problems, both for localized lesions (nodules, rib fractures) and for diffuse abnormalities (interstitial disease, infiltrates or pnumothorax). The two fitted ROC curves are nearly identical unless the conventional ROC has an ill behaved 'hook,' below the constrained ROC.

State estimation with incomplete nonlinear constraint

NASA Astrophysics Data System (ADS)

Huang, Yuan; Wang, Xueying; An, Wei

2017-10-01

A problem of state estimation with a new constraints named incomplete nonlinear constraint is considered. The targets are often move in the curve road, if the width of road is neglected, the road can be considered as the constraint, and the position of sensors, e.g., radar, is known in advance, this info can be used to enhance the performance of the tracking filter. The problem of how to incorporate the priori knowledge is considered. In this paper, a second-order sate constraint is considered. A fitting algorithm of ellipse is adopted to incorporate the priori knowledge by estimating the radius of the trajectory. The fitting problem is transformed to the nonlinear estimation problem. The estimated ellipse function is used to approximate the nonlinear constraint. Then, the typical nonlinear constraint methods proposed in recent works can be used to constrain the target state. Monte-Carlo simulation results are presented to illustrate the effectiveness proposed method in state estimation with incomplete constraint.

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

PubMed

Dung, Van Than; Tjahjowidodo, Tegoeh

2017-01-01

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.

Fitting Richards' curve to data of diverse origins

USGS Publications Warehouse

Johnson, D.H.; Sargeant, A.B.; Allen, S.H.

1975-01-01

Published techniques for fitting data to nonlinear growth curves are briefly reviewed, most techniques require knowledge of the shape of the curve. A flexible growth curve developed by Richards (1959) is discussed as an alternative when the shape is unknown. The shape of this curve is governed by a specific parameter which can be estimated from the data. We describe in detail the fitting of a diverse set of longitudinal and cross-sectional data to Richards' growth curve for the purpose of determining the age of red fox (Vulpes vulpes) pups on the basis of right hind foot length. The fitted curve is found suitable for pups less than approximately 80 days old. The curve is extrapolated to pre-natal growth and shown to be appropriate only for about 10 days prior to birth.

The complex variable boundary element method: Applications in determining approximative boundaries

USGS Publications Warehouse

Hromadka, T.V.

1984-01-01

The complex variable boundary element method (CVBEM) is used to determine approximation functions for boundary value problems of the Laplace equation such as occurs in potential theory. By determining an approximative boundary upon which the CVBEM approximator matches the desired constant (level curves) boundary conditions, the CVBEM is found to provide the exact solution throughout the interior of the transformed problem domain. Thus, the acceptability of the CVBEM approximation is determined by the closeness-of-fit of the approximative boundary to the study problem boundary. ?? 1984.

Energy functions for regularization algorithms

NASA Technical Reports Server (NTRS)

Delingette, H.; Hebert, M.; Ikeuchi, K.

1991-01-01

Regularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.

[Comparison among various software for LMS growth curve fitting methods].

PubMed

Han, Lin; Wu, Wenhong; Wei, Qiuxia

2015-03-01

To explore the methods to realize the growth curve fitting of coefficients of skewness-median-coefficient of variation (LMS) using different software, and to optimize growth curve statistical method for grass-root child and adolescent staffs. Regular physical examination data of head circumference for normal infants aging 3, 6, 9 and 12 months in Baotou City were analyzed. Statistical software such as SAS, R, STATA and SPSS were used to fit the LMS growth curve and the results were evaluated upon the user 's convenience, study circle, user interface, results display forms, software update and maintenance and so on. Growth curve fitting results showed the same calculation outcome and each of statistical software had its own advantages and disadvantages. With all the evaluation aspects in consideration, R software excelled others in LMS growth curve fitting. R software have the advantage over other software in grass roots child and adolescent staff.

On the convexity of ROC curves estimated from radiological test results.

PubMed

Pesce, Lorenzo L; Metz, Charles E; Berbaum, Kevin S

2010-08-01

Although an ideal observer's receiver operating characteristic (ROC) curve must be convex-ie, its slope must decrease monotonically-published fits to empirical data often display "hooks." Such fits sometimes are accepted on the basis of an argument that experiments are done with real, rather than ideal, observers. However, the fact that ideal observers must produce convex curves does not imply that convex curves describe only ideal observers. This article aims to identify the practical implications of nonconvex ROC curves and the conditions that can lead to empirical or fitted ROC curves that are not convex. This article views nonconvex ROC curves from historical, theoretical, and statistical perspectives, which we describe briefly. We then consider population ROC curves with various shapes and analyze the types of medical decisions that they imply. Finally, we describe how sampling variability and curve-fitting algorithms can produce ROC curve estimates that include hooks. We show that hooks in population ROC curves imply the use of an irrational decision strategy, even when the curve does not cross the chance line, and therefore usually are untenable in medical settings. Moreover, we sketch a simple approach to improve any nonconvex ROC curve by adding statistical variation to the decision process. Finally, we sketch how to test whether hooks present in ROC data are likely to have been caused by chance alone and how some hooked ROCs found in the literature can be easily explained as fitting artifacts or modeling issues. In general, ROC curve fits that show hooks should be looked on with suspicion unless other arguments justify their presence. 2010 AUR. Published by Elsevier Inc. All rights reserved.

On the convexity of ROC curves estimated from radiological test results

PubMed Central

Pesce, Lorenzo L.; Metz, Charles E.; Berbaum, Kevin S.

2010-01-01

Rationale and Objectives Although an ideal observer’s receiver operating characteristic (ROC) curve must be convex — i.e., its slope must decrease monotonically — published fits to empirical data often display “hooks.” Such fits sometimes are accepted on the basis of an argument that experiments are done with real, rather than ideal, observers. However, the fact that ideal observers must produce convex curves does not imply that convex curves describe only ideal observers. This paper aims to identify the practical implications of non-convex ROC curves and the conditions that can lead to empirical and/or fitted ROC curves that are not convex. Materials and Methods This paper views non-convex ROC curves from historical, theoretical and statistical perspectives, which we describe briefly. We then consider population ROC curves with various shapes and analyze the types of medical decisions that they imply. Finally, we describe how sampling variability and curve-fitting algorithms can produce ROC curve estimates that include hooks. Results We show that hooks in population ROC curves imply the use of an irrational decision strategy, even when the curve doesn’t cross the chance line, and therefore usually are untenable in medical settings. Moreover, we sketch a simple approach to improve any non-convex ROC curve by adding statistical variation to the decision process. Finally, we sketch how to test whether hooks present in ROC data are likely to have been caused by chance alone and how some hooked ROCs found in the literature can be easily explained as fitting artifacts or modeling issues. Conclusion In general, ROC curve fits that show hooks should be looked upon with suspicion unless other arguments justify their presence. PMID:20599155

Curve fitting methods for solar radiation data modeling

NASA Astrophysics Data System (ADS)

Karim, Samsul Ariffin Abdul; Singh, Balbir Singh Mahinder

2014-10-01

This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R2. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.

Curve fitting methods for solar radiation data modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karim, Samsul Ariffin Abdul, E-mail: samsul-ariffin@petronas.com.my, E-mail: balbir@petronas.com.my; Singh, Balbir Singh Mahinder, E-mail: samsul-ariffin@petronas.com.my, E-mail: balbir@petronas.com.my

2014-10-24

This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R{sup 2}. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both withmore » two terms) gives better results as compare with the other fitting methods.« less

Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

PubMed

Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

2017-02-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

Effect Size Measure and Analysis of Single Subject Designs

ERIC Educational Resources Information Center

Society for Research on Educational Effectiveness, 2013

2013-01-01

One of the vexing problems in the analysis of SSD is in the assessment of the effect of intervention. Serial dependence notwithstanding, the linear model approach that has been advanced involves, in general, the fitting of regression lines (or curves) to the set of observations within each phase of the design and comparing the parameters of these…

Corvettes, Curve Fitting, and Calculus

ERIC Educational Resources Information Center

Murawska, Jaclyn M.; Nabb, Keith A.

2015-01-01

Sometimes the best mathematics problems come from the most unexpected situations. Last summer, a Corvette raced down a local quarter-mile drag strip. The driver, a family member, provided the spectators with time and distance-traveled data from his time slip and asked "Can you calculate how many seconds it took me to go from 0 to 60…

Four New Binary Stars in the Field of CL Aurigae. II

NASA Astrophysics Data System (ADS)

Kim, Chun-Hwey; Lee, Jae Woo; Duck, Hyun Kim; Andronov, Ivan L.

2010-12-01

We report on a discovery of four new variable stars (USNO-B1.0 1234-0103195, 1235- 0097170, 1236-0100293 and 1236-0100092) in the field of CL Aur. The stars are classified as eclipsing binary stars with orbital periods of 0.5137413(23) (EW type), 0.8698365(26) (EA) and 4.0055842(40) (EA with a significant orbital eccentricity), respectively. The fourth star (USNO-B1.0 1236-0100092) showed only one partial ascending branch of the light curves, although 22 nights were covered at the 61-cm telescope at the Sobaeksan Optical Astronomy Observatory (SOAO) in Korea. Fourteen minima timings for these stars are published separately. In an addition to the original discovery paper (Kim et al. 2010), we discuss methodological problems and present results of mathematical modeling of the light curves using other methods, i.e. trigonometric polynomial fits and the newly developed fit "NAV" ("New Algol Variable").

An accurate surface topography restoration algorithm for white light interferometry

NASA Astrophysics Data System (ADS)

Yuan, He; Zhang, Xiangchao; Xu, Min

2017-10-01

As an important measuring technique, white light interferometry can realize fast and non-contact measurement, thus it is now widely used in the field of ultra-precision engineering. However, the traditional recovery algorithms of surface topographies have flaws and limits. In this paper, we propose a new algorithm to solve these problems. It is a combination of Fourier transform and improved polynomial fitting method. Because the white light interference signal is usually expressed as a cosine signal whose amplitude is modulated by a Gaussian function, its fringe visibility is not constant and varies with different scanning positions. The interference signal is processed first by Fourier transform, then the positive frequency part is selected and moved back to the center of the amplitude-frequency curve. In order to restore the surface morphology, a polynomial fitting method is used to fit the amplitude curve after inverse Fourier transform and obtain the corresponding topography information. The new method is then compared to the traditional algorithms. It is proved that the aforementioned drawbacks can be effectively overcome. The relative error is less than 0.8%.

Surface Fitting for Quasi Scattered Data from Coordinate Measuring Systems.

PubMed

Mao, Qing; Liu, Shugui; Wang, Sen; Ma, Xinhui

2018-01-13

Non-uniform rational B-spline (NURBS) surface fitting from data points is wildly used in the fields of computer aided design (CAD), medical imaging, cultural relic representation and object-shape detection. Usually, the measured data acquired from coordinate measuring systems is neither gridded nor completely scattered. The distribution of this kind of data is scattered in physical space, but the data points are stored in a way consistent with the order of measurement, so it is named quasi scattered data in this paper. Therefore they can be organized into rows easily but the number of points in each row is random. In order to overcome the difficulty of surface fitting from this kind of data, a new method based on resampling is proposed. It consists of three major steps: (1) NURBS curve fitting for each row, (2) resampling on the fitted curve and (3) surface fitting from the resampled data. Iterative projection optimization scheme is applied in the first and third step to yield advisable parameterization and reduce the time cost of projection. A resampling approach based on parameters, local peaks and contour curvature is proposed to overcome the problems of nodes redundancy and high time consumption in the fitting of this kind of scattered data. Numerical experiments are conducted with both simulation and practical data, and the results show that the proposed method is fast, effective and robust. What's more, by analyzing the fitting results acquired form data with different degrees of scatterness it can be demonstrated that the error introduced by resampling is negligible and therefore it is feasible.

Curve fitting air sample filter decay curves to estimate transuranic content.

PubMed

Hayes, Robert B; Chiou, Hung Cheng

2004-01-01

By testing industry standard techniques for radon progeny evaluation on air sample filters, a new technique is developed to evaluate transuranic activity on air filters by curve fitting the decay curves. The industry method modified here is simply the use of filter activity measurements at different times to estimate the air concentrations of radon progeny. The primary modification was to not look for specific radon progeny values but rather transuranic activity. By using a method that will provide reasonably conservative estimates of the transuranic activity present on a filter, some credit for the decay curve shape can then be taken. By carrying out rigorous statistical analysis of the curve fits to over 65 samples having no transuranic activity taken over a 10-mo period, an optimization of the fitting function and quality tests for this purpose was attained.

Handling of computational in vitro/in vivo correlation problems by Microsoft Excel: I. Principles and some general algorithms.

PubMed

Langenbucher, Frieder

2002-01-01

Most computations in the field of in vitro/in vivo correlations can be handled directly by Excel worksheets, without the need for specialized software. Following a summary of Excel features, applications are illustrated for numerical computation of AUC and Mean, Wagner-Nelson and Loo-Riegelman absorption plots, and polyexponential curve fitting.

Promoting convergence: The Phi spiral in abduction of mouse corneal behaviors

PubMed Central

Rhee, Jerry; Nejad, Talisa Mohammad; Comets, Olivier; Flannery, Sean; Gulsoy, Eine Begum; Iannaccone, Philip; Foster, Craig

2015-01-01

Why do mouse corneal epithelial cells display spiraling patterns? We want to provide an explanation for this curious phenomenon by applying an idealized problem solving process. Specifically, we applied complementary line-fitting methods to measure transgenic epithelial reporter expression arrangements displayed on three mature, live enucleated globes to clarify the problem. Two prominent logarithmic curves were discovered, one of which displayed the ϕ ratio, an indicator of an optimal configuration in phyllotactic systems. We then utilized two different computational approaches to expose our current understanding of the behavior. In one procedure, which involved an isotropic mechanics-based finite element method, we successfully produced logarithmic spiral curves of maximum shear strain based pathlines but computed dimensions displayed pitch angles of 35° (ϕ spiral is ∼17°), which was altered when we fitted the model with published measurements of coarse collagen orientations. We then used model-based reasoning in context of Peircean abduction to select a working hypothesis. Our work serves as a concise example of applying a scientific habit of mind and illustrates nuances of executing a common method to doing integrative science. © 2014 Wiley Periodicals, Inc. Complexity 20: 22–38, 2015 PMID:25755620

The curvature of sensitometric curves for Kodak XV-2 film irradiated with photon and electron beams.

PubMed

van Battum, L J; Huizenga, H

2006-07-01

Sensitometric curves of Kodak XV-2 film, obtained in a time period of ten years with various types of equipment, have been analyzed both for photon and electron beams. The sensitometric slope in the dataset varies more than a factor of 2, which is attributed mainly to variations in developer conditions. In the literature, the single hit equation has been proposed as a model for the sensitometric curve, as with the parameters of the sensitivity and maximum optical density. In this work, the single hit equation has been translated into a polynomial like function as with the parameters of the sensitometric slope and curvature. The model has been applied to fit the sensitometric data. If the dataset is fitted for each single sensitometric curve separately, a large variation is observed for both fit parameters. When sensitometric curves are fitted simultaneously it appears that all curves can be fitted adequately with a sensitometric curvature that is related to the sensitometric slope. When fitting each curve separately, apparently measurement uncertainty hides this relation. This relation appears to be dependent only on the type of densitometer used. No significant differences between beam energies or beam modalities are observed. Using the intrinsic relation between slope and curvature in fitting sensitometric data, e.g., for pretreatment verification of intensity-modulated radiotherapy, will increase the accuracy of the sensitometric curve. A calibration at a single dose point, together with a predetermined densitometer-dependent parameter ODmax will be adequate to find the actual relation between optical density and dose.

Anomalous diffusion and dynamics of fluorescence recovery after photobleaching in the random-comb model

NASA Astrophysics Data System (ADS)

Yuste, S. B.; Abad, E.; Baumgaertner, A.

2016-07-01

We address the problem of diffusion on a comb whose teeth display varying lengths. Specifically, the length ℓ of each tooth is drawn from a probability distribution displaying power law behavior at large ℓ ,P (ℓ ) ˜ℓ-(1 +α ) (α >0 ). To start with, we focus on the computation of the anomalous diffusion coefficient for the subdiffusive motion along the backbone. This quantity is subsequently used as an input to compute concentration recovery curves mimicking fluorescence recovery after photobleaching experiments in comblike geometries such as spiny dendrites. Our method is based on the mean-field description provided by the well-tested continuous time random-walk approach for the random-comb model, and the obtained analytical result for the diffusion coefficient is confirmed by numerical simulations of a random walk with finite steps in time and space along the backbone and the teeth. We subsequently incorporate retardation effects arising from binding-unbinding kinetics into our model and obtain a scaling law characterizing the corresponding change in the diffusion coefficient. Finally, we show that recovery curves obtained with the help of the analytical expression for the anomalous diffusion coefficient cannot be fitted perfectly by a model based on scaled Brownian motion, i.e., a standard diffusion equation with a time-dependent diffusion coefficient. However, differences between the exact curves and such fits are small, thereby providing justification for the practical use of models relying on scaled Brownian motion as a fitting procedure for recovery curves arising from particle diffusion in comblike systems.

Mixing-controlled reactive transport on travel times in heterogeneous media

NASA Astrophysics Data System (ADS)

Luo, J.; Cirpka, O.

2008-05-01

Modeling mixing-controlled reactive transport using traditional spatial discretization of the domain requires identifying the spatial distributions of hydraulic and reactive parameters including mixing-related quantities such as dispersivities and kinetic mass-transfer coefficients. In most applications, breakthrough curves of conservative and reactive compounds are measured at only a few locations and models are calibrated by matching these breakthrough curves, which is an ill posed inverse problem. By contrast, travel-time based transport models avoid costly aquifer characterization. By considering breakthrough curves measured on different scales, one can distinguish between mixing, which is a prerequisite for reactions, and spreading, which per se does not foster reactions. In the travel-time based framework, the breakthrough curve of a solute crossing an observation plane, or ending in a well, is interpreted as the weighted average of concentrations in an ensemble of non-interacting streamtubes, each of which is characterized by a distinct travel-time value. Mixing is described by longitudinal dispersion and/or kinetic mass transfer along individual streamtubes, whereas spreading is characterized by the distribution of travel times which also determines the weights associated to each stream tube. Key issues in using the travel-time based framework include the description of mixing mechanisms and the estimation of the travel-time distribution. In this work, we account for both apparent longitudinal dispersion and kinetic mass transfer as mixing mechanisms, thus generalizing the stochastic-convective model with or without inter-phase mass transfer and the advective-dispersive streamtube model. We present a nonparametric approach of determining the travel-time distribution, given a breakthrough curve integrated over an observation plane and estimated mixing parameters. The latter approach is superior to fitting parametric models in cases where the true travel-time distribution exhibits multiple peaks or long tails. It is demonstrated that there is freedom for the combinations of mixing parameters and travel-time distributions to fit conservative breakthrough curves and describe the tailing. Reactive transport cases with a bimolecular instantaneous irreversible reaction and a dual Michaelis-Menten problem demonstrate that the mixing introduced by local dispersion and mass transfer may be described by apparent mean mass transfer with coefficients evaluated by local breakthrough curves.

Real-Time Exponential Curve Fits Using Discrete Calculus

NASA Technical Reports Server (NTRS)

Rowe, Geoffrey

2010-01-01

An improved solution for curve fitting data to an exponential equation (y = Ae(exp Bt) + C) has been developed. This improvement is in four areas -- speed, stability, determinant processing time, and the removal of limits. The solution presented avoids iterative techniques and their stability errors by using three mathematical ideas: discrete calculus, a special relationship (be tween exponential curves and the Mean Value Theorem for Derivatives), and a simple linear curve fit algorithm. This method can also be applied to fitting data to the general power law equation y = Ax(exp B) + C and the general geometric growth equation y = Ak(exp Bt) + C.

Comparison of Themodynamic and Transport Property Models for Computing Equilibrium High Enthalpy Flows

NASA Astrophysics Data System (ADS)

Ramasahayam, Veda Krishna Vyas; Diwakar, Anant; Bodi, Kowsik

2017-11-01

To study the flow of high temperature air in vibrational and chemical equilibrium, accurate models for thermodynamic state and transport phenomena are required. In the present work, the performance of a state equation model and two mixing rules for determining equilibrium air thermodynamic and transport properties are compared with that of curve fits. The thermodynamic state model considers 11 species which computes flow chemistry by an iterative process and the mixing rules considered for viscosity are Wilke and Armaly-Sutton. The curve fits of Srinivasan, which are based on Grabau type transition functions, are chosen for comparison. A two-dimensional Navier-Stokes solver is developed to simulate high enthalpy flows with numerical fluxes computed by AUSM+-up. The accuracy of state equation model and curve fits for thermodynamic properties is determined using hypersonic inviscid flow over a circular cylinder. The performance of mixing rules and curve fits for viscosity are compared using hypersonic laminar boundary layer prediction on a flat plate. It is observed that steady state solutions from state equation model and curve fits match with each other. Though curve fits are significantly faster the state equation model is more general and can be adapted to any flow composition.

Testing Modified Newtonian Dynamics with Low Surface Brightness Galaxies: Rotation Curve FITS

NASA Astrophysics Data System (ADS)

de Blok, W. J. G.; McGaugh, S. S.

1998-11-01

We present modified Newtonian dynamics (MOND) fits to 15 rotation curves of low surface brightness (LSB) galaxies. Good fits are readily found, although for a few galaxies minor adjustments to the inclination are needed. Reasonable values for the stellar mass-to-light ratios are found, as well as an approximately constant value for the total (gas and stars) mass-to-light ratio. We show that the LSB galaxies investigated here lie on the one, unique Tully-Fisher relation, as predicted by MOND. The scatter on the Tully-Fisher relation can be completely explained by the observed scatter in the total mass-to-light ratio. We address the question of whether MOND can fit any arbitrary rotation curve by constructing a plausible fake model galaxy. While MOND is unable to fit this hypothetical galaxy, a normal dark-halo fit is readily found, showing that dark matter fits are much less selective in producing fits. The good fits to rotation curves of LSB galaxies support MOND, especially because these are galaxies with large mass discrepancies deep in the MOND regime.

Evaluating Model Fit for Growth Curve Models: Integration of Fit Indices from SEM and MLM Frameworks

ERIC Educational Resources Information Center

Wu, Wei; West, Stephen G.; Taylor, Aaron B.

2009-01-01

Evaluating overall model fit for growth curve models involves 3 challenging issues. (a) Three types of longitudinal data with different implications for model fit may be distinguished: balanced on time with complete data, balanced on time with data missing at random, and unbalanced on time. (b) Traditional work on fit from the structural equation…

Clarifications regarding the use of model-fitting methods of kinetic analysis for determining the activation energy from a single non-isothermal curve.

PubMed

Sánchez-Jiménez, Pedro E; Pérez-Maqueda, Luis A; Perejón, Antonio; Criado, José M

2013-02-05

This paper provides some clarifications regarding the use of model-fitting methods of kinetic analysis for estimating the activation energy of a process, in response to some results recently published in Chemistry Central journal. The model fitting methods of Arrhenius and Savata are used to determine the activation energy of a single simulated curve. It is shown that most kinetic models correctly fit the data, each providing a different value for the activation energy. Therefore it is not really possible to determine the correct activation energy from a single non-isothermal curve. On the other hand, when a set of curves are recorded under different heating schedules are used, the correct kinetic parameters can be clearly discerned. Here, it is shown that the activation energy and the kinetic model cannot be unambiguously determined from a single experimental curve recorded under non isothermal conditions. Thus, the use of a set of curves recorded under different heating schedules is mandatory if model-fitting methods are employed.

Methods for scalar-on-function regression.

PubMed

Reiss, Philip T; Goldsmith, Jeff; Shang, Han Lin; Ogden, R Todd

2017-08-01

Recent years have seen an explosion of activity in the field of functional data analysis (FDA), in which curves, spectra, images, etc. are considered as basic functional data units. A central problem in FDA is how to fit regression models with scalar responses and functional data points as predictors. We review some of the main approaches to this problem, categorizing the basic model types as linear, nonlinear and nonparametric. We discuss publicly available software packages, and illustrate some of the procedures by application to a functional magnetic resonance imaging dataset.

Reducing errors in the GRACE gravity solutions using regularization

NASA Astrophysics Data System (ADS)

Save, Himanshu; Bettadpur, Srinivas; Tapley, Byron D.

2012-09-01

The nature of the gravity field inverse problem amplifies the noise in the GRACE data, which creeps into the mid and high degree and order harmonic coefficients of the Earth's monthly gravity fields provided by GRACE. Due to the use of imperfect background models and data noise, these errors are manifested as north-south striping in the monthly global maps of equivalent water heights. In order to reduce these errors, this study investigates the use of the L-curve method with Tikhonov regularization. L-curve is a popular aid for determining a suitable value of the regularization parameter when solving linear discrete ill-posed problems using Tikhonov regularization. However, the computational effort required to determine the L-curve is prohibitively high for a large-scale problem like GRACE. This study implements a parameter-choice method, using Lanczos bidiagonalization which is a computationally inexpensive approximation to L-curve. Lanczos bidiagonalization is implemented with orthogonal transformation in a parallel computing environment and projects a large estimation problem on a problem of the size of about 2 orders of magnitude smaller for computing the regularization parameter. Errors in the GRACE solution time series have certain characteristics that vary depending on the ground track coverage of the solutions. These errors increase with increasing degree and order. In addition, certain resonant and near-resonant harmonic coefficients have higher errors as compared with the other coefficients. Using the knowledge of these characteristics, this study designs a regularization matrix that provides a constraint on the geopotential coefficients as a function of its degree and order. This regularization matrix is then used to compute the appropriate regularization parameter for each monthly solution. A 7-year time-series of the candidate regularized solutions (Mar 2003-Feb 2010) show markedly reduced error stripes compared with the unconstrained GRACE release 4 solutions (RL04) from the Center for Space Research (CSR). Post-fit residual analysis shows that the regularized solutions fit the data to within the noise level of GRACE. A time series of filtered hydrological model is used to confirm that signal attenuation for basins in the Total Runoff Integrating Pathways (TRIP) database over 320 km radii is less than 1 cm equivalent water height RMS, which is within the noise level of GRACE.

Quantifying and Reducing Curve-Fitting Uncertainty in Isc

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campanelli, Mark; Duck, Benjamin; Emery, Keith

2015-06-14

Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data pointsmore » can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.« less

Nonlinear method for including the mass uncertainty of standards and the system measurement errors in the fitting of calibration curves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pickles, W.L.; McClure, J.W.; Howell, R.H.

1978-01-01

A sophisticated non-linear multiparameter fitting program has been used to produce a best fit calibration curve for the response of an x-ray fluorescence analyzer to uranium nitrate, freeze dried, 0.2% accurate, gravimetric standards. The program is based on unconstrained minimization subroutine, VA02A. The program considers the mass values of the gravimetric standards as parameters to be fit along with the normal calibration curve parameters. The fitting procedure weights with the system errors and the mass errors in a consistent way. The resulting best fit calibration curve parameters reflect the fact that the masses of the standard samples are measured quantitiesmore » with a known error. Error estimates for the calibration curve parameters can be obtined from the curvature of the Chi-Squared Matrix or from error relaxation techniques. It has been shown that non-dispersive x-ray fluorescence analysis of 0.1 to 1 mg freeze-dried UNO/sub 3/ can have an accuracy of 0.2% in 1000 sec.« less

Quantifying and Reducing Curve-Fitting Uncertainty in Isc: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campanelli, Mark; Duck, Benjamin; Emery, Keith

Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data pointsmore » can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.« less

Use of a non-linear method for including the mass uncertainty of gravimetric standards and system measurement errors in the fitting of calibration curves for XRFA freeze-dried UNO/sub 3/ standards

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pickles, W.L.; McClure, J.W.; Howell, R.H.

1978-05-01

A sophisticated nonlinear multiparameter fitting program was used to produce a best fit calibration curve for the response of an x-ray fluorescence analyzer to uranium nitrate, freeze dried, 0.2% accurate, gravimetric standards. The program is based on unconstrained minimization subroutine, VA02A. The program considers the mass values of the gravimetric standards as parameters to be fit along with the normal calibration curve parameters. The fitting procedure weights with the system errors and the mass errors in a consistent way. The resulting best fit calibration curve parameters reflect the fact that the masses of the standard samples are measured quantities withmore » a known error. Error estimates for the calibration curve parameters can be obtained from the curvature of the ''Chi-Squared Matrix'' or from error relaxation techniques. It was shown that nondispersive XRFA of 0.1 to 1 mg freeze-dried UNO/sub 3/ can have an accuracy of 0.2% in 1000 s.« less

Hierarchical Winner-Take-All Particle Swarm Optimization Social Network for Neural Model Fitting

PubMed Central

Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.

2016-01-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models. PMID:27726048

Curve Fitting via the Criterion of Least Squares. Applications of Algebra and Elementary Calculus to Curve Fitting. [and] Linear Programming in Two Dimensions: I. Applications of High School Algebra to Operations Research. Modules and Monographs in Undergraduate Mathematics and Its Applications Project. UMAP Units 321, 453.

ERIC Educational Resources Information Center

Alexander, John W., Jr.; Rosenberg, Nancy S.

This document consists of two modules. The first of these views applications of algebra and elementary calculus to curve fitting. The user is provided with information on how to: 1) construct scatter diagrams; 2) choose an appropriate function to fit specific data; 3) understand the underlying theory of least squares; 4) use a computer program to…

Microlensing results toward the galactic bulge, theory of fitting blended light curves, and discussion of weak lensing corrections

NASA Astrophysics Data System (ADS)

Thomas, Christian L.

2006-06-01

Analysis and results (Chapters 2-5) of the full 7 year Macho Project dataset toward the Galactic bulge are presented. A total of 450 high quality, relatively large signal-to-noise ratio, events are found, including several events exhibiting exotic effects, and lensing events on possible Sagittarius dwarf galaxy stars. We examine the problem of blending in our sample and conclude that the subset of red clump giants are minimally blended. Using 42 red clump giant events near the Galactic center we calculate the optical depth toward the Galactic bulge to be t = [Special characters omitted.] × 10 -6 at ( l, b ) = ([Special characters omitted.] ) with a gradient of (1.06 ± 0.71) × 10 -6 deg -1 in latitude, and (0.29±0.43) × 10 -6 deg -1 in longitude, bringing measurements into consistency with the models for the first time. In Chapter 6 we reexamine the usefulness of fitting blended light-curve models to microlensing photometric data. We find agreement with previous workers (e.g. Wozniak & Paczynski) that this is a difficult proposition because of the degeneracy of blend fraction with other fit parameters. We show that follow-up observations at specific points along the light curve (peak region and wings) of high magnification events are the most helpful in removing degeneracies. We also show that very small errors in the baseline magnitude can result in problems in measuring the blend fraction, and study the importance of non- Gaussian errors in the fit results. The biases and skewness in the distribution of the recovered blend fraction is discussed. We also find a new approximation formula relating the blend fraction and the unblended fit parameters to the underlying event duration needed to estimate microlensing optical depth. In Chapter 7 we present work-in-progress on the possibility of correcting standard candle luminosities for the magnification due to weak lensing. We consider the importance of lenses in different mass ranges and look at the contribution from lenses that could not be observed. We conclude that it may be possible to perform this correction with relatively high precision (1-2%) and discuss possible sources of error and methods of improving our model.

Parameter setting for peak fitting method in XPS analysis of nitrogen in sewage sludge

NASA Astrophysics Data System (ADS)

Tang, Z. J.; Fang, P.; Huang, J. H.; Zhong, P. Y.

2017-12-01

Thermal decomposition method is regarded as an important route to treat increasing sewage sludge, while the high content of N causes serious nitrogen related problems, then figuring out the existing form and content of nitrogen of sewage sludge become essential. In this study, XPSpeak 4.1 was used to investigate the functional forms of nitrogen in sewage sludge, peak fitting method was adopted and the best-optimized parameters were determined. According to the result, the N1s spectra curve can be resolved into 5 peaks: pyridine-N (398.7±0.4eV), pyrrole-N(400.5±0.3eV), protein-N(400.4eV), ammonium-N(401.1±0.3eV) and nitrogen oxide-N(403.5±0.5eV). Based on the the experimental data obtained from elemental analysis and spectrophotometry method, the optimum parameters of curve fitting method were decided: background type: Tougaard, FWHM 1.2, 50% Lorentzian-Gaussian. XPS methods can be used as a practical tool to analysis the nitrogen functional groups of sewage sludge, which can reflect the real content of nitrogen of different forms.

Least-Squares Curve-Fitting Program

NASA Technical Reports Server (NTRS)

Kantak, Anil V.

1990-01-01

Least Squares Curve Fitting program, AKLSQF, easily and efficiently computes polynomial providing least-squares best fit to uniformly spaced data. Enables user to specify tolerable least-squares error in fit or degree of polynomial. AKLSQF returns polynomial and actual least-squares-fit error incurred in operation. Data supplied to routine either by direct keyboard entry or via file. Written for an IBM PC X/AT or compatible using Microsoft's Quick Basic compiler.

Galaxy luminosity function and Tully-Fisher relation: reconciled through rotation-curve studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cattaneo, Andrea; Salucci, Paolo; Papastergis, Emmanouil, E-mail: andrea.cattaneo@oamp.fr, E-mail: salucci@sissa.it, E-mail: papastergis@astro.cornell.edu

2014-03-10

The relation between galaxy luminosity L and halo virial velocity v {sub vir} required to fit the galaxy luminosity function differs from the observed Tully-Fisher relation between L and disk speed v {sub rot}. Because of this, the problem of reproducing the galaxy luminosity function and the Tully-Fisher relation simultaneously has plagued semianalytic models since their inception. Here we study the relation between v {sub rot} and v {sub vir} by fitting observational average rotation curves of disk galaxies binned in luminosity. We show that the v {sub rot}-v {sub vir} relation that we obtain in this way can fullymore » account for this seeming inconsistency. Therefore, the reconciliation of the luminosity function with the Tully-Fisher relation rests on the complex dependence of v {sub rot} on v {sub vir}, which arises because the ratio of stellar mass to dark matter mass is a strong function of halo mass.« less

Datum Feature Extraction and Deformation Analysis Method Based on Normal Vector of Point Cloud

NASA Astrophysics Data System (ADS)

Sun, W.; Wang, J.; Jin, F.; Liang, Z.; Yang, Y.

2018-04-01

In order to solve the problem lacking applicable analysis method in the application of three-dimensional laser scanning technology to the field of deformation monitoring, an efficient method extracting datum feature and analysing deformation based on normal vector of point cloud was proposed. Firstly, the kd-tree is used to establish the topological relation. Datum points are detected by tracking the normal vector of point cloud determined by the normal vector of local planar. Then, the cubic B-spline curve fitting is performed on the datum points. Finally, datum elevation and the inclination angle of the radial point are calculated according to the fitted curve and then the deformation information was analyzed. The proposed approach was verified on real large-scale tank data set captured with terrestrial laser scanner in a chemical plant. The results show that the method could obtain the entire information of the monitor object quickly and comprehensively, and reflect accurately the datum feature deformation.

Automatic Detection and Recognition of Craters Based on the Spectral Features of Lunar Rocks and Minerals

NASA Astrophysics Data System (ADS)

Ye, L.; Xu, X.; Luan, D.; Jiang, W.; Kang, Z.

2017-07-01

Crater-detection approaches can be divided into four categories: manual recognition, shape-profile fitting algorithms, machine-learning methods and geological information-based analysis using terrain and spectral data. The mainstream method is Shape-profile fitting algorithms. Many scholars throughout the world use the illumination gradient information to fit standard circles by least square method. Although this method has achieved good results, it is difficult to identify the craters with poor "visibility", complex structure and composition. Moreover, the accuracy of recognition is difficult to be improved due to the multiple solutions and noise interference. Aiming at the problem, we propose a method for the automatic extraction of impact craters based on spectral characteristics of the moon rocks and minerals: 1) Under the condition of sunlight, the impact craters are extracted from MI by condition matching and the positions as well as diameters of the craters are obtained. 2) Regolith is spilled while lunar is impacted and one of the elements of lunar regolith is iron. Therefore, incorrectly extracted impact craters can be removed by judging whether the crater contains "non iron" element. 3) Craters which are extracted correctly, are divided into two types: simple type and complex type according to their diameters. 4) Get the information of titanium and match the titanium distribution of the complex craters with normal distribution curve, then calculate the goodness of fit and set the threshold. The complex craters can be divided into two types: normal distribution curve type of titanium and non normal distribution curve type of titanium. We validated our proposed method with MI acquired by SELENE. Experimental results demonstrate that the proposed method has good performance in the test area.

Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

USGS Publications Warehouse

Bolker, Benjamin M.; Gardner, Beth; Maunder, Mark; Berg, Casper W.; Brooks, Mollie; Comita, Liza; Crone, Elizabeth; Cubaynes, Sarah; Davies, Trevor; de Valpine, Perry; Ford, Jessica; Gimenez, Olivier; Kéry, Marc; Kim, Eun Jung; Lennert-Cody, Cleridy; Magunsson, Arni; Martell, Steve; Nash, John; Nielson, Anders; Regentz, Jim; Skaug, Hans; Zipkin, Elise

2013-01-01

1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.

A new interferential multispectral image compression algorithm based on adaptive classification and curve-fitting

NASA Astrophysics Data System (ADS)

Wang, Ke-Yan; Li, Yun-Song; Liu, Kai; Wu, Cheng-Ke

2008-08-01

A novel compression algorithm for interferential multispectral images based on adaptive classification and curve-fitting is proposed. The image is first partitioned adaptively into major-interference region and minor-interference region. Different approximating functions are then constructed for two kinds of regions respectively. For the major interference region, some typical interferential curves are selected to predict other curves. These typical curves are then processed by curve-fitting method. For the minor interference region, the data of each interferential curve are independently approximated. Finally the approximating errors of two regions are entropy coded. The experimental results show that, compared with JPEG2000, the proposed algorithm not only decreases the average output bit-rate by about 0.2 bit/pixel for lossless compression, but also improves the reconstructed images and reduces the spectral distortion greatly, especially at high bit-rate for lossy compression.

Toward a Micro-Scale Acoustic Direction-Finding Sensor with Integrated Electronic Readout

DTIC Science & Technology

2013-06-01

measurements with curve fits . . . . . . . . . . . . . . . 20 Figure 2.10 Failure testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22...2.1 Sensor parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Table 2.2 Curve fit parameters...elastic, the quantity of interest is the elastic stiffness. In a typical nanoindentation test, the loading curve is nonlinear due to combined plastic

Transonic Compressor: Program System TXCO for Data Acquisition and On-Line Reduction.

DTIC Science & Technology

1980-10-01

IMONIDAYIYEARIHOUR,IMINISEC) OS16 C ............................................................... (0S17 C 0SiB C Gel dole ond line and convert the...linear curve fits SECON real intercept of linear curve fit (as from CURVE) 65 - . FLOW CHART SUBROUTINE CALIB - - - Aso C’A / oonre& *Go wSAt*irc

Sensitivity of Fit Indices to Misspecification in Growth Curve Models

ERIC Educational Resources Information Center

Wu, Wei; West, Stephen G.

2010-01-01

This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…

Edge detection and mathematic fitting for corneal surface with Matlab software.

PubMed

Di, Yue; Li, Mei-Yan; Qiao, Tong; Lu, Na

2017-01-01

To select the optimal edge detection methods to identify the corneal surface, and compare three fitting curve equations with Matlab software. Fifteen subjects were recruited. The corneal images from optical coherence tomography (OCT) were imported into Matlab software. Five edge detection methods (Canny, Log, Prewitt, Roberts, Sobel) were used to identify the corneal surface. Then two manual identifying methods (ginput and getpts) were applied to identify the edge coordinates respectively. The differences among these methods were compared. Binomial curve (y=Ax 2 +Bx+C), Polynomial curve [p(x)=p1x n +p2x n-1 +....+pnx+pn+1] and Conic section (Ax 2 +Bxy+Cy 2 +Dx+Ey+F=0) were used for curve fitting the corneal surface respectively. The relative merits among three fitting curves were analyzed. Finally, the eccentricity (e) obtained by corneal topography and conic section were compared with paired t -test. Five edge detection algorithms all had continuous coordinates which indicated the edge of the corneal surface. The ordinates of manual identifying were close to the inside of the actual edges. Binomial curve was greatly affected by tilt angle. Polynomial curve was lack of geometrical properties and unstable. Conic section could calculate the tilted symmetry axis, eccentricity, circle center, etc . There were no significant differences between 'e' values by corneal topography and conic section ( t =0.9143, P =0.3760 >0.05). It is feasible to simulate the corneal surface with mathematical curve with Matlab software. Edge detection has better repeatability and higher efficiency. The manual identifying approach is an indispensable complement for detection. Polynomial and conic section are both the alternative methods for corneal curve fitting. Conic curve was the optimal choice based on the specific geometrical properties.

Adaptive particle swarm optimization for optimal orbital elements of binary stars

NASA Astrophysics Data System (ADS)

Attia, Abdel-Fattah

2016-12-01

The paper presents an adaptive particle swarm optimization (APSO) as an alternative method to determine the optimal orbital elements of the star η Bootis of MK type G0 IV. The proposed algorithm transforms the problem of finding periodic orbits into the problem of detecting global minimizers as a function, to get a best fit of Keplerian and Phase curves. The experimental results demonstrate that the proposed approach of APSO generally more accurate than the standard particle swarm optimization (PSO) and other published optimization algorithms, in terms of solution accuracy, convergence speed and algorithm reliability.

Tensor-guided fitting of subduction slab depths

USGS Publications Warehouse

Bazargani, Farhad; Hayes, Gavin P.

2013-01-01

Geophysical measurements are often acquired at scattered locations in space. Therefore, interpolating or fitting the sparsely sampled data as a uniform function of space (a procedure commonly known as gridding) is a ubiquitous problem in geophysics. Most gridding methods require a model of spatial correlation for data. This spatial correlation model can often be inferred from some sort of secondary information, which may also be sparsely sampled in space. In this paper, we present a new method to model the geometry of a subducting slab in which we use a data‐fitting approach to address the problem. Earthquakes and active‐source seismic surveys provide estimates of depths of subducting slabs but only at scattered locations. In addition to estimates of depths from earthquake locations, focal mechanisms of subduction zone earthquakes also provide estimates of the strikes of the subducting slab on which they occur. We use these spatially sparse strike samples and the Earth’s curved surface geometry to infer a model for spatial correlation that guides a blended neighbor interpolation of slab depths. We then modify the interpolation method to account for the uncertainties associated with the depth estimates.

Materials and Modulators for 3D Displays

DTIC Science & Technology

2002-08-01

1243 nm. 0, 180 and 360 deg. in this plot correspond to parallel polarization. The dashed curve is a cos2(θ) fit to the data with a constant value...dwell time (solid bold curve ), 10 µs dwell time (dashed bold curve ) and static case (thin dashed curve ). 26 Figure. 20. Schematics of free-space...photon. The two peaks in the two photon spectrum can be fit by two Lorentzian curves . These spectra indicate that in the rhodamine B molecule the

AN ANALYSIS OF THE SHAPES OF INTERSTELLAR EXTINCTION CURVES. VI. THE NEAR-IR EXTINCTION LAW

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fitzpatrick, E. L.; Massa, D.

We combine new observations from the Hubble Space Telescope's Advanced Camera of Survey with existing data to investigate the wavelength dependence of near-IR (NIR) extinction. Previous studies suggest a power law form for NIR extinction, with a 'universal' value of the exponent, although some recent observations indicate that significant sight line-to-sight line variability may exist. We show that a power-law model for the NIR extinction provides an excellent fit to most extinction curves, but that the value of the power, {beta}, varies significantly from sight line to sight line. Therefore, it seems that a 'universal NIR extinction law' is notmore » possible. Instead, we find that as {beta} decreases, R(V) {identical_to} A(V)/E(B - V) tends to increase, suggesting that NIR extinction curves which have been considered 'peculiar' may, in fact, be typical for different R(V) values. We show that the power-law parameters can depend on the wavelength interval used to derive them, with the {beta} increasing as longer wavelengths are included. This result implies that extrapolating power-law fits to determine R(V) is unreliable. To avoid this problem, we adopt a different functional form for NIR extinction. This new form mimics a power law whose exponent increases with wavelength, has only two free parameters, can fit all of our curves over a longer wavelength baseline and to higher precision, and produces R(V) values which are consistent with independent estimates and commonly used methods for estimating R(V). Furthermore, unlike the power-law model, it gives R(V)s that are independent of the wavelength interval used to derive them. It also suggests that the relation R(V) = -1.36 E(K-V)/(E(B-V)) - 0.79 can estimate R(V) to {+-}0.12. Finally, we use model extinction curves to show that our extinction curves are in accord with theoretical expectations, and demonstrate how large samples of observational quantities can provide useful constraints on the grain properties.« less

An Empirical Fitting Method for Type Ia Supernova Light Curves: A Case Study of SN 2011fe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, WeiKang; Filippenko, Alexei V., E-mail: zwk@astro.berkeley.edu

We present a new empirical fitting method for the optical light curves of Type Ia supernovae (SNe Ia). We find that a variant broken-power-law function provides a good fit, with the simple assumption that the optical emission is approximately the blackbody emission of the expanding fireball. This function is mathematically analytic and is derived directly from the photospheric velocity evolution. When deriving the function, we assume that both the blackbody temperature and photospheric velocity are constant, but the final function is able to accommodate these changes during the fitting procedure. Applying it to the case study of SN 2011fe givesmore » a surprisingly good fit that can describe the light curves from the first-light time to a few weeks after peak brightness, as well as over a large range of fluxes (∼5 mag, and even ∼7 mag in the g band). Since SNe Ia share similar light-curve shapes, this fitting method has the potential to fit most other SNe Ia and characterize their properties in large statistical samples such as those already gathered and in the near future as new facilities become available.« less

A Survey of Xenon Ion Sputter Yield Data and Fits Relevant to Electric Propulsion Spacecraft Integration

NASA Technical Reports Server (NTRS)

Yim, John T.

2017-01-01

A survey of low energy xenon ion impact sputter yields was conducted to provide a more coherent baseline set of sputter yield data and accompanying fits for electric propulsion integration. Data uncertainties are discussed and different available curve fit formulas are assessed for their general suitability. A Bayesian parameter fitting approach is used with a Markov chain Monte Carlo method to provide estimates for the fitting parameters while characterizing the uncertainties for the resulting yield curves.

Data reduction using cubic rational B-splines

NASA Technical Reports Server (NTRS)

Chou, Jin J.; Piegl, Les A.

1992-01-01

A geometric method is proposed for fitting rational cubic B-spline curves to data that represent smooth curves including intersection or silhouette lines. The algorithm is based on the convex hull and the variation diminishing properties of Bezier/B-spline curves. The algorithm has the following structure: it tries to fit one Bezier segment to the entire data set and if it is impossible it subdivides the data set and reconsiders the subset. After accepting the subset the algorithm tries to find the longest run of points within a tolerance and then approximates this set with a Bezier cubic segment. The algorithm uses this procedure repeatedly to the rest of the data points until all points are fitted. It is concluded that the algorithm delivers fitting curves which approximate the data with high accuracy even in cases with large tolerances.

The behavioral economics of drug self-administration: A review and new analytical approach for within-session procedures

PubMed Central

Bentzley, Brandon S.; Fender, Kimberly M.; Aston-Jones, Gary

2012-01-01

Rationale Behavioral-economic demand curve analysis offers several useful measures of drug self-administration. Although generation of demand curves previously required multiple days, recent within-session procedures allow curve construction from a single 110-min cocaine self-administration session, making behavioral-economic analyses available to a broad range of self-administration experiments. However, a mathematical approach of curve fitting has not been reported for the within-session threshold procedure. Objectives We review demand curve analysis in drug self-administration experiments and provide a quantitative method for fitting curves to single-session data that incorporates relative stability of brain drug concentration. Methods Sprague-Dawley rats were trained to self-administer cocaine, and then tested with the threshold procedure in which the cocaine dose was sequentially decreased on a fixed ratio-1 schedule. Price points (responses/mg cocaine) outside of relatively stable brain cocaine concentrations were removed before curves were fit. Curve-fit accuracy was determined by the degree of correlation between graphical and calculated parameters for cocaine consumption at low price (Q0) and the price at which maximal responding occurred (Pmax). Results Removing price points that occurred at relatively unstable brain cocaine concentrations generated precise estimates of Q0 and resulted in Pmax values with significantly closer agreement with graphical Pmax than conventional methods. Conclusion The exponential demand equation can be fit to single-session data using the threshold procedure for cocaine self-administration. Removing data points that occur during relatively unstable brain cocaine concentrations resulted in more accurate estimates of demand curve slope than graphical methods, permitting a more comprehensive analysis of drug self-administration via a behavioral-economic framework. PMID:23086021

Investigation of Light-Emitting Diode (LED) Point Light Source Color Visibility against Complex Multicolored Backgrounds

DTIC Science & Technology

2017-11-01

sent from light-emitting diodes (LEDs) of 5 colors ( green , red, white, amber, and blue). Experiment 1 involved controlled laboratory measurements of...A-4 Red LED calibration curves and quadratic curve fits with R2 values . 37 Fig. A-5 Green LED calibration curves and quadratic curve fits with R2...36 Table A-4 Red LED calibration measurements ................................................... 36 Table A-5 Green LED

Methods for the Precise Locating and Forming of Arrays of Curved Features into a Workpiece

DOEpatents

Gill, David Dennis; Keeler, Gordon A.; Serkland, Darwin K.; Mukherjee, Sayan D.

2008-10-14

Methods for manufacturing high precision arrays of curved features (e.g. lenses) in the surface of a workpiece are described utilizing orthogonal sets of inter-fitting locating grooves to mate a workpiece to a workpiece holder mounted to the spindle face of a rotating machine tool. The matching inter-fitting groove sets in the workpiece and the chuck allow precisely and non-kinematically indexing the workpiece to locations defined in two orthogonal directions perpendicular to the turning axis of the machine tool. At each location on the workpiece a curved feature can then be on-center machined to create arrays of curved features on the workpiece. The averaging effect of the corresponding sets of inter-fitting grooves provide for precise repeatability in determining, the relative locations of the centers of each of the curved features in an array of curved features.

NLINEAR - NONLINEAR CURVE FITTING PROGRAM

NASA Technical Reports Server (NTRS)

Everhart, J. L.

1994-01-01

A common method for fitting data is a least-squares fit. In the least-squares method, a user-specified fitting function is utilized in such a way as to minimize the sum of the squares of distances between the data points and the fitting curve. The Nonlinear Curve Fitting Program, NLINEAR, is an interactive curve fitting routine based on a description of the quadratic expansion of the chi-squared statistic. NLINEAR utilizes a nonlinear optimization algorithm that calculates the best statistically weighted values of the parameters of the fitting function and the chi-square that is to be minimized. The inputs to the program are the mathematical form of the fitting function and the initial values of the parameters to be estimated. This approach provides the user with statistical information such as goodness of fit and estimated values of parameters that produce the highest degree of correlation between the experimental data and the mathematical model. In the mathematical formulation of the algorithm, the Taylor expansion of chi-square is first introduced, and justification for retaining only the first term are presented. From the expansion, a set of n simultaneous linear equations are derived, which are solved by matrix algebra. To achieve convergence, the algorithm requires meaningful initial estimates for the parameters of the fitting function. NLINEAR is written in Fortran 77 for execution on a CDC Cyber 750 under NOS 2.3. It has a central memory requirement of 5K 60 bit words. Optionally, graphical output of the fitting function can be plotted. Tektronix PLOT-10 routines are required for graphics. NLINEAR was developed in 1987.

Feasibility of inverse problem solution for determination of city emission function from night sky radiance measurements

NASA Astrophysics Data System (ADS)

Petržala, Jaromír

2018-07-01

The knowledge of the emission function of a city is crucial for simulation of sky glow in its vicinity. The indirect methods to achieve this function from radiances measured over a part of the sky have been recently developed. In principle, such methods represent an ill-posed inverse problem. This paper deals with the theoretical feasibility study of various approaches to solving of given inverse problem. Particularly, it means testing of fitness of various stabilizing functionals within the Tikhonov's regularization. Further, the L-curve and generalized cross validation methods were investigated as indicators of an optimal regularization parameter. At first, we created the theoretical model for calculation of a sky spectral radiance in the form of a functional of an emission spectral radiance. Consequently, all the mentioned approaches were examined in numerical experiments with synthetical data generated for the fictitious city and loaded by random errors. The results demonstrate that the second order Tikhonov's regularization method together with regularization parameter choice by the L-curve maximum curvature criterion provide solutions which are in good agreement with the supposed model emission functions.

LASR-Guided Variability Subtraction: The Linear Algorithm for Significance Reduction of Stellar Seismic Activity

NASA Astrophysics Data System (ADS)

Horvath, Sarah; Myers, Sam; Ahlers, Johnathon; Barnes, Jason W.

2017-10-01

Stellar seismic activity produces variations in brightness that introduce oscillations into transit light curves, which can create challenges for traditional fitting models. These oscillations disrupt baseline stellar flux values and potentially mask transits. We develop a model that removes these oscillations from transit light curves by minimizing the significance of each oscillation in frequency space. By removing stellar variability, we prepare each light curve for traditional fitting techniques. We apply our model to $\\delta$-Scuti KOI-976 and demonstrate that our variability subtraction routine successfully allows for measuring bulk system characteristics using traditional light curve fitting. These results open a new window for characterizing bulk system parameters of planets orbiting seismically active stars.

On the analysis of Canadian Holstein dairy cow lactation curves using standard growth functions.

PubMed

López, S; France, J; Odongo, N E; McBride, R A; Kebreab, E; AlZahal, O; McBride, B W; Dijkstra, J

2015-04-01

Six classical growth functions (monomolecular, Schumacher, Gompertz, logistic, Richards, and Morgan) were fitted to individual and average (by parity) cumulative milk production curves of Canadian Holstein dairy cows. The data analyzed consisted of approximately 91,000 daily milk yield records corresponding to 122 first, 99 second, and 92 third parity individual lactation curves. The functions were fitted using nonlinear regression procedures, and their performance was assessed using goodness-of-fit statistics (coefficient of determination, residual mean squares, Akaike information criterion, and the correlation and concordance coefficients between observed and adjusted milk yields at several days in milk). Overall, all the growth functions evaluated showed an acceptable fit to the cumulative milk production curves, with the Richards equation ranking first (smallest Akaike information criterion) followed by the Morgan equation. Differences among the functions in their goodness-of-fit were enlarged when fitted to average curves by parity, where the sigmoidal functions with a variable point of inflection (Richards and Morgan) outperformed the other 4 equations. All the functions provided satisfactory predictions of milk yield (calculated from the first derivative of the functions) at different lactation stages, from early to late lactation. The Richards and Morgan equations provided the most accurate estimates of peak yield and total milk production per 305-d lactation, whereas the least accurate estimates were obtained with the logistic equation. In conclusion, classical growth functions (especially sigmoidal functions with a variable point of inflection) proved to be feasible alternatives to fit cumulative milk production curves of dairy cows, resulting in suitable statistical performance and accurate estimates of lactation traits. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Neutron Multiplicity: LANL W Covariance Matrix for Curve Fitting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wendelberger, James G.

2016-12-08

In neutron multiplicity counting one may fit a curve by minimizing an objective function, χmore » $$2\\atop{n}$$. The objective function includes the inverse of an n by n matrix of covariances, W. The inverse of the W matrix has a closed form solution. In addition W -1 is a tri-diagonal matrix. The closed form and tridiagonal nature allows for a simpler expression of the objective function χ$$2\\atop{n}$$. Minimization of this simpler expression will provide the optimal parameters for the fitted curve.« less

The late behavior of supernova 1987A. I - The light curve. II - Gamma-ray transparency of the ejecta

NASA Technical Reports Server (NTRS)

Arnett, W. David; Fu, Albert

1989-01-01

Observations of the late (t = 20-1500 days) bolometric light curve and the gamma-lines and X-rays from supernova 1987A are compared to theoretical models. It is found that 0.073 + or - 0.015 solar masses of freshly synthesized Ni-56 must be present to fit the bolometric light curve. The results place limits on the luminosity and presumed period of the newly formed pulsar/neutron star. In the second half of the paper, the problem of computing the luminosities in gamma-ray lines and in X-rays from supernova 1987A is addressed. High-energy observations suggest the development of large-scale clumping and bubbling of radioactive material in the ejecta. A model is proposed with a hydrogen envelope mass of about 7 solar masses, homologous scale expansion velocities of about 3000 km/s, and an approximately uniform mass distribution.

Biological growth functions describe published site index curves for Lake States timber species.

Treesearch

Allen L. Lundgren; William A. Dolid

1970-01-01

Two biological growth functions, an exponential-monomolecular function and a simple monomolecular function, have been fit to published site index curves for 11 Lake States tree species: red, jack, and white pine, balsam fir, white and black spruce, tamarack, white-cedar, aspen, red oak, and paper birch. Both functions closely fit all published curves except those for...

From nonlinear optimization to convex optimization through firefly algorithm and indirect approach with applications to CAD/CAM.

PubMed

Gálvez, Akemi; Iglesias, Andrés

2013-01-01

Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor's method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently.

From Nonlinear Optimization to Convex Optimization through Firefly Algorithm and Indirect Approach with Applications to CAD/CAM

PubMed Central

Gálvez, Akemi; Iglesias, Andrés

2013-01-01

Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor's method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently. PMID:24376380

Learning curves in highly skilled chess players: a test of the generality of the power law of practice.

PubMed

Howard, Robert W

2014-09-01

The power law of practice holds that a power function best interrelates skill performance and amount of practice. However, the law's validity and generality are moot. Some researchers argue that it is an artifact of averaging individual exponential curves while others question whether the law generalizes to complex skills and to performance measures other than response time. The present study tested the power law's generality to development over many years of a very complex cognitive skill, chess playing, with 387 skilled participants, most of whom were grandmasters. A power or logarithmic function best fit grouped data but individuals showed much variability. An exponential function usually was the worst fit to individual data. Groups differing in chess talent were compared and a power function best fit the group curve for the more talented players while a quadratic function best fit that for the less talented. After extreme amounts of practice, a logarithmic function best fit grouped data but a quadratic function best fit most individual curves. Individual variability is great and the power law or an exponential law are not the best descriptions of individual chess skill development. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparison of the A-Cc curve fitting methods in determining maximum ribulose 1.5-bisphosphate carboxylase/oxygenase carboxylation rate, potential light saturated electron transport rate and leaf dark respiration.

PubMed

Miao, Zewei; Xu, Ming; Lathrop, Richard G; Wang, Yufei

2009-02-01

A review of the literature revealed that a variety of methods are currently used for fitting net assimilation of CO2-chloroplastic CO2 concentration (A-Cc) curves, resulting in considerable differences in estimating the A-Cc parameters [including maximum ribulose 1.5-bisphosphate carboxylase/oxygenase (Rubisco) carboxylation rate (Vcmax), potential light saturated electron transport rate (Jmax), leaf dark respiration in the light (Rd), mesophyll conductance (gm) and triose-phosphate utilization (TPU)]. In this paper, we examined the impacts of fitting methods on the estimations of Vcmax, Jmax, TPU, Rd and gm using grid search and non-linear fitting techniques. Our results suggested that the fitting methods significantly affected the predictions of Rubisco-limited (Ac), ribulose 1,5-bisphosphate-limited (Aj) and TPU-limited (Ap) curves and leaf photosynthesis velocities because of the inconsistent estimate of Vcmax, Jmax, TPU, Rd and gm, but they barely influenced the Jmax : Vcmax, Vcmax : Rd and Jmax : TPU ratio. In terms of fitting accuracy, simplicity of fitting procedures and sample size requirement, we recommend to combine grid search and non-linear techniques to directly and simultaneously fit Vcmax, Jmax, TPU, Rd and gm with the whole A-Cc curve in contrast to the conventional method, which fits Vcmax, Rd or gm first and then solves for Vcmax, Jmax and/or TPU with V(cmax), Rd and/or gm held as constants.

Bell-Curve Genetic Algorithm for Mixed Continuous and Discrete Optimization Problems

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.; Griffith, Michelle; Sykes, Ruth; Sobieszczanski-Sobieski, Jaroslaw

2002-01-01

In this manuscript we have examined an extension of BCB that encompasses a mix of continuous and quasi-discrete, as well as truly-discrete applications. FVe began by testing two refinements to the discrete version of BCB. The testing of midpoint versus fitness (Tables 1 and 2) proved inconclusive. The testing of discrete normal tails versus standard mutation showed was conclusive and demonstrated that the discrete normal tails are better. Next, we implemented these refinements in a combined continuous and discrete BCB and compared the performance of two discrete distance on the hub problem. Here we found when "order does matter" it pays to take it into account.

Dust in the small Magellanic Cloud. 2: Dust models from interstellar polarization and extinction data

NASA Technical Reports Server (NTRS)

Rodrigues, C. V.; Magalhaes, A. M.; Coyne, G. V.

1995-01-01

We study the dust in the Small Magellanic Cloud using our polarization and extinction data (Paper 1) and existing dust models. The data suggest that the monotonic SMC extinction curve is related to values of lambda(sub max), the wavelength of maximum polarization, which are on the average smaller than the mean for the Galaxy. On the other hand, AZV 456, a star with an extinction similar to that for the Galaxy, shows a value of lambda(sub max) similar to the mean for the Galaxy. We discuss simultaneous dust model fits to extinction and polarization. Fits to the wavelength dependent polarization data are possible for stars with small lambda(sub max). In general, they imply dust size distributions which are narrower and have smaller mean sizes compared to typical size distributions for the Galaxy. However, stars with lambda(sub max) close to the Galactic norm, which also have a narrower polarization curve, cannot be fit adequately. This holds true for all of the dust models considered. The best fits to the extinction curves are obtained with a power law size distribution by assuming that the cylindrical and spherical silicate grains have a volume distribution which is continuous from the smaller spheres to the larger cylinders. The size distribution for the cylinders is taken from the fit to the polarization. The 'typical', monotonic SMC extinction curve can be fit well with graphite and silicate grains if a small fraction of the SMC carbon is locked up in the grain. However, amorphous carbon and silicate grains also fit the data well. AZV456, which has an extinction curve similar to that for the Galaxy, has a UV bump which is too blue to be fit by spherical graphite grains.

Determination of thermoelastic material properties by differential heterodyne detection of impulsive stimulated thermal scattering

PubMed Central

Verstraeten, B.; Sermeus, J.; Salenbien, R.; Fivez, J.; Shkerdin, G.; Glorieux, C.

2015-01-01

The underlying working principle of detecting impulsive stimulated scattering signals in a differential configuration of heterodyne diffraction detection is unraveled by involving optical scattering theory. The feasibility of the method for the thermoelastic characterization of coating-substrate systems is demonstrated on the basis of simulated data containing typical levels of noise. Besides the classical analysis of the photoacoustic part of the signals, which involves fitting surface acoustic wave dispersion curves, the photothermal part of the signals is analyzed by introducing thermal wave dispersion curves to represent and interpret their grating wavelength dependence. The intrinsic possibilities and limitations of both inverse problems are quantified by making use of least and most squares analysis. PMID:26236643

Research on Standard and Automatic Judgment of Press-fit Curve of Locomotive Wheel-set Based on AAR Standard

NASA Astrophysics Data System (ADS)

Lu, Jun; Xiao, Jun; Gao, Dong Jun; Zong, Shu Yu; Li, Zhu

2018-03-01

In the production of the Association of American Railroads (AAR) locomotive wheel-set, the press-fit curve is the most important basis for the reliability of wheel-set assembly. In the past, Most of production enterprises mainly use artificial detection methods to determine the quality of assembly. There are cases of miscarriage of justice appear. For this reason, the research on the standard is carried out. And the automatic judgment of press-fit curve is analysed and designed, so as to provide guidance for the locomotive wheel-set production based on AAR standard.

An astronomer's guide to period searching

NASA Astrophysics Data System (ADS)

Schwarzenberg-Czerny, A.

2003-03-01

We concentrate on analysis of unevenly sampled time series, interrupted by periodic gaps, as often encountered in astronomy. While some of our conclusions may appear surprising, all are based on classical statistical principles of Fisher & successors. Except for discussion of the resolution issues, it is best for the reader to forget temporarily about Fourier transforms and to concentrate on problems of fitting of a time series with a model curve. According to their statistical content we divide the issues into several sections, consisting of: (ii) statistical numerical aspects of model fitting, (iii) evaluation of fitted models as hypotheses testing, (iv) the role of the orthogonal models in signal detection (v) conditions for equivalence of periodograms (vi) rating sensitivity by test power. An experienced observer working with individual objects would benefit little from formalized statistical approach. However, we demonstrate the usefulness of this approach in evaluation of performance of periodograms and in quantitative design of large variability surveys.

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

NASA Technical Reports Server (NTRS)

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.

GPU computing of compressible flow problems by a meshless method with space-filling curves

NASA Astrophysics Data System (ADS)

Ma, Z. H.; Wang, H.; Pu, S. H.

2014-04-01

A graphic processing unit (GPU) implementation of a meshless method for solving compressible flow problems is presented in this paper. Least-square fit is used to discretize the spatial derivatives of Euler equations and an upwind scheme is applied to estimate the flux terms. The compute unified device architecture (CUDA) C programming model is employed to efficiently and flexibly port the meshless solver from CPU to GPU. Considering the data locality of randomly distributed points, space-filling curves are adopted to re-number the points in order to improve the memory performance. Detailed evaluations are firstly carried out to assess the accuracy and conservation property of the underlying numerical method. Then the GPU accelerated flow solver is used to solve external steady flows over aerodynamic configurations. Representative results are validated through extensive comparisons with the experimental, finite volume or other available reference solutions. Performance analysis reveals that the running time cost of simulations is significantly reduced while impressive (more than an order of magnitude) speedups are achieved.

On the Use of Nonparametric Item Characteristic Curve Estimation Techniques for Checking Parametric Model Fit

ERIC Educational Resources Information Center

Lee, Young-Sun; Wollack, James A.; Douglas, Jeffrey

2009-01-01

The purpose of this study was to assess the model fit of a 2PL through comparison with the nonparametric item characteristic curve (ICC) estimation procedures. Results indicate that three nonparametric procedures implemented produced ICCs that are similar to that of the 2PL for items simulated to fit the 2PL. However for misfitting items,…

Statistical aspects of modeling the labor curve.

PubMed

Zhang, Jun; Troendle, James; Grantz, Katherine L; Reddy, Uma M

2015-06-01

In a recent review by Cohen and Friedman, several statistical questions on modeling labor curves were raised. This article illustrates that asking data to fit a preconceived model or letting a sufficiently flexible model fit observed data is the main difference in principles of statistical modeling between the original Friedman curve and our average labor curve. An evidence-based approach to construct a labor curve and establish normal values should allow the statistical model to fit observed data. In addition, the presence of the deceleration phase in the active phase of an average labor curve was questioned. Forcing a deceleration phase to be part of the labor curve may have artificially raised the speed of progression in the active phase with a particularly large impact on earlier labor between 4 and 6 cm. Finally, any labor curve is illustrative and may not be instructive in managing labor because of variations in individual labor pattern and large errors in measuring cervical dilation. With the tools commonly available, it may be more productive to establish a new partogram that takes the physiology of labor and contemporary obstetric population into account. Copyright © 2015 Elsevier Inc. All rights reserved.

The validation of a generalized Hooke's law for coronary arteries.

PubMed

Wang, Chong; Zhang, Wei; Kassab, Ghassan S

2008-01-01

The exponential form of constitutive model is widely used in biomechanical studies of blood vessels. There are two main issues, however, with this model: 1) the curve fits of experimental data are not always satisfactory, and 2) the material parameters may be oversensitive. A new type of strain measure in a generalized Hooke's law for blood vessels was recently proposed by our group to address these issues. The new model has one nonlinear parameter and six linear parameters. In this study, the stress-strain equation is validated by fitting the model to experimental data of porcine coronary arteries. Material constants of left anterior descending artery and right coronary artery for the Hooke's law were computed with a separable nonlinear least-squares method with an excellent goodness of fit. A parameter sensitivity analysis shows that the stability of material constants is improved compared with the exponential model and a biphasic model. A boundary value problem was solved to demonstrate that the model prediction can match the measured arterial deformation under experimental loading conditions. The validated constitutive relation will serve as a basis for the solution of various boundary value problems of cardiovascular biomechanics.

Application of separable parameter space techniques to multi-tracer PET compartment modeling.

PubMed

Zhang, Jeff L; Michael Morey, A; Kadrmas, Dan J

2016-02-07

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg-Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models.

Application of separable parameter space techniques to multi-tracer PET compartment modeling

NASA Astrophysics Data System (ADS)

Zhang, Jeff L.; Morey, A. Michael; Kadrmas, Dan J.

2016-02-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg-Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models.

An Apparatus for Sizing Particulate Matter in Solid Rocket Motors.

DTIC Science & Technology

1984-06-01

accurately measured. A curve for sizing polydispersions was presented which was used by Cramer and Hansen [Refs. 2, 12]. Two phase flow losses are often...Concentration...... 54 18. 5 Micron Polystyrene, Curve Fit .......... ... 55 19. 5 Micron Polystyrene, Two Angle Method ........ .56.... 20. 10 Micron...Polystyrene, Curve Fit .. ........ 57....[57 21. 10 Micron Polystyrene, Two Angle Method .. ....... .58 . . .6_ *22. 20J Mizron P3iystvrene Cu. .Fi

Simulation and study of small numbers of random events

NASA Technical Reports Server (NTRS)

Shelton, R. D.

1986-01-01

Random events were simulated by computer and subjected to various statistical methods to extract important parameters. Various forms of curve fitting were explored, such as least squares, least distance from a line, maximum likelihood. Problems considered were dead time, exponential decay, and spectrum extraction from cosmic ray data using binned data and data from individual events. Computer programs, mostly of an iterative nature, were developed to do these simulations and extractions and are partially listed as appendices. The mathematical basis for the compuer programs is given.

A Clock Fingerprints-Based Approach for Wireless Transmitter Identification

NASA Astrophysics Data System (ADS)

Zhao, Caidan; Xie, Liang; Huang, Lianfen; Yao, Yan

Cognitive radio (CR) was proposed as one of the promising solutions for low spectrum utilization. However, security problems such as the primary user emulation (PUE) attack severely limit its applications. In this paper, we propose a clock fingerprints-based authentication approach to prevent PUE attacks in CR networks with the help of curve fitting and classifier. An experimental setup was constructed using the WLAN cards and software radio devices, and the corresponding results show that satisfied identification can be achieved for wireless transmitters.

Space-Based Observation Technology

DTIC Science & Technology

2000-10-01

Conan, V. Michau, and S. Salem . Regularized multiframe myopic deconvolution from wavefront sensing. In Propagation through the Atmosphere III...specified false alarm rate PFA . Proceeding with curving fitting, one obtains a best-fit curve “10.1y14.2 - 0.2” as the detector for the target

Reference Curves for Field Tests of Musculoskeletal Fitness in U.S. Children and Adolescents: The 2012 NHANES National Youth Fitness Survey.

PubMed

Laurson, Kelly R; Saint-Maurice, Pedro F; Welk, Gregory J; Eisenmann, Joey C

2017-08-01

Laurson, KR, Saint-Maurice, PF, Welk, GJ, and Eisenmann, JC. Reference curves for field tests of musculoskeletal fitness in U.S. children and adolescents: The 2012 NHANES National Youth Fitness Survey. J Strength Cond Res 31(8): 2075-2082, 2017-The purpose of the study was to describe current levels of musculoskeletal fitness (MSF) in U.S. youth by creating nationally representative age-specific and sex-specific growth curves for handgrip strength (including relative and allometrically scaled handgrip), modified pull-ups, and the plank test. Participants in the National Youth Fitness Survey (n = 1,453) were tested on MSF, aerobic capacity (via submaximal treadmill test), and body composition (body mass index [BMI], waist circumference, and skinfolds). Using LMS regression, age-specific and sex-specific smoothed percentile curves of MSF were created and existing percentiles were used to assign age-specific and sex-specific z-scores for aerobic capacity and body composition. Correlation matrices were created to assess the relationships between z-scores on MSF, aerobic capacity, and body composition. At younger ages (3-10 years), boys scored higher than girls for handgrip strength and modified pull-ups, but not for the plank. By ages 13-15, differences between the boys and girls curves were more pronounced, with boys scoring higher on all tests. Correlations between tests of MSF and aerobic capacity were positive and low-to-moderate in strength. Correlations between tests of MSF and body composition were negative, excluding absolute handgrip strength, which was inversely related to other MSF tests and aerobic capacity but positively associated with body composition. The growth curves herein can be used as normative reference values or a starting point for creating health-related criterion reference standards for these tests. Comparisons with prior national surveys of physical fitness indicate that some components of MSF have likely decreased in the United States over time.

Mild angle early onset idiopathic scoliosis children avoid progression under FITS method (Functional Individual Therapy of Scoliosis).

PubMed

Białek, Marianna

2015-05-01

Physiotherapy for stabilization of idiopathic scoliosis angle in growing children remains controversial. Notably, little data on effectiveness of physiotherapy in children with Early Onset Idiopathic Scoliosis (EOIS) has been published.The aim of this study was to check results of FITS physiotherapy in a group of children with EOIS.The charts of the patients archived in a prospectively collected database were retrospectively reviewed. The inclusion criteria were:diagnosis of EOIS based on spine radiography, age below 10 years, both girls and boys, Cobb angle between 118 and 308, Risser zero, FITS therapy, no other treatment (bracing), and a follow-up at least 2 years from the initiation of the treatment. The criterion for curve progression were as follows: the Cobb angle increase of 68 or more, for curve stabilization; the Cobb angle was 58 comparing to the initial radiograph,for curve correction; and the Cobb angle decrease of 68 or more at the final follow-up radiograph.There were 41 children with EOIS, 36 girls and 5 boys, mean age 7.71.3 years (range 4 to 9 years) who started FITS therapy. The curve pattern was single thoracic (5 children), single thoracolumbar (22 children) or double thoracic/thoracolumbar (14 children), totally 55 structural curvatures. The minimum follow-up was 2 years after initiation of the FITS treatment, maximum was 16 years, mean 4.8 years). At follow-up the mean age was 12.53.4 years. Out of 41 children, 10 passed pubertal growth spurt at the final follow-up and 31 were still immature and continued FITS therapy. Out of 41 children, 27 improved, 13 were stable, and one progressed. Out of 55 structural curves, 32 improved, 22 were stable and one progressed. For the 55 structural curves, the Cobb angle significantly decreased from 18.085.48 at first assessment to 12.586.38 at last evaluation,p<0.0001, paired t-test. The angle of trunk rotation decreased significantly from 4.782.98 to 3.282.58 at last evaluation, p<0.0001,paired t-test.FITS physiotherapy was effective in preventing curve progression in children with EOIS. Final postpubertal follow-up data is needed.

Hierarchical statistical modeling of xylem vulnerability to cavitation.

PubMed

Ogle, Kiona; Barber, Jarrett J; Willson, Cynthia; Thompson, Brenda

2009-01-01

Cavitation of xylem elements diminishes the water transport capacity of plants, and quantifying xylem vulnerability to cavitation is important to understanding plant function. Current approaches to analyzing hydraulic conductivity (K) data to infer vulnerability to cavitation suffer from problems such as the use of potentially unrealistic vulnerability curves, difficulty interpreting parameters in these curves, a statistical framework that ignores sampling design, and an overly simplistic view of uncertainty. This study illustrates how two common curves (exponential-sigmoid and Weibull) can be reparameterized in terms of meaningful parameters: maximum conductivity (k(sat)), water potential (-P) at which percentage loss of conductivity (PLC) =X% (P(X)), and the slope of the PLC curve at P(X) (S(X)), a 'sensitivity' index. We provide a hierarchical Bayesian method for fitting the reparameterized curves to K(H) data. We illustrate the method using data for roots and stems of two populations of Juniperus scopulorum and test for differences in k(sat), P(X), and S(X) between different groups. Two important results emerge from this study. First, the Weibull model is preferred because it produces biologically realistic estimates of PLC near P = 0 MPa. Second, stochastic embolisms contribute an important source of uncertainty that should be included in such analyses.

Curve fits of predicted inviscid stagnation-point radiative heating rates, cooling factors, and shock standoff distances for hyperbolic earth entry

NASA Technical Reports Server (NTRS)

Suttles, J. T.; Sullivan, E. M.; Margolis, S. B.

1974-01-01

Curve-fit formulas are presented for the stagnation-point radiative heating rate, cooling factor, and shock standoff distance for inviscid flow over blunt bodies at conditions corresponding to high-speed earth entry. The data which were curve fitted were calculated by using a technique which utilizes a one-strip integral method and a detailed nongray radiation model to generate a radiatively coupled flow-field solution for air in chemical and local thermodynamic equilibrium. The range of free-stream parameters considered were altitudes from about 55 to 70 km and velocities from about 11 to 16 km.sec. Spherical bodies with nose radii from 30 to 450 cm and elliptical bodies with major-to-minor axis ratios of 2, 4, and 6 were treated. Powerlaw formulas are proposed and a least-squares logarithmic fit is used to evaluate the constants. It is shown that the data can be described in this manner with an average deviation of about 3 percent (or less) and a maximum deviation of about 10 percent (or less). The curve-fit formulas provide an effective and economic means for making preliminary design studies for situations involving high-speed earth entry.

Combining optimization methods with response spectra curve-fitting toward improved damping ratio estimation

NASA Astrophysics Data System (ADS)

Brewick, Patrick T.; Smyth, Andrew W.

2016-12-01

The authors have previously shown that many traditional approaches to operational modal analysis (OMA) struggle to properly identify the modal damping ratios for bridges under traffic loading due to the interference caused by the driving frequencies of the traffic loads. This paper presents a novel methodology for modal parameter estimation in OMA that overcomes the problems presented by driving frequencies and significantly improves the damping estimates. This methodology is based on finding the power spectral density (PSD) of a given modal coordinate, and then dividing the modal PSD into separate regions, left- and right-side spectra. The modal coordinates were found using a blind source separation (BSS) algorithm and a curve-fitting technique was developed that uses optimization to find the modal parameters that best fit each side spectra of the PSD. Specifically, a pattern-search optimization method was combined with a clustering analysis algorithm and together they were employed in a series of stages in order to improve the estimates of the modal damping ratios. This method was used to estimate the damping ratios from a simulated bridge model subjected to moving traffic loads. The results of this method were compared to other established OMA methods, such as Frequency Domain Decomposition (FDD) and BSS methods, and they were found to be more accurate and more reliable, even for modes that had their PSDs distorted or altered by driving frequencies.

Dust in the Small Magellanic Cloud

NASA Technical Reports Server (NTRS)

Rodrigues, C. V.; Coyne, G. V.; Magalhaes, A. M.

1995-01-01

We discuss simultaneous dust model fits to our extinction and polarization data for the Small Magellanic Cloud (SMC) using existing dust models. Dust model fits to the wavelength dependent polarization are possible for stars with small lambda(sub max). They generally imply size distributions which are narrower and have smaller average sizes compared to those in the Galaxy. The best fits for the extinction curves are obtained with a power law size distribution. The typical, monotonic SMC extinction curve can be well fit with graphite and silicate grains if a small fraction of the SMC carbon is locked up in the grains. Amorphous carbon and silicate grains also fit the data well.

A Global Optimization Method to Calculate Water Retention Curves

NASA Astrophysics Data System (ADS)

Maggi, S.; Caputo, M. C.; Turturro, A. C.

2013-12-01

Water retention curves (WRC) have a key role for the hydraulic characterization of soils and rocks. The behaviour of the medium is defined by relating the unsaturated water content to the matric potential. The experimental determination of WRCs requires an accurate and detailed measurement of the dependence of matric potential on water content, a time-consuming and error-prone process, in particular for rocky media. A complete experimental WRC needs at least a few tens of data points, distributed more or less uniformly from full saturation to oven dryness. Since each measurement requires to wait to reach steady state conditions (i.e., between a few tens of minutes for soils and up to several hours or days for rocks or clays), the whole process can even take a few months. The experimental data are fitted to the most appropriate parametric model, such as the widely used models of Van Genuchten, Brooks and Corey and Rossi-Nimmo, to obtain the analytic WRC. We present here a new method for the determination of the parameters that best fit the models to the available experimental data. The method is based on differential evolution, an evolutionary computation algorithm particularly useful for multidimensional real-valued global optimization problems. With this method it is possible to strongly reduce the number of measurements necessary to optimize the model parameters that accurately describe the WRC of the samples, allowing to decrease the time needed to adequately characterize the medium. In the present work, we have applied our method to calculate the WRCs of sedimentary carbonatic rocks of marine origin, belonging to 'Calcarenite di Gravina' Formation (Middle Pliocene - Early Pleistocene) and coming from two different quarry districts in Southern Italy. WRC curves calculated using the Van Genuchten model by simulated annealing (dashed curve) and differential evolution (solid curve). The curves are calculated using 10 experimental data points randomly extracted from the full experimental dataset. Simulated annealing is not able to find the optimal solution with this reduced data set.

Analysis of mixed model in gear transmission based on ADAMS

NASA Astrophysics Data System (ADS)

Li, Xiufeng; Wang, Yabin

2012-09-01

The traditional method of mechanical gear driving simulation includes gear pair method and solid to solid contact method. The former has higher solving efficiency but lower results accuracy; the latter usually obtains higher precision of results while the calculation process is complex, also it is not easy to converge. Currently, most of the researches are focused on the description of geometric models and the definition of boundary conditions. However, none of them can solve the problems fundamentally. To improve the simulation efficiency while ensure the results with high accuracy, a mixed model method which uses gear tooth profiles to take the place of the solid gear to simulate gear movement is presented under these circumstances. In the process of modeling, build the solid models of the mechanism in the SolidWorks firstly; Then collect the point coordinates of outline curves of the gear using SolidWorks API and create fit curves in Adams based on the point coordinates; Next, adjust the position of those fitting curves according to the position of the contact area; Finally, define the loading conditions, boundary conditions and simulation parameters. The method provides gear shape information by tooth profile curves; simulates the mesh process through tooth profile curve to curve contact and offer mass as well as inertia data via solid gear models. This simulation process combines the two models to complete the gear driving analysis. In order to verify the validity of the method presented, both theoretical derivation and numerical simulation on a runaway escapement are conducted. The results show that the computational efficiency of the mixed model method is 1.4 times over the traditional method which contains solid to solid contact. Meanwhile, the simulation results are more closely to theoretical calculations. Consequently, mixed model method has a high application value regarding to the study of the dynamics of gear mechanism.

A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

PubMed

Zhai, Xuetong; Chakraborty, Dev P

2017-06-01

The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics. A limited simulation validation of the method was performed. CORCBM and CORROC2 were applied to two datasets containing nine readers each contributing paired interpretations. CORCBM successfully fitted the data for all readers, whereas CORROC2 failed to fit a degenerate dataset. All fits were visually reasonable. All CORCBM fits were proper, whereas all CORROC2 fits were improper. CORCBM and CORROC2 were in agreement (a) in declaring only one of the nine readers as having significantly different performances in the two modalities; (b) in estimating higher correlations for diseased cases than for nondiseased ones; and (c) in finding that the intermodality correlation estimates for nondiseased cases were consistent between the two methods. All CORCBM fits yielded higher area under curve (AUC) than the CORROC2 fits, consistent with the fact that a proper ROC model like CORCBM is based on a likelihood-ratio-equivalent decision variable, and consequently yields higher performance than the binormal model-based CORROC2. The method gave satisfactory fits to four simulated datasets. CORCBM is a robust method for fitting paired ROC datasets, always yielding proper ROC curves, and able to fit degenerate datasets. © 2017 American Association of Physicists in Medicine.

Milky Way Kinematics. II. A Uniform Inner Galaxy H I Terminal Velocity Curve

NASA Astrophysics Data System (ADS)

McClure-Griffiths, N. M.; Dickey, John M.

2016-11-01

Using atomic hydrogen (H I) data from the VLA Galactic Plane Survey, we measure the H I terminal velocity as a function of longitude for the first quadrant of the Milky Way. We use these data, together with our previous work on the fourth Galactic quadrant, to produce a densely sampled, uniformly measured, rotation curve of the northern and southern Milky Way between 3 {kpc}\\lt R\\lt 8 {kpc}. We determine a new joint rotation curve fit for the first and fourth quadrants, which is consistent with the fit we published in McClure-Griffiths & Dickey and can be used for estimating kinematic distances interior to the solar circle. Structure in the rotation curves is now exquisitely well defined, showing significant velocity structure on lengths of ˜200 pc, which is much greater than the spatial resolution of the rotation curve. Furthermore, the shape of the rotation curves for the first and fourth quadrants, even after subtraction of a circular rotation fit shows a surprising degree of correlation with a roughly sinusoidal pattern between 4.2\\lt R\\lt 7 kpc.

Two Aspects of the Simplex Model: Goodness of Fit to Linear Growth Curve Structures and the Analysis of Mean Trends.

ERIC Educational Resources Information Center

Mandys, Frantisek; Dolan, Conor V.; Molenaar, Peter C. M.

1994-01-01

Studied the conditions under which the quasi-Markov simplex model fits a linear growth curve covariance structure and determined when the model is rejected. Presents a quasi-Markov simplex model with structured means and gives an example. (SLD)

Boundary curves of individual items in the distribution of total depressive symptom scores approximate an exponential pattern in a general population.

PubMed

Tomitaka, Shinichiro; Kawasaki, Yohei; Ide, Kazuki; Akutagawa, Maiko; Yamada, Hiroshi; Furukawa, Toshiaki A; Ono, Yutaka

2016-01-01

Previously, we proposed a model for ordinal scale scoring in which individual thresholds for each item constitute a distribution by each item. This lead us to hypothesize that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores follow a common mathematical model, which is expressed as the product of the frequency of the total depressive symptom scores and the probability of the cumulative distribution function of each item threshold. To verify this hypothesis, we investigated the boundary curves of the distribution of total depressive symptom scores in a general population. Data collected from 21,040 subjects who had completed the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire as part of a national Japanese survey were analyzed. The CES-D consists of 20 items (16 negative items and four positive items). The boundary curves of adjacent item scores in the distribution of total depressive symptom scores for the 16 negative items were analyzed using log-normal scales and curve fitting. The boundary curves of adjacent item scores for a given symptom approximated a common linear pattern on a log normal scale. Curve fitting showed that an exponential fit had a markedly higher coefficient of determination than either linear or quadratic fits. With negative affect items, the gap between the total score curve and boundary curve continuously increased with increasing total depressive symptom scores on a log-normal scale, whereas the boundary curves of positive affect items, which are not considered manifest variables of the latent trait, did not exhibit such increases in this gap. The results of the present study support the hypothesis that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores commonly follow the predicted mathematical model, which was verified to approximate an exponential mathematical pattern.

Boundary curves of individual items in the distribution of total depressive symptom scores approximate an exponential pattern in a general population

PubMed Central

Kawasaki, Yohei; Akutagawa, Maiko; Yamada, Hiroshi; Furukawa, Toshiaki A.; Ono, Yutaka

2016-01-01

Background Previously, we proposed a model for ordinal scale scoring in which individual thresholds for each item constitute a distribution by each item. This lead us to hypothesize that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores follow a common mathematical model, which is expressed as the product of the frequency of the total depressive symptom scores and the probability of the cumulative distribution function of each item threshold. To verify this hypothesis, we investigated the boundary curves of the distribution of total depressive symptom scores in a general population. Methods Data collected from 21,040 subjects who had completed the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire as part of a national Japanese survey were analyzed. The CES-D consists of 20 items (16 negative items and four positive items). The boundary curves of adjacent item scores in the distribution of total depressive symptom scores for the 16 negative items were analyzed using log-normal scales and curve fitting. Results The boundary curves of adjacent item scores for a given symptom approximated a common linear pattern on a log normal scale. Curve fitting showed that an exponential fit had a markedly higher coefficient of determination than either linear or quadratic fits. With negative affect items, the gap between the total score curve and boundary curve continuously increased with increasing total depressive symptom scores on a log-normal scale, whereas the boundary curves of positive affect items, which are not considered manifest variables of the latent trait, did not exhibit such increases in this gap. Discussion The results of the present study support the hypothesis that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores commonly follow the predicted mathematical model, which was verified to approximate an exponential mathematical pattern. PMID:27761346

SEEK: A FORTRAN optimization program using a feasible directions gradient search

NASA Technical Reports Server (NTRS)

Savage, M.

1995-01-01

This report describes the use of computer program 'SEEK' which works in conjunction with two user-written subroutines and an input data file to perform an optimization procedure on a user's problem. The optimization method uses a modified feasible directions gradient technique. SEEK is written in ANSI standard Fortran 77, has an object size of about 46K bytes, and can be used on a personal computer running DOS. This report describes the use of the program and discusses the optimizing method. The program use is illustrated with four example problems: a bushing design, a helical coil spring design, a gear mesh design, and a two-parameter Weibull life-reliability curve fit.

Fitting milk production curves through nonlinear mixed models.

PubMed

Piccardi, Monica; Macchiavelli, Raúl; Funes, Ariel Capitaine; Bó, Gabriel A; Balzarini, Mónica

2017-05-01

The aim of this work was to fit and compare three non-linear models (Wood, Milkbot and diphasic) to model lactation curves from two approaches: with and without cow random effect. Knowing the behaviour of lactation curves is critical for decision-making in a dairy farm. Knowledge of the model of milk production progress along each lactation is necessary not only at the mean population level (dairy farm), but also at individual level (cow-lactation). The fits were made in a group of high production and reproduction dairy farms; in first and third lactations in cool seasons. A total of 2167 complete lactations were involved, of which 984 were first-lactations and the remaining ones, third lactations (19 382 milk yield tests). PROC NLMIXED in SAS was used to make the fits and estimate the model parameters. The diphasic model resulted to be computationally complex and barely practical. Regarding the classical Wood and MilkBot models, although the information criteria suggest the selection of MilkBot, the differences in the estimation of production indicators did not show a significant improvement. The Wood model was found to be a good option for fitting the expected value of lactation curves. Furthermore, the three models fitted better when the subject (cow) random effect was considered, which is related to magnitude of production. The random effect improved the predictive potential of the models, but it did not have a significant effect on the production indicators derived from the lactation curves, such as milk yield and days in milk to peak.

Characteristic overpressure-impulse-distance curves for vapour cloud explosions using the TNO Multi-Energy model.

PubMed

Díaz Alonso, Fernando; González Ferradás, Enrique; Sánchez Pérez, Juan Francisco; Miñana Aznar, Agustín; Ruiz Gimeno, José; Martínez Alonso, Jesús

2006-09-21

A number of models have been proposed to calculate overpressure and impulse from accidental industrial explosions. When the blast is produced by ignition of a vapour cloud, the TNO Multi-Energy model is widely used. From the curves given by this model, data are fitted to obtain equations showing the relationship between overpressure, impulse and distance. These equations, referred herein as characteristic curves, can be fitted by means of power equations, which depend on explosion energy and charge strength. Characteristic curves allow the determination of overpressure and impulse at each distance.

Non-linear Growth Models in Mplus and SAS

PubMed Central

Grimm, Kevin J.; Ram, Nilam

2013-01-01

Non-linear growth curves or growth curves that follow a specified non-linear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this paper we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the non-linear mixed-effects modeling procedure NLMIXED in SAS. Using longitudinal achievement data collected as part of a study examining the effects of preschool instruction on academic gain we illustrate the procedures for fitting growth models of logistic, Gompertz, and Richards functions. Brief notes regarding the practical benefits, limitations, and choices faced in the fitting and estimation of such models are included. PMID:23882134

Regionalisation of low flow frequency curves for the Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Mamun, Abdullah A.; Hashim, Alias; Daoud, Jamal I.

2010-02-01

SUMMARYRegional maps and equations for the magnitude and frequency of 1, 7 and 30-day low flows were derived and are presented in this paper. The river gauging stations of neighbouring catchments that produced similar low flow frequency curves were grouped together. As such, the Peninsular Malaysia was divided into seven low flow regions. Regional equations were developed using the multivariate regression technique. An empirical relationship was developed for mean annual minimum flow as a function of catchment area, mean annual rainfall and mean annual evaporation. The regional equations exhibited good coefficient of determination ( R2 > 0.90). Three low flow frequency curves showing the low, mean and high limits for each region were proposed based on a graphical best-fit technique. Knowing the catchment area, mean annual rainfall and evaporation in the region, design low flows of different durations can be easily estimated for the ungauged catchments. This procedure is expected to overcome the problem of data unavailability in estimating low flows in the Peninsular Malaysia.

Empirical models for fitting of oral concentration time curves with and without an intravenous reference.

PubMed

Weiss, Michael

2017-06-01

Appropriate model selection is important in fitting oral concentration-time data due to the complex character of the absorption process. When IV reference data are available, the problem is the selection of an empirical input function (absorption model). In the present examples a weighted sum of inverse Gaussian density functions (IG) was found most useful. It is shown that alternative models (gamma and Weibull density) are only valid if the input function is log-concave. Furthermore, it is demonstrated for the first time that the sum of IGs model can be also applied to fit oral data directly (without IV data). In the present examples, a weighted sum of two or three IGs was sufficient. From the parameters of this function, the model-independent measures AUC and mean residence time can be calculated. It turned out that a good fit of the data in the terminal phase is essential to avoid parameter biased estimates. The time course of fractional elimination rate and the concept of log-concavity have proved as useful tools in model selection.

Application of separable parameter space techniques to multi-tracer PET compartment modeling

PubMed Central

Zhang, Jeff L; Morey, A Michael; Kadrmas, Dan J

2016-01-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg–Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models. PMID:26788888

Characterizing muscular activities using non-negative matrix factorization from EMG channels for driver swings in golf.

PubMed

Ozaki, Yasunori; Aoki, Ryosuke; Kimura, Toshitaka; Takashima, Youichi; Yamada, Tomohiro

2016-08-01

The goal of this study is to propose a data driven approach method to characterize muscular activities of complex actions in sports such as golf from a lot of EMG channels. Two problems occur in a many channel measurement. The first problem is that it takes a lot of time to check the many channel data because of combinatorial explosion. The second problem is that it is difficult to understand muscle activities related with complex actions. To solve these problems, we propose an analysis method of multi EMG channels using Non-negative Matrix Factorization and adopt the method to driver swings in golf. We measured 26 EMG channels about 4 professional coaches of golf. The results show that the proposed method detected 9 muscle synergies and the activation of each synergy were mostly fitted by sigmoid curve (R2=0.85).

A curve fitting method for solving the flutter equation. M.S. Thesis

NASA Technical Reports Server (NTRS)

Cooper, J. L.

1972-01-01

A curve fitting approach was developed to solve the flutter equation for the critical flutter velocity. The psi versus nu curves are approximated by cubic and quadratic equations. The curve fitting technique utilized the first and second derivatives of psi with respect to nu. The method was tested for two structures, one structure being six times the total mass of the other structure. The algorithm never showed any tendency to diverge from the solution. The average time for the computation of a flutter velocity was 3.91 seconds on an IBM Model 50 computer for an accuracy of five per cent. For values of nu close to the critical root of the flutter equation the algorithm converged on the first attempt. The maximum number of iterations for convergence to the critical flutter velocity was five with an assumed value of nu relatively distant from the actual crossover.

A Robust Bayesian Random Effects Model for Nonlinear Calibration Problems

PubMed Central

Fong, Y.; Wakefield, J.; De Rosa, S.; Frahm, N.

2013-01-01

Summary In the context of a bioassay or an immunoassay, calibration means fitting a curve, usually nonlinear, through the observations collected on a set of samples containing known concentrations of a target substance, and then using the fitted curve and observations collected on samples of interest to predict the concentrations of the target substance in these samples. Recent technological advances have greatly improved our ability to quantify minute amounts of substance from a tiny volume of biological sample. This has in turn led to a need to improve statistical methods for calibration. In this paper, we focus on developing calibration methods robust to dependent outliers. We introduce a novel normal mixture model with dependent error terms to model the experimental noise. In addition, we propose a re-parameterization of the five parameter logistic nonlinear regression model that allows us to better incorporate prior information. We examine the performance of our methods with simulation studies and show that they lead to a substantial increase in performance measured in terms of mean squared error of estimation and a measure of the average prediction accuracy. A real data example from the HIV Vaccine Trials Network Laboratory is used to illustrate the methods. PMID:22551415

Probability Density Functions of Observed Rainfall in Montana

NASA Technical Reports Server (NTRS)

Larsen, Scott D.; Johnson, L. Ronald; Smith, Paul L.

1995-01-01

The question of whether a rain rate probability density function (PDF) can vary uniformly between precipitation events is examined. Image analysis on large samples of radar echoes is possible because of advances in technology. The data provided by such an analysis easily allow development of radar reflectivity factors (and by extension rain rate) distribution. Finding a PDF becomes a matter of finding a function that describes the curve approximating the resulting distributions. Ideally, one PDF would exist for all cases; or many PDF's that have the same functional form with only systematic variations in parameters (such as size or shape) exist. Satisfying either of theses cases will, validate the theoretical basis of the Area Time Integral (ATI). Using the method of moments and Elderton's curve selection criteria, the Pearson Type 1 equation was identified as a potential fit for 89 percent of the observed distributions. Further analysis indicates that the Type 1 curve does approximate the shape of the distributions but quantitatively does not produce a great fit. Using the method of moments and Elderton's curve selection criteria, the Pearson Type 1 equation was identified as a potential fit for 89% of the observed distributions. Further analysis indicates that the Type 1 curve does approximate the shape of the distributions but quantitatively does not produce a great fit.

Parametric soil water retention models: a critical evaluation of expressions for the full moisture range

NASA Astrophysics Data System (ADS)

Madi, Raneem; Huibert de Rooij, Gerrit; Mielenz, Henrike; Mai, Juliane

2018-02-01

Few parametric expressions for the soil water retention curve are suitable for dry conditions. Furthermore, expressions for the soil hydraulic conductivity curves associated with parametric retention functions can behave unrealistically near saturation. We developed a general criterion for water retention parameterizations that ensures physically plausible conductivity curves. Only 3 of the 18 tested parameterizations met this criterion without restrictions on the parameters of a popular conductivity curve parameterization. A fourth required one parameter to be fixed. We estimated parameters by shuffled complex evolution (SCE) with the objective function tailored to various observation methods used to obtain retention curve data. We fitted the four parameterizations with physically plausible conductivities as well as the most widely used parameterization. The performance of the resulting 12 combinations of retention and conductivity curves was assessed in a numerical study with 751 days of semiarid atmospheric forcing applied to unvegetated, uniform, 1 m freely draining columns for four textures. Choosing different parameterizations had a minor effect on evaporation, but cumulative bottom fluxes varied by up to an order of magnitude between them. This highlights the need for a careful selection of the soil hydraulic parameterization that ideally does not only rely on goodness of fit to static soil water retention data but also on hydraulic conductivity measurements. Parameter fits for 21 soils showed that extrapolations into the dry range of the retention curve often became physically more realistic when the parameterization had a logarithmic dry branch, particularly in fine-textured soils where high residual water contents would otherwise be fitted.

ASTEROID LIGHT CURVES FROM THE PALOMAR TRANSIENT FACTORY SURVEY: ROTATION PERIODS AND PHASE FUNCTIONS FROM SPARSE PHOTOMETRY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waszczak, Adam; Chang, Chan-Kao; Cheng, Yu-Chi

We fit 54,296 sparsely sampled asteroid light curves in the Palomar Transient Factory survey to a combined rotation plus phase-function model. Each light curve consists of 20 or more observations acquired in a single opposition. Using 805 asteroids in our sample that have reference periods in the literature, we find that the reliability of our fitted periods is a complicated function of the period, amplitude, apparent magnitude, and other light-curve attributes. Using the 805-asteroid ground-truth sample, we train an automated classifier to estimate (along with manual inspection) the validity of the remaining ∼53,000 fitted periods. By this method we findmore » that 9033 of our light curves (of ∼8300 unique asteroids) have “reliable” periods. Subsequent consideration of asteroids with multiple light-curve fits indicates a 4% contamination in these “reliable” periods. For 3902 light curves with sufficient phase-angle coverage and either a reliable fit period or low amplitude, we examine the distribution of several phase-function parameters, none of which are bimodal though all correlate with the bond albedo and with visible-band colors. Comparing the theoretical maximal spin rate of a fluid body with our amplitude versus spin-rate distribution suggests that, if held together only by self-gravity, most asteroids are in general less dense than ∼2 g cm{sup −3}, while C types have a lower limit of between 1 and 2 g cm{sup −3}. These results are in agreement with previous density estimates. For 5–20 km diameters, S types rotate faster and have lower amplitudes than C types. If both populations share the same angular momentum, this may indicate the two types’ differing ability to deform under rotational stress. Lastly, we compare our absolute magnitudes (and apparent-magnitude residuals) to those of the Minor Planet Center’s nominal (G = 0.15, rotation-neglecting) model; our phase-function plus Fourier-series fitting reduces asteroid photometric rms scatter by a factor of ∼3.« less

Fitting relationship between the beam quality β factor of high-energy laser and the wavefront aberration of laser beam

NASA Astrophysics Data System (ADS)

Ji, Zhong-Ye; Zhang, Xiao-Fang

2018-01-01

The mathematical relation between the beam quality β factor of high-energy laser and the wavefront aberration of laser beam is important in beam quality control theory of the high-energy laser weapon system. In order to obtain this mathematical relation, numerical simulation is used in the research. Firstly, the Zernike representations of typically distorted atmospheric wavefront aberrations caused by the Kolmogoroff turbulence are generated. And then, the corresponding beam quality β factors of the different distorted wavefronts are calculated numerically through fast Fourier transform. Thus, the statistical distribution rule between the beam quality β factors of high-energy laser and the wavefront aberrations of the beam can be established by the calculated results. Finally, curve fitting method is chosen to establish the mathematical fitting relationship of these two parameters. And the result of the curve fitting shows that there is a quadratic curve relation between the beam quality β factor of high-energy laser and the wavefront aberration of laser beam. And in this paper, 3 fitting curves, in which the wavefront aberrations are consisted of Zernike Polynomials of 20, 36, 60 orders individually, are established to express the relationship between the beam quality β factor and atmospheric wavefront aberrations with different spatial frequency.

Comparing dark matter models, modified Newtonian dynamics and modified gravity in accounting for galaxy rotation curves

NASA Astrophysics Data System (ADS)

Li, Xin; Tang, Li; Lin, Hai-Nan

2017-05-01

We compare six models (including the baryonic model, two dark matter models, two modified Newtonian dynamics models and one modified gravity model) in accounting for galaxy rotation curves. For the dark matter models, we assume NFW profile and core-modified profile for the dark halo, respectively. For the modified Newtonian dynamics models, we discuss Milgrom’s MOND theory with two different interpolation functions, the standard and the simple interpolation functions. For the modified gravity, we focus on Moffat’s MSTG theory. We fit these models to the observed rotation curves of 9 high-surface brightness and 9 low-surface brightness galaxies. We apply the Bayesian Information Criterion and the Akaike Information Criterion to test the goodness-of-fit of each model. It is found that none of the six models can fit all the galaxy rotation curves well. Two galaxies can be best fitted by the baryonic model without involving nonluminous dark matter. MOND can fit the largest number of galaxies, and only one galaxy can be best fitted by the MSTG model. Core-modified model fits about half the LSB galaxies well, but no HSB galaxies, while the NFW model fits only a small fraction of HSB galaxies but no LSB galaxies. This may imply that the oversimplified NFW and core-modified profiles cannot model the postulated dark matter haloes well. Supported by Fundamental Research Funds for the Central Universities (106112016CDJCR301206), National Natural Science Fund of China (11305181, 11547305 and 11603005), and Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China (Y5KF181CJ1)

Developing an African youth psychosocial assessment: an application of item response theory.

PubMed

Betancourt, Theresa S; Yang, Frances; Bolton, Paul; Normand, Sharon-Lise

2014-06-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. Copyright © 2014 John Wiley & Sons, Ltd.

Developing an African youth psychosocial assessment: an application of item response theory

PubMed Central

BETANCOURT, THERESA S.; YANG, FRANCES; BOLTON, PAUL; NORMAND, SHARON-LISE

2014-01-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. PMID:24478113

Image Understanding Workshop. Proceedings of a Workshop Held in San Diego, California on January 26-29, 1992

DTIC Science & Technology

1992-01-01

studied . shows the B-spline fit on the grouped curves and the local symmetries detected (their axes) (output of steps 1 and 4 OBJECT RECOGNITION 2.a...positioned so that the specular Our primary study (Krumm and Shafer) has been on lobes of each light source do not intersect. The four lights the...segregation with a 3D representation is a con- The problem of dot clustering can also be studied from sequence of grouping processes. A 3D

A method for nonlinear exponential regression analysis

NASA Technical Reports Server (NTRS)

Junkin, B. G.

1971-01-01

A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.

Studies of cluster X-ray sources, energy spectra for the Perseus, Virgo, and Coma clusters

NASA Technical Reports Server (NTRS)

Kellogg, E.; Baldwin, J. R.; Koch, D.

1975-01-01

Final Uhuru X-ray differential-energy spectra are presented for the Perseus, Virgo, and Coma clusters. Power-law and isothermal bremsstrahlung model spectra with low-energy cutoffs are given, and the energy-dependent Gaunt factor is calculated for the bremsstrahlung. The spectra, which are best fits to the Uhuru data between 2 and 10 keV, are compared with previous observations of these sources in the energy range from 0.1 to 100 keV. The problem of parameter estimation is discussed, error bars with 68% confidence are given for the independently determined slope and cutoff parameters, and the 68% confidence limits are plotted for the fitted spectral functions. The data for Perseus above 20 keV marginally favor the bremsstrahlung fit, those for Virgo between 0.25 and 1.0 keV clearly favor that curve, and those for Coma indicate a low-energy turnover or cutoff. Implications of such a cutoff are briefly discussed.

AKLSQF - LEAST SQUARES CURVE FITTING

NASA Technical Reports Server (NTRS)

Kantak, A. V.

1994-01-01

The Least Squares Curve Fitting program, AKLSQF, computes the polynomial which will least square fit uniformly spaced data easily and efficiently. The program allows the user to specify the tolerable least squares error in the fitting or allows the user to specify the polynomial degree. In both cases AKLSQF returns the polynomial and the actual least squares fit error incurred in the operation. The data may be supplied to the routine either by direct keyboard entry or via a file. AKLSQF produces the least squares polynomial in two steps. First, the data points are least squares fitted using the orthogonal factorial polynomials. The result is then reduced to a regular polynomial using Sterling numbers of the first kind. If an error tolerance is specified, the program starts with a polynomial of degree 1 and computes the least squares fit error. The degree of the polynomial used for fitting is then increased successively until the error criterion specified by the user is met. At every step the polynomial as well as the least squares fitting error is printed to the screen. In general, the program can produce a curve fitting up to a 100 degree polynomial. All computations in the program are carried out under Double Precision format for real numbers and under long integer format for integers to provide the maximum accuracy possible. AKLSQF was written for an IBM PC X/AT or compatible using Microsoft's Quick Basic compiler. It has been implemented under DOS 3.2.1 using 23K of RAM. AKLSQF was developed in 1989.

Accelerated pharmacokinetic map determination for dynamic contrast enhanced MRI using frequency-domain based Tofts model.

PubMed

Vajuvalli, Nithin N; Nayak, Krupa N; Geethanath, Sairam

2014-01-01

Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is widely used in the diagnosis of cancer and is also a promising tool for monitoring tumor response to treatment. The Tofts model has become a standard for the analysis of DCE-MRI. The process of curve fitting employed in the Tofts equation to obtain the pharmacokinetic (PK) parameters is time-consuming for high resolution scans. Current work demonstrates a frequency-domain approach applied to the standard Tofts equation to speed-up the process of curve-fitting in order to obtain the pharmacokinetic parameters. The results obtained show that using the frequency domain approach, the process of curve fitting is computationally more efficient compared to the time-domain approach.

Computer codes for the evaluation of thermodynamic and transport properties for equilibrium air to 30000 K

NASA Technical Reports Server (NTRS)

Thompson, Richard A.; Lee, Kam-Pui; Gupta, Roop N.

1991-01-01

The computer codes developed here provide self-consistent thermodynamic and transport properties for equilibrium air for temperatures from 500 to 30000 K over a temperature range of 10 (exp -4) to 10 (exp -2) atm. These properties are computed through the use of temperature dependent curve fits for discrete values of pressure. Interpolation is employed for intermediate values of pressure. The curve fits are based on mixture values calculated from an 11-species air model. Individual species properties used in the mixture relations are obtained from a recent study by the present authors. A review and discussion of the sources and accuracy of the curve fitted data used herein are given in NASA RP 1260.

Victimization, Aggression, and Other Problem Behaviors: Trajectories of Change Within and Across Middle School Grades.

PubMed

Farrell, Albert D; Goncy, Elizabeth A; Sullivan, Terri N; Thompson, Erin L

2018-06-01

This study examined trajectories of victimization and problem behaviors within and across three grades of middle school. Participants were 2,166 adolescents from three urban middle schools in the United States who completed measures of victimization, physical and relational aggression, substance use, and delinquent behavior. Latent curve analyses modeled changes in each construct across 12 waves collected every 3 months. In each case, the best-fitting model required separate linear slopes to represent changes within each grade and a factor representing decreases in the summers. Positive cross-construct correlations were found for intercepts, linear slopes, and measures within waves. The findings suggest strong associations among victimization and problem behaviors, and individual differences in their patterns of change both within and across grades. © 2017 Society for Research on Adolescence.

[An Improved Cubic Spline Interpolation Method for Removing Electrocardiogram Baseline Drift].

PubMed

Wang, Xiangkui; Tang, Wenpu; Zhang, Lai; Wu, Minghu

2016-04-01

The selection of fiducial points has an important effect on electrocardiogram(ECG)denoise with cubic spline interpolation.An improved cubic spline interpolation algorithm for suppressing ECG baseline drift is presented in this paper.Firstly the first order derivative of original ECG signal is calculated,and the maximum and minimum points of each beat are obtained,which are treated as the position of fiducial points.And then the original ECG is fed into a high pass filter with 1.5Hz cutoff frequency.The difference between the original and the filtered ECG at the fiducial points is taken as the amplitude of the fiducial points.Then cubic spline interpolation curve fitting is used to the fiducial points,and the fitting curve is the baseline drift curve.For the two simulated case test,the correlation coefficients between the fitting curve by the presented algorithm and the simulated curve were increased by 0.242and0.13 compared with that from traditional cubic spline interpolation algorithm.And for the case of clinical baseline drift data,the average correlation coefficient from the presented algorithm achieved 0.972.

A variable-gain output feedback control design approach

NASA Technical Reports Server (NTRS)

Haylo, Nesim

1989-01-01

A multi-model design technique to find a variable-gain control law defined over the whole operating range is proposed. The design is formulated as an optimal control problem which minimizes a cost function weighing the performance at many operating points. The solution is obtained by embedding into the Multi-Configuration Control (MCC) problem, a multi-model robust control design technique. In contrast to conventional gain scheduling which uses a curve fit of single model designs, the optimal variable-gain control law stabilizes the plant at every operating point included in the design. An iterative algorithm to compute the optimal control gains is presented. The methodology has been successfully applied to reconfigurable aircraft flight control and to nonlinear flight control systems.

Prospects for Chronological Studies of Martian Rocks and Soils

NASA Technical Reports Server (NTRS)

Nyquist, L. E.; Shih, C-Y.; Reese, Y. D.

2008-01-01

Chronological information about Martian processes comes from two sources: Crater-frequency studies and laboratory studies of Martian meteorites. Each has limitations that could be overcome by studies of returned Martian rocks and soils. Chronology of Martian volcanism: The currently accepted chronology of Martian volcanic surfaces relies on crater counts for different Martian stratigraphic units [1]. However, there is a large inherent uncertainty for intermediate ages near 2 Ga ago. The effect of differing preferences for Martian cratering chronologies [1] is shown in Fig. 1. Stoeffler and Ryder [2] summarized lunar chronology, upon which Martian cratering chronology is based. Fig. 2 shows a curve fit to their data, and compares to it a corresponding lunar curve from [3]. The radiometric ages of some lunar and Martian meteorites as well as the crater-count delimiters for Martian epochs [4] also are shown for comparison to the craterfrequency curves. Scaling the Stoeffler-Ryder curve by a Mars/Moon factor of 1.55 [5] places Martian shergottite ages into the Early Amazonian to late Hesperian epochs, whereas using the lunar curve of [3] and a Mars/Moon factor 1 consigns the shergottites to the Middle-to-Late Amazonian, a less probable result. The problem is worsened if a continually decreasing cratering rate since 3 Ga ago is accepted [6]. We prefer the adjusted St ffler-Ryder curve because it gives better agreement with the meteorite ages (Fig.

Efficient Workflows for Curation of Heterogeneous Data Supporting Modeling of U-Nb Alloy Aging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ward, Logan Timothy; Hackenberg, Robert Errol

These are slides from a presentation summarizing a graduate research associate's summer project. The following topics are covered in these slides: data challenges in materials, aging in U-Nb Alloys, Building an Aging Model, Different Phase Trans. in U-Nb, the Challenge, Storing Materials Data, Example Data Source, Organizing Data: What is a Schema?, What does a "XML Schema" look like?, Our Data Schema: Nice and Simple, Storing Data: Materials Data Curation System (MDCS), Problem with MDCS: Slow Data Entry, Getting Literature into MDCS, Staging Data in Excel Document, Final Result: MDCS Records, Analyzing Image Data, Process for Making TTT Diagram, Bottleneckmore » Number 1: Image Analysis, Fitting a TTP Boundary, Fitting a TTP Curve: Comparable Results, How Does it Compare to Our Data?, Image Analysis Workflow, Curating Hardness Records, Hardness Data: Two Key Decisions, Before Peak Age? - Automation, Interactive Viz, Which Transformation?, Microstructure-Informed Model, Tracking the Entire Process, General Problem with Property Models, Pinyon: Toolkit for Managing Model Creation, Tracking Individual Decisions, Jupyter: Docs and Code in One File, Hardness Analysis Workflow, Workflow for Aging Models, and conclusions.« less

Milky Way Mass Models and MOND

NASA Astrophysics Data System (ADS)

McGaugh, Stacy S.

2008-08-01

Using the Tuorla-Heidelberg model for the mass distribution of the Milky Way, I determine the rotation curve predicted by MOND (modified Newtonian dynamics). The result is in good agreement with the observed terminal velocities interior to the solar radius and with estimates of the Galaxy's rotation curve exterior thereto. There are no fit parameters: given the mass distribution, MOND provides a good match to the rotation curve. The Tuorla-Heidelberg model does allow for a variety of exponential scale lengths; MOND prefers short scale lengths in the range 2.0 kpc lesssim Rdlesssim 2.5 kpc. The favored value of Rd depends somewhat on the choice of interpolation function. There is some preference for the "simple" interpolation function as found by Famaey & Binney. I introduce an interpolation function that shares the advantages of the simple function on galaxy scales while having a much smaller impact in the solar system. I also solve the inverse problem, inferring the surface mass density distribution of the Milky Way from the terminal velocities. The result is a Galaxy with "bumps and wiggles" in both its luminosity profile and rotation curve that are reminiscent of those frequently observed in external galaxies.

Serial position curves in free recall.

PubMed

Laming, Donald

2010-01-01

The scenario for free recall set out in Laming (2009) is developed to provide models for the serial position curves from 5 selected sets of data, for final free recall, and for multitrial free recall. The 5 sets of data reflect the effects of rate of presentation, length of list, delay of recall, and suppression of rehearsal. Each model accommodates the serial position curve for first recalls (where those data are available) as well as that for total recalls. Both curves are fit with the same parameter values, as also (with 1 exception) are all of the conditions compared within each experiment. The distributions of numbers of recalls are also examined and shown to have variances increased above what would be expected if successive recalls were independent. This is taken to signify that, in those experiments in which rehearsals were not recorded, the retrieval of words for possible recall follows the same pattern that is observed following overt rehearsal, namely, that retrieval consists of runs of consecutive elements from memory. Finally, 2 sets of data are examined that the present approach cannot accommodate. It is argued that the problem with these data derives from an interaction between the patterns of (covert) rehearsal and the parameters of list presentation.

Dynamic rating curve assessment for hydrometric stations and computation of the associated uncertainties: Quality and station management indicators

NASA Astrophysics Data System (ADS)

Morlot, Thomas; Perret, Christian; Favre, Anne-Catherine; Jalbert, Jonathan

2014-09-01

A rating curve is used to indirectly estimate the discharge in rivers based on water level measurements. The discharge values obtained from a rating curve include uncertainties related to the direct stage-discharge measurements (gaugings) used to build the curves, the quality of fit of the curve to these measurements and the constant changes in the river bed morphology. Moreover, the uncertainty of discharges estimated from a rating curve increases with the “age” of the rating curve. The level of uncertainty at a given point in time is therefore particularly difficult to assess. A “dynamic” method has been developed to compute rating curves while calculating associated uncertainties, thus making it possible to regenerate streamflow data with uncertainty estimates. The method is based on historical gaugings at hydrometric stations. A rating curve is computed for each gauging and a model of the uncertainty is fitted for each of them. The model of uncertainty takes into account the uncertainties in the measurement of the water level, the quality of fit of the curve, the uncertainty of gaugings and the increase of the uncertainty of discharge estimates with the age of the rating curve computed with a variographic analysis (Jalbert et al., 2011). The presented dynamic method can answer important questions in the field of hydrometry such as “How many gaugings a year are required to produce streamflow data with an average uncertainty of X%?” and “When and in what range of water flow rates should these gaugings be carried out?”. The Rocherousse hydrometric station (France, Haute-Durance watershed, 946 [km2]) is used as an example throughout the paper. Others stations are used to illustrate certain points.

Hybrid Micro-Electro-Mechanical Tunable Filter

DTIC Science & Technology

2007-09-01

Figure 2.10), one can see the developers have used surface micromachining techniques to build the micromirror structure over the CMOS addressing...DBRs, microcavity composition, initial air gap, contact layers, substrate Dispersion Data Curve -fit dispersion data or generate dispersion function...measurements • Curve -fit the dispersion data or generate a continuous, wavelength-dependent, representation of material dispersion • Manually design the

Consideration of Wear Rates at High Velocities

DTIC Science & Technology

2010-03-01

Strain vs. Three-dimensional Model . . . . . . . . . . . . 57 3.11 Example Single Asperity Wear Rate Integral . . . . . . . . . . 58 4.1 Third Stage...Slipper Accumulated Frictional Heating . . . . . . 67 4.2 Surface Temperature Third Stage Slipper, ave=0.5 . . . . . . . 67 4.3 Melt Depth Example...64 A3S Coefficient for Frictional Heat Curve Fit, Third Stage Slipper 66 B3S Coefficient for Frictional Heat Curve Fit, Third

Analyser-based phase contrast image reconstruction using geometrical optics.

PubMed

Kitchen, M J; Pavlov, K M; Siu, K K W; Menk, R H; Tromba, G; Lewis, R A

2007-07-21

Analyser-based phase contrast imaging can provide radiographs of exceptional contrast at high resolution (<100 microm), whilst quantitative phase and attenuation information can be extracted using just two images when the approximations of geometrical optics are satisfied. Analytical phase retrieval can be performed by fitting the analyser rocking curve with a symmetric Pearson type VII function. The Pearson VII function provided at least a 10% better fit to experimentally measured rocking curves than linear or Gaussian functions. A test phantom, a hollow nylon cylinder, was imaged at 20 keV using a Si(1 1 1) analyser at the ELETTRA synchrotron radiation facility. Our phase retrieval method yielded a more accurate object reconstruction than methods based on a linear fit to the rocking curve. Where reconstructions failed to map expected values, calculations of the Takagi number permitted distinction between the violation of the geometrical optics conditions and the failure of curve fitting procedures. The need for synchronized object/detector translation stages was removed by using a large, divergent beam and imaging the object in segments. Our image acquisition and reconstruction procedure enables quantitative phase retrieval for systems with a divergent source and accounts for imperfections in the analyser.

Using quasars as standard clocks for measuring cosmological redshift.

PubMed

Dai, De-Chang; Starkman, Glenn D; Stojkovic, Branislav; Stojkovic, Dejan; Weltman, Amanda

2012-06-08

We report hitherto unnoticed patterns in quasar light curves. We characterize segments of the quasar's light curves with the slopes of the straight lines fit through them. These slopes appear to be directly related to the quasars' redshifts. Alternatively, using only global shifts in time and flux, we are able to find significant overlaps between the light curves of different pairs of quasars by fitting the ratio of their redshifts. We are then able to reliably determine the redshift of one quasar from another. This implies that one can use quasars as standard clocks, as we explicitly demonstrate by constructing two independent methods of finding the redshift of a quasar from its light curve.

Surface fitting three-dimensional bodies

NASA Technical Reports Server (NTRS)

Dejarnette, F. R.

1974-01-01

The geometry of general three-dimensional bodies is generated from coordinates of points in several cross sections. Since these points may not be smooth, they are divided into segments and general conic sections are curve fit in a least-squares sense to each segment of a cross section. The conic sections are then blended in the longitudinal direction by fitting parametric cubic-spline curves through coordinate points which define the conic sections in the cross-sectional planes. Both the cross-sectional and longitudinal curves may be modified by specifying particular segments as straight lines and slopes at selected points. Slopes may be continuous or discontinuous and finite or infinite. After a satisfactory surface fit has been obtained, cards may be punched with the data necessary to form a geometry subroutine package for use in other computer programs. At any position on the body, coordinates, slopes and second partial derivatives are calculated. The method is applied to a blunted 70 deg delta wing, and it was found to generate the geometry very well.

Focusing of light through turbid media by curve fitting optimization

NASA Astrophysics Data System (ADS)

Gong, Changmei; Wu, Tengfei; Liu, Jietao; Li, Huijuan; Shao, Xiaopeng; Zhang, Jianqi

2016-12-01

The construction of wavefront phase plays a critical role in focusing light through turbid media. We introduce the curve fitting algorithm (CFA) into the feedback control procedure for wavefront optimization. Unlike the existing continuous sequential algorithm (CSA), the CFA locates the optimal phase by fitting a curve to the measured signals. Simulation results show that, similar to the genetic algorithm (GA), the proposed CFA technique is far less susceptible to the experimental noise than the CSA. Furthermore, only three measurements of feedback signals are enough for CFA to fit the optimal phase while obtaining a higher focal intensity than the CSA and the GA, dramatically shortening the optimization time by a factor of 3 compared with the CSA and the GA. The proposed CFA approach can be applied to enhance the focus intensity and boost the focusing speed in the fields of biological imaging, particle trapping, laser therapy, and so on, and might help to focus light through dynamic turbid media.

Modeling Latent Growth Curves With Incomplete Data Using Different Types of Structural Equation Modeling and Multilevel Software

ERIC Educational Resources Information Center

Ferrer, Emilio; Hamagami, Fumiaki; McArdle, John J.

2004-01-01

This article offers different examples of how to fit latent growth curve (LGC) models to longitudinal data using a variety of different software programs (i.e., LISREL, Mx, Mplus, AMOS, SAS). The article shows how the same model can be fitted using both structural equation modeling and multilevel software, with nearly identical results, even in…

A Monte Carlo Study of the Effect of Item Characteristic Curve Estimation on the Accuracy of Three Person-Fit Statistics

ERIC Educational Resources Information Center

St-Onge, Christina; Valois, Pierre; Abdous, Belkacem; Germain, Stephane

2009-01-01

To date, there have been no studies comparing parametric and nonparametric Item Characteristic Curve (ICC) estimation methods on the effectiveness of Person-Fit Statistics (PFS). The primary aim of this study was to determine if the use of ICCs estimated by nonparametric methods would increase the accuracy of item response theory-based PFS for…

Improvements in Spectrum's fit to program data tool.

PubMed

Mahiane, Severin G; Marsh, Kimberly; Grantham, Kelsey; Crichlow, Shawna; Caceres, Karen; Stover, John

2017-04-01

The Joint United Nations Program on HIV/AIDS-supported Spectrum software package (Glastonbury, Connecticut, USA) is used by most countries worldwide to monitor the HIV epidemic. In Spectrum, HIV incidence trends among adults (aged 15-49 years) are derived by either fitting to seroprevalence surveillance and survey data or generating curves consistent with program and vital registration data, such as historical trends in the number of newly diagnosed infections or people living with HIV and AIDS related deaths. This article describes development and application of the fit to program data (FPD) tool in Joint United Nations Program on HIV/AIDS' 2016 estimates round. In the FPD tool, HIV incidence trends are described as a simple or double logistic function. Function parameters are estimated from historical program data on newly reported HIV cases, people living with HIV or AIDS-related deaths. Inputs can be adjusted for proportions undiagnosed or misclassified deaths. Maximum likelihood estimation or minimum chi-squared distance methods are used to identify the best fitting curve. Asymptotic properties of the estimators from these fits are used to estimate uncertainty. The FPD tool was used to fit incidence for 62 countries in 2016. Maximum likelihood and minimum chi-squared distance methods gave similar results. A double logistic curve adequately described observed trends in all but four countries where a simple logistic curve performed better. Robust HIV-related program and vital registration data are routinely available in many middle-income and high-income countries, whereas HIV seroprevalence surveillance and survey data may be scarce. In these countries, the FPD tool offers a simpler, improved approach to estimating HIV incidence trends.

THINGS about MOND

NASA Astrophysics Data System (ADS)

Gentile, G.; Famaey, B.; de Blok, W. J. G.

2011-03-01

We present an analysis of 12 high-resolution galactic rotation curves from The HI Nearby Galaxy Survey (THINGS) in the context of modified Newtonian dynamics (MOND). These rotation curves were selected to be the most reliable for mass modelling, and they are the highest quality rotation curves currently available for a sample of galaxies spanning a wide range of luminosities. We fit the rotation curves with the "simple" and "standard" interpolating functions of MOND, and we find that the "simple" function yields better results. We also redetermine the value of a0, and find a median value very close to the one determined in previous studies, a0 = (1.22 ± 0.33) × 10-8 cm s-2. Leaving the distance as a free parameter within the uncertainty of its best independently determined value leads to excellent quality fits for 75% of the sample. Among the three exceptions, two are also known to give relatively poor fits in Newtonian dynamics plus dark matter. The remaining case (NGC 3198) presents some tension between the observations and the MOND fit, which might, however, be explained by the presence of non-circular motions, by a small distance, or by a value of a0 at the lower end of our best-fit interval, 0.9 × 10-8 cm s-2. The best-fit stellar M/L ratios are generally in remarkable agreement with the predictions of stellar population synthesis models. We also show that the narrow range of gravitational accelerations found to be generated by dark matter in galaxies is consistent with the narrow range of additional gravity predicted by MOND.

Determining the hydraulic and fracture properties of the Coal Seam Gas well by numerical modelling and GLUE analysis

NASA Astrophysics Data System (ADS)

Askarimarnani, Sara; Willgoose, Garry; Fityus, Stephen

2017-04-01

Coal seam gas (CSG) is a form of natural gas that occurs in some coal seams. Coal seams have natural fractures with dual-porosity systems and low permeability. In the CSG industry, hydraulic fracturing is applied to increase the permeability and extract the gas more efficiently from the coal seam. The industry claims that it can design fracking patterns. Whether this is true or not, the public (and regulators) requires assurance that once a well has been fracked that the fracking has occurred according to plan and that the fracked well is safe. Thus defensible post-fracking testing methodologies for gas generating wells are required. In 2009 a fracked well HB02, owned by AGL, near Broke, NSW, Australia was subjected to "traditional" water pump-testing as part of this assurance process. Interpretation with well Type Curves and simple single phase (i.e. only water, no gas) highlighted deficiencies in traditional water well approaches with a systemic deviation from the qualitative characteristic of well drawdown curves (e.g. concavity versus convexity of drawdown with time). Accordingly a multiphase (i.e. water and methane) model of the well was developed and compared with the observed data. This paper will discuss the results of this multiphase testing using the TOUGH2 model and its EOS7C constitutive model. A key objective was to test a methodology, based on GLUE monte-carlo calibration technique, to calibrate the characteristics of the frack using the well test drawdown curve. GLUE involves a sensitivity analysis of how changes in the fracture properties change the well hydraulics through and analysis of the drawdown curve and changes in the cone of depression. This was undertaken by changing the native coal, fracture, and gas parameters to see how changing those parameters changed the match between simulations and the observed well drawdown. Results from the GLUE analysis show how much information is contained in the well drawdown curve for estimating field scale coal and gas generation properties, the fracture geometry, and the proponent characteristics. The results with the multiphase model show a better match to the drawdown than using a single phase model but the differences between the best fit drawdowns were small, and smaller than the difference between the best fit and field data. However, the parameters derived to generate these best fits for each model were very different. We conclude that while satisfactory fits with single phase groundwater models (e.g. MODFLOW, FEFLOW) can be achieved the parameters derived will not be realistic, with potential implications for drawdowns and water yields for gas field modelling. Multiphase models are thus required and we will discuss some of the limitations of TOUGH2 for the CSG problem.

Three-dimension reconstruction based on spatial light modulator

NASA Astrophysics Data System (ADS)

Deng, Xuejiao; Zhang, Nanyang; Zeng, Yanan; Yin, Shiliang; Wang, Weiyu

2011-02-01

Three-dimension reconstruction, known as an important research direction of computer graphics, is widely used in the related field such as industrial design and manufacture, construction, aerospace, biology and so on. Via such technology we can obtain three-dimension digital point cloud from a two-dimension image, and then simulate the three-dimensional structure of the physical object for further study. At present, the obtaining of three-dimension digital point cloud data is mainly based on the adaptive optics system with Shack-Hartmann sensor and phase-shifting digital holography. Referring to surface fitting, there are also many available methods such as iterated discrete fourier transform, convolution and image interpolation, linear phase retrieval. The main problems we came across in three-dimension reconstruction are the extraction of feature points and arithmetic of curve fitting. To solve such problems, we can, first of all, calculate the relevant surface normal vector information of each pixel in the light source coordinate system, then these vectors are to be converted to the coordinates of image through the coordinate conversion, so the expectant 3D point cloud get arise. Secondly, after the following procedures of de-noising, repairing, the feature points can later be selected and fitted to get the fitting function of the surface topography by means of Zernike polynomial, so as to reconstruct the determinand's three-dimensional topography. In this paper, a new kind of three-dimension reconstruction algorithm is proposed, with the assistance of which, the topography can be estimated from its grayscale at different sample points. Moreover, the previous stimulation and the experimental results prove that the new algorithm has a strong capability to fit, especially for large-scale objects .

Tuning rules for robust FOPID controllers based on multi-objective optimization with FOPDT models.

PubMed

Sánchez, Helem Sabina; Padula, Fabrizio; Visioli, Antonio; Vilanova, Ramon

2017-01-01

In this paper a set of optimally balanced tuning rules for fractional-order proportional-integral-derivative controllers is proposed. The control problem of minimizing at once the integrated absolute error for both the set-point and the load disturbance responses is addressed. The control problem is stated as a multi-objective optimization problem where a first-order-plus-dead-time process model subject to a robustness, maximum sensitivity based, constraint has been considered. A set of Pareto optimal solutions is obtained for different normalized dead times and then the optimal balance between the competing objectives is obtained by choosing the Nash solution among the Pareto-optimal ones. A curve fitting procedure has then been applied in order to generate suitable tuning rules. Several simulation results show the effectiveness of the proposed approach. Copyright © 2016. Published by Elsevier Ltd.

Investigations into the shape-preserving interpolants using symbolic computation

NASA Technical Reports Server (NTRS)

Lam, Maria

1988-01-01

Shape representation is a central issue in computer graphics and computer-aided geometric design. Many physical phenomena involve curves and surfaces that are monotone (in some directions) or are convex. The corresponding representation problem is given some monotone or convex data, and a monotone or convex interpolant is found. Standard interpolants need not be monotone or convex even though they may match monotone or convex data. Most of the methods of investigation of this problem involve the utilization of quadratic splines or Hermite polynomials. In this investigation, a similar approach is adopted. These methods require derivative information at the given data points. The key to the problem is the selection of the derivative values to be assigned to the given data points. Schemes for choosing derivatives were examined. Along the way, fitting given data points by a conic section has also been investigated as part of the effort to study shape-preserving quadratic splines.

Recovering a MOND-like acceleration law in mimetic gravity

NASA Astrophysics Data System (ADS)

Vagnozzi, Sunny

2017-09-01

We reconsider the recently proposed mimetic gravity, focusing in particular on whether the theory is able to reproduce the inferred flat rotation curves of galaxies. We extend the theory by adding a non-minimal coupling between matter and mimetic field. Such coupling leads to the appearance of an extra force which renders the motion of test particles non-geodesic. By studying the weak field limit of the resulting equations of motion, we demonstrate that in the Newtonian limit the acceleration law induced by the non-minimal coupling reduces to a modified Newtonian dynamics (MOND)-like one. In this way, it is possible to reproduce the successes of MOND, namely the explanation for the flat galactic rotation curves and the Tully-Fisher relation, within the framework of mimetic gravity, without the need for particle dark matter. The scale-dependence of the recovered acceleration scale opens up the possibility of addressing the missing mass problem not only on galactic but also on cluster scales: we defer a full study of this issue, together with a complete analysis of fits to spiral galaxy rotation curves, to an upcoming companion paper.

Measurement And Shape Analysis Including Vertebral Rotation Of Scoliotic Spines From Single Plane Radiographs

NASA Astrophysics Data System (ADS)

Drerup, B.; Hierholzer, E.

1986-07-01

Radiological assessment and follow-up control of scoliosis, i.e. of a lateral and rotational deviation of the spine, is performed mainly by single plane radiographs. Additional information may be gained from these radiographs by introducing a parametrized vertebral model. By analyzing the radiographic contours according to this model, axial rotation can be determined for any position and orientation of the vertebra. In addition to rotation several other data are determined for each vertebra, such as the tilting angle and the two-dimensional coordinates of the centre. By handling the data as a function of the vertebral location in spine, characteristic curves are generated. In order to find simple shape parameters for these characteristics, a smooth curve has to be fitted to the data points by a least squares approximation. This problem may be solved by a Fourier decomposition of the spinal curves. It appears, that the Fourier coefficients (amplitudes and phases) and some derived shape parameters lend themselves to a medical interpretation, which is consistent with the existing classification of the scoliotic spine.

Photographic photometry with Iris diaphragm photometers

NASA Technical Reports Server (NTRS)

Schaefer, B. E.

1981-01-01

A general method is presented for solving problems encountered in the analysis of Iris diaphragm photometer (IDP) data. The method is used to derive the general shape of the calibration curve, allowing both a more accurate fit to the IDP data for comparison stars and extrapolation to magnitude ranges for which no comparison stars are measured. The profile of starlight incident and the characteristic curve of the plate are both assumed and then used to derive the profile of the star image. An IDP reading is then determined for each star image. A procedure for correcting the effects of a nonconstant background fog level on the plate is also demonstrated. Additional applications of the method are made in the appendix to determine the relation between the radius of a photographic star image and the star's magnitude, and to predict the IDP reading of the 'point of optimum density'.

On the analytical determination of relaxation modulus of viscoelastic materials by Prony's interpolation method

NASA Technical Reports Server (NTRS)

Rodriguez, Pedro I.

1986-01-01

A computer implementation to Prony's curve fitting by exponential functions is presented. The method, although more than one hundred years old, has not been utilized to its fullest capabilities due to the restriction that the time range must be given in equal increments in order to obtain the best curve fit for a given set of data. The procedure used in this paper utilizes the 3-dimensional capabilities of the Interactive Graphics Design System (I.G.D.S.) in order to obtain the equal time increments. The resultant information is then input into a computer program that solves directly for the exponential constants yielding the best curve fit. Once the exponential constants are known, a simple least squares solution can be applied to obtain the final form of the equation.

Limb-darkening and the structure of the Jovian atmosphere

NASA Technical Reports Server (NTRS)

Newman, W. I.; Sagan, C.

1978-01-01

By observing the transit of various cloud features across the Jovian disk, limb-darkening curves were constructed for three regions in the 4.6 to 5.1 mu cm band. Several models currently employed in describing the radiative or dynamical properties of planetary atmospheres are here examined to understand their implications for limb-darkening. The statistical problem of fitting these models to the observed data is reviewed and methods for applying multiple regression analysis are discussed. Analysis of variance techniques are introduced to test the viability of a given physical process as a cause of the observed limb-darkening.

Development of a program to fit data to a new logistic model for microbial growth.

PubMed

Fujikawa, Hiroshi; Kano, Yoshihiro

2009-06-01

Recently we developed a mathematical model for microbial growth in food. The model successfully predicted microbial growth at various patterns of temperature. In this study, we developed a program to fit data to the model with a spread sheet program, Microsoft Excel. Users can instantly get curves fitted to the model by inputting growth data and choosing the slope portion of a curve. The program also could estimate growth parameters including the rate constant of growth and the lag period. This program would be a useful tool for analyzing growth data and further predicting microbial growth.

Significantly Reduced Blood Pressure Measurement Variability for Both Normotensive and Hypertensive Subjects: Effect of Polynomial Curve Fitting of Oscillometric Pulses

PubMed Central

Zhu, Mingping; Chen, Aiqing

2017-01-01

This study aimed to compare within-subject blood pressure (BP) variabilities from different measurement techniques. Cuff pressures from three repeated BP measurements were obtained from 30 normotensive and 30 hypertensive subjects. Automatic BPs were determined from the pulses with normalised peak amplitude larger than a threshold (0.5 for SBP, 0.7 for DBP, and 1.0 for MAP). They were also determined from cuff pressures associated with the above thresholds on a fitted curve polynomial curve of the oscillometric pulse peaks. Finally, the standard deviation (SD) of three repeats and its coefficient of variability (CV) were compared between the two automatic techniques. For the normotensive group, polynomial curve fitting significantly reduced SD of repeats from 3.6 to 2.5 mmHg for SBP and from 3.7 to 2.1 mmHg for MAP and reduced CV from 3.0% to 2.2% for SBP and from 4.3% to 2.4% for MAP (all P < 0.01). For the hypertensive group, SD of repeats decreased from 6.5 to 5.5 mmHg for SBP and from 6.7 to 4.2 mmHg for MAP, and CV decreased from 4.2% to 3.6% for SBP and from 5.8% to 3.8% for MAP (all P < 0.05). In conclusion, polynomial curve fitting of oscillometric pulses had the ability to reduce automatic BP measurement variability. PMID:28785580

A Multi-year Multi-passband CCD Photometric Study of the W UMa Binary EQ Tauri

NASA Astrophysics Data System (ADS)

Alton, K. B.

2009-12-01

A revised ephemeris and updated orbital period for EQ Tau have been determined from newly acquired (2007-2009) CCD-derived photometric data. A Roche-type model based on the Wilson-Devinney code produced simultaneous theoretical fits of light curve data in three passbands by invoking cold spots on the primary component. These new model fits, along with similar light curve data for EQ Tau collected during the previous six seasons (2000-2006), provided a rare opportunity to follow the seasonal appearance of star spots on a W UMa binary system over nine consecutive years. Fixed values for q, ?1,2, T1, T2, and i based upon the mean of eleven separately determined model fits produced for this system are hereafter proposed for future light curve modeling of EQ Tau. With the exception of the 2001 season all other light curves produced since then required a spotted solution to address the flux asymmetry exhibited by this binary system at Max I and Max II. At least one cold spot on the primary appears in seven out of twelve light curves for EQ Tau produced over the last nine years, whereas in six instances two cold spots on the primary star were invoked to improve the model fit. Solutions using a hot spot were less common and involved positioning a single spot on the primary constituent during the 2001-2002, 2002-2003, and 2005-2006 seasons.

Method and apparatus for air-coupled transducer

NASA Technical Reports Server (NTRS)

Song, Junho (Inventor); Chimenti, Dale E. (Inventor)

2010-01-01

An air-coupled transducer includes a ultrasonic transducer body having a radiation end with a backing fixture at the radiation end. There is a flexible backplate conformingly fit to the backing fixture and a thin membrane (preferably a metallized polymer) conformingly fit to the flexible backplate. In one embodiment, the backing fixture is spherically curved and the flexible backplate is spherically curved. The flexible backplate is preferably patterned with pits or depressions.

Fitting integrated enzyme rate equations to progress curves with the use of a weighting matrix.

PubMed Central

Franco, R; Aran, J M; Canela, E I

1991-01-01

A method is presented for fitting the pairs of values product formed-time taken from progress curves to the integrated rate equation. The procedure is applied to the estimation of the kinetic parameters of the adenosine deaminase system. Simulation studies demonstrate the capabilities of this strategy. A copy of the FORTRAN77 program used can be obtained from the authors by request. PMID:2006914

Apparatus and method for qualitative and quantitative measurements of optical properties of turbid media using frequency-domain photon migration

DOEpatents

Tromberg, B.J.; Tsay, T.T.; Berns, M.W.; Svaasand, L.O.; Haskell, R.C.

1995-06-13

Optical measurements of turbid media, that is media characterized by multiple light scattering, is provided through an apparatus and method for exposing a sample to a modulated laser beam. The light beam is modulated at a fundamental frequency and at a plurality of integer harmonics thereof. Modulated light is returned from the sample and preferentially detected at cross frequencies at frequencies slightly higher than the fundamental frequency and at integer harmonics of the same. The received radiance at the beat or cross frequencies is compared against a reference signal to provide a measure of the phase lag of the radiance and modulation ratio relative to a reference beam. The phase and modulation amplitude are then provided as a frequency spectrum by an array processor to which a computer applies a complete curve fit in the case of highly scattering samples or a linear curve fit below a predetermined frequency in the case of highly absorptive samples. The curve fit in any case is determined by the absorption and scattering coefficients together with a concentration of the active substance in the sample. Therefore, the curve fitting to the frequency spectrum can be used both for qualitative and quantitative analysis of substances in the sample even though the sample is highly turbid. 14 figs.

Apparatus and method for qualitative and quantitative measurements of optical properties of turbid media using frequency-domain photon migration

DOEpatents

Tromberg, Bruce J.; Tsay, Tsong T.; Berns, Michael W.; Svaasand, Lara O.; Haskell, Richard C.

1995-01-01

Optical measurements of turbid media, that is media characterized by multiple light scattering, is provided through an apparatus and method for exposing a sample to a modulated laser beam. The light beam is modulated at a fundamental frequency and at a plurality of integer harmonics thereof. Modulated light is returned from the sample and preferentially detected at cross frequencies at frequencies slightly higher than the fundamental frequency and at integer harmonics of the same. The received radiance at the beat or cross frequencies is compared against a reference signal to provide a measure of the phase lag of the radiance and modulation ratio relative to a reference beam. The phase and modulation amplitude are then provided as a frequency spectrum by an array processor to which a computer applies a complete curve fit in the case of highly scattering samples or a linear curve fit below a predetermined frequency in the case of highly absorptive samples. The curve fit in any case is determined by the absorption and scattering coefficients together with a concentration of the active substance in the sample. Therefore, the curve fitting to the frequency spectrum can be used both for qualitative and quantitative analysis of substances in the sample even though the sample is highly turbid.

Modelling lactation curve for milk fat to protein ratio in Iranian buffaloes (Bubalus bubalis) using non-linear mixed models.

PubMed

Hossein-Zadeh, Navid Ghavi

2016-08-01

The aim of this study was to compare seven non-linear mathematical models (Brody, Wood, Dhanoa, Sikka, Nelder, Rook and Dijkstra) to examine their efficiency in describing the lactation curves for milk fat to protein ratio (FPR) in Iranian buffaloes. Data were 43 818 test-day records for FPR from the first three lactations of Iranian buffaloes which were collected on 523 dairy herds in the period from 1996 to 2012 by the Animal Breeding Center of Iran. Each model was fitted to monthly FPR records of buffaloes using the non-linear mixed model procedure (PROC NLMIXED) in SAS and the parameters were estimated. The models were tested for goodness of fit using Akaike's information criterion (AIC), Bayesian information criterion (BIC) and log maximum likelihood (-2 Log L). The Nelder and Sikka mixed models provided the best fit of lactation curve for FPR in the first and second lactations of Iranian buffaloes, respectively. However, Wood, Dhanoa and Sikka mixed models provided the best fit of lactation curve for FPR in the third parity buffaloes. Evaluation of first, second and third lactation features showed that all models, except for Dijkstra model in the third lactation, under-predicted test time at which daily FPR was minimum. On the other hand, minimum FPR was over-predicted by all equations. Evaluation of the different models used in this study indicated that non-linear mixed models were sufficient for fitting test-day FPR records of Iranian buffaloes.

Interactive contour delineation and refinement in treatment planning of image‐guided radiation therapy

PubMed Central

Zhou, Wu

2014-01-01

The accurate contour delineation of the target and/or organs at risk (OAR) is essential in treatment planning for image‐guided radiation therapy (IGRT). Although many automatic contour delineation approaches have been proposed, few of them can fulfill the necessities of applications in terms of accuracy and efficiency. Moreover, clinicians would like to analyze the characteristics of regions of interests (ROI) and adjust contours manually during IGRT. Interactive tool for contour delineation is necessary in such cases. In this work, a novel approach of curve fitting for interactive contour delineation is proposed. It allows users to quickly improve contours by a simple mouse click. Initially, a region which contains interesting object is selected in the image, then the program can automatically select important control points from the region boundary, and the method of Hermite cubic curves is used to fit the control points. Hence, the optimized curve can be revised by moving its control points interactively. Meanwhile, several curve fitting methods are presented for the comparison. Finally, in order to improve the accuracy of contour delineation, the process of the curve refinement based on the maximum gradient magnitude is proposed. All the points on the curve are revised automatically towards the positions with maximum gradient magnitude. Experimental results show that Hermite cubic curves and the curve refinement based on the maximum gradient magnitude possess superior performance on the proposed platform in terms of accuracy, robustness, and time calculation. Experimental results of real medical images demonstrate the efficiency, accuracy, and robustness of the proposed process in clinical applications. PACS number: 87.53.Tf PMID:24423846

Dust Attenuation Curves in the Local Universe: Demographics and New Laws for Star-forming Galaxies and High-redshift Analogs

NASA Astrophysics Data System (ADS)

Salim, Samir; Boquien, Médéric; Lee, Janice C.

2018-05-01

We study the dust attenuation curves of 230,000 individual galaxies in the local universe, ranging from quiescent to intensely star-forming systems, using GALEX, SDSS, and WISE photometry calibrated on the Herschel ATLAS. We use a new method of constraining SED fits with infrared luminosity (SED+LIR fitting), and parameterized attenuation curves determined with the CIGALE SED-fitting code. Attenuation curve slopes and UV bump strengths are reasonably well constrained independently from one another. We find that {A}λ /{A}V attenuation curves exhibit a very wide range of slopes that are on average as steep as the curve slope of the Small Magellanic Cloud (SMC). The slope is a strong function of optical opacity. Opaque galaxies have shallower curves—in agreement with recent radiative transfer models. The dependence of slopes on the opacity produces an apparent dependence on stellar mass: more massive galaxies have shallower slopes. Attenuation curves exhibit a wide range of UV bump amplitudes, from none to Milky Way (MW)-like, with an average strength one-third that of the MW bump. Notably, local analogs of high-redshift galaxies have an average curve that is somewhat steeper than the SMC curve, with a modest UV bump that can be, to first order, ignored, as its effect on the near-UV magnitude is 0.1 mag. Neither the slopes nor the strengths of the UV bump depend on gas-phase metallicity. Functional forms for attenuation laws are presented for normal star-forming galaxies, high-z analogs, and quiescent galaxies. We release the catalog of associated star formation rates and stellar masses (GALEX–SDSS–WISE Legacy Catalog 2).

Characterizing the UV-to-NIR shape of the dust attenuation curve of IR luminous galaxies up to z ˜ 2

NASA Astrophysics Data System (ADS)

Lo Faro, B.; Buat, V.; Roehlly, Y.; Alvarez-Marquez, J.; Burgarella, D.; Silva, L.; Efstathiou, A.

2017-12-01

In this work, we investigate the far-ultraviolet (UV) to near-infrared (NIR) shape of the dust attenuation curve of a sample of IR-selected dust obscured (ultra)luminous IR galaxies at z ∼ 2. The spectral energy distributions (SEDs) are fitted with Code Investigating GALaxy Emission, a physically motivated spectral-synthesis model based on energy balance. Its flexibility allows us to test a wide range of different analytical prescriptions for the dust attenuation curve, including the well-known Calzetti and Charlot & Fall curves, and modified versions of them. The attenuation curves computed under the assumption of our reference double power-law model are in very good agreement with those derived, in previous works, with radiative transfer (RT) SED fitting. We investigate the position of our galaxies in the IRX-β diagram and find this to be consistent with greyer slopes, on average, in the UV. We also find evidence for a flattening of the attenuation curve in the NIR with respect to more classical Calzetti-like recipes. This larger NIR attenuation yields larger derived stellar masses from SED fitting, by a median factor of ∼1.4 and up to a factor ∼10 for the most extreme cases. The star formation rate appears instead to be more dependent on the total amount of attenuation in the galaxy. Our analysis highlights the need for a flexible attenuation curve when reproducing the physical properties of a large variety of objects.

Numerical integration of discontinuous functions: moment fitting and smart octree

NASA Astrophysics Data System (ADS)

Hubrich, Simeon; Di Stolfo, Paolo; Kudela, László; Kollmannsberger, Stefan; Rank, Ernst; Schröder, Andreas; Düster, Alexander

2017-11-01

A fast and simple grid generation can be achieved by non-standard discretization methods where the mesh does not conform to the boundary or the internal interfaces of the problem. However, this simplification leads to discontinuous integrands for intersected elements and, therefore, standard quadrature rules do not perform well anymore. Consequently, special methods are required for the numerical integration. To this end, we present two approaches to obtain quadrature rules for arbitrary domains. The first approach is based on an extension of the moment fitting method combined with an optimization strategy for the position and weights of the quadrature points. In the second approach, we apply the smart octree, which generates curved sub-cells for the integration mesh. To demonstrate the performance of the proposed methods, we consider several numerical examples, showing that the methods lead to efficient quadrature rules, resulting in less integration points and in high accuracy.

STACCATO: a novel solution to supernova photometric classification with biased training sets

NASA Astrophysics Data System (ADS)

Revsbech, E. A.; Trotta, R.; van Dyk, D. A.

2018-01-01

We present a new solution to the problem of classifying Type Ia supernovae from their light curves alone given a spectroscopically confirmed but biased training set, circumventing the need to obtain an observationally expensive unbiased training set. We use Gaussian processes (GPs) to model the supernovae's (SN's) light curves, and demonstrate that the choice of covariance function has only a small influence on the GPs ability to accurately classify SNe. We extend and improve the approach of Richards et al. - a diffusion map combined with a random forest classifier - to deal specifically with the case of biased training sets. We propose a novel method called Synthetically Augmented Light Curve Classification (STACCATO) that synthetically augments a biased training set by generating additional training data from the fitted GPs. Key to the success of the method is the partitioning of the observations into subgroups based on their propensity score of being included in the training set. Using simulated light curve data, we show that STACCATO increases performance, as measured by the area under the Receiver Operating Characteristic curve (AUC), from 0.93 to 0.96, close to the AUC of 0.977 obtained using the 'gold standard' of an unbiased training set and significantly improving on the previous best result of 0.88. STACCATO also increases the true positive rate for SNIa classification by up to a factor of 50 for high-redshift/low-brightness SNe.

Phytoplankton productivity in relation to light intensity: A simple equation

USGS Publications Warehouse

Peterson, D.H.; Perry, M.J.; Bencala, K.E.; Talbot, M.C.

1987-01-01

A simple exponential equation is used to describe photosynthetic rate as a function of light intensity for a variety of unicellular algae and higher plants where photosynthesis is proportional to (1-e-??1). The parameter ?? (=Ik-1) is derived by a simultaneous curve-fitting method, where I is incident quantum-flux density. The exponential equation is tested against a wide range of data and is found to adequately describe P vs. I curves. The errors associated with photosynthetic parameters are calculated. A simplified statistical model (Poisson) of photon capture provides a biophysical basis for the equation and for its ability to fit a range of light intensities. The exponential equation provides a non-subjective simultaneous curve fitting estimate for photosynthetic efficiency (a) which is less ambiguous than subjective methods: subjective methods assume that a linear region of the P vs. I curve is readily identifiable. Photosynthetic parameters ?? and a are used widely in aquatic studies to define photosynthesis at low quantum flux. These parameters are particularly important in estuarine environments where high suspended-material concentrations and high diffuse-light extinction coefficients are commonly encountered. ?? 1987.

The Predicting Model of E-commerce Site Based on the Ideas of Curve Fitting

NASA Astrophysics Data System (ADS)

Tao, Zhang; Li, Zhang; Dingjun, Chen

On the basis of the idea of the second multiplication curve fitting, the number and scale of Chinese E-commerce site is analyzed. A preventing increase model is introduced in this paper, and the model parameters are solved by the software of Matlab. The validity of the preventing increase model is confirmed though the numerical experiment. The experimental results show that the precision of preventing increase model is ideal.

Modeling and Maximum Likelihood Fitting of Gamma-Ray and Radio Light Curves of Millisecond Pulsars Detected with Fermi

NASA Technical Reports Server (NTRS)

Johnson, T. J.; Harding, A. K.; Venter, C.

2012-01-01

Pulsed gamma rays have been detected with the Fermi Large Area Telescope (LAT) from more than 20 millisecond pulsars (MSPs), some of which were discovered in radio observations of bright, unassociated LAT sources. We have fit the radio and gamma-ray light curves of 19 LAT-detected MSPs in the context of geometric, outermagnetospheric emission models assuming the retarded vacuum dipole magnetic field using a Markov chain Monte Carlo maximum likelihood technique. We find that, in many cases, the models are able to reproduce the observed light curves well and provide constraints on the viewing geometries that are in agreement with those from radio polarization measurements. Additionally, for some MSPs we constrain the altitudes of both the gamma-ray and radio emission regions. The best-fit magnetic inclination angles are found to cover a broader range than those of non-recycled gamma-ray pulsars.

Determination of uronic acids in isolated hemicelluloses from kenaf using diffuse reflectance infrared fourier transform spectroscopy (DRIFTS) and the curve-fitting deconvolution method.

PubMed

Batsoulis, A N; Nacos, M K; Pappas, C S; Tarantilis, P A; Mavromoustakos, T; Polissiou, M G

2004-02-01

Hemicellulose samples were isolated from kenaf (Hibiscus cannabinus L.). Hemicellulosic fractions usually contain a variable percentage of uronic acids. The uronic acid content (expressed in polygalacturonic acid) of the isolated hemicelluloses was determined by diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and the curve-fitting deconvolution method. A linear relationship between uronic acids content and the sum of the peak areas at 1745, 1715, and 1600 cm(-1) was established with a high correlation coefficient (0.98). The deconvolution analysis using the curve-fitting method allowed the elimination of spectral interferences from other cell wall components. The above method was compared with an established spectrophotometric method and was found equivalent for accuracy and repeatability (t-test, F-test). This method is applicable in analysis of natural or synthetic mixtures and/or crude substances. The proposed method is simple, rapid, and nondestructive for the samples.

Observational evidence of dust evolution in galactic extinction curves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cecchi-Pestellini, Cesare; Casu, Silvia; Mulas, Giacomo

Although structural and optical properties of hydrogenated amorphous carbons are known to respond to varying physical conditions, most conventional extinction models are basically curve fits with modest predictive power. We compare an evolutionary model of the physical properties of carbonaceous grain mantles with their determination by homogeneously fitting observationally derived Galactic extinction curves with the same physically well-defined dust model. We find that a large sample of observed Galactic extinction curves are compatible with the evolutionary scenario underlying such a model, requiring physical conditions fully consistent with standard density, temperature, radiation field intensity, and average age of diffuse interstellar clouds.more » Hence, through the study of interstellar extinction we may, in principle, understand the evolutionary history of the diffuse interstellar clouds.« less

UTM, a universal simulator for lightcurves of transiting systems

NASA Astrophysics Data System (ADS)

Deeg, Hans

2009-02-01

The Universal Transit Modeller (UTM) is a light-curve simulator for all kinds of transiting or eclipsing configurations between arbitrary numbers of several types of objects, which may be stars, planets, planetary moons, and planetary rings. Applications of UTM to date have been mainly in the generation of light-curves for the testing of detection algorithms. For the preparation of such test for the Corot Mission, a special version has been used to generate multicolour light-curves in Corot's passbands. A separate fitting program, UFIT (Universal Fitter) is part of the UTM distribution and may be used to derive best fits to light-curves for any set of continuously variable parameters. UTM/UFIT is written in IDL code and its source is released in the public domain under the GNU General Public License.

The effect of semirigid dressings on below-knee amputations.

PubMed

MacLean, N; Fick, G H

1994-07-01

The effect of using semirigid dressings (SRDs) on the residual limb of individuals who have had below-knee amputations as a consequence of peripheral vascular disease was investigated, with the primary question being: Does the time to readiness for prosthetic fitting for patients treated with the SRDs differ from that of patients treated with soft dressings? Forty patients entered the study and were alternately assigned to one of two groups. Nineteen patients were assigned to the SRD group, and 21 patients were assigned to the soft dressing group. The time from surgery to readiness for prosthetic fitting was recorded for each patient. Kaplan-Meier survival curves were generated for each group, and the results were analyzed with the log-rank test. There was a difference between the two curves, and an examination of the curves suggests that the expected time to readiness for prosthetic fitting for patients treated with the SRDs would be less than half that of patients treated with soft dressings. The results suggest that a patient may be ready for prosthetic fitting sooner if treated with SRDs instead of soft dressings.

Decomposition of mineral absorption bands using nonlinear least squares curve fitting: Application to Martian meteorites and CRISM data

NASA Astrophysics Data System (ADS)

Parente, Mario; Makarewicz, Heather D.; Bishop, Janice L.

2011-04-01

This study advances curve-fitting modeling of absorption bands of reflectance spectra and applies this new model to spectra of Martian meteorites ALH 84001 and EETA 79001 and data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). This study also details a recently introduced automated parameter initialization technique. We assess the performance of this automated procedure by comparing it to the currently available initialization method and perform a sensitivity analysis of the fit results to variation in initial guesses. We explore the issues related to the removal of the continuum, offer guidelines for continuum removal when modeling the absorptions and explore different continuum-removal techniques. We further evaluate the suitability of curve fitting techniques using Gaussians/Modified Gaussians to decompose spectra into individual end-member bands. We show that nonlinear least squares techniques such as the Levenberg-Marquardt algorithm achieve comparable results to the MGM model ( Sunshine and Pieters, 1993; Sunshine et al., 1990) for meteorite spectra. Finally we use Gaussian modeling to fit CRISM spectra of pyroxene and olivine-rich terrains on Mars. Analysis of CRISM spectra of two regions show that the pyroxene-dominated rock spectra measured at Juventae Chasma were modeled well with low Ca pyroxene, while the pyroxene-rich spectra acquired at Libya Montes required both low-Ca and high-Ca pyroxene for a good fit.

Derivation of error sources for experimentally derived heliostat shapes

NASA Astrophysics Data System (ADS)

Cumpston, Jeff; Coventry, Joe

2017-06-01

Data gathered using photogrammetry that represents the surface and structure of a heliostat mirror panel is investigated in detail. A curve-fitting approach that allows the retrieval of four distinct mirror error components, while prioritizing the best fit possible to paraboloidal terms in the curve fitting equation, is presented. The angular errors associated with each of the four surfaces are calculated, and the relative magnitude for each of them is given. It is found that in this case, the mirror had a significant structural twist, and an estimate of the improvement to the mirror surface quality in the case of no twist was made.

Efficient and reliable characterization of the corticospinal system using transcranial magnetic stimulation.

PubMed

Kukke, Sahana N; Paine, Rainer W; Chao, Chi-Chao; de Campos, Ana C; Hallett, Mark

2014-06-01

The purpose of this study is to develop a method to reliably characterize multiple features of the corticospinal system in a more efficient manner than typically done in transcranial magnetic stimulation studies. Forty transcranial magnetic stimulation pulses of varying intensity were given over the first dorsal interosseous motor hot spot in 10 healthy adults. The first dorsal interosseous motor-evoked potential size was recorded during rest and activation to create recruitment curves. The Boltzmann sigmoidal function was fit to the data, and parameters relating to maximal motor-evoked potential size, curve slope, and stimulus intensity leading to half-maximal motor-evoked potential size were computed from the curve fit. Good to excellent test-retest reliability was found for all corticospinal parameters at rest and during activation with 40 transcranial magnetic stimulation pulses. Through the use of curve fitting, important features of the corticospinal system can be determined with fewer stimuli than typically used for the same information. Determining the recruitment curve provides a basis to understand the state of the corticospinal system and select subject-specific parameters for transcranial magnetic stimulation testing quickly and without unnecessary exposure to magnetic stimulation. This method can be useful in individuals who have difficulty in maintaining stillness, including children and patients with motor disorders.

Feature Detection and Curve Fitting Using Fast Walsh Transforms for Shock Tracking: Applications

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.

2017-01-01

Walsh functions form an orthonormal basis set consisting of square waves. Square waves make the system well suited for detecting and representing functions with discontinuities. Given a uniform distribution of 2p cells on a one-dimensional element, it has been proven that the inner product of the Walsh Root function for group p with every polynomial of degree < or = (p - 1) across the element is identically zero. It has also been proven that the magnitude and location of a discontinuous jump, as represented by a Heaviside function, are explicitly identified by its Fast Walsh Transform (FWT) coefficients. These two proofs enable an algorithm that quickly provides a Weighted Least Squares fit to distributions across the element that include a discontinuity. The detection of a discontinuity enables analytic relations to locally describe its evolution and provide increased accuracy. Time accurate examples are provided for advection, Burgers equation, and Riemann problems (diaphragm burst) in closed tubes and de Laval nozzles. New algorithms to detect up to two C0 and/or C1 discontinuities within a single element are developed for application to the Riemann problem, in which a contact discontinuity and shock wave form after the diaphragm bursts.

Automatic Rooftop Extraction in Stereo Imagery Using Distance and Building Shape Regularized Level Set Evolution

NASA Astrophysics Data System (ADS)

Tian, J.; Krauß, T.; d'Angelo, P.

2017-05-01

Automatic rooftop extraction is one of the most challenging problems in remote sensing image analysis. Classical 2D image processing techniques are expensive due to the high amount of features required to locate buildings. This problem can be avoided when 3D information is available. In this paper, we show how to fuse the spectral and height information of stereo imagery to achieve an efficient and robust rooftop extraction. In the first step, the digital terrain model (DTM) and in turn the normalized digital surface model (nDSM) is generated by using a newly step-edge approach. In the second step, the initial building locations and rooftop boundaries are derived by removing the low-level pixels and high-level pixels with higher probability to be trees and shadows. This boundary is then served as the initial level set function, which is further refined to fit the best possible boundaries through distance regularized level-set curve evolution. During the fitting procedure, the edge-based active contour model is adopted and implemented by using the edges indicators extracted from panchromatic image. The performance of the proposed approach is tested by using the WorldView-2 satellite data captured over Munich.

Penalized gaussian process regression and classification for high-dimensional nonlinear data.

PubMed

Yi, G; Shi, J Q; Choi, T

2011-12-01

The model based on Gaussian process (GP) prior and a kernel covariance function can be used to fit nonlinear data with multidimensional covariates. It has been used as a flexible nonparametric approach for curve fitting, classification, clustering, and other statistical problems, and has been widely applied to deal with complex nonlinear systems in many different areas particularly in machine learning. However, it is a challenging problem when the model is used for the large-scale data sets and high-dimensional data, for example, for the meat data discussed in this article that have 100 highly correlated covariates. For such data, it suffers from large variance of parameter estimation and high predictive errors, and numerically, it suffers from unstable computation. In this article, penalized likelihood framework will be applied to the model based on GPs. Different penalties will be investigated, and their ability in application given to suit the characteristics of GP models will be discussed. The asymptotic properties will also be discussed with the relevant proofs. Several applications to real biomechanical and bioinformatics data sets will be reported. © 2011, The International Biometric Society No claim to original US government works.

UFO (UnFold Operator) user guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kissel, L.; Biggs, F.; Marking, T.R.

UFO is a collection of interactive utility programs for estimating unknown functions of one variable using a wide-ranging class of information as input, for miscellaneous data-analysis applications, for performing feasibility studies, and for supplementing our other software. Inverse problems, which include spectral unfolds, inverse heat-transfer problems, time-domain deconvolution, and unusual or difficult curve-fit problems, are classes of applications for which UFO is well suited. Extensive use of B-splines and (X,Y)-datasets is made to represent functions. The (X,Y)-dataset representation is unique in that it is not restricted to equally-spaced data. This feature is used, for example, in a table-generating algorithm thatmore » evaluates a function to a user-specified interpolation accuracy while minimizing the number of points stored in the corresponding dataset. UFO offers a variety of miscellaneous data-analysis options such as plotting, comparing, transforming, scaling, integrating; and adding, subtracting, multiplying, and dividing functions together. These options are often needed as intermediate steps in analyzing and solving difficult inverse problems, but they also find frequent use in other applications. Statistical options are available to calculate goodness-of-fit to measurements, specify error bands on solutions, give confidence limits on calculated quantities, and to point out the statistical consequences of operations such as smoothing. UFO is designed to do feasibility studies on a variety of engineering measurements. It is also tailored to supplement our Test Analysis and Design codes, SRAD Test-Data Archive software, and Digital Signal Analysis routines.« less

A method to characterize average cervical spine ligament response based on raw data sets for implementation into injury biomechanics models.

PubMed

Mattucci, Stephen F E; Cronin, Duane S

2015-01-01

Experimental testing on cervical spine ligaments provides important data for advanced numerical modeling and injury prediction; however, accurate characterization of individual ligament response and determination of average mechanical properties for specific ligaments has not been adequately addressed in the literature. Existing methods are limited by a number of arbitrary choices made during the curve fits that often misrepresent the characteristic shape response of the ligaments, which is important for incorporation into numerical models to produce a biofidelic response. A method was developed to represent the mechanical properties of individual ligaments using a piece-wise curve fit with first derivative continuity between adjacent regions. The method was applied to published data for cervical spine ligaments and preserved the shape response (toe, linear, and traumatic regions) up to failure, for strain rates of 0.5s(-1), 20s(-1), and 150-250s(-1), to determine the average force-displacement curves. Individual ligament coefficients of determination were 0.989 to 1.000 demonstrating excellent fit. This study produced a novel method in which a set of experimental ligament material property data exhibiting scatter was fit using a characteristic curve approach with a toe, linear, and traumatic region, as often observed in ligaments and tendons, and could be applied to other biological material data with a similar characteristic shape. The resultant average cervical spine ligament curves provide an accurate representation of the raw test data and the expected material property effects corresponding to varying deformation rates. Copyright © 2014 Elsevier Ltd. All rights reserved.

Forgetting Curves: Implications for Connectionist Models

ERIC Educational Resources Information Center

Sikstrom, Sverker

2002-01-01

Forgetting in long-term memory, as measured in a recall or a recognition test, is faster for items encoded more recently than for items encoded earlier. Data on forgetting curves fit a power function well. In contrast, many connectionist models predict either exponential decay or completely flat forgetting curves. This paper suggests a…

Nonlinear Growth Models in M"plus" and SAS

ERIC Educational Resources Information Center

Grimm, Kevin J.; Ram, Nilam

2009-01-01

Nonlinear growth curves or growth curves that follow a specified nonlinear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this article we describe how a variety of sigmoid curves can be fit using the M"plus" structural modeling program and the nonlinear…

On the Early-Time Excess Emission in Hydrogen-Poor Superluminous Supernovae

NASA Technical Reports Server (NTRS)

Vreeswijk, Paul M.; Leloudas, Giorgos; Gal-Yam, Avishay; De Cia, Annalisa; Perley, Daniel A.; Quimby, Robert M.; Waldman, Roni; Sullivan, Mark; Yan, Lin; Ofek, Eran O.;

On The Early-Time Excess Emission In Hydrogen-Poor Superluminous Supernovae

DOE PAGES

Vreeswijk, Paul M.; Leloudas, Giorgos; Gal-Yam, Avishay; ...

2017-01-18

Here, we present the light curves of the hydrogen-poor superluminous supernovae (SLSNe I) PTF 12dam and iPTF 13dcc, discovered by the (intermediate) Palomar Transient Factory. Both show excess emission at early times and a slowly declining light curve at late times. The early bump in PTF 12dam is very similar in duration (~10 days) and brightness relative to the main peak (2-3 mag fainter) compared to that observed in other SLSNe I. In contrast, the long-duration ( > 30 days) early excess emission in iPTF 13dcc, whose brightness competes with that of the main peak, appears to be of amore » different nature. We construct bolometric light curves for both targets, and fit a variety of light-curve models to both the early bump and main peak in an attempt to understand the nature of these explosions. Even though the slope of the late-time decline in the light curves of both SLSNe is suggestively close to that expected from the radioactive decay of 56Ni and 56Co, the amount of nickel required to power the full light curves is too large considering the estimated ejecta mass. The magnetar model including an increasing escape fraction provides a reasonable description of the PTF 12dam observations. However, neither the basic nor the double-peaked magnetar model is capable of reproducing the light curve of iPTF 13dcc. A model combining a shock breakout in an extended envelope with late-time magnetar energy injection provides a reasonable fit to the iPTF 13dcc observations. Finally, we find that the light curves of both PTF 12dam and iPTF 13dcc can be adequately fit with the model involving interaction with the circumstellar medium.« less

ON THE EARLY-TIME EXCESS EMISSION IN HYDROGEN-POOR SUPERLUMINOUS SUPERNOVAE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vreeswijk, Paul M.; Leloudas, Giorgos; Gal-Yam, Avishay

2017-01-20

We present the light curves of the hydrogen-poor superluminous supernovae (SLSNe I) PTF 12dam and iPTF 13dcc, discovered by the (intermediate) Palomar Transient Factory. Both show excess emission at early times and a slowly declining light curve at late times. The early bump in PTF 12dam is very similar in duration (∼10 days) and brightness relative to the main peak (2–3 mag fainter) compared to that observed in other SLSNe I. In contrast, the long-duration (>30 days) early excess emission in iPTF 13dcc, whose brightness competes with that of the main peak, appears to be of a different nature. Wemore » construct bolometric light curves for both targets, and fit a variety of light-curve models to both the early bump and main peak in an attempt to understand the nature of these explosions. Even though the slope of the late-time decline in the light curves of both SLSNe is suggestively close to that expected from the radioactive decay of {sup 56}Ni and {sup 56}Co, the amount of nickel required to power the full light curves is too large considering the estimated ejecta mass. The magnetar model including an increasing escape fraction provides a reasonable description of the PTF 12dam observations. However, neither the basic nor the double-peaked magnetar model is capable of reproducing the light curve of iPTF 13dcc. A model combining a shock breakout in an extended envelope with late-time magnetar energy injection provides a reasonable fit to the iPTF 13dcc observations. Finally, we find that the light curves of both PTF 12dam and iPTF 13dcc can be adequately fit with the model involving interaction with the circumstellar medium.« less

Experimental study of water desorption isotherms and thin-layer convective drying kinetics of bay laurel leaves

NASA Astrophysics Data System (ADS)

Ghnimi, Thouraya; Hassini, Lamine; Bagane, Mohamed

2016-12-01

The aim of this work is to determine the desorption isotherms and the drying kinetics of bay laurel leaves ( Laurus Nobilis L.). The desorption isotherms were performed at three temperature levels: 50, 60 and 70 °C and at water activity ranging from 0.057 to 0.88 using the statistic gravimetric method. Five sorption models were used to fit desorption experimental isotherm data. It was found that Kuhn model offers the best fitting of experimental moisture isotherms in the mentioned investigated ranges of temperature and water activity. The Net isosteric heat of water desorption was evaluated using The Clausius-Clapeyron equation and was then best correlated to equilibrium moisture content by the empirical Tsami's equation. Thin layer convective drying curves of bay laurel leaves were obtained for temperatures of 45, 50, 60 and 70 °C, relative humidity of 5, 15, 30 and 45 % and air velocities of 1, 1.5 and 2 m/s. A non linear regression procedure of Levenberg-Marquardt was used to fit drying curves with five semi empirical mathematical models available in the literature, The R2 and χ2 were used to evaluate the goodness of fit of models to data. Based on the experimental drying curves the drying characteristic curve (DCC) has been established and fitted with a third degree polynomial function. It was found that the Midilli Kucuk model was the best semi-empirical model describing thin layer drying kinetics of bay laurel leaves. The bay laurel leaves effective moisture diffusivity and activation energy were also identified.

The relationship between offspring size and fitness: integrating theory and empiricism.

PubMed

Rollinson, Njal; Hutchings, Jeffrey A

2013-02-01

How parents divide the energy available for reproduction between size and number of offspring has a profound effect on parental reproductive success. Theory indicates that the relationship between offspring size and offspring fitness is of fundamental importance to the evolution of parental reproductive strategies: this relationship predicts the optimal division of resources between size and number of offspring, it describes the fitness consequences for parents that deviate from optimality, and its shape can predict the most viable type of investment strategy in a given environment (e.g., conservative vs. diversified bet-hedging). Many previous attempts to estimate this relationship and the corresponding value of optimal offspring size have been frustrated by a lack of integration between theory and empiricism. In the present study, we draw from C. Smith and S. Fretwell's classic model to explain how a sound estimate of the offspring size--fitness relationship can be derived with empirical data. We evaluate what measures of fitness can be used to model the offspring size--fitness curve and optimal size, as well as which statistical models should and should not be used to estimate offspring size--fitness relationships. To construct the fitness curve, we recommend that offspring fitness be measured as survival up to the age at which the instantaneous rate of offspring mortality becomes random with respect to initial investment. Parental fitness is then expressed in ecologically meaningful, theoretically defensible, and broadly comparable units: the number of offspring surviving to independence. Although logistic and asymptotic regression have been widely used to estimate offspring size-fitness relationships, the former provides relatively unreliable estimates of optimal size when offspring survival and sample sizes are low, and the latter is unreliable under all conditions. We recommend that the Weibull-1 model be used to estimate this curve because it provides modest improvements in prediction accuracy under experimentally relevant conditions.

On the Methodology of Studying Aging in Humans

DTIC Science & Technology

1961-01-01

prediction of death rates The relation of death rate to age has been extensively studied for over 100 years. As an illustration recent death rates for...log death rates appear to be linear, the simpler Gompertz curve fits closely. While on this subject of the Makeham-Gompertz function, it should be...Makeham-Gompertz curve to 5 year age specific death rates . Each fitting provided estimates of the parameters a, {j, and log c for each of the five year

Statistically generated weighted curve fit of residual functions for modal analysis of structures

NASA Technical Reports Server (NTRS)

Bookout, P. S.

1995-01-01

A statistically generated weighting function for a second-order polynomial curve fit of residual functions has been developed. The residual flexibility test method, from which a residual function is generated, is a procedure for modal testing large structures in an external constraint-free environment to measure the effects of higher order modes and interface stiffness. This test method is applicable to structures with distinct degree-of-freedom interfaces to other system components. A theoretical residual function in the displacement/force domain has the characteristics of a relatively flat line in the lower frequencies and a slight upward curvature in the higher frequency range. In the test residual function, the above-mentioned characteristics can be seen in the data, but due to the present limitations in the modal parameter evaluation (natural frequencies and mode shapes) of test data, the residual function has regions of ragged data. A second order polynomial curve fit is required to obtain the residual flexibility term. A weighting function of the data is generated by examining the variances between neighboring data points. From a weighted second-order polynomial curve fit, an accurate residual flexibility value can be obtained. The residual flexibility value and free-free modes from testing are used to improve a mathematical model of the structure. The residual flexibility modal test method is applied to a straight beam with a trunnion appendage and a space shuttle payload pallet simulator.

Waveform fitting and geometry analysis for full-waveform lidar feature extraction

NASA Astrophysics Data System (ADS)

Tsai, Fuan; Lai, Jhe-Syuan; Cheng, Yi-Hsiu

2016-10-01

This paper presents a systematic approach that integrates spline curve fitting and geometry analysis to extract full-waveform LiDAR features for land-cover classification. The cubic smoothing spline algorithm is used to fit the waveform curve of the received LiDAR signals. After that, the local peak locations of the waveform curve are detected using a second derivative method. According to the detected local peak locations, commonly used full-waveform features such as full width at half maximum (FWHM) and amplitude can then be obtained. In addition, the number of peaks, time difference between the first and last peaks, and the average amplitude are also considered as features of LiDAR waveforms with multiple returns. Based on the waveform geometry, dynamic time-warping (DTW) is applied to measure the waveform similarity. The sum of the absolute amplitude differences that remain after time-warping can be used as a similarity feature in a classification procedure. An airborne full-waveform LiDAR data set was used to test the performance of the developed feature extraction method for land-cover classification. Experimental results indicate that the developed spline curve- fitting algorithm and geometry analysis can extract helpful full-waveform LiDAR features to produce better land-cover classification than conventional LiDAR data and feature extraction methods. In particular, the multiple-return features and the dynamic time-warping index can improve the classification results significantly.

Graphical approach to assess the soil fertility evaluation model validity for rice (case study: southern area of Merapi Mountain, Indonesia)

NASA Astrophysics Data System (ADS)

Julianto, E. A.; Suntoro, W. A.; Dewi, W. S.; Partoyo

2018-03-01

Climate change has been reported to exacerbate land resources degradation including soil fertility decline. The appropriate validity use on soil fertility evaluation could reduce the risk of climate change effect on plant cultivation. This study aims to assess the validity of a Soil Fertility Evaluation Model using a graphical approach. The models evaluated were the Indonesian Soil Research Center (PPT) version model, the FAO Unesco version model, and the Kyuma version model. Each model was then correlated with rice production (dry grain weight/GKP). The goodness of fit of each model can be tested to evaluate the quality and validity of a model, as well as the regression coefficient (R2). This research used the Eviews 9 programme by a graphical approach. The results obtained three curves, namely actual, fitted, and residual curves. If the actual and fitted curves are widely apart or irregular, this means that the quality of the model is not good, or there are many other factors that are still not included in the model (large residual) and conversely. Indeed, if the actual and fitted curves show exactly the same shape, it means that all factors have already been included in the model. Modification of the standard soil fertility evaluation models can improve the quality and validity of a model.

Simulating the Transfer of Strontium-90 from Soil to Leafy Vegetables by Using Strontium-88.

PubMed

Kuke, Ding; Shujuan, Liu; Yingxue, He; Dong, Yan; Fengshou, Zhang; Shuifeng, Wang; Jinghua, Guo; Wei, Zhang; Xin, Wang; Xiaoyan, Jiang

The transfer, from soil to Chinese cabbage and spinach, of radioactive strontium-90 released as a result of accidents in nuclear power stations was studied using a stable isotope of strontium, namely nuclide strontium-88 ( 88 Sr). The study led to an experimental model for assessing the hazard of radionuclide strontium-90 ( 90 Sr) entering the food chain and for predicting the risk to food safety. Chinese cabbage and spinach were grown in pots in a greenhouse and irrigated with deionized water containing known quantities of strontium. Based on the strontium content of that water, the plants were divided into five groups (treatments) and strontium content of the soil, and 30-day-old plants were determined by inductively coupled plasma atomic emission spectroscopy instrument (ICP-AES). Data on the strontium content of soil and plants enabled the development of a model using MATLAB, a mathematical software package, which included curve fitting and problem solving using regression equations and differential equations. Although strontium curves for leaves, stems, and roots of Chinese cabbage were not exactly the same, all showed a non-linear increase when compared with the increase in the content of strontium in soil. Strontium curves for leaves, stems, and roots of spinach were very similar and showed an initial increase followed by a decrease. Strontium concentrations in both Chinese cabbage and spinach were initially related to the concentrations of sodium and sulfur, the next two relevant nuclides being calcium and magnesium. The relationship between calcium and strontium in Chinese cabbage was different from that in spinach. By using 88 Sr to simulate the transfer of radionuclide 90 Sr from soil to a crop, the relevant data required to deal with accidental release of strontium can be obtained using a fitting curve and regression equations, thereby providing some experimental basis for evaluating the potential hazards posed by such accidents to the food chain.

Physical fitness reference standards in fibromyalgia: The al-Ándalus project.

PubMed

Álvarez-Gallardo, I C; Carbonell-Baeza, A; Segura-Jiménez, V; Soriano-Maldonado, A; Intemann, T; Aparicio, V A; Estévez-López, F; Camiletti-Moirón, D; Herrador-Colmenero, M; Ruiz, J R; Delgado-Fernández, M; Ortega, F B

2017-11-01

We aimed (1) to report age-specific physical fitness levels in people with fibromyalgia of a representative sample from Andalusia; and (2) to compare the fitness levels of people with fibromyalgia with non-fibromyalgia controls. This cross-sectional study included 468 (21 men) patients with fibromyalgia and 360 (55 men) controls. The fibromyalgia sample was geographically representative from southern Spain. Physical fitness was assessed with the Senior Fitness Test battery plus the handgrip test. We applied the Generalized Additive Model for Location, Scale and Shape to calculate percentile curves for women and fitted mean curves using a linear regression for men. Our results show that people with fibromyalgia reached worse performance in all fitness tests than controls (P < 0.001) in all age ranges (P < 0.001). This study provides a comprehensive description of age-specific physical fitness levels among patients with fibromyalgia and controls in a large sample of patients with fibromyalgia from southern of Spain. Physical fitness levels of people with fibromyalgia from Andalusia are very low in comparison with age-matched healthy controls. This information could be useful to correctly interpret physical fitness assessments and helping health care providers to identify individuals at risk for losing physical independence. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

From least squares to multilevel modeling: A graphical introduction to Bayesian inference

NASA Astrophysics Data System (ADS)

Loredo, Thomas J.

2016-01-01

This tutorial presentation will introduce some of the key ideas and techniques involved in applying Bayesian methods to problems in astrostatistics. The focus will be on the big picture: understanding the foundations (interpreting probability, Bayes's theorem, the law of total probability and marginalization), making connections to traditional methods (propagation of errors, least squares, chi-squared, maximum likelihood, Monte Carlo simulation), and highlighting problems where a Bayesian approach can be particularly powerful (Poisson processes, density estimation and curve fitting with measurement error). The "graphical" component of the title reflects an emphasis on pictorial representations of some of the math, but also on the use of graphical models (multilevel or hierarchical models) for analyzing complex data. Code for some examples from the talk will be available to participants, in Python and in the Stan probabilistic programming language.

Automated generation of influence functions for planar crack problems

NASA Technical Reports Server (NTRS)

Sire, Robert A.; Harris, David O.; Eason, Ernest D.

1989-01-01

A numerical procedure for the generation of influence functions for Mode I planar problems is described. The resulting influence functions are in a form for convenient evaluation of stress-intensity factors for complex stress distributions. Crack surface displacements are obtained by a least-squares solution of the Williams eigenfunction expansion for displacements in a cracked body. Discrete values of the influence function, evaluated using the crack surface displacements, are curve fit using an assumed functional form. The assumed functional form includes appropriate limit-behavior terms for very deep and very shallow cracks. Continuous representation of the influence function provides a convenient means for evaluating stress-intensity factors for arbitrary stress distributions by numerical integration. The procedure is demonstrated for an edge-cracked strip and a radially cracked disk. Comparisons with available published results demonstrate the accuracy of the procedure.

Nongaussian distribution curve of heterophorias among children.

PubMed

Letourneau, J E; Giroux, R

1991-02-01

The purpose of this study was to measure the distribution curve of horizontal and vertical phorias among children. Kolmogorov-Smirnov goodness of fit tests showed that these distribution curves were not Gaussian among (N = 2048) 6- to 13-year-old children. The distribution curve of horizontal phoria at far and of vertical phorias at far and at near were leptokurtic; the distribution curve of horizontal phoria at near was platykurtic. No variation of the distribution curve of heterophorias with age was observed. Comparisons of any individual findings with the general distribution curve should take the nonGaussian distribution curve of heterophorias into account.

UTM: Universal Transit Modeller

NASA Astrophysics Data System (ADS)

Deeg, Hans J.

2014-12-01

The Universal Transit Modeller (UTM) is a light-curve simulator for all kinds of transiting or eclipsing configurations between arbitrary numbers of several types of objects, which may be stars, planets, planetary moons, and planetary rings. A separate fitting program, UFIT (Universal Fitter) is part of the UTM distribution and may be used to derive best fits to light-curves for any set of continuously variable parameters. UTM/UFIT is written in IDL code and its source is released in the public domain under the GNU General Public License.

Transformation Model Choice in Nonlinear Regression Analysis of Fluorescence-based Serial Dilution Assays

PubMed Central

Fong, Youyi; Yu, Xuesong

2016-01-01

Many modern serial dilution assays are based on fluorescence intensity (FI) readouts. We study optimal transformation model choice for fitting five parameter logistic curves (5PL) to FI-based serial dilution assay data. We first develop a generalized least squares-pseudolikelihood type algorithm for fitting heteroscedastic logistic models. Next we show that the 5PL and log 5PL functions can approximate each other well. We then compare four 5PL models with different choices of log transformation and variance modeling through a Monte Carlo study and real data. Our findings are that the optimal choice depends on the intended use of the fitted curves. PMID:27642502

The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

PubMed

Syfert, Mindy M; Smith, Matthew J; Coomes, David A

2013-01-01

Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.

A Numerical Method for Calculating Stellar Occultation Light Curves from an Arbitrary Atmospheric Model

NASA Technical Reports Server (NTRS)

Chamberlain, D. M.; Elliot, J. L.

1997-01-01

We present a method for speeding up numerical calculations of a light curve for a stellar occultation by a planetary atmosphere with an arbitrary atmospheric model that has spherical symmetry. This improved speed makes least-squares fitting for model parameters practical. Our method takes as input several sets of values for the first two radial derivatives of the refractivity at different values of model parameters, and interpolates to obtain the light curve at intermediate values of one or more model parameters. It was developed for small occulting bodies such as Pluto and Triton, but is applicable to planets of all sizes. We also present the results of a series of tests showing that our method calculates light curves that are correct to an accuracy of 10(exp -4) of the unocculted stellar flux. The test benchmarks are (i) an atmosphere with a l/r dependence of temperature, which yields an analytic solution for the light curve, (ii) an atmosphere that produces an exponential refraction angle, and (iii) a small-planet isothermal model. With our method, least-squares fits to noiseless data also converge to values of parameters with fractional errors of no more than 10(exp -4), with the largest errors occurring in small planets. These errors are well below the precision of the best stellar occultation data available. Fits to noisy data had formal errors consistent with the level of synthetic noise added to the light curve. We conclude: (i) one should interpolate refractivity derivatives and then form light curves from the interpolated values, rather than interpolating the light curves themselves; (ii) for the most accuracy, one must specify the atmospheric model for radii many scale heights above half light; and (iii) for atmospheres with smoothly varying refractivity with altitude, light curves can be sampled as coarsely as two points per scale height.

A case study demonstration of the soil temperature extrema recovery rates after precipitation cooling at 10-cm soil depth

NASA Technical Reports Server (NTRS)

Welker, Jean Edward

1991-01-01

Since the invention of maximum and minimum thermometers in the 18th century, diurnal temperature extrema have been taken for air worldwide. At some stations, these extrema temperatures were collected at various soil depths also, and the behavior of these temperatures at a 10-cm depth at the Tifton Experimental Station in Georgia is presented. After a precipitation cooling event, the diurnal temperature maxima drop to a minimum value and then start a recovery to higher values (similar to thermal inertia). This recovery represents a measure of response to heating as a function of soil moisture and soil property. Eight different curves were fitted to a wide variety of data sets for different stations and years, and both power and exponential curves were fitted to a wide variety of data sets for different stations and years. Both power and exponential curve fits were consistently found to be statistically accurate least-square fit representations of the raw data recovery values. The predictive procedures used here were multivariate regression analyses, which are applicable to soils at a variety of depths besides the 10-cm depth presented.

Recalcitrant vulnerability curves: methods of analysis and the concept of fibre bridges for enhanced cavitation resistance.

PubMed

Cai, Jing; Li, Shan; Zhang, Haixin; Zhang, Shuoxin; Tyree, Melvin T

2014-01-01

Vulnerability curves (VCs) generally can be fitted to the Weibull equation; however, a growing number of VCs appear to be recalcitrant, that is, deviate from a Weibull but seem to fit dual Weibull curves. We hypothesize that dual Weibull curves in Hippophae rhamnoides L. are due to different vessel diameter classes, inter-vessel hydraulic connections or vessels versus fibre tracheids. We used dye staining techniques, hydraulic measurements and quantitative anatomy measurements to test these hypotheses. The fibres contribute 1.3% of the total stem conductivity, which eliminates the hypothesis that fibre tracheids account for the second Weibull curve. Nevertheless, the staining pattern of vessels and fibre tracheids suggested that fibres might function as a hydraulic bridge between adjacent vessels. We also argue that fibre bridges are safer than vessel-to-vessel pits and put forward the concept as a new paradigm. Hence, we tentatively propose that the first Weibull curve may be accounted by vessels connected to each other directly by pit fields, while the second Weibull curve is associated with vessels that are connected almost exclusively by fibre bridges. Further research is needed to test the concept of fibre bridge safety in species that have recalcitrant or normal Weibull curves. © 2013 John Wiley & Sons Ltd.

An interactive graphics program to retrieve, display, compare, manipulate, curve fit, difference and cross plot wind tunnel data

NASA Technical Reports Server (NTRS)

Elliott, R. D.; Werner, N. M.; Baker, W. M.

1975-01-01

The Aerodynamic Data Analysis and Integration System (ADAIS), developed as a highly interactive computer graphics program capable of manipulating large quantities of data such that addressable elements of a data base can be called up for graphic display, compared, curve fit, stored, retrieved, differenced, etc., was described. The general nature of the system is evidenced by the fact that limited usage has already occurred with data bases consisting of thermodynamic, basic loads, and flight dynamics data. Productivity using ADAIS of five times that for conventional manual methods of wind tunnel data analysis is routinely achieved. In wind tunnel data analysis, data from one or more runs of a particular test may be called up and displayed along with data from one or more runs of a different test. Curves may be faired through the data points by any of four methods, including cubic spline and least squares polynomial fit up to seventh order.

Research on Al-alloy sheet forming formability during warm/hot sheet hydroforming based on elliptical warm bulging test

NASA Astrophysics Data System (ADS)

Cai, Gaoshen; Wu, Chuanyu; Gao, Zepu; Lang, Lihui; Alexandrov, Sergei

2018-05-01

An elliptical warm/hot sheet bulging test under different temperatures and pressure rates was carried out to predict Al-alloy sheet forming limit during warm/hot sheet hydroforming. Using relevant formulas of ultimate strain to calculate and dispose experimental data, forming limit curves (FLCS) in tension-tension state of strain (TTSS) area are obtained. Combining with the basic experimental data obtained by uniaxial tensile test under the equivalent condition with bulging test, complete forming limit diagrams (FLDS) of Al-alloy are established. Using a quadratic polynomial curve fitting method, material constants of fitting function are calculated and a prediction model equation for sheet metal forming limit is established, by which the corresponding forming limit curves in TTSS area can be obtained. The bulging test and fitting results indicated that the sheet metal FLCS obtained were very accurate. Also, the model equation can be used to instruct warm/hot sheet bulging test.

Fluorometric titration approach for calibration of quantity of binding site of purified monoclonal antibody recognizing epitope/hapten nonfluorescent at 340 nm.

PubMed

Yang, Xiaolan; Hu, Xiaolei; Xu, Bangtian; Wang, Xin; Qin, Jialin; He, Chenxiong; Xie, Yanling; Li, Yuanli; Liu, Lin; Liao, Fei

2014-06-17

A fluorometric titration approach was proposed for the calibration of the quantity of monoclonal antibody (mcAb) via the quench of fluorescence of tryptophan residues. It applied to purified mcAbs recognizing tryptophan-deficient epitopes, haptens nonfluorescent at 340 nm under the excitation at 280 nm, or fluorescent haptens bearing excitation valleys nearby 280 nm and excitation peaks nearby 340 nm to serve as Förster-resonance-energy-transfer (FRET) acceptors of tryptophan. Titration probes were epitopes/haptens themselves or conjugates of nonfluorescent haptens or tryptophan-deficient epitopes with FRET acceptors of tryptophan. Under the excitation at 280 nm, titration curves were recorded as fluorescence specific for the FRET acceptors or for mcAbs at 340 nm. To quantify the binding site of a mcAb, a universal model considering both static and dynamic quench by either type of probes was proposed for fitting to the titration curve. This was easy for fitting to fluorescence specific for the FRET acceptors but encountered nonconvergence for fitting to fluorescence of mcAbs at 340 nm. As a solution, (a) the maximum of the absolute values of first-order derivatives of a titration curve as fluorescence at 340 nm was estimated from the best-fit model for a probe level of zero, and (b) molar quantity of the binding site of the mcAb was estimated via consecutive fitting to the same titration curve by utilizing such a maximum as an approximate of the slope for linear response of fluorescence at 340 nm to quantities of the mcAb. This fluorometric titration approach was proved effective with one mcAb for six-histidine and another for penicillin G.

Incorporating Nonstationarity into IDF Curves across CONUS from Station Records and Implications

NASA Astrophysics Data System (ADS)

Wang, K.; Lettenmaier, D. P.

2017-12-01

Intensity-duration-frequency (IDF) curves are widely used for engineering design of storm-affected structures. Current practice is that IDF-curves are based on observed precipitation extremes fit to a stationary probability distribution (e.g., the extreme value family). However, there is increasing evidence of nonstationarity in station records. We apply the Mann-Kendall trend test to over 1000 stations across the CONUS at a 0.05 significance level, and find that about 30% of stations test have significant nonstationarity for at least one duration (1-, 2-, 3-, 6-, 12-, 24-, and 48-hours). We fit the stations to a GEV distribution with time-varying location and scale parameters using a Bayesian- methodology and compare the fit of stationary versus nonstationary GEV distributions to observed precipitation extremes. Within our fitted nonstationary GEV distributions, we compare distributions with a time-varying location parameter versus distributions with both time-varying location and scale parameters. For distributions with two time-varying parameters, we pay particular attention to instances where location and scale trends have opposing directions. Finally, we use the mathematical framework based on work of Koutsoyiannis to generate IDF curves based on the fitted GEV distributions and discuss the implications that using time-varying parameters may have on simple scaling relationships. We apply the above methods to evaluate how frequency statistics based on a stationary assumption compare to those that incorporate nonstationarity for both short and long term projects. Overall, we find that neglecting nonstationarity can lead to under- or over-estimates (depending on the trend for the given duration and region) of important statistics such as the design storm.

Detecting outliers when fitting data with nonlinear regression – a new method based on robust nonlinear regression and the false discovery rate

PubMed Central

Motulsky, Harvey J; Brown, Ronald E

2006-01-01

Background Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads to the familiar goal of regression: to minimize the sum of the squares of the vertical or Y-value distances between the points and the curve. Outliers can dominate the sum-of-the-squares calculation, and lead to misleading results. However, we know of no practical method for routinely identifying outliers when fitting curves with nonlinear regression. Results We describe a new method for identifying outliers when fitting data with nonlinear regression. We first fit the data using a robust form of nonlinear regression, based on the assumption that scatter follows a Lorentzian distribution. We devised a new adaptive method that gradually becomes more robust as the method proceeds. To define outliers, we adapted the false discovery rate approach to handling multiple comparisons. We then remove the outliers, and analyze the data using ordinary least-squares regression. Because the method combines robust regression and outlier removal, we call it the ROUT method. When analyzing simulated data, where all scatter is Gaussian, our method detects (falsely) one or more outlier in only about 1–3% of experiments. When analyzing data contaminated with one or several outliers, the ROUT method performs well at outlier identification, with an average False Discovery Rate less than 1%. Conclusion Our method, which combines a new method of robust nonlinear regression with a new method of outlier identification, identifies outliers from nonlinear curve fits with reasonable power and few false positives. PMID:16526949

Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

PubMed

Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

2013-07-01

Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

NOTE: A BPF-type algorithm for CT with a curved PI detector

NASA Astrophysics Data System (ADS)

Tang, Jie; Zhang, Li; Chen, Zhiqiang; Xing, Yuxiang; Cheng, Jianping

2006-08-01

Helical cone-beam CT is used widely nowadays because of its rapid scan speed and efficient utilization of x-ray dose. Recently, an exact reconstruction algorithm for helical cone-beam CT was proposed (Zou and Pan 2004a Phys. Med. Biol. 49 941 59). The algorithm is referred to as a backprojection-filtering (BPF) algorithm. This BPF algorithm for a helical cone-beam CT with a flat-panel detector (FPD-HCBCT) requires minimum data within the Tam Danielsson window and can naturally address the problem of ROI reconstruction from data truncated in both longitudinal and transversal directions. In practical CT systems, detectors are expensive and always take a very important position in the total cost. Hence, we work on an exact reconstruction algorithm for a CT system with a detector of the smallest size, i.e., a curved PI detector fitting the Tam Danielsson window. The reconstruction algorithm is derived following the framework of the BPF algorithm. Numerical simulations are done to validate our algorithm in this study.

A BPF-type algorithm for CT with a curved PI detector.

PubMed

Tang, Jie; Zhang, Li; Chen, Zhiqiang; Xing, Yuxiang; Cheng, Jianping

2006-08-21

Helical cone-beam CT is used widely nowadays because of its rapid scan speed and efficient utilization of x-ray dose. Recently, an exact reconstruction algorithm for helical cone-beam CT was proposed (Zou and Pan 2004a Phys. Med. Biol. 49 941-59). The algorithm is referred to as a backprojection-filtering (BPF) algorithm. This BPF algorithm for a helical cone-beam CT with a flat-panel detector (FPD-HCBCT) requires minimum data within the Tam-Danielsson window and can naturally address the problem of ROI reconstruction from data truncated in both longitudinal and transversal directions. In practical CT systems, detectors are expensive and always take a very important position in the total cost. Hence, we work on an exact reconstruction algorithm for a CT system with a detector of the smallest size, i.e., a curved PI detector fitting the Tam-Danielsson window. The reconstruction algorithm is derived following the framework of the BPF algorithm. Numerical simulations are done to validate our algorithm in this study.

Simple solution for a complex problem: proanthocyanidins, galloyl glucoses and ellagitannins fit on a single calibration curve in high performance-gel permeation chromatography.

PubMed

Stringano, Elisabetta; Gea, An; Salminen, Juha-Pekka; Mueller-Harvey, Irene

2011-10-28

This study was undertaken to explore gel permeation chromatography (GPC) for estimating molecular weights of proanthocyanidin fractions isolated from sainfoin (Onobrychis viciifolia). The results were compared with data obtained by thiolytic degradation of the same fractions. Polystyrene, polyethylene glycol and polymethyl methacrylate standards were not suitable for estimating the molecular weights of underivatized proanthocyanidins. Therefore, a novel HPLC-GPC method was developed based on two serially connected PolarGel-L columns using DMF that contained 5% water, 1% acetic acid and 0.15 M LiBr at 0.7 ml/min and 50 °C. This yielded a single calibration curve for galloyl glucoses (trigalloyl glucose, pentagalloyl glucose), ellagitannins (pedunculagin, vescalagin, punicalagin, oenothein B, gemin A), proanthocyanidins (procyanidin B2, cinnamtannin B1), and several other polyphenols (catechin, epicatechin gallate, epicallocatechin gallate, amentoflavone). These GPC predicted molecular weights represented a considerable advance over previously reported HPLC-GPC methods for underivatized proanthocyanidins. Copyright © 2011 Elsevier B.V. All rights reserved.

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

PubMed

Sabry, A H; W Hasan, W Z; Ab Kadir, M Z A; Radzi, M A M; Shafie, S

2018-01-01

The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

PubMed Central

W. Hasan, W. Z.

2018-01-01

The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model. PMID:29351554

Temperature-dependent inotropic and lusitropic indices based on half-logistic time constants for four segmental phases in isovolumic left ventricular pressure-time curve in excised, cross-circulated canine heart.

PubMed

Mizuno, Ju; Mohri, Satoshi; Yokoyama, Takeshi; Otsuji, Mikiya; Arita, Hideko; Hanaoka, Kazuo

2017-02-01

Varying temperature affects cardiac systolic and diastolic function and the left ventricular (LV) pressure-time curve (PTC) waveform that includes information about LV inotropism and lusitropism. Our proposed half-logistic (h-L) time constants obtained by fitting using h-L functions for four segmental phases (Phases I-IV) in the isovolumic LV PTC are more useful indices for estimating LV inotropism and lusitropism during contraction and relaxation periods than the mono-exponential (m-E) time constants at normal temperature. In this study, we investigated whether the superiority of the goodness of h-L fits remained even at hypothermia and hyperthermia. Phases I-IV in the isovolumic LV PTCs in eight excised, cross-circulated canine hearts at 33, 36, and 38 °C were analyzed using h-L and m-E functions and the least-squares method. The h-L and m-E time constants for Phases I-IV significantly shortened with increasing temperature. Curve fitting using h-L functions was significantly better than that using m-E functions for Phases I-IV at all temperatures. Therefore, the superiority of the goodness of h-L fit vs. m-E fit remained at all temperatures. As LV inotropic and lusitropic indices, temperature-dependent h-L time constants could be more useful than m-E time constants for Phases I-IV.

The Biasing Effects of Unmodeled ARMA Time Series Processes on Latent Growth Curve Model Estimates

ERIC Educational Resources Information Center

Sivo, Stephen; Fan, Xitao; Witta, Lea

2005-01-01

The purpose of this study was to evaluate the robustness of estimated growth curve models when there is stationary autocorrelation among manifest variable errors. The results suggest that when, in practice, growth curve models are fitted to longitudinal data, alternative rival hypotheses to consider would include growth models that also specify…

Binary Sources and Binary Lenses in Microlensing Surveys of MACHOs

NASA Astrophysics Data System (ADS)

Petrovic, N.; Di Stefano, R.; Perna, R.

2003-12-01

Microlensing is an intriguing phenomenon which may yield information about the nature of dark matter. Early observational searches identified hundreds of microlensing light curves. The data set consisted mainly of point-lens light curves and binary-lens events in which the light curves exhibit caustic crossings. Very few mildly perturbed light curves were observed, although this latter type should constitute the majority of binary lens light curves. Di Stefano (2001) has suggested that the failure to take binary effects into account may have influenced the estimates of optical depth derived from microlensing surveys. The work we report on here is the first step in a systematic analysis of binary lenses and binary sources and their impact on the results of statistical microlensing surveys. In order to asses the problem, we ran Monte-Carlo simulations of various microlensing events involving binary stars (both as the source and as the lens). For each event with peak magnification > 1.34, we sampled the characteristic light curve and recorded the chi squared value when fitting the curve with a point lens model; we used this to asses the perturbation rate. We also recorded the parameters of each system, the maximum magnification, the times at which each light curve started and ended and the number of caustic crossings. We found that both the binarity of sources and the binarity of lenses increased the lensing rate. While the binarity of sources had a negligible effect on the perturbation rates of the light curves, the binarity of lenses had a notable effect. The combination of binary sources and binary lenses produces an observable rate of interesting events exhibiting multiple "repeats" in which the magnification rises above and dips below 1.34 several times. Finally, the binarity of lenses impacted both the durations of the events and the maximum magnifications. This work was supported in part by the SAO intern program (NSF grant AST-9731923) and NASA contracts NAS8-39073 and NAS8-38248 (CXC).

Parametric analysis of ATM solar array.

NASA Technical Reports Server (NTRS)

Singh, B. K.; Adkisson, W. B.

1973-01-01

The paper discusses the methods used for the calculation of ATM solar array performance characteristics and provides the parametric analysis of solar panels used in SKYLAB. To predict the solar array performance under conditions other than test conditions, a mathematical model has been developed. Four computer programs have been used to convert the solar simulator test data to the parametric curves. The first performs module summations, the second determines average solar cell characteristics which will cause a mathematical model to generate a curve matching the test data, the third is a polynomial fit program which determines the polynomial equations for the solar cell characteristics versus temperature, and the fourth program uses the polynomial coefficients generated by the polynomial curve fit program to generate the parametric data.

Enhancements of Bayesian Blocks; Application to Large Light Curve Databases

NASA Technical Reports Server (NTRS)

Scargle, Jeff

2015-01-01

Bayesian Blocks are optimal piecewise linear representations (step function fits) of light-curves. The simple algorithm implementing this idea, using dynamic programming, has been extended to include more data modes and fitness metrics, multivariate analysis, and data on the circle (Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations, Scargle, Norris, Jackson and Chiang 2013, ApJ, 764, 167), as well as new results on background subtraction and refinement of the procedure for precise timing of transient events in sparse data. Example demonstrations will include exploratory analysis of the Kepler light curve archive in a search for "star-tickling" signals from extraterrestrial civilizations. (The Cepheid Galactic Internet, Learned, Kudritzki, Pakvasa1, and Zee, 2008, arXiv: 0809.0339; Walkowicz et al., in progress).

Spiral Galaxy Central Bulge Tangential Speed of Revolution Curves

NASA Astrophysics Data System (ADS)

Taff, Laurence

2013-03-01

The objective was to, for the first time in a century, scientifically analyze the ``rotation curves'' (sic) of the central bulges of scores of spiral galaxies. I commenced with a methodological, rational, geometrical, arithmetic, and statistical examination--none of them carried through before--of the radial velocity data. The requirement for such a thorough treatment is the paucity of data typically available for the central bulge: fewer than 10 observations and frequently only five. The most must be made of these. A consequence of this logical handling is the discovery of a unique model for the central bulge volume mass density resting on the positive slope, linear, rise of its tangential speed of revolution curve and hence--for the first time--a reliable mass estimate. The deduction comes from a known physics-based, mathematically valid, derivation (not assertion). It rests on the full (not partial) equations of motion plus Poisson's equation. Following that is a prediction for the gravitational potential energy and thence the gravitational force. From this comes a forecast for the tangential speed of revolution curve. It was analyzed in a fashion identical to that of the data thereby closing the circle and demonstrating internal self-consistency. This is a hallmark of a scientific method-informed approach to an experimental problem. Multiple plots of the relevant quantities and measures of goodness of fit will be shown. Astronomy related

Function approximation and documentation of sampling data using artificial neural networks.

PubMed

Zhang, Wenjun; Barrion, Albert

2006-11-01

Biodiversity studies in ecology often begin with the fitting and documentation of sampling data. This study is conducted to make function approximation on sampling data and to document the sampling information using artificial neural network algorithms, based on the invertebrate data sampled in the irrigated rice field. Three types of sampling data, i.e., the curve species richness vs. the sample size, the curve rarefaction, and the curve mean abundance of newly sampled species vs.the sample size, are fitted and documented using BP (Backpropagation) network and RBF (Radial Basis Function) network. As the comparisons, The Arrhenius model, and rarefaction model, and power function are tested for their ability to fit these data. The results show that the BP network and RBF network fit the data better than these models with smaller errors. BP network and RBF network can fit non-linear functions (sampling data) with specified accuracy and don't require mathematical assumptions. In addition to the interpolation, BP network is used to extrapolate the functions and the asymptote of the sampling data can be drawn. BP network cost a longer time to train the network and the results are always less stable compared to the RBF network. RBF network require more neurons to fit functions and generally it may not be used to extrapolate the functions. The mathematical function for sampling data can be exactly fitted using artificial neural network algorithms by adjusting the desired accuracy and maximum iterations. The total numbers of functional species of invertebrates in the tropical irrigated rice field are extrapolated as 140 to 149 using trained BP network, which are similar to the observed richness.

Temporal binning of time-correlated single photon counting data improves exponential decay fits and imaging speed

PubMed Central

Walsh, Alex J.; Sharick, Joe T.; Skala, Melissa C.; Beier, Hope T.

2016-01-01

Time-correlated single photon counting (TCSPC) enables acquisition of fluorescence lifetime decays with high temporal resolution within the fluorescence decay. However, many thousands of photons per pixel are required for accurate lifetime decay curve representation, instrument response deconvolution, and lifetime estimation, particularly for two-component lifetimes. TCSPC imaging speed is inherently limited due to the single photon per laser pulse nature and low fluorescence event efficiencies (<10%) required to reduce bias towards short lifetimes. Here, simulated fluorescence lifetime decays are analyzed by SPCImage and SLIM Curve software to determine the limiting lifetime parameters and photon requirements of fluorescence lifetime decays that can be accurately fit. Data analysis techniques to improve fitting accuracy for low photon count data were evaluated. Temporal binning of the decays from 256 time bins to 42 time bins significantly (p<0.0001) improved fit accuracy in SPCImage and enabled accurate fits with low photon counts (as low as 700 photons/decay), a 6-fold reduction in required photons and therefore improvement in imaging speed. Additionally, reducing the number of free parameters in the fitting algorithm by fixing the lifetimes to known values significantly reduced the lifetime component error from 27.3% to 3.2% in SPCImage (p<0.0001) and from 50.6% to 4.2% in SLIM Curve (p<0.0001). Analysis of nicotinamide adenine dinucleotide–lactate dehydrogenase (NADH-LDH) solutions confirmed temporal binning of TCSPC data and a reduced number of free parameters improves exponential decay fit accuracy in SPCImage. Altogether, temporal binning (in SPCImage) and reduced free parameters are data analysis techniques that enable accurate lifetime estimation from low photon count data and enable TCSPC imaging speeds up to 6x and 300x faster, respectively, than traditional TCSPC analysis. PMID:27446663

[Fitting Monocurve and Bicurve (Soper-McGuire design) rigid gas-permeable contact lenses in keratoconus patients: a prospective randomized comparative clinical trial].

PubMed

Coral-Ghanem, Cleusa; Alves, Milton Ruiz

2008-01-01

To evaluate the clinical performance of Monocurve and Bicurve (Soper-McGuire design) rigid gas-permeable contact lens fitting in patients with keratoconus. A prospective and randomized comparative clinical trial was conducted with a minimum follow-up of six months in two groups of 63 patients. One group was fitted with Monocurve contact lenses and the other with Bicurve Soper-McGuire design. Study variables included fluoresceinic pattern of lens-to-cornea fitting relationship, location and morphology of the cone, presence and degree of punctate keratitis and other corneal surface alterations, topographic changes, visual acuity for distance corrected with contact lenses and survival analysis for remaining with the same contact lens design during the study. During the follow-up there was a decrease in the number of eyes with advanced and central cones fitted with Monocurve lenses, and an increase in those fitted with Soper-McGuire design. In the Monocurve group, a flattening of both the steepest and the flattest keratometric curve was observed. In the Soper-McGuire group, a steepening of the flattest keratometric curve and a flattening of the steepest keratometric curve were observed. There was a decrease in best-corrected visual acuity with contact lens in the Monocurve group. Survival analysis for the Monocurve lens was 60.32% and for the Soper-McGuire was 71.43% at a mean follow-up of six months. This study showed that due to the changes observed in corneal topography, the same contact lens design did not provide an ideal fitting for all patients during the follow-up period. The Soper-McGuire lenses had a better performance than the Monocurve lenses in advanced and central keratoconus.

Design data for radars based on 13.9 GHz Skylab scattering coefficient measurements

NASA Technical Reports Server (NTRS)

Moore, R. K. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Measurements made at 13.9 GHz with the radar scatterometer on Skylab have been combined to produce median curves of the variation of scattering coefficient with angle of incidence out to 45 deg. Because of the large number of observations, and the large area averaged for each measured data point, these curves may be used as a new design base for radars. A reasonably good fit at larger angles is obtained using the theoretical expression based on an exponential height correlation function and also using Lambert's law. For angles under 10 deg, a different fit based on the exponential correlation function, and a fit based on geometric optics expressions are both reasonably valid.

Foveal Curvature and Asymmetry Assessed Using Optical Coherence Tomography.

PubMed

VanNasdale, Dean A; Eilerman, Amanda; Zimmerman, Aaron; Lai, Nicky; Ramsey, Keith; Sinnott, Loraine T

2017-06-01

The aims of this study were to use cross-sectional optical coherence tomography imaging and custom curve fitting software to evaluate and model the foveal curvature as a spherical surface and to compare the radius of curvature in the horizontal and vertical meridians and test the sensitivity of this technique to anticipated meridional differences. Six 30-degree foveal-centered radial optical coherence tomography cross-section scans were acquired in the right eye of 20 clinically normal subjects. Cross sections were manually segmented, and custom curve fitting software was used to determine foveal pit radius of curvature using the central 500, 1000, and 1500 μm of the foveal contour. Radius of curvature was compared across different fitting distances. Root mean square error was used to determine goodness of fit. The radius of curvature was compared between the horizontal and vertical meridians for each fitting distance. There radius of curvature was significantly different when comparing each of the three fitting distances (P < .01 for each comparison). The average radii of curvature were 970 μm (95% confidence interval [CI], 913 to 1028 μm), 1386 μm (95% CI, 1339 to 1439 μm), and 2121 μm (95% CI, 2066 to 2183) for the 500-, 1000-, and 1500-μm fitting distances, respectively. Root mean square error was also significantly different when comparing each fitting distance (P < .01 for each comparison). The average root mean square errors were 2.48 μm (95% CI, 2.41 to 2.53 μm), 6.22 μm (95% CI, 5.77 to 6.60 μm), and 13.82 μm (95% CI, 12.93 to 14.58 μm) for the 500-, 1000-, and 1500-μm fitting distances, respectively. The radius of curvature between the horizontal and vertical meridian radii was statistically different only in the 1000- and 1500-μm fitting distances (P < .01 for each), with the horizontal meridian being flatter than the vertical. The foveal contour can be modeled as a sphere with low curve fitting error over a limited distance and capable of detecting subtle foveal contour differences between meridians.

Coherent states, quantum gravity, and the Born-Oppenheimer approximation. I. General considerations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stottmeister, Alexander, E-mail: alexander.stottmeister@gravity.fau.de; Thiemann, Thomas, E-mail: thomas.thiemann@gravity.fau.de

2016-06-15

This article, as the first of three, aims at establishing the (time-dependent) Born-Oppenheimer approximation, in the sense of space adiabatic perturbation theory, for quantum systems constructed by techniques of the loop quantum gravity framework, especially the canonical formulation of the latter. The analysis presented here fits into a rather general framework and offers a solution to the problem of applying the usual Born-Oppenheimer ansatz for molecular (or structurally analogous) systems to more general quantum systems (e.g., spin-orbit models) by means of space adiabatic perturbation theory. The proposed solution is applied to a simple, finite dimensional model of interacting spin systems,more » which serves as a non-trivial, minimal model of the aforesaid problem. Furthermore, it is explained how the content of this article and its companion affect the possible extraction of quantum field theory on curved spacetime from loop quantum gravity (including matter fields).« less

Capacitive touch sensing : signal and image processing algorithms

NASA Astrophysics Data System (ADS)

Baharav, Zachi; Kakarala, Ramakrishna

2011-03-01

Capacitive touch sensors have been in use for many years, and recently gained center stage with the ubiquitous use in smart-phones. In this work we will analyze the most common method of projected capacitive sensing, that of absolute capacitive sensing, together with the most common sensing pattern, that of diamond-shaped sensors. After a brief introduction to the problem, and the reasons behind its popularity, we will formulate the problem as a reconstruction from projections. We derive analytic solutions for two simple cases: circular finger on a wire grid, and square finger on a square grid. The solutions give insight into the ambiguities of finding finger location from sensor readings. The main contribution of our paper is the discussion of interpolation algorithms including simple linear interpolation , curve fitting (parabolic and Gaussian), filtering, general look-up-table, and combinations thereof. We conclude with observations on the limits of the present algorithmic methods, and point to possible future research.

AUC-Maximizing Ensembles through Metalearning.

PubMed

LeDell, Erin; van der Laan, Mark J; Petersen, Maya

2016-05-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.

AUC-Maximizing Ensembles through Metalearning

PubMed Central

LeDell, Erin; van der Laan, Mark J.; Peterson, Maya

2016-01-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree. PMID:27227721

Comparative testing of dark matter models with 15 HSB and 15 LSB galaxies

NASA Astrophysics Data System (ADS)

Kun, E.; Keresztes, Z.; Simkó, A.; Szűcs, G.; Gergely, L. Á.

2017-12-01

Context. We assemble a database of 15 high surface brightness (HSB) and 15 low surface brightness (LSB) galaxies, for which surface brightness density and spectroscopic rotation curve data are both available and representative for various morphologies. We use this dataset to test the Navarro-Frenk-White, the Einasto, and the pseudo-isothermal sphere dark matter models. Aims: We investigate the compatibility of the pure baryonic model and baryonic plus one of the three dark matter models with observations on the assembled galaxy database. When a dark matter component improves the fit with the spectroscopic rotational curve, we rank the models according to the goodness of fit to the datasets. Methods: We constructed the spatial luminosity density of the baryonic component based on the surface brightness profile of the galaxies. We estimated the mass-to-light (M/L) ratio of the stellar component through a previously proposed color-mass-to-light ratio relation (CMLR), which yields stellar masses independent of the photometric band. We assumed an axissymetric baryonic mass model with variable axis ratios together with one of the three dark matter models to provide the theoretical rotational velocity curves, and we compared them with the dataset. In a second attempt, we addressed the question whether the dark component could be replaced by a pure baryonic model with fitted M/L ratios, varied over ranges consistent with CMLR relations derived from the available stellar population models. We employed the Akaike information criterion to establish the performance of the best-fit models. Results: For 7 galaxies (2 HSB and 5 LSB), neither model fits the dataset within the 1σ confidence level. For the other 23 cases, one of the models with dark matter explains the rotation curve data best. According to the Akaike information criterion, the pseudo-isothermal sphere emerges as most favored in 14 cases, followed by the Navarro-Frenk-White (6 cases) and the Einasto (3 cases) dark matter models. We find that the pure baryonic model with fitted M/L ratios falls within the 1σ confidence level for 10 HSB and 2 LSB galaxies, at the price of growing the M/Ls on average by a factor of two, but the fits are inferior compared to the best-fitting dark matter model.

AstroImageJ: Image Processing and Photometric Extraction for Ultra-precise Astronomical Light Curves

NASA Astrophysics Data System (ADS)

Collins, Karen A.; Kielkopf, John F.; Stassun, Keivan G.; Hessman, Frederic V.

2017-02-01

ImageJ is a graphical user interface (GUI) driven, public domain, Java-based, software package for general image processing traditionally used mainly in life sciences fields. The image processing capabilities of ImageJ are useful and extendable to other scientific fields. Here we present AstroImageJ (AIJ), which provides an astronomy specific image display environment and tools for astronomy specific image calibration and data reduction. Although AIJ maintains the general purpose image processing capabilities of ImageJ, AIJ is streamlined for time-series differential photometry, light curve detrending and fitting, and light curve plotting, especially for applications requiring ultra-precise light curves (e.g., exoplanet transits). AIJ reads and writes standard Flexible Image Transport System (FITS) files, as well as other common image formats, provides FITS header viewing and editing, and is World Coordinate System aware, including an automated interface to the astrometry.net web portal for plate solving images. AIJ provides research grade image calibration and analysis tools with a GUI driven approach, and easily installed cross-platform compatibility. It enables new users, even at the level of undergraduate student, high school student, or amateur astronomer, to quickly start processing, modeling, and plotting astronomical image data with one tightly integrated software package.

Photometric Supernova Classification with Machine Learning

NASA Astrophysics Data System (ADS)

Lochner, Michelle; McEwen, Jason D.; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K.

2016-08-01

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k-nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

Multi-Filter Photometric Analysis of Three β Lyrae-type Eclipsing Binary Stars

NASA Astrophysics Data System (ADS)

Gardner, T.; Hahs, G.; Gokhale, V.

2015-12-01

We present light curve analysis of three variable stars, ASAS J105855+1722.2, NSVS 5066754, and NSVS 9091101. These objects are selected from a list of β- Lyrae candidates published by Hoffman et al. (2008). Light curves are generated using data collected at the the 31-inch NURO telescope at the Lowell Observatory in Flagstaff, Arizona in three filters: Bessell B, V, and R. Additional observations were made using the 14-inch Meade telescope at the Truman State Observatory in Kirksville, Missouri using Baader R, G, and B filters. In this paper, we present the light curves for these three objects and generate a truncated eight-term Fourier fit to these light curves. We use the Fourier coefficients from this fit to confirm ASAS J105855+1722.2 and NSVS 5066754 as β Lyrae type systems, and NSVS 9091101 to possibly be a RR Lyrae-type system. We measure the O'Connell effect observed in two of these systems (ASAS J105855+1722.2 and NSVS 5066754), and quantify this effect by calculating the "Light Curve Asymmetry" (LCA) and the "O'Connell Effect Ratio" (OER).

The potential of artificial aging for modelling of natural aging processes of ballpoint ink.

PubMed

Weyermann, Céline; Spengler, Bernhard

2008-08-25

Artificial aging has been used to reproduce natural aging processes in an accelerated pace. Questioned documents were exposed to light or high temperature in a well-defined manner in order to simulate an increased age. This may be used to study the aging processes or to date documents by reproducing their aging curve. Ink was studied especially because it is deposited on the paper when a document, such as a contract, is produced. Once on the paper, aging processes start through degradation of dyes, solvents drying and resins polymerisation. Modelling of dye's and solvent's aging was attempted. These processes, however, follow complex pathways, influenced by many factors which can be classified as three major groups: ink composition, paper type and storage conditions. The influence of these factors is such that different aging states can be obtained for an identical point in time. Storage conditions in particular are difficult to simulate, as they are dependent on environmental conditions (e.g. intensity and dose of light, temperature, air flow, humidity) and cannot be controlled in the natural aging of questioned documents. The problem therefore lies more in the variety of different conditions a questioned document might be exposed to during its natural aging, rather than in the simulation of such conditions in the laboratory. Nevertheless, a precise modelling of natural aging curves based on artificial aging curves is obtained when performed on the same paper and ink. A standard model for aging processes of ink on paper is therefore presented that is based on a fit of aging curves to a power law of solvent concentrations as a function of time. A mathematical transformation of artificial aging curves into modelled natural aging curves results in excellent overlap with data from real natural aging processes.

Flow curve analysis of a Pickering emulsion-polymerized PEDOT:PSS/PS-based electrorheological fluid

NASA Astrophysics Data System (ADS)

Kim, So Hee; Choi, Hyoung Jin; Leong, Yee-Kwong

2017-11-01

The steady shear electrorheological (ER) response of poly(3, 4-ethylenedioxythiophene): poly(styrene sulfonate)/polystyrene (PEDOT:PSS/PS) composite particles, which were initially fabricated from Pickering emulsion polymerization, was tested with a 10 vol% ER fluid dispersed in a silicone oil. The model independent shear rate and yield stress obtained from the raw torque-rotational speed data using a Couette type rotational rheometer under an applied electric field strength were then analyzed by Tikhonov regularization, which is the most suitable technique for solving an ill-posed inverse problem. The shear stress-shear rate data also fitted well with the data extracted from the Bingham fluid model.

The Real Problem with MOND

NASA Astrophysics Data System (ADS)

Dodelson, Scott

Gravitational potentials in the cosmos are deeper than expected from observed visible objects, a phenomenon usually attributed to dark matter, presumably in the form of a new fundamental particle. Until such a particle is observed, the jury remains out on dark matter, and modified gravity models must be considered. The class of models reducing to modified Newtonian dynamics (MOND) in the weak field limit does an excellent job fitting the rotation curves of galaxies, predicting the relation between baryonic mass and velocity in gas-dominated galaxies, and explaining the properties of the local group. Several of the initial challenges facing MOND have been overcome, while others remain. Here we point out the most severe challenge facing MOND.

Anthropometric data error detecting and correction with a computer

NASA Technical Reports Server (NTRS)

Chesak, D. D.

1981-01-01

Data obtained with automated anthropometric data aquisition equipment was examined for short term errors. The least squares curve fitting technique was used to ascertain which data values were erroneous and to replace them, if possible, with corrected values. Errors were due to random reflections of light, masking of the light rays, and other types of optical and electrical interference. It was found that the signals were impossible to eliminate from the initial data produced by the television cameras, and that this was primarily a software problem requiring a digital computer to refine the data off line. The specific data of interest was related to the arm reach envelope of a human being.

Possible Transit Timing Variations of the TrES-3 Planetary System

NASA Astrophysics Data System (ADS)

Jiang, Ing-Guey; Yeh, Li-Chin; Thakur, Parijat; Wu, Yu-Ting; Chien, Ping; Lin, Yi-Ling; Chen, Hong-Yu; Hu, Juei-Hwa; Sun, Zhao; Ji, Jianghui

2013-03-01

Five newly observed transit light curves of the TrES-3 planetary system are presented. Together with other light-curve data from the literature, 23 transit light curves in total, which cover an overall timescale of 911 epochs, have been analyzed through a standard procedure. From these observational data, the system's orbital parameters are determined and possible transit timing variations (TTVs) are investigated. Given that a null TTV produces a fit with reduced χ2 = 1.52, our results agree with previous work, that TTVs might not exist in these data. However, a one-frequency oscillating TTV model, giving a fit with a reduced χ2 = 0.93, does possess a statistically higher probability. It is thus concluded that future observations and dynamical simulations for this planetary system will be very important.

Evaluation of the swelling behaviour of iota-carrageenan in monolithic matrix tablets.

PubMed

Kelemen, András; Buchholcz, Gyula; Sovány, Tamás; Pintye-Hódi, Klára

2015-08-10

The swelling properties of monolithic matrix tablets containing iota-carrageenan were studied at different pH values, with measurements of the swelling force and characterization of the profile of the swelling curve. The swelling force meter was linked to a PC by an RS232 cable and the measured data were evaluated with self-developed software. The monitor displayed the swelling force vs. time curve with the important parameters, which could be fitted with an Analysis menu. In the case of iota-carrageenan matrix tablets, it was concluded that the pH and the pressure did not influence the swelling process, and the first section of the swelling curve could be fitted by the Korsmeyer-Peppas equation. Copyright © 2015 Elsevier B.V. All rights reserved.

Application of the method of temporal moments to interpret solute transport with sorption and degradation

NASA Astrophysics Data System (ADS)

Pang, Liping; Goltz, Mark; Close, Murray

2003-01-01

In this note, we applied the temporal moment solutions of [Das and Kluitenberg, 1996. Soil Sci. Am. J. 60, 1724] for one-dimensional advective-dispersive solute transport with linear equilibrium sorption and first-order degradation for time pulse sources to analyse soil column experimental data. Unlike most other moment solutions, these solutions consider the interplay of degradation and sorption. This permits estimation of a first-order degradation rate constant using the zeroth moment of column breakthrough data, as well as estimation of the retardation factor or sorption distribution coefficient of a degrading solute using the first moment. The method of temporal moment (MOM) formulae was applied to analyse breakthrough data from a laboratory column study of atrazine, hexazinone and rhodamine WT transport in volcanic pumice sand, as well as experimental data from the literature. Transport and degradation parameters obtained using the MOM were compared to parameters obtained by fitting breakthrough data from an advective-dispersive transport model with equilibrium sorption and first-order degradation, using the nonlinear least-square curve-fitting program CXTFIT. The results derived from using the literature data were also compared with estimates reported in the literature using different equilibrium models. The good agreement suggests that the MOM could provide an additional useful means of parameter estimation for transport involving equilibrium sorption and first-order degradation. We found that the MOM fitted breakthrough curves with tailing better than curve fitting. However, the MOM analysis requires complete breakthrough curves and relatively frequent data collection to ensure the accuracy of the moments obtained from the breakthrough data.

Fitting the post-keratoplasty cornea with hydrogel lenses.

PubMed

Katsoulos, Costas; Nick, Vasileiou; Lefteris, Karageorgiadis; Theodore, Mousafeiropoulos

2009-02-01

We report two cases who have undergone penetrating keratoplasty (three eyes total), and who were fitted with hydrogel lenses. In the first case, a 28-year-old male presented with an interest in contact lens fitting. He had undergone corneal transplantation in both eyes, about 5 years ago. After topographies and trial fitting were performed, it was decided to be fitted with reverse geometry hydrogel lenses, due to the globular geometry of the cornea, the resultant instability of RGPs, and personal preference. In the second case, a 26-year-old female who had also penetrating keratoplasty was fitted with a hydrogel toric lens of high cylinder in the right eye. The final hydrogel lenses for the first subject incorporated a custom tricurve design, in which the second curve was steeper than the base curve and the third curve flatter than the second but still steeper than the first. Visual acuity was 6/7.5 RE and a mediocre 6/15 LE (OU 6/7.5). The second subject achieved 6/4.5 acuity RE with the high cylinder hydrogel toric lens. In corneas exhibiting extreme protrusion, such as keratoglobus and some cases after penetrating keratoplasty, curvatures are so extreme and the cornea so globular leading to specific fitting options: sclerals, small diameter RGPs and reverse geometry hydrogel lenses, in order to improve lens and optical stability. In selected cases such as the above, large diameter inverse geometry RGP may be fitted only if the eyelid shape and tension permits so. The first case demonstrates that the option of hydrogel lenses is viable when the patient has no interest in RGPs and in certain cases can improve vision to satisfactory levels. In other cases, graft toricity might be so high that the practitioner will need to employ hydrogel torics with large amounts of cylinder in order to correct vision. In such cases, the patient should be closely monitored in order to avoid complications from hypoxia.

Testing feedback-modified dark matter haloes with galaxy rotation curves: estimation of halo parameters and consistency with ΛCDM scaling relations

NASA Astrophysics Data System (ADS)

Katz, Harley; Lelli, Federico; McGaugh, Stacy S.; Di Cintio, Arianna; Brook, Chris B.; Schombert, James M.

2017-04-01

Cosmological N-body simulations predict dark matter (DM) haloes with steep central cusps (e.g. NFW). This contradicts observations of gas kinematics in low-mass galaxies that imply the existence of shallow DM cores. Baryonic processes such as adiabatic contraction and gas outflows can, in principle, alter the initial DM density profile, yet their relative contributions to the halo transformation remain uncertain. Recent high-resolution, cosmological hydrodynamic simulations by Di Cintio et al. (DC14) predict that inner density profiles depend systematically on the ratio of stellar-to-DM mass (M*/Mhalo). Using a Markov Chain Monte Carlo approach, we test the NFW and the M*/Mhalo-dependent DC14 halo models against a sample of 147 galaxy rotation curves from the new Spitzer Photometry and Accurate Rotation Curves data set. These galaxies all have extended H I rotation curves from radio interferometry as well as accurate stellar-mass-density profiles from near-infrared photometry. The DC14 halo profile provides markedly better fits to the data compared to the NFW profile. Unlike NFW, the DC14 halo parameters found in our rotation-curve fits naturally fall within two standard deviations of the mass-concentration relation predicted by Λ cold dark matter (ΛCDM) and the stellar mass-halo mass relation inferred from abundance matching with few outliers. Halo profiles modified by baryonic processes are therefore more consistent with expectations from ΛCDM cosmology and provide better fits to galaxy rotation curves across a wide range of galaxy properties than do halo models that neglect baryonic physics. Our results offer a solution to the decade long cusp-core discrepancy.

The Type Ia Supernova Color-Magnitude Relation and Host Galaxy Dust: A Simple Hierarchical Bayesian Model

NASA Astrophysics Data System (ADS)

Mandel, Kaisey S.; Scolnic, Daniel M.; Shariff, Hikmatali; Foley, Ryan J.; Kirshner, Robert P.

2017-06-01

Conventional Type Ia supernova (SN Ia) cosmology analyses currently use a simplistic linear regression of magnitude versus color and light curve shape, which does not model intrinsic SN Ia variations and host galaxy dust as physically distinct effects, resulting in low color-magnitude slopes. We construct a probabilistic generative model for the dusty distribution of extinguished absolute magnitudes and apparent colors as the convolution of an intrinsic SN Ia color-magnitude distribution and a host galaxy dust reddening-extinction distribution. If the intrinsic color-magnitude (M B versus B - V) slope {β }{int} differs from the host galaxy dust law R B , this convolution results in a specific curve of mean extinguished absolute magnitude versus apparent color. The derivative of this curve smoothly transitions from {β }{int} in the blue tail to R B in the red tail of the apparent color distribution. The conventional linear fit approximates this effective curve near the average apparent color, resulting in an apparent slope {β }{app} between {β }{int} and R B . We incorporate these effects into a hierarchical Bayesian statistical model for SN Ia light curve measurements, and analyze a data set of SALT2 optical light curve fits of 248 nearby SNe Ia at z< 0.10. The conventional linear fit gives {β }{app}≈ 3. Our model finds {β }{int}=2.3+/- 0.3 and a distinct dust law of {R}B=3.8+/- 0.3, consistent with the average for Milky Way dust, while correcting a systematic distance bias of ˜0.10 mag in the tails of the apparent color distribution. Finally, we extend our model to examine the SN Ia luminosity-host mass dependence in terms of intrinsic and dust components.

Peripheral absolute threshold spectral sensitivity in retinitis pigmentosa.

PubMed Central

Massof, R W; Johnson, M A; Finkelstein, D

1981-01-01

Dark-adapted spectral sensitivities were measured in the peripheral retinas of 38 patients diagnosed as having typical retinitis pigmentosa (RP) and in 3 normal volunteers. The patients included those having autosomal dominant and autosomal recessive inheritance patterns. Results were analysed by comparisons with the CIE standard scotopic spectral visibility function and with Judd's modification of the photopic spectral visibility function, with consideration of contributions from changes in spectral transmission of preretinal media. The data show 3 general patterns. One group of patients had absolute threshold spectral sensitivities that were fit by Judd's photopic visibility curve. Absolute threshold spectral sensitivities for a second group of patients were fit by a normal scotopic spectral visibility curve. The third group of patients had absolute threshold spectral sensitivities that were fit by a combination of scotopic and photopic spectral visibility curves. The autosomal dominant and autosomal recessive modes of inheritance were represented in each group of patients. These data indicate that RP patients have normal rod and/or cone spectral sensitivities, and support the subclassification of patients described previously by Massof and Finkelstein. PMID:7459312

Aleatory Uncertainty and Scale Effects in Computational Damage Models for Failure and Fragmentation

DTIC Science & Technology

2014-09-01

larger specimens, small specimens have, on average, higher strengths. Equivalently, because curves for small specimens fall below those of larger...the material strength associated with each realization parameter R in Equation (7), and strength distribution curves associated with multiple...effects in brittle media [58], which applies micromorphological dimensional analysis to obtain a universal curve which closely fits rate-dependent

Proceedings of the Annual Symposium on Frequency Control (39th) Held in Philadelphia, Pennsylvania on 29-31 May 1985

DTIC Science & Technology

1985-05-01

distribution, was evaluation of phase shift through best fit of assumed to be the beam response to the microwave theoretical curves and experimental...vibration sidebands o Acceleration as shown in the lower calculated curve . o High-Temperature Exposure o Thermal Vacuum Two of the curves show actual phase ...conclude that the method to measure the phase noise with spectrum estimation is workable, and it has no principle limitation. From the curve it has been

Least Squares Procedures.

ERIC Educational Resources Information Center

Hester, Yvette

Least squares methods are sophisticated mathematical curve fitting procedures used in all classical parametric methods. The linear least squares approximation is most often associated with finding the "line of best fit" or the regression line. Since all statistical analyses are correlational and all classical parametric methods are least…

Analysis of variation in calibration curves for Kodak XV radiographic film using model-based parameters.

PubMed

Hsu, Shu-Hui; Kulasekere, Ravi; Roberson, Peter L

2010-08-05

Film calibration is time-consuming work when dose accuracy is essential while working in a range of photon scatter environments. This study uses the single-target single-hit model of film response to fit the calibration curves as a function of calibration method, processor condition, field size and depth. Kodak XV film was irradiated perpendicular to the beam axis in a solid water phantom. Standard calibration films (one dose point per film) were irradiated at 90 cm source-to-surface distance (SSD) for various doses (16-128 cGy), depths (0.2, 0.5, 1.5, 5, 10 cm) and field sizes (5 × 5, 10 × 10 and 20 × 20 cm²). The 8-field calibration method (eight dose points per film) was used as a reference for each experiment, taken at 95 cm SSD and 5 cm depth. The delivered doses were measured using an Attix parallel plate chamber for improved accuracy of dose estimation in the buildup region. Three fitting methods with one to three dose points per calibration curve were investigated for the field sizes of 5 × 5, 10 × 10 and 20 × 20 cm². The inter-day variation of model parameters (background, saturation and slope) were 1.8%, 5.7%, and 7.7% (1 σ) using the 8-field method. The saturation parameter ratio of standard to 8-field curves was 1.083 ± 0.005. The slope parameter ratio of standard to 8-field curves ranged from 0.99 to 1.05, depending on field size and depth. The slope parameter ratio decreases with increasing depth below 0.5 cm for the three field sizes. It increases with increasing depths above 0.5 cm. A calibration curve with one to three dose points fitted with the model is possible with 2% accuracy in film dosimetry for various irradiation conditions. The proposed fitting methods may reduce workload while providing energy dependence correction in radiographic film dosimetry. This study is limited to radiographic XV film with a Lumisys scanner.

SU-F-T-104: Determining the NTCP Parameters of Pharyngeal Constrictors and Proximal Esophagus for Radiation Induced Swallowing Problems Recorded Six Months After Radiation Therapy for Head and Neck Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavroidis, P; Price, A; Kostich, M

Purpose: To estimate the radiobiological parameters of four NTCP models that describe the dose-response relations of pharyngeal constrictors and proximal esophagus regarding the severity of patient reported swallowing problems 6 months post chemo-radiotherapy. To identify the section/structure that best correlates with the manifestation of the clinical endpoints. Finally, to compare the goodness-of-fit of those models. Methods: Forty-three patients were treated on a prospective multi-institutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric datamore » of superior, medium and inferior sections of pharyngeal constrictors (SPC, MPC and IPC), superior and inferior sections of esophagus (SES and IES) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patient data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the SPC for Grade ≥ 2 (0.719 for the RS and RL models, and 0.716 for LKB and Logit). For Grade ≥ 1, the respective values were 0.699 for RS, LKB and Logit and 0.676 for RL. For MPC the AUC values varied between 0.463–0.477, for IPC between 0.396–0.458, for SES between 0.556–0.613 and for IES between 0.410–0.519. The Odds Ratio for the SPC was 15.6 (1.7–146.4) for RS, LKB and Logit for NTCP of 55%. Conclusion: All the examined NTCP models could fit the clinical data with similar accuracy. The SPC appear to correlate best with the clinical endpoints of swallowing problems. A prospective study could establish the use of NTCP values of SPC as a constraint in treatment planning.« less

Quantity of Candida Colonies in Saliva: 
A Diagnostic Evaluation for Oral Candidiasis.

PubMed

Zhou, Pei Ru; Hua, Hong; Liu, Xiao Song

To investigate the relationship between the quantity of Candida colonies in saliva and oral candidiasis (OC), as well as to identify the threshold for distinguishing oral candidiasis from healthy carriage. A diagnostic test was conducted in 197 patients with different oral problems. The diagnosis of OC was established based on clinical features. Whole saliva samples from the subjects were cultured for Candida species. Receiver operating characteristic (ROC) curve analysis was used in this study. OC patients had significantly more Candida colony-forming units per millilitre saliva (795 cfu/ml) than asymptomatic carriers (40 cfu/ml; P < 0.05). Among different types of candidiasis, the quantity of Candida colonies differed. The number of Candida colonies in pseudomembranous type was significantly higher than that in the erythematous type (P < 0.05). Candida albicans was the predominant species of Candida. The cut-off point with the best fit for OC diagnosis was calculated to be 266 cfu/ml. The sensitivity and specificity were 0.720 and 0.825, respectively. Analysis of the ROC curve indicated that Candida colonies had a high diagnostic value for OC, as demonstrated by the area under the curve (AUC = 0.873). Based on this study, the value of 270 cfu/ml was considered a threshold for distinguishing OC from carriage.

The effect of dimethylsulfoxide on the water transport response of rat hepatocytes during freezing.

PubMed

Smith, D J; Schulte, M; Bischof, J C

1998-10-01

Successful improvement of cryopreservation protocols for cells in suspension requires knowledge of how such cells respond to the biophysical stresses of freezing (intracellular ice formation, water transport) while in the presence of a cryoprotective agent (CPA). This work investigates the biophysical water transport response in a clinically important cell type--isolated hepatocytes--during freezing in the presence of dimethylsulfoxide (DMSO). Sprague-Dawley rat liver hepatocytes were frozen in Williams E media supplemented with 0, 1, and 2 M DMSO, at rates of 5, 10, and 50 degrees C/min. The water transport was measured by cell volumetric changes as assessed by cryomicroscopy and image analysis. Assuming that water is the only species transported under these conditions, a water transport model of the form dV/dT = f(Lpg([CPA]), ELp([CPA]), T(t)) was curve-fit to the experimental data to obtain the biophysical parameters of water transport--the reference hydraulic permeability (Lpg) and activation energy of water transport (ELp)--for each DMSO concentration. These parameters were estimated two ways: (1) by curve-fitting the model to the average volume of the pooled cell data, and (2) by curve-fitting individual cell volume data and averaging the resulting parameters. The experimental data showed that less dehydration occurs during freezing at a given rate in the presence of DMSO at temperatures between 0 and -10 degrees C. However, dehydration was able to continue at lower temperatures (< -10 degrees C) in the presence of DMSO. The values of Lpg and ELp obtained using the individual cell volume data both decreased from their non-CPA values--4.33 x 10(-13) m3/N-s (2.69 microns/min-atm) and 317 kJ/mol (75.9 kcal/mol), respectively--to 0.873 x 10(-13) m3/N-s (0.542 micron/min-atm) and 137 kJ/mol (32.8 kcal/mol), respectively, in 1 M DMSO and 0.715 x 10(-13) m3/N-s (0.444 micron/min-atm) and 107 kJ/mol (25.7 kcal/mol), respectively, in 2 M DMSO. The trends in the pooled volume values for Lpg and ELp were very similar, but the overall fit was considered worse than for the individual volume parameters. A unique way of presenting the curve-fitting results supports a clear trend of reduction of both biophysical parameters in the presence of DMSO, and no clear trend in cooling rate dependence of the biophysical parameters. In addition, these results suggest that close proximity of the experimental cell volume data to the equilibrium volume curve may significantly reduce the efficiency of the curve-fitting process.

Visualization and curve-parameter estimation strategies for efficient exploration of phenotype microarray kinetics.

PubMed

Vaas, Lea A I; Sikorski, Johannes; Michael, Victoria; Göker, Markus; Klenk, Hans-Peter

2012-01-01

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves. The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats. We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data.

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

PubMed Central

Vaas, Lea A. I.; Sikorski, Johannes; Michael, Victoria; Göker, Markus; Klenk, Hans-Peter

2012-01-01

Background The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed ‘-omics’ techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves. Methodology The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats. Conclusions We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data. PMID:22536335

Comparison between two scalar field models using rotation curves of spiral galaxies

NASA Astrophysics Data System (ADS)

Fernández-Hernández, Lizbeth M.; Rodríguez-Meza, Mario A.; Matos, Tonatiuh

2018-04-01

Scalar fields have been used as candidates for dark matter in the universe, from axions with masses ∼ 10-5eV until ultra-light scalar fields with masses ∼ Axions behave as cold dark matter while the ultra-light scalar fields galaxies are Bose-Einstein condensate drops. The ultra-light scalar fields are also called scalar field dark matter model. In this work we study rotation curves for low surface brightness spiral galaxies using two scalar field models: the Gross-Pitaevskii Bose-Einstein condensate in the Thomas-Fermi approximation and a scalar field solution of the Klein-Gordon equation. We also used the zero disk approximation galaxy model where photometric data is not considered, only the scalar field dark matter model contribution to rotation curve is taken into account. From the best-fitting analysis of the galaxy catalog we use, we found the range of values of the fitting parameters: the length scale and the central density. The worst fitting results (values of χ red2 much greater than 1, on the average) were for the Thomas-Fermi models, i.e., the scalar field dark matter is better than the Thomas- Fermi approximation model to fit the rotation curves of the analysed galaxies. To complete our analysis we compute from the fitting parameters the mass of the scalar field models and two astrophysical quantities of interest, the dynamical dark matter mass within 300 pc and the characteristic central surface density of the dark matter models. We found that the value of the central mass within 300 pc is in agreement with previous reported results, that this mass is ≈ 107 M ⊙/pc2, independent of the dark matter model. And, on the contrary, the value of the characteristic central surface density do depend on the dark matter model.

Protofit: A program for determining surface protonation constants from titration data

NASA Astrophysics Data System (ADS)

Turner, Benjamin F.; Fein, Jeremy B.

2006-11-01

Determining the surface protonation behavior of natural adsorbents is essential to understand how they interact with their environments. ProtoFit is a tool for analysis of acid-base titration data and optimization of surface protonation models. The program offers a number of useful features including: (1) enables visualization of adsorbent buffering behavior; (2) uses an optimization approach independent of starting titration conditions or initial surface charge; (3) does not require an initial surface charge to be defined or to be treated as an optimizable parameter; (4) includes an error analysis intrinsically as part of the computational methods; and (5) generates simulated titration curves for comparison with observation. ProtoFit will typically be run through ProtoFit-GUI, a graphical user interface providing user-friendly control of model optimization, simulation, and data visualization. ProtoFit calculates an adsorbent proton buffering value as a function of pH from raw titration data (including pH and volume of acid or base added). The data is reduced to a form where the protons required to change the pH of the solution are subtracted out, leaving protons exchanged between solution and surface per unit mass of adsorbent as a function of pH. The buffering intensity function Qads* is calculated as the instantaneous slope of this reduced titration curve. Parameters for a surface complexation model are obtained by minimizing the sum of squares between the modeled (i.e. simulated) buffering intensity curve and the experimental data. The variance in the slope estimate, intrinsically produced as part of the Qads* calculation, can be used to weight the sum of squares calculation between the measured buffering intensity and a simulated curve. Effects of analytical error on data visualization and model optimization are discussed. Examples are provided of using ProtoFit for data visualization, model optimization, and model evaluation.

Impact of fitting algorithms on errors of parameter estimates in dynamic contrast-enhanced MRI

NASA Astrophysics Data System (ADS)

Debus, C.; Floca, R.; Nörenberg, D.; Abdollahi, A.; Ingrisch, M.

2017-12-01

Parameter estimation in dynamic contrast-enhanced MRI (DCE MRI) is usually performed by non-linear least square (NLLS) fitting of a pharmacokinetic model to a measured concentration-time curve. The two-compartment exchange model (2CXM) describes the compartments ‘plasma’ and ‘interstitial volume’ and their exchange in terms of plasma flow and capillary permeability. The model function can be defined by either a system of two coupled differential equations or a closed-form analytical solution. The aim of this study was to compare these two representations in terms of accuracy, robustness and computation speed, depending on parameter combination and temporal sampling. The impact on parameter estimation errors was investigated by fitting the 2CXM to simulated concentration-time curves. Parameter combinations representing five tissue types were used, together with two arterial input functions, a measured and a theoretical population based one, to generate 4D concentration images at three different temporal resolutions. Images were fitted by NLLS techniques, where the sum of squared residuals was calculated by either numeric integration with the Runge-Kutta method or convolution. Furthermore two example cases, a prostate carcinoma and a glioblastoma multiforme patient, were analyzed in order to investigate the validity of our findings in real patient data. The convolution approach yields improved results in precision and robustness of determined parameters. Precision and stability are limited in curves with low blood flow. The model parameter ve shows great instability and little reliability in all cases. Decreased temporal resolution results in significant errors for the differential equation approach in several curve types. The convolution excelled in computational speed by three orders of magnitude. Uncertainties in parameter estimation at low temporal resolution cannot be compensated by usage of the differential equations. Fitting with the convolution approach is superior in computational time, with better stability and accuracy at the same time.

Maximum safe speed estimation using planar quintic Bezier curve with C2 continuity

NASA Astrophysics Data System (ADS)

Ibrahim, Mohamad Fakharuddin; Misro, Md Yushalify; Ramli, Ahmad; Ali, Jamaludin Md

2017-08-01

This paper describes an alternative way in estimating design speed or the maximum speed allowed for a vehicle to drive safely on a road using curvature information from Bezier curve fitting on a map. We had tested on some route in Tun Sardon Road, Balik Pulau, Penang, Malaysia. We had proposed to use piecewise planar quintic Bezier curve while satisfying the curvature continuity between joined curves in the process of mapping the road. By finding the derivatives of quintic Bezier curve, the value of curvature was calculated and design speed was derived. In this paper, a higher order of Bezier Curve had been used. A higher degree of curve will give more freedom for users to control the shape of the curve compared to curve in lower degree.

Craniofacial Reconstruction Using Rational Cubic Ball Curves

PubMed Central

Majeed, Abdul; Mt Piah, Abd Rahni; Gobithaasan, R. U.; Yahya, Zainor Ridzuan

2015-01-01

This paper proposes the reconstruction of craniofacial fracture using rational cubic Ball curve. The idea of choosing Ball curve is based on its robustness of computing efficiency over Bezier curve. The main steps are conversion of Digital Imaging and Communications in Medicine (Dicom) images to binary images, boundary extraction and corner point detection, Ball curve fitting with genetic algorithm and final solution conversion to Dicom format. The last section illustrates a real case of craniofacial reconstruction using the proposed method which clearly indicates the applicability of this method. A Graphical User Interface (GUI) has also been developed for practical application. PMID:25880632

Effect of boundary representation on viscous, separated flows in a discontinuous-Galerkin Navier-Stokes solver

NASA Astrophysics Data System (ADS)

Nelson, Daniel A.; Jacobs, Gustaaf B.; Kopriva, David A.

2016-08-01

The effect of curved-boundary representation on the physics of the separated flow over a NACA 65(1)-412 airfoil is thoroughly investigated. A method is presented to approximate curved boundaries with a high-order discontinuous-Galerkin spectral element method for the solution of the Navier-Stokes equations. Multiblock quadrilateral element meshes are constructed with the grid generation software GridPro. The boundary of a NACA 65(1)-412 airfoil, defined by a cubic natural spline, is piecewise-approximated by isoparametric polynomial interpolants that represent the edges of boundary-fitted elements. Direct numerical simulation of the airfoil is performed on a coarse mesh and fine mesh with polynomial orders ranging from four to twelve. The accuracy of the curve fitting is investigated by comparing the flows computed on curved-sided meshes with those given by straight-sided meshes. Straight-sided meshes yield irregular wakes, whereas curved-sided meshes produce a regular Karman street wake. Straight-sided meshes also produce lower lift and higher viscous drag as compared with curved-sided meshes. When the mesh is refined by reducing the sizes of the elements, the lift decrease and viscous drag increase are less pronounced. The differences in the aerodynamic performance between the straight-sided meshes and the curved-sided meshes are concluded to be the result of artificial surface roughness introduced by the piecewise-linear boundary approximation provided by the straight-sided meshes.

Early-Time Observations of the GRB 050319 Optical Transient

NASA Astrophysics Data System (ADS)

Quimby, R. M.; Rykoff, E. S.; Yost, S. A.; Aharonian, F.; Akerlof, C. W.; Alatalo, K.; Ashley, M. C. B.; Göǧüş, E.; Güver, T.; Horns, D.; Kehoe, R. L.; Kιzιloǧlu, Ü.; Mckay, T. A.; Özel, M.; Phillips, A.; Schaefer, B. E.; Smith, D. A.; Swan, H. F.; Vestrand, W. T.; Wheeler, J. C.; Wren, J.

2006-03-01

We present the unfiltered ROTSE-III light curve of the optical transient associated with GRB 050319 beginning 4 s after the cessation of γ-ray activity. We fit a power-law function to the data using the revised trigger time given by Chincarini and coworkers, and a smoothly broken power-law to the data using the original trigger disseminated through the GCN notices. Including the RAPTOR data from Woźniak and coworkers, the best-fit power-law indices are α=-0.854+/-0.014 for the single power-law and α1=-0.364+0.020-0.019, α2=-0.881+0.030-0.031, with a break at tb=418+31-30 s for the smoothly broken fit. We discuss the fit results, with emphasis placed on the importance of knowing the true start time of the optical transient for this multipeaked burst. As Swift continues to provide prompt GRB locations, it becomes more important to answer the question, ``when does the afterglow begin?'' in order to correctly interpret the light curves.

Investigation of the Failure Modes in a Metal Matrix Composite under Thermal Cycling

DTIC Science & Technology

1989-12-01

Material Characteristics. . .......... ... 76 Sectioning and SEN Photograp’... . ........ . 86 Residual Stress Analysis using .TCAN ... ....... 99 i VI...Specimen Fitted with Strain Gages ..... ........... 77 39. Modulus and Poisson’s Ratio versus Thermal Cycles . . 79 1 40 Stress /Strain Curve for Uncycled...Specimen .... ......... 82 1 41. Stress /Strain Curve for Specimen 8 (5250 Cycles) ..... .83 42. Comparison of Uncycled to Cycled Stress /Strain Curves

SU-F-BRD-16: Relative Biological Effectiveness of Double-Strand Break Induction for Modeling Cell Survival in Pristine Proton Beams of Different Dose-Averaged Linear Energy Transfers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peeler, C; Bronk, L; UT Graduate School of Biomedical Sciences at Houston, Houston, TX

2015-06-15

Purpose: High throughput in vitro experiments assessing cell survival following proton radiation indicate that both the alpha and the beta parameters of the linear quadratic model increase with increasing proton linear energy transfer (LET). We investigated the relative biological effectiveness (RBE) of double-strand break (DSB) induction as a means of explaining the experimental results. Methods: Experiments were performed with two lung cancer cell lines and a range of proton LET values (0.94 – 19.4 keV/µm) using an experimental apparatus designed to irradiate cells in a 96 well plate such that each column encounters protons of different dose-averaged LET (LETd). Traditionalmore » linear quadratic survival curve fitting was performed, and alpha, beta, and RBE values obtained. Survival curves were also fit with a model incorporating RBE of DSB induction as the sole fit parameter. Fitted values of the RBE of DSB induction were then compared to values obtained using Monte Carlo Damage Simulation (MCDS) software and energy spectra calculated with Geant4. Other parameters including alpha, beta, and number of DSBs were compared to those obtained from traditional fitting. Results: Survival curve fitting with RBE of DSB induction yielded alpha and beta parameters that increase with proton LETd, which follows from the standard method of fitting; however, relying on a single fit parameter provided more consistent trends. The fitted values of RBE of DSB induction increased beyond what is predicted from MCDS data above proton LETd of approximately 10 keV/µm. Conclusion: In order to accurately model in vitro proton irradiation experiments performed with high throughput methods, the RBE of DSB induction must increase more rapidly than predicted by MCDS above LETd of 10 keV/µm. This can be explained by considering the increased complexity of DSBs or the nature of intra-track pairwise DSB interactions in this range of LETd values. NIH Grant 2U19CA021239-35.« less

Rotation curve for the Milky Way galaxy in conformal gravity

NASA Astrophysics Data System (ADS)

O'Brien, James G.; Moss, Robert J.

2015-05-01

Galactic rotation curves have proven to be the testing ground for dark matter bounds in galaxies, and our own Milky Way is one of many large spiral galaxies that must follow the same models. Over the last decade, the rotation of the Milky Way galaxy has been studied and extended by many authors. Since the work of conformal gravity has now successfully fit the rotation curves of almost 140 galaxies, we present here the fit to our own Milky Way. However, the Milky Way is not just an ordinary galaxy to append to our list, but instead provides a robust test of a fundamental difference of conformal gravity rotation curves versus standard cold dark matter models. It was shown by Mannheim and O'Brien that in conformal gravity, the presence of a quadratic potential causes the rotation curve to eventually fall off after its flat portion. This effect can currently be seen in only a select few galaxies whose rotation curve is studied well beyond a few multiples of the optical galactic scale length. Due to the recent work of Sofue et al and Kundu et al, the rotation curve of the Milky Way has now been studied to a degree where we can test the predicted fall off in the conformal gravity rotation curve. We find that - like the other galaxies already studied in conformal gravity - we obtain amazing agreement with rotational data and the prediction includes the eventual fall off at large distances from the galactic center.

Radio emission of SN1993J: the complete picture. II. Simultaneous fit of expansion and radio light curves

NASA Astrophysics Data System (ADS)

Martí-Vidal, I.; Marcaide, J. M.; Alberdi, A.; Guirado, J. C.; Pérez-Torres, M. A.; Ros, E.

2011-02-01

We report on a simultaneous modelling of the expansion and radio light curves of the supernova SN1993J. We developed a simulation code capable of generating synthetic expansion and radio light curves of supernovae by taking into consideration the evolution of the expanding shock, magnetic fields, and relativistic electrons, as well as the finite sensitivity of the interferometric arrays used in the observations. Our software successfully fits all the available radio data of SN 1993J with a standard emission model for supernovae, which is extended with some physical considerations, such as an evolution in the opacity of the ejecta material, a radial decline in the magnetic fields within the radiating region, and a changing radial density profile for the circumstellar medium starting from day 3100 after the explosion.

POSSIBLE TRANSIT TIMING VARIATIONS OF THE TrES-3 PLANETARY SYSTEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Ing-Guey; Wu, Yu-Ting; Chien, Ping

2013-03-15

Five newly observed transit light curves of the TrES-3 planetary system are presented. Together with other light-curve data from the literature, 23 transit light curves in total, which cover an overall timescale of 911 epochs, have been analyzed through a standard procedure. From these observational data, the system's orbital parameters are determined and possible transit timing variations (TTVs) are investigated. Given that a null TTV produces a fit with reduced {chi}{sup 2} = 1.52, our results agree with previous work, that TTVs might not exist in these data. However, a one-frequency oscillating TTV model, giving a fit with a reducedmore » {chi}{sup 2} = 0.93, does possess a statistically higher probability. It is thus concluded that future observations and dynamical simulations for this planetary system will be very important.« less

PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lochner, Michelle; Peiris, Hiranya V.; Lahav, Ofer

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models tomore » curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k -nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.« less

Radial dependence of the dark matter distribution in M33

NASA Astrophysics Data System (ADS)

López Fune, E.; Salucci, P.; Corbelli, E.

2017-06-01

The stellar and gaseous mass distributions, as well as the extended rotation curve, in the nearby galaxy M33 are used to derive the radial distribution of dark matter density in the halo and to test cosmological models of galaxy formation and evolution. Two methods are examined to constrain the dark mass density profiles. The first method deals directly with fitting the rotation curve data in the range of galactocentric distances 0.24 ≤ r ≤ 22.72 kpc. Using the results of collisionless Λ cold dark matter numerical simulations, we confirm that the Navarro-Frenkel-White (NFW) dark matter profile provides a better fit to the rotation curve data than the cored Burkert profile (BRK) profile. The second method relies on the local equation of centrifugal equilibrium and on the rotation curve slope. In the aforementioned range of distances, we fit the observed velocity profile, using a function that has a rational dependence on the radius, and we derive the slope of the rotation curve. Then, we infer the effective matter densities. In the radial range 9.53 ≤ r ≤ 22.72 kpc, the uncertainties induced by the luminous matter (stars and gas) become negligible, because the dark matter density dominates, and we can determine locally the radial distribution of dark matter. With this second method, we tested the NFW and BRK dark matter profiles and we can confirm that both profiles are compatible with the data, even though in this case the cored BRK density profile provides a more reasonable value for the baryonic-to-dark matter ratio.

Data Validation in the Kepler Science Operations Center Pipeline

NASA Technical Reports Server (NTRS)

Wu, Hayley; Twicken, Joseph D.; Tenenbaum, Peter; Clarke, Bruce D.; Li, Jie; Quintana, Elisa V.; Allen, Christopher; Chandrasekaran, Hema; Jenkins, Jon M.; Caldwell, Douglas A.;

The mass of the black hole in 1A 0620-00, revisiting the ellipsoidal light curve modelling

NASA Astrophysics Data System (ADS)

van Grunsven, Theo F. J.; Jonker, Peter G.; Verbunt, Frank W. M.; Robinson, Edward L.

2017-12-01

The mass distribution of stellar-mass black holes can provide important clues to supernova modelling, but observationally it is still ill constrained. Therefore, it is of importance to make black hole mass measurements as accurate as possible. The X-ray transient 1A 0620-00 is well studied, with a published black hole mass of 6.61 ± 0.25 M⊙, based on an orbital inclination i of 51.0° ± 0.9°. This was obtained by Cantrell et al. (2010) as an average of independent fits to V-, I- and H-band light curves. In this work, we perform an independent check on the value of i by re-analysing existing YALO/SMARTS V-, I- and H-band photometry, using different modelling software and fitting strategy. Performing a fit to the three light curves simultaneously, we obtain a value for i of 54.1° ± 1.1°, resulting in a black hole mass of 5.86 ± 0.24 M⊙. Applying the same model to the light curves individually, we obtain 58.2° ± 1.9°, 53.6° ± 1.6° and 50.5° ± 2.2° for V-, I- and H-band, respectively, where the differences in best-fitting i are caused by the contribution of the residual accretion disc light in the three different bands. We conclude that the mass determination of this black hole may still be subject to systematic effects exceeding the statistical uncertainty. Obtaining more accurate masses would be greatly helped by continuous phase-resolved spectroscopic observations simultaneous with photometry.

Predicting Numbers of Problems in Development of Software

NASA Technical Reports Server (NTRS)

Simonds, Charles H.

2005-01-01

A method has been formulated to enable prediction of the amount of work that remains to be performed in developing flight software for a spacecraft. The basic concept embodied in the method is that of using an idealized curve (specifically, the Weibull function) to interpolate from (1) the numbers of problems discovered thus far to (2) a goal of discovering no new problems after launch (or six months into the future for software already in use in orbit). The steps of the method can be summarized as follows: 1. Take raw data in the form of problem reports (PRs), including the dates on which they are generated. 2. Remove, from the data collection, PRs that are subsequently withdrawn or to which no response is required. 3. Count the numbers of PRs created in 1-week periods and the running total number of PRs each week. 4. Perform the interpolation by making a least-squares fit of the Weibull function to (a) the cumulative distribution of PRs gathered thus far and (b) the goal of no more PRs after the currently anticipated launch date. The interpolation and the anticipated launch date are subject to iterative re-estimation.

GURU v2.0: An interactive Graphical User interface to fit rheometer curves in Han's model for rubber vulcanization

NASA Astrophysics Data System (ADS)

Milani, G.; Milani, F.

A GUI software (GURU) for experimental data fitting of rheometer curves in Natural Rubber (NR) vulcanized with sulphur at different curing temperatures is presented. Experimental data are automatically loaded in GURU from an Excel spreadsheet coming from the output of the experimental machine (moving die rheometer). To fit the experimental data, the general reaction scheme proposed by Han and co-workers for NR vulcanized with sulphur is considered. From the simplified kinetic scheme adopted, a closed form solution can be found for the crosslink density, with the only limitation that the induction period is excluded from computations. Three kinetic constants must be determined in such a way to minimize the absolute error between normalized experimental data and numerical prediction. Usually, this result is achieved by means of standard least-squares data fitting. On the contrary, GURU works interactively by means of a Graphical User Interface (GUI) to minimize the error and allows an interactive calibration of the kinetic constants by means of sliders. A simple mouse click on the sliders allows the assignment of a value for each kinetic constant and a visual comparison between numerical and experimental curves. Users will thus find optimal values of the constants by means of a classic trial and error strategy. An experimental case of technical relevance is shown as benchmark.

Applying a Hypoxia-Incorporating TCP Model to Experimental Data on Rat Sarcoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruggieri, Ruggero, E-mail: ruggieri.ruggero@gmail.com; Stavreva, Nadejda; Naccarato, Stefania

2012-08-01

Purpose: To verify whether a tumor control probability (TCP) model which mechanistically incorporates acute and chronic hypoxia is able to describe animal in vivo dose-response data, exhibiting tumor reoxygenation. Methods and Materials: The investigated TCP model accounts for tumor repopulation, reoxygenation of chronic hypoxia, and fluctuating oxygenation of acute hypoxia. Using the maximum likelihood method, the model is fitted to Fischer-Moulder data on Wag/Rij rats, inoculated with rat rhabdomyosarcoma BA1112, and irradiated in vivo using different fractionation schemes. This data set is chosen because two of the experimental dose-response curves exhibit an inverse dose behavior, which is interpreted as duemore » to reoxygenation. The tested TCP model is complex, and therefore, in vivo cell survival data on the same BA1112 cell line from Reinhold were added to Fischer-Moulder data and fitted simultaneously with a corresponding cell survival function. Results: The obtained fit to the combined Fischer-Moulder-Reinhold data was statistically acceptable. The best-fit values of the model parameters for which information exists were in the range of published values. The cell survival curves of well-oxygenated and hypoxic cells, computed using the best-fit values of the radiosensitivities and the initial number of clonogens, were in good agreement with the corresponding in vitro and in situ experiments of Reinhold. The best-fit values of most of the hypoxia-related parameters were used to recompute the TCP for non-small cell lung cancer patients as a function of the number of fractions, TCP(n). Conclusions: The investigated TCP model adequately describes animal in vivo data exhibiting tumor reoxygenation. The TCP(n) curve computed for non-small cell lung cancer patients with the best-fit values of most of the hypoxia-related parameters confirms previously obtained abrupt reduction in TCP for n < 10, thus warning against the adoption of severely hypofractionated schedules.« less

Curve Estimation of Number of People Killed in Traffic Accidents in Turkey

NASA Astrophysics Data System (ADS)

Berkhan Akalin, Kadir; Karacasu, Murat; Altin, Arzu Yavuz; Ergül, Bariş

2016-10-01

One or more than one vehicle in motion on the highway involving death, injury and loss events which have resulted are called accidents. As a result of increasing population and traffic density, traffic accidents continue to increase and this leads to both human losses and harm to the economy. In addition, also leads to social problems. As a result of increasing population and traffic density, traffic accidents continue to increase and this leads to both human losses and harm to the economy. In addition to this, it also leads to social problems. As a result of traffic accidents, millions of people die year by year. A great majority of these accidents occur in developing countries. One of the most important tasks of transportation engineers is to reduce traffic accidents by creating a specific system. For that reason, statistical information about traffic accidents which occur in the past years should be organized by versed people. Factors affecting the traffic accidents are analyzed in various ways. In this study, modelling the number of people killed in traffic accidents in Turkey is determined. The dead people were modelled using curve fitting method with the number of people killed in traffic accidents in Turkey dataset between 1990 and 2014. It was also predicted the number of dead people by using various models for the future. It is decided that linear model is suitable for the estimates.

Mathematical and Statistical Software Index.

DTIC Science & Technology

1986-08-01

geometric) mean HMEAN - harmonic mean MEDIAN - median MODE - mode QUANT - quantiles OGIVE - distribution curve IQRNG - interpercentile range RANGE ... range mutliphase pivoting algorithm cross-classification multiple discriminant analysis cross-tabul ation mul tipl e-objecti ve model curve fitting...Statistics). .. .. .... ...... ..... ...... ..... .. 21 *RANGEX (Correct Correlations for Curtailment of Range ). .. .. .... ...... ... 21 *RUMMAGE II (Analysis

A Software Tool for the Rapid Analysis of the Sintering Behavior of Particulate Bodies

DTIC Science & Technology

2017-11-01

bounded by a region that the user selects via cross hairs . Future plot analysis features, such as more complicated curve fitting and modeling functions...German RM. Grain growth behavior of tungsten heavy alloys based on the master sintering curve concept. Metallurgical and Materials Transactions A

COMPARING BEHAVIORAL DOSE-EFFECT CURVES FOR HUMANS AND LABORATORY ANIMALS ACUTELY EXPOSED TO TOLUENE.

EPA Science Inventory

The utility of laboratory animal data in toxicology depends upon the ability to generalize the results quantitatively to humans. To compare the acute behavioral effects of inhaled toluene in humans to those in animals, dose-effect curves were fitted by meta-analysis of published...

Annual variation in the atmospheric radon concentration in Japan.

PubMed

Kobayashi, Yuka; Yasuoka, Yumi; Omori, Yasutaka; Nagahama, Hiroyuki; Sanada, Tetsuya; Muto, Jun; Suzuki, Toshiyuki; Homma, Yoshimi; Ihara, Hayato; Kubota, Kazuhito; Mukai, Takahiro

2015-08-01

Anomalous atmospheric variations in radon related to earthquakes have been observed in hourly exhaust-monitoring data from radioisotope institutes in Japan. The extraction of seismic anomalous radon variations would be greatly aided by understanding the normal pattern of variation in radon concentrations. Using atmospheric daily minimum radon concentration data from five sampling sites, we show that a sinusoidal regression curve can be fitted to the data. In addition, we identify areas where the atmospheric radon variation is significantly affected by the variation in atmospheric turbulence and the onshore-offshore pattern of Asian monsoons. Furthermore, by comparing the sinusoidal regression curve for the normal annual (seasonal) variations at the five sites to the sinusoidal regression curve for a previously published dataset of radon values at the five Japanese prefectures, we can estimate the normal annual variation pattern. By fitting sinusoidal regression curves to the previously published dataset containing sites in all Japanese prefectures, we find that 72% of the Japanese prefectures satisfy the requirements of the sinusoidal regression curve pattern. Using the normal annual variation pattern of atmospheric daily minimum radon concentration data, these prefectures are suitable areas for obtaining anomalous radon variations related to earthquakes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Runoff potentiality of a watershed through SCS and functional data analysis technique.

PubMed

Adham, M I; Shirazi, S M; Othman, F; Rahman, S; Yusop, Z; Ismail, Z

2014-01-01

Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling.

Assessment of Shape Changes of Mistletoe Berries: A New Software Approach to Automatize the Parameterization of Path Curve Shaped Contours

PubMed Central

Derbidge, Renatus; Feiten, Linus; Conradt, Oliver; Heusser, Peter; Baumgartner, Stephan

2013-01-01

Photographs of mistletoe (Viscum album L.) berries taken by a permanently fixed camera during their development in autumn were subjected to an outline shape analysis by fitting path curves using a mathematical algorithm from projective geometry. During growth and maturation processes the shape of mistletoe berries can be described by a set of such path curves, making it possible to extract changes of shape using one parameter called Lambda. Lambda describes the outline shape of a path curve. Here we present methods and software to capture and measure these changes of form over time. The present paper describes the software used to automatize a number of tasks including contour recognition, optimization of fitting the contour via hill-climbing, derivation of the path curves, computation of Lambda and blinding the pictures for the operator. The validity of the program is demonstrated by results from three independent measurements showing circadian rhythm in mistletoe berries. The program is available as open source and will be applied in a project to analyze the chronobiology of shape in mistletoe berries and the buds of their host trees. PMID:23565255

A mathematical function for the description of nutrient-response curve

PubMed Central

Ahmadi, Hamed

2017-01-01

Several mathematical equations have been proposed to modeling nutrient-response curve for animal and human justified on the goodness of fit and/or on the biological mechanism. In this paper, a functional form of a generalized quantitative model based on Rayleigh distribution principle for description of nutrient-response phenomena is derived. The three parameters governing the curve a) has biological interpretation, b) may be used to calculate reliable estimates of nutrient response relationships, and c) provide the basis for deriving relationships between nutrient and physiological responses. The new function was successfully applied to fit the nutritional data obtained from 6 experiments including a wide range of nutrients and responses. An evaluation and comparison were also done based simulated data sets to check the suitability of new model and four-parameter logistic model for describing nutrient responses. This study indicates the usefulness and wide applicability of the new introduced, simple and flexible model when applied as a quantitative approach to characterizing nutrient-response curve. This new mathematical way to describe nutritional-response data, with some useful biological interpretations, has potential to be used as an alternative approach in modeling nutritional responses curve to estimate nutrient efficiency and requirements. PMID:29161271

Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique

PubMed Central

Adham, M. I.; Shirazi, S. M.; Othman, F.; Rahman, S.; Yusop, Z.; Ismail, Z.

2014-01-01

Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling. PMID:25152911

Exploration of Analysis Methods for Diagnostic Imaging Tests: Problems with ROC AUC and Confidence Scores in CT Colonography

PubMed Central

Mallett, Susan; Halligan, Steve; Collins, Gary S.; Altman, Doug G.

2014-01-01

Background Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. Methods In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Results Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. Conclusions The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests. PMID:25353643

Exploration of analysis methods for diagnostic imaging tests: problems with ROC AUC and confidence scores in CT colonography.

PubMed

Mallett, Susan; Halligan, Steve; Collins, Gary S; Altman, Doug G

2014-01-01

Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests.

Can Tooth Preparation Design Affect the Fit of CAD/CAM Restorations?

PubMed

Roperto, Renato Cassio; Oliveira, Marina Piolli; Porto, Thiago Soares; Ferreira, Lais Alaberti; Melo, Lucas Simino; Akkus, Anna

2017-03-01

The purpose of this study was to evaluate if the marginal fit of computer-aided design and computer-aided manufacturing (CAD/CAM) restorations manufactured with CAD/CAM systems can be affected by different tooth preparation designs. Twenty-six typodont (plastic) teeth were divided into two groups (n = 13) according to the occlusal curvature of the tooth preparation. These were the group 1 (control group) (flat occlusal design) and group 2 (curved occlusal design). Scanning of the preparations was performed, and crowns were milled using ceramic blocks. Blocks were cemented using epoxy glue on the pulpal floor only, and finger pressure was applied for 1 minute. On completion of the cementation step, poor fits between the restoration and abutment were measured by microphotography and the silicone replica technique using light-body silicon material on mesial, distal, buccal, and lingual surfaces. Two-way ANOVA analysis did not reveal a statistical difference between flat (83.61 ± 50.72) and curved (79.04 ± 30.97) preparation designs. Buccal, mesial, lingual, and distal sites on the curved design preparation showed less of a gap when compared with flat design. No difference was found on flat preparations among mesial, buccal, and distal sites (P < .05). The lingual aspect had no difference from the distal side but showed a statistically significant difference from mesial and buccal (P < .05). Difference in occlusal design did not significantly impact the marginal fit. Marginal fit was significantly affected by the location of the margin; lingual and distal locations exhibited greater margin gap values compared with buccal and mesial sites regardless of the preparation design.

FracFit: A Robust Parameter Estimation Tool for Anomalous Transport Problems

NASA Astrophysics Data System (ADS)

Kelly, J. F.; Bolster, D.; Meerschaert, M. M.; Drummond, J. D.; Packman, A. I.

2016-12-01

Anomalous transport cannot be adequately described with classical Fickian advection-dispersion equations (ADE). Rather, fractional calculus models may be used, which capture non-Fickian behavior (e.g. skewness and power-law tails). FracFit is a robust parameter estimation tool based on space- and time-fractional models used to model anomalous transport. Currently, four fractional models are supported: 1) space fractional advection-dispersion equation (sFADE), 2) time-fractional dispersion equation with drift (TFDE), 3) fractional mobile-immobile equation (FMIE), and 4) tempered fractional mobile-immobile equation (TFMIE); additional models may be added in the future. Model solutions using pulse initial conditions and continuous injections are evaluated using stable distribution PDFs and CDFs or subordination integrals. Parameter estimates are extracted from measured breakthrough curves (BTCs) using a weighted nonlinear least squares (WNLS) algorithm. Optimal weights for BTCs for pulse initial conditions and continuous injections are presented, facilitating the estimation of power-law tails. Two sample applications are analyzed: 1) continuous injection laboratory experiments using natural organic matter and 2) pulse injection BTCs in the Selke river. Model parameters are compared across models and goodness-of-fit metrics are presented, assisting model evaluation. The sFADE and time-fractional models are compared using space-time duality (Baeumer et. al., 2009), which links the two paradigms.

Robust Spatial Approximation of Laser Scanner Point Clouds by Means of Free-form Curve Approaches in Deformation Analysis

NASA Astrophysics Data System (ADS)

Bureick, Johannes; Alkhatib, Hamza; Neumann, Ingo

2016-03-01

In many geodetic engineering applications it is necessary to solve the problem of describing a measured data point cloud, measured, e. g. by laser scanner, by means of free-form curves or surfaces, e. g., with B-Splines as basis functions. The state of the art approaches to determine B-Splines yields results which are seriously manipulated by the occurrence of data gaps and outliers. Optimal and robust B-Spline fitting depend, however, on optimal selection of the knot vector. Hence we combine in our approach Monte-Carlo methods and the location and curvature of the measured data in order to determine the knot vector of the B-Spline in such a way that no oscillating effects at the edges of data gaps occur. We introduce an optimized approach based on computed weights by means of resampling techniques. In order to minimize the effect of outliers, we apply robust M-estimators for the estimation of control points. The above mentioned approach will be applied to a multi-sensor system based on kinematic terrestrial laserscanning in the field of rail track inspection.

Closed geometric models in medical applications

NASA Astrophysics Data System (ADS)

Jagannathan, Lakshmipathy; Nowinski, Wieslaw L.; Raphel, Jose K.; Nguyen, Bonnie T.

1996-04-01

Conventional surface fitting methods give twisted surfaces and complicates capping closures. This is a typical character of surfaces that lack rectangular topology. We suggest an algorithm which overcomes these limitations. The analysis of the algorithm is presented with experimental results. This algorithm assumes the mass center lying inside the object. Both capping closure and twisting are results of inadequate information on the geometric proximity of the points and surfaces which are proximal in the parametric space. Geometric proximity at the contour level is handled by mapping the points along the contour onto a hyper-spherical space. The resulting angular gradation with respect to the centroid is monotonic and hence avoids the twisting problem. Inter-contour geometric proximity is achieved by partitioning the point set based on the angle it makes with the respective centroids. Avoidance of capping complications is achieved by generating closed cross curves connecting curves which are reflections about the abscissa. The method is of immense use for the generation of the deep cerebral structures and is applied to the deep structures generated from the Schaltenbrand- Wahren brain atlas.

High pressure melting curve of platinum up to 35 GPa

NASA Astrophysics Data System (ADS)

Patel, Nishant N.; Sunder, Meenakshi

2018-04-01

Melting curve of Platinum (Pt) has been measured up to 35 GPa using our laboratory based laser heated diamond anvil cell (LHDAC) facility. Laser speckle method has been employed to detect onset of melting. High pressure melting curve of Pt obtained in the present study has been compared with previously reported experimental and theoretical results. The melting curve measured agrees well within experimental error with the results of Kavner et al. The experimental data fitted with simon equation gives (∂Tm/∂P) ˜25 K/GPa at P˜1 MPa.

Indirect synthesis of multidegree-of-freedom transient systems

NASA Technical Reports Server (NTRS)

Chen, Y. H.; Pilkey, W. D.; Kalinowski, A. J.

1976-01-01

The indirect synthesis method is developed and shown to be capable of leading a near-optimal design of multidegree-of-freedom and multidesign-element transient nonlinear dynamical systems. The basis of the approach is to select the open design parameters such that the response of the portion of the system being designed approximates the limiting performances solution. The limiting performance problem can be formulated as one of linear programming by replacing all portions of the system subject to transient disturbances by control forces and supposing that the remaining portions are linear as are the overall kinematic constraints. One then selects the design parameters that respond most closely to the limiting performance solution, which can be achieved by unconstrained curve-fitting techniques.

[Keratoconus special soft contact lens fitting].

PubMed

Yamazaki, Ester Sakae; da Silva, Vanessa Cristina Batista; Morimitsu, Vagner; Sobrinho, Marcelo; Fukushima, Nelson; Lipener, César

2006-01-01

To evaluate the fitting and use of a soft contact lens in keratoconic patients. Retrospective study on 80 eyes of 66 patients, fitted with a special soft contact lens for keratoconus, at the Contact Lens Section of UNIFESP and private clinics. Keratoconus was classified according to degrees of disease severity by keratometric pattern. Age, gender, diagnosis, keratometry, visual acuity, spherical equivalent (SE), base curve and clinical indication were recorded. Of 66 patients (80 eyes) with keratoconus the mean age was 29 years, 51.5% were men and 48.5% women. According to the groups: 15.0% were incipient, 53.7% moderate, 26.3% advanced and 5.0% were severe. The majority of the eyes of patients using contact lenses (91.25%) achieved visual acuity better than 20/40. To 88 eyes 58% were tihed with lens with spherical power (mean -5.45 diopters) and 41% with spherocylinder power (from -0.5 to -5.00 cylindrical diopters). The most frequent base curve was 7.6 in 61% of the eyes. The main reasons for this special lens fitting were due to reduced tolerance and poor fitting pattern achieved with other lenses. The special soft contact lens is useful in fitting difficult keratoconic patients by offering comfort and improving visual rehabilitation that may allow more patients to postpone the need for corneal transplant.

Why "suboptimal" is optimal: Jensen's inequality and ectotherm thermal preferences.

PubMed

Martin, Tara Laine; Huey, Raymond B

2008-03-01

Body temperature (T(b)) profoundly affects the fitness of ectotherms. Many ectotherms use behavior to control T(b) within narrow levels. These temperatures are assumed to be optimal and therefore to match body temperatures (Trmax) that maximize fitness (r). We develop an optimality model and find that optimal body temperature (T(o)) should not be centered at Trmax but shifted to a lower temperature. This finding seems paradoxical but results from two considerations relating to Jensen's inequality, which deals with how variance and skew influence integrals of nonlinear functions. First, ectotherms are not perfect thermoregulators and so experience a range of T(b). Second, temperature-fitness curves are asymmetric, such that a T(b) higher than Trmax depresses fitness more than will a T(b) displaced an equivalent amount below Trmax. Our model makes several predictions. The magnitude of the optimal shift (Trmax - To) should increase with the degree of asymmetry of temperature-fitness curves and with T(b) variance. Deviations should be relatively large for thermal specialists but insensitive to whether fitness increases with Trmax ("hotter is better"). Asymmetric (left-skewed) T(b) distributions reduce the magnitude of the optimal shift but do not eliminate it. Comparative data (insects, lizards) support key predictions. Thus, "suboptimal" is optimal.

A point cloud modeling method based on geometric constraints mixing the robust least squares method

NASA Astrophysics Data System (ADS)

Yue, JIanping; Pan, Yi; Yue, Shun; Liu, Dapeng; Liu, Bin; Huang, Nan

2016-10-01

The appearance of 3D laser scanning technology has provided a new method for the acquisition of spatial 3D information. It has been widely used in the field of Surveying and Mapping Engineering with the characteristics of automatic and high precision. 3D laser scanning data processing process mainly includes the external laser data acquisition, the internal industry laser data splicing, the late 3D modeling and data integration system. For the point cloud modeling, domestic and foreign researchers have done a lot of research. Surface reconstruction technology mainly include the point shape, the triangle model, the triangle Bezier surface model, the rectangular surface model and so on, and the neural network and the Alfa shape are also used in the curved surface reconstruction. But in these methods, it is often focused on single surface fitting, automatic or manual block fitting, which ignores the model's integrity. It leads to a serious problems in the model after stitching, that is, the surfaces fitting separately is often not satisfied with the well-known geometric constraints, such as parallel, vertical, a fixed angle, or a fixed distance. However, the research on the special modeling theory such as the dimension constraint and the position constraint is not used widely. One of the traditional modeling methods adding geometric constraints is a method combing the penalty function method and the Levenberg-Marquardt algorithm (L-M algorithm), whose stability is pretty good. But in the research process, it is found that the method is greatly influenced by the initial value. In this paper, we propose an improved method of point cloud model taking into account the geometric constraint. We first apply robust least-squares to enhance the initial value's accuracy, and then use penalty function method to transform constrained optimization problems into unconstrained optimization problems, and finally solve the problems using the L-M algorithm. The experimental results show that the internal accuracy is improved, and it is shown that the improved method for point clouds modeling proposed by this paper outperforms the traditional point clouds modeling methods.

Recognizing Physisorption and Chemisorption in Carbon Nanotubes Gas Sensors by Double Exponential Fitting of the Response.

PubMed

Calvi, Andrea; Ferrari, Alberto; Sbuelz, Luca; Goldoni, Andrea; Modesti, Silvio

2016-05-19

Multi-walled carbon nanotubes (CNTs) have been grown in situ on a SiO 2 substrate and used as gas sensors. For this purpose, the voltage response of the CNTs as a function of time has been used to detect H 2 and CO 2 at various concentrations by supplying a constant current to the system. The analysis of both adsorptions and desorptions curves has revealed two different exponential behaviours for each curve. The study of the characteristic times, obtained from the fitting of the data, has allowed us to identify separately chemisorption and physisorption processes on the CNTs.

Micromagnetic measurement for characterization of ferromagnetic materials' microstructural properties

NASA Astrophysics Data System (ADS)

Zhang, Shuo; Shi, Xiaodong; Udpa, Lalita; Deng, Yiming

2018-05-01

Magnetic Barkhausen noise (MBN) is measured in low carbon steels and the relationship between carbon content and parameter extracted from MBN signal has been investigated. The parameter is extracted experimentally by fitting the original profiles with two Gaussian curves. The gap between two peaks (ΔG) of fitted Gaussian curves shows a better linear relationship with carbon contents of samples in the experiment. The result has been validated with simulation by Monte Carlo method. To ensure the sensitivity of measurement, advanced multi-objective optimization algorithm Non-dominant sorting genetic algorithm III (NSGA III) has been used to fulfill the optimization of the magnetic core of sensor.

Financial model calibration using consistency hints.

PubMed

Abu-Mostafa, Y S

2001-01-01

We introduce a technique for forcing the calibration of a financial model to produce valid parameters. The technique is based on learning from hints. It converts simple curve fitting into genuine calibration, where broad conclusions can be inferred from parameter values. The technique augments the error function of curve fitting with consistency hint error functions based on the Kullback-Leibler distance. We introduce an efficient EM-type optimization algorithm tailored to this technique. We also introduce other consistency hints, and balance their weights using canonical errors. We calibrate the correlated multifactor Vasicek model of interest rates, and apply it successfully to Japanese Yen swaps market and US dollar yield market.

The light curve of SN 1987A revisited: constraining production masses of radioactive nuclides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seitenzahl, Ivo R.; Timmes, F. X.; Magkotsios, Georgios, E-mail: ivo.seitenzahl@anu.edu.au

2014-09-01

We revisit the evidence for the contribution of the long-lived radioactive nuclides {sup 44}Ti, {sup 55}Fe, {sup 56}Co, {sup 57}Co, and {sup 60}Co to the UVOIR light curve of SN 1987A. We show that the V-band luminosity constitutes a roughly constant fraction of the bolometric luminosity between 900 and 1900 days, and we obtain an approximate bolometric light curve out to 4334 days by scaling the late time V-band data by a constant factor where no bolometric light curve data is available. Considering the five most relevant decay chains starting at {sup 44}Ti, {sup 55}Co, {sup 56}Ni, {sup 57}Ni, andmore » {sup 60}Co, we perform a least squares fit to the constructed composite bolometric light curve. For the nickel isotopes, we obtain best fit values of M({sup 56}Ni) = (7.1 ± 0.3) × 10{sup –2} M {sub ☉} and M({sup 57}Ni) = (4.1 ± 1.8) × 10{sup –3} M {sub ☉}. Our best fit {sup 44}Ti mass is M({sup 44}Ti) = (0.55 ± 0.17) × 10{sup –4} M {sub ☉}, which is in disagreement with the much higher (3.1 ± 0.8) × 10{sup –4} M {sub ☉} recently derived from INTEGRAL observations. The associated uncertainties far exceed the best fit values for {sup 55}Co and {sup 60}Co and, as a result, we only give upper limits on the production masses of M({sup 55}Co) < 7.2 × 10{sup –3} M {sub ☉} and M({sup 60}Co) < 1.7 × 10{sup –4} M {sub ☉}. Furthermore, we find that the leptonic channels in the decay of {sup 57}Co (internal conversion and Auger electrons) are a significant contribution and constitute up to 15.5% of the total luminosity. Consideration of the kinetic energy of these electrons is essential in lowering our best fit nickel isotope production ratio to [{sup 57}Ni/{sup 56}Ni] = 2.5 ± 1.1, which is still somewhat high but is in agreement with gamma-ray observations and model predictions.« less

Three-dimensional trend mapping from wire-line logs

USGS Publications Warehouse

Doveton, J.H.; Ke-an, Z.

1985-01-01

Mapping of lithofacies and porosities of stratigraphic units is complicated because these properties vary in three dimensions. The method of moments was proposed by Krumbein and Libby (1957) as a technique to aid in resolving this problem. Moments are easily computed from wireline logs and are simple statistics which summarize vertical variation in a log trace. Combinations of moment maps have proved useful in understanding vertical and lateral changes in lithology of sedimentary rock units. Although moments have meaning both as statistical descriptors and as mechanical properties, they also define polynomial curves which approximate lithologic changes as a function of depth. These polynomials can be fitted by least-squares methods, partitioning major trends in rock properties from finescale fluctuations. Analysis of variance yields the degree of fit of any polynomial and measures the proportion of vertical variability expressed by any moment or combination of moments. In addition, polynomial curves can be differentiated to determine depths at which pronounced expressions of facies occur and to determine the locations of boundaries between major lithologic subdivisions. Moments can be estimated at any location in an area by interpolating from log moments at control wells. A matrix algebra operation then converts moment estimates to coefficients of a polynomial function which describes a continuous curve of lithologic variation with depth. If this procedure is applied to a grid of geographic locations, the result is a model of variability in three dimensions. Resolution of the model is determined largely by number of moments used in its generation. The method is illustrated with an analysis of lithofacies in the Simpson Group of south-central Kansas; the three-dimensional model is shown as cross sections and slice maps. In this study, the gamma-ray log is used as a measure of shaliness of the unit. However, the method is general and can be applied, for example, to suites of neutron, density, or sonic logs to produce three-dimensional models of porosity in reservoir rocks. ?? 1985 Plenum Publishing Corporation.

Dynamic Analysis of Recalescence Process and Interface Growth of Eutectic Fe82B17Si1 Alloy

NASA Astrophysics Data System (ADS)

Fan, Y.; Liu, A. M.; Chen, Z.; Li, P. Z.; Zhang, C. H.

2018-03-01

By employing the glass fluxing technique in combination with cyclical superheating, the microstructural evolution of the undercooled Fe82B17Si1 alloy in the obtained undercooling range was studied. With increase in undercooling, a transition of cooling curves was detected from one recalescence to two recalescences, followed by one recalescence. The two types of cooling curves were fitted by the break equation and the Johnson-Mehl-Avrami-Kolmogorov model. Based on the cooling curves at different undercoolings, the recalescence rate was calculated by the multi-logistic growth model and the Boettinger-Coriel-Trivedi model. Both the recalescence features and the interface growth kinetics of the eutectic Fe82B17Si1 alloy were explored. The fitting results that were obtained using TEM (SAED), SEM and XRD were consistent with the changing rule of microstructures. Finally, the relationship between the microstructure and hardness was also investigated.

Multivariate curve resolution-alternating least squares and kinetic modeling applied to near-infrared data from curing reactions of epoxy resins: mechanistic approach and estimation of kinetic rate constants.

PubMed

Garrido, M; Larrechi, M S; Rius, F X

2006-02-01

This study describes the combination of multivariate curve resolution-alternating least squares with a kinetic modeling strategy for obtaining the kinetic rate constants of a curing reaction of epoxy resins. The reaction between phenyl glycidyl ether and aniline is monitored by near-infrared spectroscopy under isothermal conditions for several initial molar ratios of the reagents. The data for all experiments, arranged in a column-wise augmented data matrix, are analyzed using multivariate curve resolution-alternating least squares. The concentration profiles recovered are fitted to a chemical model proposed for the reaction. The selection of the kinetic model is assisted by the information contained in the recovered concentration profiles. The nonlinear fitting provides the kinetic rate constants. The optimized rate constants are in agreement with values reported in the literature.

Nonlinear model identification and spectral submanifolds for multi-degree-of-freedom mechanical vibrations

NASA Astrophysics Data System (ADS)

Szalai, Robert; Ehrhardt, David; Haller, George

2017-06-01

In a nonlinear oscillatory system, spectral submanifolds (SSMs) are the smoothest invariant manifolds tangent to linear modal subspaces of an equilibrium. Amplitude-frequency plots of the dynamics on SSMs provide the classic backbone curves sought in experimental nonlinear model identification. We develop here, a methodology to compute analytically both the shape of SSMs and their corresponding backbone curves from a data-assimilating model fitted to experimental vibration signals. This model identification utilizes Taken's delay-embedding theorem, as well as a least square fit to the Taylor expansion of the sampling map associated with that embedding. The SSMs are then constructed for the sampling map using the parametrization method for invariant manifolds, which assumes that the manifold is an embedding of, rather than a graph over, a spectral subspace. Using examples of both synthetic and real experimental data, we demonstrate that this approach reproduces backbone curves with high accuracy.

ROC analysis of diagnostic performance in liver scintigraphy.

PubMed

Fritz, S L; Preston, D F; Gallagher, J H

1981-02-01

Studies on the accuracy of liver scintigraphy for the detection of metastases were assembled from 38 sources in the medical literature. An ROC curve was fitted to the observed values of sensitivity and specificity using an algorithm developed by Ogilvie and Creelman. This ROC curve fitted the data better than average sensitivity and specificity values in each of four subsets of the data. For the subset dealing with Tc-99m sulfur colloid scintigraphy, performed for detection of suspected metastases and containing data on 2800 scans from 17 independent series, it was not possible to reject the hypothesis that interobserver variation was entirely due to the use of different decision thresholds by the reporting clinicians. Thus the ROC curve obtained is a reasonable baseline estimate of the performance potentially achievable in today's clinical setting. Comparison of new reports with these data is possible, but is limited by the small sample sizes in most reported series.

A quantitative analysis of the effects of 2,3-diphosphoglycerate, adenosine triphosphate and inositol hexaphosphate on the oxygen dissociation curve of human haemoglobin.

PubMed Central

Goodford, P J; St-Louis, J; Wootton, R

1978-01-01

1. Oxygen dissociation curves have been measured for human haemoglobin solutions with different concentrations of the allosteric effectors 2,3-diphosphoglycerate, adenosine triphosphate and inositol hexaphosphate. 2. Each effector produces a concentration dependent right shift of the oxygen dissociation curve, but a point is reached where the shift is maximal and increasing the effector concentration has no further effect. 3. Mathematical models based on the Monod, Wyman & Changeux (1965) treatment of allosteric proteins have been fitted to the data. For each compound the simple two-state model and its extension to take account of subunit inequivalence were shown to be inadequate, and a better fit was obtained by allowing the effector to lower the oxygen affinity of the deoxy conformational state as well as binding preferentially to this conformation. PMID:722582

The Current Often Implemented Fitness Tests in Physical Education Programs: Problems and Future Directions

ERIC Educational Resources Information Center

Keating, Xiaofen Deng

2003-01-01

This paper aims to examine current nationwide youth fitness test programs, address problems embedded in the programs, and possible solutions. The current Fitnessgram, President's Challenge, and YMCA youth fitness test programs were selected to represent nationwide youth fitness test programs. Sponsors of the nationwide youth fitness test programs…

General circular velocity relation of a test particle in a 3D gravitational potential: application to the rotation curves analysis and total mass determination of UGC 8490 and UGC 9753

NASA Astrophysics Data System (ADS)

Repetto, P.; Martínez-García, E. E.; Rosado, M.; Gabbasov, R.

2018-06-01

In this paper, we derive a novel circular velocity relation for a test particle in a 3D gravitational potential applicable to every system of curvilinear coordinates, suitable to be reduced to orthogonal form. As an illustration of the potentiality of the determined circular velocity expression, we perform the rotation curves analysis of UGC 8490 and UGC 9753 and we estimate the total and dark matter mass of these two galaxies under the assumption that their respective dark matter haloes have spherical, prolate, and oblate spheroidal mass distributions. We employ stellar population synthesis models and the total H I density map to obtain the stellar and H I+He+metals rotation curves of both galaxies. The subtraction of the stellar plus gas rotation curves from the observed rotation curves of UGC 8490 and UGC 9753 generates the dark matter circular velocity curves of both galaxies. We fit the dark matter rotation curves of UGC 8490 and UGC 9753 through the newly established circular velocity formula specialized to the spherical, prolate, and oblate spheroidal mass distributions, considering the Navarro, Frenk, and White, Burkert, Di Cintio, Einasto, and Stadel dark matter haloes. Our principal findings are the following: globally, cored dark matter profiles Burkert and Einasto prevail over cuspy Navarro, Frenk, and White, and Di Cintio. Also, spherical/oblate dark matter models fit better the dark matter rotation curves of both galaxies than prolate dark matter haloes.

Interpolation and Polynomial Curve Fitting

ERIC Educational Resources Information Center

Yang, Yajun; Gordon, Sheldon P.

2014-01-01

Two points determine a line. Three noncollinear points determine a quadratic function. Four points that do not lie on a lower-degree polynomial curve determine a cubic function. In general, n + 1 points uniquely determine a polynomial of degree n, presuming that they do not fall onto a polynomial of lower degree. The process of finding such a…

Bayesian Analysis of Longitudinal Data Using Growth Curve Models

ERIC Educational Resources Information Center

Zhang, Zhiyong; Hamagami, Fumiaki; Wang, Lijuan Lijuan; Nesselroade, John R.; Grimm, Kevin J.

2007-01-01

Bayesian methods for analyzing longitudinal data in social and behavioral research are recommended for their ability to incorporate prior information in estimating simple and complex models. We first summarize the basics of Bayesian methods before presenting an empirical example in which we fit a latent basis growth curve model to achievement data…

Item Response Theory with Estimation of the Latent Density Using Davidian Curves

ERIC Educational Resources Information Center

Woods, Carol M.; Lin, Nan

2009-01-01

Davidian-curve item response theory (DC-IRT) is introduced, evaluated with simulations, and illustrated using data from the Schedule for Nonadaptive and Adaptive Personality Entitlement scale. DC-IRT is a method for fitting unidimensional IRT models with maximum marginal likelihood estimation, in which the latent density is estimated,…

Catmull-Rom Curve Fitting and Interpolation Equations

ERIC Educational Resources Information Center

Jerome, Lawrence

2010-01-01

Computer graphics and animation experts have been using the Catmull-Rom smooth curve interpolation equations since 1974, but the vector and matrix equations can be derived and simplified using basic algebra, resulting in a simple set of linear equations with constant coefficients. A variety of uses of Catmull-Rom interpolation are demonstrated,…

Educating about Sustainability while Enhancing Calculus

ERIC Educational Resources Information Center

Pfaff, Thomas J.

2011-01-01

We give an overview of why it is important to include sustainability in mathematics classes and provide specific examples of how to do this for a calculus class. We illustrate that when students use "Excel" to fit curves to real data, fundamentally important questions about sustainability become calculus questions about those curves. (Contains 5…

On the mass of the compact object in the black hole binary A0620-00

NASA Technical Reports Server (NTRS)

Haswell, Carole A.; Robinson, Edward L.; Horne, Keith; Stiening, Rae F.; Abbott, Timothy M. C.

1993-01-01

Multicolor orbital light curves of the black hole candidate binary A0620-00 are presented. The light curves exhibit ellipsoidal variations and a grazing eclipse of the mass donor companion star by the accretion disk. Synthetic light curves were generated using realistic mass donor star fluxes and an isothermal blackbody disk. For mass ratios of q = M sub 1/M sub 2 = 5.0, 10.6, and 15.0 systematic searches were executed in parameter space for synthetic light curves that fit the observations. For each mass ratio, acceptable fits were found only for a small range of orbital inclinations. It is argued that the mass ratio is unlikely to exceed q = 10.6, and an upper limit of 0.8 solar masses is placed on the mass of the companion star. These constraints imply 4.16 +/- 0.1 to 5.55 +/- 0.15 solar masses. The lower limit on M sub 1 is more than 4-sigma above the mass of a maximally rotating neutron star, and constitutes further strong evidence in favor of a black hole primary in this system.

Comparison of three methods for wind turbine capacity factor estimation.

PubMed

Ditkovich, Y; Kuperman, A

2014-01-01

Three approaches to calculating capacity factor of fixed speed wind turbines are reviewed and compared using a case study. The first "quasiexact" approach utilizes discrete wind raw data (in the histogram form) and manufacturer-provided turbine power curve (also in discrete form) to numerically calculate the capacity factor. On the other hand, the second "analytic" approach employs a continuous probability distribution function, fitted to the wind data as well as continuous turbine power curve, resulting from double polynomial fitting of manufacturer-provided power curve data. The latter approach, while being an approximation, can be solved analytically thus providing a valuable insight into aspects, affecting the capacity factor. Moreover, several other merits of wind turbine performance may be derived based on the analytical approach. The third "approximate" approach, valid in case of Rayleigh winds only, employs a nonlinear approximation of the capacity factor versus average wind speed curve, only requiring rated power and rotor diameter of the turbine. It is shown that the results obtained by employing the three approaches are very close, enforcing the validity of the analytically derived approximations, which may be used for wind turbine performance evaluation.

Inverse Diffusion Curves Using Shape Optimization.

PubMed

Zhao, Shuang; Durand, Fredo; Zheng, Changxi

2018-07-01

The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color fields via a partial differential equation (PDE). We introduce a new approach complementary to previous methods by optimizing curve geometry. In particular, we propose a novel iterative algorithm based on the theory of shape derivatives. The resulting diffusion curves are clean and well-shaped, and the final image closely approximates the input. Our method provides a user-controlled parameter to regularize curve complexity, and generalizes to handle input color fields represented in a variety of formats.

Measurement and fitting techniques for the assessment of material nonlinearity using nonlinear Rayleigh waves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Torello, David; Kim, Jin-Yeon; Qu, Jianmin

2015-03-31

This research considers the effects of diffraction, attenuation, and the nonlinearity of generating sources on measurements of nonlinear ultrasonic Rayleigh wave propagation. A new theoretical framework for correcting measurements made with air-coupled and contact piezoelectric receivers for the aforementioned effects is provided based on analytical models and experimental considerations. A method for extracting the nonlinearity parameter β{sub 11} is proposed based on a nonlinear least squares curve-fitting algorithm that is tailored for Rayleigh wave measurements. Quantitative experiments are conducted to confirm the predictions for the nonlinearity of the piezoelectric source and to demonstrate the effectiveness of the curve-fitting procedure. Thesemore » experiments are conducted on aluminum 2024 and 7075 specimens and a β{sub 11}{sup 7075}/β{sub 11}{sup 2024} measure of 1.363 agrees well with previous literature and earlier work.« less

Scaling laws for light-weight optics

NASA Technical Reports Server (NTRS)

Valente, Tina M.

1990-01-01

Scaling laws for light-weight optical systems are examined. A cubic relationship between mirror diameter and weight has been suggested and used by many designers of optical systems as the best description for all light-weight mirrors. A survey of existing light-weight systems in the open literature has been made to clarify this issue. Fifty existing optical systems were surveyed with all varieties of light-weight mirrors including glass and beryllium structured mirrors, contoured mirrors, and very thin solid mirrors. These mirrors were then categorized and weight to diameter ratio was plotted to find a best fit curve for each case. A best fitting curve program tests nineteen different equations and ranks a 'goodness of fit' for each of these equations. The resulting relationship found for each light-weight mirror category helps to quantify light-weight optical systems and methods of fabrication and provides comparisons between mirror types.

The effect of an offset polar cap dipolar magnetic field on the modeling of the Vela pulsar’s γ-ray light curves

PubMed Central

Barnard, M.; Venter, C.; Harding, A. K.

2018-01-01

We performed geometric pulsar light curve modeling using static, retarded vacuum, and offset polar cap (PC) dipole B-fields (the latter is characterized by a parameter ε), in conjunction with standard two-pole caustic (TPC) and outer gap (OG) emission geometries. The offset-PC dipole B-field mimics deviations from the static dipole (which corresponds to ε = 0). In addition to constant-emissivity geometric models, we also considered a slot gap (SG) E-field associated with the offset-PC dipole B-field and found that its inclusion leads to qualitatively different light curves. Solving the particle transport equation shows that the particle energy only becomes large enough to yield significant curvature radiation at large altitudes above the stellar surface, given this relatively low E-field. Therefore, particles do not always attain the radiation-reaction limit. Our overall optimal light curve fit is for the retarded vacuum dipole field and OG model, at an inclination angle α=78−1+1° and observer angle ζ=69−1+2°. For this B-field, the TPC model is statistically disfavored compared to the OG model. For the static dipole field, neither model is significantly preferred. We found that smaller values of ε are favored for the offset-PC dipole field when assuming constant emissivity, and larger ε values favored for variable emissivity, but not significantly so. When multiplying the SG E-field by a factor of 100, we found improved light curve fits, with α and ζ being closer to best fits from independent studies, as well as curvature radiation reaction at lower altitudes. PMID:29681648

Fatigue loading and R-curve behavior of a dental glass-ceramic with multiple flaw distributions.

PubMed

Joshi, Gaurav V; Duan, Yuanyuan; Della Bona, Alvaro; Hill, Thomas J; St John, Kenneth; Griggs, Jason A

2013-11-01

To determine the effects of surface finish and mechanical loading on the rising toughness curve (R-curve) behavior of a fluorapatite glass-ceramic (IPS e.max ZirPress) and to determine a statistical model for fitting fatigue lifetime data with multiple flaw distributions. Rectangular beam specimens were fabricated by pressing. Two groups of specimens (n=30) with polished (15 μm) or air abraded surface were tested under rapid monotonic loading in oil. Additional polished specimens were subjected to cyclic loading at 2 Hz (n=44) and 10 Hz (n=36). All fatigue tests were performed using a fully articulated four-point flexure fixture in 37°C water. Fractography was used to determine the critical flaw size and estimate fracture toughness. To prove the presence of R-curve behavior, non-linear regression was used. Forward stepwise regression was performed to determine the effects on fracture toughness of different variables, such as initial flaw type, critical flaw size, critical flaw eccentricity, cycling frequency, peak load, and number of cycles. Fatigue lifetime data were fit to an exclusive flaw model. There was an increase in fracture toughness values with increasing critical flaw size for both loading methods (rapid monotonic loading and fatigue). The values for the fracture toughness ranged from 0.75 to 1.1 MPam(1/2) reaching a plateau at different critical flaw sizes based on loading method. Cyclic loading had a significant effect on the R-curve behavior. The fatigue lifetime distribution was dependent on the flaw distribution, and it fit well to an exclusive flaw model. Copyright © 2013 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Fatigue loading and R-curve behavior of a dental glass-ceramic with multiple flaw distributions

PubMed Central

Joshi, Gaurav V.; Duan, Yuanyuan; Bona, Alvaro Della; Hill, Thomas J.; John, Kenneth St.; Griggs, Jason A.

2013-01-01

Objectives To determine the effects of surface finish and mechanical loading on the rising toughness curve (R-curve) behavior of a fluorapatite glass-ceramic (IPS e.max ZirPress) and to determine a statistical model for fitting fatigue lifetime data with multiple flaw distributions. Materials and Methods Rectangular beam specimens were fabricated by pressing. Two groups of specimens (n=30) with polished (15 μm) or air abraded surface were tested under rapid monotonic loading in oil. Additional polished specimens were subjected to cyclic loading at 2 Hz (n=44) and 10 Hz (n=36). All fatigue tests were performed using a fully articulated four-point flexure fixture in 37°C water. Fractography was used to determine the critical flaw size and estimate fracture toughness. To prove the presence of R-curve behavior, non-linear regression was used. Forward stepwise regression was performed to determine the effects on fracture toughness of different variables, such as initial flaw type, critical flaw size, critical flaw eccentricity, cycling frequency, peak load, and number of cycles. Fatigue lifetime data were fit to an exclusive flaw model. Results There was an increase in fracture toughness values with increasing critical flaw size for both loading methods (rapid monotonic loading and fatigue). The values for the fracture toughness ranged from 0.75 to 1.1 MPa·m1/2 reaching a plateau at different critical flaw sizes based on loading method. Significance Cyclic loading had a significant effect on the R-curve behavior. The fatigue lifetime distribution was dependent on the flaw distribution, and it fit well to an exclusive flaw model. PMID:24034441

The Effect of an Offset Polar Cap Dipolar Magnetic Field on the Modeling of the Vela Pulsar's Gamma-Ray Light Curves

NASA Technical Reports Server (NTRS)

Barnard, M.; Venter, C.; Harding, A. K.

2016-01-01

We performed geometric pulsar light curve modeling using static, retarded vacuum, and offset polar cap (PC) dipole B-fields (the latter is characterized by a parameter epsilon), in conjunction with standard two-pole caustic (TPC) and outer gap (OG) emission geometries. The offset-PC dipole B-field mimics deviations from the static dipole (which corresponds to epsilon equals 0). In addition to constant-emissivity geometric models, we also considered a slot gap (SG) E-field associated with the offset-PC dipole B-field and found that its inclusion leads to qualitatively different light curves. Solving the particle transport equation shows that the particle energy only becomes large enough to yield significant curvature radiation at large altitudes above the stellar surface, given this relatively low E-field. Therefore, particles do not always attain the radiation-reaction limit. Our overall optimal light curve fit is for the retarded vacuum dipole field and OG model, at an inclination angle alpha equals 78 plus or minus 1 degree and observer angle zeta equals 69 plus 2 degrees or minus 1 degree. For this B-field, the TPC model is statistically disfavored compared to the OG model. For the static dipole field, neither model is significantly preferred. We found that smaller values of epsilon are favored for the offset-PC dipole field when assuming constant emissivity, and larger epsilon values favored for variable emissivity, but not significantly so. When multiplying the SG E-field by a factor of 100, we found improved light curve fits, with alpha and zeta being closer to best fits from independent studies, as well as curvature radiation reaction at lower altitudes.

Analytic model to estimate thermonuclear neutron yield in z-pinches using the magnetic Noh problem

NASA Astrophysics Data System (ADS)

Allen, Robert C.

The objective was to build a model which could be used to estimate neutron yield in pulsed z-pinch experiments, benchmark future z-pinch simulation tools and to assist scaling for breakeven systems. To accomplish this, a recent solution to the magnetic Noh problem was utilized which incorporates a self-similar solution with cylindrical symmetry and azimuthal magnetic field (Velikovich, 2012). The self-similar solution provides the conditions needed to calculate the time dependent implosion dynamics from which batch burn is assumed and used to calculate neutron yield. The solution to the model is presented. The ion densities and time scales fix the initial mass and implosion velocity, providing estimates of the experimental results given specific initial conditions. Agreement is shown with experimental data (Coverdale, 2007). A parameter sweep was done to find the neutron yield, implosion velocity and gain for a range of densities and time scales for DD reactions and a curve fit was done to predict the scaling as a function of preshock conditions.

Dynamic Testing of Laterally Confined Concrete

DTIC Science & Technology

1990-09-01

for Intermediate Confining pressure (Dashed Curve). 31 23. Example of Regression Fit by Equation (6) for Highest Pressure Group (Dashed Curve... pressure group , loaded by a moderate striker-bar impact speed of 420 in/sec. (10.7 m/s). The peak stress of 124 MPa (18 ksi) occurs at a strain of...survived at one end. This was for the highest speed impact in the lowest confining pressure group . Curves are given in the Appendix Figure A-15. The

Reconstruction of quadratic curves in 3D using two or more perspective views: simulation studies

NASA Astrophysics Data System (ADS)

Kumar, Sanjeev; Sukavanam, N.; Balasubramanian, R.

2006-01-01

The shapes of many natural and man-made objects have planar and curvilinear surfaces. The images of such curves usually do not have sufficient distinctive features to apply conventional feature-based reconstruction algorithms. In this paper, we describe a method of reconstruction of a quadratic curve in 3-D space as an intersection of two cones containing the respective projected curve images. The correspondence between this pair of projections of the curve is assumed to be established in this work. Using least-square curve fitting, the parameters of a curve in 2-D space are found. From this we are reconstructing the 3-D quadratic curve. Relevant mathematical formulations and analytical solutions for obtaining the equation of reconstructed curve are given. The result of the described reconstruction methodology are studied by simulation studies. This reconstruction methodology is applicable to LBW decision in cricket, path of the missile, Robotic Vision, path lanning etc.

The MGGB equation-of-state for multifield applications: a numerical recipe for analytic expression of sesame EOS data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kashiwa, B. A.

2010-12-01

Abstract A thermodynamically consistent and fully general equation–of– state (EOS) for multifield applications is described. EOS functions are derived from a Helmholtz free energy expressed as the sum of thermal (fluctuational) and collisional (condensed–phase) contributions; thus the free energy is of the Mie–Gr¨uneisen1 form. The phase–coexistence region is defined using a parameterized saturation curve by extending the form introduced by Guggenheim,2 which scales the curve relative to conditions at the critical point. We use the zero–temperature condensed–phase contribution developed by Barnes,3 which extends the Thomas–Fermi–Dirac equation to zero pressure. Thus, the functional form of the EOS could be called MGGBmore » (for Mie– Gr¨uneisen–Guggenheim–Barnes). Substance–specific parameters are obtained by fitting the low–density energy to data from the Sesame4 library; fitting the zero–temperature pressure to the Sesame cold curve; and fitting the saturation curve and latent heat to laboratory data,5 if available. When suitable coexistence data, or Sesame data, are not available, then we apply the Principle of Corresponding States.2 Thus MGGB can be thought of as a numerical recipe for rendering the tabular Sesame EOS data in an analytic form that includes a proper coexistence region, and which permits the accurate calculation of derivatives associated with compressibility, expansivity, Joule coefficient, and specific heat, all of which are required for multifield applications. 1« less

Predicting long-term graft survival in adult kidney transplant recipients.

PubMed

Pinsky, Brett W; Lentine, Krista L; Ercole, Patrick R; Salvalaggio, Paolo R; Burroughs, Thomas E; Schnitzler, Mark A

2012-07-01

The ability to accurately predict a population's long-term survival has important implications for quantifying the benefits of transplantation. To identify a model that can accurately predict a kidney transplant population's long-term graft survival, we retrospectively studied the United Network of Organ Sharing data from 13,111 kidney-only transplants completed in 1988- 1989. Nineteen-year death-censored graft survival (DCGS) projections were calculated and compared with the population's actual graft survival. The projection curves were created using a two-part estimation model that (1) fits a Kaplan-Meier survival curve immediately after transplant (Part A) and (2) uses truncated observational data to model a survival function for long-term projection (Part B). Projection curves were examined using varying amounts of time to fit both parts of the model. The accuracy of the projection curve was determined by examining whether predicted survival fell within the 95% confidence interval for the 19-year Kaplan-Meier survival, and the sample size needed to detect the difference in projected versus observed survival in a clinical trial. The 19-year DCGS was 40.7% (39.8-41.6%). Excellent predictability (41.3%) can be achieved when Part A is fit for three years and Part B is projected using two additional years of data. Using less than five total years of data tended to overestimate the population's long-term survival, accurate prediction of long-term DCGS is possible, but requires attention to the quantity data used in the projection method.

Improved Cluster Method Applied to the InSAR data of the 2007 Piton de la Fournaise eruption

NASA Astrophysics Data System (ADS)

Cayol, V.; Augier, A.; Froger, J. L.; Menassian, S.

2016-12-01

Interpretation of surface displacement induced by reservoirs, whether magmatic, hydrothermal or gaseous, can be done at reduced numerical cost and with little a priori knowledge using cluster methods, where reservoirs are represented by point sources embedded in an elastic half-space. Most of the time, the solution representing the best trade-off between the data fit and the model smoothness (L-curve criterion) is chosen. This study relies on synthetic tests to improve cluster methods in several ways. Firstly, to solve problems involving steep topographies, we construct unit sources numerically. Secondly, we show that the L-curve criterion leads to several plausible solutions where the most realistic are not necessarily the best fitting. We determine that the cross-validation method, with data geographically grouped, is a more reliable way to determine the solution. Thirdly, we propose a new method, based on source ranking according to their contribution and minimization of the Akaike information criteria, to retrieve reservoirs' geometry more accurately and to better reflect information contained in the data. We show that the solution is robust in the presence of correlated noise and that reservoir complexity that can be retrieved decreases with increasing noise. We also show that it is inappropriate to use cluster methods for pressurized fractures. Finally, the method is applied to the summit deflation recorded by InSAR after the caldera collapse which occurred at Piton de la Fournaise in April 2007. Comparison with other data indicate that the deflation is probably related to poro-elastic compaction and fluid flow subsequent to the crater collapse.

Feasibility of waveform inversion of Rayleigh waves for shallow shear-wave velocity using a genetic algorithm

USGS Publications Warehouse

Zeng, C.; Xia, J.; Miller, R.D.; Tsoflias, G.P.

2011-01-01

Conventional surface wave inversion for shallow shear (S)-wave velocity relies on the generation of dispersion curves of Rayleigh waves. This constrains the method to only laterally homogeneous (or very smooth laterally heterogeneous) earth models. Waveform inversion directly fits waveforms on seismograms, hence, does not have such a limitation. Waveforms of Rayleigh waves are highly related to S-wave velocities. By inverting the waveforms of Rayleigh waves on a near-surface seismogram, shallow S-wave velocities can be estimated for earth models with strong lateral heterogeneity. We employ genetic algorithm (GA) to perform waveform inversion of Rayleigh waves for S-wave velocities. The forward problem is solved by finite-difference modeling in the time domain. The model space is updated by generating offspring models using GA. Final solutions can be found through an iterative waveform-fitting scheme. Inversions based on synthetic records show that the S-wave velocities can be recovered successfully with errors no more than 10% for several typical near-surface earth models. For layered earth models, the proposed method can generate one-dimensional S-wave velocity profiles without the knowledge of initial models. For earth models containing lateral heterogeneity in which case conventional dispersion-curve-based inversion methods are challenging, it is feasible to produce high-resolution S-wave velocity sections by GA waveform inversion with appropriate priori information. The synthetic tests indicate that the GA waveform inversion of Rayleigh waves has the great potential for shallow S-wave velocity imaging with the existence of strong lateral heterogeneity. ?? 2011 Elsevier B.V.

Characterizing L1-norm best-fit subspaces

NASA Astrophysics Data System (ADS)

Brooks, J. Paul; Dulá, José H.

2017-05-01

Fitting affine objects to data is the basis of many tools and methodologies in statistics, machine learning, and signal processing. The L1 norm is often employed to produce subspaces exhibiting a robustness to outliers and faulty observations. The L1-norm best-fit subspace problem is directly formulated as a nonlinear, nonconvex, and nondifferentiable optimization problem. The case when the subspace is a hyperplane can be solved to global optimality efficiently by solving a series of linear programs. The problem of finding the best-fit line has recently been shown to be NP-hard. We present necessary conditions for optimality for the best-fit subspace problem, and use them to characterize properties of optimal solutions.

Stepwise kinetic equilibrium models of quantitative polymerase chain reaction.

PubMed

Cobbs, Gary

2012-08-16

Numerous models for use in interpreting quantitative PCR (qPCR) data are present in recent literature. The most commonly used models assume the amplification in qPCR is exponential and fit an exponential model with a constant rate of increase to a select part of the curve. Kinetic theory may be used to model the annealing phase and does not assume constant efficiency of amplification. Mechanistic models describing the annealing phase with kinetic theory offer the most potential for accurate interpretation of qPCR data. Even so, they have not been thoroughly investigated and are rarely used for interpretation of qPCR data. New results for kinetic modeling of qPCR are presented. Two models are presented in which the efficiency of amplification is based on equilibrium solutions for the annealing phase of the qPCR process. Model 1 assumes annealing of complementary targets strands and annealing of target and primers are both reversible reactions and reach a dynamic equilibrium. Model 2 assumes all annealing reactions are nonreversible and equilibrium is static. Both models include the effect of primer concentration during the annealing phase. Analytic formulae are given for the equilibrium values of all single and double stranded molecules at the end of the annealing step. The equilibrium values are then used in a stepwise method to describe the whole qPCR process. Rate constants of kinetic models are the same for solutions that are identical except for possibly having different initial target concentrations. Analysis of qPCR curves from such solutions are thus analyzed by simultaneous non-linear curve fitting with the same rate constant values applying to all curves and each curve having a unique value for initial target concentration. The models were fit to two data sets for which the true initial target concentrations are known. Both models give better fit to observed qPCR data than other kinetic models present in the literature. They also give better estimates of initial target concentration. Model 1 was found to be slightly more robust than model 2 giving better estimates of initial target concentration when estimation of parameters was done for qPCR curves with very different initial target concentration. Both models may be used to estimate the initial absolute concentration of target sequence when a standard curve is not available. It is argued that the kinetic approach to modeling and interpreting quantitative PCR data has the potential to give more precise estimates of the true initial target concentrations than other methods currently used for analysis of qPCR data. The two models presented here give a unified model of the qPCR process in that they explain the shape of the qPCR curve for a wide variety of initial target concentrations.

Development and Assessment of a New Empirical Model for Predicting Full Creep Curves

PubMed Central

Gray, Veronica; Whittaker, Mark

2015-01-01

This paper details the development and assessment of a new empirical creep model that belongs to the limited ranks of models reproducing full creep curves. The important features of the model are that it is fully standardised and is universally applicable. By standardising, the user no longer chooses functions but rather fits one set of constants only. Testing it on 7 contrasting materials, reproducing 181 creep curves we demonstrate its universality. New model and Theta Projection curves are compared to one another using an assessment tool developed within this paper. PMID:28793458

Object-Image Correspondence for Algebraic Curves under Projections

NASA Astrophysics Data System (ADS)

Burdis, Joseph M.; Kogan, Irina A.; Hong, Hoon

2013-03-01

We present a novel algorithm for deciding whether a given planar curve is an image of a given spatial curve, obtained by a central or a parallel projection with unknown parameters. The motivation comes from the problem of establishing a correspondence between an object and an image, taken by a camera with unknown position and parameters. A straightforward approach to this problem consists of setting up a system of conditions on the projection parameters and then checking whether or not this system has a solution. The computational advantage of the algorithm presented here, in comparison to algorithms based on the straightforward approach, lies in a significant reduction of a number of real parameters that need to be eliminated in order to establish existence or non-existence of a projection that maps a given spatial curve to a given planar curve. Our algorithm is based on projection criteria that reduce the projection problem to a certain modification of the equivalence p! roblem of planar curves under affine and projective transformations. To solve the latter problem we make an algebraic adaptation of signature construction that has been used to solve the equivalence problems for smooth curves. We introduce a notion of a classifying set of rational differential invariants and produce explicit formulas for such invariants for the actions of the projective and the affine groups on the plane.

Comparison between two statistically based methods, and two physically based models developed to compute daily mean streamflow at ungaged locations in the Cedar River Basin, Iowa

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Christiansen, Daniel E.; Hutchinson, Kasey J.; Sanders, Curtis L.; Archfield, Stacey A.

2013-01-01

A variety of individuals from water resource managers to recreational users need streamflow information for planning and decisionmaking at locations where there are no streamgages. To address this problem, two statistically based methods, the Flow Duration Curve Transfer method and the Flow Anywhere method, were developed for statewide application and the two physically based models, the Precipitation Runoff Modeling-System and the Soil and Water Assessment Tool, were only developed for application for the Cedar River Basin. Observed and estimated streamflows for the two methods and models were compared for goodness of fit at 13 streamgages modeled in the Cedar River Basin by using the Nash-Sutcliffe and the percent-bias efficiency values. Based on median and mean Nash-Sutcliffe values for the 13 streamgages the Precipitation Runoff Modeling-System and Soil and Water Assessment Tool models appear to have performed similarly and better than Flow Duration Curve Transfer and Flow Anywhere methods. Based on median and mean percent bias values, the Soil and Water Assessment Tool model appears to have generally overestimated daily mean streamflows, whereas the Precipitation Runoff Modeling-System model and statistical methods appear to have underestimated daily mean streamflows. The Flow Duration Curve Transfer method produced the lowest median and mean percent bias values and appears to perform better than the other models.

The Use of Statistically Based Rolling Supply Curves for Electricity Market Analysis: A Preliminary Look

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jenkin, Thomas J; Larson, Andrew; Ruth, Mark F

In light of the changing electricity resource mixes across the United States, an important question in electricity modeling is how additions and retirements of generation, including additions in variable renewable energy (VRE) generation could impact markets by changing hourly wholesale energy prices. Instead of using resource-intensive production cost models (PCMs) or building and using simple generator supply curves, this analysis uses a 'top-down' approach based on regression analysis of hourly historical energy and load data to estimate the impact of supply changes on wholesale electricity prices, provided the changes are not so substantial that they fundamentally alter the market andmore » dispatch-order driven behavior of non-retiring units. The rolling supply curve (RSC) method used in this report estimates the shape of the supply curve that fits historical hourly price and load data for given time intervals, such as two-weeks, and then repeats this on a rolling basis through the year. These supply curves can then be modified on an hourly basis to reflect the impact of generation retirements or additions, including VRE and then reapplied to the same load data to estimate the change in hourly electricity price. The choice of duration over which these RSCs are estimated has a significant impact on goodness of fit. For example, in PJM in 2015, moving from fitting one curve per year to 26 rolling two-week supply curves improves the standard error of the regression from 16 dollars/MWh to 6 dollars/MWh and the R-squared of the estimate from 0.48 to 0.76. We illustrate the potential use and value of the RSC method by estimating wholesale price effects under various generator retirement and addition scenarios, and we discuss potential limits of the technique, some of which are inherent. The ability to do this type of analysis is important to a wide range of market participants and other stakeholders, and it may have a role in complementing use of or providing calibrating insights to PCMs.« less

Age, Physical Activity, Physical Fitness, Body Composition, and Incidence of Orthopedic Problems.

ERIC Educational Resources Information Center

Research Quarterly for Exercise and Sport, 1989

1989-01-01

Effects of age, physical activity, physical fitness, and body mass index (BMI) on the occurrence of orthopedic problems were examined. For men, physical fitness, BMI, and physical activity were associated with orthopedic problems; for women, physical activity was the main predictor. Age was not a factor for either gender. (JD)

The influence of cardiorespiratory fitness on strategic, behavioral, and electrophysiological indices of arithmetic cognition in preadolescent children

PubMed Central

Moore, R. Davis; Drollette, Eric S.; Scudder, Mark R.; Bharij, Aashiv; Hillman, Charles H.

2014-01-01

The current study investigated the influence of cardiorespiratory fitness on arithmetic cognition in forty 9–10 year old children. Measures included a standardized mathematics achievement test to assess conceptual and computational knowledge, self-reported strategy selection, and an experimental arithmetic verification task (including small and large addition problems), which afforded the measurement of event-related brain potentials (ERPs). No differences in math achievement were observed as a function of fitness level, but all children performed better on math concepts relative to math computation. Higher fit children reported using retrieval more often to solve large arithmetic problems, relative to lower fit children. During the arithmetic verification task, higher fit children exhibited superior performance for large problems, as evidenced by greater d' scores, while all children exhibited decreased accuracy and longer reaction time for large relative to small problems, and incorrect relative to correct solutions. On the electrophysiological level, modulations of early (P1, N170) and late ERP components (P3, N400) were observed as a function of problem size and solution correctness. Higher fit children exhibited selective modulations for N170, P3, and N400 amplitude relative to lower fit children, suggesting that fitness influences symbolic encoding, attentional resource allocation and semantic processing during arithmetic tasks. The current study contributes to the fitness-cognition literature by demonstrating that the benefits of cardiorespiratory fitness extend to arithmetic cognition, which has important implications for the educational environment and the context of learning. PMID:24829556

Fecal immunochemical test for predicting mucosal healing in ulcerative colitis patients: A systematic review and meta-analysis.

PubMed

Dai, Cong; Jiang, Min; Sun, Ming-Jun; Cao, Qin

2018-05-01

Fecal immunochemical test (FIT) is a promising marker for assessment of inflammatory bowel disease activity. However, the utility of FIT for predicting mucosal healing (MH) of ulcerative colitis (UC) patients has yet to be clearly demonstrated. The objective of our study was to perform a diagnostic test accuracy test meta-analysis evaluating the diagnostic accuracy of FIT in predicting MH of UC patients. We systematically searched the databases from inception to November 2017 that evaluated MH in UC. The methodological quality of each study was assessed according to the Quality Assessment of Diagnostic Accuracy Studies checklist. The extracted data were pooled using a summary receiver operating characteristic curve model. Random-effects model was used to summarize the diagnostic odds ratio, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio. Six studies comprising 625 UC patients were included in the meta-analysis. The pooled sensitivity and specificity values for predicting MH in UC were 0.77 (95% confidence interval [CI], 0.72-0.81) and 0.81 (95% CI, 0.76-0.85), respectively. The FIT level had a high rule-in value (positive likelihood ratio, 3.79; 95% CI, 2.85-5.03) and a moderate rule-out value (negative likelihood ratio, 0.26; 95% CI, 0.16-0.43) for predicting MH in UC. The results of the receiver operating characteristic curve analysis (area under the curve, 0.88; standard error of the mean, 0.02) and diagnostic odds ratio (18.08; 95% CI, 9.57-34.13) also revealed improved discrimination for identifying MH in UC with FIT concentration. Our meta-analysis has found that FIT is a simple, reliable non-invasive marker for predicting MH in UC patients. © 2018 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Identifying the Physical Fitness, Anthropometric and Athletic Movement Qualities Discriminant of Developmental Level in Elite Junior Australian Football: Implications for the Development of Talent.

PubMed

Gaudion, Sarah L; Doma, Kenji; Sinclair, Wade; Banyard, Harry G; Woods, Carl T

2017-07-01

Gaudion, SL, Doma, K, Sinclair, W, Banyard, HG, and Woods, CT. Identifying the physical fitness, anthropometric and athletic movement qualities discriminant of developmental level in elite junior Australian football: implications for the development of talent. J Strength Cond Res 31(7): 1830-1839, 2017-This study aimed to identify the physical fitness, anthropometric and athletic movement qualities discriminant of developmental level in elite junior Australian football (AF). From a total of 77 players, 2 groups were defined according to their developmental level; under 16 (U16) (n = 40, 15.6 to 15.9 years), and U18 (n = 37, 17.1 to 17.9 years). Players performed a test battery consisting of 7 physical fitness assessments, 2 anthropometric measurements, and a fundamental athletic movement assessment. A multivariate analysis of variance tested the main effect of developmental level (2 levels: U16 and U18) on the assessment criterions, whilst binary logistic regression models and receiver operating characteristic (ROC) curves were built to identify the qualities most discriminant of developmental level. A significant effect of developmental level was evident on 9 of the assessments (d = 0.27-0.88; p ≤ 0.05). However, it was a combination of body mass, dynamic vertical jump height (nondominant leg), repeat sprint time, and the score on the 20-m multistage fitness test that provided the greatest association with developmental level (Akaike's information criterion = 80.84). The ROC curve was maximized with a combined score of 180.7, successfully discriminating 89 and 60% of the U18 and U16 players, respectively (area under the curve = 79.3%). These results indicate that there are distinctive physical fitness and anthropometric qualities discriminant of developmental level within the junior AF talent pathway. Coaches should consider these differences when designing training interventions at the U16 level to assist with the development of prospective U18 AF players.

Facilitating students' application of the integral and the area under the curve concepts in physics problems

NASA Astrophysics Data System (ADS)

Nguyen, Dong-Hai

This research project investigates the difficulties students encounter when solving physics problems involving the integral and the area under the curve concepts and the strategies to facilitate students learning to solve those types of problems. The research contexts of this project are calculus-based physics courses covering mechanics and electromagnetism. In phase I of the project, individual teaching/learning interviews were conducted with 20 students in mechanics and 15 students from the same cohort in electromagnetism. The students were asked to solve problems on several topics of mechanics and electromagnetism. These problems involved calculating physical quantities (e.g. velocity, acceleration, work, electric field, electric resistance, electric current) by integrating or finding the area under the curve of functions of related quantities (e.g. position, velocity, force, charge density, resistivity, current density). Verbal hints were provided when students made an error or were unable to proceed. A total number of 140 one-hour interviews were conducted in this phase, which provided insights into students' difficulties when solving the problems involving the integral and the area under the curve concepts and the hints to help students overcome those difficulties. In phase II of the project, tutorials were created to facilitate students' learning to solve physics problems involving the integral and the area under the curve concepts. Each tutorial consisted of a set of exercises and a protocol that incorporated the helpful hints to target the difficulties that students expressed in phase I of the project. Focus group learning interviews were conducted to test the effectiveness of the tutorials in comparison with standard learning materials (i.e. textbook problems and solutions). Overall results indicated that students learning with our tutorials outperformed students learning with standard materials in applying the integral and the area under the curve concepts to physics problems. The results of this project provide broader and deeper insights into students' problem solving with the integral and the area under the curve concepts and suggest strategies to facilitate students' learning to apply these concepts to physics problems. This study also has significant implications for further research, curriculum development and instruction.

TH-EF-207A-04: A Dynamic Contrast Enhanced Cone Beam CT Technique for Evaluation of Renal Functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Z; Shi, J; Yang, Y

Purpose: To develop a simple but robust method for the early detection and evaluation of renal functions using dynamic contrast enhanced cone beam CT technique. Methods: Experiments were performed on an integrated imaging and radiation research platform developed by our lab. Animals (n=3) were anesthetized with 20uL Ketamine/Xylazine cocktail, and then received 200uL injection of iodinated contrast agent Iopamidol via tail vein. Cone beam CT was acquired following contrast injection once per minute and up to 25 minutes. The cone beam CT was reconstructed with a dimension of 300×300×800 voxels of 130×130×130um voxel resolution. The middle kidney slices in themore » transvers and coronal planes were selected for image analysis. A double exponential function was used to fit the contrast enhanced signal intensity versus the time after contrast injection. Both pixel-based and region of interest (ROI)-based curve fitting were performed. Four parameters obtained from the curve fitting, namely the amplitude and flow constant for both contrast wash in and wash out phases, were investigated for further analysis. Results: Robust curve fitting was demonstrated for both pixel based (with R{sup 2}>0.8 for >85% pixels within the kidney contour) and ROI based (R{sup 2}>0.9 for all regions) analysis. Three different functional regions: renal pelvis, medulla and cortex, were clearly differentiated in the functional parameter map in the pixel based analysis. ROI based analysis showed the half-life T1/2 for contrast wash in and wash out phases were 0.98±0.15 and 17.04±7.16, 0.63±0.07 and 17.88±4.51, and 1.48±0.40 and 10.79±3.88 minutes for the renal pelvis, medulla and cortex, respectively. Conclusion: A robust method based on dynamic contrast enhanced cone beam CT and double exponential curve fitting has been developed to analyze the renal functions for different functional regions. Future study will be performed to investigate the sensitivity of this technique in the detection of radiation induced kidney dysfunction.« less

76 FR 57677 - Defense Federal Acquisition Regulation Supplement; Increase the Use of Fixed-Price Incentive...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-16

... Under Secretary of Defense for Acquisition, Technology, & Logistics (USD(AT&L)), dated November 3, 2010... cost, share lines, and ceiling price. This regulation is not a ``one-size- fits-all'' mandate. However.../optimistic weighted average and ensure that their cost curves do not mirror cost-plus-fixed-fee cost curves...

Comparative Evaluation of Two Serial Gene Expression Experiments | Division of Cancer Prevention

Cancer.gov

Stuart G. Baker, 2014 Introduction This program fits biologically relevant response curves in comparative analysis of the two gene expression experiments involving same genes but under different scenarios and at least 12 responses. The program outputs gene pairs with biologically relevant response curve shapes including flat, linear, sigmoid, hockey stick, impulse and step

After Six Decades: Applying the U-Curve Hypothesis to the Adjustment of International Postgraduate Students

ERIC Educational Resources Information Center

Chien, Yu-Yi Grace

2016-01-01

The research described in this article concludes that the widely cited U-curve hypothesis is no longer supported by research data because the adjustment of international postgraduate students is a complex phenomenon that does not fit easily with attempts to define and categorize it. Methodological issues, different internal and external factors,…

Fixture For Drilling And Tapping A Curved Workpiece

NASA Technical Reports Server (NTRS)

Espinosa, P. S.; Lockyer, R. T.

1992-01-01

Simple fixture guides drilling and tapping of holes in prescribed locations and orientations on workpiece having curved surface. Tool conceived for use in reworking complexly curved helicopter blades made of composite materials. Fixture is block of rigid foam with epoxy filler, custom-fitted to surface contour, containing bushings and sleeves at drilling and tapping sites. Bushings changed, so taps and drills of various sizes accommodated. In use, fixture secured to surface by hold-down bolts extending through sleeves and into threads in substrate.

Locally-Based Kernal PLS Smoothing to Non-Parametric Regression Curve Fitting

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Trejo, Leonard J.; Wheeler, Kevin; Korsmeyer, David (Technical Monitor)

2002-01-01

We present a novel smoothing approach to non-parametric regression curve fitting. This is based on kernel partial least squares (PLS) regression in reproducing kernel Hilbert space. It is our concern to apply the methodology for smoothing experimental data where some level of knowledge about the approximate shape, local inhomogeneities or points where the desired function changes its curvature is known a priori or can be derived based on the observed noisy data. We propose locally-based kernel PLS regression that extends the previous kernel PLS methodology by incorporating this knowledge. We compare our approach with existing smoothing splines, hybrid adaptive splines and wavelet shrinkage techniques on two generated data sets.

Method for Making Measurements of the Post-Combustion Residence Time in a Gas Turbine Engine

NASA Technical Reports Server (NTRS)

Miles, Jeffrey H (Inventor)

2015-01-01

A system and method of measuring a residence time in a gas-turbine engine is provided, whereby the method includes placing pressure sensors at a combustor entrance and at a turbine exit of the gas-turbine engine and measuring a combustor pressure at the combustor entrance and a turbine exit pressure at the turbine exit. The method further includes computing cross-spectrum functions between a combustor pressure sensor signal from the measured combustor pressure and a turbine exit pressure sensor signal from the measured turbine exit pressure, applying a linear curve fit to the cross-spectrum functions, and computing a post-combustion residence time from the linear curve fit.

Depth estimation and camera calibration of a focused plenoptic camera for visual odometry

NASA Astrophysics Data System (ADS)

Zeller, Niclas; Quint, Franz; Stilla, Uwe

2016-08-01

This paper presents new and improved methods of depth estimation and camera calibration for visual odometry with a focused plenoptic camera. For depth estimation we adapt an algorithm previously used in structure-from-motion approaches to work with images of a focused plenoptic camera. In the raw image of a plenoptic camera, scene patches are recorded in several micro-images under slightly different angles. This leads to a multi-view stereo-problem. To reduce the complexity, we divide this into multiple binocular stereo problems. For each pixel with sufficient gradient we estimate a virtual (uncalibrated) depth based on local intensity error minimization. The estimated depth is characterized by the variance of the estimate and is subsequently updated with the estimates from other micro-images. Updating is performed in a Kalman-like fashion. The result of depth estimation in a single image of the plenoptic camera is a probabilistic depth map, where each depth pixel consists of an estimated virtual depth and a corresponding variance. Since the resulting image of the plenoptic camera contains two plains: the optical image and the depth map, camera calibration is divided into two separate sub-problems. The optical path is calibrated based on a traditional calibration method. For calibrating the depth map we introduce two novel model based methods, which define the relation of the virtual depth, which has been estimated based on the light-field image, and the metric object distance. These two methods are compared to a well known curve fitting approach. Both model based methods show significant advantages compared to the curve fitting method. For visual odometry we fuse the probabilistic depth map gained from one shot of the plenoptic camera with the depth data gained by finding stereo correspondences between subsequent synthesized intensity images of the plenoptic camera. These images can be synthesized totally focused and thus finding stereo correspondences is enhanced. In contrast to monocular visual odometry approaches, due to the calibration of the individual depth maps, the scale of the scene can be observed. Furthermore, due to the light-field information better tracking capabilities compared to the monocular case can be expected. As result, the depth information gained by the plenoptic camera based visual odometry algorithm proposed in this paper has superior accuracy and reliability compared to the depth estimated from a single light-field image.

Light-curve modelling constraints on the obliquities and aspect angles of the young Fermi pulsars

NASA Astrophysics Data System (ADS)

Pierbattista, M.; Harding, A. K.; Grenier, I. A.; Johnson, T. J.; Caraveo, P. A.; Kerr, M.; Gonthier, P. L.

2015-03-01

In more than four years of observation the Large Area Telescope on board the Fermi satellite has identified pulsed γ-ray emission from more than 80 young or middle-aged pulsars, in most cases providing light curves with high statistics. Fitting the observed profiles with geometrical models can provide estimates of the magnetic obliquity α and of the line of sight angle ζ, yielding estimates of the radiation beaming factor and radiated luminosity. Using different γ-ray emission geometries (Polar Cap, Slot Gap, Outer Gap, One Pole Caustic) and core plus cone geometries for the radio emission, we fit γ-ray light curves for 76 young or middle-aged pulsars and we jointly fit their γ-ray plus radio light curves when possible. We find that a joint radio plus γ-ray fit strategy is important to obtain (α,ζ) estimates that can explain simultaneously detectable radio and γ-ray emission: when the radio emission is available, the inclusion of the radio light curve in the fit leads to important changes in the (α,ζ) solutions. The most pronounced changes are observed for Outer Gap and One Pole Caustic models for which the γ-ray only fit leads to underestimated α or ζ when the solution is found to the left or to the right of the main α-ζ plane diagonal respectively. The intermediate-to-high altitude magnetosphere models, Slot Gap, Outer Gap, and One pole Caustic, are favoured in explaining the observations. We find no apparent evolution of α on a time scale of 106 years. For all emission geometries our derived γ-ray beaming factors are generally less than one and do not significantly evolve with the spin-down power. A more pronounced beaming factor vs. spin-down power correlation is observed for Slot Gap model and radio-quiet pulsars and for the Outer Gap model and radio-loud pulsars. The beaming factor distributions exhibit a large dispersion that is less pronounced for the Slot Gap case and that decreases from radio-quiet to radio-loud solutions. For all models, the correlation between γ-ray luminosity and spin-down power is consistent with a square root dependence. The γ-ray luminosities obtained by using the beaming factors estimated in the framework of each model do not exceed the spin-down power. This suggests that assuming a beaming factor of one for all objects, as done in other studies, likely overestimates the real values. The data show a relation between the pulsar spectral characteristics and the width of the accelerator gap. The relation obtained in the case of the Slot Gap model is consistent with the theoretical prediction. Appendices are available in electronic form at http://www.aanda.org

Light-curve modelling constraints on the obliquities and aspect angles of the young Fermi pulsars

DOE PAGES

Pierbattista, M.; Harding, A. K.; Grenier, I. A.; ...

2015-02-10

In more than four years of observation the Large Area Telescope on board the Fermi satellite has identified pulsed γ-ray emission from more than 80 young or middle-aged pulsars, in most cases providing light curves with high statistics. Fitting the observed profiles with geometrical models can provide estimates of the magnetic obliquity α and of the line of sight angle ζ, yielding estimates of the radiation beaming factor and radiated luminosity. Using different γ-ray emission geometries (Polar Cap, Slot Gap, Outer Gap, One Pole Caustic) and core plus cone geometries for the radio emission, we fit γ-ray light curves formore » 76 young or middle-aged pulsars and we jointly fit their γ-ray plus radio light curves when possible. We find that a joint radio plus γ-ray fit strategy is important to obtain (α,ζ) estimates that can explain simultaneously detectable radio and γ-ray emission: when the radio emission is available, the inclusion of the radio light curve in the fit leads to important changes in the (α,ζ) solutions. The most pronounced changes are observed for Outer Gap and One Pole Caustic models for which the γ-ray only fit leads to underestimated α or ζ when the solution is found to the left or to the right of the main α-ζ plane diagonal respectively. The intermediate-to-high altitude magnetosphere models, Slot Gap, Outer Gap, and One pole Caustic, are favoured in explaining the observations. We find no apparent evolution of α on a time scale of 106 years. For all emission geometries our derived γ-ray beaming factors are generally less than one and do not significantly evolve with the spin-down power. A more pronounced beaming factor vs. spin-down power correlation is observed for Slot Gap model and radio-quiet pulsars and for the Outer Gap model and radio-loud pulsars. The beaming factor distributions exhibit a large dispersion that is less pronounced for the Slot Gap case and that decreases from radio-quiet to radio-loud solutions. For all models, the correlation between γ-ray luminosity and spin-down power is consistent with a square root dependence. The γ-ray luminosities obtained by using the beaming factors estimated in the framework of each model do not exceed the spin-down power. This suggests that assuming a beaming factor of one for all objects, as done in other studies, likely overestimates the real values. The data show a relation between the pulsar spectral characteristics and the width of the accelerator gap. Furthermore, the relation obtained in the case of the Slot Gap model is consistent with the theoretical prediction.« less

Light-Curve Modelling Constraints on the Obliquities and Aspect Angles of the Young Fermi Pulsars

NASA Technical Reports Server (NTRS)

Pierbattista, M.; Harding, A. K.; Grenier, I. A.; Johnson, T. J.; Caraveo, P. A.; Kerr, M.; Gonthier, P. L.

2015-01-01

In more than four years of observation the Large Area Telescope on board the Fermi satellite has identified pulsed gamma-ray emission from more than 80 young or middle-aged pulsars, in most cases providing light curves with high statistics. Fitting the observed profiles with geometrical models can provide estimates of the magnetic obliquity alpha and of the line of sight angle zeta, yielding estimates of the radiation beaming factor and radiated luminosity. Using different gamma-ray emission geometries (Polar Cap, Slot Gap, Outer Gap, One Pole Caustic) and core plus cone geometries for the radio emission, we fit gamma-ray light curves for 76 young or middle-aged pulsars and we jointly fit their gamma-ray plus radio light curves when possible. We find that a joint radio plus gamma-ray fit strategy is important to obtain (alpha, zeta) estimates that can explain simultaneously detectable radio and gamma-ray emission: when the radio emission is available, the inclusion of the radio light curve in the fit leads to important changes in the (alpha, gamma) solutions. The most pronounced changes are observed for Outer Gap and One Pole Caustic models for which the gamma-ray only fit leads to underestimated alpha or zeta when the solution is found to the left or to the right of the main alpha-zeta plane diagonal respectively. The intermediate-to-high altitude magnetosphere models, Slot Gap, Outer Gap, and One pole Caustic, are favored in explaining the observations. We find no apparent evolution of a on a time scale of 106 years. For all emission geometries our derived gamma-ray beaming factors are generally less than one and do not significantly evolve with the spin-down power. A more pronounced beaming factor vs. spin-down power correlation is observed for Slot Gap model and radio-quiet pulsars and for the Outer Gap model and radio-loud pulsars. The beaming factor distributions exhibit a large dispersion that is less pronounced for the Slot Gap case and that decreases from radio-quiet to radio-loud solutions. For all models, the correlation between gamma-ray luminosity and spin-down power is consistent with a square root dependence. The gamma-ray luminosities obtained by using the beaming factors estimated in the framework of each model do not exceed the spin-down power. This suggests that assuming a beaming factor of one for all objects, as done in other studies, likely overestimates the real values. The data show a relation between the pulsar spectral characteristics and the width of the accelerator gap. The relation obtained in the case of the Slot Gap model is consistent with the theoretical prediction.

Fuzzy Multi-Objective Vendor Selection Problem with Modified S-CURVE Membership Function

NASA Astrophysics Data System (ADS)

Díaz-Madroñero, Manuel; Peidro, David; Vasant, Pandian

2010-06-01

In this paper, the S-Curve membership function methodology is used in a vendor selection (VS) problem. An interactive method for solving multi-objective VS problems with fuzzy goals is developed. The proposed method attempts simultaneously to minimize the total order costs, the number of rejected items and the number of late delivered items with reference to several constraints such as meeting buyers' demand, vendors' capacity, vendors' quota flexibility, vendors' allocated budget, etc. We compare in an industrial case the performance of S-curve membership functions, representing uncertainty goals and constraints in VS problems, with linear membership functions.

Detecting time-specific differences between temporal nonlinear curves: Analyzing data from the visual world paradigm

PubMed Central

Oleson, Jacob J; Cavanaugh, Joseph E; McMurray, Bob; Brown, Grant

2015-01-01

In multiple fields of study, time series measured at high frequencies are used to estimate population curves that describe the temporal evolution of some characteristic of interest. These curves are typically nonlinear, and the deviations of each series from the corresponding curve are highly autocorrelated. In this scenario, we propose a procedure to compare the response curves for different groups at specific points in time. The method involves fitting the curves, performing potentially hundreds of serially correlated tests, and appropriately adjusting the overall alpha level of the tests. Our motivating application comes from psycholinguistics and the visual world paradigm. We describe how the proposed technique can be adapted to compare fixation curves within subjects as well as between groups. Our results lead to conclusions beyond the scope of previous analyses. PMID:26400088

Observations of SN 2015F Suggest a Correlation between the Intrinsic Luminosity of Type Ia Supernovae and the Shape of Their Light Curves >900 Days after Explosion

NASA Astrophysics Data System (ADS)

Graur, Or; Zurek, David R.; Rest, Armin; Seitenzahl, Ivo R.; Shappee, Benjamin J.; Fisher, Robert; Guillochon, James; Shara, Michael M.; Riess, Adam G.

2018-06-01

The late-time light curves of Type Ia supernovae (SNe Ia), observed >900 days after explosion, present the possibility of a new diagnostic for SN Ia progenitor and explosion models. First, however, we must discover what physical process (or processes) leads to the slow-down of the light curve relative to a pure 56Co decay, as observed in SNe 2011fe, 2012cg, and 2014J. We present Hubble Space Telescope observations of SN 2015F, taken ≈600–1040 days past maximum light. Unlike those of the three other SNe Ia, the light curve of SN 2015F remains consistent with being powered solely by the radioactive decay of 56Co. We fit the light curves of these four SNe Ia in a consistent manner and measure possible correlations between the light-curve stretch—a proxy for the intrinsic luminosity of the SN—and the parameters of the physical model used in the fit. We propose a new, late-time Phillips-like correlation between the stretch of the SNe and the shape of their late-time light curves, which we parameterize as the difference between their pseudo-bolometric luminosities at 600 and 900 days: ΔL 900 = log(L 600/L 900). Our analysis is based on only four SNe, so a larger sample is required to test the validity of this correlation. If true, this model-independent correlation provides a new way to test which physical process lies behind the slow-down of SN Ia light curves >900 days after explosion, and, ultimately, fresh constraints on the various SN Ia progenitor and explosion models.

REFLECTED LIGHT CURVES, SPHERICAL AND BOND ALBEDOS OF JUPITER- AND SATURN-LIKE EXOPLANETS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dyudina, Ulyana; Kopparla, Pushkar; Ingersoll, Andrew P.

Reflected light curves observed for exoplanets indicate that a few of them host bright clouds. We estimate how the light curve and total stellar heating of a planet depends on forward and backward scattering in the clouds based on Pioneer and Cassini spacecraft images of Jupiter and Saturn. We fit analytical functions to the local reflected brightnesses of Jupiter and Saturn depending on the planet’s phase. These observations cover broadbands at 0.59–0.72 and 0.39–0.5 μ m, and narrowbands at 0.938 (atmospheric window), 0.889 (CH4 absorption band), and 0.24–0.28 μ m. We simulate the images of the planets with a ray-tracingmore » model, and disk-integrate them to produce the full-orbit light curves. For Jupiter, we also fit the modeled light curves to the observed full-disk brightness. We derive spherical albedos for Jupiter and Saturn, and for planets with Lambertian and Rayleigh-scattering atmospheres. Jupiter-like atmospheres can produce light curves that are a factor of two fainter at half-phase than the Lambertian planet, given the same geometric albedo at transit. The spherical albedo is typically lower than for a Lambertian planet by up to a factor of ∼1.5. The Lambertian assumption will underestimate the absorption of the stellar light and the equilibrium temperature of the planetary atmosphere. We also compare our light curves with the light curves of solid bodies: the moons Enceladus and Callisto. Their strong backscattering peak within a few degrees of opposition (secondary eclipse) can lead to an even stronger underestimate of the stellar heating.« less

Inference and analysis of xenon outflow curves under multi-pulse injection in two-dimensional chromatography.

PubMed

Shu-Jiang, Liu; Zhan-Ying, Chen; Yin-Zhong, Chang; Shi-Lian, Wang; Qi, Li; Yuan-Qing, Fan

2013-10-11

Multidimensional gas chromatography is widely applied to atmospheric xenon monitoring for the Comprehensive Nuclear-Test-Ban Treaty (CTBT). To improve the capability for xenon sampling from the atmosphere, sampling techniques have been investigated in detail. The sampling techniques are designed by xenon outflow curves which are influenced by many factors, and the injecting condition is one of the key factors that could influence the xenon outflow curves. In this paper, the xenon outflow curves of single-pulse injection in two-dimensional gas chromatography has been tested and fitted as a function of exponential modified Gaussian distribution. An inference formula of the xenon outflow curve for six-pulse injection is derived, and the inference formula is also tested to compare with its fitting formula of the xenon outflow curve. As a result, the curves of both the one-pulse and six-pulse injections obey the exponential modified Gaussian distribution when the temperature of the activated carbon column's temperature is 26°C and the flow rate of the carrier gas is 35.6mLmin(-1). The retention time of the xenon peak for one-pulse injection is 215min, and the peak width is 138min. For the six-pulse injection, however, the retention time is delayed to 255min, and the peak width broadens to 222min. According to the inferred formula of the xenon outflow curve for the six-pulse injection, the inferred retention time is 243min, the relative deviation of the retention time is 4.7%, and the inferred peak width is 225min, with a relative deviation of 1.3%. Copyright © 2013 Elsevier B.V. All rights reserved.

The Type Ia Supernova Color-Magnitude Relation and Host Galaxy Dust: A Simple Hierarchical Bayesian Model

NASA Astrophysics Data System (ADS)

Mandel, Kaisey; Scolnic, Daniel; Shariff, Hikmatali; Foley, Ryan; Kirshner, Robert

2017-01-01

Inferring peak optical absolute magnitudes of Type Ia supernovae (SN Ia) from distance-independent measures such as their light curve shapes and colors underpins the evidence for cosmic acceleration. SN Ia with broader, slower declining optical light curves are more luminous (“broader-brighter”) and those with redder colors are dimmer. But the “redder-dimmer” color-luminosity relation widely used in cosmological SN Ia analyses confounds its two separate physical origins. An intrinsic correlation arises from the physics of exploding white dwarfs, while interstellar dust in the host galaxy also makes SN Ia appear dimmer and redder. Conventional SN Ia cosmology analyses currently use a simplistic linear regression of magnitude versus color and light curve shape, which does not model intrinsic SN Ia variations and host galaxy dust as physically distinct effects, resulting in low color-magnitude slopes. We construct a probabilistic generative model for the dusty distribution of extinguished absolute magnitudes and apparent colors as the convolution of an intrinsic SN Ia color-magnitude distribution and a host galaxy dust reddening-extinction distribution. If the intrinsic color-magnitude (MB vs. B-V) slope βint differs from the host galaxy dust law RB, this convolution results in a specific curve of mean extinguished absolute magnitude vs. apparent color. The derivative of this curve smoothly transitions from βint in the blue tail to RB in the red tail of the apparent color distribution. The conventional linear fit approximates this effective curve near the average apparent color, resulting in an apparent slope βapp between βint and RB. We incorporate these effects into a hierarchical Bayesian statistical model for SN Ia light curve measurements, and analyze a dataset of SALT2 optical light curve fits of 277 nearby SN Ia at z < 0.10. The conventional linear fit obtains βapp ≈ 3. Our model finds a βint = 2.2 ± 0.3 and a distinct dust law of RB = 3.7 ± 0.3, consistent with the average for Milky Way dust, while correcting a systematic distance bias of ~0.10 mag in the tails of the apparent color distribution. This research is supported by NSF grants AST-156854, AST-1211196, and NASA grant NNX15AJ55G.

The S-curve for forecasting waste generation in construction projects.

PubMed

Lu, Weisheng; Peng, Yi; Chen, Xi; Skitmore, Martin; Zhang, Xiaoling

2016-10-01

Forecasting construction waste generation is the yardstick of any effort by policy-makers, researchers, practitioners and the like to manage construction and demolition (C&D) waste. This paper develops and tests an S-curve model to indicate accumulative waste generation as a project progresses. Using 37,148 disposal records generated from 138 building projects in Hong Kong in four consecutive years from January 2011 to June 2015, a wide range of potential S-curve models are examined, and as a result, the formula that best fits the historical data set is found. The S-curve model is then further linked to project characteristics using artificial neural networks (ANNs) so that it can be used to forecast waste generation in future construction projects. It was found that, among the S-curve models, cumulative logistic distribution is the best formula to fit the historical data. Meanwhile, contract sum, location, public-private nature, and duration can be used to forecast construction waste generation. The study provides contractors with not only an S-curve model to forecast overall waste generation before a project commences, but also with a detailed baseline to benchmark and manage waste during the course of construction. The major contribution of this paper is to the body of knowledge in the field of construction waste generation forecasting. By examining it with an S-curve model, the study elevates construction waste management to a level equivalent to project cost management where the model has already been readily accepted as a standard tool. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Geographic Information System-based Ecologic Niche Models to Forecast the Risk of Hantavirus Infection in Shandong Province, China

PubMed Central

Wei, Lan; Qian, Quan; Wang, Zhi-Qiang; Glass, Gregory E.; Song, Shao-Xia; Zhang, Wen-Yi; Li, Xiu-Jun; Yang, Hong; Wang, Xian-Jun; Fang, Li-Qun; Cao, Wu-Chun

2011-01-01

Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in Shandong Province, China. In this study, we combined ecologic niche modeling with geographic information systems (GIS) and remote sensing techniques to identify the risk factors and affected areas of hantavirus infections in rodent hosts. Land cover and elevation were found to be closely associated with the presence of hantavirus-infected rodent hosts. The averaged area under the receiver operating characteristic curve was 0.864, implying good performance. The predicted risk maps based on the model were validated both by the hantavirus-infected rodents' distribution and HFRS human case localities with a good fit. These findings have the applications for targeting control and prevention efforts. PMID:21363991

A DBN based anomaly targets detector for HSI

NASA Astrophysics Data System (ADS)

Ma, Ning; Wang, Shaojun; Yu, Jinxiang; Peng, Yu

2017-10-01

Due to the assumption that Hyperspectral image (HSI) should conform to Gaussian distribution, traditional Mahalanobis distance-based anomaly targets detectors perform poor because the assumption may not always hold. In order to solve those problems, a deep learning based detector, Deep Belief Network(DBN) anomaly detector(DBN-AD), was proposed to fit the unknown distribution of HSI by energy modeling, the reconstruction errors of this encode-decode processing are used for discriminating the anomaly targets. Experiments are implemented on real and synthesized HSI dataset which collection by Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS). Comparing to classic anomaly detector, the proposed method shows better performance, it performs about 0.17 higher in Area Under ROC Curve (AUC) than that of Reed-Xiaoli detector(RXD) and Kernel-RXD (K-RXD).

Design and Dynamic Modeling of Flexible Rehabilitation Mechanical Glove

NASA Astrophysics Data System (ADS)

Lin, M. X.; Ma, G. Y.; Liu, F. Q.; Sun, Q. S.; Song, A. Q.

2018-03-01

Rehabilitation gloves are equipment that helps rehabilitation doctors perform finger rehabilitation training, which can greatly reduce the labour intensity of rehabilitation doctors and make more people receive finger rehabilitation training. In the light of the defects of the existing rehabilitation gloves such as complicated structure and stiff movement, a rehabilitation mechanical glove is designed, which provides driving force by using the air cylinder and adopts a rope-spring mechanism to ensure the flexibility of the movement. In order to fit the size of different hands, the bandage ring which can adjust size is used to make the mechanism fixed. In the interest of solve the complex problem of dynamic equation, dynamic simulation is carried out by using Adams to obtain the motion curve, which is easy to optimize the structure of ring position.

Automated Estimation of the Orbital Parameters of Jupiter's Moons

NASA Astrophysics Data System (ADS)

Western, Emma; Ruch, Gerald T.

2016-01-01

Every semester the Physics Department at the University of St. Thomas has the Physics 104 class complete a Jupiter lab. This involves taking around twenty images of Jupiter and its moons with the telescope at the University of St. Thomas Observatory over the course of a few nights. The students then take each image and find the distance from each moon to Jupiter and plot the distances versus the elapsed time for the corresponding image. Students use the plot to fit four sinusoidal curves of the moons of Jupiter. I created a script that automates this process for the professor. It takes the list of images and creates a region file used by the students to measure the distance from the moons to Jupiter, a png image that is the graph of all the data points and the fitted curves of the four moons, and a csv file that contains the list of images, the date and time each image was taken, the elapsed time since the first image, and the distances to Jupiter for Io, Europa, Ganymede, and Callisto. This is important because it lets the professor spend more time working with the students and answering questions as opposed to spending time fitting the curves of the moons on the graph, which can be time consuming.

Calibration and accuracy analysis of a focused plenoptic camera

NASA Astrophysics Data System (ADS)

Zeller, N.; Quint, F.; Stilla, U.

2014-08-01

In this article we introduce new methods for the calibration of depth images from focused plenoptic cameras and validate the results. We start with a brief description of the concept of a focused plenoptic camera and how from the recorded raw image a depth map can be estimated. For this camera, an analytical expression of the depth accuracy is derived for the first time. In the main part of the paper, methods to calibrate a focused plenoptic camera are developed and evaluated. The optical imaging process is calibrated by using a method which is already known from the calibration of traditional cameras. For the calibration of the depth map two new model based methods, which make use of the projection concept of the camera are developed. These new methods are compared to a common curve fitting approach, which is based on Taylor-series-approximation. Both model based methods show significant advantages compared to the curve fitting method. They need less reference points for calibration than the curve fitting method and moreover, supply a function which is valid in excess of the range of calibration. In addition the depth map accuracy of the plenoptic camera was experimentally investigated for different focal lengths of the main lens and is compared to the analytical evaluation.

[Evaluation of uncertainty for determination of tin and its compounds in air of workplace by flame atomic absorption spectrometry].

PubMed

Wei, Qiuning; Wei, Yuan; Liu, Fangfang; Ding, Yalei

2015-10-01

To investigate the method for uncertainty evaluation of determination of tin and its compounds in the air of workplace by flame atomic absorption spectrometry. The national occupational health standards, GBZ/T160.28-2004 and JJF1059-1999, were used to build a mathematical model of determination of tin and its compounds in the air of workplace and to calculate the components of uncertainty. In determination of tin and its compounds in the air of workplace using flame atomic absorption spectrometry, the uncertainty for the concentration of the standard solution, atomic absorption spectrophotometer, sample digestion, parallel determination, least square fitting of the calibration curve, and sample collection was 0.436%, 0.13%, 1.07%, 1.65%, 3.05%, and 2.89%, respectively. The combined uncertainty was 9.3%.The concentration of tin in the test sample was 0.132 mg/m³, and the expanded uncertainty for the measurement was 0.012 mg/m³ (K=2). The dominant uncertainty for determination of tin and its compounds in the air of workplace comes from least squares fitting of the calibration curve and sample collection. Quality control should be improved in the process of calibration curve fitting and sample collection.

Characterization of acid functional groups of carbon dots by nonlinear regression data fitting of potentiometric titration curves

NASA Astrophysics Data System (ADS)

Alves, Larissa A.; de Castro, Arthur H.; de Mendonça, Fernanda G.; de Mesquita, João P.

2016-05-01

The oxygenated functional groups present on the surface of carbon dots with an average size of 2.7 ± 0.5 nm were characterized by a variety of techniques. In particular, we discussed the fit data of potentiometric titration curves using a nonlinear regression method based on the Levenberg-Marquardt algorithm. The results obtained by statistical treatment of the titration curve data showed that the best fit was obtained considering the presence of five Brønsted-Lowry acids on the surface of the carbon dots with constant ionization characteristics of carboxylic acids, cyclic ester, phenolic and pyrone-like groups. The total number of oxygenated acid groups obtained was 5 mmol g-1, with approximately 65% (∼2.9 mmol g-1) originating from groups with pKa < 6. The methodology showed good reproducibility and stability with standard deviations below 5%. The nature of the groups was independent of small variations in experimental conditions, i.e. the mass of carbon dots titrated and initial concentration of HCl solution. Finally, we believe that the methodology used here, together with other characterization techniques, is a simple, fast and powerful tool to characterize the complex acid-base properties of these so interesting and intriguing nanoparticles.

Estimating thermal performance curves from repeated field observations

USGS Publications Warehouse

Childress, Evan; Letcher, Benjamin H.

2017-01-01

Estimating thermal performance of organisms is critical for understanding population distributions and dynamics and predicting responses to climate change. Typically, performance curves are estimated using laboratory studies to isolate temperature effects, but other abiotic and biotic factors influence temperature-performance relationships in nature reducing these models' predictive ability. We present a model for estimating thermal performance curves from repeated field observations that includes environmental and individual variation. We fit the model in a Bayesian framework using MCMC sampling, which allowed for estimation of unobserved latent growth while propagating uncertainty. Fitting the model to simulated data varying in sampling design and parameter values demonstrated that the parameter estimates were accurate, precise, and unbiased. Fitting the model to individual growth data from wild trout revealed high out-of-sample predictive ability relative to laboratory-derived models, which produced more biased predictions for field performance. The field-based estimates of thermal maxima were lower than those based on laboratory studies. Under warming temperature scenarios, field-derived performance models predicted stronger declines in body size than laboratory-derived models, suggesting that laboratory-based models may underestimate climate change effects. The presented model estimates true, realized field performance, avoiding assumptions required for applying laboratory-based models to field performance, which should improve estimates of performance under climate change and advance thermal ecology.

Are the Nonparametric Person-Fit Statistics More Powerful than Their Parametric Counterparts? Revisiting the Simulations in Karabatsos (2003)

ERIC Educational Resources Information Center

Sinharay, Sandip

2017-01-01

Karabatsos compared the power of 36 person-fit statistics using receiver operating characteristics curves and found the "H[superscript T]" statistic to be the most powerful in identifying aberrant examinees. He found three statistics, "C", "MCI", and "U3", to be the next most powerful. These four statistics,…

A microcomputer program for analysis of nucleic acid hybridization data

PubMed Central

Green, S.; Field, J.K.; Green, C.D.; Beynon, R.J.

1982-01-01

The study of nucleic acid hybridization is facilitated by computer mediated fitting of theoretical models to experimental data. This paper describes a non-linear curve fitting program, using the `Patternsearch' algorithm, written in BASIC for the Apple II microcomputer. The advantages and disadvantages of using a microcomputer for local data processing are discussed. Images PMID:7071017

Hearing aid fine-tuning based on Dutch descriptions.

PubMed

Thielemans, Thijs; Pans, Donné; Chenault, Michelene; Anteunis, Lucien

2017-07-01

The aim of this study was to derive an independent fitting assistant based on expert consensus. Two questions were asked: (1) what (Dutch) terms do hearing impaired listeners use nowadays to describe their specific hearing aid fitting problems? (2) What is the expert consensus on how to resolve these complaints by adjusting hearing aid parameters? Hearing aid dispensers provided descriptors that impaired listeners use to describe their reactions to specific hearing aid fitting problems. Hearing aid fitting experts were asked "How would you adjust the hearing aid if its user reports that the aid sounds…?" with the blank filled with each of the 40 most frequently mentioned descriptors. 112 hearing aid dispensers and 15 hearing aid experts. The expert solution with the highest weight value was considered the best solution for that descriptor. Principal component analysis (PCA) was performed to identify a factor structure in fitting problems. Nine fitting problems could be identified resulting in an expert-based, hearing aid manufacturer independent, fine-tuning fitting assistant for clinical use. The construction of an expert-based, hearing aid manufacturer independent, fine-tuning fitting assistant to be used as an additional tool in the iterative fitting process is feasible.

Determination of time of death in forensic science via a 3-D whole body heat transfer model.

PubMed

Bartgis, Catherine; LeBrun, Alexander M; Ma, Ronghui; Zhu, Liang

2016-12-01

This study is focused on developing a whole body heat transfer model to accurately simulate temperature decay in a body postmortem. The initial steady state temperature field is simulated first and the calculated weighted average body temperature is used to determine the overall heat transfer coefficient at the skin surface, based on thermal equilibrium before death. The transient temperature field postmortem is then simulated using the same boundary condition and the temperature decay curves at several body locations are generated for a time frame of 24h. For practical purposes, curve fitting techniques are used to replace the simulations with a proposed exponential formula with an initial time delay. It is shown that the obtained temperature field in the human body agrees very well with that in the literature. The proposed exponential formula provides an excellent fit with an R 2 value larger than 0.998. For the brain and internal organ sites, the initial time delay varies from 1.6 to 2.9h, when the temperature at the measuring site does not change significantly from its original value. The curve-fitted time constant provides the measurement window after death to be between 8h and 31h if the brain site is used, while it increases 60-95% at the internal organ site. The time constant is larger when the body is exposed to colder air, since a person usually wears more clothing when it is cold outside to keep the body warm and comfortable. We conclude that a one-size-fits-all approach would lead to incorrect estimation of time of death and it is crucial to generate a database of cooling curves taking into consideration all the important factors such as body size and shape, environmental conditions, etc., therefore, leading to accurate determination of time of death. Copyright © 2016 Elsevier Ltd. All rights reserved.

A GLOBAL MODEL OF THE LIGHT CURVES AND EXPANSION VELOCITIES OF TYPE II-PLATEAU SUPERNOVAE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pejcha, Ondřej; Prieto, Jose L., E-mail: pejcha@astro.princeton.edu

2015-02-01

We present a new self-consistent and versatile method that derives photospheric radius and temperature variations of Type II-Plateau supernovae based on their expansion velocities and photometric measurements. We apply the method to a sample of 26 well-observed, nearby supernovae with published light curves and velocities. We simultaneously fit ∼230 velocity and ∼6800 mag measurements distributed over 21 photometric passbands spanning wavelengths from 0.19 to 2.2 μm. The light-curve differences among the Type II-Plateau supernovae are well modeled by assuming different rates of photospheric radius expansion, which we explain as different density profiles of the ejecta, and we argue that steeper density profiles resultmore » in flatter plateaus, if everything else remains unchanged. The steep luminosity decline of Type II-Linear supernovae is due to fast evolution of the photospheric temperature, which we verify with a successful fit of SN 1980K. Eliminating the need for theoretical supernova atmosphere models, we obtain self-consistent relative distances, reddenings, and nickel masses fully accounting for all internal model uncertainties and covariances. We use our global fit to estimate the time evolution of any missing band tailored specifically for each supernova, and we construct spectral energy distributions and bolometric light curves. We produce bolometric corrections for all filter combinations in our sample. We compare our model to the theoretical dilution factors and find good agreement for the B and V filters. Our results differ from the theory when the I, J, H, or K bands are included. We investigate the reddening law toward our supernovae and find reasonable agreement with standard R{sub V}∼3.1 reddening law in UBVRI bands. Results for other bands are inconclusive. We make our fitting code publicly available.« less

Pressure effects on the relaxation of an excited nitromethane molecule in an argon bath

NASA Astrophysics Data System (ADS)

Rivera-Rivera, Luis A.; Wagner, Albert F.; Sewell, Thomas D.; Thompson, Donald L.

2015-01-01

Classical molecular dynamics simulations were performed to study the relaxation of nitromethane in an Ar bath (of 1000 atoms) at 300 K and pressures 10, 50, 75, 100, 125, 150, 300, and 400 atm. The molecule was instantaneously excited by statistically distributing 50 kcal/mol among the internal degrees of freedom. At each pressure, 1000 trajectories were integrated for 1000 ps, except for 10 atm, for which the integration time was 5000 ps. The computed ensemble-averaged rotational energy decay is ˜100 times faster than the vibrational energy decay. Both rotational and vibrational decay curves can be satisfactorily fit with the Lendvay-Schatz function, which involves two parameters: one for the initial rate and one for the curvature of the decay curve. The decay curves for all pressures exhibit positive curvature implying the rate slows as the molecule loses energy. The initial rotational relaxation rate is directly proportional to density over the interval of simulated densities, but the initial vibrational relaxation rate decreases with increasing density relative to the extrapolation of the limiting low-pressure proportionality to density. The initial vibrational relaxation rate and curvature are fit as functions of density. For the initial vibrational relaxation rate, the functional form of the fit arises from a combinatorial model for the frequency of nitromethane "simultaneously" colliding with multiple Ar atoms. Roll-off of the initial rate from its low-density extrapolation occurs because the cross section for collision events with L Ar atoms increases with L more slowly than L times the cross section for collision events with one Ar atom. The resulting density-dependent functions of the initial rate and curvature represent, reasonably well, all the vibrational decay curves except at the lowest density for which the functions overestimate the rate of decay. The decay over all gas phase densities is predicted by extrapolating the fits to condensed-phase densities.

Pressure effects on the relaxation of an excited nitromethane molecule in an argon bath

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivera-Rivera, Luis A.; Wagner, Albert F.; Sewell, Thomas D.

2015-01-07

Classical molecular dynamics simulations were performed to study the relaxation of nitromethane in an Ar bath (of 1000 atoms) at 300 K and pressures 10, 50, 75, 100, 125, 150, 300, and 400 atm. The molecule was instantaneously excited by statistically distributing 50 kcal/mol among the internal degrees of freedom. At each pressure, 1000 trajectories were integrated for 1000 ps, except for 10 atm, for which the integration time was 5000 ps. The computed ensemble-averaged rotational energy decay is similar to 100 times faster than the vibrational energy decay. Both rotational and vibrational decay curves can be satisfactorily fit withmore » the Lendvay-Schatz function, which involves two parameters: one for the initial rate and one for the curvature of the decay curve. The decay curves for all pressures exhibit positive curvature implying the rate slows as the molecule loses energy. The initial rotational relaxation rate is directly proportional to density over the interval of simulated densities, but the initial vibrational relaxation rate decreases with increasing density relative to the extrapolation of the limiting low-pressure proportionality to density. The initial vibrational relaxation rate and curvature are fit as functions of density. For the initial vibrational relaxation rate, the functional form of the fit arises from a combinatorial model for the frequency of nitromethane "simultaneously" colliding with multiple Ar atoms. Roll-off of the initial rate from its low-density extrapolation occurs because the cross section for collision events with L Ar atoms increases with L more slowly than L times the cross section for collision events with one Ar atom. The resulting density-dependent functions of the initial rate and curvature represent, reasonably well, all the vibrational decay curves except at the lowest density for which the functions overestimate the rate of decay. The decay over all gas phase densities is predicted by extrapolating the fits to condensed-phase densities. (C) 2015 AIP Publishing LLC.« less

Pressure effects on the relaxation of an excited nitromethane molecule in an argon bath.

PubMed

Rivera-Rivera, Luis A; Wagner, Albert F; Sewell, Thomas D; Thompson, Donald L

2015-01-07

Classical molecular dynamics simulations were performed to study the relaxation of nitromethane in an Ar bath (of 1000 atoms) at 300 K and pressures 10, 50, 75, 100, 125, 150, 300, and 400 atm. The molecule was instantaneously excited by statistically distributing 50 kcal/mol among the internal degrees of freedom. At each pressure, 1000 trajectories were integrated for 1000 ps, except for 10 atm, for which the integration time was 5000 ps. The computed ensemble-averaged rotational energy decay is ∼100 times faster than the vibrational energy decay. Both rotational and vibrational decay curves can be satisfactorily fit with the Lendvay-Schatz function, which involves two parameters: one for the initial rate and one for the curvature of the decay curve. The decay curves for all pressures exhibit positive curvature implying the rate slows as the molecule loses energy. The initial rotational relaxation rate is directly proportional to density over the interval of simulated densities, but the initial vibrational relaxation rate decreases with increasing density relative to the extrapolation of the limiting low-pressure proportionality to density. The initial vibrational relaxation rate and curvature are fit as functions of density. For the initial vibrational relaxation rate, the functional form of the fit arises from a combinatorial model for the frequency of nitromethane "simultaneously" colliding with multiple Ar atoms. Roll-off of the initial rate from its low-density extrapolation occurs because the cross section for collision events with L Ar atoms increases with L more slowly than L times the cross section for collision events with one Ar atom. The resulting density-dependent functions of the initial rate and curvature represent, reasonably well, all the vibrational decay curves except at the lowest density for which the functions overestimate the rate of decay. The decay over all gas phase densities is predicted by extrapolating the fits to condensed-phase densities.

Pressure effects on the relaxation of an excited nitromethane molecule in an argon bath

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivera-Rivera, Luis A.; Sewell, Thomas D.; Thompson, Donald L.

2015-01-07

Classical molecular dynamics simulations were performed to study the relaxation of nitromethane in an Ar bath (of 1000 atoms) at 300 K and pressures 10, 50, 75, 100, 125, 150, 300, and 400 atm. The molecule was instantaneously excited by statistically distributing 50 kcal/mol among the internal degrees of freedom. At each pressure, 1000 trajectories were integrated for 1000 ps, except for 10 atm, for which the integration time was 5000 ps. The computed ensemble-averaged rotational energy decay is ∼100 times faster than the vibrational energy decay. Both rotational and vibrational decay curves can be satisfactorily fit with the Lendvay-Schatzmore » function, which involves two parameters: one for the initial rate and one for the curvature of the decay curve. The decay curves for all pressures exhibit positive curvature implying the rate slows as the molecule loses energy. The initial rotational relaxation rate is directly proportional to density over the interval of simulated densities, but the initial vibrational relaxation rate decreases with increasing density relative to the extrapolation of the limiting low-pressure proportionality to density. The initial vibrational relaxation rate and curvature are fit as functions of density. For the initial vibrational relaxation rate, the functional form of the fit arises from a combinatorial model for the frequency of nitromethane “simultaneously” colliding with multiple Ar atoms. Roll-off of the initial rate from its low-density extrapolation occurs because the cross section for collision events with L Ar atoms increases with L more slowly than L times the cross section for collision events with one Ar atom. The resulting density-dependent functions of the initial rate and curvature represent, reasonably well, all the vibrational decay curves except at the lowest density for which the functions overestimate the rate of decay. The decay over all gas phase densities is predicted by extrapolating the fits to condensed-phase densities.« less

FIT: Computer Program that Interactively Determines Polynomial Equations for Data which are a Function of Two Independent Variables

NASA Technical Reports Server (NTRS)

Arbuckle, P. D.; Sliwa, S. M.; Roy, M. L.; Tiffany, S. H.

1985-01-01

A computer program for interactively developing least-squares polynomial equations to fit user-supplied data is described. The program is characterized by the ability to compute the polynomial equations of a surface fit through data that are a function of two independent variables. The program utilizes the Langley Research Center graphics packages to display polynomial equation curves and data points, facilitating a qualitative evaluation of the effectiveness of the fit. An explanation of the fundamental principles and features of the program, as well as sample input and corresponding output, are included.

IPMP Global Fit - A one-step direct data analysis tool for predictive microbiology.

PubMed

Huang, Lihan

2017-12-04

The objective of this work is to develop and validate a unified optimization algorithm for performing one-step global regression analysis of isothermal growth and survival curves for determination of kinetic parameters in predictive microbiology. The algorithm is incorporated with user-friendly graphical interfaces (GUIs) to develop a data analysis tool, the USDA IPMP-Global Fit. The GUIs are designed to guide the users to easily navigate through the data analysis process and properly select the initial parameters for different combinations of mathematical models. The software is developed for one-step kinetic analysis to directly construct tertiary models by minimizing the global error between the experimental observations and mathematical models. The current version of the software is specifically designed for constructing tertiary models with time and temperature as the independent model parameters in the package. The software is tested with a total of 9 different combinations of primary and secondary models for growth and survival of various microorganisms. The results of data analysis show that this software provides accurate estimates of kinetic parameters. In addition, it can be used to improve the experimental design and data collection for more accurate estimation of kinetic parameters. IPMP-Global Fit can be used in combination with the regular USDA-IPMP for solving the inverse problems and developing tertiary models in predictive microbiology. Published by Elsevier B.V.

Explicitly solvable complex Chebyshev approximation problems related to sine polynomials

NASA Technical Reports Server (NTRS)

Freund, Roland

1989-01-01

Explicitly solvable real Chebyshev approximation problems on the unit interval are typically characterized by simple error curves. A similar principle is presented for complex approximation problems with error curves induced by sine polynomials. As an application, some new explicit formulae for complex best approximations are derived.

Effects of the Use of Millimeter Waves on the Statistics of Writer-to-Reader Delays in Military Communications Systems,

DTIC Science & Technology

1980-12-01

distributions of Figs. 3 and 4 may be fitted quit, accurately by broken straight lines. If we had plotted the differential distributions directly...collection process. These fluctuations are smoothed by replacing the actual differential distribution by the derivative of the fitted broken-line lognormal...for each interval T. The constants in the distribution for each broken section of the lognormal approximations are found by fitting lines to the curve

Curve fitting and modeling with splines using statistical variable selection techniques

NASA Technical Reports Server (NTRS)

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.

A curve-fitting approach to estimate the arterial plasma input function for the assessment of glucose metabolic rate and response to treatment.

PubMed

Vriens, Dennis; de Geus-Oei, Lioe-Fee; Oyen, Wim J G; Visser, Eric P

2009-12-01

For the quantification of dynamic (18)F-FDG PET studies, the arterial plasma time-activity concentration curve (APTAC) needs to be available. This can be obtained using serial sampling of arterial blood or an image-derived input function (IDIF). Arterial sampling is invasive and often not feasible in practice; IDIFs are biased because of partial-volume effects and cannot be used when no large arterial blood pool is in the field of view. We propose a mathematic function, consisting of an initial linear rising activity concentration followed by a triexponential decay, to describe the APTAC. This function was fitted to 80 oncologic patients and verified for 40 different oncologic patients by area-under-the-curve (AUC) comparison, Patlak glucose metabolic rate (MR(glc)) estimation, and therapy response monitoring (Delta MR(glc)). The proposed function was compared with the gold standard (serial arterial sampling) and the IDIF. To determine the free parameters of the function, plasma time-activity curves based on arterial samples in 80 patients were fitted after normalization for administered activity (AA) and initial distribution volume (iDV) of (18)F-FDG. The medians of these free parameters were used for the model. In 40 other patients (20 baseline and 20 follow-up dynamic (18)F-FDG PET scans), this model was validated. The population-based curve, individually calibrated by AA and iDV (APTAC(AA/iDV)), by 1 late arterial sample (APTAC(1 sample)), and by the individual IDIF (APTAC(IDIF)), was compared with the gold standard of serial arterial sampling (APTAC(sampled)) using the AUC. Additionally, these 3 methods of APTAC determination were evaluated with Patlak MR(glc) estimation and with Delta MR(glc) for therapy effects using serial sampling as the gold standard. Excellent individual fits to the function were derived with significantly different decay constants (P < 0.001). Correlations between AUC from APTAC(AA/iDV), APTAC(1 sample), and APTAC(IDIF) with the gold standard (APTAC(sampled)) were 0.880, 0.994, and 0.856, respectively. For MR(glc), these correlations were 0.963, 0.994, and 0.966, respectively. In response monitoring, these correlations were 0.947, 0.982, and 0.949, respectively. Additional scaling by 1 late arterial sample showed a significant improvement (P < 0.001). The fitted input function calibrated for AA and iDV performed similarly to IDIF. Performance improved significantly using 1 late arterial sample. The proposed model can be used when an IDIF is not available or when serial arterial sampling is not feasible.

Co-evolution for Problem Simplification

NASA Technical Reports Server (NTRS)

Haith, Gary L.; Lohn, Jason D.; Cplombano, Silvano P.; Stassinopoulos, Dimitris

1999-01-01

This paper explores a co-evolutionary approach applicable to difficult problems with limited failure/success performance feedback. Like familiar "predator-prey" frameworks this algorithm evolves two populations of individuals - the solutions (predators) and the problems (prey). The approach extends previous work by rewarding only the problems that match their difficulty to the level of solut,ion competence. In complex problem domains with limited feedback, this "tractability constraint" helps provide an adaptive fitness gradient that, effectively differentiates the candidate solutions. The algorithm generates selective pressure toward the evolution of increasingly competent solutions by rewarding solution generality and uniqueness and problem tractability and difficulty. Relative (inverse-fitness) and absolute (static objective function) approaches to evaluating problem difficulty are explored and discussed. On a simple control task, this co-evolutionary algorithm was found to have significant advantages over a genetic algorithm with either a static fitness function or a fitness function that changes on a hand-tuned schedule.

Adequacy assessment of mathematical models in the dynamics of litter decomposition in a tropical forest Mosaic Atlantic, in southeastern Brazil.

PubMed

Nunes, F P; Garcia, Q S

2015-05-01

The study of litter decomposition and nutrient cycling is essential to know native forests structure and functioning. Mathematical models can help to understand the local and temporal litter fall variations and their environmental variables relationships. The objective of this study was test the adequacy of mathematical models for leaf litter decomposition in the Atlantic Forest in southeastern Brazil. We study four native forest sites in Parque Estadual do Rio Doce, a Biosphere Reserve of the Atlantic, which were installed 200 bags of litter decomposing with 20 × 20 cm nylon screen of 2 mm, with 10 grams of litter. Monthly from 09/2007 to 04/2009, 10 litterbags were removed for determination of the mass loss. We compared 3 nonlinear models: 1 - Olson Exponential Model (1963), which considers the constant K, 2 - Model proposed by Fountain and Schowalter (2004), 3 - Model proposed by Coelho and Borges (2005), which considers the variable K through QMR, SQR, SQTC, DMA and Test F. The Fountain and Schowalter (2004) model was inappropriate for this study by overestimating decomposition rate. The decay curve analysis showed that the model with the variable K was more appropriate, although the values of QMR and DMA revealed no significant difference (p > 0.05) between the models. The analysis showed a better adjustment of DMA using K variable, reinforced by the values of the adjustment coefficient (R2). However, convergence problems were observed in this model for estimate study areas outliers, which did not occur with K constant model. This problem can be related to the non-linear fit of mass/time values to K variable generated. The model with K constant shown to be adequate to describe curve decomposition for separately areas and best adjustability without convergence problems. The results demonstrated the adequacy of Olson model to estimate tropical forest litter decomposition. Although use of reduced number of parameters equaling the steps of the decomposition process, no difficulties of convergence were observed in Olson model. So, this model can be used to describe decomposition curves in different types of environments, estimating K appropriately.

Planned Missing Designs to Optimize the Efficiency of Latent Growth Parameter Estimates

ERIC Educational Resources Information Center

Rhemtulla, Mijke; Jia, Fan; Wu, Wei; Little, Todd D.

2014-01-01

We examine the performance of planned missing (PM) designs for correlated latent growth curve models. Using simulated data from a model where latent growth curves are fitted to two constructs over five time points, we apply three kinds of planned missingness. The first is item-level planned missingness using a three-form design at each wave such…

The Impact of Student Teaching Experience on Pre-Service Teachers' Readiness for Technology Integration: A Mixed Methods Study with Growth Curve Modeling

ERIC Educational Resources Information Center

Sun, Yan; Strobel, Johannes; Newby, Timothy J.

2017-01-01

Adopting a two-phase explanatory sequential mixed methods research design, the current study examined the impact of student teaching experiences on pre-service teachers' readiness for technology integration. In phase-1 of quantitative investigation, 2-level growth curve models were fitted using online repeated measures survey data collected from…

Observing globular cluster RR Lyraes with the BYU West Mountain Observatory

NASA Astrophysics Data System (ADS)

Jeffery, E. J.; Joner, M. D.; Walton, R. S.

2016-05-01

We have utilized the 0.9-meter telescope of the Brigham Young University West Mountain Observatory to secure data on six northern hemi- sphere globular clusters. Here we present observations of RR Lyrae stars located in these clusters. We compare light curves produced using both DAOPHOT and ISIS software packages. Light curve fitting is done with FITLC.

Solutions for Determining the Significance Region Using the Johnson-Neyman Type Procedure in Generalized Linear (Mixed) Models

ERIC Educational Resources Information Center

Lazar, Ann A.; Zerbe, Gary O.

2011-01-01

Researchers often compare the relationship between an outcome and covariate for two or more groups by evaluating whether the fitted regression curves differ significantly. When they do, researchers need to determine the "significance region," or the values of the covariate where the curves significantly differ. In analysis of covariance (ANCOVA),…

Four points function fitted and first derivative procedure for determining the end points in potentiometric titration curves: statistical analysis and method comparison.

PubMed

Kholeif, S A

2001-06-01

A new method that belongs to the differential category for determining the end points from potentiometric titration curves is presented. It uses a preprocess to find first derivative values by fitting four data points in and around the region of inflection to a non-linear function, and then locate the end point, usually as a maximum or minimum, using an inverse parabolic interpolation procedure that has an analytical solution. The behavior and accuracy of the sigmoid and cumulative non-linear functions used are investigated against three factors. A statistical evaluation of the new method using linear least-squares method validation and multifactor data analysis are covered. The new method is generally applied to symmetrical and unsymmetrical potentiometric titration curves, and the end point is calculated using numerical procedures only. It outperforms the "parent" regular differential method in almost all factors levels and gives accurate results comparable to the true or estimated true end points. Calculated end points from selected experimental titration curves compatible with the equivalence point category of methods, such as Gran or Fortuin, are also compared with the new method.

Comparison of Three Methods for Wind Turbine Capacity Factor Estimation

PubMed Central

Ditkovich, Y.; Kuperman, A.

2014-01-01

Three approaches to calculating capacity factor of fixed speed wind turbines are reviewed and compared using a case study. The first “quasiexact” approach utilizes discrete wind raw data (in the histogram form) and manufacturer-provided turbine power curve (also in discrete form) to numerically calculate the capacity factor. On the other hand, the second “analytic” approach employs a continuous probability distribution function, fitted to the wind data as well as continuous turbine power curve, resulting from double polynomial fitting of manufacturer-provided power curve data. The latter approach, while being an approximation, can be solved analytically thus providing a valuable insight into aspects, affecting the capacity factor. Moreover, several other merits of wind turbine performance may be derived based on the analytical approach. The third “approximate” approach, valid in case of Rayleigh winds only, employs a nonlinear approximation of the capacity factor versus average wind speed curve, only requiring rated power and rotor diameter of the turbine. It is shown that the results obtained by employing the three approaches are very close, enforcing the validity of the analytically derived approximations, which may be used for wind turbine performance evaluation. PMID:24587755

An Algorithm for Protein Helix Assignment Using Helix Geometry

PubMed Central

Cao, Chen; Xu, Shutan; Wang, Lincong

2015-01-01

Helices are one of the most common and were among the earliest recognized secondary structure elements in proteins. The assignment of helices in a protein underlies the analysis of its structure and function. Though the mathematical expression for a helical curve is simple, no previous assignment programs have used a genuine helical curve as a model for helix assignment. In this paper we present a two-step assignment algorithm. The first step searches for a series of bona fide helical curves each one best fits the coordinates of four successive backbone Cα atoms. The second step uses the best fit helical curves as input to make helix assignment. The application to the protein structures in the PDB (protein data bank) proves that the algorithm is able to assign accurately not only regular α-helix but also 310 and π helices as well as their left-handed versions. One salient feature of the algorithm is that the assigned helices are structurally more uniform than those by the previous programs. The structural uniformity should be useful for protein structure classification and prediction while the accurate assignment of a helix to a particular type underlies structure-function relationship in proteins. PMID:26132394

TYPE Ia SUPERNOVA DISTANCE MODULUS BIAS AND DISPERSION FROM K-CORRECTION ERRORS: A DIRECT MEASUREMENT USING LIGHT CURVE FITS TO OBSERVED SPECTRAL TIME SERIES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saunders, C.; Aldering, G.; Aragon, C.

2015-02-10

We estimate systematic errors due to K-corrections in standard photometric analyses of high-redshift Type Ia supernovae. Errors due to K-correction occur when the spectral template model underlying the light curve fitter poorly represents the actual supernova spectral energy distribution, meaning that the distance modulus cannot be recovered accurately. In order to quantify this effect, synthetic photometry is performed on artificially redshifted spectrophotometric data from 119 low-redshift supernovae from the Nearby Supernova Factory, and the resulting light curves are fit with a conventional light curve fitter. We measure the variation in the standardized magnitude that would be fit for a givenmore » supernova if located at a range of redshifts and observed with various filter sets corresponding to current and future supernova surveys. We find significant variation in the measurements of the same supernovae placed at different redshifts regardless of filters used, which causes dispersion greater than ∼0.05 mag for measurements of photometry using the Sloan-like filters and a bias that corresponds to a 0.03 shift in w when applied to an outside data set. To test the result of a shift in supernova population or environment at higher redshifts, we repeat our calculations with the addition of a reweighting of the supernovae as a function of redshift and find that this strongly affects the results and would have repercussions for cosmology. We discuss possible methods to reduce the contribution of the K-correction bias and uncertainty.« less

Evaluation and Analysis of Urmia Lake Water Level Fluctuations Bettwen 1998-2006 Using Landsat Images and TOPEX Altimetry Data

NASA Astrophysics Data System (ADS)

Zahir, N.; Ali, A.

2015-12-01

The Lake Urmiah has undergone a drastic shrinkage in size over the past few decades. The initial intention of this paper is to present an approach for determining the so called "salient times" during which the trend of the shrinkage process is accelerated or decelerated. To find these salient times, a quasi_continuous curve was optimally fitted to the Topex altimetry data within the period 1998 to 2006. To find the salient points within this period of time, the points of inflections of the fitted curve is computed using a second derivative approach. The water volume was also computed using 16 cloud free Landsat images of the Lake within the periods of 1998 to 2006. In the first stage of the water volume calculation, the pixels of the Lake were segmented using the Automated Water Extraction Index (AWEI) and the shorelines of the Lake were extracted by a boundary detecting operator using the generated binary image of the Lake surface. The water volume fluctuation rate was then computed under the assumption that the two successive Lake surfaces and their corresponding water level differences demonstrate approximately a truncated pyramid. The analysis of the water level fluctuation rates were further extended by a sinusoidal curve fitted to the Topex altimetry data. This curve was intended to model the seasonal fluctuations of the water level. In the final stage of this article, the correlation between the fluctuation rates and the precipitation and temperature variations were also numerically determined. This paper reports in some details the stages mentioned above.

ON THE ROTATION SPEED OF THE MILKY WAY DETERMINED FROM H i EMISSION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reid, M. J.; Dame, T. M.

2016-12-01

The circular rotation speed of the Milky Way at the solar radius, Θ{sub 0}, has been estimated to be 220 km s{sup −1} by fitting the maximum velocity of H i emission as a function of Galactic longitude. This result is in tension with a recent estimate of Θ{sub 0} = 240 km s{sup −1}, based on Very Long Baseline Interferometry (VLBI) parallaxes and proper motions from the BeSSeL and VERA surveys for large numbers of high-mass star-forming regions across the Milky Way. We find that the rotation curve best fitted to the VLBI data is slightly curved, and that this curvaturemore » results in a biased estimate of Θ{sub 0} from the H i data when a flat rotation curve is assumed. This relieves the tension between the methods and favors Θ{sub 0} = 240 km s{sup −1}.« less

Applying Biometric Growth Curve Models to Developmental Synchronies in Cognitive Development: The Louisville Twin Study.

PubMed

Finkel, Deborah; Davis, Deborah Winders; Turkheimer, Eric; Dickens, William T

2015-11-01

Biometric latent growth curve models were applied to data from the LTS in order to replicate and extend Wilson's (Child Dev 54:298-316, 1983) findings. Assessments of cognitive development were available from 8 measurement occasions covering the period 4-15 years for 1032 individuals. Latent growth curve models were fit to percent correct for 7 subscales: information, similarities, arithmetic, vocabulary, comprehension, picture completion, and block design. Models were fit separately to WPPSI (ages 4-6 years) and WISC-R (ages 7-15). Results indicated the expected increases in heritability in younger childhood, and plateaus in heritability as children reached age 10 years. Heritability of change, per se (slope estimates), varied dramatically across domains. Significant genetic influences on slope parameters that were independent of initial levels of performance were found for only information and picture completion subscales. Thus evidence for both genetic continuity and genetic innovation in the development of cognitive abilities in childhood were found.

A geometry package for generation of input data for a three-dimensional potential-flow program

NASA Technical Reports Server (NTRS)

Halsey, N. D.; Hess, J. L.

1978-01-01

The preparation of geometric data for input to three-dimensional potential flow programs was automated and simplified by a geometry package incorporated into the NASA Langley version of the 3-D lifting potential flow program. Input to the computer program for the geometry package consists of a very sparse set of coordinate data, often with an order of magnitude of fewer points than required for the actual potential flow calculations. Isolated components, such as wings, fuselages, etc. are paneled automatically, using one of several possible element distribution algorithms. Curves of intersection between components are calculated, using a hybrid curve-fit/surface-fit approach. Intersecting components are repaneled so that adjacent elements on either side of the intersection curves line up in a satisfactory manner for the potential-flow calculations. Many cases may be run completely (from input, through the geometry package, and through the flow calculations) without interruption. Use of the package significantly reduces the time and expense involved in making three-dimensional potential flow calculations.

Ten years in the library: new data confirm paleontological patterns

NASA Technical Reports Server (NTRS)

Sepkoski, J. J. Jr; Sepkoski JJ, J. r. (Principal Investigator)

1993-01-01

A comparison is made between compilations of times of origination and extinction of fossil marine animal families published in 1982 and 1992. As a result of ten years of library research, half of the information in the compendia has changed: families have been added and deleted, low-resolution stratigraphic data been improved, and intervals of origination and extinction have been altered. Despite these changes, apparent macroevolutionary patterns for the entire marine fauna have remained constant. Diversity curves compiled from the two data bases are very similar, with a goodness-of-fit of 99%; the principal difference is that the 1992 curve averages 13% higher than the older curve. Both numbers and percentages of origination and extinction also match well, with fits ranging from 83% to 95%. All major events of radiation and extinction are identical. Therefore, errors in large paleontological data bases and arbitrariness of included taxa are not necessarily impediments to the analysis of pattern in the fossil record, so long as the data are sufficiently numerous.

Better P-curves: Making P-curve analysis more robust to errors, fraud, and ambitious P-hacking, a Reply to Ulrich and Miller (2015).

PubMed

Simonsohn, Uri; Simmons, Joseph P; Nelson, Leif D

2015-12-01

When studies examine true effects, they generate right-skewed p-curves, distributions of statistically significant results with more low (.01 s) than high (.04 s) p values. What else can cause a right-skewed p-curve? First, we consider the possibility that researchers report only the smallest significant p value (as conjectured by Ulrich & Miller, 2015), concluding that it is a very uncommon problem. We then consider more common problems, including (a) p-curvers selecting the wrong p values, (b) fake data, (c) honest errors, and (d) ambitiously p-hacked (beyond p < .05) results. We evaluate the impact of these common problems on the validity of p-curve analysis, and provide practical solutions that substantially increase its robustness. (c) 2015 APA, all rights reserved).

Bayesian inference in an item response theory model with a generalized student t link function

NASA Astrophysics Data System (ADS)

Azevedo, Caio L. N.; Migon, Helio S.

2012-10-01

In this paper we introduce a new item response theory (IRT) model with a generalized Student t-link function with unknown degrees of freedom (df), named generalized t-link (GtL) IRT model. In this model we consider only the difficulty parameter in the item response function. GtL is an alternative to the two parameter logit and probit models, since the degrees of freedom (df) play a similar role to the discrimination parameter. However, the behavior of the curves of the GtL is different from those of the two parameter models and the usual Student t link, since in GtL the curve obtained from different df's can cross the probit curves in more than one latent trait level. The GtL model has similar proprieties to the generalized linear mixed models, such as the existence of sufficient statistics and easy parameter interpretation. Also, many techniques of parameter estimation, model fit assessment and residual analysis developed for that models can be used for the GtL model. We develop fully Bayesian estimation and model fit assessment tools through a Metropolis-Hastings step within Gibbs sampling algorithm. We consider a prior sensitivity choice concerning the degrees of freedom. The simulation study indicates that the algorithm recovers all parameters properly. In addition, some Bayesian model fit assessment tools are considered. Finally, a real data set is analyzed using our approach and other usual models. The results indicate that our model fits the data better than the two parameter models.

Creep and Creep Recovery Response of Load Cells Tested According to U.S. and International Evaluation Procedures

PubMed Central

Bartel, Thomas W.; Yaniv, Simone L.

1997-01-01

The 60 min creep data from National Type Evaluation Procedure (NTEP) tests performed at the National Institute of Standards and Technology (NIST) on 65 load cells have been analyzed in order to compare their creep and creep recovery responses, and to compare the 60 min creep with creep over shorter time periods. To facilitate this comparison the data were fitted to a multiple-term exponential equation, which adequately describes the creep and creep recovery responses of load cells. The use of such a curve fit reduces the effect of the random error in the indicator readings on the calculated values of the load cell creep. Examination of the fitted curves show that the creep recovery responses, after inversion by a change in sign, are generally similar in shape to the creep response, but smaller in magnitude. The average ratio of the absolute value of the maximum creep recovery to the maximum creep is 0.86; however, no reliable correlation between creep and creep recovery can be drawn from the data. The fitted curves were also used to compare the 60 min creep of the NTEP analysis with the 30 min creep and other parameters calculated according to the Organization Internationale de Métrologie Légale (OIML) R 60 analysis. The average ratio of the 30 min creep value to the 60 min value is 0.84. The OIML class C creep tolerance is less than 0.5 of the NTEP tolerance for classes III and III L. PMID:27805151

Open-path FTIR data reduction algorithm with atmospheric absorption corrections: the NONLIN code

NASA Astrophysics Data System (ADS)

Phillips, William; Russwurm, George M.

1999-02-01

This paper describes the progress made to date in developing, testing, and refining a data reduction computer code, NONLIN, that alleviates many of the difficulties experienced in the analysis of open path FTIR data. Among the problems that currently effect FTIR open path data quality are: the inability to obtain a true I degree or background, spectral interferences of atmospheric gases such as water vapor and carbon dioxide, and matching the spectral resolution and shift of the reference spectra to a particular field instrument. This algorithm is based on a non-linear fitting scheme and is therefore not constrained by many of the assumptions required for the application of linear methods such as classical least squares (CLS). As a result, a more realistic mathematical model of the spectral absorption measurement process can be employed in the curve fitting process. Applications of the algorithm have proven successful in circumventing open path data reduction problems. However, recent studies, by one of the authors, of the temperature and pressure effects on atmospheric absorption indicate there exist temperature and water partial pressure effects that should be incorporated into the NONLIN algorithm for accurate quantification of gas concentrations. This paper investigates the sources of these phenomena. As a result of this study a partial pressure correction has been employed in NONLIN computer code. Two typical field spectra are examined to determine what effect the partial pressure correction has on gas quantification.

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †

PubMed Central

Zhang, Meiyan; Zheng, Yahong Rosa

2017-01-01

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X−Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem. PMID:28696377

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †.

PubMed

Cai, Wenyu; Zhang, Meiyan; Zheng, Yahong Rosa

2017-07-11

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X - Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.

Estimating sunspot number

NASA Technical Reports Server (NTRS)

Wilson, R. M.; Reichmann, E. J.; Teuber, D. L.

1984-01-01

An empirical method is developed to predict certain parameters of future solar activity cycles. Sunspot cycle statistics are examined, and curve fitting and linear regression analysis techniques are utilized.

A new analytical method for estimating lumped parameter constants of linear viscoelastic models from strain rate tests

NASA Astrophysics Data System (ADS)

Mattei, G.; Ahluwalia, A.

2018-04-01

We introduce a new function, the apparent elastic modulus strain-rate spectrum, E_{app} ( \\dot{ɛ} ), for the derivation of lumped parameter constants for Generalized Maxwell (GM) linear viscoelastic models from stress-strain data obtained at various compressive strain rates ( \\dot{ɛ}). The E_{app} ( \\dot{ɛ} ) function was derived using the tangent modulus function obtained from the GM model stress-strain response to a constant \\dot{ɛ} input. Material viscoelastic parameters can be rapidly derived by fitting experimental E_{app} data obtained at different strain rates to the E_{app} ( \\dot{ɛ} ) function. This single-curve fitting returns similar viscoelastic constants as the original epsilon dot method based on a multi-curve global fitting procedure with shared parameters. Its low computational cost permits quick and robust identification of viscoelastic constants even when a large number of strain rates or replicates per strain rate are considered. This method is particularly suited for the analysis of bulk compression and nano-indentation data of soft (bio)materials.

Calibrating nadir striped artifacts in a multibeam backscatter image using the equal mean-variance fitting model

NASA Astrophysics Data System (ADS)

Yang, Fanlin; Zhao, Chunxia; Zhang, Kai; Feng, Chengkai; Ma, Yue

2017-07-01

Acoustic seafloor classification with multibeam backscatter measurements is an attractive approach for mapping seafloor properties over a large area. However, artifacts in the multibeam backscatter measurements prevent accurate characterization of the seafloor. In particular, the backscatter level is extremely strong and highly variable in the near-nadir region due to the specular echo phenomenon. Consequently, striped artifacts emerge in the backscatter image, which can degrade the classification accuracy. This study focuses on the striped artifacts in multibeam backscatter images. To this end, a calibration algorithm based on equal mean-variance fitting is developed. By fitting the local shape of the angular response curve, the striped artifacts are compressed and moved according to the relations between the mean and variance in the near-nadir and off-nadir region. The algorithm utilized the measured data of near-nadir region and retained the basic shape of the response curve. The experimental results verify the high performance of the proposed method.

Liquid-vapor relations for the system NaCl-H2O: summary of the P-T- x surface from 300° to 500°C

USGS Publications Warehouse

Bischoff, J.L.; Pitzer, Kenneth S.

1989-01-01

Experimental data on the vapor-liquid equilibrium relations for the system NaCl-H2O were compiled and compared in order to provide an improved estimate of the P-T-x surface between 300° to 500°C, a range for which the system changes from subcritical to critical behavior. Data for the three-phase curve (halite + liquid + vapor) and the NaCl-H2O critical curve were evaluated, and the best fits for these extrema then were used to guide selection of best fit for isothermal plots for the vapor-liquid region in-between. Smoothing was carried out in an iterative procedure by replotting the best-fit data as isobars and then as isopleths, until an internally consistent set of data was obtained. The results are presented in table form that will have application to theoretical modelling and to the understanding of two-phase behavior in saline geothermal systems.

Understanding the relationship between duration of untreated psychosis and outcomes: A statistical perspective.

PubMed

Hannigan, Ailish; Bargary, Norma; Kinsella, Anthony; Clarke, Mary

2017-06-14

Although the relationships between duration of untreated psychosis (DUP) and outcomes are often assumed to be linear, few studies have explored the functional form of these relationships. The aim of this study is to demonstrate the potential of recent advances in curve fitting approaches (splines) to explore the form of the relationship between DUP and global assessment of functioning (GAF). Curve fitting approaches were used in models to predict change in GAF at long-term follow-up using DUP for a sample of 83 individuals with schizophrenia. The form of the relationship between DUP and GAF was non-linear. Accounting for non-linearity increased the percentage of variance in GAF explained by the model, resulting in better prediction and understanding of the relationship. The relationship between DUP and outcomes may be complex and model fit may be improved by accounting for the form of the relationship. This should be routinely assessed and new statistical approaches for non-linear relationships exploited, if appropriate. © 2017 John Wiley & Sons Australia, Ltd.

No-threshold dose-response curves for nongenotoxic chemicals: Findings and applications for risk assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheehan, Daniel M.

2006-01-15

We tested the hypothesis that no threshold exists when estradiol acts through the same mechanism as an active endogenous estrogen. A Michaelis-Menten (MM) equation accounting for response saturation, background effects, and endogenous estrogen level fit a turtle sex-reversal data set with no threshold and estimated the endogenous dose. Additionally, 31 diverse literature dose-response data sets were analyzed by adding a term for nonhormonal background; good fits were obtained but endogenous dose estimations were not significant due to low resolving power. No thresholds were observed. Data sets were plotted using a normalized MM equation; all 178 data points were accommodated onmore » a single graph. Response rates from {approx}1% to >95% were well fit. The findings contradict the threshold assumption and low-dose safety. Calculating risk and assuming additivity of effects from multiple chemicals acting through the same mechanism rather than assuming a safe dose for nonthresholded curves is appropriate.« less

Soil Water Characteristics of Cores from Low- and High-Centered Polygons, Barrow, Alaska, 2012

DOE Data Explorer

Graham, David; Moon, Ji-Won

2016-08-22

This dataset includes soil water characteristic curves for soil and permafrost in two representative frozen cores collected from a high-center polygon (HCP) and a low-center polygon (LCP) from the Barrow Environmental Observatory. Data include soil water content and soil water potential measured using the simple evaporation method for hydrological and biogeochemical simulations and experimental data analysis. Data can be used to generate a soil moisture characteristic curve, which can be fit to a variety of hydrological functions to infer critical parameters for soil physics. Considering the measured the soil water properties, the van Genuchten model predicted well the HCP, in contrast, the Kosugi model well fitted LCP which had more saturated condition.

Modal analysis using a Fourier analyzer, curve-fitting, and modal tuning

NASA Technical Reports Server (NTRS)

Craig, R. R., Jr.; Chung, Y. T.

1981-01-01

The proposed modal test program differs from single-input methods in that preliminary data may be acquired using multiple inputs, and modal tuning procedures may be employed to define closely spaced frquency modes more accurately or to make use of frequency response functions (FRF's) which are based on several input locations. In some respects the proposed modal test proram resembles earlier sine-sweep and sine-dwell testing in that broadband FRF's are acquired using several input locations, and tuning is employed to refine the modal parameter estimates. The major tasks performed in the proposed modal test program are outlined. Data acquisition and FFT processing, curve fitting, and modal tuning phases are described and examples are given to illustrate and evaluate them.

Operation SANDSTONE. Nuclear Explosions 1948, Scientific Director’s Report of Atomic Weapon Tests. Annex 9, Parts 1, 2, 3, 4 and 5. Contamination Studies

DTIC Science & Technology

1949-01-01

de - cay curves. The fit depended on the points chosen for the determination of K and L and by a suitable choice a -12- reasonably good fit could be...the previous test the crater de - cal curves indicate a mixture of Na24 and fission products. Ot)ier active materials may be present for observed...IVT N N 4-1 ui ui 0 i ’ T ; -mW 1 310 X--SH R TI ’ De A?--ŘZ (u E I EFT HAND SCA tf; t: iliT, M160 20 40 60 so 100 120 1*0 0 100 200 300 400 500 600

Tensile stress-strain behavior of graphite/epoxy laminates

NASA Technical Reports Server (NTRS)

Garber, D. P.

1982-01-01

The tensile stress-strain behavior of a variety of graphite/epoxy laminates was examined. Longitudinal and transverse specimens from eleven different layups were monotonically loaded in tension to failure. Ultimate strength, ultimate strain, and strss-strain curves wee obtained from four replicate tests in each case. Polynominal equations were fitted by the method of least squares to the stress-strain data to determine average curves. Values of Young's modulus and Poisson's ratio, derived from polynomial coefficients, were compared with laminate analysis results. While the polynomials appeared to accurately fit the stress-strain data in most cases, the use of polynomial coefficients to calculate elastic moduli appeared to be of questionable value in cases involving sharp changes in the slope of the stress-strain data or extensive scatter.

Species area relationships in mediterranean-climate plant communities

USGS Publications Warehouse

Keeley, Jon E.; Fotheringham, C.J.

2003-01-01

Aim To determine the best-fit model of species–area relationships for Mediterranean-type plant communities and evaluate how community structure affects these species–area models.Location Data were collected from California shrublands and woodlands and compared with literature reports for other Mediterranean-climate regions.Methods The number of species was recorded from 1, 100 and 1000 m2 nested plots. Best fit to the power model or exponential model was determined by comparing adjusted r2 values from the least squares regression, pattern of residuals, homoscedasticity across scales, and semi-log slopes at 1–100 m2 and 100–1000 m2. Dominance–diversity curves were tested for fit to the lognormal model, MacArthur's broken stick model, and the geometric and harmonic series.Results Early successional Western Australia and California shrublands represented the extremes and provide an interesting contrast as the exponential model was the best fit for the former, and the power model for the latter, despite similar total species richness. We hypothesize that structural differences in these communities account for the different species–area curves and are tied to patterns of dominance, equitability and life form distribution. Dominance–diversity relationships for Western Australian heathlands exhibited a close fit to MacArthur's broken stick model, indicating more equitable distribution of species. In contrast, Californian shrublands, both postfire and mature stands, were best fit by the geometric model indicating strong dominance and many minor subordinate species. These regions differ in life form distribution, with annuals being a major component of diversity in early successional Californian shrublands although they are largely lacking in mature stands. Both young and old Australian heathlands are dominated by perennials, and annuals are largely absent. Inherent in all of these ecosystems is cyclical disequilibrium caused by periodic fires. The potential for community reassembly is greater in Californian shrublands where only a quarter of the flora resprout, whereas three quarters resprout in Australian heathlands.Other Californian vegetation types sampled include coniferous forests, oak savannas and desert scrub, and demonstrate that different community structures may lead to a similar species–area relationship. Dominance–diversity relationships for coniferous forests closely follow a geometric model whereas associated oak savannas show a close fit to the lognormal model. However, for both communities, species–area curves fit a power model. The primary driver appears to be the presence of annuals. Desert scrub communities illustrate dramatic changes in both species diversity and dominance–diversity relationships in high and low rainfall years, because of the disappearance of annuals in drought years.Main conclusions Species–area curves for immature shrublands in California and the majority of Mediterranean plant communities fit a power function model. Exceptions that fit the exponential model are not because of sampling error or scaling effects, rather structural differences in these communities provide plausible explanations. The exponential species–area model may arise in more than one way. In the highly diverse Australian heathlands it results from a rapid increase in species richness at small scales. In mature California shrublands it results from very depauperate richness at the community scale. In both instances the exponential model is tied to a preponderance of perennials and paucity of annuals. For communities fit by a power model, coefficients z and log c exhibit a number of significant correlations with other diversity parameters, suggesting that they have some predictive value in ecological communities.

Evaluation of quantification methods for real-time PCR minor groove binding hybridization probe assays.

PubMed

Durtschi, Jacob D; Stevenson, Jeffery; Hymas, Weston; Voelkerding, Karl V

2007-02-01

Real-time PCR data analysis for quantification has been the subject of many studies aimed at the identification of new and improved quantification methods. Several analysis methods have been proposed as superior alternatives to the common variations of the threshold crossing method. Notably, sigmoidal and exponential curve fit methods have been proposed. However, these studies have primarily analyzed real-time PCR with intercalating dyes such as SYBR Green. Clinical real-time PCR assays, in contrast, often employ fluorescent probes whose real-time amplification fluorescence curves differ from those of intercalating dyes. In the current study, we compared four analysis methods related to recent literature: two versions of the threshold crossing method, a second derivative maximum method, and a sigmoidal curve fit method. These methods were applied to a clinically relevant real-time human herpes virus type 6 (HHV6) PCR assay that used a minor groove binding (MGB) Eclipse hybridization probe as well as an Epstein-Barr virus (EBV) PCR assay that used an MGB Pleiades hybridization probe. We found that the crossing threshold method yielded more precise results when analyzing the HHV6 assay, which was characterized by lower signal/noise and less developed amplification curve plateaus. In contrast, the EBV assay, characterized by greater signal/noise and amplification curves with plateau regions similar to those observed with intercalating dyes, gave results with statistically similar precision by all four analysis methods.

Estimating non-isothermal bacterial growth in foods from isothermal experimental data.

PubMed

Corradini, M G; Peleg, M

2005-01-01

To develop a mathematical method to estimate non-isothermal microbial growth curves in foods from experiments performed under isothermal conditions and demonstrate the method's applicability with published growth data. Published isothermal growth curves of Pseudomonas spp. in refrigerated fish at 0-8 degrees C and Escherichia coli 1952 in a nutritional broth at 27.6-36 degrees C were fitted with two different three-parameter 'primary models' and the temperature dependence of their parameters was fitted by ad hoc empirical 'secondary models'. These were used to generate non-isothermal growth curves by solving, numerically, a differential equation derived on the premise that the momentary non-isothermal growth rate is the isothermal rate at the momentary temperature, at a time that corresponds to the momentary growth level of the population. The predicted non-isothermal growth curves were in agreement with the reported experimental ones and, as expected, the quality of the predictions did not depend on the 'primary model' chosen for the calculation. A common type of sigmoid growth curve can be adequately described by three-parameter 'primary models'. At least in the two systems examined, these could be used to predict growth patterns under a variety of continuous and discontinuous non-isothermal temperature profiles. The described mathematical method whenever validated experimentally will enable the simulation of the microbial quality of stored and transported foods under a large variety of existing or contemplated commercial temperature histories.

Photoluminescence Analysis of White-Light-Emitting Si Nanoparticles Using Effective Mass Approximation Method

NASA Astrophysics Data System (ADS)

Lee, Soojin; Cho, Woon Jo; Kim, Yang Do; Kim, Eun Kyu; Park, Jae Gwan

2005-07-01

White-light-emitting Si nanoparticles were prepared from the sodium silicide (NaSi) precursor. The photoluminescence of colloidal Si nanoparticles has been fitted by effective mass approximation (EMA). We analyzed the correlation between experimental photoluminescence and simulated fitting curves. Both the mean diameter and the size dispersion of the white-light-emitting Si nanoparticles were estimated.

Note: Index of refraction measurement using the Fresnel equations.

PubMed

McClymer, J P

2014-08-01

The real part of the refractive index is measured from 1.30 to above 3.00 without the use of index matching fluids. This approach expands upon the Brewster angle technique as both S and P polarized lights are used and the full Fresnel equations fitted to the data to extract the index of refraction using nonlinear curve fitting.

[Quantitative study of diesel/CNG buses exhaust particulate size distribution in a road tunnel].

PubMed

Zhu, Chun; Zhang, Xu

2010-10-01

Vehicle emission is one of main sources of fine/ultra-fine particles in many cities. This study firstly presents daily mean particle size distributions of mixed diesel/CNG buses traffic flow by 4 days consecutive real world measurement in an Australia road tunnel. Emission factors (EFs) of particle size distribution of diesel buses and CNG buses are obtained by MLR methods, particle distributions of diesel buses and CNG buses are observed as single accumulation mode and nuclei-mode separately. Particle size distributions of mixed traffic flow are decomposed by two log-normal fitting curves for each 30 min interval mean scans, the degrees of fitting between combined fitting curves and corresponding in-situ scans for totally 90 fitting scans are from 0.972 to 0.998. Finally particle size distributions of diesel buses and CNG buses are quantified by statistical whisker-box charts. For log-normal particle size distribution of diesel buses, accumulation mode diameters are 74.5-86.5 nm, geometric standard deviations are 1.88-2.05. As to log-normal particle size distribution of CNG buses, nuclei-mode diameters are 19.9-22.9 nm, geometric standard deviations are 1.27-1.3.

Hydraulic properties of Mt. Simon aquifer, Prairie Island Indian community, southeastern Minnesota, 2001

USGS Publications Warehouse

Winterstein, Thomas A.

2002-01-01

Hantush and Theis methods type curves were fitted to the measured drawdown and recovery curves in the observation well. The results of matching the type curves to the measured data indicate that leakage is negligible from the overlying Eau Claire confining unit into the Mt. Simon aquifer. The transmissivity and storage coeffi-cients for the Mt. Simon aquifer, determined by both methods, are 3, 000 ft2/d and 3 x 10-4, respectively. The average hydraulic conductivity, assuming an aquifer thickness of 233 ft, is 10 ft/d.

Comment on the paper "Thermoluminescence glow-curve deconvolution functions for mixed order of kinetics and continuous trap distribution by G. Kitis, J.M. Gomez-Ros, Nuclear Instruments and Methods in Physics Research A 440, 2000, pp 224-231"

NASA Astrophysics Data System (ADS)

Kazakis, Nikolaos A.

2018-01-01

The present comment concerns the correct presentation of an algorithm proposed in the above paper for the glow-curve deconvolution in the case of continuous distribution of trapping states. Since most researchers would use directly the proposed algorithm as published, they should be notified of its correct formulation during the fitting of TL glow curves of materials with continuous trap distribution using this Equation.

An Exploration of the Importance of Flood Heterogeneity for Regionalization in Arizona using the Expected Moments Algorithm

NASA Astrophysics Data System (ADS)

Zamora-Reyes, D.; Hirschboeck, K. K.; Paretti, N. V.

2012-12-01

Bulletin 17B (B17B) has prevailed for 30 years as the standard manual for determining flood frequency in the United States. Recently proposed updates to B17B include revising the issue of flood heterogeneity, and improving flood estimates by using the Expected Moments Algorithm (EMA) which can better address low outliers and accommodate information on historical peaks. Incorporating information on mixed populations, such as flood-causing mechanisms, into flood estimates for regions that have noticeable flood heterogeneity can be statistically challenging when systematic flood records are short. The problem magnifies when the population sample size is reduced by decomposing the record, especially if multiple flood mechanisms are involved. In B17B, the guidelines for dealing with mixed populations focus primarily on how to rule out any need to perform a mixed-population analysis. However, in some regions mixed flood populations are critically important determinants of regional flood frequency variations and should be explored from this perspective. Arizona is an area with a heterogeneous mixture of flood processes due to: warm season convective thunderstorms, cool season synoptic-scale storms, and tropical cyclone-enhanced convective activity occurring in the late summer or early fall. USGS station data throughout Arizona was compiled into a database and each flood peak (annual and partial duration series) was classified according to its meteorological cause. Using these data, we have explored the role of flood heterogeneity in Arizona flood estimates through composite flood frequency analysis based on mixed flood populations using EMA. First, for selected stations, the three flood-causing populations were separated out from the systematic annual flood series record and analyzed individually. Second, to create composite probability curves, the individual curves for each of the three populations were generated and combined using Crippen's (1978) composite probability equations for sites that have two or more independent flood populations. Finally, the individual probability curves generated for each of the three flood-causing populations were compared with both the site's composite probability curve and the standard B17B curve to explore the influence of heterogeneity using the 100-year and 200-year flood estimates as a basis of comparison. Results showed that sites located in southern Arizona and along the abrupt elevation transition zone of the Mogollon Rim exhibit a better fit to the systematic data using their composite probability curves than the curves derived from standard B17B analysis. Synoptic storm floods and tropical cyclone-enhanced floods had the greatest influence on 100-year and 200-year flood estimates. This was especially true in southern Arizona, even though summer convective floods are much more frequent and therefore dominate the composite curve. Using the EMA approach also influenced our results because all possible low outliers were censored by the built-in Multiple Grubbs-Beck Test, providing a better fit to the systematic data in the upper probabilities. In conclusion, flood heterogeneity can play an important role in regional flood frequency variations in Arizona and that understanding its influence is important when making projections about future flood variations.

Limb darkening laws for two exoplanet host stars derived from 3D stellar model atmospheres. Comparison with 1D models and HST light curve observations

NASA Astrophysics Data System (ADS)

Hayek, W.; Sing, D.; Pont, F.; Asplund, M.

2012-03-01

We compare limb darkening laws derived from 3D hydrodynamical model atmospheres and 1D hydrostatic MARCS models for the host stars of two well-studied transiting exoplanet systems, the late-type dwarfs HD 209458 and HD 189733. The surface brightness distribution of the stellar disks is calculated for a wide spectral range using 3D LTE spectrum formation and opacity sampling⋆. We test our theoretical predictions using least-squares fits of model light curves to wavelength-integrated primary eclipses that were observed with the Hubble Space Telescope (HST). The limb darkening law derived from the 3D model of HD 209458 in the spectral region between 2900 Å and 5700 Å produces significantly better fits to the HST data, removing systematic residuals that were previously observed for model light curves based on 1D limb darkening predictions. This difference arises mainly from the shallower mean temperature structure of the 3D model, which is a consequence of the explicit simulation of stellar surface granulation where 1D models need to rely on simplified recipes. In the case of HD 189733, the model atmospheres produce practically equivalent limb darkening curves between 2900 Å and 5700 Å, partly due to obstruction by spectral lines, and the data are not sufficient to distinguish between the light curves. We also analyze HST observations between 5350 Å and 10 500 Å for this star; the 3D model leads to a better fit compared to 1D limb darkening predictions. The significant improvement of fit quality for the HD 209458 system demonstrates the higher degree of realism of 3D hydrodynamical models and the importance of surface granulation for the formation of the atmospheric radiation field of late-type stars. This result agrees well with recent investigations of limb darkening in the solar continuum and other observational tests of the 3D models. The case of HD 189733 is no contradiction as the model light curves are less sensitive to the temperature stratification of the stellar atmosphere and the observed data in the 2900-5700 Å region are not sufficient to distinguish more clearly between the 3D and 1D limb darkening predictions. Full theoretical spectra for both stars are available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/539/A102, as well as at www.astro.ex.ac.uk/people/sing.

Comparison of all atom, continuum, and linear fitting empirical models for charge screening effect of aqueous medium surrounding a protein molecule

NASA Astrophysics Data System (ADS)

Takahashi, Takuya; Sugiura, Junnnosuke; Nagayama, Kuniaki

2002-05-01

To investigate the role hydration plays in the electrostatic interactions of proteins, the time-averaged electrostatic potential of the B1 domain of protein G in an aqueous solution was calculated with full atomic molecular dynamics simulations that explicitly considers every atom (i.e., an all atom model). This all atom calculated potential was compared with the potential obtained from an electrostatic continuum model calculation. In both cases, the charge-screening effect was fairly well formulated with an effective relative dielectric constant which increased linearly with increasing charge-charge distance. This simulated linear dependence agrees with the experimentally determined linear relation proposed by Pickersgill. Cut-off approximations for Coulomb interactions failed to reproduce this linear relation. Correlation between the all atom model and the continuum models was found to be better than the respective correlation calculated for linear fitting to the two models. This confirms that the continuum model is better at treating the complicated shapes of protein conformations than the simple linear fitting empirical model. We have tried a sigmoid fitting empirical model in addition to the linear one. When weights of all data were treated equally, the sigmoid model, which requires two fitting parameters, fits results of both the all atom and the continuum models less accurately than the linear model which requires only one fitting parameter. When potential values are chosen as weighting factors, the fitting error of the sigmoid model became smaller, and the slope of both linear fitting curves became smaller. This suggests the screening effect of an aqueous medium within a short range, where potential values are relatively large, is smaller than that expected from the linear fitting curve whose slope is almost 4. To investigate the linear increase of the effective relative dielectric constant, the Poisson equation of a low-dielectric sphere in a high-dielectric medium was solved and charges distributed near the molecular surface were indicated as leading to the apparent linearity.

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

NASA Astrophysics Data System (ADS)

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.

Arsenic speciation in biological samples using XAS and mixed oxidation state calibration standards of inorganic arsenic.

PubMed

Parsons, J G; Lopez, M L; Castillo-Michel, H; Peralta-Videa, J R; Gardea-Torresdey, J L

2009-08-01

The speciation of elements without pre-edge features preformed with X-ray absorption near edge structure (XANES) can lead to problems when the energy difference between two species is small. The speciation of arsenic (As) in plant samples was investigated using the mixtures As2S3/As2O5, As2S3/As2O3, or As2O3/As2O5. The data showed that the energy separation (eV) between As2O5 and As2S3 was 5.8, between As2O3 and As2O5 was 3.6, and between As2S3 and As2O3 was 2.1. From the intensity of the white-line feature and the concentration of As species, calibration curves showing a limit of detection of approximately 10% were generated. In addition, an error of +/-10% was determined for the linear combination-XANES (LC-XANES) fitting technique. The difference between the LC-XANES fittings and calculations from the calibration curves was <10%. The data also showed that the speciation of As in a sample can be determined using EXAFS (extended X-ray absorption fine structure). Finally, it was also shown that both EXAFS and XANES of the sample should be examined to determine the true speciation of an element. Even though there is a difference of 2 eV between As(III) bound to O and As(III) bound to S, in the EXAFS region the As(III)-S and As(III)-O ligands are clearly visible. However, distinction between the As(III)-O and As(V)-O ligands in the EXAFS spectra was not clearly visible in this study.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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; Muthuvalu, M. S., E-mail: sudaram-@yahoo.com, E-mail: jumat@ums.edu.my

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 ofmore » 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.« less

Application of Impedance Microbiology for Evaluating Potential Acidifying Performances of Starter Lactic Acid Bacteria to Employ in Milk Transformation.

PubMed

Bancalari, Elena; Bernini, Valentina; Bottari, Benedetta; Neviani, Erasmo; Gatti, Monica

2016-01-01

Impedance microbiology is a method that enables tracing microbial growth by measuring the change in the electrical conductivity. Different systems, able to perform this measurement, are available in commerce and are commonly used for food control analysis by mean of measuring a point of the impedance curve, defined "time of detection." With this work we wanted to find an objective way to interpret the metabolic significance of impedance curves and propose it as a valid approach to evaluate the potential acidifying performances of starter lactic acid bacteria to be employed in milk transformation. To do this it was firstly investigated the possibility to use the Gompertz equation to describe the data coming from the impedance curve obtained by mean of BacTrac 4300®. Lag time (λ), maximum specific M% rate (μmax), and maximum value of M% (Yend) have been calculated and, given the similarity of the impedance fitted curve to the bacterial growth curve, their meaning has been interpreted. Potential acidifying performances of eighty strains belonging to Lactobacillus helveticus, Lactobacillus delbrueckii subsp. bulgaricus, Lactococcus lactis , and Streptococcus thermophilus species have been evaluated by using the kinetics parameters, obtained from Excel add-in DMFit version 2.1. The novelty and importance of our findings, obtained by means of BacTrac 4300®, is that they can also be applied to data obtained from other devices. Moreover, the meaning of λ, μmax, and Yend that we have extrapolated from Modified Gompertz equation and discussed for lactic acid bacteria in milk, can be exploited also to other food environment or other bacteria, assuming that they can give a curve and that curve is properly fitted with Gompertz equation.

Application of Impedance Microbiology for Evaluating Potential Acidifying Performances of Starter Lactic Acid Bacteria to Employ in Milk Transformation

PubMed Central

Bancalari, Elena; Bernini, Valentina; Bottari, Benedetta; Neviani, Erasmo; Gatti, Monica

2016-01-01

Impedance microbiology is a method that enables tracing microbial growth by measuring the change in the electrical conductivity. Different systems, able to perform this measurement, are available in commerce and are commonly used for food control analysis by mean of measuring a point of the impedance curve, defined “time of detection.” With this work we wanted to find an objective way to interpret the metabolic significance of impedance curves and propose it as a valid approach to evaluate the potential acidifying performances of starter lactic acid bacteria to be employed in milk transformation. To do this it was firstly investigated the possibility to use the Gompertz equation to describe the data coming from the impedance curve obtained by mean of BacTrac 4300®. Lag time (λ), maximum specific M% rate (μmax), and maximum value of M% (Yend) have been calculated and, given the similarity of the impedance fitted curve to the bacterial growth curve, their meaning has been interpreted. Potential acidifying performances of eighty strains belonging to Lactobacillus helveticus, Lactobacillus delbrueckii subsp. bulgaricus, Lactococcus lactis, and Streptococcus thermophilus species have been evaluated by using the kinetics parameters, obtained from Excel add-in DMFit version 2.1. The novelty and importance of our findings, obtained by means of BacTrac 4300®, is that they can also be applied to data obtained from other devices. Moreover, the meaning of λ, μmax, and Yend that we have extrapolated from Modified Gompertz equation and discussed for lactic acid bacteria in milk, can be exploited also to other food environment or other bacteria, assuming that they can give a curve and that curve is properly fitted with Gompertz equation. PMID:27799925

FIT-MART: Quantum Magnetism with a Gentle Learning Curve

NASA Astrophysics Data System (ADS)

Engelhardt, Larry; Garland, Scott C.; Rainey, Cameron; Freeman, Ray A.

We present a new open-source software package, FIT-MART, that allows non-experts to quickly get started sim- ulating quantum magnetism. FIT-MART can be downloaded as a platform-idependent executable Java (JAR) file. It allows the user to define (Heisenberg) Hamiltonians by electronically drawing pictures that represent quantum spins and operators. Sliders are automatically generated to control the values of the parameters in the model, and when the values change, several plots are updated in real time to display both the resulting energy spectra and the equilibruim magnetic properties. Several experimental data sets for real magnetic molecules are included in FIT-MART to allow easy comparison between simulated and experimental data, and FIT-MART users can also import their own data for analysis and compare the goodness of fit for different models.

A New Approach for Obtaining Cosmological Constraints from Type Ia Supernovae using Approximate Bayesian Computation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jennings, Elise; Wolf, Rachel; Sako, Masao

2016-11-09

Cosmological parameter estimation techniques that robustly account for systematic measurement uncertainties will be crucial for the next generation of cosmological surveys. We present a new analysis method, superABC, for obtaining cosmological constraints from Type Ia supernova (SN Ia) light curves using Approximate Bayesian Computation (ABC) without any likelihood assumptions. The ABC method works by using a forward model simulation of the data where systematic uncertainties can be simulated and marginalized over. A key feature of the method presented here is the use of two distinct metrics, the `Tripp' and `Light Curve' metrics, which allow us to compare the simulated data to the observed data set. The Tripp metric takes as input the parameters of models fit to each light curve with the SALT-II method, whereas the Light Curve metric uses the measured fluxes directly without model fitting. We apply the superABC sampler to a simulated data set ofmore » $$\\sim$$1000 SNe corresponding to the first season of the Dark Energy Survey Supernova Program. Varying $$\\Omega_m, w_0, \\alpha$$ and $$\\beta$$ and a magnitude offset parameter, with no systematics we obtain $$\\Delta(w_0) = w_0^{\\rm true} - w_0^{\\rm best \\, fit} = -0.036\\pm0.109$$ (a $$\\sim11$$% 1$$\\sigma$$ uncertainty) using the Tripp metric and $$\\Delta(w_0) = -0.055\\pm0.068$$ (a $$\\sim7$$% 1$$\\sigma$$ uncertainty) using the Light Curve metric. Including 1% calibration uncertainties in four passbands, adding 4 more parameters, we obtain $$\\Delta(w_0) = -0.062\\pm0.132$$ (a $$\\sim14$$% 1$$\\sigma$$ uncertainty) using the Tripp metric. Overall we find a $17$% increase in the uncertainty on $$w_0$$ with systematics compared to without. We contrast this with a MCMC approach where systematic effects are approximately included. We find that the MCMC method slightly underestimates the impact of calibration uncertainties for this simulated data set.« less

Goldindec: A Novel Algorithm for Raman Spectrum Baseline Correction

PubMed Central

Liu, Juntao; Sun, Jianyang; Huang, Xiuzhen; Li, Guojun; Liu, Binqiang

2016-01-01

Raman spectra have been widely used in biology, physics, and chemistry and have become an essential tool for the studies of macromolecules. Nevertheless, the raw Raman signal is often obscured by a broad background curve (or baseline) due to the intrinsic fluorescence of the organic molecules, which leads to unpredictable negative effects in quantitative analysis of Raman spectra. Therefore, it is essential to correct this baseline before analyzing raw Raman spectra. Polynomial fitting has proven to be the most convenient and simplest method and has high accuracy. In polynomial fitting, the cost function used and its parameters are crucial. This article proposes a novel iterative algorithm named Goldindec, freely available for noncommercial use as noted in text, with a new cost function that not only conquers the influence of great peaks but also solves the problem of low correction accuracy when there is a high peak number. Goldindec automatically generates parameters from the raw data rather than by empirical choice, as in previous methods. Comparisons with other algorithms on the benchmark data show that Goldindec has a higher accuracy and computational efficiency, and is hardly affected by great peaks, peak number, and wavenumber. PMID:26037638

Standardization and validation of the body weight adjustment regression equations in Olympic weightlifting.

PubMed

Kauhanen, Heikki; Komi, Paavo V; Häkkinen, Keijo

2002-02-01

The problems in comparing the performances of Olympic weightlifters arise from the fact that the relationship between body weight and weightlifting results is not linear. In the present study, this relationship was examined by using a nonparametric curve fitting technique of robust locally weighted regression (LOWESS) on relatively large data sets of the weightlifting results made in top international competitions. Power function formulas were derived from the fitted LOWESS values to represent the relationship between the 2 variables in a way that directly compares the snatch, clean-and-jerk, and total weightlifting results of a given athlete with those of the world-class weightlifters (golden standards). A residual analysis of several other parametric models derived from the initial results showed that they all experience inconsistencies, yielding either underestimation or overestimation of certain body weights. In addition, the existing handicapping formulas commonly used in normalizing the performances of Olympic weightlifters did not yield satisfactory results when applied to the present data. It was concluded that the devised formulas may provide objective means for the evaluation of the performances of male weightlifters, regardless of their body weights, ages, or performance levels.

Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data

NASA Astrophysics Data System (ADS)

Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2017-05-01

A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data.

PubMed

Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2017-05-07

A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

THE PROPERTIES OF THE 2175 A EXTINCTION FEATURE DISCOVERED IN GRB AFTERGLOWS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zafar, Tayyaba; Watson, Darach; Eliasdottir, Ardis

The unequivocal, spectroscopic detection of the 2175 A bump in extinction curves outside the Local Group is rare. To date, the properties of the bump have been examined in only two gamma-ray burst (GRB) afterglows (GRB 070802 and GRB 080607). In this work, we analyze in detail the detections of the 2175 Angstrom-Sign extinction bump in the optical spectra of two further GRB afterglows: GRB 080605 and 080805. We gather all available optical/near-infrared photometric, spectroscopic, and X-ray data to construct multi-epoch spectral energy distributions (SEDs) for both GRB afterglows. We fit the SEDs with the Fitzpatrick and Massa model withmore » a single or broken power law. We also fit a sample of 38 GRB afterglows, known to prefer a Small Magellanic Cloud (SMC)-type extinction curve, with the same model. We find that the SEDs of GRB 080605 and GRB 080805 at two epochs are fit well with a single power law with a derived extinction of A{sub V} = 0.52{sup +0.13}{sub -0.16} and 0.50{sup +0.13}{sub -0.10}, and 2.1{sup +0.7}{sub -0.6} and 1.5 {+-} 0.2, respectively. While the slope of the extinction curve of GRB 080805 is not well constrained, the extinction curve of GRB 080605 has an unusual very steep far-UV rise together with the 2175 A bump. Such an extinction curve has previously been found in only a small handful of sightlines in the Milky Way. One possible explanation of such an extinction curve may be dust arising from two different regions with two separate grain populations, however we cannot distinguish the origin of the curve. We finally compare the four 2175 A bump sightlines to the larger GRB afterglow sample and to Local Group sightlines. We find that while the width and central positions of the bumps are consistent with what is observed in the Local Group, the relative strength of the detected bump (A{sub bump}) for GRB afterglows is weaker for a given A{sub V} than for almost any Local Group sightline. Such dilution of the bump strength may offer tentative support to a dual dust-population scenario.« less

Characterization of viscoelastic response and damping of composite materials used in flywheel rotors

NASA Astrophysics Data System (ADS)

Chen, Jianmin

The long-term goal for spacecraft flywheel systems with higher energy density at the system level requires new and innovative composite material concepts. Multi-Direction Composite (MDC) offers significant advantages over traditional filament-wound and multi-ring press-fit filament-wound wheels in providing higher energy density (i.e., less mass), better crack resistance, and enhanced safety. However there is a lack of systematic characterization for dynamic properties of MDC composite materials. In order to improve the flywheel materials reliability, durability and life time, it is very important to evaluate the time dependent aging effects and damping properties of MDC material, which are significant dynamic parameter for vibration and sound control, fatigue endurance, and impact resistance. The physical aging effects are quantified based on a set of creep curves measured at different aging time or different aging temperature. One parameter (tau) curve fit was proposed to represent the relationship of aging time and aging temperature between different master curves. The long term mechanical behavior was predicted by obtained master curves. The time and temperature shift factors of matrix were obtained from creep curves and the aging time shift rate were calculated. The aging effects on composite are obtained from experiments and compared with prediction. The mechanical quasi-behavior of MDC composite was analyzed. The correspondence principle was used to relate quasi-static elastic properties of composite materials to time-dependent properties of its constituent materials (i.e., fiber and matrix). The Prony series combined with the multi-data fitting method was applied to inverse Laplace transform and to calculate the time dependent stiffness matrix effectively. Accelerated time-dependent deformation of two flywheel rim designs were studied for a period equivalent to 31 years and are compared with hoop reinforcement only composite. Damping of pure resin and T700/epoxy composite lamina and laminate in longitudinal and transverse directions were investigated experimentally and analytically. The effect of aging on damping was also studied by placing samples at 60°C in an oven for extended periods. Damping master curves versus frequency were constructed from individual curves at different temperatures based on the Arrhenius equation. The damping response of the composite lamina was used to predict the response of laminate composites. Analytical results give close numerical values to experimental results from damping of cantilever beam laminated composite samples.

Physical characteristics related to bra fit.

PubMed

Chen, Chin-Man; LaBat, Karen; Bye, Elizabeth

2010-04-01

Producing well-fitting garments has been a challenge for retailers and manufacturers since mass production began. Poorly fitted bras can cause discomfort or pain and result in lost sales for retailers. Because body contours are important factors affecting bra fit, this study analyses the relationship of physical characteristics to bra-fit problems. This study has used 3-D body-scanning technology to extract upper body angles from a sample of 103 college women; these data were used to categorise physical characteristics into shoulder slope, bust prominence, back curvature and acromion placement. Relationships between these physical categories and bra-fit problems were then analysed. Results show that significant main effects and two-way interactions of the physical categories exist in the fit problems of poor bra support and bra-motion restriction. The findings are valuable in helping the apparel industry create better-fitting bras. STATEMENT OF RELEVANCE: Poorly fitted bras can cause discomfort or pain and result in lost sales for retailers. The findings regarding body-shape classification provide researchers with a statistics method to quantify physical characteristics and the findings regarding the relationship analysis between physical characteristics and bra fit offer bra companies valuable information about bra-fit perceptions attributable to women with figure variations.

Advantages of estimating parameters of photosynthesis model by fitting A-Ci curves at multiple subsaturating light intensities

NASA Astrophysics Data System (ADS)

Fu, W.; Gu, L.; Hoffman, F. M.

2013-12-01

The photosynthesis model of Farquhar, von Caemmerer & Berry (1980) is an important tool for predicting the response of plants to climate change. So far, the critical parameters required by the model have been obtained from the leaf-level measurements of gas exchange, namely the net assimilation of CO2 against intercellular CO2 concentration (A-Ci) curves, made at saturating light conditions. With such measurements, most points are likely in the Rubisco-limited state for which the model is structurally overparameterized (the model is also overparameterized in the TPU-limited state). In order to reliably estimate photosynthetic parameters, there must be sufficient number of points in the RuBP regeneration-limited state, which has no structural over-parameterization. To improve the accuracy of A-Ci data analysis, we investigate the potential of using multiple A-Ci curves at subsaturating light intensities to generate some important parameter estimates more accurately. Using subsaturating light intensities allow more RuBp regeneration-limited points to be obtained. In this study, simulated examples are used to demonstrate how this method can eliminate the errors of conventional A-Ci curve fitting methods. Some fitted parameters like the photocompensation point and day respiration impose a significant limitation on modeling leaf CO2 exchange. The multiple A-Ci curves fitting can also improve over the so-called Laisk (1977) method, which was shown by some recent publication to produce incorrect estimates of photocompensation point and day respiration. We also test the approach with actual measurements, along with suggested measurement conditions to constrain measured A-Ci points to maximize the occurrence of RuBP regeneration-limited photosynthesis. Finally, we use our measured gas exchange datasets to quantify the magnitude of resistance of chloroplast and cell wall-plasmalemma and explore the effect of variable mesophyll conductance. The variable mesophyll conductance takes into account the influence of CO2 from mitochondria, comparing to the commonly used constant value of mesophyll conductance. We show that after considering this effect the other parameters of the photosynthesis model can be re-estimated. Our results indicate that variable mesophyll conductance has most effect on the estimation of the parameter of the maximum electron transport rate (Jmax), but has a negligible impact on the estimated day respiration (Rd) and photocompensation point (<2%).

Introduction: Occam’s Razor (SOT - Fit for Purpose workshop introduction)

EPA Science Inventory

Mathematical models provide important, reproducible, and transparent information for risk-based decision making. However, these models must be constructed to fit the needs of the problem to be solved. A “fit for purpose” model is an abstraction of a complicated problem that allow...

Estimation of kinetic parameters from list-mode data using an indirect apporach

NASA Astrophysics Data System (ADS)

Ortiz, Joseph Christian

This dissertation explores the possibility of using an imaging approach to model classical pharmacokinetic (PK) problems. The kinetic parameters which describe the uptake rates of a drug within a biological system, are parameters of interest. Knowledge of the drug uptake in a system is useful in expediting the drug development process, as well as providing a dosage regimen for patients. Traditionally, the uptake rate of a drug in a system is obtained via sampling the concentration of the drug in a central compartment, usually the blood, and fitting the data to a curve. In a system consisting of multiple compartments, the number of kinetic parameters is proportional to the number of compartments, and in classical PK experiments, the number of identifiable parameters is less than the total number of parameters. Using an imaging approach to model classical PK problems, the support region of each compartment within the system will be exactly known, and all the kinetic parameters are uniquely identifiable. To solve for the kinetic parameters, an indirect approach, which is a two part process, was used. First the compartmental activity was obtained from data, and next the kinetic parameters were estimated. The novel aspect of the research is using listmode data to obtain the activity curves from a system as opposed to a traditional binned approach. Using techniques from information theoretic learning, particularly kernel density estimation, a non-parametric probability density function for the voltage outputs on each photo-multiplier tube, for each event, was generated on the fly, which was used in a least squares optimization routine to estimate the compartmental activity. The estimability of the activity curves for varying noise levels as well as time sample densities were explored. Once an estimate for the activity was obtained, the kinetic parameters were obtained using multiple cost functions, and the compared to each other using the mean squared error as the figure of merit.

Eliminating the blood-flow confounding effect in intravoxel incoherent motion (IVIM) using the non-negative least square analysis in liver.

PubMed

Gambarota, Giulio; Hitti, Eric; Leporq, Benjamin; Saint-Jalmes, Hervé; Beuf, Olivier

2017-01-01

Tissue perfusion measurements using intravoxel incoherent motion (IVIM) diffusion-MRI are of interest for investigations of liver pathologies. A confounding factor in the perfusion quantification is the partial volume between liver tissue and large blood vessels. The aim of this study was to assess and correct for this partial volume effect in the estimation of the perfusion fraction. MRI experiments were performed at 3 Tesla with a diffusion-MRI sequence at 12 b-values. Diffusion signal decays in liver were analyzed using the non-negative least square (NNLS) method and the biexponential fitting approach. In some voxels, the NNLS analysis yielded a very fast-decaying component that was assigned to partial volume with the blood flowing in large vessels. Partial volume correction was performed by biexponential curve fitting, where the first data point (b = 0 s/mm 2 ) was eliminated in voxels with a very fast-decaying component. Biexponential fitting with partial volume correction yielded parametric maps with perfusion fraction values smaller than biexponential fitting without partial volume correction. The results of the current study indicate that the NNLS analysis in combination with biexponential curve fitting allows to correct for partial volume effects originating from blood flow in IVIM perfusion fraction measurements. Magn Reson Med 77:310-317, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Quasi-periodic oscillations in short recurring bursts of magnetars SGR 1806–20 and SGR 1900+14 observed with RXTE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huppenkothen, D.; Heil, L. M.; Watts, A. L.

2014-11-10

Quasi-periodic oscillations (QPOs) observed in the giant flares of magnetars are of particular interest due to their potential to open up a window into the neutron star interior via neutron star asteroseismology. However, only three giant flares have been observed. We therefore make use of the much larger data set of shorter, less energetic recurrent bursts. Here, we report on a search for QPOs in a large data set of bursts from the two most burst-active magnetars, SGR 1806-20 and SGR 1900+14, observed with Rossi X-ray Timing Explorer. We find a single detection in an averaged periodogram comprising 30 burstsmore » from SGR 1806–20, with a frequency of 57 Hz and a width of 5 Hz, remarkably similar to a giant flare QPO observed from SGR 1900+14. This QPO fits naturally within the framework of global magneto-elastic torsional oscillations employed to explain giant flare QPOs. Additionally, we uncover a limit on the applicability of Fourier analysis for light curves with low background count rates and strong variability on short timescales. In this regime, standard Fourier methodology and more sophisticated Fourier analyses fail in equal parts by yielding an unacceptably large number of false-positive detections. This problem is not straightforward to solve in the Fourier domain. Instead, we show how simulations of light curves can offer a viable solution for QPO searches in these light curves.« less

Revisiting the Estimation of Dinosaur Growth Rates

PubMed Central

Myhrvold, Nathan P.

2013-01-01

Previous growth-rate studies covering 14 dinosaur taxa, as represented by 31 data sets, are critically examined and reanalyzed by using improved statistical techniques. The examination reveals that some previously reported results cannot be replicated by using the methods originally reported; results from new methods are in many cases different, in both the quantitative rates and the qualitative nature of the growth, from results in the prior literature. Asymptotic growth curves, which have been hypothesized to be ubiquitous, are shown to provide best fits for only four of the 14 taxa. Possible reasons for non-asymptotic growth patterns are discussed; they include systematic errors in the age-estimation process and, more likely, a bias toward younger ages among the specimens analyzed. Analysis of the data sets finds that only three taxa include specimens that could be considered skeletally mature (i.e., having attained 90% of maximum body size predicted by asymptotic curve fits), and eleven taxa are quite immature, with the largest specimen having attained less than 62% of predicted asymptotic size. The three taxa that include skeletally mature specimens are included in the four taxa that are best fit by asymptotic curves. The totality of results presented here suggests that previous estimates of both maximum dinosaur growth rates and maximum dinosaur sizes have little statistical support. Suggestions for future research are presented. PMID:24358133

Transverse Tension Fatigue Life Characterization Through Flexure Testing of Composite Materials

NASA Technical Reports Server (NTRS)

OBrien, T. Kevin; Chawan, Arun D.; Krueger, Ronald; Paris, Isabelle

2001-01-01

The transverse tension fatigue life of S2/8552 glass-epoxy and IM7/8552 carbon-epoxy was characterized using flexure tests of 90-degree laminates loaded in 3-point and 4-point bending. The influence of specimen polishing and specimen configuration on transverse tension fatigue life was examined using the glass-epoxy laminates. Results showed that 90-degree bend specimens with polished machined edges and polished tension-side surfaces, where bending failures where observed, had lower fatigue lives than unpolished specimens when cyclically loaded at equal stress levels. The influence of specimen thickness and the utility of a Weibull scaling law was examined using the carbon-epoxy laminates. The influence of test frequency on fatigue results was also documented for the 4-point bending configuration. A Weibull scaling law was used to predict the 4-point bending fatigue lives from the 3-point bending curve fit and vice-versa. Scaling was performed based on maximum cyclic stress level as well as fatigue life. The scaling laws based on stress level shifted the curve fit S-N characterizations in the desired direction, however, the magnitude of the shift was not adequate to accurately predict the fatigue lives. Furthermore, the scaling law based on fatigue life shifted the curve fit S-N characterizations in the opposite direction from measured values. Therefore, these scaling laws were not adequate for obtaining accurate predictions of the transverse tension fatigue lives.

The Application of Curve Fitting on the Voltammograms of Various Isoforms of Metallothioneins–Metal Complexes

PubMed Central

Merlos Rodrigo, Miguel Angel; Molina-López, Jorge; Jimenez Jimenez, Ana Maria; Planells Del Pozo, Elena; Adam, Pavlina; Eckschlager, Tomas; Zitka, Ondrej; Richtera, Lukas; Adam, Vojtech

2017-01-01

The translation of metallothioneins (MTs) is one of the defense strategies by which organisms protect themselves from metal-induced toxicity. MTs belong to a family of proteins comprising MT-1, MT-2, MT-3, and MT-4 classes, with multiple isoforms within each class. The main aim of this study was to determine the behavior of MT in dependence on various externally modelled environments, using electrochemistry. In our study, the mass distribution of MTs was characterized using MALDI-TOF. After that, adsorptive transfer stripping technique with differential pulse voltammetry was selected for optimization of electrochemical detection of MTs with regard to accumulation time and pH effects. Our results show that utilization of 0.5 M NaCl, pH 6.4, as the supporting electrolyte provides a highly complicated fingerprint, showing a number of non-resolved voltammograms. Hence, we further resolved the voltammograms exhibiting the broad and overlapping signals using curve fitting. The separated signals were assigned to the electrochemical responses of several MT complexes with zinc(II), cadmium(II), and copper(II), respectively. Our results show that electrochemistry could serve as a great tool for metalloproteomic applications to determine the ratio of metal ion bonds within the target protein structure, however, it provides highly complicated signals, which require further resolution using a proper statistical method, such as curve fitting. PMID:28287470

Simultaneous CCD Photometry of Two Eclipsing Binary Stars in Pegasus - Part2: BX Peg

NASA Astrophysics Data System (ADS)

Alton, K. B.

2013-05-01

BX Peg is an overcontact W UMa binary system (P = 0.280416 d) which has been rather well studied, but not fully understood due to complex changes in eclipse timings and light curve variations attributed to star spots. Photometric data collected in three bandpasses (B, V, and Ic) produced nineteen new times of minimum for BX Peg. These were used to update the linear ephemeris and further analyze potential changes in orbital periodicity by examining long-term changes in eclipse timings. In addition, synthetic fitting of light curves by Roche modeling was accomplished with the assistance of three different programs, two of which employ the Wilson-Devinney code. Different spotted solutions were necessary to achieve the best Roche model fits for BX Peg light curves collected in 2008 and 2011. Overall, the long-;term decrease (9.66 × 10-3 sec y-1) in orbital period defined by the parabolic fit of eclipse timing data could arise from mass transfer or angular momentum loss. The remaining residuals from observed minus predicted eclipse timings for BX Peg exhibit complex but non-random behavior. These may be related to magnetic activity cycles and/or the presence of an unseen mass influencing the times of minimum, however, additional minima need to be collected over a much longer timescale to resolve the nature of these complex changes.

Quark-novae Occurring in Massive Binaries : A Universal Energy Source in Superluminous Supernovae with Double-peaked Light Curves

NASA Astrophysics Data System (ADS)

Ouyed, Rachid; Leahy, Denis; Koning, Nico

2016-02-01

A quark-nova (QN; the sudden transition from a neutron star into a quark star), which occurs in the second common envelope (CE) phase of a massive binary, gives excellent fits to superluminous, hydrogen-poor, supernovae (SLSNe) with double-peaked light curves, including DES13S2cmm, SN 2006oz, and LSQ14bdq (http://www.quarknova.ca/LCGallery.html). In our model, the H envelope of the less massive companion is ejected during the first CE phase, while the QN occurs deep inside the second, He-rich, CE phase after the CE has expanded in size to a radius of a few tens to a few thousands of solar radii; this yields the first peak in our model. The ensuing merging of the quark star with the CO core leads to black hole formation and accretion, explaining the second long-lasting peak. We study a sample of eight SLSNe Ic with double-humped light curves. Our model provides good fits to all of these, with a universal explosive energy of 2 × 1052 erg (which is the kinetic energy of the QN ejecta) for the first hump. The late-time emissions seen in iPTF13ehe and LSQ14bdq are fit with a shock interaction between the outgoing He-rich (I.e., second) CE and the previously ejected H-rich (I.e., first) CE.

UNSUPERVISED TRANSIENT LIGHT CURVE ANALYSIS VIA HIERARCHICAL BAYESIAN INFERENCE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanders, N. E.; Soderberg, A. M.; Betancourt, M., E-mail: nsanders@cfa.harvard.edu

2015-02-10

Historically, light curve studies of supernovae (SNe) and other transient classes have focused on individual objects with copious and high signal-to-noise observations. In the nascent era of wide field transient searches, objects with detailed observations are decreasing as a fraction of the overall known SN population, and this strategy sacrifices the majority of the information contained in the data about the underlying population of transients. A population level modeling approach, simultaneously fitting all available observations of objects in a transient sub-class of interest, fully mines the data to infer the properties of the population and avoids certain systematic biases. Wemore » present a novel hierarchical Bayesian statistical model for population level modeling of transient light curves, and discuss its implementation using an efficient Hamiltonian Monte Carlo technique. As a test case, we apply this model to the Type IIP SN sample from the Pan-STARRS1 Medium Deep Survey, consisting of 18,837 photometric observations of 76 SNe, corresponding to a joint posterior distribution with 9176 parameters under our model. Our hierarchical model fits provide improved constraints on light curve parameters relevant to the physical properties of their progenitor stars relative to modeling individual light curves alone. Moreover, we directly evaluate the probability for occurrence rates of unseen light curve characteristics from the model hyperparameters, addressing observational biases in survey methodology. We view this modeling framework as an unsupervised machine learning technique with the ability to maximize scientific returns from data to be collected by future wide field transient searches like LSST.« less

Reverse engineering of aircraft wing data using a partial differential equation surface model

NASA Astrophysics Data System (ADS)

Huband, Jacalyn Mann

Reverse engineering is a multi-step process used in industry to determine a production representation of an existing physical object. This representation is in the form of mathematical equations that are compatible with computer-aided design and computer-aided manufacturing (CAD/CAM) equipment. The four basic steps to the reverse engineering process are data acquisition, data separation, surface or curve fitting, and CAD/CAM production. The surface fitting step determines the design representation of the object, and thus is critical to the success or failure of the reverse engineering process. Although surface fitting methods described in the literature are used to model a variety of surfaces, they are not suitable for reversing aircraft wings. In this dissertation, we develop and demonstrate a new strategy for reversing a mathematical representation of an aircraft wing. The basis of our strategy is to take an aircraft design model and determine if an inverse model can be derived. A candidate design model for this research is the partial differential equation (PDE) surface model, proposed by Bloor and Wilson and used in the Rapid Airplane Parameter Input Design (RAPID) tool at the NASA-LaRC Geolab. There are several basic mathematical problems involved in reversing the PDE surface model: (i) deriving a computational approximation of the surface function; (ii) determining a radial parametrization of the wing; (iii) choosing mathematical models or classes of functions for representation of the boundary functions; (iv) fitting the boundary data points by the chosen boundary functions; and (v) simultaneously solving for the axial parameterization and the derivative boundary functions. The study of the techniques to solve the above mathematical problems has culminated in a reverse PDE surface model and two reverse PDE surface algorithms. One reverse PDE surface algorithm recovers engineering design parameters for the RAPID tool from aircraft wing data and the other generates a PDE surface model with spline boundary functions from an arbitrary set of grid points. Our numerical tests show that the reverse PDE surface model and the reverse PDE surface algorithms can be used for the reverse engineering of aircraft wing data.

Organic Model of Interstellar Grains

NASA Astrophysics Data System (ADS)

Yabushita, S.; Inagaki, T.; Kawabe, T.; Wada, K.

1987-04-01

Extinction efficiency of grains is calculated from the Mie formula on the premise that the grains are of organic composition. The optical constants adopted for the calculations are those of E. coli, polystyrene and bovine albumin. The grain radius a is assumed to obey a distribution of the form N(a) ∝ a-α and the value of α is chosen so as to make the calculated extinction curve match the observed interstellar extinction curve. Although the calculated curve gives a reasonably good fit to the observed extinction curve for wavelengths less than 2100 Å, at longer wavelength regions, agreement is poor. It is concluded that another component is required for the organic model to be viable.

On the use of the covariance matrix to fit correlated data

NASA Astrophysics Data System (ADS)

D'Agostini, G.

1994-07-01

Best fits to data which are affected by systematic uncertainties on the normalization factor have the tendency to produce curves lower than expected if the covariance matrix of the data points is used in the definition of the χ2. This paper shows that the effect is a direct consequence of the hypothesis used to estimate the empirical covariance matrix, namely the linearization on which the usual error propagation relies. The bias can become unacceptable if the normalization error is large, or a large number of data points are fitted.

JMFA2—a graphically interactive Java program that fits microfibril angle X-ray diffraction data

Treesearch

Steve P. Verrill; David E. Kretschmann; Victoria L. Herian

2006-01-01

X-ray diffraction techniques have the potential to decrease the time required to determine microfibril angles dramatically. In this paper, we discuss the latest version of a curve-fitting toll that permits us to reduce the time required to evaluate MFA X-ray diffraction patterns. Further, because this tool reflects the underlying physics more accurately than existing...

Efficient, adaptive estimation of two-dimensional firing rate surfaces via Gaussian process methods.

PubMed

Rad, Kamiar Rahnama; Paninski, Liam

2010-01-01

Estimating two-dimensional firing rate maps is a common problem, arising in a number of contexts: the estimation of place fields in hippocampus, the analysis of temporally nonstationary tuning curves in sensory and motor areas, the estimation of firing rates following spike-triggered covariance analyses, etc. Here we introduce methods based on Gaussian process nonparametric Bayesian techniques for estimating these two-dimensional rate maps. These techniques offer a number of advantages: the estimates may be computed efficiently, come equipped with natural errorbars, adapt their smoothness automatically to the local density and informativeness of the observed data, and permit direct fitting of the model hyperparameters (e.g., the prior smoothness of the rate map) via maximum marginal likelihood. We illustrate the method's flexibility and performance on a variety of simulated and real data.

EOSlib, Version 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woods, Nathan; Menikoff, Ralph

2017-02-03

Equilibrium thermodynamics underpins many of the technologies used throughout theoretical physics, yet verification of the various theoretical models in the open literature remains challenging. EOSlib provides a single, consistent, verifiable implementation of these models, in a single, easy-to-use software package. It consists of three parts: a software library implementing various published equation-of-state (EOS) models; a database of fitting parameters for various materials for these models; and a number of useful utility functions for simplifying thermodynamic calculations such as computing Hugoniot curves or Riemann problem solutions. Ready availability of this library will enable reliable code-to- code testing of equation-of-state implementations, asmore » well as a starting point for more rigorous verification work. EOSlib also provides a single, consistent API for its analytic and tabular EOS models, which simplifies the process of comparing models for a particular application.« less

Squared exponential covariance function for prediction of hydrocarbon in seabed logging application

NASA Astrophysics Data System (ADS)

Mukhtar, Siti Mariam; Daud, Hanita; Dass, Sarat Chandra

2016-11-01

Seabed Logging technology (SBL) has progressively emerged as one of the demanding technologies in Exploration and Production (E&P) industry. Hydrocarbon prediction in deep water areas is crucial task for a driller in any oil and gas company as drilling cost is very expensive. Simulation data generated by Computer Software Technology (CST) is used to predict the presence of hydrocarbon where the models replicate real SBL environment. These models indicate that the hydrocarbon filled reservoirs are more resistive than surrounding water filled sediments. Then, as hydrocarbon depth is increased, it is more challenging to differentiate data with and without hydrocarbon. MATLAB is used for data extractions for curve fitting process using Gaussian process (GP). GP can be classified into regression and classification problems, where this work only focuses on Gaussian process regression (GPR) problem. Most popular choice to supervise GPR is squared exponential (SE), as it provides stability and probabilistic prediction in huge amounts of data. Hence, SE is used to predict the presence or absence of hydrocarbon in the reservoir from the data generated.

MATHEMATICS PANEL QUARTERLY PROGRESS REPORT FOR PERIOD ENDING JULY 31, 1952

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perry, C.L. ed.

1952-10-27

The background and status of the following projects of the Mathematics Panel are reported: test problems for the ORAC arithmetic units errors in matrix operations; basic studies in the Monte Carlo methods A Sturm-Liouville problems approximate steady-state solution of the equation of continuity; estimation of volume of lymph space; xradiation effects on respiration rates in grasshopper embnyos; temperature effects in irradiation experiments with yeast; LD/sub 50/ estimation for burros and swine exposed to gamma radiation; thermal-neutron penetration in tissues; kinetics of HBr-HBrO/sub 3/ reaction; isotope effect in reaction rate constants; experimental determination of diffusivity coefficientss Dirac wave equationss fitting amore » calibration curves beta decay (field factors); neutron decay theorys calculation of internal conversion coefficients with screening; estimation of alignment ratios; optimum allocation of counting times calculation of coincidence probabilities for a double-crystal detectors reactor inequalities; heat flow in long rectangular tubes; solving an equation by numerical methods; numerical integration; evalvation of a functions depigmentation of a biological dosimeter. (L.M.T.)« less

Myocardial serotonin exchange: negligible uptake by capillary endothelium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moffett, T.C.; Chan, I.S.; Bassingthwaighte, J.B.

1988-03-01

The extraction of serotonin from the blood during transorgan passage through the heart was studied using Langendorff-perfused rabbit hearts. Outflow dilution curves of /sup 131/I- or /sup 125/I-labeled albumin, (/sup 14/C)sucrose, and (3H)serotonin injected simultaneously into the inflow were fitted with an axially distributed blood-tissue exchange model to examine the extraction process. The model fits of the albumin and sucrose outflow dilution curves were used to define flow heterogeneity, intravascular dispersion, capillary permeability, and the volume of the interstitial space, which reduced the degrees of freedom in fitting the model to the serotonin curves. Serotonin extractions, measured against albumin, duringmore » single transcapillary passage, ranged from 24 to 64%. The ratio of the capillary permeability-surface area products for serotonin and sucrose, based on the maximum instantaneous extraction, was 1.37 +/- 0.2 (n = 18), very close to the predicted value of 1.39, the ratio of free diffusion coefficients calculated from the molecular weights. This result shows that the observed uptake of serotonin can be accounted for solely on the basis of diffusion between endothelial cells into the interstitial space. Thus it appears that the permeability of the luminal surface of the endothelial cell is negligible in comparison to diffusion through the clefts between endothelial cells. In 18 sets of dilution curves, with and without receptor and transport blockers or competitors (ketanserin, desipramine, imipramine, serotonin), the extractions and estimates of the capillary permeability-surface area product were not reduced, nor were the volumes of distribution. The apparent absence of transporters and receptors in rabbit myocardial capillary endothelium contrasts with their known abundance in the pulmonary vasculature.« less

Quantifying intervertebral disc mechanics: a new definition of the neutral zone

PubMed Central

2011-01-01

Background The neutral zone (NZ) is the range over which a spinal motion segment (SMS) moves with minimal resistance. Clear as this may seem, the various methods to quantify NZ described in the literature depend on rather arbitrary criteria. Here we present a stricter, more objective definition. Methods To mathematically represent load-deflection of a SMS, the asymmetric curve was fitted by a summed sigmoid function. The first derivative of this curve represents the SMS compliance and the region with the highest compliance (minimal stiffness) is the NZ. To determine the boundaries of this region, the inflection points of compliance can be used as unique points. These are defined by the maximum and the minimum in the second derivative of the fitted curve, respectively. The merits of the model were investigated experimentally: eight porcine lumbar SMS's were bent in flexion-extension, before and after seven hours of axial compression. Results The summed sigmoid function provided an excellent fit to the measured data (r2 > 0.976). The NZ by the new definition was on average 2.4 (range 0.82-7.4) times the NZ as determined by the more commonly used angulation difference at zero loading. Interestingly, NZ consistently and significantly decreased after seven hours of axial compression when determined by the new definition. On the other hand, NZ increased when defined as angulation difference, probably reflecting the increase of hysteresis. The methods thus address different aspects of the load-deflection curve. Conclusions A strict mathematical definition of the NZ is proposed, based on the compliance of the SMS. This operational definition is objective, conceptually correct, and does not depend on arbitrarily chosen criteria. PMID:21299900

Three-dimensional simulation of human teeth and its application in dental education and research.

PubMed

Koopaie, Maryam; Kolahdouz, Sajad

2016-01-01

Background: A comprehensive database, comprising geometry and properties of human teeth, is needed for dentistry education and dental research. The aim of this study was to create a three-dimensional model of human teeth to improve the dental E-learning and dental research. Methods: In this study, a cross-section picture of the three-dimensional model of the teeth was used. CT-Scan images were used in the first method. The space between the cross- sectional images was about 200 to 500 micrometers. Hard tissue margin was detected in each image by Matlab (R2009b), as image processing software. The images were transferred to Solidworks 2015 software. Tooth border curve was fitted on B-spline curves, using the least square-curve fitting algorithm. After transferring all curves for each tooth to Solidworks, the surface was created based on the surface fitting technique. This surface was meshed in Meshlab-v132 software, and the optimization of the surface was done based on the remeshing technique. The mechanical properties of the teeth were applied to the dental model. Results: This study presented a methodology for communication between CT-Scan images and the finite element and training software through which modeling and simulation of the teeth were performed. In this study, cross-sectional images were used for modeling. According to the findings, the cost and time were reduced compared to other studies. Conclusion: The three-dimensional model method presented in this study facilitated the learning of the dental students and dentists. Based on the three-dimensional model proposed in this study, designing and manufacturing the implants and dental prosthesis are possible.

Three-dimensional simulation of human teeth and its application in dental education and research

PubMed Central

Koopaie, Maryam; Kolahdouz, Sajad

2016-01-01

Background: A comprehensive database, comprising geometry and properties of human teeth, is needed for dentistry education and dental research. The aim of this study was to create a three-dimensional model of human teeth to improve the dental E-learning and dental research. Methods: In this study, a cross-section picture of the three-dimensional model of the teeth was used. CT-Scan images were used in the first method. The space between the cross- sectional images was about 200 to 500 micrometers. Hard tissue margin was detected in each image by Matlab (R2009b), as image processing software. The images were transferred to Solidworks 2015 software. Tooth border curve was fitted on B-spline curves, using the least square-curve fitting algorithm. After transferring all curves for each tooth to Solidworks, the surface was created based on the surface fitting technique. This surface was meshed in Meshlab-v132 software, and the optimization of the surface was done based on the remeshing technique. The mechanical properties of the teeth were applied to the dental model. Results: This study presented a methodology for communication between CT-Scan images and the finite element and training software through which modeling and simulation of the teeth were performed. In this study, cross-sectional images were used for modeling. According to the findings, the cost and time were reduced compared to other studies. Conclusion: The three-dimensional model method presented in this study facilitated the learning of the dental students and dentists. Based on the three-dimensional model proposed in this study, designing and manufacturing the implants and dental prosthesis are possible. PMID:28491836

Constraining the String Gauge Field by Galaxy Rotation Curves and Perihelion Precession of Planets

NASA Astrophysics Data System (ADS)

Cheung, Yeuk-Kwan E.; Xu, Feng

2013-09-01

We discuss a cosmological model in which the string gauge field coupled universally to matter gives rise to an extra centripetal force and will have observable signatures on cosmological and astronomical observations. Several tests are performed using data including galaxy rotation curves of 22 spiral galaxies of varied luminosities and sizes and perihelion precessions of planets in the solar system. The rotation curves of the same group of galaxies are independently fit using a dark matter model with the generalized Navarro-Frenk-White (NFW) profile and the string model. A remarkable fit of galaxy rotation curves is achieved using the one-parameter string model as compared to the three-parameter dark matter model with the NFW profile. The average χ2 value of the NFW fit is 9% better than that of the string model at a price of two more free parameters. Furthermore, from the string model, we can give a dynamical explanation for the phenomenological Tully-Fisher relation. We are able to derive a relation between field strength, galaxy size, and luminosity, which can be verified with data from the 22 galaxies. To further test the hypothesis of the universal existence of the string gauge field, we apply our string model to the solar system. Constraint on the magnitude of the string field in the solar system is deduced from the current ranges for any anomalous perihelion precession of planets allowed by the latest observations. The field distribution resembles a dipole field originating from the Sun. The string field strength deduced from the solar system observations is of a similar magnitude as the field strength needed to sustain the rotational speed of the Sun inside the Milky Way. This hypothesis can be tested further by future observations with higher precision.

Deep Space Network Scheduling Using Evolutionary Computational Methods

NASA Technical Reports Server (NTRS)

Guillaume, Alexandre; Lee, Seugnwon; Wang, Yeou-Fang; Terrile, Richard J.

2007-01-01

The paper presents the specific approach taken to formulate the problem in terms of gene encoding, fitness function, and genetic operations. The genome is encoded such that a subset of the scheduling constraints is automatically satisfied. Several fitness functions are formulated to emphasize different aspects of the scheduling problem. The optimal solutions of the different fitness functions demonstrate the trade-off of the scheduling problem and provide insight into a conflict resolution process.

What Mathematical Competencies Are Needed for Success in College.

ERIC Educational Resources Information Center

Garofalo, Joe

1990-01-01

Identifies requisite math skills for a microeconomics course, offering samples of supply curves, demand curves, equilibrium prices, elasticity, and complex graph problems. Recommends developmental mathematics competencies, including problem solving, reasoning, connections, communication, number and operation sense, algebra, relationships,…

Automated Blazar Light Curves Using Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Spencer James

2017-07-27

This presentation describes a problem and methodology pertaining to automated blazar light curves. Namely, optical variability patterns for blazars require the construction of light curves and in order to generate the light curves, data must be filtered before processing to ensure quality.

Three-dimensional curvilinear device reconstruction from two fluoroscopic views

NASA Astrophysics Data System (ADS)

Delmas, Charlotte; Berger, Marie-Odile; Kerrien, Erwan; Riddell, Cyril; Trousset, Yves; Anxionnat, René; Bracard, Serge

2015-03-01

In interventional radiology, navigating devices under the sole guidance of fluoroscopic images inside a complex architecture of tortuous and narrow vessels like the cerebral vascular tree is a difficult task. Visualizing the device in 3D could facilitate this navigation. For curvilinear devices such as guide-wires and catheters, a 3D reconstruction may be achieved using two simultaneous fluoroscopic views, as available on a biplane acquisition system. The purpose of this paper is to present a new automatic three-dimensional curve reconstruction method that has the potential to reconstruct complex 3D curves and does not require a perfect segmentation of the endovascular device. Using epipolar geometry, our algorithm translates the point correspondence problem into a segment correspondence problem. Candidate 3D curves can be formed and evaluated independently after identifying all possible combinations of compatible 3D segments. Correspondence is then inherently solved by looking in 3D space for the most coherent curve in terms of continuity and curvature. This problem can be cast into a graph problem where the most coherent curve corresponds to the shortest path of a weighted graph. We present quantitative results of curve reconstructions performed from numerically simulated projections of tortuous 3D curves extracted from cerebral vascular trees affected with brain arteriovenous malformations as well as fluoroscopic image pairs of a guide-wire from both phantom and clinical sets. Our method was able to select the correct 3D segments in 97.5% of simulated cases thus demonstrating its ability to handle complex 3D curves and can deal with imperfect 2D segmentation.

ARPEFS as an analytic technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schach von Wittenau, A.E.

1991-04-01

Two modifications to the ARPEFS technique are introduced. These are studied using p(2 {times} 2)S/Cu(001) as a model system. The first modification is the obtaining of ARPEFS {chi}(k) curves at temperatures as low as our equipment will permit. While adding to the difficulty of the experiment, this modification is shown to almost double the signal-to-noise ratio of normal emission p(2 {times} 2)S/Cu(001) {chi}(k) curves. This is shown by visual comparison of the raw data and by the improved precision of the extracted structural parameters. The second change is the replacement of manual fitting of the Fourier filtered {chi}(k) curves bymore » the use of the simplex algorithm for parameter determination. Again using p(2 {times} 2)S/Cu(001) data, this is shown to result in better agreement between experimental {chi}(k) curves and curves calculated based on model structures. The improved ARPEFS is then applied to p(2 {times} 2)S/Ni(111) and ({radical}3 {times} {radical}3) R30{degree}S/Ni(111). For p(2 {times} 2)S/Cu(001) we find a S-Cu bond length of 2.26 {Angstrom}, with the S adatom 1.31 {Angstrom} above the fourfold hollow site. The second Cu layer appears to be corrugated. Analysis of the p(2 {times} 2)S/Ni(111) data indicates that the S adatom adatom adsorbs onto the FCC threefold hollow site 1.53 {Angstrom} above the Ni surface. The S-Ni bond length is determined to be 2.13 {Angstrom}, indicating an outwards shift of the first layer Ni atoms. We are unable to assign a unique structure to ({radical}3 {times} {radical}3)R30{degree}S/Ni(111). An analysis of the strengths and weaknesses of ARPEFS as an experimental and analytic technique is presented, along with a summary of problems still to be addressed.« less

On the Existence of Step-To-Step Breakpoint Transitions in Accelerated Sprinting

PubMed Central

McGhie, David; Danielsen, Jørgen; Sandbakk, Øyvind; Haugen, Thomas

2016-01-01

Accelerated running is characterised by a continuous change of kinematics from one step to the next. It has been argued that breakpoints in the step-to-step transitions may occur, and that these breakpoints are an essential characteristic of dynamics during accelerated running. We examined this notion by comparing a continuous exponential curve fit (indicating continuity, i.e., smooth transitions) with linear piecewise fitting (indicating breakpoint). We recorded the kinematics of 24 well trained sprinters during a 25 m sprint run with start from competition starting blocks. Kinematic data were collected for 24 anatomical landmarks in 3D, and the location of centre of mass (CoM) was calculated from this data set. The step-to-step development of seven variables (four related to CoM position, and ground contact time, aerial time and step length) were analysed by curve fitting. In most individual sprints (in total, 41 sprints were successfully recorded) no breakpoints were identified for the variables investigated. However, for the mean results (i.e., the mean curve for all athletes) breakpoints were identified for the development of vertical CoM position, angle of acceleration and distance between support surface and CoM. It must be noted that for these variables the exponential fit showed high correlations (r2>0.99). No relationship was found between the occurrences of breakpoints for different variables as investigated using odds ratios (Mantel-Haenszel Chi-square statistic). It is concluded that although breakpoints regularly appear during accelerated running, these are not the rule and thereby unlikely a fundamental characteristic, but more likely an expression of imperfection of performance. PMID:27467387

Treatment of hyperthyroidism with radioiodine targeted activity: A comparison between two dosimetric methods.

PubMed

Amato, Ernesto; Campennì, Alfredo; Leotta, Salvatore; Ruggeri, Rosaria M; Baldari, Sergio

2016-06-01

Radioiodine therapy is an effective and safe treatment of hyperthyroidism due to Graves' disease, toxic adenoma, toxic multinodular goiter. We compared the outcomes of a traditional calculation method based on an analytical fit of the uptake curve and subsequent dose calculation with the MIRD approach, and an alternative computation approach based on a formulation implemented in a public-access website, searching for the best timing of radioiodine uptake measurements in pre-therapeutic dosimetry. We report about sixty-nine hyperthyroid patients that were treated after performing a pre-therapeutic dosimetry calculated by fitting a six-point uptake curve (3-168h). In order to evaluate the results of the radioiodine treatment, patients were followed up to sixty-four months after treatment (mean 47.4±16.9). Patient dosimetry was then retrospectively recalculated with the two above-mentioned methods. Several time schedules for uptake measurements were considered, with different timings and total number of points. Early time schedules, sampling uptake up to 48h, do not allow to set-up an accurate treatment plan, while schedules including the measurement at one week give significantly better results. The analytical fit procedure applied to the three-point time schedule 3(6)-24-168h gave results significantly more accurate than the website approach exploiting either the same schedule, or the single measurement at 168h. Consequently, the best strategy among the ones considered is to sample the uptake at 3(6)-24-168h, and carry out an analytical fit of the curve, while extra measurements at 48 and 72h lead only marginal improvements in the accuracy of therapeutic activity determination. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Two regimes of galaxy dynamics: mass models of NGC 5055 and DDO 154

NASA Astrophysics Data System (ADS)

Jovanović, Milena

2017-08-01

We derive detailed dynamical models for two galaxies, the massive spiral galaxy NGC 5055 and the dwarf irregular DDO 154. We used Navarro, Frenk & White (NFW) and isothermal halo models for the dark matter (DM) distribution, along with the most recent and reliable radio observations of H I to determine the rotation curves of these galaxies. Contributions from the neutral gas and the luminous matter were accounted for. For NGC 5055, the latest stellar population synthesis (SPS) models, combining metallicity and age as indicators of the stellar mass-to-light ratio (M/L) were used to better constrain both the DM model and the contribution to the total mass from all components. The isothermal dark halo model successfully fitted both observed rotation curves with realistic values for stellar M/L, while the NFW model needed further constraints for M/L to fit the rotation curve of DDO 154. In the case of NGC 5055, we found the best-fitting M/L in the 3.6 μm band (M/L3.6) for stellar disc to be 0.57 ± 0.04 for isothermal, and 0.50 ± 0.05 for NFW DM model. The most probable value for M/L3.6 from SPS models is 0.46, which is in agreement within uncertainties with our best-fitting NFW model. In the case of DDO 154, we obtained the stellar disc M/L3.6 of 0.25 ± 0.20 for the isothermal DM model. The stellar disc M/L3.6 for the NFW model was fixed to 0.26, as best reasonable value. For NGC 5055, we derived radial profiles of stellar M/L for our best estimate for a particular DM model.

Conservative treatment of idiopathic scoliosis according to FITS concept: presentation of the method and preliminary, short term radiological and clinical results based on SOSORT and SRS criteria

PubMed Central

2011-01-01

Background Conservative scoliosis therapy according to the FITS Concept is applied as a unique treatment or in combination with corrective bracing. The aim of the study was to present author's method of diagnosis and therapy for idiopathic scoliosis FITS-Functional Individual Therapy of Scoliosis and to analyze the early results of FITS therapy in a series of consecutive patients. Methods The analysis comprised separately: (1) single structural thoracic, thoracolumbar or lumbar curves and (2) double structural scoliosis-thoracic and thoracolumbar or lumbar curves. The Cobb angle and Risser sign were analyzed at the initial stage and at the 2.8-year follow-up. The percentage of patients improved (defined as decrease of Cobb angle of more than 5 degrees), stable (+/- 5 degrees), and progressed (increase of Cobb angle of more than 5 degrees) was calculated. The clinical assessment comprised: the Angle of Trunk Rotation (ATR) initial and follow-up value, the plumb line imbalance, the scapulae level and the distance from the apical spinous process of the primary curve to the plumb line. Results In the Group A: (1) in single structural scoliosis 50,0% of patients improved, 46,2% were stable and 3,8% progressed, while (2) in double scoliosis 50,0% of patients improved, 30,8% were stable and 19,2% progressed. In the Group B: (1) in single scoliosis 20,0% of patients improved, 80,0% were stable, no patient progressed, while (2) in double scoliosis 28,1% of patients improved, 46,9% were stable and 25,0% progressed. Conclusion Best results were obtained in 10-25 degrees scoliosis which is a good indication to start therapy before more structural changes within the spine establish. PMID:22122964