Bayesian and Frequentist Methods for Estimating Joint Uncertainty of Freundlich Adsorption Isotherm Fitting Parameters

EPA Science Inventory

In this paper, we present methods for estimating Freundlich isotherm fitting parameters (K and N) and their joint uncertainty, which have been implemented into the freeware software platforms R and WinBUGS. These estimates were determined by both Frequentist and Bayesian analyse...

On the Nature of SEM Estimates of ARMA Parameters.

ERIC Educational Resources Information Center

Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M.

2002-01-01

Reexamined the nature of structural equation modeling (SEM) estimates of autoregressive moving average (ARMA) models, replicated the simulation experiments of P. Molenaar, and examined the behavior of the log-likelihood ratio test. Simulation studies indicate that estimates of ARMA parameters observed with SEM software are identical to those…

Software cost/resource modeling: Deep space network software cost estimation model

NASA Technical Reports Server (NTRS)

Tausworthe, R. J.

1980-01-01

A parametric software cost estimation model prepared for JPL deep space network (DSN) data systems implementation tasks is presented. The resource estimation model incorporates principles and data from a number of existing models, such as those of the General Research Corporation, Doty Associates, IBM (Walston-Felix), Rome Air Force Development Center, University of Maryland, and Rayleigh-Norden-Putnam. The model calibrates task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit JPL software lifecycle statistics. The estimation model output scales a standard DSN work breakdown structure skeleton, which is then input to a PERT/CPM system, producing a detailed schedule and resource budget for the project being planned.

Parameters Estimation For A Patellofemoral Joint Of A Human Knee Using A Vector Method

NASA Astrophysics Data System (ADS)

Ciszkiewicz, A.; Knapczyk, J.

2015-08-01

Position and displacement analysis of a spherical model of a human knee joint using the vector method was presented. Sensitivity analysis and parameter estimation were performed using the evolutionary algorithm method. Computer simulations for the mechanism with estimated parameters proved the effectiveness of the prepared software. The method itself can be useful when solving problems concerning the displacement and loads analysis in the knee joint.

SP_Ace: Stellar Parameters And Chemical abundances Estimator

NASA Astrophysics Data System (ADS)

Boeche, C.; Grebel, E. K.

2018-05-01

SP_Ace (Stellar Parameters And Chemical abundances Estimator) estimates the stellar parameters Teff, log g, [M/H], and elemental abundances. It employs 1D stellar atmosphere models in Local Thermodynamic Equilibrium (LTE). The code is highly automated and suitable for analyzing the spectra of large spectroscopic surveys with low or medium spectral resolution (R = 2000-20 000). A web service for calculating these values with the software is also available.

A Comparison of Limited-Information and Full-Information Methods in M"plus" for Estimating Item Response Theory Parameters for Nonnormal Populations

ERIC Educational Resources Information Center

DeMars, Christine E.

2012-01-01

In structural equation modeling software, either limited-information (bivariate proportions) or full-information item parameter estimation routines could be used for the 2-parameter item response theory (IRT) model. Limited-information methods assume the continuous variable underlying an item response is normally distributed. For skewed and…

FRAMES-2.0 Software System: Frames 2.0 Pest Integration (F2PEST)

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

Castleton, Karl J.; Meyer, Philip D.

2009-06-17

The implementation of the FRAMES 2.0 F2PEST module is described, including requirements, design, and specifications of the software. This module integrates the PEST parameter estimation software within the FRAMES 2.0 environmental modeling framework. A test case is presented.

NHPP-Based Software Reliability Models Using Equilibrium Distribution

NASA Astrophysics Data System (ADS)

Xiao, Xiao; Okamura, Hiroyuki; Dohi, Tadashi

Non-homogeneous Poisson processes (NHPPs) have gained much popularity in actual software testing phases to estimate the software reliability, the number of remaining faults in software and the software release timing. In this paper, we propose a new modeling approach for the NHPP-based software reliability models (SRMs) to describe the stochastic behavior of software fault-detection processes. The fundamental idea is to apply the equilibrium distribution to the fault-detection time distribution in NHPP-based modeling. We also develop efficient parameter estimation procedures for the proposed NHPP-based SRMs. Through numerical experiments, it can be concluded that the proposed NHPP-based SRMs outperform the existing ones in many data sets from the perspective of goodness-of-fit and prediction performance.

Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel.

PubMed

Dansirikul, Chantaratsamon; Choi, Malcolm; Duffull, Stephen B

2005-06-01

This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel spreadsheet was implemented with the use of Solver and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

Estimation of water quality parameters of inland and coastal waters with the use of a toolkit for processing of remote sensing data

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

Dekker, A.G.; Hoogenboom, H.J.; Rijkeboer, M.

1997-06-01

Deriving thematic maps of water quality parameters from a remote sensing image requires a number of processing steps, such as calibration, atmospheric correction, air/water interface correction, and application of water quality algorithms. A prototype software environment has recently been developed that enables the user to perform and control these processing steps. Main parts of this environment are: (i) access to the MODTRAN 3 radiative transfer code for removing atmospheric and air-water interface influences, (ii) a tool for analyzing of algorithms for estimating water quality and (iii) a spectral database, containing apparent and inherent optical properties and associated water quality parameters.more » The use of the software is illustrated by applying implemented algorithms for estimating chlorophyll to data from a spectral library of Dutch inland waters with CHL ranging from 1 to 500 pg 1{sup -1}. The algorithms currently implemented in the Toolkit software are recommended for optically simple waters, but for optically complex waters development of more advanced retrieval methods is required.« less

Assessment and modeling of the groundwater hydrogeochemical quality parameters via geostatistical approaches

NASA Astrophysics Data System (ADS)

Karami, Shawgar; Madani, Hassan; Katibeh, Homayoon; Fatehi Marj, Ahmad

2018-03-01

Geostatistical methods are one of the advanced techniques used for interpolation of groundwater quality data. The results obtained from geostatistics will be useful for decision makers to adopt suitable remedial measures to protect the quality of groundwater sources. Data used in this study were collected from 78 wells in Varamin plain aquifer located in southeast of Tehran, Iran, in 2013. Ordinary kriging method was used in this study to evaluate groundwater quality parameters. According to what has been mentioned in this paper, seven main quality parameters (i.e. total dissolved solids (TDS), sodium adsorption ratio (SAR), electrical conductivity (EC), sodium (Na+), total hardness (TH), chloride (Cl-) and sulfate (SO4 2-)), have been analyzed and interpreted by statistical and geostatistical methods. After data normalization by Nscore method in WinGslib software, variography as a geostatistical tool to define spatial regression was compiled and experimental variograms were plotted by GS+ software. Then, the best theoretical model was fitted to each variogram based on the minimum RSS. Cross validation method was used to determine the accuracy of the estimated data. Eventually, estimation maps of groundwater quality were prepared in WinGslib software and estimation variance map and estimation error map were presented to evaluate the quality of estimation in each estimated point. Results showed that kriging method is more accurate than the traditional interpolation methods.

HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.

PubMed

Wiecki, Thomas V; Sofer, Imri; Frank, Michael J

2013-01-01

The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of response time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model), which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject/condition than non-hierarchical methods, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g., fMRI) influence decision-making parameters. This paper will first describe the theoretical background of the drift diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the χ(2)-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs/

Proceedings of the Workshop on Computational Aspects in the Control of Flexible Systems, part 2

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr. (Compiler)

1989-01-01

The Control/Structures Integration Program, a survey of available software for control of flexible structures, computational efficiency and capability, modeling and parameter estimation, and control synthesis and optimization software are discussed.

Estimation of octanol/water partition coefficients using LSER parameters

USGS Publications Warehouse

Luehrs, Dean C.; Hickey, James P.; Godbole, Kalpana A.; Rogers, Tony N.

1998-01-01

The logarithms of octanol/water partition coefficients, logKow, were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for logKow was 0.49. The regression equation was then used to estimate logKow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.

Phenological Parameters Estimation Tool

NASA Technical Reports Server (NTRS)

McKellip, Rodney D.; Ross, Kenton W.; Spruce, Joseph P.; Smoot, James C.; Ryan, Robert E.; Gasser, Gerald E.; Prados, Donald L.; Vaughan, Ronald D.

2010-01-01

The Phenological Parameters Estimation Tool (PPET) is a set of algorithms implemented in MATLAB that estimates key vegetative phenological parameters. For a given year, the PPET software package takes in temporally processed vegetation index data (3D spatio-temporal arrays) generated by the time series product tool (TSPT) and outputs spatial grids (2D arrays) of vegetation phenological parameters. As a precursor to PPET, the TSPT uses quality information for each pixel of each date to remove bad or suspect data, and then interpolates and digitally fills data voids in the time series to produce a continuous, smoothed vegetation index product. During processing, the TSPT displays NDVI (Normalized Difference Vegetation Index) time series plots and images from the temporally processed pixels. Both the TSPT and PPET currently use moderate resolution imaging spectroradiometer (MODIS) satellite multispectral data as a default, but each software package is modifiable and could be used with any high-temporal-rate remote sensing data collection system that is capable of producing vegetation indices. Raw MODIS data from the Aqua and Terra satellites is processed using the TSPT to generate a filtered time series data product. The PPET then uses the TSPT output to generate phenological parameters for desired locations. PPET output data tiles are mosaicked into a Conterminous United States (CONUS) data layer using ERDAS IMAGINE, or equivalent software package. Mosaics of the vegetation phenology data products are then reprojected to the desired map projection using ERDAS IMAGINE

An Algorithm and R Program for Fitting and Simulation of Pharmacokinetic and Pharmacodynamic Data.

PubMed

Li, Jijie; Yan, Kewei; Hou, Lisha; Du, Xudong; Zhu, Ping; Zheng, Li; Zhu, Cairong

2017-06-01

Pharmacokinetic/pharmacodynamic link models are widely used in dose-finding studies. By applying such models, the results of initial pharmacokinetic/pharmacodynamic studies can be used to predict the potential therapeutic dose range. This knowledge can improve the design of later comparative large-scale clinical trials by reducing the number of participants and saving time and resources. However, the modeling process can be challenging, time consuming, and costly, even when using cutting-edge, powerful pharmacological software. Here, we provide a freely available R program for expediently analyzing pharmacokinetic/pharmacodynamic data, including data importation, parameter estimation, simulation, and model diagnostics. First, we explain the theory related to the establishment of the pharmacokinetic/pharmacodynamic link model. Subsequently, we present the algorithms used for parameter estimation and potential therapeutic dose computation. The implementation of the R program is illustrated by a clinical example. The software package is then validated by comparing the model parameters and the goodness-of-fit statistics generated by our R package with those generated by the widely used pharmacological software WinNonlin. The pharmacokinetic and pharmacodynamic parameters as well as the potential recommended therapeutic dose can be acquired with the R package. The validation process shows that the parameters estimated using our package are satisfactory. The R program developed and presented here provides pharmacokinetic researchers with a simple and easy-to-access tool for pharmacokinetic/pharmacodynamic analysis on personal computers.

Estimation of Geodetic and Geodynamical Parameters with VieVS

NASA Technical Reports Server (NTRS)

Spicakova, Hana; Bohm, Johannes; Bohm, Sigrid; Nilsson, tobias; Pany, Andrea; Plank, Lucia; Teke, Kamil; Schuh, Harald

2010-01-01

Since 2008 the VLBI group at the Institute of Geodesy and Geophysics at TU Vienna has focused on the development of a new VLBI data analysis software called VieVS (Vienna VLBI Software). One part of the program, currently under development, is a unit for parameter estimation in so-called global solutions, where the connection of the single sessions is done by stacking at the normal equation level. We can determine time independent geodynamical parameters such as Love and Shida numbers of the solid Earth tides. Apart from the estimation of the constant nominal values of Love and Shida numbers for the second degree of the tidal potential, it is possible to determine frequency dependent values in the diurnal band together with the resonance frequency of Free Core Nutation. In this paper we show first results obtained from the 24-hour IVS R1 and R4 sessions.

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.

The effects of clutter-rejection filtering on estimating weather spectrum parameters

NASA Technical Reports Server (NTRS)

Davis, W. T.

1989-01-01

The effects of clutter-rejection filtering on estimating the weather parameters from pulse Doppler radar measurement data are investigated. The pulse pair method of estimating the spectrum mean and spectrum width of the weather is emphasized. The loss of sensitivity, a measure of the signal power lost due to filtering, is also considered. A flexible software tool developed to investigate these effects is described. It allows for simulated weather radar data, in which the user specifies an underlying truncated Gaussian spectrum, as well as for externally generated data which may be real or simulated. The filter may be implemented in either the time or the frequency domain. The software tool is validated by comparing unfiltered spectrum mean and width estimates to their true values, and by reproducing previously published results. The effects on the weather parameter estimates using simulated weather-only data are evaluated for five filters: an ideal filter, two infinite impulse response filters, and two finite impulse response filters. Results considering external data, consisting of weather and clutter data, are evaluated on a range cell by range cell basis. Finally, it is shown theoretically and by computer simulation that a linear phase response is not required for a clutter rejection filter preceeding pulse-pair parameter estimation.

Parameter estimation for the exponential-normal convolution model for background correction of affymetrix GeneChip data.

PubMed

McGee, Monnie; Chen, Zhongxue

2006-01-01

There are many methods of correcting microarray data for non-biological sources of error. Authors routinely supply software or code so that interested analysts can implement their methods. Even with a thorough reading of associated references, it is not always clear how requisite parts of the method are calculated in the software packages. However, it is important to have an understanding of such details, as this understanding is necessary for proper use of the output, or for implementing extensions to the model. In this paper, the calculation of parameter estimates used in Robust Multichip Average (RMA), a popular preprocessing algorithm for Affymetrix GeneChip brand microarrays, is elucidated. The background correction method for RMA assumes that the perfect match (PM) intensities observed result from a convolution of the true signal, assumed to be exponentially distributed, and a background noise component, assumed to have a normal distribution. A conditional expectation is calculated to estimate signal. Estimates of the mean and variance of the normal distribution and the rate parameter of the exponential distribution are needed to calculate this expectation. Simulation studies show that the current estimates are flawed; therefore, new ones are suggested. We examine the performance of preprocessing under the exponential-normal convolution model using several different methods to estimate the parameters.

Prediction of Software Reliability using Bio Inspired Soft Computing Techniques.

PubMed

Diwaker, Chander; Tomar, Pradeep; Poonia, Ramesh C; Singh, Vijander

2018-04-10

A lot of models have been made for predicting software reliability. The reliability models are restricted to using particular types of methodologies and restricted number of parameters. There are a number of techniques and methodologies that may be used for reliability prediction. There is need to focus on parameters consideration while estimating reliability. The reliability of a system may increase or decreases depending on the selection of different parameters used. Thus there is need to identify factors that heavily affecting the reliability of the system. In present days, reusability is mostly used in the various area of research. Reusability is the basis of Component-Based System (CBS). The cost, time and human skill can be saved using Component-Based Software Engineering (CBSE) concepts. CBSE metrics may be used to assess those techniques which are more suitable for estimating system reliability. Soft computing is used for small as well as large-scale problems where it is difficult to find accurate results due to uncertainty or randomness. Several possibilities are available to apply soft computing techniques in medicine related problems. Clinical science of medicine using fuzzy-logic, neural network methodology significantly while basic science of medicine using neural-networks-genetic algorithm most frequently and preferably. There is unavoidable interest shown by medical scientists to use the various soft computing methodologies in genetics, physiology, radiology, cardiology and neurology discipline. CBSE boost users to reuse the past and existing software for making new products to provide quality with a saving of time, memory space, and money. This paper focused on assessment of commonly used soft computing technique like Genetic Algorithm (GA), Neural-Network (NN), Fuzzy Logic, Support Vector Machine (SVM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). This paper presents working of soft computing techniques and assessment of soft computing techniques to predict reliability. The parameter considered while estimating and prediction of reliability are also discussed. This study can be used in estimation and prediction of the reliability of various instruments used in the medical system, software engineering, computer engineering and mechanical engineering also. These concepts can be applied to both software and hardware, to predict the reliability using CBSE.

PROUCL 4.0 SOFTWARE

EPA Science Inventory

Statistical inference, including both estimation and hypotheses testing approaches, is routinely used to: estimate environmental parameters of interest, such as exposure point concentration (EPC) terms, not-to-exceed values, and background level threshold values (BTVs) for contam...

Estimating multilevel logistic regression models when the number of clusters is low: a comparison of different statistical software procedures.

PubMed

Austin, Peter C

2010-04-22

Multilevel logistic regression models are increasingly being used to analyze clustered data in medical, public health, epidemiological, and educational research. Procedures for estimating the parameters of such models are available in many statistical software packages. There is currently little evidence on the minimum number of clusters necessary to reliably fit multilevel regression models. We conducted a Monte Carlo study to compare the performance of different statistical software procedures for estimating multilevel logistic regression models when the number of clusters was low. We examined procedures available in BUGS, HLM, R, SAS, and Stata. We found that there were qualitative differences in the performance of different software procedures for estimating multilevel logistic models when the number of clusters was low. Among the likelihood-based procedures, estimation methods based on adaptive Gauss-Hermite approximations to the likelihood (glmer in R and xtlogit in Stata) or adaptive Gaussian quadrature (Proc NLMIXED in SAS) tended to have superior performance for estimating variance components when the number of clusters was small, compared to software procedures based on penalized quasi-likelihood. However, only Bayesian estimation with BUGS allowed for accurate estimation of variance components when there were fewer than 10 clusters. For all statistical software procedures, estimation of variance components tended to be poor when there were only five subjects per cluster, regardless of the number of clusters.

Molecular radiotherapy: the NUKFIT software for calculating the time-integrated activity coefficient.

PubMed

Kletting, P; Schimmel, S; Kestler, H A; Hänscheid, H; Luster, M; Fernández, M; Bröer, J H; Nosske, D; Lassmann, M; Glatting, G

2013-10-01

Calculation of the time-integrated activity coefficient (residence time) is a crucial step in dosimetry for molecular radiotherapy. However, available software is deficient in that it is either not tailored for the use in molecular radiotherapy and/or does not include all required estimation methods. The aim of this work was therefore the development and programming of an algorithm which allows for an objective and reproducible determination of the time-integrated activity coefficient and its standard error. The algorithm includes the selection of a set of fitting functions from predefined sums of exponentials and the choice of an error model for the used data. To estimate the values of the adjustable parameters an objective function, depending on the data, the parameters of the error model, the fitting function and (if required and available) Bayesian information, is minimized. To increase reproducibility and user-friendliness the starting values are automatically determined using a combination of curve stripping and random search. Visual inspection, the coefficient of determination, the standard error of the fitted parameters, and the correlation matrix are provided to evaluate the quality of the fit. The functions which are most supported by the data are determined using the corrected Akaike information criterion. The time-integrated activity coefficient is estimated by analytically integrating the fitted functions. Its standard error is determined assuming Gaussian error propagation. The software was implemented using MATLAB. To validate the proper implementation of the objective function and the fit functions, the results of NUKFIT and SAAM numerical, a commercially available software tool, were compared. The automatic search for starting values was successfully tested for reproducibility. The quality criteria applied in conjunction with the Akaike information criterion allowed the selection of suitable functions. Function fit parameters and their standard error estimated by using SAAM numerical and NUKFIT showed differences of <1%. The differences for the time-integrated activity coefficients were also <1% (standard error between 0.4% and 3%). In general, the application of the software is user-friendly and the results are mathematically correct and reproducible. An application of NUKFIT is presented for three different clinical examples. The software tool with its underlying methodology can be employed to objectively and reproducibly estimate the time integrated activity coefficient and its standard error for most time activity data in molecular radiotherapy.

Nonstationary Extreme Value Analysis in a Changing Climate: A Software Package

NASA Astrophysics Data System (ADS)

Cheng, L.; AghaKouchak, A.; Gilleland, E.

2013-12-01

Numerous studies show that climatic extremes have increased substantially in the second half of the 20th century. For this reason, analysis of extremes under a nonstationary assumption has received a great deal of attention. This paper presents a software package developed for estimation of return levels, return periods, and risks of climatic extremes in a changing climate. This MATLAB software package offers tools for analysis of climate extremes under both stationary and non-stationary assumptions. The Nonstationary Extreme Value Analysis (hereafter, NEVA) provides an efficient and generalized framework for analyzing extremes using Bayesian inference. NEVA estimates the extreme value parameters using a Differential Evolution Markov Chain (DE-MC) which utilizes the genetic algorithm Differential Evolution (DE) for global optimization over the real parameter space with the Markov Chain Monte Carlo (MCMC) approach and has the advantage of simplicity, speed of calculation and convergence over conventional MCMC. NEVA also offers the confidence interval and uncertainty bounds of estimated return levels based on the sampled parameters. NEVA integrates extreme value design concepts, data analysis tools, optimization and visualization, explicitly designed to facilitate analysis extremes in geosciences. The generalized input and output files of this software package make it attractive for users from across different fields. Both stationary and nonstationary components of the package are validated for a number of case studies using empirical return levels. The results show that NEVA reliably describes extremes and their return levels.

A Comprehensive Software and Database Management System for Glomerular Filtration Rate Estimation by Radionuclide Plasma Sampling and Serum Creatinine Methods.

PubMed

Jha, Ashish Kumar

2015-01-01

Glomerular filtration rate (GFR) estimation by plasma sampling method is considered as the gold standard. However, this method is not widely used because the complex technique and cumbersome calculations coupled with the lack of availability of user-friendly software. The routinely used Serum Creatinine method (SrCrM) of GFR estimation also requires the use of online calculators which cannot be used without internet access. We have developed user-friendly software "GFR estimation software" which gives the options to estimate GFR by plasma sampling method as well as SrCrM. We have used Microsoft Windows(®) as operating system and Visual Basic 6.0 as the front end and Microsoft Access(®) as database tool to develop this software. We have used Russell's formula for GFR calculation by plasma sampling method. GFR calculations using serum creatinine have been done using MIRD, Cockcroft-Gault method, Schwartz method, and Counahan-Barratt methods. The developed software is performing mathematical calculations correctly and is user-friendly. This software also enables storage and easy retrieval of the raw data, patient's information and calculated GFR for further processing and comparison. This is user-friendly software to calculate the GFR by various plasma sampling method and blood parameter. This software is also a good system for storing the raw and processed data for future analysis.

Formation of Minor Phases in a Nickel-Based Disk Superalloy

NASA Technical Reports Server (NTRS)

Gabb, T. P.; Garg, A.; Miller, D. R.; Sudbrack, C. K.; Hull, D. R.; Johnson, D.; Rogers, R. B.; Gayda, J.; Semiatin, S. L.

2012-01-01

The minor phases of powder metallurgy disk superalloy LSHR were studied. Samples were consistently heat treated at three different temperatures for long times to approximate equilibrium. Additional heat treatments were also performed for shorter times, to then assess non-equilibrium conditions. Minor phases including MC carbides, M23C6 carbides, M3B2 borides, and sigma were identified. Their transformation temperatures, lattice parameters, compositions, average sizes and total area fractions were determined, and compared to estimates of an existing phase prediction software package. Parameters measured at equilibrium sometimes agreed reasonably well with software model estimates, with potential for further improvements. Results for shorter times representing non-equilibrium indicated significant potential for further extension of the software to such conditions, which are more commonly observed during heat treatments and service at high temperatures for disk applications.

Method and system for diagnostics of apparatus

NASA Technical Reports Server (NTRS)

Gorinevsky, Dimitry (Inventor)

2012-01-01

Proposed is a method, implemented in software, for estimating fault state of an apparatus outfitted with sensors. At each execution period the method processes sensor data from the apparatus to obtain a set of parity parameters, which are further used for estimating fault state. The estimation method formulates a convex optimization problem for each fault hypothesis and employs a convex solver to compute fault parameter estimates and fault likelihoods for each fault hypothesis. The highest likelihoods and corresponding parameter estimates are transmitted to a display device or an automated decision and control system. The obtained accurate estimate of fault state can be used to improve safety, performance, or maintenance processes for the apparatus.

Digital adaptive controllers for VTOL vehicles. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Hartmann, G. L.; Stein, G.; Pratt, S. G.

1979-01-01

The VTOL approach and landing test (VALT) adaptive software is documented. Two self-adaptive algorithms, one based on an implicit model reference design and the other on an explicit parameter estimation technique were evaluated. The organization of the software, user options, and a nominal set of input data are presented along with a flow chart and program listing of each algorithm.

Advanced multilateration theory, software development, and data processing: The MICRODOT system

NASA Technical Reports Server (NTRS)

Escobal, P. R.; Gallagher, J. F.; Vonroos, O. H.

1976-01-01

The process of geometric parameter estimation to accuracies of one centimeter, i.e., multilateration, is defined and applications are listed. A brief functional explanation of the theory is presented. Next, various multilateration systems are described in order of increasing system complexity. Expected systems accuracy is discussed from a general point of view and a summary of the errors is listed. An outline of the design of a software processing system for multilateration, called MICRODOT, is presented next. The links of this software, which can be used for multilateration data simulations or operational data reduction, are examined on an individual basis. Functional flow diagrams are presented to aid in understanding the software capability. MICRODOT capability is described with respect to vehicle configurations, interstation coordinate reduction, geophysical parameter estimation, and orbit determination. Numerical results obtained from MICRODOT via data simulations are displayed both for hypothetical and real world vehicle/station configurations such as used in the GEOS-3 Project. These simulations show the inherent power of the multilateration procedure.

Proceedings of the Workshop on Computational Aspects in the Control of Flexible Systems, part 1

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr. (Compiler)

1989-01-01

Control/Structures Integration program software needs, computer aided control engineering for flexible spacecraft, computer aided design, computational efficiency and capability, modeling and parameter estimation, and control synthesis and optimization software for flexible structures and robots are among the topics discussed.

Multirate state and parameter estimation in an antibiotic fermentation with delayed measurements.

PubMed

Gudi, R D; Shah, S L; Gray, M R

1994-12-01

This article discusses issues related to estimation and monitoring of fermentation processes that exhibit endogenous metabolism and time-varying maintenance activity. Such culture-related activities hamper the use of traditional, software sensor-based algorithms, such as the extended kalman filter (EKF). In the approach presented here, the individual effects of the endogenous decay and the true maintenance processes have been lumped to represent a modified maintenance coefficient, m(c). Model equations that relate measurable process outputs, such as the carbon dioxide evolution rate (CER) and biomass, to the observable process parameters (such as net specific growth rate and the modified maintenance coefficient) are proposed. These model equations are used in an estimator that can formally accommodate delayed, infrequent measurements of the culture states (such as the biomass) as well as frequent, culture-related secondary measurements (such as the CER). The resulting multirate software sensor-based estimation strategy is used to monitor biomass profiles as well as profiles of critical fermentation parameters, such as the specific growth for a fed-batch fermentation of Streptomyces clavuligerus.

Noncoherent sampling technique for communications parameter estimations

NASA Technical Reports Server (NTRS)

Su, Y. T.; Choi, H. J.

1985-01-01

This paper presents a method of noncoherent demodulation of the PSK signal for signal distortion analysis at the RF interface. The received RF signal is downconverted and noncoherently sampled for further off-line processing. Any mismatch in phase and frequency is then compensated for by the software using the estimation techniques to extract the baseband waveform, which is needed in measuring various signal parameters. In this way, various kinds of modulated signals can be treated uniformly, independent of modulation format, and additional distortions introduced by the receiver or the hardware measurement instruments can thus be eliminated. Quantization errors incurred by digital sampling and ensuing software manipulations are analyzed and related numerical results are presented also.

Equilibrium expert: an add-in to Microsoft Excel for multiple binding equilibrium simulations and parameter estimations.

PubMed

Raguin, Olivier; Gruaz-Guyon, Anne; Barbet, Jacques

2002-11-01

An add-in to Microsoft Excel was developed to simulate multiple binding equilibriums. A partition function, readily written even when the equilibrium is complex, describes the experimental system. It involves the concentrations of the different free molecular species and of the different complexes present in the experiment. As a result, the software is not restricted to a series of predefined experimental setups but can handle a large variety of problems involving up to nine independent molecular species. Binding parameters are estimated by nonlinear least-square fitting of experimental measurements as supplied by the user. The fitting process allows user-defined weighting of the experimental data. The flexibility of the software and the way it may be used to describe common experimental situations and to deal with usual problems such as tracer reactivity or nonspecific binding is demonstrated by a few examples. The software is available free of charge upon request.

Dynamic Testing of a Pre-stretched Flexible Tube for Identifying the Factors Affecting Modal Parameter Estimation

NASA Astrophysics Data System (ADS)

Unnikrishnan, Madhusudanan; Rajan, Akash; Basanthvihar Raghunathan, Binulal; Kochupillai, Jayaraj

2017-08-01

Experimental modal analysis is the primary tool for obtaining the fundamental dynamic characteristics like natural frequency, mode shape and modal damping ratio that determine the behaviour of any structure under dynamic loading conditions. This paper discusses about a carefully designed experimental method for calculating the dynamic characteristics of a pre-stretched horizontal flexible tube made of polyurethane material. The factors that affect the modal parameter estimation like the application time of shaker excitation, pause time between successive excitation cycles, averaging and windowing of measured signal, as well as the precautions to be taken during the experiment are explained in detail. The modal parameter estimation is done using MEscopeVESTM software. A finite element based pre-stressed modal analysis of the flexible tube is also done using ANSYS ver.14.0 software. The experimental and analytical results agreed well. The proposed experimental methodology may be extended for carrying out the modal analysis of many flexible structures like inflatables, tires and membranes.

System IDentification Programs for AirCraft (SIDPAC)

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2002-01-01

A collection of computer programs for aircraft system identification is described and demonstrated. The programs, collectively called System IDentification Programs for AirCraft, or SIDPAC, were developed in MATLAB as m-file functions. SIDPAC has been used successfully at NASA Langley Research Center with data from many different flight test programs and wind tunnel experiments. SIDPAC includes routines for experiment design, data conditioning, data compatibility analysis, model structure determination, equation-error and output-error parameter estimation in both the time and frequency domains, real-time and recursive parameter estimation, low order equivalent system identification, estimated parameter error calculation, linear and nonlinear simulation, plotting, and 3-D visualization. An overview of SIDPAC capabilities is provided, along with a demonstration of the use of SIDPAC with real flight test data from the NASA Glenn Twin Otter aircraft. The SIDPAC software is available without charge to U.S. citizens by request to the author, contingent on the requestor completing a NASA software usage agreement.

Evaluation of bond strength of resin cements using different general-purpose statistical software packages for two-parameter Weibull statistics.

PubMed

Roos, Malgorzata; Stawarczyk, Bogna

2012-07-01

This study evaluated and compared Weibull parameters of resin bond strength values using six different general-purpose statistical software packages for two-parameter Weibull distribution. Two-hundred human teeth were randomly divided into 4 groups (n=50), prepared and bonded on dentin according to the manufacturers' instructions using the following resin cements: (i) Variolink (VAN, conventional resin cement), (ii) Panavia21 (PAN, conventional resin cement), (iii) RelyX Unicem (RXU, self-adhesive resin cement) and (iv) G-Cem (GCM, self-adhesive resin cement). Subsequently, all specimens were stored in water for 24h at 37°C. Shear bond strength was measured and the data were analyzed using Anderson-Darling goodness-of-fit (MINITAB 16) and two-parameter Weibull statistics with the following statistical software packages: Excel 2011, SPSS 19, MINITAB 16, R 2.12.1, SAS 9.1.3. and STATA 11.2 (p≤0.05). Additionally, the three-parameter Weibull was fitted using MNITAB 16. Two-parameter Weibull calculated with MINITAB and STATA can be compared using an omnibus test and using 95% CI. In SAS only 95% CI were directly obtained from the output. R provided no estimates of 95% CI. In both SAS and R the global comparison of the characteristic bond strength among groups is provided by means of the Weibull regression. EXCEL and SPSS provided no default information about 95% CI and no significance test for the comparison of Weibull parameters among the groups. In summary, conventional resin cement VAN showed the highest Weibull modulus and characteristic bond strength. There are discrepancies in the Weibull statistics depending on the software package and the estimation method. The information content in the default output provided by the software packages differs to very high extent. Copyright © 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Multistage Estimation Of Frequency And Phase

NASA Technical Reports Server (NTRS)

Kumar, Rajendra

1991-01-01

Conceptual two-stage software scheme serves as prototype of multistage scheme for digital estimation of phase, frequency, and rate of change of frequency ("Doppler rate") of possibly phase-modulated received sinusoidal signal in communication system in which transmitter and/or receiver traveling rapidly, accelerating, and/or jerking severely. Each additional stage of multistage scheme provides increasingly refined estimate of frequency and phase of signal. Conceived for use in estimating parameters of signals from spacecraft and high dynamic GPS signal parameters, also applicable, to terrestrial stationary/mobile (e.g., cellular radio) and land-mobile/satellite communication systems.

A Short Note on Estimating the Testlet Model with Different Estimators in Mplus

ERIC Educational Resources Information Center

Luo, Yong

2018-01-01

Mplus is a powerful latent variable modeling software program that has become an increasingly popular choice for fitting complex item response theory models. In this short note, we demonstrate that the two-parameter logistic testlet model can be estimated as a constrained bifactor model in Mplus with three estimators encompassing limited- and…

Application of square-root filtering for spacecraft attitude control

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Schmidt, S. F.; Goka, T.

1978-01-01

Suitable digital algorithms are developed and tested for providing on-board precision attitude estimation and pointing control for potential use in the Landsat-D spacecraft. These algorithms provide pointing accuracy of better than 0.01 deg. To obtain necessary precision with efficient software, a six state-variable square-root Kalman filter combines two star tracker measurements to update attitude estimates obtained from processing three gyro outputs. The validity of the estimation and control algorithms are established, and the sensitivity of their performance to various error sources and software parameters are investigated by detailed digital simulation. Spacecraft computer memory, cycle time, and accuracy requirements are estimated.

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

CEval: All-in-one software for data processing and statistical evaluations in affinity capillary electrophoresis.

PubMed

Dubský, Pavel; Ördögová, Magda; Malý, Michal; Riesová, Martina

2016-05-06

We introduce CEval software (downloadable for free at echmet.natur.cuni.cz) that was developed for quicker and easier electrophoregram evaluation and further data processing in (affinity) capillary electrophoresis. This software allows for automatic peak detection and evaluation of common peak parameters, such as its migration time, area, width etc. Additionally, the software includes a nonlinear regression engine that performs peak fitting with the Haarhoff-van der Linde (HVL) function, including automated initial guess of the HVL function parameters. HVL is a fundamental peak-shape function in electrophoresis, based on which the correct effective mobility of the analyte represented by the peak is evaluated. Effective mobilities of an analyte at various concentrations of a selector can be further stored and plotted in an affinity CE mode. Consequently, the mobility of the free analyte, μA, mobility of the analyte-selector complex, μAS, and the apparent complexation constant, K('), are first guessed automatically from the linearized data plots and subsequently estimated by the means of nonlinear regression. An option that allows two complexation dependencies to be fitted at once is especially convenient for enantioseparations. Statistical processing of these data is also included, which allowed us to: i) express the 95% confidence intervals for the μA, μAS and K(') least-squares estimates, ii) do hypothesis testing on the estimated parameters for the first time. We demonstrate the benefits of the CEval software by inspecting complexation of tryptophan methyl ester with two cyclodextrins, neutral heptakis(2,6-di-O-methyl)-β-CD and charged heptakis(6-O-sulfo)-β-CD. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimating soil hydraulic parameters from transient flow experiments in a centrifuge using parameter optimization technique

USGS Publications Warehouse

Šimůnek, Jirka; Nimmo, John R.

2005-01-01

A modified version of the Hydrus software package that can directly or inversely simulate water flow in a transient centrifugal field is presented. The inverse solver for parameter estimation of the soil hydraulic parameters is then applied to multirotation transient flow experiments in a centrifuge. Using time‐variable water contents measured at a sequence of several rotation speeds, soil hydraulic properties were successfully estimated by numerical inversion of transient experiments. The inverse method was then evaluated by comparing estimated soil hydraulic properties with those determined independently using an equilibrium analysis. The optimized soil hydraulic properties compared well with those determined using equilibrium analysis and steady state experiment. Multirotation experiments in a centrifuge not only offer significant time savings by accelerating time but also provide significantly more information for the parameter estimation procedure compared to multistep outflow experiments in a gravitational field.

Application of troposphere model from NWP and GNSS data into real-time precise positioning

NASA Astrophysics Data System (ADS)

Wilgan, Karina; Hadas, Tomasz; Kazmierski, Kamil; Rohm, Witold; Bosy, Jaroslaw

2016-04-01

The tropospheric delay empirical models are usually functions of meteorological parameters (temperature, pressure and humidity). The application of standard atmosphere parameters or global models, such as GPT (global pressure/temperature) model or UNB3 (University of New Brunswick, version 3) model, may not be sufficient, especially for positioning in non-standard weather conditions. The possible solution is to use regional troposphere models based on real-time or near-real time measurements. We implement a regional troposphere model into the PPP (Precise Point Positioning) software GNSS-WARP (Wroclaw Algorithms for Real-time Positioning) developed at Wroclaw University of Environmental and Life Sciences. The software is capable of processing static and kinematic multi-GNSS data in real-time and post-processing mode and takes advantage of final IGS (International GNSS Service) products as well as IGS RTS (Real-Time Service) products. A shortcoming of PPP technique is the time required for the solution to converge. One of the reasons is the high correlation among the estimated parameters: troposphere delay, receiver clock offset and receiver height. To efficiently decorrelate these parameters, a significant change in satellite geometry is required. Alternative solution is to introduce the external high-quality regional troposphere delay model to constrain troposphere estimates. The proposed model consists of zenith total delays (ZTD) and mapping functions calculated from meteorological parameters from Numerical Weather Prediction model WRF (Weather Research and Forecasting) and ZTDs from ground-based GNSS stations using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays) developed at ETH Zurich.

Predicting tool life in turning operations using neural networks and image processing

NASA Astrophysics Data System (ADS)

Mikołajczyk, T.; Nowicki, K.; Bustillo, A.; Yu Pimenov, D.

2018-05-01

A two-step method is presented for the automatic prediction of tool life in turning operations. First, experimental data are collected for three cutting edges under the same constant processing conditions. In these experiments, the parameter of tool wear, VB, is measured with conventional methods and the same parameter is estimated using Neural Wear, a customized software package that combines flank wear image recognition and Artificial Neural Networks (ANNs). Second, an ANN model of tool life is trained with the data collected from the first two cutting edges and the subsequent model is evaluated on two different subsets for the third cutting edge: the first subset is obtained from the direct measurement of tool wear and the second is obtained from the Neural Wear software that estimates tool wear using edge images. Although the complete-automated solution, Neural Wear software for tool wear recognition plus the ANN model of tool life prediction, presented a slightly higher error than the direct measurements, it was within the same range and can meet all industrial requirements. These results confirm that the combination of image recognition software and ANN modelling could potentially be developed into a useful industrial tool for low-cost estimation of tool life in turning operations.

Methodology for Software Reliability Prediction. Volume 2.

DTIC Science & Technology

1987-11-01

The overall acquisition ,z program shall include the resources, schedule, management, structure , and controls necessary to ensure that specified AD...Independent Verification/Validation - Programming Team Structure - Educational Level of Team Members - Experience Level of Team Members * Methods Used...Prediction or Estimation Parameter Supported: Software - Characteristics 3. Objectives: Structured programming studies and Government Ur.’.. procurement

TOWARD DEVELOPMENT OF A COMMON SOFTWARE APPLICATION PROGRAMMING INTERFACE (API) FOR UNCERTAINTY, SENSITIVITY, AND PARAMETER ESTIMATION METHODS AND TOOLS

EPA Science Inventory

The final session of the workshop considered the subject of software technology and how it might be better constructed to support those who develop, evaluate, and apply multimedia environmental models. Two invited presentations were featured along with an extended open discussio...

ConvAn: a convergence analyzing tool for optimization of biochemical networks.

PubMed

Kostromins, Andrejs; Mozga, Ivars; Stalidzans, Egils

2012-01-01

Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations

USGS Publications Warehouse

Ward, Adam S.; Kelleher, Christa A.; Mason, Seth J. K.; Wagener, Thorsten; McIntyre, Neil; McGlynn, Brian L.; Runkel, Robert L.; Payn, Robert A.

2017-01-01

Researchers and practitioners alike often need to understand and characterize how water and solutes move through a stream in terms of the relative importance of in-stream and near-stream storage and transport processes. In-channel and subsurface storage processes are highly variable in space and time and difficult to measure. Storage estimates are commonly obtained using transient-storage models (TSMs) of the experimentally obtained solute-tracer test data. The TSM equations represent key transport and storage processes with a suite of numerical parameters. Parameter values are estimated via inverse modeling, in which parameter values are iteratively changed until model simulations closely match observed solute-tracer data. Several investigators have shown that TSM parameter estimates can be highly uncertain. When this is the case, parameter values cannot be used reliably to interpret stream-reach functioning. However, authors of most TSM studies do not evaluate or report parameter certainty. Here, we present a software tool linked to the One-dimensional Transport with Inflow and Storage (OTIS) model that enables researchers to conduct uncertainty analyses via Monte-Carlo parameter sampling and to visualize uncertainty and sensitivity results. We demonstrate application of our tool to 2 case studies and compare our results to output obtained from more traditional implementation of the OTIS model. We conclude by suggesting best practices for transient-storage modeling and recommend that future applications of TSMs include assessments of parameter certainty to support comparisons and more reliable interpretations of transport processes.

Nitrous oxide emissions from cropland: a procedure for calibrating the DayCent biogeochemical model using inverse modelling

USGS Publications Warehouse

Rafique, Rashad; Fienen, Michael N.; Parkin, Timothy B.; Anex, Robert P.

2013-01-01

DayCent is a biogeochemical model of intermediate complexity widely used to simulate greenhouse gases (GHG), soil organic carbon and nutrients in crop, grassland, forest and savannah ecosystems. Although this model has been applied to a wide range of ecosystems, it is still typically parameterized through a traditional “trial and error” approach and has not been calibrated using statistical inverse modelling (i.e. algorithmic parameter estimation). The aim of this study is to establish and demonstrate a procedure for calibration of DayCent to improve estimation of GHG emissions. We coupled DayCent with the parameter estimation (PEST) software for inverse modelling. The PEST software can be used for calibration through regularized inversion as well as model sensitivity and uncertainty analysis. The DayCent model was analysed and calibrated using N2O flux data collected over 2 years at the Iowa State University Agronomy and Agricultural Engineering Research Farms, Boone, IA. Crop year 2003 data were used for model calibration and 2004 data were used for validation. The optimization of DayCent model parameters using PEST significantly reduced model residuals relative to the default DayCent parameter values. Parameter estimation improved the model performance by reducing the sum of weighted squared residual difference between measured and modelled outputs by up to 67 %. For the calibration period, simulation with the default model parameter values underestimated mean daily N2O flux by 98 %. After parameter estimation, the model underestimated the mean daily fluxes by 35 %. During the validation period, the calibrated model reduced sum of weighted squared residuals by 20 % relative to the default simulation. Sensitivity analysis performed provides important insights into the model structure providing guidance for model improvement.

Calibration of a COTS Integration Cost Model Using Local Project Data

NASA Technical Reports Server (NTRS)

Boland, Dillard; Coon, Richard; Byers, Kathryn; Levitt, David

1997-01-01

The software measures and estimation techniques appropriate to a Commercial Off the Shelf (COTS) integration project differ from those commonly used for custom software development. Labor and schedule estimation tools that model COTS integration are available. Like all estimation tools, they must be calibrated with the organization's local project data. This paper describes the calibration of a commercial model using data collected by the Flight Dynamics Division (FDD) of the NASA Goddard Spaceflight Center (GSFC). The model calibrated is SLIM Release 4.0 from Quantitative Software Management (QSM). By adopting the SLIM reuse model and by treating configuration parameters as lines of code, we were able to establish a consistent calibration for COTS integration projects. The paper summarizes the metrics, the calibration process and results, and the validation of the calibration.

Computational tools for fitting the Hill equation to dose-response curves.

PubMed

Gadagkar, Sudhindra R; Call, Gerald B

2015-01-01

Many biological response curves commonly assume a sigmoidal shape that can be approximated well by means of the 4-parameter nonlinear logistic equation, also called the Hill equation. However, estimation of the Hill equation parameters requires access to commercial software or the ability to write computer code. Here we present two user-friendly and freely available computer programs to fit the Hill equation - a Solver-based Microsoft Excel template and a stand-alone GUI-based "point and click" program, called HEPB. Both computer programs use the iterative method to estimate two of the Hill equation parameters (EC50 and the Hill slope), while constraining the values of the other two parameters (the minimum and maximum asymptotes of the response variable) to fit the Hill equation to the data. In addition, HEPB draws the prediction band at a user-defined confidence level, and determines the EC50 value for each of the limits of this band to give boundary values that help objectively delineate sensitive, normal and resistant responses to the drug being tested. Both programs were tested by analyzing twelve datasets that varied widely in data values, sample size and slope, and were found to yield estimates of the Hill equation parameters that were essentially identical to those provided by commercial software such as GraphPad Prism and nls, the statistical package in the programming language R. The Excel template provides a means to estimate the parameters of the Hill equation and plot the regression line in a familiar Microsoft Office environment. HEPB, in addition to providing the above results, also computes the prediction band for the data at a user-defined level of confidence, and determines objective cut-off values to distinguish among response types (sensitive, normal and resistant). Both programs are found to yield estimated values that are essentially the same as those from standard software such as GraphPad Prism and the R-based nls. Furthermore, HEPB also has the option to simulate 500 response values based on the range of values of the dose variable in the original data and the fit of the Hill equation to that data. Copyright © 2014. Published by Elsevier Inc.

INFOS: spectrum fitting software for NMR analysis.

PubMed

Smith, Albert A

2017-02-01

Software for fitting of NMR spectra in MATLAB is presented. Spectra are fitted in the frequency domain, using Fourier transformed lineshapes, which are derived using the experimental acquisition and processing parameters. This yields more accurate fits compared to common fitting methods that use Lorentzian or Gaussian functions. Furthermore, a very time-efficient algorithm for calculating and fitting spectra has been developed. The software also performs initial peak picking, followed by subsequent fitting and refinement of the peak list, by iteratively adding and removing peaks to improve the overall fit. Estimation of error on fitting parameters is performed using a Monte-Carlo approach. Many fitting options allow the software to be flexible enough for a wide array of applications, while still being straightforward to set up with minimal user input.

Operations analysis (study 2.1): Shuttle upper stage software requirements

NASA Technical Reports Server (NTRS)

Wolfe, R. R.

1974-01-01

An investigation of software costs related to space shuttle upper stage operations with emphasis on the additional costs attributable to space servicing was conducted. The questions and problem areas include the following: (1) the key parameters involved with software costs; (2) historical data for extrapolation of future costs; (3) elements of the basic software development effort that are applicable to servicing functions; (4) effect of multiple servicing on complexity of the operation; and (5) are recurring software costs significant. The results address these questions and provide a foundation for estimating software costs based on the costs of similar programs and a series of empirical factors.

F-8C adaptive control law refinement and software development

NASA Technical Reports Server (NTRS)

Hartmann, G. L.; Stein, G.

1981-01-01

An explicit adaptive control algorithm based on maximum likelihood estimation of parameters was designed. To avoid iterative calculations, the algorithm uses parallel channels of Kalman filters operating at fixed locations in parameter space. This algorithm was implemented in NASA/DFRC's Remotely Augmented Vehicle (RAV) facility. Real-time sensor outputs (rate gyro, accelerometer, surface position) are telemetered to a ground computer which sends new gain values to an on-board system. Ground test data and flight records were used to establish design values of noise statistics and to verify the ground-based adaptive software.

Estimating BrAC from transdermal alcohol concentration data using the BrAC estimator software program.

PubMed

Luczak, Susan E; Rosen, I Gary

2014-08-01

Transdermal alcohol sensor (TAS) devices have the potential to allow researchers and clinicians to unobtrusively collect naturalistic drinking data for weeks at a time, but the transdermal alcohol concentration (TAC) data these devices produce do not consistently correspond with breath alcohol concentration (BrAC) data. We present and test the BrAC Estimator software, a program designed to produce individualized estimates of BrAC from TAC data by fitting mathematical models to a specific person wearing a specific TAS device. Two TAS devices were worn simultaneously by 1 participant for 18 days. The trial began with a laboratory alcohol session to calibrate the model and was followed by a field trial with 10 drinking episodes. Model parameter estimates and fit indices were compared across drinking episodes to examine the calibration phase of the software. Software-generated estimates of peak BrAC, time of peak BrAC, and area under the BrAC curve were compared with breath analyzer data to examine the estimation phase of the software. In this single-subject design with breath analyzer peak BrAC scores ranging from 0.013 to 0.057, the software created consistent models for the 2 TAS devices, despite differences in raw TAC data, and was able to compensate for the attenuation of peak BrAC and latency of the time of peak BrAC that are typically observed in TAC data. This software program represents an important initial step for making it possible for non mathematician researchers and clinicians to obtain estimates of BrAC from TAC data in naturalistic drinking environments. Future research with more participants and greater variation in alcohol consumption levels and patterns, as well as examination of gain scheduling calibration procedures and nonlinear models of diffusion, will help to determine how precise these software models can become. Copyright © 2014 by the Research Society on Alcoholism.

Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

NASA Astrophysics Data System (ADS)

Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

2017-06-01

A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

Quantitative CT: technique dependence of volume estimation on pulmonary nodules

NASA Astrophysics Data System (ADS)

Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Colsher, James; Amurao, Maxwell; Samei, Ehsan

2012-03-01

Current estimation of lung nodule size typically relies on uni- or bi-dimensional techniques. While new three-dimensional volume estimation techniques using MDCT have improved size estimation of nodules with irregular shapes, the effect of acquisition and reconstruction parameters on accuracy (bias) and precision (variance) of the new techniques has not been fully investigated. To characterize the volume estimation performance dependence on these parameters, an anthropomorphic chest phantom containing synthetic nodules was scanned and reconstructed with protocols across various acquisition and reconstruction parameters. Nodule volumes were estimated by a clinical lung analysis software package, LungVCAR. Precision and accuracy of the volume assessment were calculated across the nodules and compared between protocols via a generalized estimating equation analysis. Results showed that the precision and accuracy of nodule volume quantifications were dependent on slice thickness, with different dependences for different nodule characteristics. Other parameters including kVp, pitch, and reconstruction kernel had lower impact. Determining these technique dependences enables better volume quantification via protocol optimization and highlights the importance of consistent imaging parameters in sequential examinations.

Logistic regression for circular data

NASA Astrophysics Data System (ADS)

Al-Daffaie, Kadhem; Khan, Shahjahan

2017-05-01

This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.

catcher: A Software Program to Detect Answer Copying in Multiple-Choice Tests Based on Nominal Response Model

ERIC Educational Resources Information Center

Kalender, Ilker

2012-01-01

catcher is a software program designed to compute the [omega] index, a common statistical index for the identification of collusions (cheating) among examinees taking an educational or psychological test. It requires (a) responses and (b) ability estimations of individuals, and (c) item parameters to make computations and outputs the results of…

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis :

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

Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S.

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components requiredmore » for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.« less

Improving phylogenetic analyses by incorporating additional information from genetic sequence databases.

PubMed

Liang, Li-Jung; Weiss, Robert E; Redelings, Benjamin; Suchard, Marc A

2009-10-01

Statistical analyses of phylogenetic data culminate in uncertain estimates of underlying model parameters. Lack of additional data hinders the ability to reduce this uncertainty, as the original phylogenetic dataset is often complete, containing the entire gene or genome information available for the given set of taxa. Informative priors in a Bayesian analysis can reduce posterior uncertainty; however, publicly available phylogenetic software specifies vague priors for model parameters by default. We build objective and informative priors using hierarchical random effect models that combine additional datasets whose parameters are not of direct interest but are similar to the analysis of interest. We propose principled statistical methods that permit more precise parameter estimates in phylogenetic analyses by creating informative priors for parameters of interest. Using additional sequence datasets from our lab or public databases, we construct a fully Bayesian semiparametric hierarchical model to combine datasets. A dynamic iteratively reweighted Markov chain Monte Carlo algorithm conveniently recycles posterior samples from the individual analyses. We demonstrate the value of our approach by examining the insertion-deletion (indel) process in the enolase gene across the Tree of Life using the phylogenetic software BALI-PHY; we incorporate prior information about indels from 82 curated alignments downloaded from the BAliBASE database.

Adaptive MCMC in Bayesian phylogenetics: an application to analyzing partitioned data in BEAST.

PubMed

Baele, Guy; Lemey, Philippe; Rambaut, Andrew; Suchard, Marc A

2017-06-15

Advances in sequencing technology continue to deliver increasingly large molecular sequence datasets that are often heavily partitioned in order to accurately model the underlying evolutionary processes. In phylogenetic analyses, partitioning strategies involve estimating conditionally independent models of molecular evolution for different genes and different positions within those genes, requiring a large number of evolutionary parameters that have to be estimated, leading to an increased computational burden for such analyses. The past two decades have also seen the rise of multi-core processors, both in the central processing unit (CPU) and Graphics processing unit processor markets, enabling massively parallel computations that are not yet fully exploited by many software packages for multipartite analyses. We here propose a Markov chain Monte Carlo (MCMC) approach using an adaptive multivariate transition kernel to estimate in parallel a large number of parameters, split across partitioned data, by exploiting multi-core processing. Across several real-world examples, we demonstrate that our approach enables the estimation of these multipartite parameters more efficiently than standard approaches that typically use a mixture of univariate transition kernels. In one case, when estimating the relative rate parameter of the non-coding partition in a heterochronous dataset, MCMC integration efficiency improves by > 14-fold. Our implementation is part of the BEAST code base, a widely used open source software package to perform Bayesian phylogenetic inference. guy.baele@kuleuven.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Regional Earthquake Shaking and Loss Estimation

NASA Astrophysics Data System (ADS)

Sesetyan, K.; Demircioglu, M. B.; Zulfikar, C.; Durukal, E.; Erdik, M.

2009-04-01

This study, conducted under the JRA-3 component of the EU NERIES Project, develops a methodology and software (ELER) for the rapid estimation of earthquake shaking and losses in the Euro-Mediterranean region. This multi-level methodology developed together with researchers from Imperial College, NORSAR and ETH-Zurich is capable of incorporating regional variability and sources of uncertainty stemming from ground motion predictions, fault finiteness, site modifications, inventory of physical and social elements subjected to earthquake hazard and the associated vulnerability relationships. GRM Risk Management, Inc. of Istanbul serves as sub-contractor tor the coding of the ELER software. The methodology encompasses the following general steps: 1. Finding of the most likely location of the source of the earthquake using regional seismotectonic data base and basic source parameters, and if and when possible, by the estimation of fault rupture parameters from rapid inversion of data from on-line stations. 2. Estimation of the spatial distribution of selected ground motion parameters through region specific ground motion attenuation relationships and using shear wave velocity distributions.(Shake Mapping) 4. Incorporation of strong ground motion and other empirical macroseismic data for the improvement of Shake Map 5. Estimation of the losses (damage, casualty and economic) at different levels of sophistication (0, 1 and 2) that commensurate with the availability of inventory of human built environment (Loss Mapping) Both Level 0 (similar to PAGER system of USGS) and Level 1 analyses of the ELER routine are based on obtaining intensity distributions analytically and estimating total number of casualties and their geographic distribution either using regionally adjusted intensity-casualty or magnitude-casualty correlations (Level 0) of using regional building inventory data bases (Level 1). Level 0 analysis is similar to the PAGER system being developed by USGS. For given basis source parameters the intensity distributions can be computed using: a)Regional intensity attenuation relationships, b)Intensity correlations with attenuation relationship based PGV, PGA, and Spectral Amplitudes and, c)Intensity correlations with synthetic Fourier Amplitude Spectrum. In Level 1 analysis EMS98 based building vulnerability relationships are used for regional estimates of building damage and the casualty distributions. Results obtained from pilot applications of the Level 0 and Level 1 analysis modes of the ELER software to the 1999 M 7.4 Kocaeli, 1995 M 6.1 Dinar, and 2007 M 5.4 Bingol earthquakes in terms of ground shaking and losses are presented and comparisons with the observed losses are made. The regional earthquake shaking and loss information is intented for dissemination in a timely manner to related agencies for the planning and coordination of the post-earthquake emergency response. However the same software can also be used for scenario earthquake loss estimation and related Monte-Carlo type simulations.

SigrafW: An easy-to-use program for fitting enzyme kinetic data.

PubMed

Leone, Francisco Assis; Baranauskas, José Augusto; Furriel, Rosa Prazeres Melo; Borin, Ivana Aparecida

2005-11-01

SigrafW is Windows-compatible software developed using the Microsoft® Visual Basic Studio program that uses the simplified Hill equation for fitting kinetic data from allosteric and Michaelian enzymes. SigrafW uses a modified Fibonacci search to calculate maximal velocity (V), the Hill coefficient (n), and the enzyme-substrate apparent dissociation constant (K). The estimation of V, K, and the sum of the squares of residuals is performed using a Wilkinson nonlinear regression at any Hill coefficient (n). In contrast to many currently available kinetic analysis programs, SigrafW shows several advantages for the determination of kinetic parameters of both hyperbolic and nonhyperbolic saturation curves. No initial estimates of the kinetic parameters are required, a measure of the goodness-of-the-fit for each calculation performed is provided, the nonlinear regression used for calculations eliminates the statistical bias inherent in linear transformations, and the software can be used for enzyme kinetic simulations either for educational or research purposes. Persons interested in receiving a free copy of the software should contact Dr. F. A. Leone. Copyright © 2005 International Union of Biochemistry and Molecular Biology, Inc.

Implementation and Simulation Results using Autonomous Aerobraking Development Software

NASA Technical Reports Server (NTRS)

Maddock, Robert W.; DwyerCianciolo, Alicia M.; Bowes, Angela; Prince, Jill L. H.; Powell, Richard W.

2011-01-01

An Autonomous Aerobraking software system is currently under development with support from the NASA Engineering and Safety Center (NESC) that would move typically ground-based operations functions to onboard an aerobraking spacecraft, reducing mission risk and mission cost. The suite of software that will enable autonomous aerobraking is the Autonomous Aerobraking Development Software (AADS) and consists of an ephemeris model, onboard atmosphere estimator, temperature and loads prediction, and a maneuver calculation. The software calculates the maneuver time, magnitude and direction commands to maintain the spacecraft periapsis parameters within design structural load and/or thermal constraints. The AADS is currently tested in simulations at Mars, with plans to also evaluate feasibility and performance at Venus and Titan.

Approaches in highly parameterized inversion: TSPROC, a general time-series processor to assist in model calibration and result summarization

USGS Publications Warehouse

Westenbroek, Stephen M.; Doherty, John; Walker, John F.; Kelson, Victor A.; Hunt, Randall J.; Cera, Timothy B.

2012-01-01

The TSPROC (Time Series PROCessor) computer software uses a simple scripting language to process and analyze time series. It was developed primarily to assist in the calibration of environmental models. The software is designed to perform calculations on time-series data commonly associated with surface-water models, including calculation of flow volumes, transformation by means of basic arithmetic operations, and generation of seasonal and annual statistics and hydrologic indices. TSPROC can also be used to generate some of the key input files required to perform parameter optimization by means of the PEST (Parameter ESTimation) computer software. Through the use of TSPROC, the objective function for use in the model-calibration process can be focused on specific components of a hydrograph.

A framework for scalable parameter estimation of gene circuit models using structural information.

PubMed

Kuwahara, Hiroyuki; Fan, Ming; Wang, Suojin; Gao, Xin

2013-07-01

Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. http://sfb.kaust.edu.sa/Pages/Software.aspx. Supplementary data are available at Bioinformatics online.

Profile-Likelihood Approach for Estimating Generalized Linear Mixed Models with Factor Structures

ERIC Educational Resources Information Center

Jeon, Minjeong; Rabe-Hesketh, Sophia

2012-01-01

In this article, the authors suggest a profile-likelihood approach for estimating complex models by maximum likelihood (ML) using standard software and minimal programming. The method works whenever setting some of the parameters of the model to known constants turns the model into a standard model. An important class of models that can be…

R programming for parameters estimation of geographically weighted ordinal logistic regression (GWOLR) model based on Newton Raphson

NASA Astrophysics Data System (ADS)

Zuhdi, Shaifudin; Saputro, Dewi Retno Sari

2017-03-01

GWOLR model used for represent relationship between dependent variable has categories and scale of category is ordinal with independent variable influenced the geographical location of the observation site. Parameters estimation of GWOLR model use maximum likelihood provide system of nonlinear equations and hard to be found the result in analytic resolution. By finishing it, it means determine the maximum completion, this thing associated with optimizing problem. The completion nonlinear system of equations optimize use numerical approximation, which one is Newton Raphson method. The purpose of this research is to make iteration algorithm Newton Raphson and program using R software to estimate GWOLR model. Based on the research obtained that program in R can be used to estimate the parameters of GWOLR model by forming a syntax program with command "while".

Dual ant colony operational modal analysis parameter estimation method

NASA Astrophysics Data System (ADS)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

Technology Estimating 2: A Process to Determine the Cost and Schedule of Space Technology Research and Development

NASA Technical Reports Server (NTRS)

Cole, Stuart K.; Wallace, Jon; Schaffer, Mark; May, M. Scott; Greenberg, Marc W.

2014-01-01

As a leader in space technology research and development, NASA is continuing in the development of the Technology Estimating process, initiated in 2012, for estimating the cost and schedule of low maturity technology research and development, where the Technology Readiness Level is less than TRL 6. NASA' s Technology Roadmap areas consist of 14 technology areas. The focus of this continuing Technology Estimating effort included four Technology Areas (TA): TA3 Space Power and Energy Storage, TA4 Robotics, TA8 Instruments, and TA12 Materials, to confine the research to the most abundant data pool. This research report continues the development of technology estimating efforts completed during 2013-2014, and addresses the refinement of parameters selected and recommended for use in the estimating process, where the parameters developed are applicable to Cost Estimating Relationships (CERs) used in the parametric cost estimating analysis. This research addresses the architecture for administration of the Technology Cost and Scheduling Estimating tool, the parameters suggested for computer software adjunct to any technology area, and the identification of gaps in the Technology Estimating process.

Airborne Doppler Wind Lidar Post Data Processing Software DAPS-LV

NASA Technical Reports Server (NTRS)

Kavaya, Michael J. (Inventor); Beyon, Jeffrey Y. (Inventor); Koch, Grady J. (Inventor)

2015-01-01

Systems, methods, and devices of the present invention enable post processing of airborne Doppler wind LIDAR data. In an embodiment, airborne Doppler wind LIDAR data software written in LabVIEW may be provided and may run two versions of different airborne wind profiling algorithms. A first algorithm may be the Airborne Wind Profiling Algorithm for Doppler Wind LIDAR ("APOLO") using airborne wind LIDAR data from two orthogonal directions to estimate wind parameters, and a second algorithm may be a five direction based method using pseudo inverse functions to estimate wind parameters. The various embodiments may enable wind profiles to be compared using different algorithms, may enable wind profile data for long haul color displays to be generated, may display long haul color displays, and/or may enable archiving of data at user-selectable altitudes over a long observation period for data distribution and population.

Seasonal station variations in the Vienna VLBI terrestrial reference frame VieTRF16a

NASA Astrophysics Data System (ADS)

Krásná, Hana; Böhm, Johannes; Madzak, Matthias

2017-04-01

The special analysis center of the International Very Long Baseline Interferometry (VLBI) Service for Geodesy and Astrometry (IVS) at TU Wien (VIE) routinely analyses the VLBI measurements and estimates its own Terrestrial Reference Frame (TRF) solutions. We present our latest solution VieTRF16a (1979.0 - 2016.5) computed with the software VieVS version 3.0. Several recent updates of the software have been applied, e.g., the estimation of annual and semi-annual station variations as global parameters. The VieTRF16a is determined in the form of the conventional model (station position and its linear velocity) simultaneously with the celestial reference frame and Earth orientation parameters. In this work, we concentrate on the seasonal station variations in the residual time series and compare our TRF with the three combined TRF solutions ITRF2014, DTRF2014 and JTRF2014.

Identification of Spey engine dynamics in the augmentor wing jet STOL research aircraft from flight data

NASA Technical Reports Server (NTRS)

Dehoff, R. L.; Reed, W. B.; Trankle, T. L.

1977-01-01

The development and validation of a spey engine model is described. An analysis of the dynamical interactions involved in the propulsion unit is presented. The model was reduced to contain only significant effects, and was used, in conjunction with flight data obtained from an augmentor wing jet STOL research aircraft, to develop initial estimates of parameters in the system. The theoretical background employed in estimating the parameters is outlined. The software package developed for processing the flight data is described. Results are summarized.

libSRES: a C library for stochastic ranking evolution strategy for parameter estimation.

PubMed

Ji, Xinglai; Xu, Ying

2006-01-01

Estimation of kinetic parameters in a biochemical pathway or network represents a common problem in systems studies of biological processes. We have implemented a C library, named libSRES, to facilitate a fast implementation of computer software for study of non-linear biochemical pathways. This library implements a (mu, lambda)-ES evolutionary optimization algorithm that uses stochastic ranking as the constraint handling technique. Considering the amount of computing time it might require to solve a parameter-estimation problem, an MPI version of libSRES is provided for parallel implementation, as well as a simple user interface. libSRES is freely available and could be used directly in any C program as a library function. We have extensively tested the performance of libSRES on various pathway parameter-estimation problems and found its performance to be satisfactory. The source code (in C) is free for academic users at http://csbl.bmb.uga.edu/~jix/science/libSRES/

Department of Defense Software Factbook

DTIC Science & Technology

2017-07-07

parameters, these rules of thumb may not provide a lot of value to project managers estimating their software efforts. To get the information useful to them...organization determine the total cost of a particular project , but it is a useful metric to technical managers when they are required to submit an annual...outcome. It is most likely a combination of engineering, management , and funding factors. Although a project may resist planning a schedule slip, this

The Model Human Processor and the Older Adult: Parameter Estimation and Validation Within a Mobile Phone Task

PubMed Central

Jastrzembski, Tiffany S.; Charness, Neil

2009-01-01

The authors estimate weighted mean values for nine information processing parameters for older adults using the Card, Moran, and Newell (1983) Model Human Processor model. The authors validate a subset of these parameters by modeling two mobile phone tasks using two different phones and comparing model predictions to a sample of younger (N = 20; Mage = 20) and older (N = 20; Mage = 69) adults. Older adult models fit keystroke-level performance at the aggregate grain of analysis extremely well (R = 0.99) and produced equivalent fits to previously validated younger adult models. Critical path analyses highlighted points of poor design as a function of cognitive workload, hardware/software design, and user characteristics. The findings demonstrate that estimated older adult information processing parameters are valid for modeling purposes, can help designers understand age-related performance using existing interfaces, and may support the development of age-sensitive technologies. PMID:18194048

The Model Human Processor and the older adult: parameter estimation and validation within a mobile phone task.

PubMed

Jastrzembski, Tiffany S; Charness, Neil

2007-12-01

The authors estimate weighted mean values for nine information processing parameters for older adults using the Card, Moran, and Newell (1983) Model Human Processor model. The authors validate a subset of these parameters by modeling two mobile phone tasks using two different phones and comparing model predictions to a sample of younger (N = 20; M-sub(age) = 20) and older (N = 20; M-sub(age) = 69) adults. Older adult models fit keystroke-level performance at the aggregate grain of analysis extremely well (R = 0.99) and produced equivalent fits to previously validated younger adult models. Critical path analyses highlighted points of poor design as a function of cognitive workload, hardware/software design, and user characteristics. The findings demonstrate that estimated older adult information processing parameters are valid for modeling purposes, can help designers understand age-related performance using existing interfaces, and may support the development of age-sensitive technologies.

A Modular GIS-Based Software Architecture for Model Parameter Estimation using the Method of Anchored Distributions (MAD)

NASA Astrophysics Data System (ADS)

Ames, D. P.; Osorio-Murillo, C.; Over, M. W.; Rubin, Y.

2012-12-01

The Method of Anchored Distributions (MAD) is an inverse modeling technique that is well-suited for estimation of spatially varying parameter fields using limited observations and Bayesian methods. This presentation will discuss the design, development, and testing of a free software implementation of the MAD technique using the open source DotSpatial geographic information system (GIS) framework, R statistical software, and the MODFLOW groundwater model. This new tool, dubbed MAD-GIS, is built using a modular architecture that supports the integration of external analytical tools and models for key computational processes including a forward model (e.g. MODFLOW, HYDRUS) and geostatistical analysis (e.g. R, GSLIB). The GIS-based graphical user interface provides a relatively simple way for new users of the technique to prepare the spatial domain, to identify observation and anchor points, to perform the MAD analysis using a selected forward model, and to view results. MAD-GIS uses the Managed Extensibility Framework (MEF) provided by the Microsoft .NET programming platform to support integration of different modeling and analytical tools at run-time through a custom "driver." Each driver establishes a connection with external programs through a programming interface, which provides the elements for communicating with core MAD software. This presentation gives an example of adapting the MODFLOW to serve as the external forward model in MAD-GIS for inferring the distribution functions of key MODFLOW parameters. Additional drivers for other models are being developed and it is expected that the open source nature of the project will engender the development of additional model drivers by 3rd party scientists.

Geospatial approach towards enumerative analysis of suspended sediment concentration for Ganges-Brahmaputra Bay

NASA Astrophysics Data System (ADS)

Pandey, Palak; Kunte, Pravin D.

2016-10-01

This study presents an easy, modular, user-friendly, and flexible software package for processing of Landsat 7 ETM and Landsat 8 OLI-TIRS data for estimating suspended particulate matter concentrations in the coastal waters. This package includes 1) algorithm developed using freely downloadable SCILAB package, 2) ERDAS Models for iterative processing of Landsat images and 3) ArcMAP tool for plotting and map making. Utilizing SCILAB package, a module is written for geometric corrections, radiometric corrections and obtaining normalized water-leaving reflectance by incorporating Landsat 8 OLI-TIRS and Landsat 7 ETM+ data. Using ERDAS models, a sequence of modules are developed for iterative processing of Landsat images and estimating suspended particulate matter concentrations. Processed images are used for preparing suspended sediment concentration maps. The applicability of this software package is demonstrated by estimating and plotting seasonal suspended sediment concentration maps off the Bengal delta. The software is flexible enough to accommodate other remotely sensed data like Ocean Color monitor (OCM) data, Indian Remote Sensing data (IRS), MODIS data etc. by replacing a few parameters in the algorithm, for estimating suspended sediment concentration in coastal waters.

Combination of Vlbi, GPS and Slr Observations At The Observation Level For The Realization of Terrestrial and Celestial Reference Frames

NASA Astrophysics Data System (ADS)

Andersen, P. H.

Forsvarets forskningsinstitutt (FFI, the Norwegian Defence Research Establishment) has during the last 17 years developed a software system called GEOSAT, for the analysis of any type of high precision space geodetic observations. A unique feature of GEOSAT is the possibility of combining any combination of different space geode- tic data at the observation level with one consistent model and one consistent strategy. This is a much better strategy than the strategy in use today where different types of observations are processed separately using analysis software developed specifically for each technique. The results from each technique are finally combined a posteriori. In practice the models implemented in the software packages differ at the 1-cm level which is almost one order of magnitude larger than the internal precision of the most precise techniques. Another advantage of the new proposed combination method is that for example VLBI and GPS can use the same tropospheric model with common parameterization. The same is the case for the Earth orientation parameters, the geo- center coordinates and other geodetic or geophysical parameters where VLBI, GPS and SLR can have a common estimate for each of the parameters. The analysis with GEOSAT is automated for the combination of VLBI, SLR and GPS observations. The data are analyzed in batches of one day where the result from each daily arc is a SRIF array (Square Root Information Filter). A large number of SRIF arrays can be combined into a multi-year solution using the CSRIFS program (Com- bination Square Root Information Filter and Smoother). Four parameter levels are available and any parameter can, at each level, either be represented as a constant or a stochastic parameter (white noise, colored noise, or random walk). The batch length (i.e. the time interval between the addition of noise to the SRIF array) can be made time- and parameter dependent. GEOSAT and CSRIFS have been applied in the analysis of selected VLBI and SLR data (LAGEOS I &II) from the period January 1993 to July 2001. A selected number of arcs also include GPS data. Earth orientation parameters, geocenter motion, sta- tion coordinates and velocities were estimated simultaneously with the coordinates of the radio sources and satellite orbital parameters. Recent software improvements and 1 results of analyses will be presented at the meeting. 2

A hybrid artificial neural network as a software sensor for optimal control of a wastewater treatment process.

PubMed

Choi, D J; Park, H

2001-11-01

For control and automation of biological treatment processes, lack of reliable on-line sensors to measure water quality parameters is one of the most important problems to overcome. Many parameters cannot be measured directly with on-line sensors. The accuracy of existing hardware sensors is also not sufficient and maintenance problems such as electrode fouling often cause trouble. This paper deals with the development of software sensor techniques that estimate the target water quality parameter from other parameters using the correlation between water quality parameters. We focus our attention on the preprocessing of noisy data and the selection of the best model feasible to the situation. Problems of existing approaches are also discussed. We propose a hybrid neural network as a software sensor inferring wastewater quality parameter. Multivariate regression, artificial neural networks (ANN), and a hybrid technique that combines principal component analysis as a preprocessing stage are applied to data from industrial wastewater processes. The hybrid ANN technique shows an enhancement of prediction capability and reduces the overfitting problem of neural networks. The result shows that the hybrid ANN technique can be used to extract information from noisy data and to describe the nonlinearity of complex wastewater treatment processes.

High Performance Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System at NASA/GSFC

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Kumar, S. V.; Santanello, J. A.; Tian, Y.; Rodell, M.; Mocko, D.; Reichle, R.

2008-12-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters-Lidard et al., 2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. The LIS software was the co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts - North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell et al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of these systems, now use specific configurations of the LIS software in their current implementations. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through 'plugins'. In addition to these capabilities, LIS has also been demonstrated for parameter estimation (Peters-Lidard et al., 2008; Santanello et al., 2007) and data assimilation (Kumar et al., 2008). Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, land data assimilation and parameter estimation will be presented.

SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology.

PubMed

Adams, Richard; Clark, Allan; Yamaguchi, Azusa; Hanlon, Neil; Tsorman, Nikos; Ali, Shakir; Lebedeva, Galina; Goltsov, Alexey; Sorokin, Anatoly; Akman, Ozgur E; Troein, Carl; Millar, Andrew J; Goryanin, Igor; Gilmore, Stephen

2013-03-01

Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting; SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers; and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSI's use of standard data formats. All SBSI binaries and source-code are freely available from http://sourceforge.net/projects/sbsi under an Apache 2 open-source license. The server-side SBSINumerics runs on any Unix-based operating system; both SBSIVisual and SBSIDispatcher are written in Java and are platform independent, allowing use on Windows, Linux and Mac OS X. The SBSI project website at http://www.sbsi.ed.ac.uk provides documentation and tutorials.

An open-source, FireWire camera-based, Labview-controlled image acquisition system for automated, dynamic pupillometry and blink detection.

PubMed

de Souza, John Kennedy Schettino; Pinto, Marcos Antonio da Silva; Vieira, Pedro Gabrielle; Baron, Jerome; Tierra-Criollo, Carlos Julio

2013-12-01

The dynamic, accurate measurement of pupil size is extremely valuable for studying a large number of neuronal functions and dysfunctions. Despite tremendous and well-documented progress in image processing techniques for estimating pupil parameters, comparatively little work has been reported on practical hardware issues involved in designing image acquisition systems for pupil analysis. Here, we describe and validate the basic features of such a system which is based on a relatively compact, off-the-shelf, low-cost FireWire digital camera. We successfully implemented two configurable modes of video record: a continuous mode and an event-triggered mode. The interoperability of the whole system is guaranteed by a set of modular software components hosted on a personal computer and written in Labview. An offline analysis suite of image processing algorithms for automatically estimating pupillary and eyelid parameters were assessed using data obtained in human subjects. Our benchmark results show that such measurements can be done in a temporally precise way at a sampling frequency of up to 120 Hz and with an estimated maximum spatial resolution of 0.03 mm. Our software is made available free of charge to the scientific community, allowing end users to either use the software as is or modify it to suit their own needs. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Accommodating Chromosome Inversions in Linkage Analysis

PubMed Central

Chen, Gary K.; Slaten, Erin; Ophoff, Roel A.; Lange, Kenneth

2006-01-01

This work develops a population-genetics model for polymorphic chromosome inversions. The model precisely describes how an inversion changes the nature of and approach to linkage equilibrium. The work also describes algorithms and software for allele-frequency estimation and linkage analysis in the presence of an inversion. The linkage algorithms implemented in the software package Mendel estimate recombination parameters and calculate the posterior probability that each pedigree member carries the inversion. Application of Mendel to eight Centre d'Étude du Polymorphisme Humain pedigrees in a region containing a common inversion on 8p23 illustrates its potential for providing more-precise estimates of the location of an unmapped marker or trait gene. Our expanded cytogenetic analysis of these families further identifies inversion carriers and increases the evidence of linkage. PMID:16826515

Obtaining continuous BrAC/BAC estimates in the field: A hybrid system integrating transdermal alcohol biosensor, Intellidrink smartphone app, and BrAC Estimator software tools.

PubMed

Luczak, Susan E; Hawkins, Ashley L; Dai, Zheng; Wichmann, Raphael; Wang, Chunming; Rosen, I Gary

2018-08-01

Biosensors have been developed to measure transdermal alcohol concentration (TAC), but converting TAC into interpretable indices of blood/breath alcohol concentration (BAC/BrAC) is difficult because of variations that occur in TAC across individuals, drinking episodes, and devices. We have developed mathematical models and the BrAC Estimator software for calibrating and inverting TAC into quantifiable BrAC estimates (eBrAC). The calibration protocol to determine the individualized parameters for a specific individual wearing a specific device requires a drinking session in which BrAC and TAC measurements are obtained simultaneously. This calibration protocol was originally conducted in the laboratory with breath analyzers used to produce the BrAC data. Here we develop and test an alternative calibration protocol using drinking diary data collected in the field with the smartphone app Intellidrink to produce the BrAC calibration data. We compared BrAC Estimator software results for 11 drinking episodes collected by an expert user when using Intellidrink versus breath analyzer measurements as BrAC calibration data. Inversion phase results indicated the Intellidrink calibration protocol produced similar eBrAC curves and captured peak eBrAC to within 0.0003%, time of peak eBrAC to within 18min, and area under the eBrAC curve to within 0.025% alcohol-hours as the breath analyzer calibration protocol. This study provides evidence that drinking diary data can be used in place of breath analyzer data in the BrAC Estimator software calibration procedure, which can reduce participant and researcher burden and expand the potential software user pool beyond researchers studying participants who can drink in the laboratory. Copyright © 2017. Published by Elsevier Ltd.

Flight data processing with the F-8 adaptive algorithm

NASA Technical Reports Server (NTRS)

Hartmann, G.; Stein, G.; Petersen, K.

1977-01-01

An explicit adaptive control algorithm based on maximum likelihood estimation of parameters has been designed for NASA's DFBW F-8 aircraft. To avoid iterative calculations, the algorithm uses parallel channels of Kalman filters operating at fixed locations in parameter space. This algorithm has been implemented in NASA/DFRC's Remotely Augmented Vehicle (RAV) facility. Real-time sensor outputs (rate gyro, accelerometer and surface position) are telemetered to a ground computer which sends new gain values to an on-board system. Ground test data and flight records were used to establish design values of noise statistics and to verify the ground-based adaptive software. The software and its performance evaluation based on flight data are described

Numerical Problem Solving Using Mathcad in Undergraduate Reaction Engineering

ERIC Educational Resources Information Center

Parulekar, Satish J.

2006-01-01

Experience in using a user-friendly software, Mathcad, in the undergraduate chemical reaction engineering course is discussed. Example problems considered for illustration deal with simultaneous solution of linear algebraic equations (kinetic parameter estimation), nonlinear algebraic equations (equilibrium calculations for multiple reactions and…

A Nonlinear, Multiinput, Multioutput Process Control Laboratory Experiment

ERIC Educational Resources Information Center

Young, Brent R.; van der Lee, James H.; Svrcek, William Y.

2006-01-01

Experience in using a user-friendly software, Mathcad, in the undergraduate chemical reaction engineering course is discussed. Example problems considered for illustration deal with simultaneous solution of linear algebraic equations (kinetic parameter estimation), nonlinear algebraic equations (equilibrium calculations for multiple reactions and…

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

Dana L. Kelly

Typical engineering systems in applications with high failure consequences such as nuclear reactor plants often employ redundancy and diversity of equipment in an effort to lower the probability of failure and therefore risk. However, it has long been recognized that dependencies exist in these redundant and diverse systems. Some dependencies, such as common sources of electrical power, are typically captured in the logic structure of the risk model. Others, usually referred to as intercomponent dependencies, are treated implicitly by introducing one or more statistical parameters into the model. Such common-cause failure models have limitations in a simulation environment. In addition,more » substantial subjectivity is associated with parameter estimation for these models. This paper describes an approach in which system performance is simulated by drawing samples from the joint distributions of dependent variables. The approach relies on the notion of a copula distribution, a notion which has been employed by the actuarial community for ten years or more, but which has seen only limited application in technological risk assessment. The paper also illustrates how equipment failure data can be used in a Bayesian framework to estimate the parameter values in the copula model. This approach avoids much of the subjectivity required to estimate parameters in traditional common-cause failure models. Simulation examples are presented for failures in time. The open-source software package R is used to perform the simulations. The open-source software package WinBUGS is used to perform the Bayesian inference via Markov chain Monte Carlo sampling.« less

PyPWA: A partial-wave/amplitude analysis software framework

NASA Astrophysics Data System (ADS)

Salgado, Carlos

2016-05-01

The PyPWA project aims to develop a software framework for Partial Wave and Amplitude Analysis of data; providing the user with software tools to identify resonances from multi-particle final states in photoproduction. Most of the code is written in Python. The software is divided into two main branches: one general-shell where amplitude's parameters (or any parametric model) are to be estimated from the data. This branch also includes software to produce simulated data-sets using the fitted amplitudes. A second branch contains a specific realization of the isobar model (with room to include Deck-type and other isobar model extensions) to perform PWA with an interface into the computer resources at Jefferson Lab. We are currently implementing parallelism and vectorization using the Intel's Xeon Phi family of coprocessors.

DAISY: a new software tool to test global identifiability of biological and physiological systems.

PubMed

Bellu, Giuseppina; Saccomani, Maria Pia; Audoly, Stefania; D'Angiò, Leontina

2007-10-01

A priori global identifiability is a structural property of biological and physiological models. It is considered a prerequisite for well-posed estimation, since it concerns the possibility of recovering uniquely the unknown model parameters from measured input-output data, under ideal conditions (noise-free observations and error-free model structure). Of course, determining if the parameters can be uniquely recovered from observed data is essential before investing resources, time and effort in performing actual biomedical experiments. Many interesting biological models are nonlinear but identifiability analysis for nonlinear system turns out to be a difficult mathematical problem. Different methods have been proposed in the literature to test identifiability of nonlinear models but, to the best of our knowledge, so far no software tools have been proposed for automatically checking identifiability of nonlinear models. In this paper, we describe a software tool implementing a differential algebra algorithm to perform parameter identifiability analysis for (linear and) nonlinear dynamic models described by polynomial or rational equations. Our goal is to provide the biological investigator a completely automatized software, requiring minimum prior knowledge of mathematical modelling and no in-depth understanding of the mathematical tools. The DAISY (Differential Algebra for Identifiability of SYstems) software will potentially be useful in biological modelling studies, especially in physiology and clinical medicine, where research experiments are particularly expensive and/or difficult to perform. Practical examples of use of the software tool DAISY are presented. DAISY is available at the web site http://www.dei.unipd.it/~pia/.

VLBI-derived troposphere parameters during CONT08

NASA Astrophysics Data System (ADS)

Heinkelmann, R.; Böhm, J.; Bolotin, S.; Engelhardt, G.; Haas, R.; Lanotte, R.; MacMillan, D. S.; Negusini, M.; Skurikhina, E.; Titov, O.; Schuh, H.

2011-07-01

Time-series of zenith wet and total troposphere delays as well as north and east gradients are compared, and zenith total delays ( ZTD) are combined on the level of parameter estimates. Input data sets are provided by ten Analysis Centers (ACs) of the International VLBI Service for Geodesy and Astrometry (IVS) for the CONT08 campaign (12-26 August 2008). The inconsistent usage of meteorological data and models, such as mapping functions, causes systematics among the ACs, and differing parameterizations and constraints add noise to the troposphere parameter estimates. The empirical standard deviation of ZTD among the ACs with regard to an unweighted mean is 4.6 mm. The ratio of the analysis noise to the observation noise assessed by the operator/software impact (OSI) model is about 2.5. These and other effects have to be accounted for to improve the intra-technique combination of VLBI-derived troposphere parameters. While the largest systematics caused by inconsistent usage of meteorological data can be avoided and the application of different mapping functions can be considered by applying empirical corrections, the noise has to be modeled in the stochastic model of intra-technique combination. The application of different stochastic models shows no significant effects on the combined parameters but results in different mean formal errors: the mean formal errors of the combined ZTD are 2.3 mm (unweighted), 4.4 mm (diagonal), 8.6 mm [variance component (VC) estimation], and 8.6 mm (operator/software impact, OSI). On the one hand, the OSI model, i.e. the inclusion of off-diagonal elements in the cofactor-matrix, considers the reapplication of observations yielding a factor of about two for mean formal errors as compared to the diagonal approach. On the other hand, the combination based on VC estimation shows large differences among the VCs and exhibits a comparable scaling of formal errors. Thus, for the combination of troposphere parameters a combination of the two extensions of the stochastic model is recommended.

Estimation of species richness and parameters reflecting community dynamics using data from ecological monitoring programs

USGS Publications Warehouse

Nichols, J.D.; Sauer, J.R.; Hines, J.E.; Boulinier, T.; Pollock, K.H.; Therres, Glenn D.

2001-01-01

Although many ecological monitoring programs are now in place, the use of resulting data to draw inferences about changes in biodiversity is problematic. The difficulty arises because of the inability to count all animals present in any sampled area. This inability results not only in underestimation of species richness but also in potentially misleading comparisons of species richness over time and space. We recommend the use of probabilistic estimators for estimating species richness and related parameters (e.g., rate of change in species richness, local extinction probability, local turnover, local colonization) when animal detection probabilities are <1. We illustrate these methods using data from the North American Breeding Bird Survey obtained along survey routes in Maryland. We also introduce software to implement these estimation methods.

Observation model and parameter partials for the JPL VLBI parameter estimation software MODEST, 19 94

NASA Technical Reports Server (NTRS)

Sovers, O. J.; Jacobs, C. S.

1994-01-01

This report is a revision of the document Observation Model and Parameter Partials for the JPL VLBI Parameter Estimation Software 'MODEST'---1991, dated August 1, 1991. It supersedes that document and its four previous versions (1983, 1985, 1986, and 1987). A number of aspects of the very long baseline interferometry (VLBI) model were improved from 1991 to 1994. Treatment of tidal effects is extended to model the effects of ocean tides on universal time and polar motion (UTPM), including a default model for nearly diurnal and semidiurnal ocean tidal UTPM variations, and partial derivatives for all (solid and ocean) tidal UTPM amplitudes. The time-honored 'K(sub 1) correction' for solid earth tides has been extended to include analogous frequency-dependent response of five tidal components. Partials of ocean loading amplitudes are now supplied. The Zhu-Mathews-Oceans-Anisotropy (ZMOA) 1990-2 and Kinoshita-Souchay models of nutation are now two of the modeling choices to replace the increasingly inadequate 1980 International Astronomical Union (IAU) nutation series. A rudimentary model of antenna thermal expansion is provided. Two more troposphere mapping functions have been added to the repertoire. Finally, corrections among VLBI observations via the model of Treuhaft and lanyi improve modeling of the dynamic troposphere. A number of minor misprints in Rev. 4 have been corrected.

Inverse Flush Air Data System (FADS) for Real Time Simulations

NASA Astrophysics Data System (ADS)

Madhavanpillai, Jayakumar; Dhoaya, Jayanta; Balakrishnan, Vidya Saraswathi; Narayanan, Remesh; Chacko, Finitha Kallely; Narayanan, Shyam Mohan

2017-12-01

Flush Air Data Sensing System (FADS) forms a mission critical sub system in future reentry vehicles. FADS makes use of surface pressure measurements from the nose cap of the vehicle for deriving the air data parameters of the vehicle such as angle of attack, angle of sideslip, Mach number, etc. These parameters find use in the flight control and guidance systems, and also assist in the overall mission management. The FADS under consideration in this paper makes use of nine pressure ports located in the nose cap of a technology demonstrator vehicle. In flight, the air data parameters are obtained from the FADS estimation algorithm using the pressure data at the nine pressure ports. But, these pressure data will not be available, for testing the FADS package during ground simulation. So, an inverse software to FADS which estimates the pressure data at the pressure ports for a given flight condition is developed. These pressure data at the nine ports will go as input to the FADS package during ground simulation. The software is run to generate the pressure data for the descent phase trajectory of the technology demonstrator. This data is used again to generate the air data parameters from FADS algorithm. The computed results from FADS algorithm match well with the trajectory data.

GPS-based system for satellite tracking and geodesy

NASA Technical Reports Server (NTRS)

Bertiger, Willy I.; Thornton, Catherine L.

1989-01-01

High-performance receivers and data processing systems developed for GPS are reviewed. The GPS Inferred Positioning System (GIPSY) and the Orbiter Analysis and Simulation Software (OASIS) are described. The OASIS software is used to assess GPS system performance using GIPSY for data processing. Consideration is given to parameter estimation for multiday arcs, orbit repeatability, orbit prediction, daily baseline repeatability, agreement with VLBI, and ambiguity resolution. Also, the dual-frequency Rogue receiver, which can track up to eight GPS satellites simultaneously, is discussed.

Wavelet extractor: A Bayesian well-tie and wavelet extraction program

NASA Astrophysics Data System (ADS)

Gunning, James; Glinsky, Michael E.

2006-06-01

We introduce a new open-source toolkit for the well-tie or wavelet extraction problem of estimating seismic wavelets from seismic data, time-to-depth information, and well-log suites. The wavelet extraction model is formulated as a Bayesian inverse problem, and the software will simultaneously estimate wavelet coefficients, other parameters associated with uncertainty in the time-to-depth mapping, positioning errors in the seismic imaging, and useful amplitude-variation-with-offset (AVO) related parameters in multi-stack extractions. It is capable of multi-well, multi-stack extractions, and uses continuous seismic data-cube interpolation to cope with the problem of arbitrary well paths. Velocity constraints in the form of checkshot data, interpreted markers, and sonic logs are integrated in a natural way. The Bayesian formulation allows computation of full posterior uncertainties of the model parameters, and the important problem of the uncertain wavelet span is addressed uses a multi-model posterior developed from Bayesian model selection theory. The wavelet extraction tool is distributed as part of the Delivery seismic inversion toolkit. A simple log and seismic viewing tool is included in the distribution. The code is written in Java, and thus platform independent, but the Seismic Unix (SU) data model makes the inversion particularly suited to Unix/Linux environments. It is a natural companion piece of software to Delivery, having the capacity to produce maximum likelihood wavelet and noise estimates, but will also be of significant utility to practitioners wanting to produce wavelet estimates for other inversion codes or purposes. The generation of full parameter uncertainties is a crucial function for workers wishing to investigate questions of wavelet stability before proceeding to more advanced inversion studies.

SiGN-SSM: open source parallel software for estimating gene networks with state space models.

PubMed

Tamada, Yoshinori; Yamaguchi, Rui; Imoto, Seiya; Hirose, Osamu; Yoshida, Ryo; Nagasaki, Masao; Miyano, Satoru

2011-04-15

SiGN-SSM is an open-source gene network estimation software able to run in parallel on PCs and massively parallel supercomputers. The software estimates a state space model (SSM), that is a statistical dynamic model suitable for analyzing short time and/or replicated time series gene expression profiles. SiGN-SSM implements a novel parameter constraint effective to stabilize the estimated models. Also, by using a supercomputer, it is able to determine the gene network structure by a statistical permutation test in a practical time. SiGN-SSM is applicable not only to analyzing temporal regulatory dependencies between genes, but also to extracting the differentially regulated genes from time series expression profiles. SiGN-SSM is distributed under GNU Affero General Public Licence (GNU AGPL) version 3 and can be downloaded at http://sign.hgc.jp/signssm/. The pre-compiled binaries for some architectures are available in addition to the source code. The pre-installed binaries are also available on the Human Genome Center supercomputer system. The online manual and the supplementary information of SiGN-SSM is available on our web site. tamada@ims.u-tokyo.ac.jp.

HEART: an automated beat-to-beat cardiovascular analysis package using Matlab.

PubMed

Schroeder, M J Mark J; Perreault, Bill; Ewert, D L Daniel L; Koenig, S C Steven C

2004-07-01

A computer program is described for beat-to-beat analysis of cardiovascular parameters from high-fidelity pressure and flow waveforms. The Hemodynamic Estimation and Analysis Research Tool (HEART) is a post-processing analysis software package developed in Matlab that enables scientists and clinicians to document, load, view, calibrate, and analyze experimental data that have been digitally saved in ascii or binary format. Analysis routines include traditional hemodynamic parameter estimates as well as more sophisticated analyses such as lumped arterial model parameter estimation and vascular impedance frequency spectra. Cardiovascular parameter values of all analyzed beats can be viewed and statistically analyzed. An attractive feature of the HEART program is the ability to analyze data with visual quality assurance throughout the process, thus establishing a framework toward which Good Laboratory Practice (GLP) compliance can be obtained. Additionally, the development of HEART on the Matlab platform provides users with the flexibility to adapt or create study specific analysis files according to their specific needs. Copyright 2003 Elsevier Ltd.

Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models

USGS Publications Warehouse

Welter, David E.; Doherty, John E.; Hunt, Randall J.; Muffels, Christopher T.; Tonkin, Matthew J.; Schreuder, Willem A.

2012-01-01

An object-oriented parameter estimation code was developed to incorporate benefits of object-oriented programming techniques for solving large parameter estimation modeling problems. The code is written in C++ and is a formulation and expansion of the algorithms included in PEST, a widely used parameter estimation code written in Fortran. The new code is called PEST++ and is designed to lower the barriers of entry for users and developers while providing efficient algorithms that can accommodate large, highly parameterized problems. This effort has focused on (1) implementing the most popular features of PEST in a fashion that is easy for novice or experienced modelers to use and (2) creating a software design that is easy to extend; that is, this effort provides a documented object-oriented framework designed from the ground up to be modular and extensible. In addition, all PEST++ source code and its associated libraries, as well as the general run manager source code, have been integrated in the Microsoft Visual Studio® 2010 integrated development environment. The PEST++ code is designed to provide a foundation for an open-source development environment capable of producing robust and efficient parameter estimation tools for the environmental modeling community into the future.

Performance comparison of first-order conditional estimation with interaction and Bayesian estimation methods for estimating the population parameters and its distribution from data sets with a low number of subjects.

PubMed

Pradhan, Sudeep; Song, Byungjeong; Lee, Jaeyeon; Chae, Jung-Woo; Kim, Kyung Im; Back, Hyun-Moon; Han, Nayoung; Kwon, Kwang-Il; Yun, Hwi-Yeol

2017-12-01

Exploratory preclinical, as well as clinical trials, may involve a small number of patients, making it difficult to calculate and analyze the pharmacokinetic (PK) parameters, especially if the PK parameters show very high inter-individual variability (IIV). In this study, the performance of a classical first-order conditional estimation with interaction (FOCE-I) and expectation maximization (EM)-based Markov chain Monte Carlo Bayesian (BAYES) estimation methods were compared for estimating the population parameters and its distribution from data sets having a low number of subjects. In this study, 100 data sets were simulated with eight sampling points for each subject and with six different levels of IIV (5%, 10%, 20%, 30%, 50%, and 80%) in their PK parameter distribution. A stochastic simulation and estimation (SSE) study was performed to simultaneously simulate data sets and estimate the parameters using four different methods: FOCE-I only, BAYES(C) (FOCE-I and BAYES composite method), BAYES(F) (BAYES with all true initial parameters and fixed ω 2 ), and BAYES only. Relative root mean squared error (rRMSE) and relative estimation error (REE) were used to analyze the differences between true and estimated values. A case study was performed with a clinical data of theophylline available in NONMEM distribution media. NONMEM software assisted by Pirana, PsN, and Xpose was used to estimate population PK parameters, and R program was used to analyze and plot the results. The rRMSE and REE values of all parameter (fixed effect and random effect) estimates showed that all four methods performed equally at the lower IIV levels, while the FOCE-I method performed better than other EM-based methods at higher IIV levels (greater than 30%). In general, estimates of random-effect parameters showed significant bias and imprecision, irrespective of the estimation method used and the level of IIV. Similar performance of the estimation methods was observed with theophylline dataset. The classical FOCE-I method appeared to estimate the PK parameters more reliably than the BAYES method when using a simple model and data containing only a few subjects. EM-based estimation methods can be considered for adapting to the specific needs of a modeling project at later steps of modeling.

Approaches in highly parameterized inversion: bgaPEST, a Bayesian geostatistical approach implementation with PEST: documentation and instructions

USGS Publications Warehouse

Fienen, Michael N.; D'Oria, Marco; Doherty, John E.; Hunt, Randall J.

2013-01-01

The application bgaPEST is a highly parameterized inversion software package implementing the Bayesian Geostatistical Approach in a framework compatible with the parameter estimation suite PEST. Highly parameterized inversion refers to cases in which parameters are distributed in space or time and are correlated with one another. The Bayesian aspect of bgaPEST is related to Bayesian probability theory in which prior information about parameters is formally revised on the basis of the calibration dataset used for the inversion. Conceptually, this approach formalizes the conditionality of estimated parameters on the specific data and model available. The geostatistical component of the method refers to the way in which prior information about the parameters is used. A geostatistical autocorrelation function is used to enforce structure on the parameters to avoid overfitting and unrealistic results. Bayesian Geostatistical Approach is designed to provide the smoothest solution that is consistent with the data. Optionally, users can specify a level of fit or estimate a balance between fit and model complexity informed by the data. Groundwater and surface-water applications are used as examples in this text, but the possible uses of bgaPEST extend to any distributed parameter applications.

Software for Estimating Costs of Testing Rocket Engines

NASA Technical Reports Server (NTRS)

Hines, Merlon M.

2004-01-01

A high-level parametric mathematical model for estimating the costs of testing rocket engines and components at Stennis Space Center has been implemented as a Microsoft Excel program that generates multiple spreadsheets. The model and the program are both denoted, simply, the Cost Estimating Model (CEM). The inputs to the CEM are the parameters that describe particular tests, including test types (component or engine test), numbers and duration of tests, thrust levels, and other parameters. The CEM estimates anticipated total project costs for a specific test. Estimates are broken down into testing categories based on a work-breakdown structure and a cost-element structure. A notable historical assumption incorporated into the CEM is that total labor times depend mainly on thrust levels. As a result of a recent modification of the CEM to increase the accuracy of predicted labor times, the dependence of labor time on thrust level is now embodied in third- and fourth-order polynomials.

Software for Estimating Costs of Testing Rocket Engines

NASA Technical Reports Server (NTRS)

Hines, Merion M.

2002-01-01

A high-level parametric mathematical model for estimating the costs of testing rocket engines and components at Stennis Space Center has been implemented as a Microsoft Excel program that generates multiple spreadsheets. The model and the program are both denoted, simply, the Cost Estimating Model (CEM). The inputs to the CEM are the parameters that describe particular tests, including test types (component or engine test), numbers and duration of tests, thrust levels, and other parameters. The CEM estimates anticipated total project costs for a specific test. Estimates are broken down into testing categories based on a work-breakdown structure and a cost-element structure. A notable historical assumption incorporated into the CEM is that total labor times depend mainly on thrust levels. As a result of a recent modification of the CEM to increase the accuracy of predicted labor times, the dependence of labor time on thrust level is now embodied in third- and fourth-order polynomials.

Software for Estimating Costs of Testing Rocket Engines

NASA Technical Reports Server (NTRS)

Hines, Merlon M.

2003-01-01

A high-level parametric mathematical model for estimating the costs of testing rocket engines and components at Stennis Space Center has been implemented as a Microsoft Excel program that generates multiple spreadsheets. The model and the program are both denoted, simply, the Cost Estimating Model (CEM). The inputs to the CEM are the parameters that describe particular tests, including test types (component or engine test), numbers and duration of tests, thrust levels, and other parameters. The CEM estimates anticipated total project costs for a specific test. Estimates are broken down into testing categories based on a work-breakdown structure and a cost-element structure. A notable historical assumption incorporated into the CEM is that total labor times depend mainly on thrust levels. As a result of a recent modification of the CEM to increase the accuracy of predicted labor times, the dependence of labor time on thrust level is now embodied in third- and fourth-order polynomials.

VLBI Analysis with the Multi-Technique Software GEOSAT

NASA Technical Reports Server (NTRS)

Kierulf, Halfdan Pascal; Andersen, Per-Helge; Boeckmann, Sarah; Kristiansen, Oddgeir

2010-01-01

GEOSAT is a multi-technique geodetic analysis software developed at Forsvarets Forsknings Institutt (Norwegian defense research establishment). The Norwegian Mapping Authority has now installed the software and has, together with Forsvarets Forsknings Institutt, adapted the software to deliver datum-free normal equation systems in SINEX format. The goal is to be accepted as an IVS Associate Analysis Center and to provide contributions to the IVS EOP combination on a routine basis. GEOSAT is based on an upper diagonal factorized Kalman filter which allows estimation of time variable parameters like the troposphere and clocks as stochastic parameters. The tropospheric delays in various directions are mapped to tropospheric zenith delay using ray-tracing. Meteorological data from ECMWF with a resolution of six hours is used to perform the ray-tracing which depends both on elevation and azimuth. Other models are following the IERS and IVS conventions. The Norwegian Mapping Authority has submitted test SINEX files produced with GEOSAT to IVS. The results have been compared with the existing IVS combined products. In this paper the outcome of these comparisons is presented.

Structural Equation Modeling: A Framework for Ocular and Other Medical Sciences Research

PubMed Central

Christ, Sharon L.; Lee, David J.; Lam, Byron L.; Diane, Zheng D.

2017-01-01

Structural equation modeling (SEM) is a modeling framework that encompasses many types of statistical models and can accommodate a variety of estimation and testing methods. SEM has been used primarily in social sciences but is increasingly used in epidemiology, public health, and the medical sciences. SEM provides many advantages for the analysis of survey and clinical data, including the ability to model latent constructs that may not be directly observable. Another major feature is simultaneous estimation of parameters in systems of equations that may include mediated relationships, correlated dependent variables, and in some instances feedback relationships. SEM allows for the specification of theoretically holistic models because multiple and varied relationships may be estimated together in the same model. SEM has recently expanded by adding generalized linear modeling capabilities that include the simultaneous estimation of parameters of different functional form for outcomes with different distributions in the same model. Therefore, mortality modeling and other relevant health outcomes may be evaluated. Random effects estimation using latent variables has been advanced in the SEM literature and software. In addition, SEM software has increased estimation options. Therefore, modern SEM is quite general and includes model types frequently used by health researchers, including generalized linear modeling, mixed effects linear modeling, and population average modeling. This article does not present any new information. It is meant as an introduction to SEM and its uses in ocular and other health research. PMID:24467557

Estimating parameters of hidden Markov models based on marked individuals: use of robust design data

USGS Publications Warehouse

Kendall, William L.; White, Gary C.; Hines, James E.; Langtimm, Catherine A.; Yoshizaki, Jun

2012-01-01

Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last twenty years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We also provide user-friendly software to implement these models. This general framework could also be used by practitioners to consider constrained models of particular interest, or model the relationship between within-primary period parameters (e.g., state structure) and between-primary period parameters (e.g., state transition probabilities).

DAISY: a new software tool to test global identifiability of biological and physiological systems

PubMed Central

Bellu, Giuseppina; Saccomani, Maria Pia; Audoly, Stefania; D’Angiò, Leontina

2009-01-01

A priori global identifiability is a structural property of biological and physiological models. It is considered a prerequisite for well-posed estimation, since it concerns the possibility of recovering uniquely the unknown model parameters from measured input-output data, under ideal conditions (noise-free observations and error-free model structure). Of course, determining if the parameters can be uniquely recovered from observed data is essential before investing resources, time and effort in performing actual biomedical experiments. Many interesting biological models are nonlinear but identifiability analysis for nonlinear system turns out to be a difficult mathematical problem. Different methods have been proposed in the literature to test identifiability of nonlinear models but, to the best of our knowledge, so far no software tools have been proposed for automatically checking identifiability of nonlinear models. In this paper, we describe a software tool implementing a differential algebra algorithm to perform parameter identifiability analysis for (linear and) nonlinear dynamic models described by polynomial or rational equations. Our goal is to provide the biological investigator a completely automatized software, requiring minimum prior knowledge of mathematical modelling and no in-depth understanding of the mathematical tools. The DAISY (Differential Algebra for Identifiability of SYstems) software will potentially be useful in biological modelling studies, especially in physiology and clinical medicine, where research experiments are particularly expensive and/or difficult to perform. Practical examples of use of the software tool DAISY are presented. DAISY is available at the web site http://www.dei.unipd.it/~pia/. PMID:17707944

A flexible system for the estimation of infiltration and hydraulic resistance parameters in surface irrigation

USDA-ARS?s Scientific Manuscript database

Critical to the use of modeling tools for the hydraulic analysis of surface irrigation systems is characterizing the infiltration and hydraulic resistance process. Since those processes are still not well understood, various formulations are currently used to represent them. A software component h...

DINA Model and Parameter Estimation: A Didactic

ERIC Educational Resources Information Center

de la Torre, Jimmy

2009-01-01

Cognitive and skills diagnosis models are psychometric models that have immense potential to provide rich information relevant for instruction and learning. However, wider applications of these models have been hampered by their novelty and the lack of commercially available software that can be used to analyze data from this psychometric…

Evidence of Absence software

USGS Publications Warehouse

Dalthorp, Daniel; Huso, Manuela M. P.; Dail, David; Kenyon, Jessica

2014-01-01

Evidence of Absence software (EoA) is a user-friendly application used for estimating bird and bat fatalities at wind farms and designing search protocols. The software is particularly useful in addressing whether the number of fatalities has exceeded a given threshold and what search parameters are needed to give assurance that thresholds were not exceeded. The software is applicable even when zero carcasses have been found in searches. Depending on the effectiveness of the searches, such an absence of evidence of mortality may or may not be strong evidence that few fatalities occurred. Under a search protocol in which carcasses are detected with nearly 100 percent certainty, finding zero carcasses would be convincing evidence that overall mortality rate was near zero. By contrast, with a less effective search protocol with low probability of detecting a carcass, finding zero carcasses does not rule out the possibility that large numbers of animals were killed but not detected in the searches. EoA uses information about the search process and scavenging rates to estimate detection probabilities to determine a maximum credible number of fatalities, even when zero or few carcasses are observed.

Predictive Model and Software for Inbreeding-Purging Analysis of Pedigreed Populations

PubMed Central

García-Dorado, Aurora; Wang, Jinliang; López-Cortegano, Eugenio

2016-01-01

The inbreeding depression of fitness traits can be a major threat to the survival of populations experiencing inbreeding. However, its accurate prediction requires taking into account the genetic purging induced by inbreeding, which can be achieved using a “purged inbreeding coefficient”. We have developed a method to compute purged inbreeding at the individual level in pedigreed populations with overlapping generations. Furthermore, we derive the inbreeding depression slope for individual logarithmic fitness, which is larger than that for the logarithm of the population fitness average. In addition, we provide a new software, PURGd, based on these theoretical results that allows analyzing pedigree data to detect purging, and to estimate the purging coefficient, which is the parameter necessary to predict the joint consequences of inbreeding and purging. The software also calculates the purged inbreeding coefficient for each individual, as well as standard and ancestral inbreeding. Analysis of simulation data show that this software produces reasonably accurate estimates for the inbreeding depression rate and for the purging coefficient that are useful for predictive purposes. PMID:27605515

On the Multilevel Nature of Meta-Analysis: A Tutorial, Comparison of Software Programs, and Discussion of Analytic Choices.

PubMed

Pastor, Dena A; Lazowski, Rory A

2018-01-01

The term "multilevel meta-analysis" is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term "multilevel meta-analysis" is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analytic choices, not between meta-analytic models, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed.

A pharmacometric case study regarding the sensitivity of structural model parameter estimation to error in patient reported dosing times.

PubMed

Knights, Jonathan; Rohatagi, Shashank

2015-12-01

Although there is a body of literature focused on minimizing the effect of dosing inaccuracies on pharmacokinetic (PK) parameter estimation, most of the work centers on missing doses. No attempt has been made to specifically characterize the effect of error in reported dosing times. Additionally, existing work has largely dealt with cases in which the compound of interest is dosed at an interval no less than its terminal half-life. This work provides a case study investigating how error in patient reported dosing times might affect the accuracy of structural model parameter estimation under sparse sampling conditions when the dosing interval is less than the terminal half-life of the compound, and the underlying kinetics are monoexponential. Additional effects due to noncompliance with dosing events are not explored and it is assumed that the structural model and reasonable initial estimates of the model parameters are known. Under the conditions of our simulations, with structural model CV % ranging from ~20 to 60 %, parameter estimation inaccuracy derived from error in reported dosing times was largely controlled around 10 % on average. Given that no observed dosing was included in the design and sparse sampling was utilized, we believe these error results represent a practical ceiling given the variability and parameter estimates for the one-compartment model. The findings suggest additional investigations may be of interest and are noteworthy given the inability of current PK software platforms to accommodate error in dosing times.

Full-envelope aerodynamic modeling of the Harrier aircraft

NASA Technical Reports Server (NTRS)

Mcnally, B. David

1986-01-01

A project to identify a full-envelope model of the YAV-8B Harrier using flight-test and parameter identification techniques is described. As part of the research in advanced control and display concepts for V/STOL aircraft, a full-envelope aerodynamic model of the Harrier is identified, using mathematical model structures and parameter identification methods. A global-polynomial model structure is also used as a basis for the identification of the YAV-8B aerodynamic model. State estimation methods are used to ensure flight data consistency prior to parameter identification.Equation-error methods are used to identify model parameters. A fixed-base simulator is used extensively to develop flight test procedures and to validate parameter identification software. Using simple flight maneuvers, a simulated data set was created covering the YAV-8B flight envelope from about 0.3 to 0.7 Mach and about -5 to 15 deg angle of attack. A singular value decomposition implementation of the equation-error approach produced good parameter estimates based on this simulated data set.

State and parameter estimation of the heat shock response system using Kalman and particle filters.

PubMed

Liu, Xin; Niranjan, Mahesan

2012-06-01

Traditional models of systems biology describe dynamic biological phenomena as solutions to ordinary differential equations, which, when parameters in them are set to correct values, faithfully mimic observations. Often parameter values are tweaked by hand until desired results are achieved, or computed from biochemical experiments carried out in vitro. Of interest in this article, is the use of probabilistic modelling tools with which parameters and unobserved variables, modelled as hidden states, can be estimated from limited noisy observations of parts of a dynamical system. Here we focus on sequential filtering methods and take a detailed look at the capabilities of three members of this family: (i) extended Kalman filter (EKF), (ii) unscented Kalman filter (UKF) and (iii) the particle filter, in estimating parameters and unobserved states of cellular response to sudden temperature elevation of the bacterium Escherichia coli. While previous literature has studied this system with the EKF, we show that parameter estimation is only possible with this method when the initial guesses are sufficiently close to the true values. The same turns out to be true for the UKF. In this thorough empirical exploration, we show that the non-parametric method of particle filtering is able to reliably estimate parameters and states, converging from initial distributions relatively far away from the underlying true values. Software implementation of the three filters on this problem can be freely downloaded from http://users.ecs.soton.ac.uk/mn/HeatShock

GBIS (Geodetic Bayesian Inversion Software): Rapid Inversion of InSAR and GNSS Data to Estimate Surface Deformation Source Parameters and Uncertainties

NASA Astrophysics Data System (ADS)

Bagnardi, M.; Hooper, A. J.

2017-12-01

Inversions of geodetic observational data, such as Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS) measurements, are often performed to obtain information about the source of surface displacements. Inverse problem theory has been applied to study magmatic processes, the earthquake cycle, and other phenomena that cause deformation of the Earth's interior and of its surface. Together with increasing improvements in data resolution, both spatial and temporal, new satellite missions (e.g., European Commission's Sentinel-1 satellites) are providing the unprecedented opportunity to access space-geodetic data within hours from their acquisition. To truly take advantage of these opportunities we must become able to interpret geodetic data in a rapid and robust manner. Here we present the open-source Geodetic Bayesian Inversion Software (GBIS; available for download at http://comet.nerc.ac.uk/gbis). GBIS is written in Matlab and offers a series of user-friendly and interactive pre- and post-processing tools. For example, an interactive function has been developed to estimate the characteristics of noise in InSAR data by calculating the experimental semi-variogram. The inversion software uses a Markov-chain Monte Carlo algorithm, incorporating the Metropolis-Hastings algorithm with adaptive step size, to efficiently sample the posterior probability distribution of the different source parameters. The probabilistic Bayesian approach allows the user to retrieve estimates of the optimal (best-fitting) deformation source parameters together with the associated uncertainties produced by errors in the data (and by scaling, errors in the model). The current version of GBIS (V1.0) includes fast analytical forward models for magmatic sources of different geometry (e.g., point source, finite spherical source, prolate spheroid source, penny-shaped sill-like source, and dipping-dike with uniform opening) and for dipping faults with uniform slip, embedded in a isotropic elastic half-space. However, the software architecture allows the user to easily add any other analytical or numerical forward models to calculate displacements at the surface. GBIS is delivered with a detailed user manual and three synthetic datasets for testing and practical training.

Measurements of Deposition, Lung Surface Area and Lung Fluid for Simulation of Inhaled Compounds.

PubMed

Fröhlich, Eleonore; Mercuri, Annalisa; Wu, Shengqian; Salar-Behzadi, Sharareh

2016-01-01

Modern strategies in drug development employ in silico techniques in the design of compounds as well as estimations of pharmacokinetics, pharmacodynamics and toxicity parameters. The quality of the results depends on software algorithm, data library and input data. Compared to simulations of absorption, distribution, metabolism, excretion, and toxicity of oral drug compounds, relatively few studies report predictions of pharmacokinetics and pharmacodynamics of inhaled substances. For calculation of the drug concentration at the absorption site, the pulmonary epithelium, physiological parameters such as lung surface and distribution volume (lung lining fluid) have to be known. These parameters can only be determined by invasive techniques and by postmortem studies. Very different values have been reported in the literature. This review addresses the state of software programs for simulation of orally inhaled substances and focuses on problems in the determination of particle deposition, lung surface and of lung lining fluid. The different surface areas for deposition and for drug absorption are difficult to include directly into the simulations. As drug levels are influenced by multiple parameters the role of single parameters in the simulations cannot be identified easily.

Power estimation using simulations for air pollution time-series studies

PubMed Central

2012-01-01

Background Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Methods Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. Results In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. Conclusions These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided. PMID:22995599

Power estimation using simulations for air pollution time-series studies.

PubMed

Winquist, Andrea; Klein, Mitchel; Tolbert, Paige; Sarnat, Stefanie Ebelt

2012-09-20

Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided.

Terrestrial reference frame solution with the Vienna VLBI Software VieVS and implication of tropospheric gradient estimation

NASA Astrophysics Data System (ADS)

Spicakova, H.; Plank, L.; Nilsson, T.; Böhm, J.; Schuh, H.

2011-07-01

The Vienna VLBI Software (VieVS) has been developed at the Institute of Geodesy and Geophysics at TU Vienna since 2008. In this presentation, we present the module Vie_glob which is the part of VieVS that allows the parameter estimation from multiple VLBI sessions in a so-called global solution. We focus on the determination of the terrestrial reference frame (TRF) using all suitable VLBI sessions since 1984. We compare different analysis options like the choice of loading corrections or of one of the models for the tropospheric delays. The effect of atmosphere loading corrections on station heights if neglected at observation level will be shown. Time series of station positions (using a previously determined TRF as a priori values) are presented and compared to other estimates of site positions from individual IVS (International VLBI Service for Geodesy and Astrometry) Analysis Centers.

Earth-moon system: Dynamics and parameter estimation

NASA Technical Reports Server (NTRS)

Breedlove, W. J., Jr.

1975-01-01

A theoretical development of the equations of motion governing the earth-moon system is presented. The earth and moon were treated as finite rigid bodies and a mutual potential was utilized. The sun and remaining planets were treated as particles. Relativistic, non-rigid, and dissipative effects were not included. The translational and rotational motion of the earth and moon were derived in a fully coupled set of equations. Euler parameters were used to model the rotational motions. The mathematical model is intended for use with data analysis software to estimate physical parameters of the earth-moon system using primarily LURE type data. Two program listings are included. Program ANEAMO computes the translational/rotational motion of the earth and moon from analytical solutions. Program RIGEM numerically integrates the fully coupled motions as described above.

SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology

PubMed Central

Adams, Richard; Clark, Allan; Yamaguchi, Azusa; Hanlon, Neil; Tsorman, Nikos; Ali, Shakir; Lebedeva, Galina; Goltsov, Alexey; Sorokin, Anatoly; Akman, Ozgur E.; Troein, Carl; Millar, Andrew J.; Goryanin, Igor; Gilmore, Stephen

2013-01-01

Summary: Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting; SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers; and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSI’s use of standard data formats. Availability and implementation: All SBSI binaries and source-code are freely available from http://sourceforge.net/projects/sbsi under an Apache 2 open-source license. The server-side SBSINumerics runs on any Unix-based operating system; both SBSIVisual and SBSIDispatcher are written in Java and are platform independent, allowing use on Windows, Linux and Mac OS X. The SBSI project website at http://www.sbsi.ed.ac.uk provides documentation and tutorials. Contact: stg@inf.ed.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23329415

Computer-aided diagnosis of prostate cancer using multi-parametric MRI: comparison between PUN and Tofts models

NASA Astrophysics Data System (ADS)

Mazzetti, S.; Giannini, V.; Russo, F.; Regge, D.

2018-05-01

Computer-aided diagnosis (CAD) systems are increasingly being used in clinical settings to report multi-parametric magnetic resonance imaging (mp-MRI) of the prostate. Usually, CAD systems automatically highlight cancer-suspicious regions to the radiologist, reducing reader variability and interpretation errors. Nevertheless, implementing this software requires the selection of which mp-MRI parameters can best discriminate between malignant and non-malignant regions. To exploit functional information, some parameters are derived from dynamic contrast-enhanced (DCE) acquisitions. In particular, much CAD software employs pharmacokinetic features, such as K trans and k ep, derived from the Tofts model, to estimate a likelihood map of malignancy. However, non-pharmacokinetic models can be also used to describe DCE-MRI curves, without any requirement for prior knowledge or measurement of the arterial input function, which could potentially lead to large errors in parameter estimation. In this work, we implemented an empirical function derived from the phenomenological universalities (PUN) class to fit DCE-MRI. The parameters of the PUN model are used in combination with T2-weighted and diffusion-weighted acquisitions to feed a support vector machine classifier to produce a voxel-wise malignancy likelihood map of the prostate. The results were all compared to those for a CAD system based on Tofts pharmacokinetic features to describe DCE-MRI curves, using different quality aspects of image segmentation, while also evaluating the number and size of false positive (FP) candidate regions. This study included 61 patients with 70 biopsy-proven prostate cancers (PCa). The metrics used to evaluate segmentation quality between the two CAD systems were not statistically different, although the PUN-based CAD reported a lower number of FP, with reduced size compared to the Tofts-based CAD. In conclusion, the CAD software based on PUN parameters is a feasible means with which to detect PCa, without affecting segmentation quality, and hence it could be successfully applied in clinical settings, improving the automated diagnosis process and reducing computational complexity.

A new tool for rapid and automatic estimation of earthquake source parameters and generation of seismic bulletins

NASA Astrophysics Data System (ADS)

Zollo, Aldo

2016-04-01

RISS S.r.l. is a Spin-off company recently born from the initiative of the research group constituting the Seismology Laboratory of the Department of Physics of the University of Naples Federico II. RISS is an innovative start-up, based on the decade-long experience in earthquake monitoring systems and seismic data analysis of its members and has the major goal to transform the most recent innovations of the scientific research into technological products and prototypes. With this aim, RISS has recently started the development of a new software, which is an elegant solution to manage and analyse seismic data and to create automatic earthquake bulletins. The software has been initially developed to manage data recorded at the ISNet network (Irpinia Seismic Network), which is a network of seismic stations deployed in Southern Apennines along the active fault system responsible for the 1980, November 23, MS 6.9 Irpinia earthquake. The software, however, is fully exportable and can be used to manage data from different networks, with any kind of station geometry or network configuration and is able to provide reliable estimates of earthquake source parameters, whichever is the background seismicity level of the area of interest. Here we present the real-time automated procedures and the analyses performed by the software package, which is essentially a chain of different modules, each of them aimed at the automatic computation of a specific source parameter. The P-wave arrival times are first detected on the real-time streaming of data and then the software performs the phase association and earthquake binding. As soon as an event is automatically detected by the binder, the earthquake location coordinates and the origin time are rapidly estimated, using a probabilistic, non-linear, exploration algorithm. Then, the software is able to automatically provide three different magnitude estimates. First, the local magnitude (Ml) is computed, using the peak-to-peak amplitude of the equivalent Wood-Anderson displacement recordings. The moment magnitude (Mw) is then estimated from the inversion of displacement spectra. The duration magnitude (Md) is rapidly computed, based on a simple and automatic measurement of the seismic wave coda duration. Starting from the magnitude estimates, other relevant pieces of information are also computed, such as the corner frequency, the seismic moment, the source radius and the seismic energy. The ground-shaking maps on a Google map are produced, for peak ground acceleration (PGA), peak ground velocity (PGV) and instrumental intensity (in SHAKEMAP® format), or a plot of the measured peak ground values. Furthermore, based on a specific decisional scheme, the automatic discrimination between local earthquakes occurred within the network and regional/teleseismic events occurred outside the network is performed. Finally, for largest events, if a consistent number of P-wave polarity reading are available, the focal mechanism is also computed. For each event, all of the available pieces of information are stored in a local database and the results of the automatic analyses are published on an interactive web page. "The Bulletin" shows a map with event location and stations, as well as a table listing all the events, with the associated parameters. The catalogue fields are the event ID, the origin date and time, latitude, longitude, depth, Ml, Mw, Md, the number of triggered stations, the S-displacement spectra, and shaking maps. Some of these entries also provide additional information, such as the focal mechanism (when available). The picked traces are uploaded in the database and from the web interface of the Bulletin the traces can be download for more specific analysis. This innovative software represents a smart solution, with a friendly and interactive interface, for high-level analysis of seismic data analysis and it may represent a relevant tool not only for seismologists, but also for non-expert external users who are interested in the seismological data. The software is a valid tool for the automatic analysis of the background seismicity at different time scales and can be a relevant tool for the monitoring of both natural and induced seismicity.

Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module

PubMed Central

Lo, Yuan-Chieh; Hu, Yuh-Chung; Chang, Pei-Zen

2018-01-01

Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system. PMID:29473877

Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module.

PubMed

Lo, Yuan-Chieh; Hu, Yuh-Chung; Chang, Pei-Zen

2018-02-23

Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system.

MATLAB-implemented estimation procedure for model-based assessment of hepatic insulin degradation from standard intravenous glucose tolerance test data.

PubMed

Di Nardo, Francesco; Mengoni, Michele; Morettini, Micaela

2013-05-01

Present study provides a novel MATLAB-based parameter estimation procedure for individual assessment of hepatic insulin degradation (HID) process from standard frequently-sampled intravenous glucose tolerance test (FSIGTT) data. Direct access to the source code, offered by MATLAB, enabled us to design an optimization procedure based on the alternating use of Gauss-Newton's and Levenberg-Marquardt's algorithms, which assures the full convergence of the process and the containment of computational time. Reliability was tested by direct comparison with the application, in eighteen non-diabetic subjects, of well-known kinetic analysis software package SAAM II, and by application on different data. Agreement between MATLAB and SAAM II was warranted by intraclass correlation coefficients ≥0.73; no significant differences between corresponding mean parameter estimates and prediction of HID rate; and consistent residual analysis. Moreover, MATLAB optimization procedure resulted in a significant 51% reduction of CV% for the worst-estimated parameter by SAAM II and in maintaining all model-parameter CV% <20%. In conclusion, our MATLAB-based procedure was suggested as a suitable tool for the individual assessment of HID process. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

A new procedure of modal parameter estimation for high-speed digital image correlation

NASA Astrophysics Data System (ADS)

Huňady, Róbert; Hagara, Martin

2017-09-01

The paper deals with the use of 3D digital image correlation in determining modal parameters of mechanical systems. It is a non-contact optical method, which for the measurement of full-field spatial displacements and strains of bodies uses precise digital cameras with high image resolution. Most often this method is utilized for testing of components or determination of material properties of various specimens. In the case of using high-speed cameras for measurement, the correlation system is capable of capturing various dynamic behaviors, including vibration. This enables the potential use of the mentioned method in experimental modal analysis. For that purpose, the authors proposed a measuring chain for the correlation system Q-450 and developed a software application called DICMAN 3D, which allows the direct use of this system in the area of modal testing. The created application provides the post-processing of measured data and the estimation of modal parameters. It has its own graphical user interface, in which several algorithms for the determination of natural frequencies, mode shapes and damping of particular modes of vibration are implemented. The paper describes the basic principle of the new estimation procedure which is crucial in the light of post-processing. Since the FRF matrix resulting from the measurement is usually relatively large, the estimation of modal parameters directly from the FRF matrix may be time-consuming and may occupy a large part of computer memory. The procedure implemented in DICMAN 3D provides a significant reduction in memory requirements and computational time while achieving a high accuracy of modal parameters. Its computational efficiency is particularly evident when the FRF matrix consists of thousands of measurement DOFs. The functionality of the created software application is presented on a practical example in which the modal parameters of a composite plate excited by an impact hammer were determined. For the verification of the obtained results a verification experiment was conducted during which the vibration responses were measured using conventional acceleration sensors. In both cases MIMO analysis was realized.

Parameter optimization for the visco-hyperelastic constitutive model of tendon using FEM.

PubMed

Tang, C Y; Ng, G Y F; Wang, Z W; Tsui, C P; Zhang, G

2011-01-01

Numerous constitutive models describing the mechanical properties of tendons have been proposed during the past few decades. However, few were widely used owing to the lack of implementation in the general finite element (FE) software, and very few systematic studies have been done on selecting the most appropriate parameters for these constitutive laws. In this work, the visco-hyperelastic constitutive model of the tendon implemented through the use of three-parameter Mooney-Rivlin form and sixty-four-parameter Prony series were firstly analyzed using ANSYS FE software. Afterwards, an integrated optimization scheme was developed by coupling two optimization toolboxes (OPTs) of ANSYS and MATLAB for estimating these unknown constitutive parameters of the tendon. Finally, a group of Sprague-Dawley rat tendons was used to execute experimental and numerical simulation investigation. The simulated results showed good agreement with the experimental data. An important finding revealed that too many Maxwell elements was not necessary for assuring accuracy of the model, which is often neglected in most open literatures. Thus, all these proved that the constitutive parameter optimization scheme was reliable and highly efficient. Furthermore, the approach can be extended to study other tendons or ligaments, as well as any visco-hyperelastic solid materials.

Empirical Histograms in Item Response Theory with Ordinal Data

ERIC Educational Resources Information Center

Woods, Carol M.

2007-01-01

The purpose of this research is to describe, test, and illustrate a new implementation of the empirical histogram (EH) method for ordinal items. The EH method involves the estimation of item response model parameters simultaneously with the approximation of the distribution of the random latent variable (theta) as a histogram. Software for the EH…

Fitting ARMA Time Series by Structural Equation Models.

ERIC Educational Resources Information Center

van Buuren, Stef

1997-01-01

This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)

ECOUL: an interactive computer tool to study hydraulic behavior of swelling and rigid soils

NASA Astrophysics Data System (ADS)

Perrier, Edith; Garnier, Patricia; Leclerc, Christian

2002-11-01

ECOUL is an interactive, didactic software package which simulates vertical water flow in unsaturated soils. End-users are given an easily-used tool to predict the evolution of the soil water profile, with a large range of possible boundary conditions, through a classical numerical solution scheme for the Richards equation. Soils must be characterized by water retention curves and hydraulic conductivity curves, the form of which can be chosen among different analytical expressions from the literature. When the parameters are unknown, an inverse method is provided to estimate them from available experimental flow data. A significant original feature of the software is to include recent algorithms extending the water flow model to deal with deforming porous media: widespread swelling soils, the volume of which varies as a function of water content, must be described by a third hydraulic characteristic property, the deformation curve. Again, estimation of the parameters by means of inverse procedures and visualization facilities enable exploration, understanding and then prediction of soil hydraulic behavior under various experimental conditions.

Thermodynamically consistent model calibration in chemical kinetics

PubMed Central

2011-01-01

Background The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function. Results We introduce a thermodynamically consistent model calibration (TCMC) method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints) into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database. Conclusions TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new models. Furthermore, TCMC can provide dimensionality reduction, better estimation performance, and lower computational complexity, and can help to alleviate the problem of data overfitting. PMID:21548948

SlugIn 1.0: A Free Tool for Automated Slug Test Analysis.

PubMed

Martos-Rosillo, Sergio; Guardiola-Albert, Carolina; Padilla Benítez, Alberto; Delgado Pastor, Joaquín; Azcón González, Antonio; Durán Valsero, Juan José

2018-05-01

The correct characterization of aquifer parameters is essential for water-supply and water-quality investigations. Slug tests are widely used for these purposes. While free software is available to interpret slug tests, some codes are not user-friendly, or do not include a wide range of methods to interpret the results, or do not include automatic, inverse solutions to the test data. The private sector has also generated several good programs to interpret slug test data, but they are not free of charge. The computer program SlugIn 1.0 is available online for free download, and is demonstrated to aid in the analysis of slug tests to estimate hydraulic parameters. The program provides an easy-to-use Graphical User Interface. SlugIn 1.0 incorporates automated parameter estimation and facilitates the visualization of several interpretations of the same test. It incorporates solutions for confined and unconfined aquifers, partially penetrating wells, skin effects, shape factor, anisotropy, high hydraulic conductivity formations and the Mace test for large-diameter wells. It is available in English and Spanish and can be downloaded from the web site of the Geological Survey of Spain. Two field examples are presented to illustrate how the software operates. © 2018, National Ground Water Association.

Urban Earthquake Shaking and Loss Assessment

NASA Astrophysics Data System (ADS)

Hancilar, U.; Tuzun, C.; Yenidogan, C.; Zulfikar, C.; Durukal, E.; Erdik, M.

2009-04-01

This study, conducted under the JRA-3 component of the EU NERIES Project, develops a methodology and software (ELER) for the rapid estimation of earthquake shaking and losses the Euro-Mediterranean region. This multi-level methodology developed together with researchers from Imperial College, NORSAR and ETH-Zurich is capable of incorporating regional variability and sources of uncertainty stemming from ground motion predictions, fault finiteness, site modifications, inventory of physical and social elements subjected to earthquake hazard and the associated vulnerability relationships. GRM Risk Management, Inc. of Istanbul serves as sub-contractor tor the coding of the ELER software. The methodology encompasses the following general steps: 1. Finding of the most likely location of the source of the earthquake using regional seismotectonic data base and basic source parameters, and if and when possible, by the estimation of fault rupture parameters from rapid inversion of data from on-line stations. 2. Estimation of the spatial distribution of selected ground motion parameters through region specific ground motion attenuation relationships and using shear wave velocity distributions.(Shake Mapping) 4. Incorporation of strong ground motion and other empirical macroseismic data for the improvement of Shake Map 5. Estimation of the losses (damage, casualty and economic) at different levels of sophistication (0, 1 and 2) that commensurate with the availability of inventory of human built environment (Loss Mapping) Level 2 analysis of the ELER Software (similar to HAZUS and SELENA) is essentially intended for earthquake risk assessment (building damage, consequential human casualties and macro economic loss quantifiers) in urban areas. The basic Shake Mapping is similar to the Level 0 and Level 1 analysis however, options are available for more sophisticated treatment of site response through externally entered data and improvement of the shake map through incorporation of accelerometric and other macroseismic data (similar to the USGS ShakeMap System). The building inventory data for the Level 2 analysis will consist of grid (geo-cell) based urban building and demographic inventories. For building grouping the European building typology developed within the EU-FP5 RISK-EU project is used. The building vulnerability/fragility relationships to be used can be user selected from a list of applicable relationships developed on the basis of a comprehensive study, Both empirical and analytical relationships (based on the Coefficient Method, Equivalent Linearization Method and the Reduction Factor Method of analysis) can be employed. Casualties in Level 2 analysis are estimated based on the number of buildings in different damaged states and the casualty rates for each building type and damage level. Modifications to the casualty rates can be used if necessary. ELER Level 2 analysis will include calculation of direct monetary losses as a result building damage that will allow for repair-cost estimations and specific investigations associated with earthquake insurance applications (PML and AAL estimations). ELER Level 2 analysis loss results obtained for Istanbul for a scenario earthquake using different techniques will be presented with comparisons using different earthquake damage assessment software. The urban earthquake shaking and loss information is intented for dissemination in a timely manner to related agencies for the planning and coordination of the post-earthquake emergency response. However the same software can also be used for scenario earthquake loss estimation, related Monte-Carlo type simulations and eathquake insurance applications.

Direct estimation of tidally induced Earth rotation variations observed by VLBI

NASA Astrophysics Data System (ADS)

Englich, S.; Heinkelmann, R.; BOHM, J.; Schuh, H.

2009-09-01

The subject of our study is the investigation of periodical variations induced by solid Earth tides and ocean tides in Earth rotation parameters (ERP: polar motion, UT1)observed by VLBI. There are two strategies to determine the amplitudes and phases of Earth rotation variations from observations of space geodetic techniques. The common way is to derive time series of Earth rotation parameters first and to estimate amplitudes and phases in a second step. Results obtained by this means were shown in previous studies for zonal tidal variations (Englich et al.; 2008a) and variations caused by ocean tides (Englich et al.; 2008b). The alternative method is to estimate the tidal parameters directly within the VLBI data analysis procedure together with other parameters such as station coordinates, tropospheric delays, clocks etc. The purpose of this work was the application of this direct method to a combined VLBI data analysis using the software packages OCCAM (Version 6.1, Gauss-Markov-Model) and DOGSCS (Gerstl et al.; 2001). The theoretical basis and the preparatory steps for the implementation of this approach are presented here.

A Web-Based System for Bayesian Benchmark Dose Estimation.

PubMed

Shao, Kan; Shapiro, Andrew J

2018-01-11

Benchmark dose (BMD) modeling is an important step in human health risk assessment and is used as the default approach to identify the point of departure for risk assessment. A probabilistic framework for dose-response assessment has been proposed and advocated by various institutions and organizations; therefore, a reliable tool is needed to provide distributional estimates for BMD and other important quantities in dose-response assessment. We developed an online system for Bayesian BMD (BBMD) estimation and compared results from this software with U.S. Environmental Protection Agency's (EPA's) Benchmark Dose Software (BMDS). The system is built on a Bayesian framework featuring the application of Markov chain Monte Carlo (MCMC) sampling for model parameter estimation and BMD calculation, which makes the BBMD system fundamentally different from the currently prevailing BMD software packages. In addition to estimating the traditional BMDs for dichotomous and continuous data, the developed system is also capable of computing model-averaged BMD estimates. A total of 518 dichotomous and 108 continuous data sets extracted from the U.S. EPA's Integrated Risk Information System (IRIS) database (and similar databases) were used as testing data to compare the estimates from the BBMD and BMDS programs. The results suggest that the BBMD system may outperform the BMDS program in a number of aspects, including fewer failed BMD and BMDL calculations and estimates. The BBMD system is a useful alternative tool for estimating BMD with additional functionalities for BMD analysis based on most recent research. Most importantly, the BBMD has the potential to incorporate prior information to make dose-response modeling more reliable and can provide distributional estimates for important quantities in dose-response assessment, which greatly facilitates the current trend for probabilistic risk assessment. https://doi.org/10.1289/EHP1289.

Abschätzung des Einflusses von Parameterunsicherheiten bei der Planung und Auswertung von Tracertests unter Verwendung von Ensembleprognosen

NASA Astrophysics Data System (ADS)

Klotzsch, Stephan; Binder, Martin; Händel, Falk

2017-06-01

While planning tracer tests, uncertainties in geohydraulic parameters should be considered as an important factor. Neglecting these uncertainties can lead to missing the tracer breakthrough, for example. One way to consider uncertainties during tracer test design is the so called ensemble forecast. The applicability of this method to geohydrological problems is demonstrated by coupling the method with two analytical solute transport models. The algorithm presented in this article is suitable for prediction as well as parameter estimation. The parameter estimation function can be used in a tracer test for reducing the uncertainties in the measured data which can improve the initial prediction. The algorithm was implemented into a software tool which is freely downloadable from the website of the Institute for Groundwater Management at TU Dresden, Germany.

Geoelectrohydraulic investigation of the surficial aquifer units and corrosivity in parts of Uyo L. G. A., Akwa Ibom State, Southern Nigeria

NASA Astrophysics Data System (ADS)

Ibuot, Johnson C.; Obiora, Daniel N.; Ekpa, Moses M. M.; Okoroh, Doris O.

2017-12-01

This study was carried out employing vertical electrical sounding (VES) with Schlumberger electrode configuration. The objectives were to investigate the distribution of the geohydraulic parameters and the corrosivity of the aquifer layer within the study area. The sand-to-coarse grain sands aquifer have resistivity ranging from 8.1 to 2204 Ωm, while the thickness ranged from 7.4 to 55.3 m. These parameters were used in computing the geohydraulic parameters. Hydraulic conductivity was estimated using the Heigold equation, and its values ranged from 1.42 to 54.90 m/day. Estimated hydraulic conductivity values were employed in determining the aquifer transmissivity which ranged from 11.28 to 812.00 m2/day, fractional porosities ranged from 0.0351 to 0.0598. The longitudinarl conductance also varies from 0.01 to 1.83 Ω-1. The contour plots generated from the SURFER software package show the variation of these parameters. The ranges of these estimated parameters indicate variation in grain sizes, magnitude of pore sizes and facies changes. The corrosivity rating indicates that most of the VES points were practically non-corrosive.

EGADS: A microcomputer program for estimating the aerodynamic performance of general aviation aircraft

NASA Technical Reports Server (NTRS)

Melton, John E.

1994-01-01

EGADS is a comprehensive preliminary design tool for estimating the performance of light, single-engine general aviation aircraft. The software runs on the Apple Macintosh series of personal computers and assists amateur designers and aeronautical engineering students in performing the many repetitive calculations required in the aircraft design process. The program makes full use of the mouse and standard Macintosh interface techniques to simplify the input of various design parameters. Extensive graphics, plotting, and text output capabilities are also included.

Occupancy models to study wildlife

USGS Publications Warehouse

Bailey, Larissa; Adams, Michael John

2005-01-01

Many wildlife studies seek to understand changes or differences in the proportion of sites occupied by a species of interest. These studies are hampered by imperfect detection of these species, which can result in some sites appearing to be unoccupied that are actually occupied. Occupancy models solve this problem and produce unbiased estimates of occupancy and related parameters. Required data (detection/non-detection information) are relatively simple and inexpensive to collect. Software is available free of charge to aid investigators in occupancy estimation.

Rapid earthquake hazard and loss assessment for Euro-Mediterranean region

NASA Astrophysics Data System (ADS)

Erdik, Mustafa; Sesetyan, Karin; Demircioglu, Mine; Hancilar, Ufuk; Zulfikar, Can; Cakti, Eser; Kamer, Yaver; Yenidogan, Cem; Tuzun, Cuneyt; Cagnan, Zehra; Harmandar, Ebru

2010-10-01

The almost-real time estimation of ground shaking and losses after a major earthquake in the Euro-Mediterranean region was performed in the framework of the Joint Research Activity 3 (JRA-3) component of the EU FP6 Project entitled "Network of Research Infra-structures for European Seismology, NERIES". This project consists of finding the most likely location of the earthquake source by estimating the fault rupture parameters on the basis of rapid inversion of data from on-line regional broadband stations. It also includes an estimation of the spatial distribution of selected site-specific ground motion parameters at engineering bedrock through region-specific ground motion prediction equations (GMPEs) or physical simulation of ground motion. By using the Earthquake Loss Estimation Routine (ELER) software, the multi-level methodology developed for real time estimation of losses is capable of incorporating regional variability and sources of uncertainty stemming from GMPEs, fault finiteness, site modifications, inventory of physical and social elements subjected to earthquake hazard and the associated vulnerability relationships.

Interactive system for geomagnetic data analysis

NASA Astrophysics Data System (ADS)

Solovev, Igor

2017-10-01

The paper suggests the methods for analyzing geomagnetic field variations, which are implemented in "Aurora" software system for complex analysis of geophysical parameters. The software system allows one to perform a detailed magnetic data analysis. The methods allow one to estimate the intensity of geomagnetic perturbations and to allocate increased geomagnetic activity periods. The software system is publicly available (http://aurorasa.ikir.ru:8580, http://www.ikir.ru:8280/lsaserver/MagneticPage.jsp). This research was supported by the Russian Science Foundation (Project No. 14-11-00194).

A Bayesian modification to the Jelinski-Moranda software reliability growth model

NASA Technical Reports Server (NTRS)

Littlewood, B.; Sofer, A.

1983-01-01

The Jelinski-Moranda (JM) model for software reliability was examined. It is suggested that a major reason for the poor results given by this model is the poor performance of the maximum likelihood method (ML) of parameter estimation. A reparameterization and Bayesian analysis, involving a slight modelling change, are proposed. It is shown that this new Bayesian-Jelinski-Moranda model (BJM) is mathematically quite tractable, and several metrics of interest to practitioners are obtained. The BJM and JM models are compared by using several sets of real software failure data collected and in all cases the BJM model gives superior reliability predictions. A change in the assumption which underlay both models to present the debugging process more accurately is discussed.

Real-Time GPS Monitoring for Earthquake Rapid Assessment in the San Francisco Bay Area

NASA Astrophysics Data System (ADS)

Guillemot, C.; Langbein, J. O.; Murray, J. R.

2012-12-01

The U.S. Geological Survey Earthquake Science Center has deployed a network of eight real-time Global Positioning System (GPS) stations in the San Francisco Bay area and is implementing software applications to continuously evaluate the status of the deformation within the network. Real-time monitoring of the station positions is expected to provide valuable information for rapidly estimating source parameters should a large earthquake occur in the San Francisco Bay area. Because earthquake response applications require robust data access, as a first step we have developed a suite of web-based applications which are now routinely used to monitor the network's operational status and data streaming performance. The web tools provide continuously updated displays of important telemetry parameters such as data latency and receive rates, as well as source voltage and temperature information within each instrument enclosure. Automated software on the backend uses the streaming performance data to mitigate the impact of outages, radio interference and bandwidth congestion on deformation monitoring operations. A separate set of software applications manages the recovery of lost data due to faulty communication links. Displacement estimates are computed in real-time for various combinations of USGS, Plate Boundary Observatory (PBO) and Bay Area Regional Deformation (BARD) network stations. We are currently comparing results from two software packages (one commercial and one open-source) used to process 1-Hz data on the fly and produce estimates of differential positions. The continuous monitoring of telemetry makes it possible to tune the network to minimize the impact of transient interruptions of the data flow, from one or more stations, on the estimated positions. Ongoing work is focused on using data streaming performance history to optimize the quality of the position, reduce drift and outliers by switching to the best set of stations within the network, and automatically select the "next best" station to use as reference. We are also working towards minimizing the loss of streamed data during concurrent data downloads by improving file management on the GPS receivers.

JuPOETs: a constrained multiobjective optimization approach to estimate biochemical model ensembles in the Julia programming language.

PubMed

Bassen, David M; Vilkhovoy, Michael; Minot, Mason; Butcher, Jonathan T; Varner, Jeffrey D

2017-01-25

Ensemble modeling is a promising approach for obtaining robust predictions and coarse grained population behavior in deterministic mathematical models. Ensemble approaches address model uncertainty by using parameter or model families instead of single best-fit parameters or fixed model structures. Parameter ensembles can be selected based upon simulation error, along with other criteria such as diversity or steady-state performance. Simulations using parameter ensembles can estimate confidence intervals on model variables, and robustly constrain model predictions, despite having many poorly constrained parameters. In this software note, we present a multiobjective based technique to estimate parameter or models ensembles, the Pareto Optimal Ensemble Technique in the Julia programming language (JuPOETs). JuPOETs integrates simulated annealing with Pareto optimality to estimate ensembles on or near the optimal tradeoff surface between competing training objectives. We demonstrate JuPOETs on a suite of multiobjective problems, including test functions with parameter bounds and system constraints as well as for the identification of a proof-of-concept biochemical model with four conflicting training objectives. JuPOETs identified optimal or near optimal solutions approximately six-fold faster than a corresponding implementation in Octave for the suite of test functions. For the proof-of-concept biochemical model, JuPOETs produced an ensemble of parameters that gave both the mean of the training data for conflicting data sets, while simultaneously estimating parameter sets that performed well on each of the individual objective functions. JuPOETs is a promising approach for the estimation of parameter and model ensembles using multiobjective optimization. JuPOETs can be adapted to solve many problem types, including mixed binary and continuous variable types, bilevel optimization problems and constrained problems without altering the base algorithm. JuPOETs is open source, available under an MIT license, and can be installed using the Julia package manager from the JuPOETs GitHub repository.

Approaches to highly parameterized inversion: Pilot-point theory, guidelines, and research directions

USGS Publications Warehouse

Doherty, John E.; Fienen, Michael N.; Hunt, Randall J.

2011-01-01

Pilot points have been used in geophysics and hydrogeology for at least 30 years as a means to bridge the gap between estimating a parameter value in every cell of a model and subdividing models into a small number of homogeneous zones. Pilot points serve as surrogate parameters at which values are estimated in the inverse-modeling process, and their values are interpolated onto the modeling domain in such a way that heterogeneity can be represented at a much lower computational cost than trying to estimate parameters in every cell of a model. Although the use of pilot points is increasingly common, there are few works documenting the mathematical implications of their use and even fewer sources of guidelines for their implementation in hydrogeologic modeling studies. This report describes the mathematics of pilot-point use, provides guidelines for their use in the parameter-estimation software suite (PEST), and outlines several research directions. Two key attributes for pilot-point definitions are highlighted. First, the difference between the information contained in the every-cell parameter field and the surrogate parameter field created using pilot points should be in the realm of parameters which are not informed by the observed data (the null space). Second, the interpolation scheme for projecting pilot-point values onto model cells ideally should be orthogonal. These attributes are informed by the mathematics and have important ramifications for both the guidelines and suggestions for future research.

Comparative study of age estimation using dentinal translucency by digital and conventional methods.

PubMed

Bommannavar, Sushma; Kulkarni, Meena

2015-01-01

Estimating age using the dentition plays a significant role in identification of the individual in forensic cases. Teeth are one of the most durable and strongest structures in the human body. The morphology and arrangement of teeth vary from person-to-person and is unique to an individual as are the fingerprints. Therefore, the use of dentition is the method of choice in the identification of the unknown. Root dentin translucency is considered to be one of the best parameters for dental age estimation. Traditionally, root dentin translucency was measured using calipers. Recently, the use of custom built software programs have been proposed for the same. The present study describes a method to measure root dentin translucency on sectioned teeth using a custom built software program Adobe Photoshop 7.0 version (Adobe system Inc, Mountain View California). A total of 50 single rooted teeth were sectioned longitudinally to derive a 0.25 mm uniform thickness and the root dentin translucency was measured using digital and caliper methods and compared. The Gustafson's morphohistologic approach is used in this study. Correlation coefficients of translucency measurements to age were statistically significant for both the methods (P < 0.125) and linear regression equations derived from both methods revealed better ability of the digital method to assess age. The custom built software program used in the present study is commercially available and widely used image editing software. Furthermore, this method is easy to use and less time consuming. The measurements obtained using this method are more precise and thus help in more accurate age estimation. Considering these benefits, the present study recommends the use of digital method to assess translucency for age estimation.

Comparative study of age estimation using dentinal translucency by digital and conventional methods

PubMed Central

Bommannavar, Sushma; Kulkarni, Meena

2015-01-01

Introduction: Estimating age using the dentition plays a significant role in identification of the individual in forensic cases. Teeth are one of the most durable and strongest structures in the human body. The morphology and arrangement of teeth vary from person-to-person and is unique to an individual as are the fingerprints. Therefore, the use of dentition is the method of choice in the identification of the unknown. Root dentin translucency is considered to be one of the best parameters for dental age estimation. Traditionally, root dentin translucency was measured using calipers. Recently, the use of custom built software programs have been proposed for the same. Objectives: The present study describes a method to measure root dentin translucency on sectioned teeth using a custom built software program Adobe Photoshop 7.0 version (Adobe system Inc, Mountain View California). Materials and Methods: A total of 50 single rooted teeth were sectioned longitudinally to derive a 0.25 mm uniform thickness and the root dentin translucency was measured using digital and caliper methods and compared. The Gustafson's morphohistologic approach is used in this study. Results: Correlation coefficients of translucency measurements to age were statistically significant for both the methods (P < 0.125) and linear regression equations derived from both methods revealed better ability of the digital method to assess age. Conclusion: The custom built software program used in the present study is commercially available and widely used image editing software. Furthermore, this method is easy to use and less time consuming. The measurements obtained using this method are more precise and thus help in more accurate age estimation. Considering these benefits, the present study recommends the use of digital method to assess translucency for age estimation. PMID:25709325

Evaluation of Available Software for Reconstruction of a Structure from its Imagery

DTIC Science & Technology

2017-04-01

Math . 2, 164–168. Lowe, D. G. (1999) Object recognition from local scale-invariant features, in Proc. Int. Conf. Computer Vision, Vol. 2, pp. 1150–1157...Marquardt, D. (1963) An algorithm for least-squares estimation of nonlinear parameters, SIAM J. Appl. Math . 11(2), 431–441. UNCLASSIFIED 11 DST-Group–TR

Cost Estimation of Software Development and the Implications for the Program Manager

DTIC Science & Technology

1992-06-01

Software Lifecycle Model (SLIM), the Jensen System-4 model, the Software Productivity, Quality, and Reliability Estimator ( SPQR \\20), the Constructive...function models in current use are the Software Productivity, Quality, and Reliability Estimator ( SPQR /20) and the Software Architecture Sizing and...Estimator ( SPQR /20) was developed by T. Capers Jones of Software Productivity Research, Inc., in 1985. The model is intended to estimate the outcome

Measurements of Deposition, Lung Surface Area and Lung Fluid for Simulation of Inhaled Compounds

PubMed Central

Fröhlich, Eleonore; Mercuri, Annalisa; Wu, Shengqian; Salar-Behzadi, Sharareh

2016-01-01

Modern strategies in drug development employ in silico techniques in the design of compounds as well as estimations of pharmacokinetics, pharmacodynamics and toxicity parameters. The quality of the results depends on software algorithm, data library and input data. Compared to simulations of absorption, distribution, metabolism, excretion, and toxicity of oral drug compounds, relatively few studies report predictions of pharmacokinetics and pharmacodynamics of inhaled substances. For calculation of the drug concentration at the absorption site, the pulmonary epithelium, physiological parameters such as lung surface and distribution volume (lung lining fluid) have to be known. These parameters can only be determined by invasive techniques and by postmortem studies. Very different values have been reported in the literature. This review addresses the state of software programs for simulation of orally inhaled substances and focuses on problems in the determination of particle deposition, lung surface and of lung lining fluid. The different surface areas for deposition and for drug absorption are difficult to include directly into the simulations. As drug levels are influenced by multiple parameters the role of single parameters in the simulations cannot be identified easily. PMID:27445817

Time-delayed chameleon: Analysis, synchronization and FPGA implementation

NASA Astrophysics Data System (ADS)

Rajagopal, Karthikeyan; Jafari, Sajad; Laarem, Guessas

2017-12-01

In this paper we report a time-delayed chameleon-like chaotic system which can belong to different families of chaotic attractors depending on the choices of parameters. Such a characteristic of self-excited and hidden chaotic flows in a simple 3D system with time delay has not been reported earlier. Dynamic analysis of the proposed time-delayed systems are analysed in time-delay space and parameter space. A novel adaptive modified functional projective lag synchronization algorithm is derived for synchronizing identical time-delayed chameleon systems with uncertain parameters. The proposed time-delayed systems and the synchronization algorithm with controllers and parameter estimates are then implemented in FPGA using hardware-software co-simulation and the results are presented.

Software thresholds alter the bias of actigraphy for monitoring sleep in team-sport athletes.

PubMed

Fuller, Kate L; Juliff, Laura; Gore, Christopher J; Peiffer, Jeremiah J; Halson, Shona L

2017-08-01

Actical ® actigraphy is commonly used to monitor athlete sleep. The proprietary software, called Actiware ® , processes data with three different sleep-wake thresholds (Low, Medium or High), but there is no standardisation regarding their use. The purpose of this study was to examine validity and bias of the sleep-wake thresholds for processing Actical ® sleep data in team sport athletes. Validation study comparing actigraph against accepted gold standard polysomnography (PSG). Sixty seven nights of sleep were recorded simultaneously with polysomnography and Actical ® devices. Individual night data was compared across five sleep measures for each sleep-wake threshold using Actiware ® software. Accuracy of each sleep-wake threshold compared with PSG was evaluated from mean bias with 95% confidence limits, Pearson moment-product correlation and associated standard error of estimate. The Medium threshold generated the smallest mean bias compared with polysomnography for total sleep time (8.5min), sleep efficiency (1.8%) and wake after sleep onset (-4.1min); whereas the Low threshold had the smallest bias (7.5min) for wake bouts. Bias in sleep onset latency was the same across thresholds (-9.5min). The standard error of the estimate was similar across all thresholds; total sleep time ∼25min, sleep efficiency ∼4.5%, wake after sleep onset ∼21min, and wake bouts ∼8 counts. Sleep parameters measured by the Actical ® device are greatly influenced by the sleep-wake threshold applied. In the present study the Medium threshold produced the smallest bias for most parameters compared with PSG. Given the magnitude of measurement variability, confidence limits should be employed when interpreting changes in sleep parameters. Copyright © 2017 Sports Medicine Australia. All rights reserved.

Beef quality parameters estimation using ultrasound and color images

PubMed Central

2015-01-01

Background Beef quality measurement is a complex task with high economic impact. There is high interest in obtaining an automatic quality parameters estimation in live cattle or post mortem. In this paper we set out to obtain beef quality estimates from the analysis of ultrasound (in vivo) and color images (post mortem), with the measurement of various parameters related to tenderness and amount of meat: rib eye area, percentage of intramuscular fat and backfat thickness or subcutaneous fat. Proposal An algorithm based on curve evolution is implemented to calculate the rib eye area. The backfat thickness is estimated from the profile of distances between two curves that limit the steak and the rib eye, previously detected. A model base in Support Vector Regression (SVR) is trained to estimate the intramuscular fat percentage. A series of features extracted on a region of interest, previously detected in both ultrasound and color images, were proposed. In all cases, a complete evaluation was performed with different databases including: color and ultrasound images acquired by a beef industry expert, intramuscular fat estimation obtained by an expert using a commercial software, and chemical analysis. Conclusions The proposed algorithms show good results to calculate the rib eye area and the backfat thickness measure and profile. They are also promising in predicting the percentage of intramuscular fat. PMID:25734452

Gpufit: An open-source toolkit for GPU-accelerated curve fitting.

PubMed

Przybylski, Adrian; Thiel, Björn; Keller-Findeisen, Jan; Stock, Bernd; Bates, Mark

2017-11-16

We present a general purpose, open-source software library for estimation of non-linear parameters by the Levenberg-Marquardt algorithm. The software, Gpufit, runs on a Graphics Processing Unit (GPU) and executes computations in parallel, resulting in a significant gain in performance. We measured a speed increase of up to 42 times when comparing Gpufit with an identical CPU-based algorithm, with no loss of precision or accuracy. Gpufit is designed such that it is easily incorporated into existing applications or adapted for new ones. Multiple software interfaces, including to C, Python, and Matlab, ensure that Gpufit is accessible from most programming environments. The full source code is published as an open source software repository, making its function transparent to the user and facilitating future improvements and extensions. As a demonstration, we used Gpufit to accelerate an existing scientific image analysis package, yielding significantly improved processing times for super-resolution fluorescence microscopy datasets.

A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package

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

Genser, Krzysztof; Hatcher, Robert; Kelsey, Michael

The Geant4 simulation toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. These models rely on measured cross-sections and phenomenological models with the physically motivated parameters that are tuned to cover many application domains. To study what uncertainties are associated with the Geant4 physics models we have designed and implemented a comprehensive, modular, user-friendly software toolkit that allows the variation of one or more parameters of one or more Geant4 physics models involved in simulation studies. It also enables analysis of multiple variantsmore » of the resulting physics observables of interest in order to estimate the uncertainties associated with the simulation model choices. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. exible run-time con gurable work ow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented in this paper and illustrated with selected results.« less

Development of Software Sensors for Determining Total Phosphorus and Total Nitrogen in Waters

PubMed Central

Lee, Eunhyoung; Han, Sanghoon; Kim, Hyunook

2013-01-01

Total nitrogen (TN) and total phosphorus (TP) concentrations are important parameters to assess the quality of water bodies and are used as criteria to regulate the water quality of the effluent from a wastewater treatment plant (WWTP) in Korea. Therefore, continuous monitoring of TN and TP using in situ instruments is conducted nationwide in Korea. However, most in situ instruments in the market are expensive and require a time-consuming sample pretreatment step, which hinders the widespread use of in situ TN and TP monitoring. In this study, therefore, software sensors based on multiple-regression with a few easily in situ measurable water quality parameters were applied to estimate the TN and TP concentrations in a stream, a lake, combined sewer overflows (CSOs), and WWTP effluent. In general, the developed software sensors predicted TN and TP concentrations of the WWTP effluent and CSOs reasonably well. However, they showed relatively lower predictability for TN and TP concentrations of stream and lake waters, possibly because the water quality of stream and lake waters is more variable than that of WWTP effluent or CSOs. PMID:23307350

Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

USGS Publications Warehouse

Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

2015-01-01

The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

Parameter estimation for compact binary coalescence signals with the first generation gravitational-wave detector network

NASA Astrophysics Data System (ADS)

Aasi, J.; Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M.; Accadia, T.; Acernese, F.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Ajith, P.; Allen, B.; Allocca, A.; Amador Ceron, E.; Amariutei, D.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Ast, S.; Aston, S. M.; Astone, P.; Atkinson, D.; Aufmuth, P.; Aulbert, C.; Aylott, B. E.; Babak, S.; Baker, P.; Ballardin, G.; Ballmer, S.; Bao, Y.; Barayoga, J. C. B.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Bastarrika, M.; Basti, A.; Batch, J.; Bauchrowitz, J.; Bauer, Th. S.; Bebronne, M.; Beck, D.; Behnke, B.; Bejger, M.; Beker, M. G.; Bell, A. S.; Bell, C.; Belopolski, I.; Benacquista, M.; Berliner, J. M.; Bertolini, A.; Betzwieser, J.; Beveridge, N.; Beyersdorf, P. T.; Bhadbade, T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biswas, R.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Bland, B.; Blom, M.; Bock, O.; Bodiya, T. P.; Bogan, C.; Bond, C.; Bondarescu, R.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, S.; Bosi, L.; Bouhou, B.; Braccini, S.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Breyer, J.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Britzger, M.; Brooks, A. F.; Brown, D. A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Burguet–Castell, J.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Calloni, E.; Camp, J. B.; Campsie, P.; Cannon, K.; Canuel, B.; Cao, J.; Capano, C. D.; Carbognani, F.; Carbone, L.; Caride, S.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chalermsongsak, T.; Charlton, P.; Chassande-Mottin, E.; Chen, W.; Chen, X.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Chow, J.; Christensen, N.; Chua, S. S. Y.; Chung, C. T. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, D. E.; Clark, J. A.; Clayton, J. H.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colacino, C. N.; Colla, A.; Colombini, M.; Conte, A.; Conte, R.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M.; Coulon, J.-P.; Couvares, P.; Coward, D. M.; Cowart, M.; Coyne, D. C.; Creighton, J. D. E.; Creighton, T. D.; Cruise, A. M.; Cumming, A.; Cunningham, L.; Cuoco, E.; Cutler, R. M.; Dahl, K.; Damjanic, M.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dattilo, V.; Daudert, B.; Daveloza, H.; Davier, M.; Daw, E. J.; Dayanga, T.; De Rosa, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; Del Pozzo, W.; Dent, T.; Dergachev, V.; DeRosa, R.; Dhurandhar, S.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Paolo Emilio, M.; Di Virgilio, A.; Díaz, M.; Dietz, A.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorsher, S.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dumas, J.-C.; Dwyer, S.; Eberle, T.; Edgar, M.; Edwards, M.; Effler, A.; Ehrens, P.; Endrőczi, G.; Engel, R.; Etzel, T.; Evans, K.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Farr, B. F.; Farr, W. M.; Favata, M.; Fazi, D.; Fehrmann, H.; Feldbaum, D.; Feroz, F.; Ferrante, I.; Ferrini, F.; Fidecaro, F.; Finn, L. S.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Foley, S.; Forsi, E.; Forte, L. A.; Fotopoulos, N.; Fournier, J.-D.; Franc, J.; Franco, S.; Frasca, S.; Frasconi, F.; Frede, M.; Frei, M. A.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Friedrich, D.; Fritschel, P.; Frolov, V. V.; Fujimoto, M.-K.; Fulda, P. J.; Fyffe, M.; Gair, J.; Galimberti, M.; Gammaitoni, L.; Garcia, J.; Garufi, F.; Gáspár, M. E.; Gelencser, G.; Gemme, G.; Genin, E.; Gennai, A.; Gergely, L. Á.; Ghosh, S.; Giaime, J. A.; Giampanis, S.; Giardina, K. D.; Giazotto, A.; Gil-Casanova, S.; Gill, C.; Gleason, J.; Goetz, E.; González, G.; Gorodetsky, M. L.; Goßler, S.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gray, C.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Griffo, C.; Grote, H.; Grover, K.; Grunewald, S.; Guidi, G. M.; Guido, C.; Gupta, R.; Gustafson, E. K.; Gustafson, R.; Hallam, J. M.; Hammer, D.; Hammond, G.; Hanks, J.; Hanna, C.; Hanson, J.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Hayama, K.; Hayau, J.-F.; Heefner, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M. A.; Heng, I. S.; Heptonstall, A. W.; Herrera, V.; Heurs, M.; Hewitson, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Holt, K.; Holtrop, M.; Hong, T.; Hooper, S.; Hough, J.; Howell, E. J.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Ingram, D. R.; Inta, R.; Isogai, T.; Ivanov, A.; Izumi, K.; Jacobson, M.; James, E.; Jang, Y. J.; Jaranowski, P.; Jesse, E.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Kalmus, P.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kasprzack, M.; Kasturi, R.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kaufman, K.; Kawabe, K.; Kawamura, S.; Kawazoe, F.; Keitel, D.; Kelley, D.; Kells, W.; Keppel, D. G.; Keresztes, Z.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, B. K.; Kim, C.; Kim, H.; Kim, K.; Kim, N.; Kim, Y. M.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kline, J.; Kokeyama, K.; Kondrashov, V.; Koranda, S.; Korth, W. Z.; Kowalska, I.; Kozak, D.; Kringel, V.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kurdyumov, R.; Kwee, P.; Lam, P. K.; Landry, M.; Langley, A.; Lantz, B.; Lastzka, N.; Lawrie, C.; Lazzarini, A.; Le Roux, A.; Leaci, P.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Leong, J. R.; Leonor, I.; Leroy, N.; Letendre, N.; Lhuillier, V.; Li, J.; Li, T. G. F.; Lindquist, P. E.; Litvine, V.; Liu, Y.; Liu, Z.; Lockerbie, N. A.; Lodhia, D.; Logue, J.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Lubinski, M.; Lück, H.; Lundgren, A. P.; Macarthur, J.; Macdonald, E.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Mageswaran, M.; Mailand, K.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Marque, J.; Martelli, F.; Martin, I. W.; Martin, R. M.; Marx, J. N.; Mason, K.; Masserot, A.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McIntyre, G.; McIver, J.; Meadors, G. D.; Mehmet, M.; Meier, T.; Melatos, A.; Melissinos, A. C.; Mendell, G.; Menéndez, D. F.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyer, M. S.; Miao, H.; Michel, C.; Milano, L.; Miller, J.; Minenkov, Y.; Mingarelli, C. M. F.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moe, B.; Mohan, M.; Mohapatra, S. R. P.; Moraru, D.; Moreno, G.; Morgado, N.; Morgia, A.; Mori, T.; Morriss, S. R.; Mosca, S.; Mossavi, K.; Mours, B.; Mow–Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Müller-Ebhardt, H.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nash, T.; Naticchioni, L.; Necula, V.; Nelson, J.; Neri, I.; Newton, G.; Nguyen, T.; Nishizawa, A.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E.; Nuttall, L.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Oldenberg, R. G.; O'Reilly, B.; O'Shaughnessy, R.; Osthelder, C.; Ott, C. D.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Page, A.; Palladino, L.; Palomba, C.; Pan, Y.; Pankow, C.; Paoletti, F.; Paoletti, R.; Papa, M. A.; Parisi, M.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Pedraza, M.; Penn, S.; Perreca, A.; Persichetti, G.; Phelps, M.; Pichot, M.; Pickenpack, M.; Piergiovanni, F.; Pierro, V.; Pihlaja, M.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Pletsch, H. J.; Plissi, M. V.; Poggiani, R.; Pöld, J.; Postiglione, F.; Poux, C.; Prato, M.; Predoi, V.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Quetschke, V.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Rakhmanov, M.; Ramet, C.; Rankins, B.; Rapagnani, P.; Raymond, V.; Re, V.; Reed, C. M.; Reed, T.; Regimbau, T.; Reid, S.; Reitze, D. H.; Ricci, F.; Riesen, R.; Riles, K.; Roberts, M.; Robertson, N. A.; Robinet, F.; Robinson, C.; Robinson, E. L.; Rocchi, A.; Roddy, S.; Rodriguez, C.; Rodruck, M.; Rolland, L.; Rollins, J. G.; Romano, R.; Romie, J. H.; Rosińska, D.; Röver, C.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Salemi, F.; Sammut, L.; Sandberg, V.; Sankar, S.; Sannibale, V.; Santamaría, L.; Santiago-Prieto, I.; Santostasi, G.; Saracco, E.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Savage, R. L.; Schilling, R.; Schnabel, R.; Schofield, R. M. S.; Schulz, B.; Schutz, B. F.; Schwinberg, P.; Scott, J.; Scott, S. M.; Seifert, F.; Sellers, D.; Sentenac, D.; Sergeev, A.; Shaddock, D. A.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sidery, T. L.; Siemens, X.; Sigg, D.; Simakov, D.; Singer, A.; Singer, L.; Sintes, A. M.; Skelton, G. R.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M. R.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Somiya, K.; Sorazu, B.; Speirits, F. C.; Sperandio, L.; Stefszky, M.; Steinert, E.; Steinlechner, J.; Steinlechner, S.; Steplewski, S.; Stochino, A.; Stone, R.; Strain, K. A.; Strigin, S. E.; Stroeer, A. S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sung, M.; Susmithan, S.; Sutton, P. J.; Swinkels, B.; Szeifert, G.; Tacca, M.; Taffarello, L.; Talukder, D.; Tanner, D. B.; Tarabrin, S. P.; Taylor, R.; ter Braack, A. P. M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Thüring, A.; Titsler, C.; Tokmakov, K. V.; Tomlinson, C.; Toncelli, A.; Tonelli, M.; Torre, O.; Torres, C. V.; Torrie, C. I.; Tournefier, E.; Travasso, F.; Traylor, G.; Tse, M.; Ugolini, D.; Vahlbruch, H.; Vajente, G.; van den Brand, J. F. J.; Van Den Broeck, C.; van der Putten, S.; van Veggel, A. A.; Vass, S.; Vasuth, M.; Vaulin, R.; Vavoulidis, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Villar, A. E.; Vinet, J.-Y.; Vitale, S.; Vocca, H.; Vorvick, C.; Vyatchanin, S. P.; Wade, A.; Wade, L.; Wade, M.; Waldman, S. J.; Wallace, L.; Wan, Y.; Wang, M.; Wang, X.; Wanner, A.; Ward, R. L.; Was, M.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Wessels, P.; West, M.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S. E.; White, D. J.; Whiting, B. F.; Wiesner, K.; Wilkinson, C.; Willems, P. A.; Williams, L.; Williams, R.; Willke, B.; Wimmer, M.; Winkelmann, L.; Winkler, W.; Wipf, C. C.; Wiseman, A. G.; Wittel, H.; Woan, G.; Wooley, R.; Worden, J.; Yablon, J.; Yakushin, I.; Yamamoto, H.; Yamamoto, K.; Yancey, C. C.; Yang, H.; Yeaton-Massey, D.; Yoshida, S.; Yvert, M.; Zadrożny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, F.; Zhang, L.; Zhao, C.; Zotov, N.; Zucker, M. E.; Zweizig, J.

2013-09-01

Compact binary systems with neutron stars or black holes are one of the most promising sources for ground-based gravitational-wave detectors. Gravitational radiation encodes rich information about source physics; thus parameter estimation and model selection are crucial analysis steps for any detection candidate events. Detailed models of the anticipated waveforms enable inference on several parameters, such as component masses, spins, sky location and distance, that are essential for new astrophysical studies of these sources. However, accurate measurements of these parameters and discrimination of models describing the underlying physics are complicated by artifacts in the data, uncertainties in the waveform models and in the calibration of the detectors. Here we report such measurements on a selection of simulated signals added either in hardware or software to the data collected by the two LIGO instruments and the Virgo detector during their most recent joint science run, including a “blind injection” where the signal was not initially revealed to the collaboration. We exemplify the ability to extract information about the source physics on signals that cover the neutron-star and black-hole binary parameter space over the component mass range 1M⊙-25M⊙ and the full range of spin parameters. The cases reported in this study provide a snapshot of the status of parameter estimation in preparation for the operation of advanced detectors.

Estimation of the discharges of the multiple water level stations by multi-objective optimization

NASA Astrophysics Data System (ADS)

Matsumoto, Kazuhiro; Miyamoto, Mamoru; Yamakage, Yuzuru; Tsuda, Morimasa; Yanami, Hitoshi; Anai, Hirokazu; Iwami, Yoichi

2016-04-01

This presentation shows two aspects of the parameter identification to estimate the discharges of the multiple water level stations by multi-objective optimization. One is how to adjust the parameters to estimate the discharges accurately. The other is which optimization algorithms are suitable for the parameter identification. Regarding the previous studies, there is a study that minimizes the weighted error of the discharges of the multiple water level stations by single-objective optimization. On the other hand, there are some studies that minimize the multiple error assessment functions of the discharge of a single water level station by multi-objective optimization. This presentation features to simultaneously minimize the errors of the discharges of the multiple water level stations by multi-objective optimization. Abe River basin in Japan is targeted. The basin area is 567.0km2. There are thirteen rainfall stations and three water level stations. Nine flood events are investigated. They occurred from 2005 to 2012 and the maximum discharges exceed 1,000m3/s. The discharges are calculated with PWRI distributed hydrological model. The basin is partitioned into the meshes of 500m x 500m. Two-layer tanks are placed on each mesh. Fourteen parameters are adjusted to estimate the discharges accurately. Twelve of them are the hydrological parameters and two of them are the parameters of the initial water levels of the tanks. Three objective functions are the mean squared errors between the observed and calculated discharges at the water level stations. Latin Hypercube sampling is one of the uniformly sampling algorithms. The discharges are calculated with respect to the parameter values sampled by a simplified version of Latin Hypercube sampling. The observed discharge is surrounded by the calculated discharges. It suggests that it might be possible to estimate the discharge accurately by adjusting the parameters. In a sense, it is true that the discharge of a water level station can be accurately estimated by setting the parameter values optimized to the responding water level station. However, there are some cases that the calculated discharge by setting the parameter values optimized to one water level station does not meet the observed discharge at another water level station. It is important to estimate the discharges of all the water level stations in some degree of accuracy. It turns out to be possible to select the parameter values from the pareto optimal solutions by the condition that all the normalized errors by the minimum error of the responding water level station are under 3. The optimization performance of five implementations of the algorithms and a simplified version of Latin Hypercube sampling are compared. Five implementations are NSGA2 and PAES of an optimization software inspyred and MCO_NSGA2R, MOPSOCD and NSGA2R_NSGA2R of a statistical software R. NSGA2, PAES and MOPSOCD are the optimization algorithms of a genetic algorithm, an evolution strategy and a particle swarm optimization respectively. The number of the evaluations of the objective functions is 10,000. Two implementations of NSGA2 of R outperform the others. They are promising to be suitable for the parameter identification of PWRI distributed hydrological model.

Using Predictive Uncertainty Analysis to Assess Hydrologic Model Performance for a Watershed in Oregon

NASA Astrophysics Data System (ADS)

Brannan, K. M.; Somor, A.

2016-12-01

A variety of statistics are used to assess watershed model performance but these statistics do not directly answer the question: what is the uncertainty of my prediction. Understanding predictive uncertainty is important when using a watershed model to develop a Total Maximum Daily Load (TMDL). TMDLs are a key component of the US Clean Water Act and specify the amount of a pollutant that can enter a waterbody when the waterbody meets water quality criteria. TMDL developers use watershed models to estimate pollutant loads from nonpoint sources of pollution. We are developing a TMDL for bacteria impairments in a watershed in the Coastal Range of Oregon. We setup an HSPF model of the watershed and used the calibration software PEST to estimate HSPF hydrologic parameters and then perform predictive uncertainty analysis of stream flow. We used Monte-Carlo simulation to run the model with 1,000 different parameter sets and assess predictive uncertainty. In order to reduce the chance of specious parameter sets, we accounted for the relationships among parameter values by using mathematically-based regularization techniques and an estimate of the parameter covariance when generating random parameter sets. We used a novel approach to select flow data for predictive uncertainty analysis. We set aside flow data that occurred on days that bacteria samples were collected. We did not use these flows in the estimation of the model parameters. We calculated a percent uncertainty for each flow observation based 1,000 model runs. We also used several methods to visualize results with an emphasis on making the data accessible to both technical and general audiences. We will use the predictive uncertainty estimates in the next phase of our work, simulating bacteria fate and transport in the watershed.

Non-intrusive parameter identification procedure user's guide

NASA Technical Reports Server (NTRS)

Hanson, G. D.; Jewell, W. F.

1983-01-01

Written in standard FORTRAN, NAS is capable of identifying linear as well as nonlinear relations between input and output parameters; the only restriction is that the input/output relation be linear with respect to the unknown coefficients of the estimation equations. The output of the identification algorithm can be specified to be in either the time domain (i.e., the estimation equation coefficients) or in the frequency domain (i.e., a frequency response of the estimation equation). The frame length ("window") over which the identification procedure is to take place can be specified to be any portion of the input time history, thereby allowing the freedom to start and stop the identification procedure within a time history. There also is an option which allows a sliding window, which gives a moving average over the time history. The NAS software also includes the ability to identify several assumed solutions simultaneously for the same or different input data.

Electron Beam Lithography Double Step Exposure Technique for Fabrication of Mushroom-Like Profile in Bilayer Resist System

NASA Astrophysics Data System (ADS)

Kornelia, Indykiewicz; Bogdan, Paszkiewicz; Tomasz, Szymański; Regina, Paszkiewicz

2015-01-01

The Hi/Lo bilayer resist system exposure in e-beam lithography (EBL) process, intended for mushroom-like profile fabrication, was studied. Different exposure parameters and theirs influence on the resist layers were simulated in CASINO software and the obtained results were compared with the experimental data. The AFM technique was used for the estimation of the e-beam penetration depth in the resist stack. Performed numerical and experimental results allow us to establish the useful ranges of the exposure parameters.

DEM Calibration Approach: design of experiment

NASA Astrophysics Data System (ADS)

Boikov, A. V.; Savelev, R. V.; Payor, V. A.

2018-05-01

The problem of DEM models calibration is considered in the article. It is proposed to divide models input parameters into those that require iterative calibration and those that are recommended to measure directly. A new method for model calibration based on the design of the experiment for iteratively calibrated parameters is proposed. The experiment is conducted using a specially designed stand. The results are processed with technical vision algorithms. Approximating functions are obtained and the error of the implemented software and hardware complex is estimated. The prospects of the obtained results are discussed.

A generic open-source software framework supporting scenario simulations in bioterrorist crises.

PubMed

Falenski, Alexander; Filter, Matthias; Thöns, Christian; Weiser, Armin A; Wigger, Jan-Frederik; Davis, Matthew; Douglas, Judith V; Edlund, Stefan; Hu, Kun; Kaufman, James H; Appel, Bernd; Käsbohrer, Annemarie

2013-09-01

Since the 2001 anthrax attack in the United States, awareness of threats originating from bioterrorism has grown. This led internationally to increased research efforts to improve knowledge of and approaches to protecting human and animal populations against the threat from such attacks. A collaborative effort in this context is the extension of the open-source Spatiotemporal Epidemiological Modeler (STEM) simulation and modeling software for agro- or bioterrorist crisis scenarios. STEM, originally designed to enable community-driven public health disease models and simulations, was extended with new features that enable integration of proprietary data as well as visualization of agent spread along supply and production chains. STEM now provides a fully developed open-source software infrastructure supporting critical modeling tasks such as ad hoc model generation, parameter estimation, simulation of scenario evolution, estimation of effects of mitigation or management measures, and documentation. This open-source software resource can be used free of charge. Additionally, STEM provides critical features like built-in worldwide data on administrative boundaries, transportation networks, or environmental conditions (eg, rainfall, temperature, elevation, vegetation). Users can easily combine their own confidential data with built-in public data to create customized models of desired resolution. STEM also supports collaborative and joint efforts in crisis situations by extended import and export functionalities. In this article we demonstrate specifically those new software features implemented to accomplish STEM application in agro- or bioterrorist crisis scenarios.

Engineering Margin Factors Used in the Design of the VVER Fuel Cycles

NASA Astrophysics Data System (ADS)

Lizorkin, M. P.; Shishkov, L. K.

2017-12-01

The article describes methods for determination of the engineering margin factors currently used to estimate the uncertainties of the VVER reactor design parameters calculated via the KASKAD software package developed at the National Research Center Kurchatov Institute. These margin factors ensure the meeting of the operating (design) limits and a number of other restrictions under normal operating conditions.

Arc Habitat Suitability Index computer software

Treesearch

Thomas M. Juntti; Mark A. Rumble

2006-01-01

This user manual describes the Arc Habitat Suitability Index (ArcHSI), which is a geographical information system (GIS) model that estimates the ability of an area to meet the food and cover requirements of an animal species. The components and parameters of the model occur in tables and can be easily edited or otherwise modified. ArcHSI runs on personal computers with...

Myokit: A simple interface to cardiac cellular electrophysiology.

PubMed

Clerx, Michael; Collins, Pieter; de Lange, Enno; Volders, Paul G A

2016-01-01

Myokit is a new powerful and versatile software tool for modeling and simulation of cardiac cellular electrophysiology. Myokit consists of an easy-to-read modeling language, a graphical user interface, single and multi-cell simulation engines and a library of advanced analysis tools accessible through a Python interface. Models can be loaded from Myokit's native file format or imported from CellML. Model export is provided to C, MATLAB, CellML, CUDA and OpenCL. Patch-clamp data can be imported and used to estimate model parameters. In this paper, we review existing tools to simulate the cardiac cellular action potential to find that current tools do not cater specifically to model development and that there is a gap between easy-to-use but limited software and powerful tools that require strong programming skills from their users. We then describe Myokit's capabilities, focusing on its model description language, simulation engines and import/export facilities in detail. Using three examples, we show how Myokit can be used for clinically relevant investigations, multi-model testing and parameter estimation in Markov models, all with minimal programming effort from the user. This way, Myokit bridges a gap between performance, versatility and user-friendliness. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computational Software to Fit Seismic Data Using Epidemic-Type Aftershock Sequence Models and Modeling Performance Comparisons

NASA Astrophysics Data System (ADS)

Chu, A.

2016-12-01

Modern earthquake catalogs are often analyzed using spatial-temporal point process models such as the epidemic-type aftershock sequence (ETAS) models of Ogata (1998). My work implements three of the homogeneous ETAS models described in Ogata (1998). With a model's log-likelihood function, my software finds the Maximum-Likelihood Estimates (MLEs) of the model's parameters to estimate the homogeneous background rate and the temporal and spatial parameters that govern triggering effects. EM-algorithm is employed for its advantages of stability and robustness (Veen and Schoenberg, 2008). My work also presents comparisons among the three models in robustness, convergence speed, and implementations from theory to computing practice. Up-to-date regional seismic data of seismic active areas such as Southern California and Japan are used to demonstrate the comparisons. Data analysis has been done using computer languages Java and R. Java has the advantages of being strong-typed and easiness of controlling memory resources, while R has the advantages of having numerous available functions in statistical computing. Comparisons are also made between the two programming languages in convergence and stability, computational speed, and easiness of implementation. Issues that may affect convergence such as spatial shapes are discussed.

Foreign Object Damage Identification in Turbine Engines

NASA Technical Reports Server (NTRS)

Strack, William; Zhang, Desheng; Turso, James; Pavlik, William; Lopez, Isaac

2005-01-01

This report summarizes the collective work of a five-person team from different organizations examining the problem of detecting foreign object damage (FOD) events in turbofan engines from gas path thermodynamic and bearing accelerometer sensors, and determining the severity of damage to each component (diagnosis). Several detection and diagnostic approaches were investigated and a software tool (FODID) was developed to assist researchers detect/diagnose FOD events. These approaches include (1) fan efficiency deviation computed from upstream and downstream temperature/ pressure measurements, (2) gas path weighted least squares estimation of component health parameter deficiencies, (3) Kalman filter estimation of component health parameters, and (4) use of structural vibration signal processing to detect both large and small FOD events. The last three of these approaches require a significant amount of computation in conjunction with a physics-based analytic model of the underlying phenomenon the NPSS thermodynamic cycle code for approaches 1 to 3 and the DyRoBeS reduced-order rotor dynamics code for approach 4. A potential application of the FODID software tool, in addition to its detection/diagnosis role, is using its sensitivity results to help identify the best types of sensors and their optimum locations within the gas path, and similarly for bearing accelerometers.

Practical Methods for Estimating Software Systems Fault Content and Location

NASA Technical Reports Server (NTRS)

Nikora, A.; Schneidewind, N.; Munson, J.

1999-01-01

Over the past several years, we have developed techniques to discriminate between fault-prone software modules and those that are not, to estimate a software system's residual fault content, to identify those portions of a software system having the highest estimated number of faults, and to estimate the effects of requirements changes on software quality.

Differences between the most used equations in BAT-human studies to estimate parameters of skin temperature in young lean men.

PubMed

Martinez-Tellez, Borja; Sanchez-Delgado, Guillermo; Acosta, Francisco M; Alcantara, Juan M A; Boon, Mariëtte R; Rensen, Patrick C N; Ruiz, Jonatan R

2017-09-05

Cold exposure is necessary to activate human brown adipose tissue (BAT), resulting in heat production. Skin temperature is an indirect measure to monitor the body's reaction to cold. The aim of this research was to study whether the most used equations to estimate parameters of skin temperature in BAT-human studies measure the same values of temperature in young lean men (n = 11: 23.4 ± 0.5 years, fat mass: 19.9 ± 1.2%). Skin temperature was measured with 26 ibuttons at 1-minute intervals in warm and cold room conditions. We used 12 equations to estimate parameters of mean, proximal, and distal skin temperature as well as skin temperature gradients. Data were analysed with Temperatus software. Significant differences were found across equations to measure the same parameters of skin temperature in warm and cold room conditions, hampering comparison across studies. Based on these findings, we suggest to use a set of 14 ibuttons at anatomical positions reported by ISO STANDARD 9886:2004 plus five ibuttons placed on the right supraclavicular fossa, right middle clavicular bone, right middle upper forearm, right top of forefinger, and right upper chest.

Dynamic modeling of lactic acid fermentation metabolism with Lactococcus lactis.

PubMed

Oh, Euhlim; Lu, Mingshou; Park, Changhun; Park, Changhun; Oh, Han Bin; Lee, Sang Yup; Lee, Jinwon

2011-02-01

A dynamic model of lactic acid fermentation using Lactococcus lactis was constructed, and a metabolic flux analysis (MFA) and metabolic control analysis (MCA) were performed to reveal an intensive metabolic understanding of lactic acid bacteria (LAB). The parameter estimation was conducted with COPASI software to construct a more accurate metabolic model. The experimental data used in the parameter estimation were obtained from an LC-MS/ MS analysis and time-course simulation study. The MFA results were a reasonable explanation of the experimental data. Through the parameter estimation, the metabolic system of lactic acid bacteria can be thoroughly understood through comparisons with the original parameters. The coefficients derived from the MCA indicated that the reaction rate of L-lactate dehydrogenase was activated by fructose 1,6-bisphosphate and pyruvate, and pyruvate appeared to be a stronger activator of L-lactate dehydrogenase than fructose 1,6-bisphosphate. Additionally, pyruvate acted as an inhibitor to pyruvate kinase and the phosphotransferase system. Glucose 6-phosphate and phosphoenolpyruvate showed activation effects on pyruvate kinase. Hexose transporter was the strongest effector on the flux through L-lactate dehydrogenase. The concentration control coefficient (CCC) showed similar results to the flux control coefficient (FCC).

Unresolved Galaxy Classifier for ESA/Gaia mission: Support Vector Machines approach

NASA Astrophysics Data System (ADS)

Bellas-Velidis, Ioannis; Kontizas, Mary; Dapergolas, Anastasios; Livanou, Evdokia; Kontizas, Evangelos; Karampelas, Antonios

A software package Unresolved Galaxy Classifier (UGC) is being developed for the ground-based pipeline of ESA's Gaia mission. It aims to provide an automated taxonomic classification and specific parameters estimation analyzing Gaia BP/RP instrument low-dispersion spectra of unresolved galaxies. The UGC algorithm is based on a supervised learning technique, the Support Vector Machines (SVM). The software is implemented in Java as two separate modules. An offline learning module provides functions for SVM-models training. Once trained, the set of models can be repeatedly applied to unknown galaxy spectra by the pipeline's application module. A library of galaxy models synthetic spectra, simulated for the BP/RP instrument, is used to train and test the modules. Science tests show a very good classification performance of UGC and relatively good regression performance, except for some of the parameters. Possible approaches to improve the performance are discussed.

An expert system for prediction of chemical toxicity

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino-Reader, Dora R.; Frank, Anthony M.

1992-01-01

The National Fisheries Research Center- Great Lakes has developed an interactive computer program that uses the structure of an organic molecule to predict its acute toxicity to four aquatic species. The expert system software, written in the muLISP language, identifies the skeletal structures and substituent groups of an organic molecule from a user-supplied standard chemical notation known as a SMILES string, and then generates values for four solvatochromic parameters. Multiple regression equations relate these parameters to the toxicities (expressed as log10LC50s and log10EC50s, along with 95% confidence intervals) for four species. The system is demonstrated by prediction of toxicity for anilide-type pesticides to the fathead minnow (Pimephales promelas). This software is designed for use on an IBM-compatible personal computer by personnel with minimal toxicology background for rapid estimation of chemical toxicity. The system has numerous applications, with much potential for use in the pharmaceutical industry

Computational tools for multi-linked flexible structures

NASA Technical Reports Server (NTRS)

Lee, Gordon K. F.; Brubaker, Thomas A.; Shults, James R.

1990-01-01

A software module which designs and tests controllers and filters in Kalman Estimator form, based on a polynomial state-space model is discussed. The user-friendly program employs an interactive graphics approach to simplify the design process. A variety of input methods are provided to test the effectiveness of the estimator. Utilities are provided which address important issues in filter design such as graphical analysis, statistical analysis, and calculation time. The program also provides the user with the ability to save filter parameters, inputs, and outputs for future use.

Working covariance model selection for generalized estimating equations.

PubMed

Carey, Vincent J; Wang, You-Gan

2011-11-20

We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice. Copyright © 2011 John Wiley & Sons, Ltd.

Approaches to highly parameterized inversion-A guide to using PEST for groundwater-model calibration

USGS Publications Warehouse

Doherty, John E.; Hunt, Randall J.

2010-01-01

Highly parameterized groundwater models can create calibration difficulties. Regularized inversion-the combined use of large numbers of parameters with mathematical approaches for stable parameter estimation-is becoming a common approach to address these difficulties and enhance the transfer of information contained in field measurements to parameters used to model that system. Though commonly used in other industries, regularized inversion is somewhat imperfectly understood in the groundwater field. There is concern that this unfamiliarity can lead to underuse, and misuse, of the methodology. This document is constructed to facilitate the appropriate use of regularized inversion for calibrating highly parameterized groundwater models. The presentation is directed at an intermediate- to advanced-level modeler, and it focuses on the PEST software suite-a frequently used tool for highly parameterized model calibration and one that is widely supported by commercial graphical user interfaces. A brief overview of the regularized inversion approach is provided, and techniques for mathematical regularization offered by PEST are outlined, including Tikhonov, subspace, and hybrid schemes. Guidelines for applying regularized inversion techniques are presented after a logical progression of steps for building suitable PEST input. The discussion starts with use of pilot points as a parameterization device and processing/grouping observations to form multicomponent objective functions. A description of potential parameter solution methodologies and resources available through the PEST software and its supporting utility programs follows. Directing the parameter-estimation process through PEST control variables is then discussed, including guidance for monitoring and optimizing the performance of PEST. Comprehensive listings of PEST control variables, and of the roles performed by PEST utility support programs, are presented in the appendixes.

Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

NASA Technical Reports Server (NTRS)

Rizvi, Farheen

2016-01-01

Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

Recommended Parameter Values for GENII Modeling of Radionuclides in Routine Air and Water Releases

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

Snyder, Sandra F.; Arimescu, Carmen; Napier, Bruce A.

The GENII v2 code is used to estimate dose to individuals or populations from the release of radioactive materials into air or water. Numerous parameter values are required for input into this code. User-defined parameters cover the spectrum from chemical data, meteorological data, agricultural data, and behavioral data. This document is a summary of parameter values that reflect conditions in the United States. Reasonable regional and age-dependent data is summarized. Data availability and quality varies. The set of parameters described address scenarios for chronic air emissions or chronic releases to public waterways. Considerations for the special tritium and carbon-14 modelsmore » are briefly addressed. GENIIv2.10.0 is the current software version that this document supports.« less

Engine structures analysis software: Component Specific Modeling (COSMO)

NASA Astrophysics Data System (ADS)

McKnight, R. L.; Maffeo, R. J.; Schwartz, S.

1994-08-01

A component specific modeling software program has been developed for propulsion systems. This expert program is capable of formulating the component geometry as finite element meshes for structural analysis which, in the future, can be spun off as NURB geometry for manufacturing. COSMO currently has geometry recipes for combustors, turbine blades, vanes, and disks. Component geometry recipes for nozzles, inlets, frames, shafts, and ducts are being added. COSMO uses component recipes that work through neutral files with the Technology Benefit Estimator (T/BEST) program which provides the necessary base parameters and loadings. This report contains the users manual for combustors, turbine blades, vanes, and disks.

Engine Structures Analysis Software: Component Specific Modeling (COSMO)

NASA Technical Reports Server (NTRS)

Mcknight, R. L.; Maffeo, R. J.; Schwartz, S.

1994-01-01

A component specific modeling software program has been developed for propulsion systems. This expert program is capable of formulating the component geometry as finite element meshes for structural analysis which, in the future, can be spun off as NURB geometry for manufacturing. COSMO currently has geometry recipes for combustors, turbine blades, vanes, and disks. Component geometry recipes for nozzles, inlets, frames, shafts, and ducts are being added. COSMO uses component recipes that work through neutral files with the Technology Benefit Estimator (T/BEST) program which provides the necessary base parameters and loadings. This report contains the users manual for combustors, turbine blades, vanes, and disks.

Relative azimuth inversion by way of damped maximum correlation estimates

USGS Publications Warehouse

Ringler, A.T.; Edwards, J.D.; Hutt, C.R.; Shelly, F.

2012-01-01

Horizontal seismic data are utilized in a large number of Earth studies. Such work depends on the published orientations of the sensitive axes of seismic sensors relative to true North. These orientations can be estimated using a number of different techniques: SensOrLoc (Sensitivity, Orientation and Location), comparison to synthetics (Ekstrom and Busby, 2008), or by way of magnetic compass. Current methods for finding relative station azimuths are unable to do so with arbitrary precision quickly because of limitations in the algorithms (e.g. grid search methods). Furthermore, in order to determine instrument orientations during station visits, it is critical that any analysis software be easily run on a large number of different computer platforms and the results be obtained quickly while on site. We developed a new technique for estimating relative sensor azimuths by inverting for the orientation with the maximum correlation to a reference instrument, using a non-linear parameter estimation routine. By making use of overlapping windows, we are able to make multiple azimuth estimates, which helps to identify the confidence of our azimuth estimate, even when the signal-to-noise ratio (SNR) is low. Finally, our algorithm has been written as a stand-alone, platform independent, Java software package with a graphical user interface for reading and selecting data segments to be analyzed.

Efficient QR sequential least square algorithm for high frequency GNSS precise point positioning seismic application

NASA Astrophysics Data System (ADS)

Barbu, Alina L.; Laurent-Varin, Julien; Perosanz, Felix; Mercier, Flavien; Marty, Jean-Charles

2018-01-01

The implementation into the GINS CNES geodetic software of a more efficient filter was needed to satisfy the users who wanted to compute high-rate GNSS PPP solutions. We selected the SRI approach and a QR factorization technique including an innovative algorithm which optimizes the matrix reduction step. A full description of this algorithm is given for future users. The new capacities of the software have been tested using a set of 1 Hz data from the Japanese GEONET network including the Mw 9.0 2011 Tohoku earthquake. Station coordinates solution agreed at a sub-decimeter level with previous publications as well as with solutions we computed with the National Resource Canada software. An additional benefit from the implementation of the SRI filter is the capability to estimate high-rate tropospheric parameters too. As the CPU time to estimate a 1 Hz kinematic solution from 1 h of data is now less than 1 min we could produced series of coordinates for the full 1300 stations of the Japanese network. The corresponding movie shows the impressive co-seismic deformation as well as the wave propagation along the island. The processing was straightforward using a cluster of PCs which illustrates the new potentiality of the GINS software for massive network high rate PPP processing.

Observation model and parameter partials for the JPL VLBI parameter estimation software MASTERFIT-1987

NASA Technical Reports Server (NTRS)

Sovers, O. J.; Fanselow, J. L.

1987-01-01

This report is a revision of the document of the same title (1986), dated August 1, which it supersedes. Model changes during 1986 and 1987 included corrections for antenna feed rotation, refraction in modelling antenna axis offsets, and an option to employ improved values of the semiannual and annual nutation amplitudes. Partial derivatives of the observables with respect to an additional parameter (surface temperature) are now available. New versions of two figures representing the geometric delay are incorporated. The expressions for the partial derivatives with respect to the nutation parameters have been corrected to include contributions from the dependence of UTI on nutation. The authors hope to publish revisions of this document in the future, as modeling improvements warrant.

Observation model and parameter partials for the JPL VLBI parameter estimation software MASTERFIT-1987

NASA Astrophysics Data System (ADS)

Sovers, O. J.; Fanselow, J. L.

1987-12-01

This report is a revision of the document of the same title (1986), dated August 1, which it supersedes. Model changes during 1986 and 1987 included corrections for antenna feed rotation, refraction in modelling antenna axis offsets, and an option to employ improved values of the semiannual and annual nutation amplitudes. Partial derivatives of the observables with respect to an additional parameter (surface temperature) are now available. New versions of two figures representing the geometric delay are incorporated. The expressions for the partial derivatives with respect to the nutation parameters have been corrected to include contributions from the dependence of UTI on nutation. The authors hope to publish revisions of this document in the future, as modeling improvements warrant.

Estimating stage-specific daily survival probabilities of nests when nest age is unknown

USGS Publications Warehouse

Stanley, T.R.

2004-01-01

Estimation of daily survival probabilities of nests is common in studies of avian populations. Since the introduction of Mayfield's (1961, 1975) estimator, numerous models have been developed to relax Mayfield's assumptions and account for biologically important sources of variation. Stanley (2000) presented a model for estimating stage-specific (e.g. incubation stage, nestling stage) daily survival probabilities of nests that conditions on “nest type” and requires that nests be aged when they are found. Because aging nests typically requires handling the eggs, there may be situations where nests can not or should not be aged and the Stanley (2000) model will be inapplicable. Here, I present a model for estimating stage-specific daily survival probabilities that conditions on nest stage for active nests, thereby obviating the need to age nests when they are found. Specifically, I derive the maximum likelihood function for the model, evaluate the model's performance using Monte Carlo simulations, and provide software for estimating parameters (along with an example). For sample sizes as low as 50 nests, bias was small and confidence interval coverage was close to the nominal rate, especially when a reduced-parameter model was used for estimation.

Hierarchical models and Bayesian analysis of bird survey information

USGS Publications Warehouse

Sauer, J.R.; Link, W.A.; Royle, J. Andrew; Ralph, C. John; Rich, Terrell D.

2005-01-01

Summary of bird survey information is a critical component of conservation activities, but often our summaries rely on statistical methods that do not accommodate the limitations of the information. Prioritization of species requires ranking and analysis of species by magnitude of population trend, but often magnitude of trend is a misleading measure of actual decline when trend is poorly estimated. Aggregation of population information among regions is also complicated by varying quality of estimates among regions. Hierarchical models provide a reasonable means of accommodating concerns about aggregation and ranking of quantities of varying precision. In these models the need to consider multiple scales is accommodated by placing distributional assumptions on collections of parameters. For collections of species trends, this allows probability statements to be made about the collections of species-specific parameters, rather than about the estimates. We define and illustrate hierarchical models for two commonly encountered situations in bird conservation: (1) Estimating attributes of collections of species estimates, including ranking of trends, estimating number of species with increasing populations, and assessing population stability with regard to predefined trend magnitudes; and (2) estimation of regional population change, aggregating information from bird surveys over strata. User-friendly computer software makes hierarchical models readily accessible to scientists.

Software forecasting as it is really done: A study of JPL software engineers

NASA Technical Reports Server (NTRS)

Griesel, Martha Ann; Hihn, Jairus M.; Bruno, Kristin J.; Fouser, Thomas J.; Tausworthe, Robert C.

1993-01-01

This paper presents a summary of the results to date of a Jet Propulsion Laboratory internally funded research task to study the costing process and parameters used by internally recognized software cost estimating experts. Protocol Analysis and Markov process modeling were used to capture software engineer's forecasting mental models. While there is significant variation between the mental models that were studied, it was nevertheless possible to identify a core set of cost forecasting activities, and it was also found that the mental models cluster around three forecasting techniques. Further partitioning of the mental models revealed clustering of activities, that is very suggestive of a forecasting lifecycle. The different forecasting methods identified were based on the use of multiple-decomposition steps or multiple forecasting steps. The multiple forecasting steps involved either forecasting software size or an additional effort forecast. Virtually no subject used risk reduction steps in combination. The results of the analysis include: the identification of a core set of well defined costing activities, a proposed software forecasting life cycle, and the identification of several basic software forecasting mental models. The paper concludes with a discussion of the implications of the results for current individual and institutional practices.

Optimal Model-Based Fault Estimation and Correction for Particle Accelerators and Industrial Plants Using Combined Support Vector Machines and First Principles Models

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

Sayyar-Rodsari, Bijan; Schweiger, Carl; /SLAC /Pavilion Technologies, Inc., Austin, TX

2010-08-25

Timely estimation of deviations from optimal performance in complex systems and the ability to identify corrective measures in response to the estimated parameter deviations has been the subject of extensive research over the past four decades. The implications in terms of lost revenue from costly industrial processes, operation of large-scale public works projects and the volume of the published literature on this topic clearly indicates the significance of the problem. Applications range from manufacturing industries (integrated circuits, automotive, etc.), to large-scale chemical plants, pharmaceutical production, power distribution grids, and avionics. In this project we investigated a new framework for buildingmore » parsimonious models that are suited for diagnosis and fault estimation of complex technical systems. We used Support Vector Machines (SVMs) to model potentially time-varying parameters of a First-Principles (FP) description of the process. The combined SVM & FP model was built (i.e. model parameters were trained) using constrained optimization techniques. We used the trained models to estimate faults affecting simulated beam lifetime. In the case where a large number of process inputs are required for model-based fault estimation, the proposed framework performs an optimal nonlinear principal component analysis of the large-scale input space, and creates a lower dimension feature space in which fault estimation results can be effectively presented to the operation personnel. To fulfill the main technical objectives of the Phase I research, our Phase I efforts have focused on: (1) SVM Training in a Combined Model Structure - We developed the software for the constrained training of the SVMs in a combined model structure, and successfully modeled the parameters of a first-principles model for beam lifetime with support vectors. (2) Higher-order Fidelity of the Combined Model - We used constrained training to ensure that the output of the SVM (i.e. the parameters of the beam lifetime model) are physically meaningful. (3) Numerical Efficiency of the Training - We investigated the numerical efficiency of the SVM training. More specifically, for the primal formulation of the training, we have developed a problem formulation that avoids the linear increase in the number of the constraints as a function of the number of data points. (4) Flexibility of Software Architecture - The software framework for the training of the support vector machines was designed to enable experimentation with different solvers. We experimented with two commonly used nonlinear solvers for our simulations. The primary application of interest for this project has been the sustained optimal operation of particle accelerators at the Stanford Linear Accelerator Center (SLAC). Particle storage rings are used for a variety of applications ranging from 'colliding beam' systems for high-energy physics research to highly collimated x-ray generators for synchrotron radiation science. Linear accelerators are also used for collider research such as International Linear Collider (ILC), as well as for free electron lasers, such as the Linear Coherent Light Source (LCLS) at SLAC. One common theme in the operation of storage rings and linear accelerators is the need to precisely control the particle beams over long periods of time with minimum beam loss and stable, yet challenging, beam parameters. We strongly believe that beyond applications in particle accelerators, the high fidelity and cost benefits of a combined model-based fault estimation/correction system will attract customers from a wide variety of commercial and scientific industries. Even though the acquisition of Pavilion Technologies, Inc. by Rockwell Automation Inc. in 2007 has altered the small business status of the Pavilion and it no longer qualifies for a Phase II funding, our findings in the course of the Phase I research have convinced us that further research will render a workable model-based fault estimation and correction for particle accelerators and industrial plants feasible.« less

Assuring Software Cost Estimates: Is it an Oxymoron?

NASA Technical Reports Server (NTRS)

Hihn, Jarius; Tregre, Grant

2013-01-01

The software industry repeatedly observes cost growth of well over 100% even after decades of cost estimation research and well-known best practices, so "What's the problem?" In this paper we will provide an overview of the current state oj software cost estimation best practice. We then explore whether applying some of the methods used in software assurance might improve the quality of software cost estimates. This paper especially focuses on issues associated with model calibration, estimate review, and the development and documentation of estimates as part alan integrated plan.

Galactic and extragalactic hydrogen in the X-ray spectra of Gamma Ray Bursts

NASA Astrophysics Data System (ADS)

Rácz, I. I.; Bagoly, Z.; Tóth, L. V.; Balázs, L. G.; Horváth, I.; Pintér, S.

2017-07-01

Two types of emission can be observed from gamma-ray bursts (GRBs): the prompt emission from the central engine which can be observed in gamma or X-ray (as a low energy tail) and the afterglow from the environment in X-ray and at shorter frequencies. We examined the Swift XRT spectra with the XSPEC software. The correct estimation of the galactic interstellar medium is very important because we observe the host emission together with the galactic hydrogen absorption. We found that the estimated intrinsic hydrogen column density and the X-ray flux depend heavily on the redshift and the galactic foreground hydrogen. We also found that the initial parameters of the iteration and the cosmological parameters did not have much effect on the fitting result.

A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

PubMed

Karabatsos, George

2017-02-01

Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected functionals and values of covariates. The software is illustrated through the BNP regression analysis of real data.

Evaluation of Statistical Methodologies Used in U. S. Army Ordnance and Explosive Work

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

Ostrouchov, G

2000-02-14

Oak Ridge National Laboratory was tasked by the U.S. Army Engineering and Support Center (Huntsville, AL) to evaluate the mathematical basis of existing software tools used to assist the Army with the characterization of sites potentially contaminated with unexploded ordnance (UXO). These software tools are collectively known as SiteStats/GridStats. The first purpose of the software is to guide sampling of underground anomalies to estimate a site's UXO density. The second purpose is to delineate areas of homogeneous UXO density that can be used in the formulation of response actions. It was found that SiteStats/GridStats does adequately guide the sampling somore » that the UXO density estimator for a sector is unbiased. However, the software's techniques for delineation of homogeneous areas perform less well than visual inspection, which is frequently used to override the software in the overall sectorization methodology. The main problems with the software lie in the criteria used to detect nonhomogeneity and those used to recommend the number of homogeneous subareas. SiteStats/GridStats is not a decision-making tool in the classical sense. Although it does provide information to decision makers, it does not require a decision based on that information. SiteStats/GridStats provides information that is supplemented by visual inspections, land-use plans, and risk estimates prior to making any decisions. Although the sector UXO density estimator is unbiased regardless of UXO density variation within a sector, its variability increases with increased sector density variation. For this reason, the current practice of visual inspection of individual sampled grid densities (as provided by Site-Stats/GridStats) is necessary to ensure approximate homogeneity, particularly at sites with medium to high UXO density. Together with Site-Stats/GridStats override capabilities, this provides a sufficient mechanism for homogeneous sectorization and thus yields representative UXO density estimates. Objections raised by various parties to the use of a numerical ''discriminator'' in SiteStats/GridStats were likely because of the fact that the concerned statistical technique is customarily applied for a different purpose and because of poor documentation. The ''discriminator'', in Site-Stats/GridStats is a ''tuning parameter'' for the sampling process, and it affects the precision of the grid density estimates through changes in required sample size. It is recommended that sector characterization in terms of a map showing contour lines of constant UXO density with an expressed uncertainty or confidence level is a better basis for remediation decisions than a sector UXO density point estimate. A number of spatial density estimation techniques could be adapted to the UXO density estimation problem.« less

Free software for performing physical analysis of systems for digital radiography and mammography.

PubMed

Donini, Bruno; Rivetti, Stefano; Lanconelli, Nico; Bertolini, Marco

2014-05-01

In this paper, the authors present a free software for assisting users in achieving the physical characterization of x-ray digital systems and image quality checks. The program was developed as a plugin of a well-known public-domain suite ImageJ. The software can assist users in calculating various physical parameters such as the response curve (also termed signal transfer property), modulation transfer function (MTF), noise power spectra (NPS), and detective quantum efficiency (DQE). It also includes the computation of some image quality checks: defective pixel analysis, uniformity, dark analysis, and lag. The software was made available in 2009 and has been used during the last couple of years by many users who gave us valuable feedback for improving its usability. It was tested for achieving the physical characterization of several clinical systems for digital radiography and mammography. Various published papers made use of the outcomes of the plugin. This software is potentially beneficial to a variety of users: physicists working in hospitals, staff working in radiological departments, such as medical physicists, physicians, engineers. The plugin, together with a brief user manual, are freely available and can be found online (www.medphys.it/downloads.htm). With our plugin users can estimate all three most important parameters used for physical characterization (MTF, NPS, and also DQE). The plugin can run on any operating system equipped with ImageJ suite. The authors validated the software by comparing MTF and NPS curves on a common set of images with those obtained with other dedicated programs, achieving a very good agreement.

Estimation of Stability and Control Derivatives of an F-15

NASA Technical Reports Server (NTRS)

Smith, Mark; Moes, Tim

2006-01-01

A technique for real-time estimation of stability and control derivatives (derivatives of moment coefficients with respect to control-surface deflection angles) was used to support a flight demonstration of a concept of an indirect-adaptive intelligent flight control system (IFCS). Traditionally, parameter identification, including estimation of stability and control derivatives, is done post-flight. However, for the indirect-adaptive IFCS concept, parameter identification is required during flight so that the system can modify control laws for a damaged aircraft. The flight demonstration was carried out on a highly modified F-15 airplane (see Figure 1). The main objective was to estimate the stability and control derivatives of the airplane in nearly real time. A secondary goal was to develop a system to automatically assess the quality of the results, so as to be able to tell a learning neural network which data to use. Parameter estimation was performed by use of Fourier-transform regression (FTR) a technique developed at NASA Langley Research Center. FTR is an equation- error technique that operates in the frequency domain. Data are put into the frequency domain by use of a recursive Fourier transform for a discrete frequency set. This calculation simplifies many subsequent calculations, removes biases, and automatically filters out data beyond the chosen frequency range. FTR as applied here was tailored to work with pilot inputs, which produce correlated surface positions that prevent accurate parameter estimates, by replacing half the derivatives with predicted values. FTR was also set up to work only on a recent window of data, to accommodate changes in flight condition. A system of confidence measures was developed to identify quality-parameter estimates that a learning neural network could use. This system judged the estimates primarily on the basis of their estimated variances and of the level of aircraft response. The resulting FTR system was implemented in the Simulink software system and auto-coded in the C programming language for use on the Airborne Research Test System (ARTS II) computer installed in the F-15 airplane. The Simulink model was also used in a control room that utilizes the Ring Buffered Network Bus hardware and software, making it possible to evaluate test points during flights. In-flight parameter estimation was done for piloted and automated maneuvers, primarily at three test conditions. Figure 2 shows results for pitching moment due to symmetric stabilator actuations for a series of three pitch doublet maneuvers (in a doublet maneuver, a command to change attitude in a given direction by a given amount is followed immediately by a command to change attitude in the opposite direction by the same amount). A time window of 5 seconds was used. The portions of the curves shown in red are those that passed the confidence tests. The technique showed good convergence for most derivatives for both kinds of maneuvers - typically within a few seconds. The confidence tests were marginally successful, and it would be necessary to refine them for use in an IFCS.

Modeling of microporous silicon betaelectric converter with 63Ni plating in GEANT4 toolkit*

NASA Astrophysics Data System (ADS)

Zelenkov, P. V.; Sidorov, V. G.; Lelekov, E. T.; Khoroshko, A. Y.; Bogdanov, S. V.; Lelekov, A. T.

2016-04-01

The model of electron-hole pairs generation rate distribution in semiconductor is needed to optimize the parameters of microporous silicon betaelectric converter, which uses 63Ni isotope radiation. By using Monte-Carlo methods of GEANT4 software with ultra-low energy electron physics models this distribution in silicon was calculated and approximated with exponential function. Optimal pore configuration was estimated.

Analysis of patient CT dose data using virtualdose

NASA Astrophysics Data System (ADS)

Bennett, Richard

X-ray computer tomography has many benefits to medical and research applications. Recently, over the last decade CT has had a large increase in usage in hospitals and medical diagnosis. In pediatric care, from 2000 to 2006, abdominal CT scans increased by 49 % and chest CT by 425 % in the emergency room (Broder 2007). Enormous amounts of effort have been performed across multiple academic and government groups to determine an accurate measure of organ dose to patients who undergo a CT scan due to the inherent risks with ionizing radiation. Considering these intrinsic risks, CT dose estimating software becomes a necessary tool that health care providers and radiologist must use to determine many metrics to base the risks versus rewards of having an x-ray CT scan. This thesis models the resultant organ dose as body mass increases for patients with all other related scan parameters fixed. In addition to this,this thesis compares a modern dose estimating software, VirtualDose CT to two other programs, CT-Expo and ImPACT CT. The comparison shows how the software's theoretical basis and the phantom they use to represent the human body affect the range of results in organ dose. CT-Expo and ImPACT CT dose estimating software uses a different model for anatomical representation of the organs in the human body and the results show how that approach dramatically changes the outcome. The results categorizes four datasets as compared to the three software types where the appropriate phantom was available. Modeling was done to simulate chest abdominal pelvis scans and whole body scans. Organ dose difference versus body mass index shows as body mass index (BMI) ranges from 23.5 kg/m 2 to 45 kg/m2 the amount of organ dose also trends a percent change from -4.58 to -176.19 %. Comparing organ dose difference with increasing x-ray tube potential from 120 kVp to 140 kVp the percent change in organ dose increases from 55 % to 65 % across all phantoms. In comparing VirtualDose to CT-Expo for organ dose difference versus age, male phantoms show percent difference of -19 % to 25 % for various organs minus bone surface and breast tissues results. Finally, for organ dose difference across all software for average adult phantom the results range from -45 % to 6 % in the comparison of ImPACT CT to VirtualDose and -27 % to 66 % for the comparison of CT-Expo to VirtualDose. In the comparison for increased BMI (done only in VirtualDose), results show that with all other parameters fixed, the organ dose goes down as BMI increases, which is due to the increase in adipose tissue and bulk of the patient model. The range of results when comparing all the three softwares have a wide range, in some cases greater than 150 %, it is evident that using a different anatomical basis for the human phantom and the theoretical basis for the dose estimation will cause fluctuation in the results. Therefore, choosing the software with the most accurate human phantom will provide a closer range to the true dose to the organ.

A new software for deformation source optimization, the Bayesian Earthquake Analysis Tool (BEAT)

NASA Astrophysics Data System (ADS)

Vasyura-Bathke, H.; Dutta, R.; Jonsson, S.; Mai, P. M.

2017-12-01

Modern studies of crustal deformation and the related source estimation, including magmatic and tectonic sources, increasingly use non-linear optimization strategies to estimate geometric and/or kinematic source parameters and often consider both jointly, geodetic and seismic data. Bayesian inference is increasingly being used for estimating posterior distributions of deformation source model parameters, given measured/estimated/assumed data and model uncertainties. For instance, some studies consider uncertainties of a layered medium and propagate these into source parameter uncertainties, while others use informative priors to reduce the model parameter space. In addition, innovative sampling algorithms have been developed to efficiently explore the high-dimensional parameter spaces. Compared to earlier studies, these improvements have resulted in overall more robust source model parameter estimates that include uncertainties. However, the computational burden of these methods is high and estimation codes are rarely made available along with the published results. Even if the codes are accessible, it is usually challenging to assemble them into a single optimization framework as they are typically coded in different programing languages. Therefore, further progress and future applications of these methods/codes are hampered, while reproducibility and validation of results has become essentially impossible. In the spirit of providing open-access and modular codes to facilitate progress and reproducible research in deformation source estimations, we undertook the effort of developing BEAT, a python package that comprises all the above-mentioned features in one single programing environment. The package builds on the pyrocko seismological toolbox (www.pyrocko.org), and uses the pymc3 module for Bayesian statistical model fitting. BEAT is an open-source package (https://github.com/hvasbath/beat), and we encourage and solicit contributions to the project. Here, we present our strategy for developing BEAT and show application examples; especially the effect of including the model prediction uncertainty of the velocity model in following source optimizations: full moment tensor, Mogi source, moderate strike-slip earth-quake.

Burden Calculator: a simple and open analytical tool for estimating the population burden of injuries.

PubMed

Bhalla, Kavi; Harrison, James E

2016-04-01

Burden of disease and injury methods can be used to summarise and compare the effects of conditions in terms of disability-adjusted life years (DALYs). Burden estimation methods are not inherently complex. However, as commonly implemented, the methods include complex modelling and estimation. To provide a simple and open-source software tool that allows estimation of incidence-DALYs due to injury, given data on incidence of deaths and non-fatal injuries. The tool includes a default set of estimation parameters, which can be replaced by users. The tool was written in Microsoft Excel. All calculations and values can be seen and altered by users. The parameter sets currently used in the tool are based on published sources. The tool is available without charge online at http://calculator.globalburdenofinjuries.org. To use the tool with the supplied parameter sets, users need to only paste a table of population and injury case data organised by age, sex and external cause of injury into a specified location in the tool. Estimated DALYs can be read or copied from tables and figures in another part of the tool. In some contexts, a simple and user-modifiable burden calculator may be preferable to undertaking a more complex study to estimate the burden of disease. The tool and the parameter sets required for its use can be improved by user innovation, by studies comparing DALYs estimates calculated in this way and in other ways, and by shared experience of its use. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Distribution of smile line, gingival angle and tooth shape among the Saudi Arabian subpopulation and their association with gingival biotype.

PubMed

AlQahtani, Nabeeh A; Haralur, Satheesh B; AlMaqbol, Mohammad; AlMufarrij, Ali Jubran; Al Dera, Ahmed Ali; Al-Qarni, Mohammed

2016-04-01

To determine the occurrence of smile line and maxillary tooth shape in the Saudi Arabian subpopulation, and to estimate the association between these parameters with gingival biotype. On the fulfillment of selection criteria, total 315 patients belong to Saudi Arabian ethnic group were randomly selected. Two frontal photographs of the patients were acquired. The tooth morphology, gingival angle, and smile line classification were determined with ImageJ image analyzing software. The gingival biotype was assessed by probe transparency method. The obtained data were analyzed with SPSS 19 (IBM Corporation, New York, USA) software to determine the frequency and association between other parameters and gingival biotype. Among the clinical parameters evaluated, the tapering tooth morphology (56.8%), thick gingival biotype (53%), and average smile line (57.5%) was more prevalent. The statistically significant association was found between thick gingival biotype and the square tooth, high smile line. The high gingival angle was associated with thin gingival biotype. The study results indicate the existence of an association between tooth shape, smile line, and gingival angle with gingival biotype.

Estimating extinction using unsupervised machine learning

NASA Astrophysics Data System (ADS)

Meingast, Stefan; Lombardi, Marco; Alves, João

2017-05-01

Dust extinction is the most robust tracer of the gas distribution in the interstellar medium, but measuring extinction is limited by the systematic uncertainties involved in estimating the intrinsic colors to background stars. In this paper we present a new technique, Pnicer, that estimates intrinsic colors and extinction for individual stars using unsupervised machine learning algorithms. This new method aims to be free from any priors with respect to the column density and intrinsic color distribution. It is applicable to any combination of parameters and works in arbitrary numbers of dimensions. Furthermore, it is not restricted to color space. Extinction toward single sources is determined by fitting Gaussian mixture models along the extinction vector to (extinction-free) control field observations. In this way it becomes possible to describe the extinction for observed sources with probability densities, rather than a single value. Pnicer effectively eliminates known biases found in similar methods and outperforms them in cases of deep observational data where the number of background galaxies is significant, or when a large number of parameters is used to break degeneracies in the intrinsic color distributions. This new method remains computationally competitive, making it possible to correctly de-redden millions of sources within a matter of seconds. With the ever-increasing number of large-scale high-sensitivity imaging surveys, Pnicer offers a fast and reliable way to efficiently calculate extinction for arbitrary parameter combinations without prior information on source characteristics. The Pnicer software package also offers access to the well-established Nicer technique in a simple unified interface and is capable of building extinction maps including the Nicest correction for cloud substructure. Pnicer is offered to the community as an open-source software solution and is entirely written in Python.

PyCoTools: A Python Toolbox for COPASI.

PubMed

Welsh, Ciaran M; Fullard, Nicola; Proctor, Carole J; Martinez-Guimera, Alvaro; Isfort, Robert J; Bascom, Charles C; Tasseff, Ryan; Przyborski, Stefan A; Shanley, Daryl P

2018-05-22

COPASI is an open source software package for constructing, simulating and analysing dynamic models of biochemical networks. COPASI is primarily intended to be used with a graphical user interface but often it is desirable to be able to access COPASI features programmatically, with a high level interface. PyCoTools is a Python package aimed at providing a high level interface to COPASI tasks with an emphasis on model calibration. PyCoTools enables the construction of COPASI models and the execution of a subset of COPASI tasks including time courses, parameter scans and parameter estimations. Additional 'composite' tasks which use COPASI tasks as building blocks are available for increasing parameter estimation throughput, performing identifiability analysis and performing model selection. PyCoTools supports exploratory data analysis on parameter estimation data to assist with troubleshooting model calibrations. We demonstrate PyCoTools by posing a model selection problem designed to show case PyCoTools within a realistic scenario. The aim of the model selection problem is to test the feasibility of three alternative hypotheses in explaining experimental data derived from neonatal dermal fibroblasts in response to TGF-β over time. PyCoTools is used to critically analyse the parameter estimations and propose strategies for model improvement. PyCoTools can be downloaded from the Python Package Index (PyPI) using the command 'pip install pycotools' or directly from GitHub (https://github.com/CiaranWelsh/pycotools). Documentation at http://pycotools.readthedocs.io. Supplementary data are available at Bioinformatics.

SU-E-I-25: Determining Tube Current, Tube Voltage and Pitch Suitable for Low- Dose Lung Screening CT

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

Williams, K; Matthews, K

2014-06-01

Purpose: The quality of a computed tomography (CT) image and the dose delivered during its acquisition depend upon the acquisition parameters used. Tube current, tube voltage, and pitch are acquisition parameters that potentially affect image quality and dose. This study investigated physicians' abilities to characterize small, solid nodules in low-dose CT images for combinations of current, voltage and pitch, for three CT scanner models. Methods: Lung CT images was acquired of a Data Spectrum anthropomorphic torso phantom with various combinations of pitch, tube current, and tube voltage; this phantom was used because acrylic beads of various sizes could be placedmore » within the lung compartments to simulate nodules. The phantom was imaged on two 16-slice scanners and a 64-slice scanner. The acquisition parameters spanned a range of estimated CTDI levels; the CTDI estimates from the acquisition software were verified by measurement. Several experienced radiologists viewed the phantom lung CT images and noted nodule location, size and shape, as well as the acceptability of overall image quality. Results: Image quality for assessment of nodules was deemed unsatisfactory for all scanners at 80 kV (any tube current) and at 35 mA (any tube voltage). Tube current of 50 mA or more at 120 kV resulted in similar assessments from all three scanners. Physician-measured sphere diameters were closer to actual diameters for larger spheres, higher tube current, and higher kV. Pitch influenced size measurements less for larger spheres than for smaller spheres. CTDI was typically overestimated by the scanner software compared to measurement. Conclusion: Based on this survey of acquisition parameters, a low-dose CT protocol of 120 kV, 50 mA, and pitch of 1.4 is recommended to balance patient dose and acceptable image quality. For three models of scanners, this protocol resulted in estimated CTDIs from 2.9–3.6 mGy.« less

Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Hanson, Andrea; Reed, Erik; Cavanagh, Peter

2011-01-01

Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.

ArcNLET: A GIS-based software to simulate groundwater nitrate load from septic systems to surface water bodies

NASA Astrophysics Data System (ADS)

Rios, J. Fernando; Ye, Ming; Wang, Liying; Lee, Paul Z.; Davis, Hal; Hicks, Rick

2013-03-01

Onsite wastewater treatment systems (OWTS), or septic systems, can be a significant source of nitrates in groundwater and surface water. The adverse effects that nitrates have on human and environmental health have given rise to the need to estimate the actual or potential level of nitrate contamination. With the goal of reducing data collection and preparation costs, and decreasing the time required to produce an estimate compared to complex nitrate modeling tools, we developed the ArcGIS-based Nitrate Load Estimation Toolkit (ArcNLET) software. Leveraging the power of geographic information systems (GIS), ArcNLET is an easy-to-use software capable of simulating nitrate transport in groundwater and estimating long-term nitrate loads from groundwater to surface water bodies. Data requirements are reduced by using simplified models of groundwater flow and nitrate transport which consider nitrate attenuation mechanisms (subsurface dispersion and denitrification) as well as spatial variability in the hydraulic parameters and septic tank distribution. ArcNLET provides a spatial distribution of nitrate plumes from multiple septic systems and a load estimate to water bodies. ArcNLET's conceptual model is divided into three sub-models: a groundwater flow model, a nitrate transport and fate model, and a load estimation model which are implemented as an extension to ArcGIS. The groundwater flow model uses a map of topography in order to generate a steady-state approximation of the water table. In a validation study, this approximation was found to correlate well with a water table produced by a calibrated numerical model although it was found that the degree to which the water table resembles the topography can vary greatly across the modeling domain. The transport model uses a semi-analytical solution to estimate the distribution of nitrate within groundwater, which is then used to estimate a nitrate load using a mass balance argument. The estimates given by ArcNLET are suitable for a screening-level analysis.

Program Analyzes Radar Altimeter Data

NASA Technical Reports Server (NTRS)

Vandemark, Doug; Hancock, David; Tran, Ngan

2004-01-01

A computer program has been written to perform several analyses of radar altimeter data. The program was designed to improve on previous methods of analysis of altimeter engineering data by (1) facilitating and accelerating the analysis of large amounts of data in a more direct manner and (2) improving the ability to estimate performance of radar-altimeter instrumentation and provide data corrections. The data in question are openly available to the international scientific community and can be downloaded from anonymous file-transfer- protocol (FTP) locations that are accessible via links from altimetry Web sites. The software estimates noise in range measurements, estimates corrections for electromagnetic bias, and performs statistical analyses on various parameters for comparison of different altimeters. Whereas prior techniques used to perform similar analyses of altimeter range noise require comparison of data from repetitions of satellite ground tracks, the present software uses a high-pass filtering technique to obtain similar results from single satellite passes. Elimination of the requirement for repeat-track analysis facilitates the analysis of large amounts of satellite data to assess subtle variations in range noise.

STEAM: a software tool based on empirical analysis for micro electro mechanical systems

NASA Astrophysics Data System (ADS)

Devasia, Archana; Pasupuleti, Ajay; Sahin, Ferat

2006-03-01

In this research a generalized software framework that enables accurate computer aided design of MEMS devices is developed. The proposed simulation engine utilizes a novel material property estimation technique that generates effective material properties at the microscopic level. The material property models were developed based on empirical analysis and the behavior extraction of standard test structures. A literature review is provided on the physical phenomena that govern the mechanical behavior of thin films materials. This survey indicates that the present day models operate under a wide range of assumptions that may not be applicable to the micro-world. Thus, this methodology is foreseen to be an essential tool for MEMS designers as it would develop empirical models that relate the loading parameters, material properties, and the geometry of the microstructures with its performance characteristics. This process involves learning the relationship between the above parameters using non-parametric learning algorithms such as radial basis function networks and genetic algorithms. The proposed simulation engine has a graphical user interface (GUI) which is very adaptable, flexible, and transparent. The GUI is able to encompass all parameters associated with the determination of the desired material property so as to create models that provide an accurate estimation of the desired property. This technique was verified by fabricating and simulating bilayer cantilevers consisting of aluminum and glass (TEOS oxide) in our previous work. The results obtained were found to be very encouraging.

BGFit: management and automated fitting of biological growth curves.

PubMed

Veríssimo, André; Paixão, Laura; Neves, Ana Rute; Vinga, Susana

2013-09-25

Existing tools to model cell growth curves do not offer a flexible integrative approach to manage large datasets and automatically estimate parameters. Due to the increase of experimental time-series from microbiology and oncology, the need for a software that allows researchers to easily organize experimental data and simultaneously extract relevant parameters in an efficient way is crucial. BGFit provides a web-based unified platform, where a rich set of dynamic models can be fitted to experimental time-series data, further allowing to efficiently manage the results in a structured and hierarchical way. The data managing system allows to organize projects, experiments and measurements data and also to define teams with different editing and viewing permission. Several dynamic and algebraic models are already implemented, such as polynomial regression, Gompertz, Baranyi, Logistic and Live Cell Fraction models and the user can add easily new models thus expanding current ones. BGFit allows users to easily manage their data and models in an integrated way, even if they are not familiar with databases or existing computational tools for parameter estimation. BGFit is designed with a flexible architecture that focus on extensibility and leverages free software with existing tools and methods, allowing to compare and evaluate different data modeling techniques. The application is described in the context of bacterial and tumor cells growth data fitting, but it is also applicable to any type of two-dimensional data, e.g. physical chemistry and macroeconomic time series, being fully scalable to high number of projects, data and model complexity.

ODEion--a software module for structural identification of ordinary differential equations.

PubMed

Gennemark, Peter; Wedelin, Dag

2014-02-01

In the systems biology field, algorithms for structural identification of ordinary differential equations (ODEs) have mainly focused on fixed model spaces like S-systems and/or on methods that require sufficiently good data so that derivatives can be accurately estimated. There is therefore a lack of methods and software that can handle more general models and realistic data. We present ODEion, a software module for structural identification of ODEs. Main characteristic features of the software are: • The model space is defined by arbitrary user-defined functions that can be nonlinear in both variables and parameters, such as for example chemical rate reactions. • ODEion implements computationally efficient algorithms that have been shown to efficiently handle sparse and noisy data. It can run a range of realistic problems that previously required a supercomputer. • ODEion is easy to use and provides SBML output. We describe the mathematical problem, the ODEion system itself, and provide several examples of how the system can be used. Available at: http://www.odeidentification.org.

A new software for dimensional measurements in 3D endodontic root canal instrumentation.

PubMed

Sinibaldi, Raffaele; Pecci, Raffaella; Somma, Francesco; Della Penna, Stefania; Bedini, Rossella

2012-01-01

The main issue to be faced to get size estimates of 3D modification of the dental canal after endodontic treatment is the co-registration of the image stacks obtained through micro computed tomography (micro-CT) scans before and after treatment. Here quantitative analysis of micro-CT images have been performed by means of new dedicated software targeted to the analysis of root canal after endodontic instrumentation. This software analytically calculates the best superposition between the pre and post structures using the inertia tensor of the tooth. This strategy avoid minimization procedures, which can be user dependent, and time consuming. Once the co-registration have been achieved dimensional measurements have then been performed by contemporary evaluation of quantitative parameters over the two superimposed stacks of micro-CT images. The software automatically calculated the changes of volume, surface and symmetry axes in 3D occurring after the instrumentation. The calculation is based on direct comparison of the canal and canal branches selected by the user on the pre treatment image stack.

Errors in the estimation method for the rejection of vibrations in adaptive optics systems

NASA Astrophysics Data System (ADS)

Kania, Dariusz

2017-06-01

In recent years the problem of the mechanical vibrations impact in adaptive optics (AO) systems has been renewed. These signals are damped sinusoidal signals and have deleterious effect on the system. One of software solutions to reject the vibrations is an adaptive method called AVC (Adaptive Vibration Cancellation) where the procedure has three steps: estimation of perturbation parameters, estimation of the frequency response of the plant, update the reference signal to reject/minimalize the vibration. In the first step a very important problem is the estimation method. A very accurate and fast (below 10 ms) estimation method of these three parameters has been presented in several publications in recent years. The method is based on using the spectrum interpolation and MSD time windows and it can be used to estimate multifrequency signals. In this paper the estimation method is used in the AVC method to increase the system performance. There are several parameters that affect the accuracy of obtained results, e.g. CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, b - number of ADC bits, γ - damping ratio of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value for systematic error is approximately 10^-10 Hz/Hz for N = 2048 and CiR = 0.1. This paper presents equations that can used to estimate maximum systematic errors for given values of H, CiR and N before the start of the estimation process.

Compositional Effects on Nickel-Base Superalloy Single Crystal Microstructures

NASA Technical Reports Server (NTRS)

MacKay, Rebecca A.; Gabb, Timothy P.; Garg,Anita; Rogers, Richard B.; Nathal, Michael V.

2012-01-01

Fourteen nickel-base superalloy single crystals containing 0 to 5 wt% chromium (Cr), 0 to 11 wt% cobalt (Co), 6 to 12 wt% molybdenum (Mo), 0 to 4 wt% rhenium (Re), and fixed amounts of aluminum (Al) and tantalum (Ta) were examined to determine the effect of bulk composition on basic microstructural parameters, including gamma' solvus, gamma' volume fraction, volume fraction of topologically close-packed (TCP) phases, phase chemistries, and gamma - gamma'. lattice mismatch. Regression models were developed to describe the influence of bulk alloy composition on the microstructural parameters and were compared to predictions by a commercially available software tool that used computational thermodynamics. Co produced the largest change in gamma' solvus over the wide compositional range used in this study, and Mo produced the largest effect on the gamma lattice parameter and the gamma - gamma' lattice mismatch over its compositional range, although Re had a very potent influence on all microstructural parameters investigated. Changing the Cr, Co, Mo, and Re contents in the bulk alloy had a significant impact on their concentrations in the gamma matrix and, to a smaller extent, in the gamma' phase. The gamma phase chemistries exhibited strong temperature dependencies that were influenced by the gamma and gamma' volume fractions. A computational thermodynamic modeling tool significantly underpredicted gamma' solvus temperatures and grossly overpredicted the amount of TCP phase at 982 C. Furthermore, the predictions by the software tool for the gamma - gamma' lattice mismatch were typically of the wrong sign and magnitude, but predictions could be improved if TCP formation was suspended within the software program. However, the statistical regression models provided excellent estimations of the microstructural parameters based on bulk alloy composition, thereby demonstrating their usefulness.

Software Review: A program for testing capture-recapture data for closure

USGS Publications Warehouse

Stanley, Thomas R.; Richards, Jon D.

2005-01-01

Capture-recapture methods are widely used to estimate population parameters of free-ranging animals. Closed-population capture-recapture models, which assume there are no additions to or losses from the population over the period of study (i.e., the closure assumption), are preferred for population estimation over the open-population models, which do not assume closure, because heterogeneity in detection probabilities can be accounted for and this improves estimates. In this paper we introduce CloseTest, a new Microsoft® Windows-based program that computes the Otis et al. (1978) and Stanley and Burnham (1999) closure tests for capture-recapture data sets. Information on CloseTest features and where to obtain the program are provided.

Software Effort Estimation Accuracy: A Comparative Study of Estimations Based on Software Sizing and Development Methods

ERIC Educational Resources Information Center

Lafferty, Mark T.

2010-01-01

The number of project failures and those projects completed over cost and over schedule has been a significant issue for software project managers. Among the many reasons for failure, inaccuracy in software estimation--the basis for project bidding, budgeting, planning, and probability estimates--has been identified as a root cause of a high…

NASA Software Cost Estimation Model: An Analogy Based Estimation Model

NASA Technical Reports Server (NTRS)

Hihn, Jairus; Juster, Leora; Menzies, Tim; Mathew, George; Johnson, James

2015-01-01

The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K-­ nearest neighbor prediction model performance on the same data set.

Computing ordinary least-squares parameter estimates for the National Descriptive Model of Mercury in Fish

USGS Publications Warehouse

Donato, David I.

2013-01-01

A specialized technique is used to compute weighted ordinary least-squares (OLS) estimates of the parameters of the National Descriptive Model of Mercury in Fish (NDMMF) in less time using less computer memory than general methods. The characteristics of the NDMMF allow the two products X'X and X'y in the normal equations to be filled out in a second or two of computer time during a single pass through the N data observations. As a result, the matrix X does not have to be stored in computer memory and the computationally expensive matrix multiplications generally required to produce X'X and X'y do not have to be carried out. The normal equations may then be solved to determine the best-fit parameters in the OLS sense. The computational solution based on this specialized technique requires O(8p2+16p) bytes of computer memory for p parameters on a machine with 8-byte double-precision numbers. This publication includes a reference implementation of this technique and a Gaussian-elimination solver in preliminary custom software.

Practical Issues in Implementing Software Reliability Measurement

NASA Technical Reports Server (NTRS)

Nikora, Allen P.; Schneidewind, Norman F.; Everett, William W.; Munson, John C.; Vouk, Mladen A.; Musa, John D.

1999-01-01

Many ways of estimating software systems' reliability, or reliability-related quantities, have been developed over the past several years. Of particular interest are methods that can be used to estimate a software system's fault content prior to test, or to discriminate between components that are fault-prone and those that are not. The results of these methods can be used to: 1) More accurately focus scarce fault identification resources on those portions of a software system most in need of it. 2) Estimate and forecast the risk of exposure to residual faults in a software system during operation, and develop risk and safety criteria to guide the release of a software system to fielded use. 3) Estimate the efficiency of test suites in detecting residual faults. 4) Estimate the stability of the software maintenance process.

Estimates of genetics and phenotypics parameters for the yield and quality of soybean seeds.

PubMed

Zambiazzi, E V; Bruzi, A T; Guilherme, S R; Pereira, D R; Lima, J G; Zuffo, A M; Ribeiro, F O; Mendes, A E S; Godinho, S H M; Carvalho, M L M

2017-09-27

Estimating genotype x environment (GxE) parameters for quality and yield in soybean seed grown in different environments in Minas Gerais State was the goal of this study, as well as to evaluate interaction effects of GxE for soybean seeds yield and quality. Seeds were produced in three locations in Minas Gerais State (Lavras, Inconfidentes, and Patos de Minas) in 2013/14 and 2014/15 seasons. Field experiments were conducted in randomized blocks in a factorial 17 x 6 (GxE), and three replications. Seed yield and quality were evaluated for germination in substrates paper and sand, seedling emergence, speed emergency index, mechanical damage by sodium hypochlorite, electrical conductivity, speed aging, vigor and viability of seeds by tetrazolium test in laboratory using completely randomized design. Quadratic component genotypic, GXE variance component, genotype determination coefficient, genetic variation coefficient and environmental variation coefficient were estimated using the Genes software. Percentage analysis of genotypes contribution, environments and genotype x environment interaction were conducted by sites combination two by two and three sites combination, using the R software. Considering genotypes selection of broad adaptation, TMG 1179 RR, CD 2737 RR, and CD 237 RR associated better yield performance at high physical and physiological potential of seed. Environmental effect was more expressive for most of the characters related to soybean seed quality. GxE interaction effects were expressive though genotypes did not present coincidental behavior in different environments.

An open tool for input function estimation and quantification of dynamic PET FDG brain scans.

PubMed

Bertrán, Martín; Martínez, Natalia; Carbajal, Guillermo; Fernández, Alicia; Gómez, Álvaro

2016-08-01

Positron emission tomography (PET) analysis of clinical studies is mostly restricted to qualitative evaluation. Quantitative analysis of PET studies is highly desirable to be able to compute an objective measurement of the process of interest in order to evaluate treatment response and/or compare patient data. But implementation of quantitative analysis generally requires the determination of the input function: the arterial blood or plasma activity which indicates how much tracer is available for uptake in the brain. The purpose of our work was to share with the community an open software tool that can assist in the estimation of this input function, and the derivation of a quantitative map from the dynamic PET study. Arterial blood sampling during the PET study is the gold standard method to get the input function, but is uncomfortable and risky for the patient so it is rarely used in routine studies. To overcome the lack of a direct input function, different alternatives have been devised and are available in the literature. These alternatives derive the input function from the PET image itself (image-derived input function) or from data gathered from previous similar studies (population-based input function). In this article, we present ongoing work that includes the development of a software tool that integrates several methods with novel strategies for the segmentation of blood pools and parameter estimation. The tool is available as an extension to the 3D Slicer software. Tests on phantoms were conducted in order to validate the implemented methods. We evaluated the segmentation algorithms over a range of acquisition conditions and vasculature size. Input function estimation algorithms were evaluated against ground truth of the phantoms, as well as on their impact over the final quantification map. End-to-end use of the tool yields quantification maps with [Formula: see text] relative error in the estimated influx versus ground truth on phantoms. The main contribution of this article is the development of an open-source, free to use tool that encapsulates several well-known methods for the estimation of the input function and the quantification of dynamic PET FDG studies. Some alternative strategies are also proposed and implemented in the tool for the segmentation of blood pools and parameter estimation. The tool was tested on phantoms with encouraging results that suggest that even bloodless estimators could provide a viable alternative to blood sampling for quantification using graphical analysis. The open tool is a promising opportunity for collaboration among investigators and further validation on real studies.

Alignment-free Transcriptomic and Metatranscriptomic Comparison Using Sequencing Signatures with Variable Length Markov Chains.

PubMed

Liao, Weinan; Ren, Jie; Wang, Kun; Wang, Shun; Zeng, Feng; Wang, Ying; Sun, Fengzhu

2016-11-23

The comparison between microbial sequencing data is critical to understand the dynamics of microbial communities. The alignment-based tools analyzing metagenomic datasets require reference sequences and read alignments. The available alignment-free dissimilarity approaches model the background sequences with Fixed Order Markov Chain (FOMC) yielding promising results for the comparison of microbial communities. However, in FOMC, the number of parameters grows exponentially with the increase of the order of Markov Chain (MC). Under a fixed high order of MC, the parameters might not be accurately estimated owing to the limitation of sequencing depth. In our study, we investigate an alternative to FOMC to model background sequences with the data-driven Variable Length Markov Chain (VLMC) in metatranscriptomic data. The VLMC originally designed for long sequences was extended to apply to high-throughput sequencing reads and the strategies to estimate the corresponding parameters were developed. The flexible number of parameters in VLMC avoids estimating the vast number of parameters of high-order MC under limited sequencing depth. Different from the manual selection in FOMC, VLMC determines the MC order adaptively. Several beta diversity measures based on VLMC were applied to compare the bacterial RNA-Seq and metatranscriptomic datasets. Experiments show that VLMC outperforms FOMC to model the background sequences in transcriptomic and metatranscriptomic samples. A software pipeline is available at https://d2vlmc.codeplex.com.

A Galerkin method for the estimation of parameters in hybrid systems governing the vibration of flexible beams with tip bodies

NASA Technical Reports Server (NTRS)

Banks, H. T.; Rosen, I. G.

1985-01-01

An approximation scheme is developed for the identification of hybrid systems describing the transverse vibrations of flexible beams with attached tip bodies. In particular, problems involving the estimation of functional parameters are considered. The identification problem is formulated as a least squares fit to data subject to the coupled system of partial and ordinary differential equations describing the transverse displacement of the beam and the motion of the tip bodies respectively. A cubic spline-based Galerkin method applied to the state equations in weak form and the discretization of the admissible parameter space yield a sequence of approximating finite dimensional identification problems. It is shown that each of the approximating problems admits a solution and that from the resulting sequence of optimal solutions a convergent subsequence can be extracted, the limit of which is a solution to the original identification problem. The approximating identification problems can be solved using standard techniques and readily available software.

Analysis of Air Traffic Track Data with the AutoBayes Synthesis System

NASA Technical Reports Server (NTRS)

Schumann, Johann Martin Philip; Cate, Karen; Lee, Alan G.

2010-01-01

The Next Generation Air Traffic System (NGATS) is aiming to provide substantial computer support for the air traffic controllers. Algorithms for the accurate prediction of aircraft movements are of central importance for such software systems but trajectory prediction has to work reliably in the presence of unknown parameters and uncertainties. We are using the AutoBayes program synthesis system to generate customized data analysis algorithms that process large sets of aircraft radar track data in order to estimate parameters and uncertainties. In this paper, we present, how the tasks of finding structure in track data, estimation of important parameters in climb trajectories, and the detection of continuous descent approaches can be accomplished with compact task-specific AutoBayes specifications. We present an overview of the AutoBayes architecture and describe, how its schema-based approach generates customized analysis algorithms, documented C/C++ code, and detailed mathematical derivations. Results of experiments with actual air traffic control data are discussed.

Application of ADM1 for modeling of biogas production from anaerobic digestion of Hydrilla verticillata.

PubMed

Chen, Xiaojuan; Chen, Zhihua; Wang, Xun; Huo, Chan; Hu, Zhiquan; Xiao, Bo; Hu, Mian

2016-07-01

The present study focused on the application of anaerobic digestion model no. 1 (ADM1) to simulate biogas production from Hydrilla verticillata. Model simulation was carried out by implementing ADM1 in AQUASIM 2.0 software. Sensitivity analysis was used to select the most sensitive parameters for estimation using the absolute-relative sensitivity function. Among all the kinetic parameters, disintegration constant (kdis), hydrolysis constant of protein (khyd_pr), Monod maximum specific substrate uptake rate (km_aa, km_ac, km_h2) and half-saturation constants (Ks_aa, Ks_ac) affect biogas production significantly, which were optimized by fitting of the model equations to the data obtained from batch experiments. The ADM1 model after parameter estimation was able to well predict the experimental results of daily biogas production and biogas composition. The simulation results of evolution of organic acids, bacteria concentrations and inhibition effects also helped to get insight into the reaction mechanisms. Copyright © 2016. Published by Elsevier Ltd.

A Conceptual Wing Flutter Analysis Tool for Systems Analysis and Parametric Design Study

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivek

2003-01-01

An interactive computer program was developed for wing flutter analysis in the conceptual design stage. The objective was to estimate flutt er instability boundaries of a typical wing, when detailed structural and aerodynamic data are not available. Effects of change in key flu tter parameters can also be estimated in order to guide the conceptual design. This userfriendly software was developed using MathCad and M atlab codes. The analysis method was based on non-dimensional paramet ric plots of two primary flutter parameters, namely Regier number and Flutter number, with normalization factors based on wing torsion stiffness, sweep, mass ratio, taper ratio, aspect ratio, center of gravit y location and pitch-inertia radius of gyration. These parametric plo ts were compiled in a Chance-Vought Corporation report from database of past experiments and wind tunnel test results. An example was prese nted for conceptual flutter analysis of outer-wing of a Blended-Wing- Body aircraft.

Comparision of the different probability distributions for earthquake hazard assessment in the North Anatolian Fault Zone

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

Yilmaz, Şeyda, E-mail: seydayilmaz@ktu.edu.tr; Bayrak, Erdem, E-mail: erdmbyrk@gmail.com; Bayrak, Yusuf, E-mail: bayrak@ktu.edu.tr

In this study we examined and compared the three different probabilistic distribution methods for determining the best suitable model in probabilistic assessment of earthquake hazards. We analyzed a reliable homogeneous earthquake catalogue between a time period 1900-2015 for magnitude M ≥ 6.0 and estimated the probabilistic seismic hazard in the North Anatolian Fault zone (39°-41° N 30°-40° E) using three distribution methods namely Weibull distribution, Frechet distribution and three-parameter Weibull distribution. The distribution parameters suitability was evaluated Kolmogorov-Smirnov (K-S) goodness-of-fit test. We also compared the estimated cumulative probability and the conditional probabilities of occurrence of earthquakes for different elapsed timemore » using these three distribution methods. We used Easyfit and Matlab software to calculate these distribution parameters and plotted the conditional probability curves. We concluded that the Weibull distribution method was the most suitable than other distribution methods in this region.« less

ROI Analysis of the System Architecture Virtual Integration Initiative

DTIC Science & Technology

2018-04-01

The ROI anal- ysis uses conservative estimates of costs and benefits, especially for those parameters that have a proven, strong correlation to overall...formula: • In Section 3, we discuss the exponential growth of avionics software systems in terms of SLOC by analyzing the historical data to correlate ...which implies that the system has good structure (high cohesion, low coupling), good ap- plication clarity (good correlation between program and

Oscillating-Flow Regenerator Test Rig: Hardware and Theory With Derived Correlations for Screens and Felts

NASA Technical Reports Server (NTRS)

Gedeon, D.; Wood, J. G.

1996-01-01

A number of wire mesh and metal felt test samples, with a range of porosities, yield generic correlations for friction factor, Nusselt number, enhanced axial conduction ratio, and overall heat flux ratio. This information is directed primarily toward stirling cycle regenerator modelers, but will be of use to anyone seeking to better model fluid flow through these porous materials. Behind these results lies an oscillating-flow test rig, which measures pumping dissipation and thermal energy transport in sample matrices, and several stages of data-reduction software, which correlate instantaneous values for the above dimensionless groups. Within the software, theoretical model reduces instantaneous quantifies from cycle-averaged measurables using standard parameter estimation techniques.

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

Carter, Faustin Wirkus; Khaire, Trupti S.; Novosad, Valentyn

We present "scraps" (SuperConducting Analysis and Plotting Software), a Python package designed to aid in the analysis and visualization of large amounts of superconducting resonator data, specifically complex transmission as a function of frequency, acquired at many different temperatures and driving powers. The package includes a least-squares fitting engine as well as a Monte-Carlo Markov Chain sampler for sampling the posterior distribution given priors, marginalizing over nuisance parameters, and estimating covariances. A set of plotting tools for generating publication-quality figures is also provided in the package. Lastly, we discuss the functionality of the software and provide some examples of itsmore » utility on data collected from a niobium-nitride coplanar waveguide resonator fabricated at Argonne National Laboratory.« less

Selection of optimal oligonucleotide probes for microarrays usingmultiple criteria, global alignment and parameter estimation.

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

Li, Xingyuan; He, Zhili; Zhou, Jizhong

2005-10-30

The oligonucleotide specificity for microarray hybridizationcan be predicted by its sequence identity to non-targets, continuousstretch to non-targets, and/or binding free energy to non-targets. Mostcurrently available programs only use one or two of these criteria, whichmay choose 'false' specific oligonucleotides or miss 'true' optimalprobes in a considerable proportion. We have developed a software tool,called CommOligo using new algorithms and all three criteria forselection of optimal oligonucleotide probes. A series of filters,including sequence identity, free energy, continuous stretch, GC content,self-annealing, distance to the 3'-untranslated region (3'-UTR) andmelting temperature (Tm), are used to check each possibleoligonucleotide. A sequence identity is calculated based onmore » gapped globalalignments. A traversal algorithm is used to generate alignments for freeenergy calculation. The optimal Tm interval is determined based on probecandidates that have passed all other filters. Final probes are pickedusing a combination of user-configurable piece-wise linear functions andan iterative process. The thresholds for identity, stretch and freeenergy filters are automatically determined from experimental data by anaccessory software tool, CommOligo_PE (CommOligo Parameter Estimator).The program was used to design probes for both whole-genome and highlyhomologous sequence data. CommOligo and CommOligo_PE are freely availableto academic users upon request.« less

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflights systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for design, failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes, These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Binary variable multiple-model multiple imputation to address missing data mechanism uncertainty: Application to a smoking cessation trial

PubMed Central

Siddique, Juned; Harel, Ofer; Crespi, Catherine M.; Hedeker, Donald

2014-01-01

The true missing data mechanism is never known in practice. We present a method for generating multiple imputations for binary variables that formally incorporates missing data mechanism uncertainty. Imputations are generated from a distribution of imputation models rather than a single model, with the distribution reflecting subjective notions of missing data mechanism uncertainty. Parameter estimates and standard errors are obtained using rules for nested multiple imputation. Using simulation, we investigate the impact of missing data mechanism uncertainty on post-imputation inferences and show that incorporating this uncertainty can increase the coverage of parameter estimates. We apply our method to a longitudinal smoking cessation trial where nonignorably missing data were a concern. Our method provides a simple approach for formalizing subjective notions regarding nonresponse and can be implemented using existing imputation software. PMID:24634315

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

Spycher, Nicolas; Peiffer, Loic; Finsterle, Stefan

GeoT implements the multicomponent geothermometry method developed by Reed and Spycher (1984, Geochim. Cosmichim. Acta 46 513–528) into a stand-alone computer program, to ease the application of this method and to improve the prediction of geothermal reservoir temperatures using full and integrated chemical analyses of geothermal fluids. Reservoir temperatures are estimated from statistical analyses of mineral saturation indices computed as a function of temperature. The reconstruction of the deep geothermal fluid compositions, and geothermometry computations, are all implemented into the same computer program, allowing unknown or poorly constrained input parameters to be estimated by numerical optimization using existing parameter estimationmore » software, such as iTOUGH2, PEST, or UCODE. This integrated geothermometry approach presents advantages over classical geothermometers for fluids that have not fully equilibrated with reservoir minerals and/or that have been subject to processes such as dilution and gas loss.« less

Simplex GPS and InSAR Inversion Software

NASA Technical Reports Server (NTRS)

Donnellan, Andrea; Parker, Jay W.; Lyzenga, Gregory A.; Pierce, Marlon E.

2012-01-01

Changes in the shape of the Earth's surface can be routinely measured with precisions better than centimeters. Processes below the surface often drive these changes and as a result, investigators require models with inversion methods to characterize the sources. Simplex inverts any combination of GPS (global positioning system), UAVSAR (uninhabited aerial vehicle synthetic aperture radar), and InSAR (interferometric synthetic aperture radar) data simultaneously for elastic response from fault and fluid motions. It can be used to solve for multiple faults and parameters, all of which can be specified or allowed to vary. The software can be used to study long-term tectonic motions and the faults responsible for those motions, or can be used to invert for co-seismic slip from earthquakes. Solutions involving estimation of fault motion and changes in fluid reservoirs such as magma or water are possible. Any arbitrary number of faults or parameters can be considered. Simplex specifically solves for any of location, geometry, fault slip, and expansion/contraction of a single or multiple faults. It inverts GPS and InSAR data for elastic dislocations in a half-space. Slip parameters include strike slip, dip slip, and tensile dislocations. It includes a map interface for both setting up the models and viewing the results. Results, including faults, and observed, computed, and residual displacements, are output in text format, a map interface, and can be exported to KML. The software interfaces with the QuakeTables database allowing a user to select existing fault parameters or data. Simplex can be accessed through the QuakeSim portal graphical user interface or run from a UNIX command line.

An automation of design and modelling tasks in NX Siemens environment with original software - cost module

NASA Astrophysics Data System (ADS)

Zbiciak, R.; Grabowik, C.; Janik, W.

2015-11-01

The design-constructional process is a creation activity which strives to fulfil, as well as it possible at the certain moment of time, all demands and needs formulated by a user taking into account social, technical and technological advances. Engineer knowledge and skills and their inborn abilities have the greatest influence on the final product quality and cost. They have also deciding influence on product technical and economic value. Taking into account above it seems to be advisable to make software tools that support an engineer in the process of manufacturing cost estimation. The Cost module is built with analytical procedures which are used for relative manufacturing cost estimation. As in the case of the Generator module the Cost module was written in object programming language C# in Visual Studio environment. During the research the following eight factors, that have the greatest influence on overall manufacturing cost, were distinguished and defined: (i) a gear wheel teeth type it is straight or helicoidal, (ii) a gear wheel design shape A, B with or without wheel hub, (iii) a gear tooth module, (iv) teeth number, (v) gear rim width, (vi) gear wheel material, (vii) heat treatment or thermochemical treatment, (viii) accuracy class. Knowledge of parameters (i) to (v) is indispensable for proper modelling of 3D gear wheels models in CAD system environment. These parameters are also processed in the Cost module. The last three parameters it is (vi) to (viii) are exclusively used in the Cost module. The estimation of manufacturing relative cost is based on indexes calculated for each particular parameter. Estimated in this way the manufacturing relative cost gives an overview of design parameters influence on the final gear wheel manufacturing cost. This relative manufacturing cost takes values from 0.00 to 1,00 range. The bigger index value the higher relative manufacturing cost is. Verification whether the proposed algorithm of relative manufacturing costs estimation has been designed properly was made by comparison of the achieved from the algorithm results with those obtained from industry. This verification has indicated that in most cases both group of results are similar. Taking into account above it is possible to draw a conclusion that the Cost module might play significant role in design constructional process by adding an engineer at the selection stage of alternative gear wheels design. It should be remembered that real manufacturing cost can differ significantly according to available in a factory manufacturing techniques and stock of machine tools.

Determination of the stability and control derivatives of the NASA F/A-18 HARV using flight data

NASA Technical Reports Server (NTRS)

Napolitano, Marcello R.; Spagnuolo, Joelle M.

1993-01-01

This report documents the research conducted for the NASA-Ames Cooperative Agreement No. NCC 2-759 with West Virginia University. A complete set of the stability and control derivatives for varying angles of attack from 10 deg to 60 deg were estimated from flight data of the NASA F/A-18 HARV. The data were analyzed with the use of the pEst software which implements the output-error method of parameter estimation. Discussions of the aircraft equations of motion, parameter estimation process, design of flight test maneuvers, and formulation of the mathematical model are presented. The added effects of the thrust vectoring and single surface excitation systems are also addressed. The results of the longitudinal and lateral directional derivative estimates at varying angles of attack are presented and compared to results from previous analyses. The results indicate a significant improvement due to the independent control surface deflections induced by the single surface excitation system, and at the same time, a need for additional flight data especially at higher angles of attack.

A linear least squares approach for evaluation of crack tip stress field parameters using DIC

NASA Astrophysics Data System (ADS)

Harilal, R.; Vyasarayani, C. P.; Ramji, M.

2015-12-01

In the present work, an experimental study is carried out to estimate the mixed-mode stress intensity factors (SIF) for different cracked specimen configurations using digital image correlation (DIC) technique. For the estimation of mixed-mode SIF's using DIC, a new algorithm is proposed for the extraction of crack tip location and coefficients in the multi-parameter displacement field equations. From those estimated coefficients, SIF could be extracted. The required displacement data surrounding the crack tip has been obtained using 2D-DIC technique. An open source 2D DIC software Ncorr is used for the displacement field extraction. The presented methodology has been used to extract mixed-mode SIF's for specimen configurations like single edge notch (SEN) specimen and centre slant crack (CSC) specimens made out of Al 2014-T6 alloy. The experimental results have been compared with the analytical values and they are found to be in good agreement, thereby confirming the accuracy of the algorithm being proposed.

Robust automatic measurement of 3D scanned models for the human body fat estimation.

PubMed

Giachetti, Andrea; Lovato, Christian; Piscitelli, Francesco; Milanese, Chiara; Zancanaro, Carlo

2015-03-01

In this paper, we present an automatic tool for estimating geometrical parameters from 3-D human scans independent on pose and robustly against the topological noise. It is based on an automatic segmentation of body parts exploiting curve skeleton processing and ad hoc heuristics able to remove problems due to different acquisition poses and body types. The software is able to locate body trunk and limbs, detect their directions, and compute parameters like volumes, areas, girths, and lengths. Experimental results demonstrate that measurements provided by our system on 3-D body scans of normal and overweight subjects acquired in different poses are highly correlated with the body fat estimates obtained on the same subjects with dual-energy X-rays absorptiometry (DXA) scanning. In particular, maximal lengths and girths, not requiring precise localization of anatomical landmarks, demonstrate a good correlation (up to 96%) with the body fat and trunk fat. Regression models based on our automatic measurements can be used to predict body fat values reasonably well.

Modeling Complex Equilibria in ITC Experiments: Thermodynamic Parameters Estimation for a Three Binding Site Model

PubMed Central

Le, Vu H.; Buscaglia, Robert; Chaires, Jonathan B.; Lewis, Edwin A.

2013-01-01

Isothermal Titration Calorimetry, ITC, is a powerful technique that can be used to estimate a complete set of thermodynamic parameters (e.g. Keq (or ΔG), ΔH, ΔS, and n) for a ligand binding interaction described by a thermodynamic model. Thermodynamic models are constructed by combination of equilibrium constant, mass balance, and charge balance equations for the system under study. Commercial ITC instruments are supplied with software that includes a number of simple interaction models, for example one binding site, two binding sites, sequential sites, and n-independent binding sites. More complex models for example, three or more binding sites, one site with multiple binding mechanisms, linked equilibria, or equilibria involving macromolecular conformational selection through ligand binding need to be developed on a case by case basis by the ITC user. In this paper we provide an algorithm (and a link to our MATLAB program) for the non-linear regression analysis of a multiple binding site model with up to four overlapping binding equilibria. Error analysis demonstrates that fitting ITC data for multiple parameters (e.g. up to nine parameters in the three binding site model) yields thermodynamic parameters with acceptable accuracy. PMID:23262283

EOS MLS Level 2 Data Processing Software Version 3

NASA Technical Reports Server (NTRS)

Livesey, Nathaniel J.; VanSnyder, Livesey W.; Read, William G.; Schwartz, Michael J.; Lambert, Alyn; Santee, Michelle L.; Nguyen, Honghanh T.; Froidevaux, Lucien; wang, Shuhui; Manney, Gloria L.;

ISOT_Calc: A versatile tool for parameter estimation in sorption isotherms

NASA Astrophysics Data System (ADS)

Beltrán, José L.; Pignatello, Joseph J.; Teixidó, Marc

2016-09-01

Geochemists and soil chemists commonly use parametrized sorption data to assess transport and impact of pollutants in the environment. However, this evaluation is often hampered by a lack of detailed sorption data analysis, which implies further non-accurate transport modeling. To this end, we present a novel software tool to precisely analyze and interpret sorption isotherm data. Our developed tool, coded in Visual Basic for Applications (VBA), operates embedded within the Microsoft Excel™ environment. It consists of a user-defined function named ISOT_Calc, followed by a supplementary optimization Excel macro (Ref_GN_LM). The ISOT_Calc function estimates the solute equilibrium concentration in the aqueous and solid phases (Ce and q, respectively). Hence, it represents a very flexible way in the optimization of the sorption isotherm parameters, as it can be carried out over the residuals of q, Ce, or both simultaneously (i.e., orthogonal distance regression). The developed function includes the most usual sorption isotherm models, as predefined equations, as well as the possibility to easily introduce custom-defined ones. Regarding the Ref_GN_LM macro, it allows the parameter optimization by using a Levenberg-Marquardt modified Gauss-Newton iterative procedure. In order to evaluate the performance of the presented tool, both function and optimization macro have been applied to different sorption data examples described in the literature. Results showed that the optimization of the isotherm parameters was successfully achieved in all cases, indicating the robustness and reliability of the developed tool. Thus, the presented software tool, available to researchers and students for free, has proven to be a user-friendly and an interesting alternative to conventional fitting tools used in sorption data analysis.

AU-FREDI - AUTONOMOUS FREQUENCY DOMAIN IDENTIFICATION

NASA Technical Reports Server (NTRS)

Yam, Y.

1994-01-01

The Autonomous Frequency Domain Identification program, AU-FREDI, is a system of methods, algorithms and software that was developed for the identification of structural dynamic parameters and system transfer function characterization for control of large space platforms and flexible spacecraft. It was validated in the CALTECH/Jet Propulsion Laboratory's Large Spacecraft Control Laboratory. Due to the unique characteristics of this laboratory environment, and the environment-specific nature of many of the software's routines, AU-FREDI should be considered to be a collection of routines which can be modified and reassembled to suit system identification and control experiments on large flexible structures. The AU-FREDI software was originally designed to command plant excitation and handle subsequent input/output data transfer, and to conduct system identification based on the I/O data. Key features of the AU-FREDI methodology are as follows: 1. AU-FREDI has on-line digital filter design to support on-orbit optimal input design and data composition. 2. Data composition of experimental data in overlapping frequency bands overcomes finite actuator power constraints. 3. Recursive least squares sine-dwell estimation accurately handles digitized sinusoids and low frequency modes. 4. The system also includes automated estimation of model order using a product moment matrix. 5. A sample-data transfer function parametrization supports digital control design. 6. Minimum variance estimation is assured with a curve fitting algorithm with iterative reweighting. 7. Robust root solvers accurately factorize high order polynomials to determine frequency and damping estimates. 8. Output error characterization of model additive uncertainty supports robustness analysis. The research objectives associated with AU-FREDI were particularly useful in focusing the identification methodology for realistic on-orbit testing conditions. Rather than estimating the entire structure, as is typically done in ground structural testing, AU-FREDI identifies only the key transfer function parameters and uncertainty bounds that are necessary for on-line design and tuning of robust controllers. AU-FREDI's system identification algorithms are independent of the JPL-LSCL environment, and can easily be extracted and modified for use with input/output data files. The basic approach of AU-FREDI's system identification algorithms is to non-parametrically identify the sampled data in the frequency domain using either stochastic or sine-dwell input, and then to obtain a parametric model of the transfer function by curve-fitting techniques. A cross-spectral analysis of the output error is used to determine the additive uncertainty in the estimated transfer function. The nominal transfer function estimate and the estimate of the associated additive uncertainty can be used for robust control analysis and design. AU-FREDI's I/O data transfer routines are tailored to the environment of the CALTECH/ JPL-LSCL which included a special operating system to interface with the testbed. Input commands for a particular experiment (wideband, narrowband, or sine-dwell) were computed on-line and then issued to respective actuators by the operating system. The operating system also took measurements through displacement sensors and passed them back to the software for storage and off-line processing. In order to make use of AU-FREDI's I/O data transfer routines, a user would need to provide an operating system capable of overseeing such functions between the software and the experimental setup at hand. The program documentation contains information designed to support users in either providing such an operating system or modifying the system identification algorithms for use with input/output data files. It provides a history of the theoretical, algorithmic and software development efforts including operating system requirements and listings of some of the various special purpose subroutines which were developed and optimized for Lahey FORTRAN compilers on IBM PC-AT computers before the subroutines were integrated into the system software. Potential purchasers are encouraged to purchase and review the documentation before purchasing the AU-FREDI software. AU-FREDI is distributed in DEC VAX BACKUP format on a 1600 BPI 9-track magnetic tape (standard media) or a TK50 tape cartridge. AU-FREDI was developed in 1989 and is a copyrighted work with all copyright vested in NASA.

Systems Engineering and Integration (SE and I)

NASA Technical Reports Server (NTRS)

Chevers, ED; Haley, Sam

1990-01-01

The issue of technology advancement and future space transportation vehicles is addressed. The challenge is to develop systems which can be evolved and improved in small incremental steps where each increment reduces present cost, improves, reliability, or does neither but sets the stage for a second incremental upgrade that does. Future requirements are interface standards for commercial off the shelf products to aid in the development of integrated facilities; enhanced automated code generation system slightly coupled to specification and design documentation; modeling tools that support data flow analysis; and shared project data bases consisting of technical characteristics cast information, measurement parameters, and reusable software programs. Topics addressed include: advanced avionics development strategy; risk analysis and management; tool quality management; low cost avionics; cost estimation and benefits; computer aided software engineering; computer systems and software safety; system testability; and advanced avionics laboratories - and rapid prototyping. This presentation is represented by viewgraphs only.

Software Toolbox Development for Rapid Earthquake Source Optimisation Combining InSAR Data and Seismic Waveforms

NASA Astrophysics Data System (ADS)

Isken, Marius P.; Sudhaus, Henriette; Heimann, Sebastian; Steinberg, Andreas; Bathke, Hannes M.

2017-04-01

We present a modular open-source software framework (pyrocko, kite, grond; http://pyrocko.org) for rapid InSAR data post-processing and modelling of tectonic and volcanic displacement fields derived from satellite data. Our aim is to ease and streamline the joint optimisation of earthquake observations from InSAR and GPS data together with seismological waveforms for an improved estimation of the ruptures' parameters. Through this approach we can provide finite models of earthquake ruptures and therefore contribute to a timely and better understanding of earthquake kinematics. The new kite module enables a fast processing of unwrapped InSAR scenes for source modelling: the spatial sub-sampling and data error/noise estimation for the interferogram is evaluated automatically and interactively. The rupture's near-field surface displacement data are then combined with seismic far-field waveforms and jointly modelled using the pyrocko.gf framwork, which allows for fast forward modelling based on pre-calculated elastodynamic and elastostatic Green's functions. Lastly the grond module supplies a bootstrap-based probabilistic (Monte Carlo) joint optimisation to estimate the parameters and uncertainties of a finite-source earthquake rupture model. We describe the developed and applied methods as an effort to establish a semi-automatic processing and modelling chain. The framework is applied to Sentinel-1 data from the 2016 Central Italy earthquake sequence, where we present the earthquake mechanism and rupture model from which we derive regions of increased coulomb stress. The open source software framework is developed at GFZ Potsdam and at the University of Kiel, Germany, it is written in Python and C programming languages. The toolbox architecture is modular and independent, and can be utilized flexibly for a variety of geophysical problems. This work is conducted within the BridGeS project (http://www.bridges.uni-kiel.de) funded by the German Research Foundation DFG through an Emmy-Noether grant.

Software Size Estimation Using Expert Estimation: A Fuzzy Logic Approach

ERIC Educational Resources Information Center

Stevenson, Glenn A.

2012-01-01

For decades software managers have been using formal methodologies such as the Constructive Cost Model and Function Points to estimate the effort of software projects during the early stages of project development. While some research shows these methodologies to be effective, many software managers feel that they are overly complicated to use and…

Experimental investigation of dynamic impact of firearm with suppressor

NASA Astrophysics Data System (ADS)

Kilikevicius, Arturas; Skeivalas, Jonas; Jurevicius, Mindaugas; Turla, Vytautas; Kilikeviciene, Kristina; Bureika, Gintautas; Jakstas, Arunas

2017-09-01

The internal ballistics processes occur in the tube during firearm firing. They cause tremendous vibratory shock forces and robust sounds. The determination of these dynamic parameters is relevant in order to reasonably estimate the firearm ergonomic and noise reduction features. The objective of this study is to improve the reliability of the results of measuring a firearm suppressor's dynamic parameters. The analysis of indicator stability is based on an assessment of dynamic parameters and setting the correlation during experimental research. An examination of the spread of intensity of firearm with suppressor dynamic vibration and an analysis of its signals upon applying the theory of covariance functions are carried out in this paper. The results of measuring the intensity of vibrations in fixed points of a firearm and a shooter have been recorded on a time scale in the form of data arrays (matrices). The estimates of covariance functions between the arrays of digital results in measuring the intensity of firearm vibrations and the estimates of covariance functions of single arrays have been calculated upon changing the quantization interval on the time scale. Software Matlab 7 has been applied in the calculation. Finally, basic conclusions are given.

[Simulation and data analysis of stereological modeling based on virtual slices].

PubMed

Wang, Hao; Shen, Hong; Bai, Xiao-yan

2008-05-01

To establish a computer-assisted stereological model for simulating the process of slice section and evaluate the relationship between section surface and estimated three-dimensional structure. The model was designed by mathematic method as a win32 software based on the MFC using Microsoft visual studio as IDE for simulating the infinite process of sections and analysis of the data derived from the model. The linearity of the fitting of the model was evaluated by comparison with the traditional formula. The win32 software based on this algorithm allowed random sectioning of the particles distributed randomly in an ideal virtual cube. The stereological parameters showed very high throughput (>94.5% and 92%) in homogeneity and independence tests. The data of density, shape and size of the section were tested to conform to normal distribution. The output of the model and that from the image analysis system showed statistical correlation and consistency. The algorithm we described can be used for evaluating the stereologic parameters of the structure of tissue slices.

Mars Pathfinder Atmospheric Entry Navigation Operations

NASA Technical Reports Server (NTRS)

Braun, R. D.; Spencer, D. A.; Kallemeyn, P. H.; Vaughan, R. M.

1997-01-01

On July 4, 1997, after traveling close to 500 million km, the Pathfinder spacecraft successfully completed entry, descent, and landing, coming to rest on the surface of Mars just 27 km from its target point. In the present paper, the atmospheric entry and approach navigation activities required in support of this mission are discussed. In particular, the flight software parameter update and landing site prediction analyses performed by the Pathfinder operations navigation team are described. A suite of simulation tools developed during Pathfinder's design cycle, but extendible to Pathfinder operations, are also presented. Data regarding the accuracy of the primary parachute deployment algorithm is extracted from the Pathfinder flight data, demonstrating that this algorithm performed as predicted. The increased probability of mission success through the software parameter update process is discussed. This paper also demonstrates the importance of modeling atmospheric flight uncertainties in the estimation of an accurate landing site. With these atmospheric effects included, the final landed ellipse prediction differs from the post-flight determined landing site by less then 0.5 km in downtrack.

Bayesian parameter estimation for the Wnt pathway: an infinite mixture models approach.

PubMed

Koutroumpas, Konstantinos; Ballarini, Paolo; Votsi, Irene; Cournède, Paul-Henry

2016-09-01

Likelihood-free methods, like Approximate Bayesian Computation (ABC), have been extensively used in model-based statistical inference with intractable likelihood functions. When combined with Sequential Monte Carlo (SMC) algorithms they constitute a powerful approach for parameter estimation and model selection of mathematical models of complex biological systems. A crucial step in the ABC-SMC algorithms, significantly affecting their performance, is the propagation of a set of parameter vectors through a sequence of intermediate distributions using Markov kernels. In this article, we employ Dirichlet process mixtures (DPMs) to design optimal transition kernels and we present an ABC-SMC algorithm with DPM kernels. We illustrate the use of the proposed methodology using real data for the canonical Wnt signaling pathway. A multi-compartment model of the pathway is developed and it is compared to an existing model. The results indicate that DPMs are more efficient in the exploration of the parameter space and can significantly improve ABC-SMC performance. In comparison to alternative sampling schemes that are commonly used, the proposed approach can bring potential benefits in the estimation of complex multimodal distributions. The method is used to estimate the parameters and the initial state of two models of the Wnt pathway and it is shown that the multi-compartment model fits better the experimental data. Python scripts for the Dirichlet Process Gaussian Mixture model and the Gibbs sampler are available at https://sites.google.com/site/kkoutroumpas/software konstantinos.koutroumpas@ecp.fr. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

COSTMODL: An automated software development cost estimation tool

NASA Technical Reports Server (NTRS)

Roush, George B.

1991-01-01

The cost of developing computer software continues to consume an increasing portion of many organizations' total budgets, both in the public and private sector. As this trend develops, the capability to produce reliable estimates of the effort and schedule required to develop a candidate software product takes on increasing importance. The COSTMODL program was developed to provide an in-house capability to perform development cost estimates for NASA software projects. COSTMODL is an automated software development cost estimation tool which incorporates five cost estimation algorithms including the latest models for the Ada language and incrementally developed products. The principal characteristic which sets COSTMODL apart from other software cost estimation programs is its capacity to be completely customized to a particular environment. The estimation equations can be recalibrated to reflect the programmer productivity characteristics demonstrated by the user's organization, and the set of significant factors which effect software development costs can be customized to reflect any unique properties of the user's development environment. Careful use of a capability such as COSTMODL can significantly reduce the risk of cost overruns and failed projects.

Development of a software framework for data assimilation and its applications for streamflow forecasting in Japan

NASA Astrophysics Data System (ADS)

Noh, S. J.; Tachikawa, Y.; Shiiba, M.; Yorozu, K.; Kim, S.

2012-04-01

Data assimilation methods have received increased attention to accomplish uncertainty assessment and enhancement of forecasting capability in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modeling software are based on a deterministic approach. In this study, we developed a hydrological modeling framework for sequential data assimilation, so called MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modeling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. Sequential data assimilation based on the particle filters is available for any hydrologic models based on MPI-OHyMoS considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for short-term streamflow forecasting of several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and remotely-sensed rainfall data such as X-band or C-band radar is estimated and mitigated in the sequential data assimilation.

Software Transition Project Retrospectives and the Application of SEL Effort Estimation Model and Boehm's COCOMO to Complex Software Transition Projects

NASA Technical Reports Server (NTRS)

McNeill, Justin

1995-01-01

The Multimission Image Processing Subsystem (MIPS) at the Jet Propulsion Laboratory (JPL) has managed transitions of application software sets from one operating system and hardware platform to multiple operating systems and hardware platforms. As a part of these transitions, cost estimates were generated from the personal experience of in-house developers and managers to calculate the total effort required for such projects. Productivity measures have been collected for two such transitions, one very large and the other relatively small in terms of source lines of code. These estimates used a cost estimation model similar to the Software Engineering Laboratory (SEL) Effort Estimation Model. Experience in transitioning software within JPL MIPS have uncovered a high incidence of interface complexity. Interfaces, both internal and external to individual software applications, have contributed to software transition project complexity, and thus to scheduling difficulties and larger than anticipated design work on software to be ported.

Parameter Balancing in Kinetic Models of Cell Metabolism†

PubMed Central

2010-01-01

Kinetic modeling of metabolic pathways has become a major field of systems biology. It combines structural information about metabolic pathways with quantitative enzymatic rate laws. Some of the kinetic constants needed for a model could be collected from ever-growing literature and public web resources, but they are often incomplete, incompatible, or simply not available. We address this lack of information by parameter balancing, a method to complete given sets of kinetic constants. Based on Bayesian parameter estimation, it exploits the thermodynamic dependencies among different biochemical quantities to guess realistic model parameters from available kinetic data. Our algorithm accounts for varying measurement conditions in the input data (pH value and temperature). It can process kinetic constants and state-dependent quantities such as metabolite concentrations or chemical potentials, and uses prior distributions and data augmentation to keep the estimated quantities within plausible ranges. An online service and free software for parameter balancing with models provided in SBML format (Systems Biology Markup Language) is accessible at www.semanticsbml.org. We demonstrate its practical use with a small model of the phosphofructokinase reaction and discuss its possible applications and limitations. In the future, parameter balancing could become an important routine step in the kinetic modeling of large metabolic networks. PMID:21038890

Systematic parameter estimation in data-rich environments for cell signalling dynamics

PubMed Central

Nim, Tri Hieu; Luo, Le; Clément, Marie-Véronique; White, Jacob K.; Tucker-Kellogg, Lisa

2013-01-01

Motivation: Computational models of biological signalling networks, based on ordinary differential equations (ODEs), have generated many insights into cellular dynamics, but the model-building process typically requires estimating rate parameters based on experimentally observed concentrations. New proteomic methods can measure concentrations for all molecular species in a pathway; this creates a new opportunity to decompose the optimization of rate parameters. Results: In contrast with conventional parameter estimation methods that minimize the disagreement between simulated and observed concentrations, the SPEDRE method fits spline curves through observed concentration points, estimates derivatives and then matches the derivatives to the production and consumption of each species. This reformulation of the problem permits an extreme decomposition of the high-dimensional optimization into a product of low-dimensional factors, each factor enforcing the equality of one ODE at one time slice. Coarsely discretized solutions to the factors can be computed systematically. Then the discrete solutions are combined using loopy belief propagation, and refined using local optimization. SPEDRE has unique asymptotic behaviour with runtime polynomial in the number of molecules and timepoints, but exponential in the degree of the biochemical network. SPEDRE performance is comparatively evaluated on a novel model of Akt activation dynamics including redox-mediated inactivation of PTEN (phosphatase and tensin homologue). Availability and implementation: Web service, software and supplementary information are available at www.LtkLab.org/SPEDRE Supplementary information: Supplementary data are available at Bioinformatics online. Contact: LisaTK@nus.edu.sg PMID:23426255

Galileo spacecraft autonomous attitude determination using a V-slit star scanner

NASA Technical Reports Server (NTRS)

Mobasser, Sohrab; Lin, Shuh-Ren

1991-01-01

The autonomous attitude determination system of Galileo spacecraft, consisting of a radiation hardened star scanner and a processing algorithm is presented. The algorithm applying to this system are the sequential star identification and attitude estimation. The star scanner model is reviewed in detail and the flight software parameters that must be updated frequently during flight, due to degradation of the scanner response and the star background change are identified.

Observation model and parameter partials for the JPL VLBI parameter estimation software MODEST/1991

NASA Technical Reports Server (NTRS)

Sovers, O. J.

1991-01-01

A revision is presented of MASTERFIT-1987, which it supersedes. Changes during 1988 to 1991 included introduction of the octupole component of solid Earth tides, the NUVEL tectonic motion model, partial derivatives for the precession constant and source position rates, the option to correct for source structure, a refined model for antenna offsets, modeling the unique antenna at Richmond, FL, improved nutation series due to Zhu, Groten, and Reigber, and reintroduction of the old (Woolard) nutation series for simulation purposes. Text describing the relativistic transformations and gravitational contributions to the delay model was also revised in order to reflect the computer code more faithfully.

Distribution of smile line, gingival angle and tooth shape among the Saudi Arabian subpopulation and their association with gingival biotype

PubMed Central

AlQahtani, Nabeeh A.; Haralur, Satheesh B.; AlMaqbol, Mohammad; AlMufarrij, Ali Jubran; Al Dera, Ahmed Ali; Al-Qarni, Mohammed

2016-01-01

Objectives: To determine the occurrence of smile line and maxillary tooth shape in the Saudi Arabian subpopulation, and to estimate the association between these parameters with gingival biotype. Materials and Methods: On the fulfillment of selection criteria, total 315 patients belong to Saudi Arabian ethnic group were randomly selected. Two frontal photographs of the patients were acquired. The tooth morphology, gingival angle, and smile line classification were determined with ImageJ image analyzing software. The gingival biotype was assessed by probe transparency method. The obtained data were analyzed with SPSS 19 (IBM Corporation, New York, USA) software to determine the frequency and association between other parameters and gingival biotype. Results: Among the clinical parameters evaluated, the tapering tooth morphology (56.8%), thick gingival biotype (53%), and average smile line (57.5%) was more prevalent. The statistically significant association was found between thick gingival biotype and the square tooth, high smile line. The high gingival angle was associated with thin gingival biotype. Conclusions: The study results indicate the existence of an association between tooth shape, smile line, and gingival angle with gingival biotype. PMID:27195228

Development and validation of open-source software for DNA mixture interpretation based on a quantitative continuous model

PubMed Central

Manabe, Sho; Morimoto, Chie; Hamano, Yuya; Fujimoto, Shuntaro

2017-01-01

In criminal investigations, forensic scientists need to evaluate DNA mixtures. The estimation of the number of contributors and evaluation of the contribution of a person of interest (POI) from these samples are challenging. In this study, we developed a new open-source software “Kongoh” for interpreting DNA mixture based on a quantitative continuous model. The model uses quantitative information of peak heights in the DNA profile and considers the effect of artifacts and allelic drop-out. By using this software, the likelihoods of 1–4 persons’ contributions are calculated, and the most optimal number of contributors is automatically determined; this differs from other open-source software. Therefore, we can eliminate the need to manually determine the number of contributors before the analysis. Kongoh also considers allele- or locus-specific effects of biological parameters based on the experimental data. We then validated Kongoh by calculating the likelihood ratio (LR) of a POI’s contribution in true contributors and non-contributors by using 2–4 person mixtures analyzed through a 15 short tandem repeat typing system. Most LR values obtained from Kongoh during true-contributor testing strongly supported the POI’s contribution even for small amounts or degraded DNA samples. Kongoh correctly rejected a false hypothesis in the non-contributor testing, generated reproducible LR values, and demonstrated higher accuracy of the estimated number of contributors than another software based on the quantitative continuous model. Therefore, Kongoh is useful in accurately interpreting DNA evidence like mixtures and small amounts or degraded DNA samples. PMID:29149210

Development and validation of open-source software for DNA mixture interpretation based on a quantitative continuous model.

PubMed

Manabe, Sho; Morimoto, Chie; Hamano, Yuya; Fujimoto, Shuntaro; Tamaki, Keiji

2017-01-01

In criminal investigations, forensic scientists need to evaluate DNA mixtures. The estimation of the number of contributors and evaluation of the contribution of a person of interest (POI) from these samples are challenging. In this study, we developed a new open-source software "Kongoh" for interpreting DNA mixture based on a quantitative continuous model. The model uses quantitative information of peak heights in the DNA profile and considers the effect of artifacts and allelic drop-out. By using this software, the likelihoods of 1-4 persons' contributions are calculated, and the most optimal number of contributors is automatically determined; this differs from other open-source software. Therefore, we can eliminate the need to manually determine the number of contributors before the analysis. Kongoh also considers allele- or locus-specific effects of biological parameters based on the experimental data. We then validated Kongoh by calculating the likelihood ratio (LR) of a POI's contribution in true contributors and non-contributors by using 2-4 person mixtures analyzed through a 15 short tandem repeat typing system. Most LR values obtained from Kongoh during true-contributor testing strongly supported the POI's contribution even for small amounts or degraded DNA samples. Kongoh correctly rejected a false hypothesis in the non-contributor testing, generated reproducible LR values, and demonstrated higher accuracy of the estimated number of contributors than another software based on the quantitative continuous model. Therefore, Kongoh is useful in accurately interpreting DNA evidence like mixtures and small amounts or degraded DNA samples.

Examples of testing global identifiability of biological and biomedical models with the DAISY software.

PubMed

Saccomani, Maria Pia; Audoly, Stefania; Bellu, Giuseppina; D'Angiò, Leontina

2010-04-01

DAISY (Differential Algebra for Identifiability of SYstems) is a recently developed computer algebra software tool which can be used to automatically check global identifiability of (linear and) nonlinear dynamic models described by differential equations involving polynomial or rational functions. Global identifiability is a fundamental prerequisite for model identification which is important not only for biological or medical systems but also for many physical and engineering systems derived from first principles. Lack of identifiability implies that the parameter estimation techniques may not fail but any obtained numerical estimates will be meaningless. The software does not require understanding of the underlying mathematical principles and can be used by researchers in applied fields with a minimum of mathematical background. We illustrate the DAISY software by checking the a priori global identifiability of two benchmark nonlinear models taken from the literature. The analysis of these two examples includes comparison with other methods and demonstrates how identifiability analysis is simplified by this tool. Thus we illustrate the identifiability analysis of other two examples, by including discussion of some specific aspects related to the role of observability and knowledge of initial conditions in testing identifiability and to the computational complexity of the software. The main focus of this paper is not on the description of the mathematical background of the algorithm, which has been presented elsewhere, but on illustrating its use and on some of its more interesting features. DAISY is available on the web site http://www.dei.unipd.it/ approximately pia/. 2010 Elsevier Ltd. All rights reserved.

Cost and schedule estimation study report

NASA Technical Reports Server (NTRS)

Condon, Steve; Regardie, Myrna; Stark, Mike; Waligora, Sharon

1993-01-01

This report describes the analysis performed and the findings of a study of the software development cost and schedule estimation models used by the Flight Dynamics Division (FDD), Goddard Space Flight Center. The study analyzes typical FDD projects, focusing primarily on those developed since 1982. The study reconfirms the standard SEL effort estimation model that is based on size adjusted for reuse; however, guidelines for the productivity and growth parameters in the baseline effort model have been updated. The study also produced a schedule prediction model based on empirical data that varies depending on application type. Models for the distribution of effort and schedule by life-cycle phase are also presented. Finally, this report explains how to use these models to plan SEL projects.

Ask Pete, software planning and estimation through project characterization

NASA Technical Reports Server (NTRS)

Kurtz, T.

2001-01-01

Ask Pete, was developed by NASA to provide a tool for integrating the estimation and planning activities for a software development effort. It incorporates COCOMO II estimating with NASA's software development practices and IV&V criteria to characterize a project. This characterization is then used to generate estimates and tailored planning documents.

Comment on "High resolution coherence analysis between planetary and climate oscillations"

NASA Astrophysics Data System (ADS)

Holm, Sverre

2018-07-01

The paper by Scafetta entitled "High resolution coherence analysis between planetary and climate oscillations", May 2016 claims coherence between planetary movements and the global temperature anomaly. The claim is based on data analysis using the canonical covariance analysis (CCA) estimator for the magnitude squared coherence (MSC). It assumes a model with a predetermined number of sinusoids for the climate data. The results are highly dependent on this prior assumption, and may therefore be criticized for being based on the opposite of a null hypothesis. More importantly, since values of key parameters in the CCA method are not given, some experiments have been performed using the software of the original authors of the CCA estimator. The purpose was to replicate the results of Scafetta using what was perceived to be the most probable parameter values. Despite best efforts, this was not possible.

MO-F-CAMPUS-I-01: A System for Automatically Calculating Organ and Effective Dose for Fluoroscopically-Guided Procedures

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

Xiong, Z; Vijayan, S; Rana, V

2015-06-15

Purpose: A system was developed that automatically calculates the organ and effective dose for individual fluoroscopically-guided procedures using a log of the clinical exposure parameters. Methods: We have previously developed a dose tracking system (DTS) to provide a real-time color-coded 3D- mapping of skin dose. This software produces a log file of all geometry and exposure parameters for every x-ray pulse during a procedure. The data in the log files is input into PCXMC, a Monte Carlo program that calculates organ and effective dose for projections and exposure parameters set by the user. We developed a MATLAB program to readmore » data from the log files produced by the DTS and to automatically generate the definition files in the format used by PCXMC. The processing is done at the end of a procedure after all exposures are completed. Since there are thousands of exposure pulses with various parameters for fluoroscopy, DA and DSA and at various projections, the data for exposures with similar parameters is grouped prior to entry into PCXMC to reduce the number of Monte Carlo calculations that need to be performed. Results: The software developed automatically transfers data from the DTS log file to PCXMC and runs the program for each grouping of exposure pulses. When the dose from all exposure events are calculated, the doses for each organ and all effective doses are summed to obtain procedure totals. For a complicated interventional procedure, the calculations can be completed on a PC without manual intervention in less than 30 minutes depending on the level of data grouping. Conclusion: This system allows organ dose to be calculated for individual procedures for every patient without tedious calculations or data entry so that estimates of stochastic risk can be obtained in addition to the deterministic risk estimate provided by the DTS. Partial support from NIH grant R01EB002873 and Toshiba Medical Systems Corp.« less

VLBI-SLR Combination Solution Using GEODYN

NASA Technical Reports Server (NTRS)

MacMillan, Dan; Pavlis, Despina; Lemoine, Frank; Chinn, Douglas; Rowlands, David

2010-01-01

We would like to generate a multi-technique solution combining all of the geodetic techniques (VLBI, SLR, GPS, and DORIS) using the same software and using the same a priori models. Here we use GEODYN software and consider only the VLBI-SLR combination. Here we report initial results of our work on the combination. We first performed solutions with GEODYN using only VLBI data and found that VLBI EOP solution results produced with GEODYN agree with results using CALC/SOLVE at the 1-sigma level. We then combined the VLBI normal equations in GEODYN with weekly SLR normal equations for the period 2007-2008. Agreement of estimated Earth orientation parameters with IERS C04 were not significantly different for the VLBI-only, SLR-only, and VLBI+SLR solutions

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

Salama, A.; Mikhail, M.

Comprehensive software packages have been developed at the Western Research Centre as tools to help coal preparation engineers analyze, evaluate, and control coal cleaning processes. The COal Preparation Software package (COPS) performs three functions: (1) data handling and manipulation, (2) data analysis, including the generation of washability data, performance evaluation and prediction, density and size modeling, evaluation of density and size partition characteristics and attrition curves, and (3) generation of graphics output. The Separation ChARacteristics Estimation software packages (SCARE) are developed to balance raw density or size separation data. The cases of density and size separation data are considered. Themore » generated balanced data can take the balanced or normalized forms. The scaled form is desirable for direct determination of the partition functions (curves). The raw and generated separation data are displayed in tabular and/or graphical forms. The computer softwares described in this paper are valuable tools for coal preparation plant engineers and operators for evaluating process performance, adjusting plant parameters, and balancing raw density or size separation data. These packages have been applied very successfully in many projects carried out by WRC for the Canadian coal preparation industry. The software packages are designed to run on a personal computer (PC).« less

A Toolkit to Study Sensitivity of the Geant4 Predictions to the Variations of the Physics Model Parameters

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

Fields, Laura; Genser, Krzysztof; Hatcher, Robert

Geant4 is the leading detector simulation toolkit used in high energy physics to design detectors and to optimize calibration and reconstruction software. It employs a set of carefully validated physics models to simulate interactions of particles with matter across a wide range of interaction energies. These models, especially the hadronic ones, rely largely on directly measured cross-sections and phenomenological predictions with physically motivated parameters estimated by theoretical calculation or measurement. Because these models are tuned to cover a very wide range of possible simulation tasks, they may not always be optimized for a given process or a given material. Thismore » raises several critical questions, e.g. how sensitive Geant4 predictions are to the variations of the model parameters, or what uncertainties are associated with a particular tune of a Geant4 physics model, or a group of models, or how to consistently derive guidance for Geant4 model development and improvement from a wide range of available experimental data. We have designed and implemented a comprehensive, modular, user-friendly software toolkit to study and address such questions. It allows one to easily modify parameters of one or several Geant4 physics models involved in the simulation, and to perform collective analysis of multiple variants of the resulting physics observables of interest and comparison against a variety of corresponding experimental data. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. flexible run-time configurable workflow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented and illustrated with results obtained with Geant4 key hadronic models.« less

Functional Mixed Effects Model for Small Area Estimation.

PubMed

Maiti, Tapabrata; Sinha, Samiran; Zhong, Ping-Shou

2016-09-01

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fit a varying coefficient linear mixed effect model where the varying coefficients are semi-parametrically modeled via B-splines. We propose a method of estimating the fixed effect parameters and consider prediction of random effects that can be implemented using a standard software. For measuring prediction uncertainties, we derive an analytical expression for the mean squared errors, and propose a method of estimating the mean squared errors. The procedure is illustrated via a real data example, and operating characteristics of the method are judged using finite sample simulation studies.

Parallel computers - Estimate errors caused by imprecise data

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik; Bernat, Andrew; Villa, Elsa; Mariscal, Yvonne

1991-01-01

A new approach to the problem of estimating errors caused by imprecise data is proposed in the context of software engineering. A software device is used to produce an ideal solution to the problem, when the computer is capable of computing errors of arbitrary programs. The software engineering aspect of this problem is to describe a device for computing the error estimates in software terms and then to provide precise numbers with error estimates to the user. The feasibility of the program capable of computing both some quantity and its error estimate in the range of possible measurement errors is demonstrated.

A Novel Rules Based Approach for Estimating Software Birthmark

PubMed Central

Binti Alias, Norma; Anwar, Sajid

2015-01-01

Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark. PMID:25945363

A Project Management Approach to Using Simulation for Cost Estimation on Large, Complex Software Development Projects

NASA Technical Reports Server (NTRS)

Mizell, Carolyn; Malone, Linda

2007-01-01

It is very difficult for project managers to develop accurate cost and schedule estimates for large, complex software development projects. None of the approaches or tools available today can estimate the true cost of software with any high degree of accuracy early in a project. This paper provides an approach that utilizes a software development process simulation model that considers and conveys the level of uncertainty that exists when developing an initial estimate. A NASA project will be analyzed using simulation and data from the Software Engineering Laboratory to show the benefits of such an approach.

Status and plans for the future of the Vienna VLBI Software

NASA Astrophysics Data System (ADS)

Madzak, Matthias; Böhm, Johannes; Böhm, Sigrid; Girdiuk, Anastasiia; Hellerschmied, Andreas; Hofmeister, Armin; Krasna, Hana; Kwak, Younghee; Landskron, Daniel; Mayer, David; McCallum, Jamie; Plank, Lucia; Schönberger, Caroline; Shabala, Stanislav; Sun, Jing; Teke, Kamil

2016-04-01

The Vienna VLBI Software (VieVS) is a VLBI analysis software developed and maintained at Technische Universität Wien (TU Wien) since 2008 with contributions from groups all over the world. It is used for both academic purposes in university courses as well as for providing VLBI analysis results to the geodetic community. Written in a modular structure in Matlab, VieVS offers easy access to the source code and the possibility to adapt the programs for particular purposes. The new version 2.3, released in December 2015, includes several new parameters to be estimated in the global solution, such as tidal ERP variation coefficients. The graphical user interface was slightly modified for an improved user functionality and, e.g., the possibility of deriving baseline length repeatabilities. The scheduling of satellite observations was refined, the simulator newly includes the effect of source structure which can also be corrected for in the analysis. This poster gives an overview of all VLBI-related activities in Vienna and provides an outlook to future plans concerning the Vienna VLBI Software.

A dose-response curve for biodosimetry from a 6 MV electron linear accelerator

PubMed Central

Lemos-Pinto, M.M.P.; Cadena, M.; Santos, N.; Fernandes, T.S.; Borges, E.; Amaral, A.

2015-01-01

Biological dosimetry (biodosimetry) is based on the investigation of radiation-induced biological effects (biomarkers), mainly dicentric chromosomes, in order to correlate them with radiation dose. To interpret the dicentric score in terms of absorbed dose, a calibration curve is needed. Each curve should be constructed with respect to basic physical parameters, such as the type of ionizing radiation characterized by low or high linear energy transfer (LET) and dose rate. This study was designed to obtain dose calibration curves by scoring of dicentric chromosomes in peripheral blood lymphocytes irradiated in vitro with a 6 MV electron linear accelerator (Mevatron M, Siemens, USA). Two software programs, CABAS (Chromosomal Aberration Calculation Software) and Dose Estimate, were used to generate the curve. The two software programs are discussed; the results obtained were compared with each other and with other published low LET radiation curves. Both software programs resulted in identical linear and quadratic terms for the curve presented here, which was in good agreement with published curves for similar radiation quality and dose rates. PMID:26445334

An Introduction to Goodness of Fit for PMU Parameter Estimation

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

Riepnieks, Artis; Kirkham, Harold

2017-10-01

New results of measurements of phasor-like signals are presented based on our previous work on the topic. In this document an improved estimation method is described. The algorithm (which is realized in MATLAB software) is discussed. We examine the effect of noisy and distorted signals on the Goodness of Fit metric. The estimation method is shown to be performing very well with clean data and with a measurement window as short as a half a cycle and as few as 5 samples per cycle. The Goodness of Fit decreases predictably with added phase noise, and seems to be acceptable evenmore » with visible distortion in the signal. While the exact results we obtain are specific to our method of estimation, the Goodness of Fit method could be implemented in any phasor measurement unit.« less

Development of the FITS tools package for multiple software environments

NASA Technical Reports Server (NTRS)

Pence, W. D.; Blackburn, J. K.

1992-01-01

The HEASARC is developing a package of general purpose software for analyzing data files in FITS format. This paper describes the design philosophy which makes the software both machine-independent (it runs on VAXs, Suns, and DEC-stations) and software environment-independent. Currently the software can be compiled and linked to produce IRAF tasks, or alternatively, the same source code can be used to generate stand-alone tasks using one of two implementations of a user-parameter interface library. The machine independence of the software is achieved by writing the source code in ANSI standard Fortran or C, using the machine-independent FITSIO subroutine interface for all data file I/O, and using a standard user-parameter subroutine interface for all user I/O. The latter interface is based on the Fortran IRAF Parameter File interface developed at STScI. The IRAF tasks are built by linking to the IRAF implementation of this parameter interface library. Two other implementations of this parameter interface library, which have no IRAF dependencies, are now available which can be used to generate stand-alone executable tasks. These stand-alone tasks can simply be executed from the machine operating system prompt either by supplying all the task parameters on the command line or by entering the task name after which the user will be prompted for any required parameters. A first release of this FTOOLS package is now publicly available. The currently available tasks are described, along with instructions on how to obtain a copy of the software.

Algorithm for fast event parameters estimation on GEM acquired data

NASA Astrophysics Data System (ADS)

Linczuk, Paweł; Krawczyk, Rafał D.; Poźniak, Krzysztof T.; Kasprowicz, Grzegorz; Wojeński, Andrzej; Chernyshova, Maryna; Czarski, Tomasz

2016-09-01

We present study of a software-hardware environment for developing fast computation with high throughput and low latency methods, which can be used as back-end in High Energy Physics (HEP) and other High Performance Computing (HPC) systems, based on high amount of input from electronic sensor based front-end. There is a parallelization possibilities discussion and testing on Intel HPC solutions with consideration of applications with Gas Electron Multiplier (GEM) measurement systems presented in this paper.

Bayesian Treatment of Uncertainty in Environmental Modeling: Optimization, Sampling and Data Assimilation Using the DREAM Software Package

NASA Astrophysics Data System (ADS)

Vrugt, J. A.

2012-12-01

In the past decade much progress has been made in the treatment of uncertainty in earth systems modeling. Whereas initial approaches has focused mostly on quantification of parameter and predictive uncertainty, recent methods attempt to disentangle the effects of parameter, forcing (input) data, model structural and calibration data errors. In this talk I will highlight some of our recent work involving theory, concepts and applications of Bayesian parameter and/or state estimation. In particular, new methods for sequential Monte Carlo (SMC) and Markov Chain Monte Carlo (MCMC) simulation will be presented with emphasis on massively parallel distributed computing and quantification of model structural errors. The theoretical and numerical developments will be illustrated using model-data synthesis problems in hydrology, hydrogeology and geophysics.

ExpertEyes: open-source, high-definition eyetracking.

PubMed

Parada, Francisco J; Wyatte, Dean; Yu, Chen; Akavipat, Ruj; Emerick, Brandi; Busey, Thomas

2015-03-01

ExpertEyes is a low-cost, open-source package of hardware and software that is designed to provide portable high-definition eyetracking. The project involves several technological innovations, including portability, high-definition video recording, and multiplatform software support. It was designed for challenging recording environments, and all processing is done offline to allow for optimization of parameter estimation. The pupil and corneal reflection are estimated using a novel forward eye model that simultaneously fits both the pupil and the corneal reflection with full ellipses, addressing a common situation in which the corneal reflection sits at the edge of the pupil and therefore breaks the contour of the ellipse. The accuracy and precision of the system are comparable to or better than what is available in commercial eyetracking systems, with a typical accuracy of less than 0.4° and best accuracy below 0.3°, and with a typical precision (SD method) around 0.3° and best precision below 0.2°. Part of the success of the system comes from a high-resolution eye image. The high image quality results from uncasing common digital camcorders and recording directly to SD cards, which avoids the limitations of the analog NTSC format. The software is freely downloadable, and complete hardware plans are available, along with sources for custom parts.

www.common-metrics.org: a web application to estimate scores from different patient-reported outcome measures on a common scale.

PubMed

Fischer, H Felix; Rose, Matthias

2016-10-19

Recently, a growing number of Item-Response Theory (IRT) models has been published, which allow estimation of a common latent variable from data derived by different Patient Reported Outcomes (PROs). When using data from different PROs, direct estimation of the latent variable has some advantages over the use of sum score conversion tables. It requires substantial proficiency in the field of psychometrics to fit such models using contemporary IRT software. We developed a web application ( http://www.common-metrics.org ), which allows estimation of latent variable scores more easily using IRT models calibrating different measures on instrument independent scales. Currently, the application allows estimation using six different IRT models for Depression, Anxiety, and Physical Function. Based on published item parameters, users of the application can directly estimate latent trait estimates using expected a posteriori (EAP) for sum scores as well as for specific response patterns, Bayes modal (MAP), Weighted likelihood estimation (WLE) and Maximum likelihood (ML) methods and under three different prior distributions. The obtained estimates can be downloaded and analyzed using standard statistical software. This application enhances the usability of IRT modeling for researchers by allowing comparison of the latent trait estimates over different PROs, such as the Patient Health Questionnaire Depression (PHQ-9) and Anxiety (GAD-7) scales, the Center of Epidemiologic Studies Depression Scale (CES-D), the Beck Depression Inventory (BDI), PROMIS Anxiety and Depression Short Forms and others. Advantages of this approach include comparability of data derived with different measures and tolerance against missing values. The validity of the underlying models needs to be investigated in the future.

TU-H-CAMPUS-IeP1-03: Comparison of Monte Carlo Simulation and Conversion Factor Based Method On Estimation of Effective Dose in Pediatric Patients Undergoing Interventional Cardiac Procedures

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

Leung, K; Wong, M; Ng, Y

Purpose: Interventional cardiac procedures utilize frequent fluoroscopy and cineangiography, which impose considerable radiation risk to patients, especially pediatric patients. Accurate calculation of effective dose is important in order to estimate cancer risk over the rest of their lifetime. This study evaluates the difference in effective dose calculated by Monte Carlo simulation with those estimated by locally-derived conversion factors (CF-local) and by commonly quoted conversion factors from Karambatsakidou et al (CF-K). Methods: Effective dose (E),of 12 pediatric patients, age between 2.5–19 years old, who had undergone interventional cardiac procedures, were calculated using PCXMC-2.0 software. Tube spectrum, irradiation geometry, exposure parameters andmore » dose-area product (DAP) of each projection were included in the software calculation. Effective doses for each patient were also estimated by two Methods: 1) CF-local: conversion factor derived locally by generalizing results of 12 patients, multiplied by DAP of each patient gives E-local. 2) CF-K: selected factor from above-mentioned literature, multiplied by DAP of each patient gives E-K. Results: Mean of E, E-local and E-K were 16.01 mSv, 16.80 mSv and 22.25 mSv respectively. A deviation of −29.35% to +34.85% between E and E-local, while a greater deviation of −28.96% to +60.86% between E and EK were observed. E-K overestimated the effective dose for patients at age 7.5–19. Conclusion: Effective dose obtained by conversion factors is simple and quick to estimate radiation risk of pediatric patients. This study showed that estimation by CF-local may bear an error of 35% when compared with Monte Carlo calculation. If using conversion factors derived by other studies may result in an even greater error, of up to 60%, due to factors that are not catered for in the estimation, including patient size, projection angles, exposure parameters, tube filtration, etc. Users must be aware of these potential inaccuracies when simple conversion method is employed.« less

Probabilistic segmentation and intensity estimation for microarray images.

PubMed

Gottardo, Raphael; Besag, Julian; Stephens, Matthew; Murua, Alejandro

2006-01-01

We describe a probabilistic approach to simultaneous image segmentation and intensity estimation for complementary DNA microarray experiments. The approach overcomes several limitations of existing methods. In particular, it (a) uses a flexible Markov random field approach to segmentation that allows for a wider range of spot shapes than existing methods, including relatively common 'doughnut-shaped' spots; (b) models the image directly as background plus hybridization intensity, and estimates the two quantities simultaneously, avoiding the common logical error that estimates of foreground may be less than those of the corresponding background if the two are estimated separately; and (c) uses a probabilistic modeling approach to simultaneously perform segmentation and intensity estimation, and to compute spot quality measures. We describe two approaches to parameter estimation: a fast algorithm, based on the expectation-maximization and the iterated conditional modes algorithms, and a fully Bayesian framework. These approaches produce comparable results, and both appear to offer some advantages over other methods. We use an HIV experiment to compare our approach to two commercial software products: Spot and Arrayvision.

Addressing the impact of environmental uncertainty in plankton model calibration with a dedicated software system: the Marine Model Optimization Testbed (MarMOT 1.1 alpha)

NASA Astrophysics Data System (ADS)

Hemmings, J. C. P.; Challenor, P. G.

2012-04-01

A wide variety of different plankton system models have been coupled with ocean circulation models, with the aim of understanding and predicting aspects of environmental change. However, an ability to make reliable inferences about real-world processes from the model behaviour demands a quantitative understanding of model error that remains elusive. Assessment of coupled model output is inhibited by relatively limited observing system coverage of biogeochemical components. Any direct assessment of the plankton model is further inhibited by uncertainty in the physical state. Furthermore, comparative evaluation of plankton models on the basis of their design is inhibited by the sensitivity of their dynamics to many adjustable parameters. Parameter uncertainty has been widely addressed by calibrating models at data-rich ocean sites. However, relatively little attention has been given to quantifying uncertainty in the physical fields required by the plankton models at these sites, and tendencies in the biogeochemical properties due to the effects of horizontal processes are often neglected. Here we use model twin experiments, in which synthetic data are assimilated to estimate a system's known "true" parameters, to investigate the impact of error in a plankton model's environmental input data. The experiments are supported by a new software tool, the Marine Model Optimization Testbed, designed for rigorous analysis of plankton models in a multi-site 1-D framework. Simulated errors are derived from statistical characterizations of the mixed layer depth, the horizontal flux divergence tendencies of the biogeochemical tracers and the initial state. Plausible patterns of uncertainty in these data are shown to produce strong temporal and spatial variability in the expected simulation error variance over an annual cycle, indicating variation in the significance attributable to individual model-data differences. An inverse scheme using ensemble-based estimates of the simulation error variance to allow for this environment error performs well compared with weighting schemes used in previous calibration studies, giving improved estimates of the known parameters. The efficacy of the new scheme in real-world applications will depend on the quality of statistical characterizations of the input data. Practical approaches towards developing reliable characterizations are discussed.

Forest height estimation from mountain forest areas using general model-based decomposition for polarimetric interferometric synthetic aperture radar images

NASA Astrophysics Data System (ADS)

Minh, Nghia Pham; Zou, Bin; Cai, Hongjun; Wang, Chengyi

2014-01-01

The estimation of forest parameters over mountain forest areas using polarimetric interferometric synthetic aperture radar (PolInSAR) images is one of the greatest interests in remote sensing applications. For mountain forest areas, scattering mechanisms are strongly affected by the ground topography variations. Most of the previous studies in modeling microwave backscattering signatures of forest area have been carried out over relatively flat areas. Therefore, a new algorithm for the forest height estimation from mountain forest areas using the general model-based decomposition (GMBD) for PolInSAR image is proposed. This algorithm enables the retrieval of not only the forest parameters, but also the magnitude associated with each mechanism. In addition, general double- and single-bounce scattering models are proposed to fit for the cross-polarization and off-diagonal term by separating their independent orientation angle, which remains unachieved in the previous model-based decompositions. The efficiency of the proposed approach is demonstrated with simulated data from PolSARProSim software and ALOS-PALSAR spaceborne PolInSAR datasets over the Kalimantan areas, Indonesia. Experimental results indicate that forest height could be effectively estimated by GMBD.

Fairbanks North Star borough rural roads upgrade inventory and cost estimation software user guide : version I.

DOT National Transportation Integrated Search

2013-04-01

The Rural Road Upgrade Inventory and Cost Estimation Software is designed by the AUTC : research team to help the Fairbanks North Star Borough (FNSB) estimate the cost of upgrading : rural roads located in the Borough's Service Areas. The Software pe...

An Improved Method for Seismic Event Depth and Moment Tensor Determination: CTBT Related Application

NASA Astrophysics Data System (ADS)

Stachnik, J.; Rozhkov, M.; Baker, B.

2016-12-01

According to the Protocol to CTBT, International Data Center is required to conduct expert technical analysis and special studies to improve event parameters and assist State Parties in identifying the source of specific event. Determination of seismic event source mechanism and its depth is a part of these tasks. It is typically done through a strategic linearized inversion of the waveforms for a complete or subset of source parameters, or similarly defined grid search through precomputed Greens Functions created for particular source models. We show preliminary results using the latter approach from an improved software design and applied on a moderately powered computer. In this development we tried to be compliant with different modes of CTBT monitoring regime and cover wide range of source-receiver distances (regional to teleseismic), resolve shallow source depths, provide full moment tensor solution based on body and surface waves recordings, be fast to satisfy both on-demand studies and automatic processing and properly incorporate observed waveforms and any uncertainties a priori as well as accurately estimate posteriori uncertainties. Implemented HDF5 based Green's Functions pre-packaging allows much greater flexibility in utilizing different software packages and methods for computation. Further additions will have the rapid use of Instaseis/AXISEM full waveform synthetics added to a pre-computed GF archive. Along with traditional post processing analysis of waveform misfits through several objective functions and variance reduction, we follow a probabilistic approach to assess the robustness of moment tensor solution. In a course of this project full moment tensor and depth estimates are determined for DPRK 2009, 2013 and 2016 events and shallow earthquakes using a new implementation of waveform fitting of teleseismic P waves. A full grid search over the entire moment tensor space is used to appropriately sample all possible solutions. A recent method by Tape & Tape (2012) to discretize the complete moment tensor space from a geometric perspective is used. Moment tensors for DPRK events show isotropic percentages greater than 50%. Depth estimates for the DPRK events range from 1.0-1.4 km. Probabilistic uncertainty estimates on the moment tensor parameters provide robustness to solution.

New optical package and algorithms for accurate estimation and interactive recording of the cloud cover information over land and sea

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail; Sinitsyn, Alexey; Gulev, Sergey

2014-05-01

Cloud fraction is a critical parameter for the accurate estimation of short-wave and long-wave radiation - one of the most important surface fluxes over sea and land. Massive estimates of the total cloud cover as well as cloud amount for different layers of clouds are available from visual observations, satellite measurements and reanalyses. However, these data are subject of different uncertainties and need continuous validation against highly accurate in-situ measurements. Sky imaging with high resolution fish eye camera provides an excellent opportunity for collecting cloud cover data supplemented with additional characteristics hardly available from routine visual observations (e.g. structure of cloud cover under broken cloud conditions, parameters of distribution of cloud dimensions). We present operational automatic observational package which is based on fish eye camera taking sky images with high resolution (up to 1Hz) in time and a spatial resolution of 968x648px. This spatial resolution has been justified as an optimal by several sensitivity experiments. For the use of the package at research vessel when the horizontal positioning becomes critical, a special extension of the hardware and software to the package has been developed. These modules provide the explicit detection of the optimal moment for shooting. For the post processing of sky images we developed a software realizing the algorithm of the filtering of sunburn effect in case of small and moderate could cover and broken cloud conditions. The same algorithm accurately quantifies the cloud fraction by analyzing color mixture for each point and introducing the so-called "grayness rate index" for every pixel. The accuracy of the algorithm has been tested using the data collected during several campaigns in 2005-2011 in the North Atlantic Ocean. The collection of images included more than 3000 images for different cloud conditions supplied with observations of standard parameters. The system is fully autonomous and has a block for digital data collection at the hard disk. The system has been tested for a wide range of open ocean cloud conditions and we will demonstrate some pilot results of data processing and physical interpretation of fractional cloud cover estimation.

Is liver perfusion CT reproducible? A study on intra- and interobserver agreement of normal hepatic haemodynamic parameters obtained with two different software packages.

PubMed

Bretas, Elisa Almeida Sathler; Torres, Ulysses S; Torres, Lucas Rios; Bekhor, Daniel; Saito Filho, Celso Fernando; Racy, Douglas Jorge; Faggioni, Lorenzo; D'Ippolito, Giuseppe

2017-10-01

To evaluate the agreement between the measurements of perfusion CT parameters in normal livers by using two different software packages. This retrospective study was based on 78 liver perfusion CT examinations acquired for detecting suspected liver metastasis. Patients with any morphological or functional hepatic abnormalities were excluded. The final analysis included 37 patients (59.7 ± 14.9 y). Two readers (1 and 2) independently measured perfusion parameters using different software packages from two major manufacturers (A and B). Arterial perfusion (AP) and portal perfusion (PP) were determined using the dual-input vascular one-compartmental model. Inter-reader agreement for each package and intrareader agreement between both packages were assessed with intraclass correlation coefficients (ICC) and Bland-Altman statistics. Inter-reader agreement was substantial for AP using software A (ICC = 0.82) and B (ICC = 0.85-0.86), fair for PP using software A (ICC = 0.44) and fair to moderate for PP using software B (ICC = 0.56-0.77). Intrareader agreement between software A and B ranged from slight to moderate (ICC = 0.32-0.62) for readers 1 and 2 considering the AP parameters, and from fair to moderate (ICC = 0.40-0.69) for readers 1 and 2 considering the PP parameters. At best there was only moderate agreement between both software packages, resulting in some uncertainty and suboptimal reproducibility. Advances in knowledge: Software-dependent factors may contribute to variance in perfusion measurements, demanding further technical improvements. AP measurements seem to be the most reproducible parameter to be adopted when evaluating liver perfusion CT.

Program for Weibull Analysis of Fatigue Data

NASA Technical Reports Server (NTRS)

Krantz, Timothy L.

2005-01-01

A Fortran computer program has been written for performing statistical analyses of fatigue-test data that are assumed to be adequately represented by a two-parameter Weibull distribution. This program calculates the following: (1) Maximum-likelihood estimates of the Weibull distribution; (2) Data for contour plots of relative likelihood for two parameters; (3) Data for contour plots of joint confidence regions; (4) Data for the profile likelihood of the Weibull-distribution parameters; (5) Data for the profile likelihood of any percentile of the distribution; and (6) Likelihood-based confidence intervals for parameters and/or percentiles of the distribution. The program can account for tests that are suspended without failure (the statistical term for such suspension of tests is "censoring"). The analytical approach followed in this program for the software is valid for type-I censoring, which is the removal of unfailed units at pre-specified times. Confidence regions and intervals are calculated by use of the likelihood-ratio method.

Accuracy of estimating Unicondylar Knee Replacement implant varus/valgus angles from antero-posterior radiographs.

PubMed

Khare, Rahul; Jaramaz, Branislav

2016-12-01

Unicondylar Knee Replacement (UKR) is an orthopedic surgical procedure to reduce pain and improve function in the knee. Load-bearing long-standing antero-posterior (AP) radiographs are typically used postoperatively to measure the leg alignment and assess the varus/valgus implant orientation. However, implant out-of-plane rotations, user variability, and X-ray acquisition parameters introduce errors in the estimation of the implant varus/valgus estimation. Previous work has explored the accuracy of various imaging modalities in this estimation. In this work, we explored the impact of out-of-plane rotations and X-ray acquisition parameters on the estimation of implant component varus/valgus angles. For our study, we used a single CT scan and positioned femoral and tibial implants under varying orientations within the CT volume. Then, a custom software application was used to obtain digitally reconstructed radiographs from the CT scan with implants under varying orientations. Two users were then asked to manually estimate the varus/valgus angles for the implants. We found that there was significant inter-user variability (p < 0.05) in the varus/valgus estimates for the two users. However, the 'ideal' measurements, obtained using actual implant orientations, showed small errors due to variations in implant orientation. We also found that variation in the projection center does not have a statistically significant impact (p < 0.01) on the estimation of implant varus/valgus angles. We conclude that manual estimates of UKR implant varus/valgus orientations are unreliable.

A genetic-algorithm approach for assessing the liquefaction potential of sandy soils

NASA Astrophysics Data System (ADS)

Sen, G.; Akyol, E.

2010-04-01

The determination of liquefaction potential is required to take into account a large number of parameters, which creates a complex nonlinear structure of the liquefaction phenomenon. The conventional methods rely on simple statistical and empirical relations or charts. However, they cannot characterise these complexities. Genetic algorithms are suited to solve these types of problems. A genetic algorithm-based model has been developed to determine the liquefaction potential by confirming Cone Penetration Test datasets derived from case studies of sandy soils. Software has been developed that uses genetic algorithms for the parameter selection and assessment of liquefaction potential. Then several estimation functions for the assessment of a Liquefaction Index have been generated from the dataset. The generated Liquefaction Index estimation functions were evaluated by assessing the training and test data. The suggested formulation estimates the liquefaction occurrence with significant accuracy. Besides, the parametric study on the liquefaction index curves shows a good relation with the physical behaviour. The total number of misestimated cases was only 7.8% for the proposed method, which is quite low when compared to another commonly used method.

Extraction of Lateral-Directional Stability and Control Derivatives for the Basic F-18 Aircraft at High Angles of Attack

NASA Technical Reports Server (NTRS)

Iliff, Kenneth W.; Wang, Kon-Sheng Charles

1997-01-01

The results of parameter identification to determine the lateral-directional stability and control derivatives of an F-18 research aircraft in its basic hardware and software configuration are presented. The derivatives are estimated from dynamic flight data using a specialized identification program developed at NASA Dryden Flight Research Center. The formulation uses the linearized aircraft equations of motions in their continuous/discrete form and a maximum likelihood estimator that accounts for both state and measurement noise. State noise is used to model the uncommanded forcing function caused by unsteady aerodynamics, such as separated and vortical flows, over the aircraft. The derivatives are plotted as functions of angle of attack between 3 deg and 47 deg and compared with wind-tunnel predictions. The quality of the derivative estimates obtained by parameter identification is somewhat degraded because the maneuvers were flown with the aircraft's control augmentation system engaged, which introduced relatively high correlations between the control variables and response variables as a result of control motions from the feedback control system.

Enhanced methods for determining operational capabilities and support costs of proposed space systems

NASA Technical Reports Server (NTRS)

Ebeling, Charles

1993-01-01

This report documents the work accomplished during the first two years of research to provide support to NASA in predicting operational and support parameters and costs of proposed space systems. The first year's research developed a methodology for deriving reliability and maintainability (R & M) parameters based upon the use of regression analysis to establish empirical relationships between performance and design specifications and corresponding mean times of failure and repair. The second year focused on enhancements to the methodology, increased scope of the model, and software improvements. This follow-on effort expands the prediction of R & M parameters and their effect on the operations and support of space transportation vehicles to include other system components such as booster rockets and external fuel tanks. It also increases the scope of the methodology and the capabilities of the model as implemented by the software. The focus is on the failure and repair of major subsystems and their impact on vehicle reliability, turn times, maintenance manpower, and repairable spares requirements. The report documents the data utilized in this study, outlines the general methodology for estimating and relating R&M parameters, presents the analyses and results of application to the initial data base, and describes the implementation of the methodology through the use of a computer model. The report concludes with a discussion on validation and a summary of the research findings and results.

Ground Data System Analysis Tools to Track Flight System State Parameters for the Mars Science Laboratory (MSL) and Beyond

NASA Technical Reports Server (NTRS)

Allard, Dan; Deforrest, Lloyd

2014-01-01

Flight software parameters enable space mission operators fine-tuned control over flight system configurations, enabling rapid and dynamic changes to ongoing science activities in a much more flexible manner than can be accomplished with (otherwise broadly used) configuration file based approaches. The Mars Science Laboratory (MSL), Curiosity, makes extensive use of parameters to support complex, daily activities via commanded changes to said parameters in memory. However, as the loss of Mars Global Surveyor (MGS) in 2006 demonstrated, flight system management by parameters brings with it risks, including the possibility of losing track of the flight system configuration and the threat of invalid command executions. To mitigate this risk a growing number of missions have funded efforts to implement parameter tracking parameter state software tools and services including MSL and the Soil Moisture Active Passive (SMAP) mission. This paper will discuss the engineering challenges and resulting software architecture of MSL's onboard parameter state tracking software and discuss the road forward to make parameter management tools suitable for use on multiple missions.

MODEST - JPL GEODETIC AND ASTROMETRIC VLBI MODELING AND PARAMETER ESTIMATION PROGRAM

NASA Technical Reports Server (NTRS)

Sovers, O. J.

1994-01-01

Observations of extragalactic radio sources in the gigahertz region of the radio frequency spectrum by two or more antennas, separated by a baseline as long as the diameter of the Earth, can be reduced, by radio interferometry techniques, to yield time delays and their rates of change. The Very Long Baseline Interferometric (VLBI) observables can be processed by the MODEST software to yield geodetic and astrometric parameters of interest in areas such as geophysical satellite and spacecraft tracking applications and geodynamics. As the accuracy of radio interferometry has improved, increasingly complete models of the delay and delay rate observables have been developed. MODEST is a delay model (MOD) and parameter estimation (EST) program that takes into account delay effects such as geometry, clock, troposphere, and the ionosphere. MODEST includes all known effects at the centimeter level in modeling. As the field evolves and new effects are discovered, these can be included in the model. In general, the model includes contributions to the observables from Earth orientation, antenna motion, clock behavior, atmospheric effects, and radio source structure. Within each of these categories, a number of unknown parameters may be estimated from the observations. Since all parts of the time delay model contain nearly linear parameter terms, a square-root-information filter (SRIF) linear least-squares algorithm is employed in parameter estimation. Flexibility (via dynamic memory allocation) in the MODEST code ensures that the same executable can process a wide array of problems. These range from a few hundred observations on a single baseline, yielding estimates of tens of parameters, to global solutions estimating tens of thousands of parameters from hundreds of thousands of observations at antennas widely distributed over the Earth's surface. Depending on memory and disk storage availability, large problems may be subdivided into more tractable pieces that are processed sequentially. MODEST is written in FORTRAN 77, C-language, and VAX ASSEMBLER for DEC VAX series computers running VMS. It requires 6Mb of RAM for execution. The standard distribution medium for this package is a 1600 BPI 9-track magnetic tape in DEC VAX BACKUP format. It is also available on a TK50 tape cartridge in DEC VAX BACKUP format. Instructions for use and sample input and output data are available on the distribution media. This program was released in 1993 and is a copyrighted work with all copyright vested in NASA.

Forecasting the mortality rates of Malaysian population using Heligman-Pollard model

NASA Astrophysics Data System (ADS)

Ibrahim, Rose Irnawaty; Mohd, Razak; Ngataman, Nuraini; Abrisam, Wan Nur Azifah Wan Mohd

2017-08-01

Actuaries, demographers and other professionals have always been aware of the critical importance of mortality forecasting due to declining trend of mortality and continuous increases in life expectancy. Heligman-Pollard model was introduced in 1980 and has been widely used by researchers in modelling and forecasting future mortality. This paper aims to estimate an eight-parameter model based on Heligman and Pollard's law of mortality. Since the model involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 7.0 (MATLAB 7.0) software will be used in order to estimate the parameters. Statistical Package for the Social Sciences (SPSS) will be applied to forecast all the parameters according to Autoregressive Integrated Moving Average (ARIMA). The empirical data sets of Malaysian population for period of 1981 to 2015 for both genders will be considered, which the period of 1981 to 2010 will be used as "training set" and the period of 2011 to 2015 as "testing set". In order to investigate the accuracy of the estimation, the forecast results will be compared against actual data of mortality rates. The result shows that Heligman-Pollard model fit well for male population at all ages while the model seems to underestimate the mortality rates for female population at the older ages.

Quantitative fluorescence angiography for neurosurgical interventions.

PubMed

Weichelt, Claudia; Duscha, Philipp; Steinmeier, Ralf; Meyer, Tobias; Kuß, Julia; Cimalla, Peter; Kirsch, Matthias; Sobottka, Stephan B; Koch, Edmund; Schackert, Gabriele; Morgenstern, Ute

2013-06-01

Present methods for quantitative measurement of cerebral perfusion during neurosurgical operations require additional technology for measurement, data acquisition, and processing. This study used conventional fluorescence video angiography--as an established method to visualize blood flow in brain vessels--enhanced by a quantifying perfusion software tool. For these purposes, the fluorescence dye indocyanine green is given intravenously, and after activation by a near-infrared light source the fluorescence signal is recorded. Video data are analyzed by software algorithms to allow quantification of the blood flow. Additionally, perfusion is measured intraoperatively by a reference system. Furthermore, comparing reference measurements using a flow phantom were performed to verify the quantitative blood flow results of the software and to validate the software algorithm. Analysis of intraoperative video data provides characteristic biological parameters. These parameters were implemented in the special flow phantom for experimental validation of the developed software algorithms. Furthermore, various factors that influence the determination of perfusion parameters were analyzed by means of mathematical simulation. Comparing patient measurement, phantom experiment, and computer simulation under certain conditions (variable frame rate, vessel diameter, etc.), the results of the software algorithms are within the range of parameter accuracy of the reference methods. Therefore, the software algorithm for calculating cortical perfusion parameters from video data presents a helpful intraoperative tool without complex additional measurement technology.

Effect of software version and parameter settings on the marginal and internal adaptation of crowns fabricated with the CAD/CAM system.

PubMed

Shim, Ji Suk; Lee, Jin Sook; Lee, Jeong Yol; Choi, Yeon Jo; Shin, Sang Wan; Ryu, Jae Jun

2015-10-01

This study investigated the marginal and internal adaptation of individual dental crowns fabricated using a CAD/CAM system (Sirona's BlueCam), also evaluating the effect of the software version used, and the specific parameter settings in the adaptation of crowns. Forty digital impressions of a master model previously prepared were acquired using an intraoral scanner and divided into four groups based on the software version and on the spacer settings used. The versions 3.8 and 4.2 of the software were used, and the spacer parameter was set at either 40 μm or 80 μm. The marginal and internal fit of the crowns were measured using the replica technique, which uses a low viscosity silicone material that simulates the thickness of the cement layer. The data were analyzed using a Friedman two-way analysis of variance (ANOVA) and paired t-tests with significance level set at p<0.05. The two-way ANOVA analysis showed the software version (p<0.05) and the spacer parameter (p<0.05) significantly affected the crown adaptation. The crowns designed with the version 4.2 of the software showed a better fit than those designed with the version 3.8, particularly in the axial wall and in the inner margin. The spacer parameter was more accurately represented in the version 4.2 of the software than in the version 3.8. In addition, the use of the version 4.2 of the software combined with the spacer parameter set at 80 μm showed the least variation. On the other hand, the outer margin was not affected by the variables. Compared to the version 3.8 of the software, the version 4.2 can be recommended for the fabrication of well-fitting crown restorations, and for the appropriate regulation of the spacer parameter.

Dose Estimating Application Software Modification: Additional Function of a Size-Specific Effective Dose Calculator and Auto Exposure Control.

PubMed

Kobayashi, Masanao; Asada, Yasuki; Matsubara, Kosuke; Suzuki, Shouichi; Matsunaga, Yuta; Haba, Tomonobu; Kawaguchi, Ai; Daioku, Tomihiko; Toyama, Hiroshi; Kato, Ryoichi

2017-05-01

Adequate dose management during computed tomography is important. In the present study, the dosimetric application software ImPACT was added to a functional calculator of the size-specific dose estimate and was part of the scan settings for the auto exposure control (AEC) technique. This study aimed to assess the practicality and accuracy of the modified ImPACT software for dose estimation. We compared the conversion factors identified by the software with the values reported by the American Association of Physicists in Medicine Task Group 204, and we noted similar results. Moreover, doses were calculated with the AEC technique and a fixed-tube current of 200 mA for the chest-pelvis region. The modified ImPACT software could estimate each organ dose, which was based on the modulated tube current. The ability to perform beneficial modifications indicates the flexibility of the ImPACT software. The ImPACT software can be further modified for estimation of other doses. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A semi-automated volumetric software for segmentation and perfusion parameter quantification of brain tumors using 320-row multidetector computed tomography: a validation study.

PubMed

Chae, Soo Young; Suh, Sangil; Ryoo, Inseon; Park, Arim; Noh, Kyoung Jin; Shim, Hackjoon; Seol, Hae Young

2017-05-01

We developed a semi-automated volumetric software, NPerfusion, to segment brain tumors and quantify perfusion parameters on whole-brain CT perfusion (WBCTP) images. The purpose of this study was to assess the feasibility of the software and to validate its performance compared with manual segmentation. Twenty-nine patients with pathologically proven brain tumors who underwent preoperative WBCTP between August 2012 and February 2015 were included. Three perfusion parameters, arterial flow (AF), equivalent blood volume (EBV), and Patlak flow (PF, which is a measure of permeability of capillaries), of brain tumors were generated by a commercial software and then quantified volumetrically by NPerfusion, which also semi-automatically segmented tumor boundaries. The quantification was validated by comparison with that of manual segmentation in terms of the concordance correlation coefficient and Bland-Altman analysis. With NPerfusion, we successfully performed segmentation and quantified whole volumetric perfusion parameters of all 29 brain tumors that showed consistent perfusion trends with previous studies. The validation of the perfusion parameter quantification exhibited almost perfect agreement with manual segmentation, with Lin concordance correlation coefficients (ρ c ) for AF, EBV, and PF of 0.9988, 0.9994, and 0.9976, respectively. On Bland-Altman analysis, most differences between this software and manual segmentation on the commercial software were within the limit of agreement. NPerfusion successfully performs segmentation of brain tumors and calculates perfusion parameters of brain tumors. We validated this semi-automated segmentation software by comparing it with manual segmentation. NPerfusion can be used to calculate volumetric perfusion parameters of brain tumors from WBCTP.

Thermodynamic Analysis and Optimization of a High Temperature Triple Absorption Heat Transformer

PubMed Central

Khamooshi, Mehrdad; Yari, Mortaza; Egelioglu, Fuat; Salati, Hana

2014-01-01

First law of thermodynamics has been used to analyze and optimize inclusively the performance of a triple absorption heat transformer operating with LiBr/H2O as the working pair. A thermodynamic model was developed in EES (engineering equation solver) to estimate the performance of the system in terms of the most essential parameters. The assumed parameters are the temperature of the main components, weak and strong solutions, economizers' efficiencies, and bypass ratios. The whole cycle is optimized by EES software from the viewpoint of maximizing the COP via applying the direct search method. The optimization results showed that the COP of 0.2491 is reachable by the proposed cycle. PMID:25136702

A software package for evaluating the performance of a star sensor operation

NASA Astrophysics Data System (ADS)

Sarpotdar, Mayuresh; Mathew, Joice; Sreejith, A. G.; Nirmal, K.; Ambily, S.; Prakash, Ajin; Safonova, Margarita; Murthy, Jayant

2017-02-01

We have developed a low-cost off-the-shelf component star sensor ( StarSense) for use in minisatellites and CubeSats to determine the attitude of a satellite in orbit. StarSense is an imaging camera with a limiting magnitude of 6.5, which extracts information from star patterns it records in the images. The star sensor implements a centroiding algorithm to find centroids of the stars in the image, a Geometric Voting algorithm for star pattern identification, and a QUEST algorithm for attitude quaternion calculation. Here, we describe the software package to evaluate the performance of these algorithms as a star sensor single operating system. We simulate the ideal case where sky background and instrument errors are omitted, and a more realistic case where noise and camera parameters are added to the simulated images. We evaluate such performance parameters of the algorithms as attitude accuracy, calculation time, required memory, star catalog size, sky coverage, etc., and estimate the errors introduced by each algorithm. This software package is written for use in MATLAB. The testing is parametrized for different hardware parameters, such as the focal length of the imaging setup, the field of view (FOV) of the camera, angle measurement accuracy, distortion effects, etc., and therefore, can be applied to evaluate the performance of such algorithms in any star sensor. For its hardware implementation on our StarSense, we are currently porting the codes in form of functions written in C. This is done keeping in view its easy implementation on any star sensor electronics hardware.

WEB downloadable software for training in cardiovascular hemodynamics in the (3-D) stress echo lab

PubMed Central

2010-01-01

When a physiological (exercise) stress echo is scheduled, interest focuses on wall motion segmental contraction abnormalities to diagnose ischemic response to stress, and on left ventricular ejection fraction to assess contractile reserve. Echocardiographic evaluation of volumes (plus standard assessment of heart rate and blood pressure) is ideally suited for the quantitative and accurate calculation of a set of parameters allowing a complete characterization of cardiovascular hemodynamics (including cardiac output and systemic vascular resistance), left ventricular elastance (mirroring left ventricular contractility, theoretically independent of preload and afterload changes heavily affecting the ejection fraction), arterial elastance, ventricular arterial coupling (a central determinant of net cardiovascular performance in normal and pathological conditions), and diastolic function (through the diastolic mean filling rate). All these parameters were previously inaccessible, inaccurate or labor-intensive and now become, at least in principle, available in the stress echocardiography laboratory since all of them need an accurate estimation of left ventricular volumes and stroke volume, easily derived from 3 D echo. Aims of this paper are: 1) to propose a simple method to assess a set of parameters allowing a complete characterization of cardiovascular hemodynamics in the stress echo lab, from basic measurements to calculations 2) to propose a simple, web-based software program, to learn and training calculations as a phantom of the everyday activity in the busy stress echo lab 3) to show examples of software testing in a way that proves its value. The informatics infrastructure is available on the web, linking to http://cctrainer.ifc.cnr.it PMID:21073738

Structural reliability methods: Code development status

NASA Astrophysics Data System (ADS)

Millwater, Harry R.; Thacker, Ben H.; Wu, Y.-T.; Cruse, T. A.

1991-05-01

The Probabilistic Structures Analysis Method (PSAM) program integrates state of the art probabilistic algorithms with structural analysis methods in order to quantify the behavior of Space Shuttle Main Engine structures subject to uncertain loadings, boundary conditions, material parameters, and geometric conditions. An advanced, efficient probabilistic structural analysis software program, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a deliverable. NESSUS contains a number of integrated software components to perform probabilistic analysis of complex structures. A nonlinear finite element module NESSUS/FEM is used to model the structure and obtain structural sensitivities. Some of the capabilities of NESSUS/FEM are shown. A Fast Probability Integration module NESSUS/FPI estimates the probability given the structural sensitivities. A driver module, PFEM, couples the FEM and FPI. NESSUS, version 5.0, addresses component reliability, resistance, and risk.

Structural reliability methods: Code development status

NASA Technical Reports Server (NTRS)

Millwater, Harry R.; Thacker, Ben H.; Wu, Y.-T.; Cruse, T. A.

1991-01-01

The Probabilistic Structures Analysis Method (PSAM) program integrates state of the art probabilistic algorithms with structural analysis methods in order to quantify the behavior of Space Shuttle Main Engine structures subject to uncertain loadings, boundary conditions, material parameters, and geometric conditions. An advanced, efficient probabilistic structural analysis software program, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a deliverable. NESSUS contains a number of integrated software components to perform probabilistic analysis of complex structures. A nonlinear finite element module NESSUS/FEM is used to model the structure and obtain structural sensitivities. Some of the capabilities of NESSUS/FEM are shown. A Fast Probability Integration module NESSUS/FPI estimates the probability given the structural sensitivities. A driver module, PFEM, couples the FEM and FPI. NESSUS, version 5.0, addresses component reliability, resistance, and risk.

scraps: An open-source Python-based analysis package for analyzing and plotting superconducting resonator data

DOE PAGES

Carter, Faustin Wirkus; Khaire, Trupti S.; Novosad, Valentyn; ...

2016-11-07

We present "scraps" (SuperConducting Analysis and Plotting Software), a Python package designed to aid in the analysis and visualization of large amounts of superconducting resonator data, specifically complex transmission as a function of frequency, acquired at many different temperatures and driving powers. The package includes a least-squares fitting engine as well as a Monte-Carlo Markov Chain sampler for sampling the posterior distribution given priors, marginalizing over nuisance parameters, and estimating covariances. A set of plotting tools for generating publication-quality figures is also provided in the package. Lastly, we discuss the functionality of the software and provide some examples of itsmore » utility on data collected from a niobium-nitride coplanar waveguide resonator fabricated at Argonne National Laboratory.« less

Vienna Special Analysis Center Annual Report 2012

NASA Technical Reports Server (NTRS)

Boehm, Johannes; Boehm, Sigrid; Krasna, Hana; Madzak, Matthias; Nilsson, Tobias; Plank, Lucia; Raposo, Virginia; Schuh, Harald; Soja, Benedikt; Sun Jing;

An Implanted, Stimulated Muscle Powered Piezoelectric Generator

NASA Technical Reports Server (NTRS)

Lewandowski, Beth; Gustafson, Kenneth; Kilgore, Kevin

2007-01-01

A totally implantable piezoelectric generator system able to harness power from electrically activated muscle could be used to augment the power systems of implanted medical devices, such as neural prostheses, by reducing the number of battery replacement surgeries or by allowing periods of untethered functionality. The features of our generator design are no moving parts and the use of a portion of the generated power for system operation and regulation. A software model of the system has been developed and simulations have been performed to predict the output power as the system parameters were varied within their constraints. Mechanical forces that mimic muscle forces have been experimentally applied to a piezoelectric generator to verify the accuracy of the simulations and to explore losses due to mechanical coupling. Depending on the selection of system parameters, software simulations predict that this generator concept can generate up to approximately 700 W of power, which is greater than the power necessary to drive the generator, conservatively estimated to be 50 W. These results suggest that this concept has the potential to be an implantable, self-replenishing power source and further investigation is underway.

The determination of the most applicable PWV model for Turkey

NASA Astrophysics Data System (ADS)

Deniz, Ilke; Gurbuz, Gokhan; Mekik, Cetin

2016-07-01

Water vapor is a key component for modelling atmosphere and climate studies. Moreover, long-term water vapor changes can be an independent source for detecting climate changes. Since Global Navigation Satellite Systems (GNSS) use microwaves passing through the atmosphere, atmospheric effects are modeled with high accuracy. Tropospheric effects on GNSS signals are estimated with total zenith delay parameter (ZTD) which is the sum of hydrostatic (ZHD) and wet zenith delay (ZWD). The first component can be obtained from meteorological observations with high accuracy; the second component, however, can be computed by subtracting ZHD from ZTD (ZWD=ZTD-ZHD). Afterwards, the weighted mean temperature (Tm) or the conversion factor (Q) is used for the conversion between the precipitable water vapor (PWV) and ZWD. The parameters Tm and Q are derived from the analysis of radiosonde stations' profile observations. Numerous Q and Tm models have been developed for each radiosonde station, radiosonde station group, countries and global fields such as Bevis Tm model and Emardson and Derks' Q models. So, PWV models (Tm and Q models) applied for Turkey have been developed using a year of radiosonde data (2011) from 8 radiosonde stations. In this study the models developed are tested by comparing PWVGNSS computed applying Tm and Q models to the ZTD estimates derived by Bernese and GAMIT/GLOBK software at GNSS stations established at Istanbul and Ankara with those from the collocated radiosonde stations (PWVRS) from October 2013 to December 2014 with the data obtained from a project (no 112Y350) supported by the Scientific and Technological Research Council of Turkey (TUBITAK). The comparison results show that PWVGNSS and PWVRS are in high correlation (86 % for Ankara and 90% for Istanbul). Thus, the most applicable model for Turkey and the accuracy of GNSS meteorology are investigated. In addition, Tm model was applied to the ZTD estimates of 20 TUSAGA-Active (CORS-TR) stations in the 38.0°-42.0° northern latitudes and 28.0°-34.0° eastern longitudes of Turkey and PWV were computed. ZTD estimates of these stations were computed using Bernese GNSS Software v5.0 during the period from June 2013 to June 2014. Preceding the PWV estimation, meteorological parameters for these stations (temperature, pressure and humidity) are derived by applying spherical harmonics modelling and interpolation to the above-mentioned meteorological parameters measured by meteorological stations surrounding TUSAGA-Active stations. Results of spherical harmonics modelling and interpolation yield the precision of ±1.74 K in temperature, ±0.95 hPa in pressure and ±14.88 % in humidity. Also, the PWV of TUSAGA-Active stations selected were estimated.

Kepler: A Search for Terrestrial Planets - SOC 9.3 DR25 Pipeline Parameter Configuration Reports

NASA Technical Reports Server (NTRS)

Campbell, Jennifer R.

2017-01-01

This document describes the manner in which the pipeline and algorithm parameters for the Kepler Science Operations Center (SOC) science data processing pipeline were managed. This document is intended for scientists and software developers who wish to better understand the software design for the final Kepler codebase (SOC 9.3) and the effect of the software parameters on the Data Release (DR) 25 archival products.

Demosaicking of noisy Bayer-sampled color images with least-squares luma-chroma demultiplexing and noise level estimation.

PubMed

Jeon, Gwanggil; Dubois, Eric

2013-01-01

This paper adapts the least-squares luma-chroma demultiplexing (LSLCD) demosaicking method to noisy Bayer color filter array (CFA) images. A model is presented for the noise in white-balanced gamma-corrected CFA images. A method to estimate the noise level in each of the red, green, and blue color channels is then developed. Based on the estimated noise parameters, one of a finite set of configurations adapted to a particular level of noise is selected to demosaic the noisy data. The noise-adaptive demosaicking scheme is called LSLCD with noise estimation (LSLCD-NE). Experimental results demonstrate state-of-the-art performance over a wide range of noise levels, with low computational complexity. Many results with several algorithms, noise levels, and images are presented on our companion web site along with software to allow reproduction of our results.

Experimental (FT-IR, NMR and UV) and theoretical (M06-2X and DFT) investigation, and frequency estimation analyses on (E)-3-(4-bromo-5-methylthiophen-2-yl)acrylonitrile

NASA Astrophysics Data System (ADS)

Sert, Yusuf; Balakit, Asim A.; Öztürk, Nuri; Ucun, Fatih; El-Hiti, Gamal A.

2014-10-01

The spectroscopic properties of (E)-3-(4-bromo-5-methylthiophen-2-yl)acrylonitrile have been investigated by FT-IR, UV, 1H and 13C NMR techniques. The theoretical vibrational frequencies and optimized geometric parameters (bond lengths and angles) have been calculated using density functional theory (DFT/B3LYP: Becke, 3-parameter, Lee-Yang-Parr) and DFT/M06-2X (the highly parameterized, empirical exchange correlation function) quantum chemical methods with 6-311++G(d,p) basis set by Gaussian 03 software, for the first time. The assignments of the vibrational frequencies have been carried out by potential energy distribution (PED) analysis by using VEDA 4 software. The theoretical optimized geometric parameters and vibrational frequencies were in good agreement with the corresponding experimental data, and with the results in the literature. 1H and 13C NMR chemical shifts were calculated by using the gauge-invariant atomic orbital (GIAO) method. The electronic properties, such as excitation energies, oscillator strength wavelengths were performed by B3LYP methods. In addition, the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) energies and the other related molecular energy values have been calculated and depicted.

Automated Estimation Of Software-Development Costs

NASA Technical Reports Server (NTRS)

Roush, George B.; Reini, William

1993-01-01

COSTMODL is automated software development-estimation tool. Yields significant reduction in risk of cost overruns and failed projects. Accepts description of software product developed and computes estimates of effort required to produce it, calendar schedule required, and distribution of effort and staffing as function of defined set of development life-cycle phases. Written for IBM PC(R)-compatible computers.

Rapid processing of data based on high-performance algorithms for solving inverse problems and 3D-simulation of the tsunami and earthquakes

NASA Astrophysics Data System (ADS)

Marinin, I. V.; Kabanikhin, S. I.; Krivorotko, O. I.; Karas, A.; Khidasheli, D. G.

2012-04-01

We consider new techniques and methods for earthquake and tsunami related problems, particularly - inverse problems for the determination of tsunami source parameters, numerical simulation of long wave propagation in soil and water and tsunami risk estimations. In addition, we will touch upon the issue of database management and destruction scenario visualization. New approaches and strategies, as well as mathematical tools and software are to be shown. The long joint investigations by researchers of the Institute of Mathematical Geophysics and Computational Mathematics SB RAS and specialists from WAPMERR and Informap have produced special theoretical approaches, numerical methods, and software tsunami and earthquake modeling (modeling of propagation and run-up of tsunami waves on coastal areas), visualization, risk estimation of tsunami, and earthquakes. Algorithms are developed for the operational definition of the origin and forms of the tsunami source. The system TSS numerically simulates the source of tsunami and/or earthquakes and includes the possibility to solve the direct and the inverse problem. It becomes possible to involve advanced mathematical results to improve models and to increase the resolution of inverse problems. Via TSS one can construct maps of risks, the online scenario of disasters, estimation of potential damage to buildings and roads. One of the main tools for the numerical modeling is the finite volume method (FVM), which allows us to achieve stability with respect to possible input errors, as well as to achieve optimum computing speed. Our approach to the inverse problem of tsunami and earthquake determination is based on recent theoretical results concerning the Dirichlet problem for the wave equation. This problem is intrinsically ill-posed. We use the optimization approach to solve this problem and SVD-analysis to estimate the degree of ill-posedness and to find the quasi-solution. The software system we developed is intended to create technology «no frost», realizing a steady stream of direct and inverse problems: solving the direct problem, the visualization and comparison with observed data, to solve the inverse problem (correction of the model parameters). The main objective of further work is the creation of a workstation operating emergency tool that could be used by an emergency duty person in real time.

Elastic and Photoelastic Properties of M(NO3)2, MO (M = Mg, Ca, Sr, Ba)

NASA Astrophysics Data System (ADS)

Zhuravlev, Yu. N.; Korabel'nikov, D. V.

2017-05-01

The paper deals with ab initio investigations of elastic and photoelastic properties of oxides and nitrates of alkaline-earth metals. In gradient approximation of the density functional theory (DFT), these properties are studied with the use of the linear combination of the atomic orbital technique. DFT calculations are done with the CRYSTAL 14 software package. The paper introduces the elastic and photoelastic constants, anisotropy parameters for single-crystalline phases and the elastic modules, hardness, Poisson ratio for polycrystalline phases. Such parameters as sonic speed, Debye temperature, thermal conductivity, and Gruneisen parameter are estimated herein. For the fist time, mechanical stability, anisotropy of elastic and photoelastic properties and their dependences are investigated ab initio in this paper. Experimental results on elastic and photoelastic properties of oxides and nitrates are in good agreement with theoretical calculations.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.

2011-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

Investigation of the dependence of joint contact forces on musculotendon parameters using a codified workflow for image-based modelling.

PubMed

Modenese, Luca; Montefiori, Erica; Wang, Anqi; Wesarg, Stefan; Viceconti, Marco; Mazzà, Claudia

2018-05-17

The generation of subject-specific musculoskeletal models of the lower limb has become a feasible task thanks to improvements in medical imaging technology and musculoskeletal modelling software. Nevertheless, clinical use of these models in paediatric applications is still limited for what concerns the estimation of muscle and joint contact forces. Aiming to improve the current state of the art, a methodology to generate highly personalized subject-specific musculoskeletal models of the lower limb based on magnetic resonance imaging (MRI) scans was codified as a step-by-step procedure and applied to data from eight juvenile individuals. The generated musculoskeletal models were used to simulate 107 gait trials using stereophotogrammetric and force platform data as input. To ensure completeness of the modelling procedure, muscles' architecture needs to be estimated. Four methods to estimate muscles' maximum isometric force and two methods to estimate musculotendon parameters (optimal fiber length and tendon slack length) were assessed and compared, in order to quantify their influence on the models' output. Reported results represent the first comprehensive subject-specific model-based characterization of juvenile gait biomechanics, including profiles of joint kinematics and kinetics, muscle forces and joint contact forces. Our findings suggest that, when musculotendon parameters were linearly scaled from a reference model and the muscle force-length-velocity relationship was accounted for in the simulations, realistic knee contact forces could be estimated and these forces were not sensitive the method used to compute muscle maximum isometric force. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Application of an automatic approach to calibrate the NEMURO nutrient-phytoplankton-zooplankton food web model in the Oyashio region

NASA Astrophysics Data System (ADS)

Ito, Shin-ichi; Yoshie, Naoki; Okunishi, Takeshi; Ono, Tsuneo; Okazaki, Yuji; Kuwata, Akira; Hashioka, Taketo; Rose, Kenneth A.; Megrey, Bernard A.; Kishi, Michio J.; Nakamachi, Miwa; Shimizu, Yugo; Kakehi, Shigeho; Saito, Hiroaki; Takahashi, Kazutaka; Tadokoro, Kazuaki; Kusaka, Akira; Kasai, Hiromi

2010-10-01

The Oyashio region in the western North Pacific supports high biological productivity and has been well monitored. We applied the NEMURO (North Pacific Ecosystem Model for Understanding Regional Oceanography) model to simulate the nutrients, phytoplankton, and zooplankton dynamics. Determination of parameters values is very important, yet ad hoc calibration methods are often used. We used the automatic calibration software PEST (model-independent Parameter ESTimation), which has been used previously with NEMURO but in a system without ontogenetic vertical migration of the large zooplankton functional group. Determining the performance of PEST with vertical migration, and obtaining a set of realistic parameter values for the Oyashio, will likely be useful in future applications of NEMURO. Five identical twin simulation experiments were performed with the one-box version of NEMURO. The experiments differed in whether monthly snapshot or averaged state variables were used, in whether state variables were model functional groups or were aggregated (total phytoplankton, small plus large zooplankton), and in whether vertical migration of large zooplankton was included or not. We then applied NEMURO to monthly climatological field data covering 1 year for the Oyashio, and compared model fits and parameter values between PEST-determined estimates and values used in previous applications to the Oyashio region that relied on ad hoc calibration. We substituted the PEST and ad hoc calibrated parameter values into a 3-D version of NEMURO for the western North Pacific, and compared the two sets of spatial maps of chlorophyll- a with satellite-derived data. The identical twin experiments demonstrated that PEST could recover the known model parameter values when vertical migration was included, and that over-fitting can occur as a result of slight differences in the values of the state variables. PEST recovered known parameter values when using monthly snapshots of aggregated state variables, but estimated a different set of parameters with monthly averaged values. Both sets of parameters resulted in good fits of the model to the simulated data. Disaggregating the variables provided to PEST into functional groups did not solve the over-fitting problem, and including vertical migration seemed to amplify the problem. When we used the climatological field data, simulated values with PEST-estimated parameters were closer to these field data than with the previously determined ad hoc set of parameter values. When these same PEST and ad hoc sets of parameter values were substituted into 3-D-NEMURO (without vertical migration), the PEST-estimated parameter values generated spatial maps that were similar to the satellite data for the Kuroshio Extension during January and March and for the subarctic ocean from May to November. With non-linear problems, such as vertical migration, PEST should be used with caution because parameter estimates can be sensitive to how the data are prepared and to the values used for the searching parameters of PEST. We recommend the usage of PEST, or other parameter optimization methods, to generate first-order parameter estimates for simulating specific systems and for insertion into 2-D and 3-D models. The parameter estimates that are generated are useful, and the inconsistencies between simulated values and the available field data provide valuable information on model behavior and the dynamics of the ecosystem.

Rule-Based Flight Software Cost Estimation

NASA Technical Reports Server (NTRS)

Stukes, Sherry A.; Spagnuolo, John N. Jr.

2015-01-01

This paper discusses the fundamental process for the computation of Flight Software (FSW) cost estimates. This process has been incorporated in a rule-based expert system [1] that can be used for Independent Cost Estimates (ICEs), Proposals, and for the validation of Cost Analysis Data Requirements (CADRe) submissions. A high-level directed graph (referred to here as a decision graph) illustrates the steps taken in the production of these estimated costs and serves as a basis of design for the expert system described in this paper. Detailed discussions are subsequently given elaborating upon the methodology, tools, charts, and caveats related to the various nodes of the graph. We present general principles for the estimation of FSW using SEER-SEM as an illustration of these principles when appropriate. Since Source Lines of Code (SLOC) is a major cost driver, a discussion of various SLOC data sources for the preparation of the estimates is given together with an explanation of how contractor SLOC estimates compare with the SLOC estimates used by JPL. Obtaining consistency in code counting will be presented as well as factors used in reconciling SLOC estimates from different code counters. When sufficient data is obtained, a mapping into the JPL Work Breakdown Structure (WBS) from the SEER-SEM output is illustrated. For across the board FSW estimates, as was done for the NASA Discovery Mission proposal estimates performed at JPL, a comparative high-level summary sheet for all missions with the SLOC, data description, brief mission description and the most relevant SEER-SEM parameter values is given to illustrate an encapsulation of the used and calculated data involved in the estimates. The rule-based expert system described provides the user with inputs useful or sufficient to run generic cost estimation programs. This system's incarnation is achieved via the C Language Integrated Production System (CLIPS) and will be addressed at the end of this paper.

COMDYN: Software to study the dynamics of animal communities using a capture-recapture approach

USGS Publications Warehouse

Hines, J.E.; Boulinier, T.; Nichols, J.D.; Sauer, J.R.; Pollock, K.H.

1999-01-01

COMDYN is a set of programs developed for estimation of parameters associated with community dynamics using count data from two locations or time periods. It is Internet-based, allowing remote users either to input their own data, or to use data from the North American Breeding Bird Survey for analysis. COMDYN allows probability of detection to vary among species and among locations and time periods. The basic estimator for species richness underlying all estimators is the jackknife estimator proposed by Burnham and Overton. Estimators are presented for quantities associated with temporal change in species richness, including rate of change in species richness over time, local extinction probability, local species turnover and number of local colonizing species. Estimators are also presented for quantities associated with spatial variation in species richness, including relative richness at two locations and proportion of species present in one location that are also present at a second location. Application of the estimators to species richness estimation has been previously described and justified. The potential applications of these programs are discussed.

Onboard TDI stage estimation and calibration using SNR analysis

NASA Astrophysics Data System (ADS)

Haghshenas, Javad

2017-09-01

Electro-Optical design of a push-broom space camera for a Low Earth Orbit (LEO) remote sensing satellite is performed based on the noise analysis of TDI sensors for very high GSDs and low light level missions. It is well demonstrated that the CCD TDI mode of operation provides increased photosensitivity relative to a linear CCD array, without the sacrifice of spatial resolution. However, for satellite imaging, in order to utilize the advantages which the TDI mode of operation offers, attention should be given to the parameters which affect the image quality of TDI sensors such as jitters, vibrations, noises and etc. A predefined TDI stages may not properly satisfy image quality requirement of the satellite camera. Furthermore, in order to use the whole dynamic range of the sensor, imager must be capable to set the TDI stages in every shots based on the affecting parameters. This paper deals with the optimal estimation and setting the stages based on tradeoffs among MTF, noises and SNR. On-board SNR estimation is simulated using the atmosphere analysis based on the MODTRAN algorithm in PcModWin software. According to the noises models, we have proposed a formulation to estimate TDI stages in such a way to satisfy the system SNR requirement. On the other hand, MTF requirement must be satisfy in the same manner. A proper combination of both parameters will guaranty the full dynamic range usage along with the high SNR and image quality.

SU-G-IeP3-12: Preliminary Report On the Experience of Patient Radiation Dose Monitoring and Tracking Systems; PEMNET, Radimetrics and DoseWatch

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

Lin, P; Corwin, F; Ghita, M

Purpose: Three patient radiation dose monitoring and tracking (PRDMT) systems have been in operation at this institution for the past 6 months. There are useful information that should be disseminated to those who are considering installation of PRDMT programs. In addition, there are “problems” uncovered in the process of estimating fluoroscopic “peak” skin dose (PSD), especially, for those patients who received interventional angiographic studies and in conjunction with surgical procedures. Methods: Upon exporting the PRDMT data to Microsoft Excel program, the peak skin dose can be estimated by applying various correction factors including; attenuation due to the tabletop and examinationmore » mattress, table height, tabletop translation, backscatter, etc. A procedure was established to screen and divide the PRDMT reported radiation dose and estimated PSD to three different levels of threshold to assess the potential skin injuries, to assist patient follow-up, risk management and provide radiation dosimetry information in case of “Sentinel Event”. Results: The Radiation Dose Structured Report (RDSR) was found to be the prerequisite for the PRDMT systems to work seamlessly. And, the geometrical parameters (gantry and table orientation) displayed by the equipment are not necessarily implemented in the “patient centric” manner which could result in a large error in the PSD estimation. Since, the PRDMT systems obtain their pertinent data from the DICOM tags including the polarity (+ and − signs), the geometrical parameters need to be verified. Conclusion: PRDMT systems provide a more accurate PSD estimation than previously possible as the air-kerma-area dose meter become widely implemented. However, care should be exercised to correctly apply the geometrical parameters in estimating the patient dose. In addition, further refinement is necessary for these software programs to account for all geometrical parameters such as the tabletop translation in the z-direction in particular.« less

On the Impurity Parameters for Impurities Detected in the Eutectics Co-C and Pt-C and Their Role in the Estimate of the Uncertainty in the Eutectic Temperatures

NASA Astrophysics Data System (ADS)

Bloembergen, Pieter; Dong, Wei; Bai, Cheng-Yu; Wang, Tie-Jun

2011-12-01

In this paper, impurity parameters m i and k i have been calculated for a range of impurities I as detected in the eutectics Co-C and Pt-C, by means of the software package Thermo-Calc within the ternary phase spaces Co-C- I and Pt-C- I. The choice of the impurities is based upon a selection out of the results of impurity analyses performed for a representative set of samples for each of the eutectics in study. The analyses in question are glow discharge mass spectrometry (GDMS) or inductively coupled plasma mass spectrometry (ICP-mass). Tables and plots of the impurity parameters against the atomic number Z i of the impurities will be presented, as well as plots demonstrating the validity of van't Hoff's law, the cornerstone to this study, for both eutectics. For the eutectics in question, the uncertainty u( T E - T liq ) in the correction T E - T liq will be derived, where T E and T liq refer to the transition temperature of the pure system and to the liquidus temperature in the limit of zero growth rate of the solid phase during solidification of the actual system, respectively. Uncertainty estimates based upon the current scheme SIE-OME, combining the sum of individual estimates (SIE) and the overall maximum estimate (OME) are compared with two alternative schemes proposed in this paper, designated as IE-IRE, combining individual estimates (IE) and individual random estimates (IRE), and the hybrid scheme SIE-IE-IRE, combining SIE, IE, and IRE.

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes.

PubMed

Li, Baoyue; Lingsma, Hester F; Steyerberg, Ewout W; Lesaffre, Emmanuel

2011-05-23

Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC.Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain.

Star Tracker Performance Estimate with IMU

NASA Technical Reports Server (NTRS)

Aretskin-Hariton, Eliot D.; Swank, Aaron J.

2015-01-01

A software tool for estimating cross-boresight error of a star tracker combined with an inertial measurement unit (IMU) was developed to support trade studies for the Integrated Radio and Optical Communication project (iROC) at the National Aeronautics and Space Administration Glenn Research Center. Typical laser communication systems, such as the Lunar Laser Communication Demonstration (LLCD) and the Laser Communication Relay Demonstration (LCRD), use a beacon to locate ground stations. iROC is investigating the use of beaconless precision laser pointing to enable laser communication at Mars orbits and beyond. Precision attitude knowledge is essential to the iROC mission to enable high-speed steering of the optical link. The preliminary concept to achieve this precision attitude knowledge is to use star trackers combined with an IMU. The Star Tracker Accuracy (STAcc) software was developed to rapidly assess the capabilities of star tracker and IMU configurations. STAcc determines the overall cross-boresight error of a star tracker with an IMU given the characteristic parameters: quantum efficiency, aperture, apparent star magnitude, exposure time, field of view, photon spread, detector pixels, spacecraft slew rate, maximum stars used for quaternion estimation, and IMU angular random walk. This paper discusses the supporting theory used to construct STAcc, verification of the program and sample results.

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

PubMed

Ligon, Thomas S; Fröhlich, Fabian; Chis, Oana T; Banga, Julio R; Balsa-Canto, Eva; Hasenauer, Jan

2018-04-15

Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models. GenSSI 2.0 is an open-source MATLAB toolbox and available at https://github.com/genssi-developer/GenSSI. thomas.ligon@physik.uni-muenchen.de or jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Estimating Consequences of MMOD Penetrations on ISS

NASA Technical Reports Server (NTRS)

Evans, H.; Hyde, James; Christiansen, E.; Lear, D.

2017-01-01

The threat from micrometeoroid and orbital debris (MMOD) impacts on space vehicles is often quantified in terms of the probability of no penetration (PNP). However, for large spacecraft, especially those with multiple compartments, a penetration may have a number of possible outcomes. The extent of the damage (diameter of hole, crack length or penetration depth), the location of the damage relative to critical equipment or crew, crew response, and even the time of day of the penetration are among the many factors that can affect the outcome. For the International Space Station (ISS), a Monte-Carlo style software code called Manned Spacecraft Crew Survivability (MSCSurv) is used to predict the probability of several outcomes of an MMOD penetration-broadly classified as loss of crew (LOC), crew evacuation (Evac), loss of escape vehicle (LEV), and nominal end of mission (NEOM). By generating large numbers of MMOD impacts (typically in the billions) and tracking the consequences, MSCSurv allows for the inclusion of a large number of parameters and models as well as enabling the consideration of uncertainties in the models and parameters. MSCSurv builds upon the results from NASA's Bumper software (which provides the probability of penetration and critical input data to MSCSurv) to allow analysts to estimate the probability of LOC, Evac, LEV, and NEOM. This paper briefly describes the overall methodology used by NASA to quantify LOC, Evac, LEV, and NEOM with particular emphasis on describing in broad terms how MSCSurv works and its capabilities and most significant models.

Maximum likelihood techniques applied to quasi-elastic light scattering

NASA Technical Reports Server (NTRS)

Edwards, Robert V.

1992-01-01

There is a necessity of having an automatic procedure for reliable estimation of the quality of the measurement of particle size from QELS (Quasi-Elastic Light Scattering). Getting the measurement itself, before any error estimates can be made, is a problem because it is obtained by a very indirect measurement of a signal derived from the motion of particles in the system and requires the solution of an inverse problem. The eigenvalue structure of the transform that generates the signal is such that an arbitrarily small amount of noise can obliterate parts of any practical inversion spectrum. This project uses the Maximum Likelihood Estimation (MLE) as a framework to generate a theory and a functioning set of software to oversee the measurement process and extract the particle size information, while at the same time providing error estimates for those measurements. The theory involved verifying a correct form of the covariance matrix for the noise on the measurement and then estimating particle size parameters using a modified histogram approach.

FRAGS: estimation of coding sequence substitution rates from fragmentary data

PubMed Central

Swart, Estienne C; Hide, Winston A; Seoighe, Cathal

2004-01-01

Background Rates of substitution in protein-coding sequences can provide important insights into evolutionary processes that are of biomedical and theoretical interest. Increased availability of coding sequence data has enabled researchers to estimate more accurately the coding sequence divergence of pairs of organisms. However the use of different data sources, alignment protocols and methods to estimate substitution rates leads to widely varying estimates of key parameters that define the coding sequence divergence of orthologous genes. Although complete genome sequence data are not available for all organisms, fragmentary sequence data can provide accurate estimates of substitution rates provided that an appropriate and consistent methodology is used and that differences in the estimates obtainable from different data sources are taken into account. Results We have developed FRAGS, an application framework that uses existing, freely available software components to construct in-frame alignments and estimate coding substitution rates from fragmentary sequence data. Coding sequence substitution estimates for human and chimpanzee sequences, generated by FRAGS, reveal that methodological differences can give rise to significantly different estimates of important substitution parameters. The estimated substitution rates were also used to infer upper-bounds on the amount of sequencing error in the datasets that we have analysed. Conclusion We have developed a system that performs robust estimation of substitution rates for orthologous sequences from a pair of organisms. Our system can be used when fragmentary genomic or transcript data is available from one of the organisms and the other is a completely sequenced genome within the Ensembl database. As well as estimating substitution statistics our system enables the user to manage and query alignment and substitution data. PMID:15005802

Analysis of longitudinal data of beef cattle raised on pasture from northern Brazil using nonlinear models.

PubMed

Lopes, Fernando B; da Silva, Marcelo C; Marques, Ednira G; McManus, Concepta M

2012-12-01

This study was undertaken to aim of estimating the genetic parameters and trends for asymptotic weight (A) and maturity rate (k) of Nellore cattle from northern Brazil. The data set was made available by the Brazilian Association of Zebu Breeders and collected between the years of 1997 and 2007. The Von Bertalanffy, Brody, Gompertz, and logistic nonlinear models were fitted by the Gauss-Newton method to weight-age data of 45,895 animals collected quarterly of the birth to 750 days old. The curve parameters were analyzed using the procedures GLM and CORR. The estimation of (co)variance components and genetic parameters was obtained using the MTDFREML software. The estimated heritability coefficients were 0.21 ± 0.013 and 0.25 ± 0.014 for asymptotic weight and maturity rate, respectively. This indicates that selection for any trait shall results in genetic progress in the herd. The genetic correlation between A and k was negative (-0.57 ± 0.03) and indicated that animals selected for high maturity rate shall result in low asymptotic weight. The Von Bertalanffy function is adequate to establish the mean growth patterns and to predict the adult weight of Nellore cattle. This model is more accurate in predicting the birth weight of these animals and has better overall fit. The prediction of adult weight using nonlinear functions can be accurate when growth curve parameters and their (co)variance components are estimated jointly. The model used in this study can be applied to the prediction of mature weight in herds where a portion of the animals are culled before they reach the adult age.

Precise Orbital and Geodetic Parameter Estimation using SLR Observations for ILRS AAC

NASA Astrophysics Data System (ADS)

Kim, Young-Rok; Park, Eunseo; Oh, Hyungjik Jay; Park, Sang-Young; Lim, Hyung-Chul; Park, Chandeok

2013-12-01

In this study, we present results of precise orbital geodetic parameter estimation using satellite laser ranging (SLR) observations for the International Laser Ranging Service (ILRS) associate analysis center (AAC). Using normal point observations of LAGEOS-1, LAGEOS-2, ETALON-1, and ETALON-2 in SLR consolidated laser ranging data format, the NASA/ GSFC GEODYN II and SOLVE software programs were utilized for precise orbit determination (POD) and finding solutions of a terrestrial reference frame (TRF) and Earth orientation parameters (EOPs). For POD, a weekly-based orbit determination strategy was employed to process SLR observations taken from 20 weeks in 2013. For solutions of TRF and EOPs, loosely constrained scheme was used to integrate POD results of four geodetic SLR satellites. The coordinates of 11 ILRS core sites were determined and daily polar motion and polar motion rates were estimated. The root mean square (RMS) value of post-fit residuals was used for orbit quality assessment, and both the stability of TRF and the precision of EOPs by external comparison were analyzed for verification of our solutions. Results of post-fit residuals show that the RMS of the orbits of LAGEOS-1 and LAGEOS-2 are 1.20 and 1.12 cm, and those of ETALON-1 and ETALON-2 are 1.02 and 1.11 cm, respectively. The stability analysis of TRF shows that the mean value of 3D stability of the coordinates of 11 ILRS core sites is 7.0 mm. An external comparison, with respect to International Earth rotation and Reference systems Service (IERS) 08 C04 results, shows that standard deviations of polar motion XP and YP are 0.754 milliarcseconds (mas) and 0.576 mas, respectively. Our results of precise orbital and geodetic parameter estimation are reasonable and help advance research at ILRS AAC.

Statistically Self-Consistent and Accurate Errors for SuperDARN Data

NASA Astrophysics Data System (ADS)

Reimer, A. S.; Hussey, G. C.; McWilliams, K. A.

2018-01-01

The Super Dual Auroral Radar Network (SuperDARN)-fitted data products (e.g., spectral width and velocity) are produced using weighted least squares fitting. We present a new First-Principles Fitting Methodology (FPFM) that utilizes the first-principles approach of Reimer et al. (2016) to estimate the variance of the real and imaginary components of the mean autocorrelation functions (ACFs) lags. SuperDARN ACFs fitted by the FPFM do not use ad hoc or empirical criteria. Currently, the weighting used to fit the ACF lags is derived from ad hoc estimates of the ACF lag variance. Additionally, an overcautious lag filtering criterion is used that sometimes discards data that contains useful information. In low signal-to-noise (SNR) and/or low signal-to-clutter regimes the ad hoc variance and empirical criterion lead to underestimated errors for the fitted parameter because the relative contributions of signal, noise, and clutter to the ACF variance is not taken into consideration. The FPFM variance expressions include contributions of signal, noise, and clutter. The clutter is estimated using the maximal power-based self-clutter estimator derived by Reimer and Hussey (2015). The FPFM was successfully implemented and tested using synthetic ACFs generated with the radar data simulator of Ribeiro, Ponomarenko, et al. (2013). The fitted parameters and the fitted-parameter errors produced by the FPFM are compared with the current SuperDARN fitting software, FITACF. Using self-consistent statistical analysis, the FPFM produces reliable or trustworthy quantitative measures of the errors of the fitted parameters. For an SNR in excess of 3 dB and velocity error below 100 m/s, the FPFM produces 52% more data points than FITACF.

U.S. ENVIRONMENTAL PROTECTION AGENCY'S LANDFILL GAS EMISSION MODEL (LANDGEM)

EPA Science Inventory

The paper discusses EPA's available software for estimating landfill gas emissions. This software is based on a first-order decomposition rate equation using empirical data from U.S. landfills. The software provides a relatively simple approach to estimating landfill gas emissi...

Computerized Workstation for Tsunami Hazard Monitoring

NASA Astrophysics Data System (ADS)

Lavrentiev-Jr, Mikhail; Marchuk, Andrey; Romanenko, Alexey; Simonov, Konstantin; Titov, Vasiliy

2010-05-01

We present general structure and functionality of the proposed Computerized Workstation for Tsunami Hazard Monitoring (CWTHM). The tool allows interactive monitoring of hazard, tsunami risk assessment, and mitigation - at all stages, from the period of strong tsunamigenic earthquake preparation to inundation of the defended coastal areas. CWTHM is a software-hardware complex with a set of software applications, optimized to achieve best performance on hardware platforms in use. The complex is calibrated for selected tsunami source zone(s) and coastal zone(s) to be defended. The number of zones (both source and coastal) is determined, or restricted, by available hardware resources. The presented complex performs monitoring of selected tsunami source zone via the Internet. The authors developed original algorithms, which enable detection of the preparation zone of the strong underwater earthquake automatically. For the so-determined zone the event time, magnitude and spatial location of tsunami source are evaluated by means of energy of the seismic precursors (foreshocks) analysis. All the above parameters are updated after each foreshock. Once preparing event is detected, several scenarios are forecasted for wave amplitude parameters as well as the inundation zone. Estimations include the lowest and the highest wave amplitudes and the least and the most inundation zone. In addition to that, the most probable case is calculated. In case of multiple defended coastal zones, forecasts and estimates can be done in parallel. Each time the simulated model wave reaches deep ocean buoys or tidal gauge, expected values of wave parameters and inundation zones are updated with historical events information and pre-calculated scenarios. The Method of Splitting Tsunami (MOST) software package is used for mathematical simulation. The authors suggest code acceleration for deep water wave propagation. As a result, performance is 15 times faster compared to MOST, original version. Performance gain is achieved by compiler options, use of optimized libraries, and advantages of OpenMP parallel technology. Moreover, it is possible to achieve 100 times code acceleration by using modern Graphics Processing Units (GPU). Parallel evaluation of inundation zones for multiple coastal zones is also available. All computer codes can be easily assembled under MS Windows and Unix OS family. Although software is virtually platform independent, the most performance gain is achieved while using the recommended hardware components. When the seismic event occurs, all valuable parameters are updated with seismic data and wave propagation monitoring is enabled. As soon as the wave passes each deep ocean tsunameter, parameters of the initial displacement at source are updated from direct calculations based on original algorithms. For better source reconstruction, a combination of two methods is used: optimal unit source linear combination from preliminary calculated database and direct numerical inversion along the wave ray between real source and particular measurement buoys. Specific dissipation parameter along with the wave ray is also taken into account. During the entire wave propagation process the expected wave parameters and inundation zone(s) characteristics are updated with all available information. If recommended hardware components are used, monitoring results are available in real time. The suggested version of CWTHM has been tested by analyzing seismic precursors (foreshocks) and the measured tsunami waves at North Pacific for the Central Kuril's tsunamigenic earthquake of November 15, 2006.

GPS Water Vapor Tomography Based on Accurate Estimations of the GPS Tropospheric Parameters

NASA Astrophysics Data System (ADS)

Champollion, C.; Masson, F.; Bock, O.; Bouin, M.; Walpersdorf, A.; Doerflinger, E.; van Baelen, J.; Brenot, H.

2003-12-01

The Global Positioning System (GPS) is now a common technique for the retrieval of zenithal integrated water vapor (IWV). Further applications in meteorology need also slant integrated water vapor (SIWV) which allow to precisely define the high variability of tropospheric water vapor at different temporal and spatial scales. Only precise estimations of IWV and horizontal gradients allow the estimation of accurate SIWV. We present studies developed to improve the estimation of tropospheric water vapor from GPS data. Results are obtained from several field experiments (MAP, ESCOMPTE, OHM-CV, IHOP, .). First IWV are estimated using different GPS processing strategies and results are compared to radiosondes. The role of the reference frame and the a priori constraints on the coordinates of the fiducial and local stations is generally underestimated. It seems to be of first order in the estimation of the IWV. Second we validate the estimated horizontal gradients comparing zenith delay gradients and single site gradients. IWV, gradients and post-fit residuals are used to construct slant integrated water delays. Validation of the SIWV is under progress comparing GPS SIWV, Lidar measurements and high resolution meteorological models (Meso-NH). A careful analysis of the post-fit residuals is needed to separate tropospheric signal from multipaths. The slant tropospheric delays are used to study the 3D heterogeneity of the troposphere. We develop a tomographic software to model the three-dimensional distribution of the tropospheric water vapor from GPS data. The software is applied to the ESCOMPTE field experiment, a dense network of 17 dual frequency GPS receivers operated in southern France. Three inversions have been successfully compared to three successive radiosonde launches. Good resolution is obtained up to heights of 3000 m.

The Toxicity Estimation Software Tool (T.E.S.T.)

EPA Science Inventory

The Toxicity Estimation Software Tool (T.E.S.T.) has been developed to estimate toxicological values for aquatic and mammalian species considering acute and chronic endpoints for screening purposes within TSCA and REACH programs.

VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data

PubMed Central

Daunizeau, Jean; Adam, Vincent; Rigoux, Lionel

2014-01-01

This work is in line with an on-going effort tending toward a computational (quantitative and refutable) understanding of human neuro-cognitive processes. Many sophisticated models for behavioural and neurobiological data have flourished during the past decade. Most of these models are partly unspecified (i.e. they have unknown parameters) and nonlinear. This makes them difficult to peer with a formal statistical data analysis framework. In turn, this compromises the reproducibility of model-based empirical studies. This work exposes a software toolbox that provides generic, efficient and robust probabilistic solutions to the three problems of model-based analysis of empirical data: (i) data simulation, (ii) parameter estimation/model selection, and (iii) experimental design optimization. PMID:24465198

An extended BET format for La RC shuttle experiments: Definition and development

NASA Technical Reports Server (NTRS)

Findlay, J. T.; Kelly, G. M.; Henry, M. W.

1981-01-01

A program for shuttle post-flight data reduction is discussed. An extended Best Estimate Trajectory (BET) file was developed. The extended format results in some subtle changes to the header record. The major change is the addition of twenty-six words to each data record. These words include atmospheric related parameters, body axis rate and acceleration data, computed aerodynamic coefficients, and angular accelerations. These parameters were added to facilitate post-flight aerodynamic coefficient determinations as well as shuttle entry air data sensor analyses. Software (NEWBET) was developed to generate the extended BET file utilizing the previously defined ENTREE BET, a dynamic data file which may be either derived inertial measurement unit data or aerodynamic coefficient instrument package data, and some atmospheric information.

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies

USGS Publications Warehouse

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J. Andrew

2010-01-01

We develop a hierarchical capture–recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture–recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture–recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

Examining the effect of initialization strategies on the performance of Gaussian mixture modeling.

PubMed

Shireman, Emilie; Steinley, Douglas; Brusco, Michael J

2017-02-01

Mixture modeling is a popular technique for identifying unobserved subpopulations (e.g., components) within a data set, with Gaussian (normal) mixture modeling being the form most widely used. Generally, the parameters of these Gaussian mixtures cannot be estimated in closed form, so estimates are typically obtained via an iterative process. The most common estimation procedure is maximum likelihood via the expectation-maximization (EM) algorithm. Like many approaches for identifying subpopulations, finite mixture modeling can suffer from locally optimal solutions, and the final parameter estimates are dependent on the initial starting values of the EM algorithm. Initial values have been shown to significantly impact the quality of the solution, and researchers have proposed several approaches for selecting the set of starting values. Five techniques for obtaining starting values that are implemented in popular software packages are compared. Their performances are assessed in terms of the following four measures: (1) the ability to find the best observed solution, (2) settling on a solution that classifies observations correctly, (3) the number of local solutions found by each technique, and (4) the speed at which the start values are obtained. On the basis of these results, a set of recommendations is provided to the user.

A less field-intensive robust design for estimating demographic parameters with Mark-resight data

USGS Publications Warehouse

McClintock, B.T.; White, Gary C.

2009-01-01

The robust design has become popular among animal ecologists as a means for estimating population abundance and related demographic parameters with mark-recapture data. However, two drawbacks of traditional mark-recapture are financial cost and repeated disturbance to animals. Mark-resight methodology may in many circumstances be a less expensive and less invasive alternative to mark-recapture, but the models developed to date for these data have overwhelmingly concentrated only on the estimation of abundance. Here we introduce a mark-resight model analogous to that used in mark-recapture for the simultaneous estimation of abundance, apparent survival, and transition probabilities between observable and unobservable states. The model may be implemented using standard statistical computing software, but it has also been incorporated into the freeware package Program MARK. We illustrate the use of our model with mainland New Zealand Robin (Petroica australis) data collected to ascertain whether this methodology may be a reliable alternative for monitoring endangered populations of a closely related species inhabiting the Chatham Islands. We found this method to be a viable alternative to traditional mark-recapture when cost or disturbance to species is of particular concern in long-term population monitoring programs. ?? 2009 by the Ecological Society of America.

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies.

PubMed

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J Andrew

2010-11-01

We develop a hierarchical capture-recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture-recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture-recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

Extracting galactic structure parameters from multivariated density estimation

NASA Technical Reports Server (NTRS)

Chen, B.; Creze, M.; Robin, A.; Bienayme, O.

1992-01-01

Multivariate statistical analysis, including includes cluster analysis (unsupervised classification), discriminant analysis (supervised classification) and principle component analysis (dimensionlity reduction method), and nonparameter density estimation have been successfully used to search for meaningful associations in the 5-dimensional space of observables between observed points and the sets of simulated points generated from a synthetic approach of galaxy modelling. These methodologies can be applied as the new tools to obtain information about hidden structure otherwise unrecognizable, and place important constraints on the space distribution of various stellar populations in the Milky Way. In this paper, we concentrate on illustrating how to use nonparameter density estimation to substitute for the true densities in both of the simulating sample and real sample in the five-dimensional space. In order to fit model predicted densities to reality, we derive a set of equations which include n lines (where n is the total number of observed points) and m (where m: the numbers of predefined groups) unknown parameters. A least-square estimation will allow us to determine the density law of different groups and components in the Galaxy. The output from our software, which can be used in many research fields, will also give out the systematic error between the model and the observation by a Bayes rule.

Fitting a function to time-dependent ensemble averaged data.

PubMed

Fogelmark, Karl; Lomholt, Michael A; Irbäck, Anders; Ambjörnsson, Tobias

2018-05-03

Time-dependent ensemble averages, i.e., trajectory-based averages of some observable, are of importance in many fields of science. A crucial objective when interpreting such data is to fit these averages (for instance, squared displacements) with a function and extract parameters (such as diffusion constants). A commonly overlooked challenge in such function fitting procedures is that fluctuations around mean values, by construction, exhibit temporal correlations. We show that the only available general purpose function fitting methods, correlated chi-square method and the weighted least squares method (which neglects correlation), fail at either robust parameter estimation or accurate error estimation. We remedy this by deriving a new closed-form error estimation formula for weighted least square fitting. The new formula uses the full covariance matrix, i.e., rigorously includes temporal correlations, but is free of the robustness issues, inherent to the correlated chi-square method. We demonstrate its accuracy in four examples of importance in many fields: Brownian motion, damped harmonic oscillation, fractional Brownian motion and continuous time random walks. We also successfully apply our method, weighted least squares including correlation in error estimation (WLS-ICE), to particle tracking data. The WLS-ICE method is applicable to arbitrary fit functions, and we provide a publically available WLS-ICE software.

Sci—Thur AM: YIS - 11: Estimation of Bladder-Wall Cumulative Dose in Multi-Fraction Image-Based Gynaecological Brachytherapy Using Deformable Point Set Registration

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

Zakariaee, R; Brown, C J; Hamarneh, G

2014-08-15

Dosimetric parameters based on dose-volume histograms (DVH) of contoured structures are routinely used to evaluate dose delivered to target structures and organs at risk. However, the DVH provides no information on the spatial distribution of the dose in situations of repeated fractions with changes in organ shape or size. The aim of this research was to develop methods to more accurately determine geometrically localized, cumulative dose to the bladder wall in intracavitary brachytherapy for cervical cancer. The CT scans and treatment plans of 20 cervical cancer patients were used. Each patient was treated with five high-dose-rate (HDR) brachytherapy fractions ofmore » 600cGy prescribed dose. The bladder inner and outer surfaces were delineated using MIM Maestro software (MIM Software Inc.) and were imported into MATLAB (MathWorks) as 3-dimensional point clouds constituting the “bladder wall”. A point-set registration toolbox for MATLAB, Coherent Point Drift (CPD), was used to non-rigidly transform the bladder-wall points from four of the fractions to the coordinate system of the remaining (reference) fraction, which was chosen to be the emptiest bladder for each patient. The doses were accumulated on the reference fraction and new cumulative dosimetric parameters were calculated. The LENT-SOMA toxicity scores of these patients were studied against the cumulative dose parameters. Based on this study, there was no significant correlation between the toxicity scores and the determined cumulative dose parameters.« less

Calibrating a Soil-Vegetation-Atmosphere system with a genetical algorithm

NASA Astrophysics Data System (ADS)

Schneider, S.; Jacques, D.; Mallants, D.

2009-04-01

Accuracy of model prediction is well known for being very sensitive to the quality of the calibration of the model. It is also known that quantifying soil hydraulic parameters in a Soil-Vegetation-Atmosphere (SVA) system is a highly non-linear parameter estimation problem, and that robust methods are needed to avoid the optimization process to lead to non-optimal parameters. Evolutionary algorithms and specifically genetic algorithms (GAs) are very well suited for those complex parameter optimization problems. The SVA system in this study concerns a pine stand on a heterogeneous sandy soil (podzol) in the north of Belgium (Campine region). Throughfall and other meteorological data and water contents at different soil depths have been recorded during one year at a daily time step. The water table level, which is varying between 95 and 170 cm, has been recorded with a frequency of 0.5 hours. Based on the profile description, four soil layers have been distinguished in the podzol and used for the numerical simulation with the hydrus1D model (Simunek and al., 2005). For the inversion procedure the MYGA program (Yedder, 2002), which is an elitism GA, was used. Optimization was based on the water content measurements realized at the depths of 10, 20, 40, 50, 60, 70, 90, 110, and 120 cm to estimate parameters describing the unsaturated hydraulic soil properties of the different soil layers. Comparison between the modeled and measured water contents shows a good similarity during the simulated year. Impacts of short and intensive events (rainfall) on the water content of the soil are also well reproduced. Errors on predictions are on average equal to 5%, which is considered as a good result. A. Ben Haj Yedder. Numerical optimization and optimal control : (molecular chemistry applications). PhD thesis, Ecole Nationale des Ponts et Chaussées, 2002. Šimůnek, J., M. Th. van Genuchten, and M. Šejna, The HYDRUS-1D software package for simulating the one-dimensional movement of water, heat, and multiple solutes in variably saturated media. Version 3.0, HYDRUS Software Series 1, Department of Environmental Sciences, University of California Riverside, Riverside, CA, 270 pp., 2005.

Hiereachical Bayesian Model for Combining Geochemical and Geophysical Data for Environmental Applications Software

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

Chen, Jinsong

2013-05-01

Development of a hierarchical Bayesian model to estimate the spatiotemporal distribution of aqueous geochemical parameters associated with in-situ bioremediation using surface spectral induced polarization (SIP) data and borehole geochemical measurements collected during a bioremediation experiment at a uranium-contaminated site near Rifle, Colorado. The SIP data are first inverted for Cole-Cole parameters including chargeability, time constant, resistivity at the DC frequency and dependence factor, at each pixel of two-dimensional grids using a previously developed stochastic method. Correlations between the inverted Cole-Cole parameters and the wellbore-based groundwater chemistry measurements indicative of key metabolic processes within the aquifer (e.g. ferrous iron, sulfate, uranium)more » were established and used as a basis for petrophysical model development. The developed Bayesian model consists of three levels of statistical sub-models: 1) data model, providing links between geochemical and geophysical attributes, 2) process model, describing the spatial and temporal variability of geochemical properties in the subsurface system, and 3) parameter model, describing prior distributions of various parameters and initial conditions. The unknown parameters are estimated using Markov chain Monte Carlo methods. By combining the temporally distributed geochemical data with the spatially distributed geophysical data, we obtain the spatio-temporal distribution of ferrous iron, sulfate and sulfide, and their associated uncertainity information. The obtained results can be used to assess the efficacy of the bioremediation treatment over space and time and to constrain reactive transport models.« less

Characterization of human passive muscles for impact loads using genetic algorithm and inverse finite element methods.

PubMed

Chawla, A; Mukherjee, S; Karthikeyan, B

2009-02-01

The objective of this study is to identify the dynamic material properties of human passive muscle tissues for the strain rates relevant to automobile crashes. A novel methodology involving genetic algorithm (GA) and finite element method is implemented to estimate the material parameters by inverse mapping the impact test data. Isolated unconfined impact tests for average strain rates ranging from 136 s(-1) to 262 s(-1) are performed on muscle tissues. Passive muscle tissues are modelled as isotropic, linear and viscoelastic material using three-element Zener model available in PAMCRASH(TM) explicit finite element software. In the GA based identification process, fitness values are calculated by comparing the estimated finite element forces with the measured experimental forces. Linear viscoelastic material parameters (bulk modulus, short term shear modulus and long term shear modulus) are thus identified at strain rates 136 s(-1), 183 s(-1) and 262 s(-1) for modelling muscles. Extracted optimal parameters from this study are comparable with reported parameters in literature. Bulk modulus and short term shear modulus are found to be more influential in predicting the stress-strain response than long term shear modulus for the considered strain rates. Variations within the set of parameters identified at different strain rates indicate the need for new or improved material model, which is capable of capturing the strain rate dependency of passive muscle response with single set of material parameters for wide range of strain rates.

Inverse modeling with RZWQM2 to predict water quality

USGS Publications Warehouse

Nolan, Bernard T.; Malone, Robert W.; Ma, Liwang; Green, Christopher T.; Fienen, Michael N.; Jaynes, Dan B.

2011-01-01

This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the Walnut Creek watershed in central Iowa, which is predominantly in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals and sensitivities. We describe operation of PEST in both parameter estimation and predictive analysis modes. The goal of parameter estimation is to identify a unique set of parameters that minimize a weighted least squares objective function, and the goal of predictive analysis is to construct a nonlinear confidence interval for a prediction of interest by finding a set of parameters that maximizes or minimizes the prediction while maintaining the model in a calibrated state. We also describe PEST utilities (PAR2PAR, TSPROC) for maintaining ordered relations among model parameters (e.g., soil root growth factor) and for post-processing of RZWQM2 outputs representing different cropping practices at the Iowa site. Inverse modeling provided reasonable fits to observed water and N fluxes and directly benefitted the modeling through: (i) simultaneous adjustment of multiple parameters versus one-at-a-time adjustment in manual approaches; (ii) clear indication by convergence criteria of when calibration is complete; (iii) straightforward detection of nonunique and insensitive parameters, which can affect the stability of PEST and RZWQM2; and (iv) generation of confidence intervals for uncertainty analysis of parameters and model predictions. Composite scaled sensitivities, which reflect the total information provided by the observations for a parameter, indicated that most of the RZWQM2 parameters at the California study site (CA) and Iowa study site (IA) could be reliably estimated by regression. Correlations obtained in the CA case indicated that all model parameters could be uniquely estimated by inverse modeling. Although water content at field capacity was highly correlated with bulk density (−0.94), the correlation is less than the threshold for nonuniqueness (0.95, absolute value basis). Additionally, we used truncated singular value decomposition (SVD) at CA to mitigate potential problems with highly correlated and insensitive parameters. Singular value decomposition estimates linear combinations (eigenvectors) of the original process-model parameters. Parameter confidence intervals (CIs) at CA indicated that parameters were reliably estimated with the possible exception of an organic pool transfer coefficient (R45), which had a comparatively wide CI. However, the 95% confidence interval for R45 (0.03–0.35) is mostly within the range of values reported for this parameter. Predictive analysis at CA generated confidence intervals that were compared with independently measured annual water flux (groundwater recharge) and median nitrate concentration in a collocated monitoring well as part of model evaluation. Both the observed recharge (42.3 cm yr−1) and nitrate concentration (24.3 mg L−1) were within their respective 90% confidence intervals, indicating that overall model error was within acceptable limits.

Software Cost-Estimation Model

NASA Technical Reports Server (NTRS)

Tausworthe, R. C.

1985-01-01

Software Cost Estimation Model SOFTCOST provides automated resource and schedule model for software development. Combines several cost models found in open literature into one comprehensive set of algorithms. Compensates for nearly fifty implementation factors relative to size of task, inherited baseline, organizational and system environment and difficulty of task.

ToxPredictor: a Toxicity Estimation Software Tool

EPA Science Inventory

The Computational Toxicology Team within the National Risk Management Research Laboratory has developed a software tool that will allow the user to estimate the toxicity for a variety of endpoints (such as acute aquatic toxicity). The software tool is coded in Java and can be ac...

High-throughput method for ear phenotyping and kernel weight estimation in maize using ear digital imaging.

PubMed

Makanza, R; Zaman-Allah, M; Cairns, J E; Eyre, J; Burgueño, J; Pacheco, Ángela; Diepenbrock, C; Magorokosho, C; Tarekegne, A; Olsen, M; Prasanna, B M

2018-01-01

Grain yield, ear and kernel attributes can assist to understand the performance of maize plant under different environmental conditions and can be used in the variety development process to address farmer's preferences. These parameters are however still laborious and expensive to measure. A low-cost ear digital imaging method was developed that provides estimates of ear and kernel attributes i.e., ear number and size, kernel number and size as well as kernel weight from photos of ears harvested from field trial plots. The image processing method uses a script that runs in a batch mode on ImageJ; an open source software. Kernel weight was estimated using the total kernel number derived from the number of kernels visible on the image and the average kernel size. Data showed a good agreement in terms of accuracy and precision between ground truth measurements and data generated through image processing. Broad-sense heritability of the estimated parameters was in the range or higher than that for measured grain weight. Limitation of the method for kernel weight estimation is discussed. The method developed in this work provides an opportunity to significantly reduce the cost of selection in the breeding process, especially for resource constrained crop improvement programs and can be used to learn more about the genetic bases of grain yield determinants.

Combining nutation and surface gravity observations to estimate the Earth's core and inner core resonant frequencies

NASA Astrophysics Data System (ADS)

Ziegler, Yann; Lambert, Sébastien; Rosat, Séverine; Nurul Huda, Ibnu; Bizouard, Christian

2017-04-01

Nutation time series derived from very long baseline interferometry (VLBI) and time varying surface gravity data recorded by superconducting gravimeters (SG) have long been used separately to assess the Earth's interior via the estimation of the free core and inner core resonance effects on nutation or tidal gravity. The results obtained from these two techniques have been shown recently to be consistent, making relevant the combination of VLBI and SG observables and the estimation of Earth's interior parameters in a single inversion. We present here the intermediate results of the ongoing project of combining nutation and surface gravity time series to improve estimates of the Earth's core and inner core resonant frequencies. We use VLBI nutation time series spanning 1984-2016 derived by the International VLBI Service for geodesy and astrometry (IVS) as the result of a combination of inputs from various IVS analysis centers, and surface gravity data from about 15 SG stations. We address here the resonance model used for describing the Earth's interior response to tidal excitation, the data preparation consisting of the error recalibration and amplitude fitting for nutation data, and processing of SG time-varying gravity to remove any gaps, spikes, steps and other disturbances, followed by the tidal analysis with the ETERNA 3.4 software package, the preliminary estimates of the resonant periods, and the correlations between parameters.

Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches.

PubMed

Chan, Jennifer S K

2016-05-01

Dropouts are common in longitudinal study. If the dropout probability depends on the missing observations at or after dropout, this type of dropout is called informative (or nonignorable) dropout (ID). Failure to accommodate such dropout mechanism into the model will bias the parameter estimates. We propose a conditional autoregressive model for longitudinal binary data with an ID model such that the probabilities of positive outcomes as well as the drop-out indicator in each occasion are logit linear in some covariates and outcomes. This model adopting a marginal model for outcomes and a conditional model for dropouts is called a selection model. To allow for the heterogeneity and clustering effects, the outcome model is extended to incorporate mixture and random effects. Lastly, the model is further extended to a novel model that models the outcome and dropout jointly such that their dependency is formulated through an odds ratio function. Parameters are estimated by a Bayesian approach implemented using the user-friendly Bayesian software WinBUGS. A methadone clinic dataset is analyzed to illustrate the proposed models. Result shows that the treatment time effect is still significant but weaker after allowing for an ID process in the data. Finally the effect of drop-out on parameter estimates is evaluated through simulation studies. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Toxicity Estimation Software Tool (TEST)

EPA Science Inventory

The Toxicity Estimation Software Tool (TEST) was developed to allow users to easily estimate the toxicity of chemicals using Quantitative Structure Activity Relationships (QSARs) methodologies. QSARs are mathematical models used to predict measures of toxicity from the physical c...

The Modular Modeling System (MMS): A toolbox for water- and environmental-resources management

USGS Publications Warehouse

Leavesley, G.H.; Markstrom, S.L.; Viger, R.J.; Hay, L.E.; ,

2005-01-01

The increasing complexity of water- and environmental-resource problems require modeling approaches that incorporate knowledge from a broad range of scientific and software disciplines. To address this need, the U.S. Geological Survey (USGS) has developed the Modular Modeling System (MMS). MMS is an integrated system of computer software for model development, integration, and application. Its modular design allows a high level of flexibility and adaptability to enable modelers to incorporate their own software into a rich array of built-in models and modeling tools. These include individual process models, tightly coupled models, loosely coupled models, and fully- integrated decision support systems. A geographic information system (GIS) interface, the USGS GIS Weasel, has been integrated with MMS to enable spatial delineation and characterization of basin and ecosystem features, and to provide objective parameter-estimation methods for models using available digital data. MMS provides optimization and sensitivity-analysis tools to analyze model parameters and evaluate the extent to which uncertainty in model parameters affects uncertainty in simulation results. MMS has been coupled with the Bureau of Reclamation object-oriented reservoir and river-system modeling framework, RiverWare, to develop models to evaluate and apply optimal resource-allocation and management strategies to complex, operational decisions on multipurpose reservoir systems and watersheds. This decision support system approach has been developed, tested, and implemented in the Gunnison, Yakima, San Joaquin, Rio Grande, and Truckee River basins of the western United States. MMS is currently being coupled with the U.S. Forest Service model SIMulating Patterns and Processes at Landscape Scales (SIMPPLLE) to assess the effects of alternative vegetation-management strategies on a variety of hydrological and ecological responses. Initial development and testing of the MMS-SIMPPLLE integration is being conducted on the Colorado Plateau region of the western United Sates.

Impact of orbit, clock and EOP errors in GNSS Precise Point Positioning

NASA Astrophysics Data System (ADS)

Hackman, C.

2012-12-01

Precise point positioning (PPP; [1]) has gained ever-increasing usage in GNSS carrier-phase positioning, navigation and timing (PNT) since its inception in the late 1990s. In this technique, high-precision satellite clocks, satellite ephemerides and earth-orientation parameters (EOPs) are applied as fixed input by the user in order to estimate receiver/location-specific quantities such as antenna coordinates, troposphere delay and receiver-clock corrections. This is in contrast to "network" solutions, in which (typically) less-precise satellite clocks, satellite ephemerides and EOPs are used as input, and in which these parameters are estimated simultaneously with the receiver/location-specific parameters. The primary reason for increased PPP application is that it offers most of the benefits of a network solution with a smaller computing cost. In addition, the software required to do PPP positioning can be simpler than that required for network solutions. Finally, PPP permits high-precision positioning of single or sparsely spaced receivers that may have few or no GNSS satellites in common view. A drawback of PPP is that the accuracy of the results depend directly on the accuracy of the supplied orbits, clocks and EOPs, since these parameters are not adjusted during the processing. In this study, we will examine the impact of orbit, EOP and satellite clock estimates on PPP solutions. Our primary focus will be the impact of these errors on station coordinates; however the study may be extended to error propagation into receiver-clock corrections and/or troposphere estimates if time permits. Study motivation: the United States Naval Observatory (USNO) began testing PPP processing using its own predicted orbits, clocks and EOPs in Summer 2012 [2]. The results of such processing could be useful for real- or near-real-time applications should they meet accuracy/precision requirements. Understanding how errors in satellite clocks, satellite orbits and EOPs propagate into PPP positioning and timing results allows researchers to focus their improvement efforts in areas most in need of attention. The initial study will be conducted using the simulation capabilities of Bernese GPS Software and extended to using real data if time permits. [1] J.F. Zumberge, M.B. Heflin, D.C. Jefferson, M.M. Watkins and F.H. Webb, Precise point positioning for the efficient and robust analysis of GPS data from large networks, J. Geophys. Res., 102(B3), 5005-5017, doi:10.1029/96JB03860, 1997. [2] C. Hackman, S.M. Byram, V.J. Slabinski and J.C. Tracey, Near-real-time and other high-precision GNSS-based orbit/clock/earth-orientation/troposphere parameters available from USNO, Proc. 2012 ION Joint Navigation Conference, 15 pp., in press, 2012.

Advanced Integrated Display System V/STOL Program Performance Specification. Volume I.

DTIC Science & Technology

1980-06-01

sensor inputs required before the sensor can be designated acceptable. The reactivation count of each sensor parameter which satisfies its veri...129 3.5.2 AIDS Configuration Parameters .............. 133 3.5.3 AIDS Throughput Requirements ............... 133 4 QUALITY ASSURANCE...lists the adaptation parameters of the AIDS software; these parameters include the throughput and memory requirements of the software. 3.2 SYSTEM

An objective analysis of the dynamic nature of field capacity

NASA Astrophysics Data System (ADS)

Twarakavi, Navin K. C.; Sakai, Masaru; Å Imå¯Nek, Jirka

2009-10-01

Field capacity is one of the most commonly used, and yet poorly defined, soil hydraulic properties. Traditionally, field capacity has been defined as the amount of soil moisture after excess water has drained away and the rate of downward movement has materially decreased. Unfortunately, this qualitative definition does not lend itself to an unambiguous quantitative approach for estimation. Because of the vagueness in defining what constitutes "drainage of excess water" from a soil, the estimation of field capacity has often been based upon empirical guidelines. These empirical guidelines are either time, pressure, or flux based. In this paper, we developed a numerical approach to estimate field capacity using a flux-based definition. The resulting approach was implemented on the soil parameter data set used by Schaap et al. (2001), and the estimated field capacity was compared to traditional definitions of field capacity. The developed modeling approach was implemented using the HYDRUS-1D software with the capability of simultaneously estimating field capacity for multiple soils with soil hydraulic parameter data. The Richards equation was used in conjunction with the van Genuchten-Mualem model to simulate variably saturated flow in a soil. Using the modeling approach to estimate field capacity also resulted in additional information such as (1) the pressure head, at which field capacity is attained, and (2) the drainage time needed to reach field capacity from saturated conditions under nonevaporative conditions. We analyzed the applicability of the modeling-based approach to estimate field capacity on real-world soils data. We also used the developed method to create contour diagrams showing the variation of field capacity with texture. It was found that using benchmark pressure heads to estimate field capacity from the retention curve leads to inaccurate results. Finally, a simple analytical equation was developed to predict field capacity from soil hydraulic parameter information. The analytical equation was found to be effective in its ability to predict field capacities.

TEST (Toxicity Estimation Software Tool) Ver 4.1

EPA Science Inventory

The Toxicity Estimation Software Tool (T.E.S.T.) has been developed to allow users to easily estimate toxicity and physical properties using a variety of QSAR methodologies. T.E.S.T allows a user to estimate toxicity without requiring any external programs. Users can input a chem...

Dose-escalation designs in oncology: ADEPT and the CRM.

PubMed

Shu, Jianfen; O'Quigley, John

2008-11-20

The ADEPT software package is not a statistical method in its own right as implied by Gerke and Siedentop (Statist. Med. 2008; DOI: 10.1002/sim.3037). ADEPT implements two-parameter CRM models as described in O'Quigley et al. (Biometrics 1990; 46(1):33-48). All of the basic ideas (use of a two-parameter logistic model, use of a two-dimensional prior for the unknown slope and intercept parameters, sequential estimation and subsequent patient allocation based on minimization of some loss function, flexibility to use cohorts instead of one by one inclusion) are strictly identical. The only, and quite trivial, difference arises in the setting of the prior. O'Quigley et al. (Biometrics 1990; 46(1):33-48) used priors having an analytic expression whereas Whitehead and Brunier (Statist. Med. 1995; 14:33-48) use pseudo-data to play the role of the prior. The question of interest is whether two-parameter CRM works as well, or better, than the one-parameter CRM recommended in O'Quigley et al. (Biometrics 1990; 46(1):33-48). Gerke and Siedentop argue that it does. The published literature suggests otherwise. The conclusions of Gerke and Siedentop stem from three highly particular, and somewhat contrived, situations. Unlike one-parameter CRM (Biometrika 1996; 83:395-405; J. Statist. Plann. Inference 2006; 136:1765-1780; Biometrika 2005; 92:863-873), no statistical properties appear to have been studied for two-parameter CRM. In particular, for two-parameter CRM, the parameter estimates are inconsistent. This ought to be a source of major concern to those proposing its use. Worse still, for finite samples the behavior of estimates can be quite wild despite having incorporated the kind of dampening priors discussed by Gerke and Siedentop. An example in which we illustrate this behavior describes a single patient included at level 1 of 6 levels and experiencing a dose limiting toxicity. The subsequent recommendation is to experiment at level 6! Such problematic behavior is not common. Even so, we show that the allocation behavior of two-parameter CRM is very much less stable than that of one-parameter CRM.

Wrist Actigraphy

PubMed Central

Hakim, Alex D.

2011-01-01

To record sleep, actigraph devices are worn on the wrist and record movements that can be used to estimate sleep parameters with specialized algorithms in computer software programs. With the recent establishment of a Current Procedural Terminology code for wrist actigraphy, this technology is being used increasingly in clinical settings as actigraphy has the advantage of providing objective information on sleep habits in the patient’s natural sleep environment. Actigraphy has been well validated for the estimation of nighttime sleep parameters across age groups, but the validity of the estimation of sleep-onset latency and daytime sleeping is limited. Clinical guidelines and research suggest that wrist actigraphy is particularly useful in the documentation of sleep patterns prior to a multiple sleep latency test, in the evaluation of circadian rhythm sleep disorders, to evaluate treatment outcomes, and as an adjunct to home monitoring of sleep-disordered breathing. Actigraphy has also been well studied in the evaluation of sleep in the context of depression and dementia. Although actigraphy should not be viewed as a substitute for clinical interviews, sleep diaries, or overnight polysomnography when indicated, it can provide useful information about sleep in the natural sleep environment and/or when extended monitoring is clinically indicated. PMID:21652563

Quantitative software models for the estimation of cost, size, and defects

NASA Technical Reports Server (NTRS)

Hihn, J.; Bright, L.; Decker, B.; Lum, K.; Mikulski, C.; Powell, J.

2002-01-01

The presentation will provide a brief overview of the SQI measurement program as well as describe each of these models and how they are currently being used in supporting JPL project, task and software managers to estimate and plan future software systems and subsystems.

Modeling individual effects in the Cormack-Jolly-Seber Model: A state-space formulation

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

In population and evolutionary biology, there exists considerable interest in individual heterogeneity in parameters of demographic models for open populations. However, flexible and practical solutions to the development of such models have proven to be elusive. In this article, I provide a state-space formulation of open population capture-recapture models with individual effects. The state-space formulation provides a generic and flexible framework for modeling and inference in models with individual effects, and it yields a practical means of estimation in these complex problems via contemporary methods of Markov chain Monte Carlo. A straightforward implementation can be achieved in the software package WinBUGS. I provide an analysis of a simple model with constant parameter detection and survival probability parameters. A second example is based on data from a 7-year study of European dippers, in which a model with year and individual effects is fitted.

A curve fitting method for extrinsic camera calibration from a single image of a cylindrical object

NASA Astrophysics Data System (ADS)

Winkler, A. W.; Zagar, B. G.

2013-08-01

An important step in the process of optical steel coil quality assurance is to measure the proportions of width and radius of steel coils as well as the relative position and orientation of the camera. This work attempts to estimate these extrinsic parameters from single images by using the cylindrical coil itself as the calibration target. Therefore, an adaptive least-squares algorithm is applied to fit parametrized curves to the detected true coil outline in the acquisition. The employed model allows for strictly separating the intrinsic and the extrinsic parameters. Thus, the intrinsic camera parameters can be calibrated beforehand using available calibration software. Furthermore, a way to segment the true coil outline in the acquired images is motivated. The proposed optimization method yields highly accurate results and can be generalized even to measure other solids which cannot be characterized by the identification of simple geometric primitives.

Uncertainty and Sensitivity of Direct Economic Flood Damages: the FloodRisk Free and Open-Source Software

NASA Astrophysics Data System (ADS)

Albano, R.; Sole, A.; Mancusi, L.; Cantisani, A.; Perrone, A.

2017-12-01

The considerable increase of flood damages in the the past decades has shifted in Europe the attention from protection against floods to managing flood risks. In this context, the expected damages assessment represents a crucial information within the overall flood risk management process. The present paper proposes an open source software, called FloodRisk, that is able to operatively support stakeholders in the decision making processes with a what-if approach by carrying out the rapid assessment of the flood consequences, in terms of direct economic damage and loss of human lives. The evaluation of the damage scenarios, trough the use of the GIS software proposed here, is essential for cost-benefit or multi-criteria analysis of risk mitigation alternatives. However, considering that quantitative assessment of flood damages scenarios is characterized by intrinsic uncertainty, a scheme has been developed to identify and quantify the role of the input parameters in the total uncertainty of flood loss model application in urban areas with mild terrain and complex topography. By the concept of parallel models, the contribution of different module and input parameters to the total uncertainty is quantified. The results of the present case study have exhibited a high epistemic uncertainty on the damage estimation module and, in particular, on the type and form of the utilized damage functions, which have been adapted and transferred from different geographic and socio-economic contexts because there aren't depth-damage functions that are specifically developed for Italy. Considering that uncertainty and sensitivity depend considerably on local characteristics, the epistemic uncertainty associated with the risk estimate is reduced by introducing additional information into the risk analysis. In the light of the obtained results, it is evident the need to produce and disseminate (open) data to develop micro-scale vulnerability curves. Moreover, the urgent need to push forward research into the implementation of methods and models for the assimilation of uncertainties in decision-making processes emerges.

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, Andreas; Künsch, Hans Rudolf; Schwierz, Cornelia; Stahel, Werner A.

2013-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outliers affect the modelling of the large-scale spatial trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation (Welsh and Richardson, 1997). Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and non-sampled locations and kriging variances. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis a data set on heavy metal contamination of the soil in the vicinity of a metal smelter. Marchant, B.P. and Lark, R.M. 2007. Robust estimation of the variogram by residual maximum likelihood. Geoderma 140: 62-72. Richardson, A.M. and Welsh, A.H. 1995. Robust restricted maximum likelihood in mixed linear models. Biometrics 51: 1429-1439. Welsh, A.H. and Richardson, A.M. 1997. Approaches to the robust estimation of mixed models. In: Handbook of Statistics Vol. 15, Elsevier, pp. 343-384.

Investigation for improving Global Positioning System (GPS) orbits using a discrete sequential estimator and stochastic models of selected physical processes

NASA Technical Reports Server (NTRS)

Goad, Clyde C.; Chadwell, C. David

1993-01-01

GEODYNII is a conventional batch least-squares differential corrector computer program with deterministic models of the physical environment. Conventional algorithms were used to process differenced phase and pseudorange data to determine eight-day Global Positioning system (GPS) orbits with several meter accuracy. However, random physical processes drive the errors whose magnitudes prevent improving the GPS orbit accuracy. To improve the orbit accuracy, these random processes should be modeled stochastically. The conventional batch least-squares algorithm cannot accommodate stochastic models, only a stochastic estimation algorithm is suitable, such as a sequential filter/smoother. Also, GEODYNII cannot currently model the correlation among data values. Differenced pseudorange, and especially differenced phase, are precise data types that can be used to improve the GPS orbit precision. To overcome these limitations and improve the accuracy of GPS orbits computed using GEODYNII, we proposed to develop a sequential stochastic filter/smoother processor by using GEODYNII as a type of trajectory preprocessor. Our proposed processor is now completed. It contains a correlated double difference range processing capability, first order Gauss Markov models for the solar radiation pressure scale coefficient and y-bias acceleration, and a random walk model for the tropospheric refraction correction. The development approach was to interface the standard GEODYNII output files (measurement partials and variationals) with software modules containing the stochastic estimator, the stochastic models, and a double differenced phase range processing routine. Thus, no modifications to the original GEODYNII software were required. A schematic of the development is shown. The observational data are edited in the preprocessor and the data are passed to GEODYNII as one of its standard data types. A reference orbit is determined using GEODYNII as a batch least-squares processor and the GEODYNII measurement partial (FTN90) and variational (FTN80, V-matrix) files are generated. These two files along with a control statement file and a satellite identification and mass file are passed to the filter/smoother to estimate time-varying parameter states at each epoch, improved satellite initial elements, and improved estimates of constant parameters.

Probabilistic migration modelling focused on functional barrier efficiency and low migration concepts in support of risk assessment.

PubMed

Brandsch, Rainer

2017-10-01

Migration modelling provides reliable migration estimates from food-contact materials (FCM) to food or food simulants based on mass-transfer parameters like diffusion and partition coefficients related to individual materials. In most cases, mass-transfer parameters are not readily available from the literature and for this reason are estimated with a given uncertainty. Historically, uncertainty was accounted for by introducing upper limit concepts first, turning out to be of limited applicability due to highly overestimated migration results. Probabilistic migration modelling gives the possibility to consider uncertainty of the mass-transfer parameters as well as other model inputs. With respect to a functional barrier, the most important parameters among others are the diffusion properties of the functional barrier and its thickness. A software tool that accepts distribution as inputs and is capable of applying Monte Carlo methods, i.e., random sampling from the input distributions of the relevant parameters (i.e., diffusion coefficient and layer thickness), predicts migration results with related uncertainty and confidence intervals. The capabilities of probabilistic migration modelling are presented in the view of three case studies (1) sensitivity analysis, (2) functional barrier efficiency and (3) validation by experimental testing. Based on the predicted migration by probabilistic migration modelling and related exposure estimates, safety evaluation of new materials in the context of existing or new packaging concepts is possible. Identifying associated migration risk and potential safety concerns in the early stage of packaging development is possible. Furthermore, dedicated material selection exhibiting required functional barrier efficiency under application conditions becomes feasible. Validation of the migration risk assessment by probabilistic migration modelling through a minimum of dedicated experimental testing is strongly recommended.

Utilizing High-Performance Computing to Investigate Parameter Sensitivity of an Inversion Model for Vadose Zone Flow and Transport

NASA Astrophysics Data System (ADS)

Fang, Z.; Ward, A. L.; Fang, Y.; Yabusaki, S.

2011-12-01

High-resolution geologic models have proven effective in improving the accuracy of subsurface flow and transport predictions. However, many of the parameters in subsurface flow and transport models cannot be determined directly at the scale of interest and must be estimated through inverse modeling. A major challenge, particularly in vadose zone flow and transport, is the inversion of the highly-nonlinear, high-dimensional problem as current methods are not readily scalable for large-scale, multi-process models. In this paper we describe the implementation of a fully automated approach for addressing complex parameter optimization and sensitivity issues on massively parallel multi- and many-core systems. The approach is based on the integration of PNNL's extreme scale Subsurface Transport Over Multiple Phases (eSTOMP) simulator, which uses the Global Array toolkit, with the Beowulf-Cluster inspired parallel nonlinear parameter estimation software, BeoPEST in the MPI mode. In the eSTOMP/BeoPEST implementation, a pre-processor generates all of the PEST input files based on the eSTOMP input file. Simulation results for comparison with observations are extracted automatically at each time step eliminating the need for post-process data extractions. The inversion framework was tested with three different experimental data sets: one-dimensional water flow at Hanford Grass Site; irrigation and infiltration experiment at the Andelfingen Site; and a three-dimensional injection experiment at Hanford's Sisson and Lu Site. Good agreements are achieved in all three applications between observations and simulations in both parameter estimates and water dynamics reproduction. Results show that eSTOMP/BeoPEST approach is highly scalable and can be run efficiently with hundreds or thousands of processors. BeoPEST is fault tolerant and new nodes can be dynamically added and removed. A major advantage of this approach is the ability to use high-resolution geologic models to preserve the spatial structure in the inverse model, which leads to better parameter estimates and improved predictions when using the inverse-conditioned realizations of parameter fields.

Microwave-Assisted Preparation of Activated Carbon from Eupatorium Adenophorum: Effects of Preparation Parameters

NASA Astrophysics Data System (ADS)

Cheng, Song; Zhang, Shengzhou; Zhang, Libo; Xia, Hongying; Peng, Jinhui; Wang, Shixing

2017-09-01

Eupatorium adenophorum, global exotic weeds, was utilized as feedstock for preparation of activated carbon (AC) via microwave-induced KOH activation. Influences of the three vital process parameters - microwave power, activation time and impregnation ratio (IR) - have been assessed on the adsorption capacity and yield of AC. The process parameters were optimized utilizing the Design Expert software and were identified to be a microwave power of 700 W, an activation time of 15 min and an IR of 4, with the resultant iodine adsorption number and yield being 2,621 mg/g and 28.25 %, respectively. The key parameters that characterize the AC such as the brunauer emmett teller (BET) surface area, total pore volume and average pore diameter were estimated to be 3,918 m2/g, 2,383 ml/g and 2.43 nm, respectively, under the optimized process conditions. The surface characteristics of AC were characterized by Fourier transform infrared spectroscopy, scanning electron microscope and Transmission electron microscope.

PROC IRT: A SAS Procedure for Item Response Theory

PubMed Central

Matlock Cole, Ki; Paek, Insu

2017-01-01

This article reviews the procedure for item response theory (PROC IRT) procedure in SAS/STAT 14.1 to conduct item response theory (IRT) analyses of dichotomous and polytomous datasets that are unidimensional or multidimensional. The review provides an overview of available features, including models, estimation procedures, interfacing, input, and output files. A small-scale simulation study evaluates the IRT model parameter recovery of the PROC IRT procedure. The use of the IRT procedure in Statistical Analysis Software (SAS) may be useful for researchers who frequently utilize SAS for analyses, research, and teaching.

Crustal deformations in the Central Mediterranean derived from the WHAT A CAT GPS project.

NASA Astrophysics Data System (ADS)

Kaniuth, K.; Drewes, H.; Stuber, K.; Tremel, H.; Kahler, H.-G.; Peter, Y.; Zerbini, S.; Tonti, G.; Veis, G.; Fagard, H.

1999-03-01

The West Hellenic Arc Tectonics and Calabrian Arc Tectonics (WHAT A CAT) project aimes at monitoring crustal deformations in the Central Mediterranean by repeated GPS campaigns. The data set acquired so far is rather heterogeneous in terms of availability of GPS satellites, performance of the involved receiver systems and quality of the satellites' orbits. The paper presents the velocity estimates achieved using a modified version of the Bernese GPS software. Main characteristic of the solution strategy is the definition of station velocity parameters already on theobservation equation level.

Segmentation and intensity estimation of microarray images using a gamma-t mixture model.

PubMed

Baek, Jangsun; Son, Young Sook; McLachlan, Geoffrey J

2007-02-15

We present a new approach to the analysis of images for complementary DNA microarray experiments. The image segmentation and intensity estimation are performed simultaneously by adopting a two-component mixture model. One component of this mixture corresponds to the distribution of the background intensity, while the other corresponds to the distribution of the foreground intensity. The intensity measurement is a bivariate vector consisting of red and green intensities. The background intensity component is modeled by the bivariate gamma distribution, whose marginal densities for the red and green intensities are independent three-parameter gamma distributions with different parameters. The foreground intensity component is taken to be the bivariate t distribution, with the constraint that the mean of the foreground is greater than that of the background for each of the two colors. The degrees of freedom of this t distribution are inferred from the data but they could be specified in advance to reduce the computation time. Also, the covariance matrix is not restricted to being diagonal and so it allows for nonzero correlation between R and G foreground intensities. This gamma-t mixture model is fitted by maximum likelihood via the EM algorithm. A final step is executed whereby nonparametric (kernel) smoothing is undertaken of the posterior probabilities of component membership. The main advantages of this approach are: (1) it enjoys the well-known strengths of a mixture model, namely flexibility and adaptability to the data; (2) it considers the segmentation and intensity simultaneously and not separately as in commonly used existing software, and it also works with the red and green intensities in a bivariate framework as opposed to their separate estimation via univariate methods; (3) the use of the three-parameter gamma distribution for the background red and green intensities provides a much better fit than the normal (log normal) or t distributions; (4) the use of the bivariate t distribution for the foreground intensity provides a model that is less sensitive to extreme observations; (5) as a consequence of the aforementioned properties, it allows segmentation to be undertaken for a wide range of spot shapes, including doughnut, sickle shape and artifacts. We apply our method for gridding, segmentation and estimation to cDNA microarray real images and artificial data. Our method provides better segmentation results in spot shapes as well as intensity estimation than Spot and spotSegmentation R language softwares. It detected blank spots as well as bright artifact for the real data, and estimated spot intensities with high-accuracy for the synthetic data. The algorithms were implemented in Matlab. The Matlab codes implementing both the gridding and segmentation/estimation are available upon request. Supplementary material is available at Bioinformatics online.

Rapid impact testing for quantitative assessment of large populations of bridges

NASA Astrophysics Data System (ADS)

Zhou, Yun; Prader, John; DeVitis, John; Deal, Adrienne; Zhang, Jian; Moon, Franklin; Aktan, A. Emin

2011-04-01

Although the widely acknowledged shortcomings of visual inspection have fueled significant advances in the areas of non-destructive evaluation and structural health monitoring (SHM) over the last several decades, the actual practice of bridge assessment has remained largely unchanged. The authors believe the lack of adoption, especially of SHM technologies, is related to the 'single structure' scenarios that drive most research. To overcome this, the authors have developed a concept for a rapid single-input, multiple-output (SIMO) impact testing device that will be capable of capturing modal parameters and estimating flexibility/deflection basins of common highway bridges during routine inspections. The device is composed of a trailer-mounted impact source (capable of delivering a 50 kip impact) and retractable sensor arms, and will be controlled by an automated data acquisition, processing and modal parameter estimation software. The research presented in this paper covers (a) the theoretical basis for SISO, SIMO and MIMO impact testing to estimate flexibility, (b) proof of concept numerical studies using a finite element model, and (c) a pilot implementation on an operating highway bridge. Results indicate that the proposed approach can estimate modal flexibility within a few percent of static flexibility; however, the estimated modal flexibility matrix is only reliable for the substructures associated with the various SIMO tests. To overcome this shortcoming, a modal 'stitching' approach for substructure integration to estimate the full Eigen vector matrix is developed, and preliminary results of these methods are also presented.

Approaches in highly parameterized inversion-PESTCommander, a graphical user interface for file and run management across networks

USGS Publications Warehouse

Karanovic, Marinko; Muffels, Christopher T.; Tonkin, Matthew J.; Hunt, Randall J.

2012-01-01

Models of environmental systems have become increasingly complex, incorporating increasingly large numbers of parameters in an effort to represent physical processes on a scale approaching that at which they occur in nature. Consequently, the inverse problem of parameter estimation (specifically, model calibration) and subsequent uncertainty analysis have become increasingly computation-intensive endeavors. Fortunately, advances in computing have made computational power equivalent to that of dozens to hundreds of desktop computers accessible through a variety of alternate means: modelers have various possibilities, ranging from traditional Local Area Networks (LANs) to cloud computing. Commonly used parameter estimation software is well suited to take advantage of the availability of such increased computing power. Unfortunately, logistical issues become increasingly important as an increasing number and variety of computers are brought to bear on the inverse problem. To facilitate efficient access to disparate computer resources, the PESTCommander program documented herein has been developed to provide a Graphical User Interface (GUI) that facilitates the management of model files ("file management") and remote launching and termination of "slave" computers across a distributed network of computers ("run management"). In version 1.0 described here, PESTCommander can access and ascertain resources across traditional Windows LANs: however, the architecture of PESTCommander has been developed with the intent that future releases will be able to access computing resources (1) via trusted domains established in Wide Area Networks (WANs) in multiple remote locations and (2) via heterogeneous networks of Windows- and Unix-based operating systems. The design of PESTCommander also makes it suitable for extension to other computational resources, such as those that are available via cloud computing. Version 1.0 of PESTCommander was developed primarily to work with the parameter estimation software PEST; the discussion presented in this report focuses on the use of the PESTCommander together with Parallel PEST. However, PESTCommander can be used with a wide variety of programs and models that require management, distribution, and cleanup of files before or after model execution. In addition to its use with the Parallel PEST program suite, discussion is also included in this report regarding the use of PESTCommander with the Global Run Manager GENIE, which was developed simultaneously with PESTCommander.

Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes

NASA Astrophysics Data System (ADS)

Guerrero, José-Luis; Pernica, Patricia; Wheater, Howard; Mackay, Murray; Spence, Chris

2017-12-01

Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere - heat-exchange fluxes - is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue - different parameter-value combinations yielding equivalent results - the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.

Application of Real Options Theory to Software Engineering for Strategic Decision Making in Software Related Capital Investments

DTIC Science & Technology

2008-12-01

between our current project and the historical projects. Therefore to refine the historical volatility estimate of the previously completed software... historical volatility estimates obtained in the form of beliefs and plausibility based on subjective probabilities that take into consideration unique

Estimation of toxicity using a Java based software tool

EPA Science Inventory

A software tool has been developed that will allow a user to estimate the toxicity for a variety of endpoints (such as acute aquatic toxicity). The software tool is coded in Java and can be accessed using a web browser (or alternatively downloaded and ran as a stand alone applic...

EuroForMix: An open source software based on a continuous model to evaluate STR DNA profiles from a mixture of contributors with artefacts.

PubMed

Bleka, Øyvind; Storvik, Geir; Gill, Peter

2016-03-01

We have released a software named EuroForMix to analyze STR DNA profiles in a user-friendly graphical user interface. The software implements a model to explain the allelic peak height on a continuous scale in order to carry out weight-of-evidence calculations for profiles which could be from a mixture of contributors. Through a properly parameterized model we are able to do inference on mixture proportions, the peak height properties, stutter proportion and degradation. In addition, EuroForMix includes models for allele drop-out, allele drop-in and sub-population structure. EuroForMix supports two inference approaches for likelihood ratio calculations. The first approach uses maximum likelihood estimation of the unknown parameters. The second approach is Bayesian based which requires prior distributions to be specified for the parameters involved. The user may specify any number of known and unknown contributors in the model, however we find that there is a practical computing time limit which restricts the model to a maximum of four unknown contributors. EuroForMix is the first freely open source, continuous model (accommodating peak height, stutter, drop-in, drop-out, population substructure and degradation), to be reported in the literature. It therefore serves an important purpose to act as an unrestricted platform to compare different solutions that are available. The implementation of the continuous model used in the software showed close to identical results to the R-package DNAmixtures, which requires a HUGIN Expert license to be used. An additional feature in EuroForMix is the ability for the user to adapt the Bayesian inference framework by incorporating their own prior information. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Software analysis handbook: Software complexity analysis and software reliability estimation and prediction

NASA Technical Reports Server (NTRS)

Lee, Alice T.; Gunn, Todd; Pham, Tuan; Ricaldi, Ron

1994-01-01

This handbook documents the three software analysis processes the Space Station Software Analysis team uses to assess space station software, including their backgrounds, theories, tools, and analysis procedures. Potential applications of these analysis results are also presented. The first section describes how software complexity analysis provides quantitative information on code, such as code structure and risk areas, throughout the software life cycle. Software complexity analysis allows an analyst to understand the software structure, identify critical software components, assess risk areas within a software system, identify testing deficiencies, and recommend program improvements. Performing this type of analysis during the early design phases of software development can positively affect the process, and may prevent later, much larger, difficulties. The second section describes how software reliability estimation and prediction analysis, or software reliability, provides a quantitative means to measure the probability of failure-free operation of a computer program, and describes the two tools used by JSC to determine failure rates and design tradeoffs between reliability, costs, performance, and schedule.

Software For Computing Reliability Of Other Software

NASA Technical Reports Server (NTRS)

Nikora, Allen; Antczak, Thomas M.; Lyu, Michael

1995-01-01

Computer Aided Software Reliability Estimation (CASRE) computer program developed for use in measuring reliability of other software. Easier for non-specialists in reliability to use than many other currently available programs developed for same purpose. CASRE incorporates mathematical modeling capabilities of public-domain Statistical Modeling and Estimation of Reliability Functions for Software (SMERFS) computer program and runs in Windows software environment. Provides menu-driven command interface; enabling and disabling of menu options guides user through (1) selection of set of failure data, (2) execution of mathematical model, and (3) analysis of results from model. Written in C language.

Experimental (FT-IR, NMR and UV) and theoretical (M06-2X and DFT) investigation, and frequency estimation analyses on (E)-3-(4-bromo-5-methylthiophen-2-yl)acrylonitrile.

PubMed

Sert, Yusuf; Balakit, Asim A; Öztürk, Nuri; Ucun, Fatih; El-Hiti, Gamal A

2014-10-15

The spectroscopic properties of (E)-3-(4-bromo-5-methylthiophen-2-yl)acrylonitrile have been investigated by FT-IR, UV, (1)H and (13)C NMR techniques. The theoretical vibrational frequencies and optimized geometric parameters (bond lengths and angles) have been calculated using density functional theory (DFT/B3LYP: Becke, 3-parameter, Lee-Yang-Parr) and DFT/M06-2X (the highly parameterized, empirical exchange correlation function) quantum chemical methods with 6-311++G(d,p) basis set by Gaussian 03 software, for the first time. The assignments of the vibrational frequencies have been carried out by potential energy distribution (PED) analysis by using VEDA 4 software. The theoretical optimized geometric parameters and vibrational frequencies were in good agreement with the corresponding experimental data, and with the results in the literature. (1)H and (13)C NMR chemical shifts were calculated by using the gauge-invariant atomic orbital (GIAO) method. The electronic properties, such as excitation energies, oscillator strength wavelengths were performed by B3LYP methods. In addition, the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) energies and the other related molecular energy values have been calculated and depicted. Copyright © 2014 Elsevier B.V. All rights reserved.

A fast and robust method for moment tensor and depth determination of shallow seismic events in CTBT related studies.

NASA Astrophysics Data System (ADS)

Baker, Ben; Stachnik, Joshua; Rozhkov, Mikhail

2017-04-01

International Data Center is required to conduct expert technical analysis and special studies to improve event parameters and assist State Parties in identifying the source of specific event according to the protocol to the Protocol to the Comprehensive Nuclear Test Ban Treaty. Determination of seismic event source mechanism and its depth is closely related to these tasks. It is typically done through a strategic linearized inversion of the waveforms for a complete or subset of source parameters, or similarly defined grid search through precomputed Greens Functions created for particular source models. In this presentation we demonstrate preliminary results obtained with the latter approach from an improved software design. In this development we tried to be compliant with different modes of CTBT monitoring regime and cover wide range of source-receiver distances (regional to teleseismic), resolve shallow source depths, provide full moment tensor solution based on body and surface waves recordings, be fast to satisfy both on-demand studies and automatic processing and properly incorporate observed waveforms and any uncertainties a priori as well as accurately estimate posteriori uncertainties. Posterior distributions of moment tensor parameters show narrow peaks where a significant number of reliable surface wave observations are available. For earthquake examples, fault orientation (strike, dip, and rake) posterior distributions also provide results consistent with published catalogues. Inclusion of observations on horizontal components will provide further constraints. In addition, the calculation of teleseismic P wave Green's Functions are improved through prior analysis to determine an appropriate attenuation parameter for each source-receiver path. Implemented HDF5 based Green's Functions pre-packaging allows much greater flexibility in utilizing different software packages and methods for computation. Further additions will have the rapid use of Instaseis/AXISEM full waveform synthetics added to a pre-computed GF archive. Along with traditional post processing analysis of waveform misfits through several objective functions and variance reduction, we follow a probabilistic approach to assess the robustness of moment tensor solution. In a course of this project full moment tensor and depth estimates are determined for DPRK events and shallow earthquakes using a new implementation of teleseismic P waves waveform fitting. A full grid search over the entire moment tensor space is used to appropriately sample all possible solutions. A recent method by Tape & Tape (2012) to discretize the complete moment tensor space from a geometric perspective is used. Probabilistic uncertainty estimates on the moment tensor parameters provide robustness to solution.

Periodic orbits of hybrid systems and parameter estimation via AD.

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

Guckenheimer, John.; Phipps, Eric Todd; Casey, Richard

Rhythmic, periodic processes are ubiquitous in biological systems; for example, the heart beat, walking, circadian rhythms and the menstrual cycle. Modeling these processes with high fidelity as periodic orbits of dynamical systems is challenging because: (1) (most) nonlinear differential equations can only be solved numerically; (2) accurate computation requires solving boundary value problems; (3) many problems and solutions are only piecewise smooth; (4) many problems require solving differential-algebraic equations; (5) sensitivity information for parameter dependence of solutions requires solving variational equations; and (6) truncation errors in numerical integration degrade performance of optimization methods for parameter estimation. In addition, mathematical modelsmore » of biological processes frequently contain many poorly-known parameters, and the problems associated with this impedes the construction of detailed, high-fidelity models. Modelers are often faced with the difficult problem of using simulations of a nonlinear model, with complex dynamics and many parameters, to match experimental data. Improved computational tools for exploring parameter space and fitting models to data are clearly needed. This paper describes techniques for computing periodic orbits in systems of hybrid differential-algebraic equations and parameter estimation methods for fitting these orbits to data. These techniques make extensive use of automatic differentiation to accurately and efficiently evaluate derivatives for time integration, parameter sensitivities, root finding and optimization. The boundary value problem representing a periodic orbit in a hybrid system of differential algebraic equations is discretized via multiple-shooting using a high-degree Taylor series integration method [GM00, Phi03]. Numerical solutions to the shooting equations are then estimated by a Newton process yielding an approximate periodic orbit. A metric is defined for computing the distance between two given periodic orbits which is then minimized using a trust-region minimization algorithm [DS83] to find optimal fits of the model to a reference orbit [Cas04]. There are two different yet related goals that motivate the algorithmic choices listed above. The first is to provide a simple yet powerful framework for studying periodic motions in mechanical systems. Formulating mechanically correct equations of motion for systems of interconnected rigid bodies, while straightforward, is a time-consuming error prone process. Much of this difficulty stems from computing the acceleration of each rigid body in an inertial reference frame. The acceleration is computed most easily in a redundant set of coordinates giving the spatial positions of each body: since the acceleration is just the second derivative of these positions. Rather than providing explicit formulas for these derivatives, automatic differentiation can be employed to compute these quantities efficiently during the course of a simulation. The feasibility of these ideas was investigated by applying these techniques to the problem of locating stable walking motions for a disc-foot passive walking machine [CGMR01, Gar99, McG91]. The second goal for this work was to investigate the application of smooth optimization methods to periodic orbit parameter estimation problems in neural oscillations. Others [BB93, FUS93, VB99] have favored non-continuous optimization methods such as genetic algorithms, stochastic search methods, simulated annealing and brute-force random searches because of their perceived suitability to the landscape of typical objective functions in parameter space, particularly for multi-compartmental neural models. Here we argue that a carefully formulated optimization problem is amenable to Newton-like methods and has a sufficiently smooth landscape in parameter space that these methods can be an efficient and effective alternative. The plan of this paper is as follows. In Section 1 we provide a definition of hybrid systems that is the basis for modeling systems with discontinuities or discrete transitions. Sections 2, 3, and 4 briefly describe the Taylor series integration, periodic orbit tracking, and parameter estimation algorithms. For full treatments of these algorithms, we refer the reader to [Phi03, Cas04, CPG04]. The software implementation of these algorithms is briefly described in Section 5 with particular emphasis on the automatic differentiation software ADMC++. Finally, these algorithms are applied to the bipedal walking and Hodgkin-Huxley based neural oscillation problems discussed above in Section 6.« less

SEDA: A software package for the Statistical Earthquake Data Analysis

NASA Astrophysics Data System (ADS)

Lombardi, A. M.

2017-03-01

In this paper, the first version of the software SEDA (SEDAv1.0), designed to help seismologists statistically analyze earthquake data, is presented. The package consists of a user-friendly Matlab-based interface, which allows the user to easily interact with the application, and a computational core of Fortran codes, to guarantee the maximum speed. The primary factor driving the development of SEDA is to guarantee the research reproducibility, which is a growing movement among scientists and highly recommended by the most important scientific journals. SEDAv1.0 is mainly devoted to produce accurate and fast outputs. Less care has been taken for the graphic appeal, which will be improved in the future. The main part of SEDAv1.0 is devoted to the ETAS modeling. SEDAv1.0 contains a set of consistent tools on ETAS, allowing the estimation of parameters, the testing of model on data, the simulation of catalogs, the identification of sequences and forecasts calculation. The peculiarities of routines inside SEDAv1.0 are discussed in this paper. More specific details on the software are presented in the manual accompanying the program package.

SEDA: A software package for the Statistical Earthquake Data Analysis

PubMed Central

Lombardi, A. M.

2017-01-01

In this paper, the first version of the software SEDA (SEDAv1.0), designed to help seismologists statistically analyze earthquake data, is presented. The package consists of a user-friendly Matlab-based interface, which allows the user to easily interact with the application, and a computational core of Fortran codes, to guarantee the maximum speed. The primary factor driving the development of SEDA is to guarantee the research reproducibility, which is a growing movement among scientists and highly recommended by the most important scientific journals. SEDAv1.0 is mainly devoted to produce accurate and fast outputs. Less care has been taken for the graphic appeal, which will be improved in the future. The main part of SEDAv1.0 is devoted to the ETAS modeling. SEDAv1.0 contains a set of consistent tools on ETAS, allowing the estimation of parameters, the testing of model on data, the simulation of catalogs, the identification of sequences and forecasts calculation. The peculiarities of routines inside SEDAv1.0 are discussed in this paper. More specific details on the software are presented in the manual accompanying the program package. PMID:28290482

Remote Sensing and Capacity Building to Improve Food Security

NASA Astrophysics Data System (ADS)

Husak, G. J.; Funk, C. C.; Verdin, J. P.; Rowland, J.; Budde, M. E.

2012-12-01

The Famine Early Warning Systems Network (FEWS NET) is a U.S. Agency for International Development (USAID) supported project designed to monitor and anticipate food insecurity in the developing world, primarily Africa, Central America, the Caribbean and Central Asia. This is done through a network of partners involving U.S. government agencies, universities, country representatives, and partner institutions. This presentation will focus on the remotely sensed data used in FEWS NET activities and capacity building efforts designed to expand and enhance the use of FEWS NET tools and techniques. Remotely sensed data are of particular value in the developing world, where ground data networks and data reporting are limited. FEWS NET uses satellite based rainfall and vegetation greenness measures to monitor and assess food production conditions. Satellite rainfall estimates also drive crop models which are used in determining yield potential. Recent FEWS NET products also include estimates of actual evapotranspiration. Efforts are currently underway to assimilate these products into a single tool which would indicate areas experiencing abnormal conditions with implications for food production. FEWS NET is also involved in a number of capacity building activities. Two primary examples are the development of software and training of institutional partners in basic GIS and remote sensing. Software designed to incorporate rainfall station data with existing satellite-derived rainfall estimates gives users the ability to enhance satellite rainfall estimates or long-term means, resulting in gridded fields of rainfall that better reflect ground conditions. Further, this software includes a crop water balance model driven by the improved rainfall estimates. Finally, crop parameters, such as the planting date or length of growing period, can be adjusted by users to tailor the crop model to actual conditions. Training workshops in the use of this software, as well as basic GIS and remote sensing tools, are routinely conducted by FEWS NET representatives at host country meteorological and agricultural services. These institutions are then able to produce information that can more accurately inform food security decision making. Informed decision making reduces the risk associated with a given hazard. In the case of FEWS NET, this involves identification of shocks to food availability, allowing for the pre-positioning of aid to be available when a hazard strikes. Developing tools to incorporate better information in food production estimates and working closely with local staff trained in state-of-the-practice techniques results in a more informed decision making process, reducing the impacts of food security hazards.

Experimental Design for Stochastic Models of Nonlinear Signaling Pathways Using an Interval-Wise Linear Noise Approximation and State Estimation.

PubMed

Zimmer, Christoph

2016-01-01

Computational modeling is a key technique for analyzing models in systems biology. There are well established methods for the estimation of the kinetic parameters in models of ordinary differential equations (ODE). Experimental design techniques aim at devising experiments that maximize the information encoded in the data. For ODE models there are well established approaches for experimental design and even software tools. However, data from single cell experiments on signaling pathways in systems biology often shows intrinsic stochastic effects prompting the development of specialized methods. While simulation methods have been developed for decades and parameter estimation has been targeted for the last years, only very few articles focus on experimental design for stochastic models. The Fisher information matrix is the central measure for experimental design as it evaluates the information an experiment provides for parameter estimation. This article suggest an approach to calculate a Fisher information matrix for models containing intrinsic stochasticity and high nonlinearity. The approach makes use of a recently suggested multiple shooting for stochastic systems (MSS) objective function. The Fisher information matrix is calculated by evaluating pseudo data with the MSS technique. The performance of the approach is evaluated with simulation studies on an Immigration-Death, a Lotka-Volterra, and a Calcium oscillation model. The Calcium oscillation model is a particularly appropriate case study as it contains the challenges inherent to signaling pathways: high nonlinearity, intrinsic stochasticity, a qualitatively different behavior from an ODE solution, and partial observability. The computational speed of the MSS approach for the Fisher information matrix allows for an application in realistic size models.

Emission rate modeling and risk assessment at an automobile plant from painting operations

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

Kumar, A.; Shrivastava, A.; Kulkarni, A.

Pollution from automobile plants from painting operations has been addressed in the Clean Act Amendments (1990). The estimation of pollutant emissions from automobile painting operation were done mostly by approximate procedures than by actual calculations. The purpose of this study was to develop a methodology for calculating the emissions of the pollutants from painting operation in an automobile plant. Five scenarios involving an automobile painting operation, located in Columbus (Ohio), were studied for pollutant emission and concomitant risk associated with that. In the study of risk, a sensitivity analysis was done using Crystal Ball{reg{underscore}sign} on the parameters involved in risk.more » This software uses the Monte Carlo principle. The most sensitive factor in the risk analysis was the ground level concentration of the pollutants. All scenarios studied met the safety goal (a risk value of 1 x 10{sup {minus}6}) with different confidence levels. The highest level of confidence in meeting the safety goal was displayed by Scenario 1 (Alpha Industries). The results from the scenarios suggest that risk is associated with the quantity of released toxic pollutants. The sensitivity analysis of the various parameter shows that average spray rate of paint is the most important parameter in the estimation of pollutants from the painting operations. The entire study is a complete module that can be used by the environmental pollution control agencies for estimation of pollution levels and estimation of associated risk. The study can be further extended to other operations in an automobile industry or to different industries.« less

Generating standardized image data for testing and calibrating quantification of volumes, surfaces, lengths, and object counts in fibrous and porous materials using X-ray microtomography.

PubMed

Jiřík, Miroslav; Bartoš, Martin; Tomášek, Petr; Malečková, Anna; Kural, Tomáš; Horáková, Jana; Lukáš, David; Suchý, Tomáš; Kochová, Petra; Hubálek Kalbáčová, Marie; Králíčková, Milena; Tonar, Zbyněk

2018-06-01

Quantification of the structure and composition of biomaterials using micro-CT requires image segmentation due to the low contrast and overlapping radioopacity of biological materials. The amount of bias introduced by segmentation procedures is generally unknown. We aim to develop software that generates three-dimensional models of fibrous and porous structures with known volumes, surfaces, lengths, and object counts in fibrous materials and to provide a software tool that calibrates quantitative micro-CT assessments. Virtual image stacks were generated using the newly developed software TeIGen, enabling the simulation of micro-CT scans of unconnected tubes, connected tubes, and porosities. A realistic noise generator was incorporated. Forty image stacks were evaluated using micro-CT, and the error between the true known and estimated data was quantified. Starting with geometric primitives, the error of the numerical estimation of surfaces and volumes was eliminated, thereby enabling the quantification of volumes and surfaces of colliding objects. Analysis of the sensitivity of the thresholding upon parameters of generated testing image sets revealed the effects of decreasing resolution and increasing noise on the accuracy of the micro-CT quantification. The size of the error increased with decreasing resolution when the voxel size exceeded 1/10 of the typical object size, which simulated the effect of the smallest details that could still be reliably quantified. Open-source software for calibrating quantitative micro-CT assessments by producing and saving virtually generated image data sets with known morphometric data was made freely available to researchers involved in morphometry of three-dimensional fibrillar and porous structures in micro-CT scans. © 2018 Wiley Periodicals, Inc.

Determination of Eros Physical Parameters for Near Earth Asteroid Rendezvous Orbit Phase Navigation

NASA Technical Reports Server (NTRS)

Miller, J. K.; Antreasian, P. J.; Georgini, J.; Owen, W. M.; Williams, B. G.; Yeomans, D. K.

1995-01-01

Navigation of the orbit phase of the Near Earth steroid Rendezvous (NEAR) mission will re,quire determination of certain physical parameters describing the size, shape, gravity field, attitude and inertial properties of Eros. Prior to launch, little was known about Eros except for its orbit which could be determined with high precision from ground based telescope observations. Radar bounce and light curve data provided a rough estimate of Eros shape and a fairly good estimate of the pole, prime meridian and spin rate. However, the determination of the NEAR spacecraft orbit requires a high precision model of Eros's physical parameters and the ground based data provides only marginal a priori information. Eros is the principal source of perturbations of the spacecraft's trajectory and the principal source of data for determining the orbit. The initial orbit determination strategy is therefore concerned with developing a precise model of Eros. The original plan for Eros orbital operations was to execute a series of rendezvous burns beginning on December 20,1998 and insert into a close Eros orbit in January 1999. As a result of an unplanned termination of the rendezvous burn on December 20, 1998, the NEAR spacecraft continued on its high velocity approach trajectory and passed within 3900 km of Eros on December 23, 1998. The planned rendezvous burn was delayed until January 3, 1999 which resulted in the spacecraft being placed on a trajectory that slowly returns to Eros with a subsequent delay of close Eros orbital operations until February 2001. The flyby of Eros provided a brief glimpse and allowed for a crude estimate of the pole, prime meridian and mass of Eros. More importantly for navigation, orbit determination software was executed in the landmark tracking mode to determine the spacecraft orbit and a preliminary shape and landmark data base has been obtained. The flyby also provided an opportunity to test orbit determination operational procedures that will be used in February of 2001. The initial attitude and spin rate of Eros, as well as estimates of reference landmark locations, are obtained from images of the asteroid. These initial estimates are used as a priori values for a more precise refinement of these parameters by the orbit determination software which combines optical measurements with Doppler tracking data to obtain solutions for the required parameters. As the spacecraft is maneuvered; closer to the asteroid, estimates of spacecraft state, asteroid attitude, solar pressure, landmark locations and Eros physical parameters including mass, moments of inertia and gravity harmonics are determined with increasing precision. The determination of the elements of the inertia tensor of the asteroid is critical to spacecraft orbit determination and prediction of the asteroid attitude. The moments of inertia about the principal axes are also of scientific interest since they provide some insight into the internal mass distribution. Determination of the principal axes moments of inertia will depend on observing free precession in the asteroid's attitude dynamics. Gravity harmonics are in themselves of interest to science. When compared with the asteroid shape, some insight may be obtained into Eros' internal structure. The location of the center of mass derived from the first degree harmonic coefficients give a direct indication of overall mass distribution. The second degree harmonic coefficients relate to the radial distribution of mass. Higher degree harmonics may be compared with surface features to gain additional insight into mass distribution. In this paper, estimates of Eros physical parameters obtained from the December 23,1998 flyby will be presented. This new knowledge will be applied to simplification of Eros orbital operations in February of 2001. The resulting revision to the orbit determination strategy will also be discussed.

GuiTope: an application for mapping random-sequence peptides to protein sequences.

PubMed

Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert

2012-01-03

Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

An Exploratory Study of Software Cost Estimating at the Electronic Systems Division.

DTIC Science & Technology

1976-07-01

action’. to improve the software cost Sestimating proces., While thin research was limited to the M.nD onvironment, the same types of problema may exist...Methods in Social Science. Now York: Random House, 1969. 57. Smith, Ronald L. Structured Programming Series (Vol. XI) - Estimating Software Project

Cost benefits of advanced software: A review of methodology used at Kennedy Space Center

NASA Technical Reports Server (NTRS)

Joglekar, Prafulla N.

1993-01-01

To assist rational investments in advanced software, a formal, explicit, and multi-perspective cost-benefit analysis methodology is proposed. The methodology can be implemented through a six-stage process which is described and explained. The current practice of cost-benefit analysis at KSC is reviewed in the light of this methodology. The review finds that there is a vicious circle operating. Unsound methods lead to unreliable cost-benefit estimates. Unreliable estimates convince management that cost-benefit studies should not be taken seriously. Then, given external demands for cost-benefit estimates, management encourages software enginees to somehow come up with the numbers for their projects. Lacking the expertise needed to do a proper study, courageous software engineers with vested interests use ad hoc and unsound methods to generate some estimates. In turn, these estimates are unreliable, and the cycle continues. The proposed methodology should help KSC to break out of this cycle.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Kumar, Sujay V.; Santanello, Joseph A., Jr.; Reichle, Rolf H.

2009-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

Software Metrics

DTIC Science & Technology

1988-12-01

software development scene is often charac- c. SPQR Model-Jones terized by: * schedule and cost estimates that are gross-d. COPMO-Thebaut ly inaccurate, SEI...time c. SPQR Model-Jones (in seconds) is simply derived from E by dividing T. Capers Jones has developed a software cost by the Stroud number, S...estimation model called the Software Produc- T=E/S tivity, Quality, and Reliability ( SPQR ) model. The basic approach is similar to that of Boehm’s The value

Sign: large-scale gene network estimation environment for high performance computing.

PubMed

Tamada, Yoshinori; Shimamura, Teppei; Yamaguchi, Rui; Imoto, Seiya; Nagasaki, Masao; Miyano, Satoru

2011-01-01

Our research group is currently developing software for estimating large-scale gene networks from gene expression data. The software, called SiGN, is specifically designed for the Japanese flagship supercomputer "K computer" which is planned to achieve 10 petaflops in 2012, and other high performance computing environments including Human Genome Center (HGC) supercomputer system. SiGN is a collection of gene network estimation software with three different sub-programs: SiGN-BN, SiGN-SSM and SiGN-L1. In these three programs, five different models are available: static and dynamic nonparametric Bayesian networks, state space models, graphical Gaussian models, and vector autoregressive models. All these models require a huge amount of computational resources for estimating large-scale gene networks and therefore are designed to be able to exploit the speed of 10 petaflops. The software will be available freely for "K computer" and HGC supercomputer system users. The estimated networks can be viewed and analyzed by Cell Illustrator Online and SBiP (Systems Biology integrative Pipeline). The software project web site is available at http://sign.hgc.jp/ .

The 2005 Workbook: an improved tool for estimating HIV prevalence in countries with low level and concentrated epidemics.

PubMed

Lyerla, R; Gouws, E; García-Calleja, J M; Zaniewski, E

2006-06-01

This paper describes improvements and updates to an established approach to making epidemiological estimates of HIV prevalence in countries with low level and concentrated epidemics. The structure of the software used to make estimates is briefly described, with particular attention to changes and improvements. The approach focuses on identifying populations which, through their behaviour, are at high risk of infection with HIV or who are exposed through the risk behaviour of their sexual partners. Estimates of size and HIV prevalence of these populations allow the total number of HIV infected people in a country or region to be estimated. Major changes in the software focus on the move away from short term projections and towards developing an epidemiological curve that more accurately represents the change in prevalence of HIV over time. The software continues to provide an output file for use in the Spectrum software so as to estimate the demographic impact of HIV infection at country level.

Processing EOS MLS Level-2 Data

NASA Technical Reports Server (NTRS)

Snyder, W. Van; Wu, Dong; Read, William; Jiang, Jonathan; Wagner, Paul; Livesey, Nathaniel; Schwartz, Michael; Filipiak, Mark; Pumphrey, Hugh; Shippony, Zvi

2006-01-01

A computer program performs level-2 processing of thermal-microwave-radiance data from observations of the limb of the Earth by the Earth Observing System (EOS) Microwave Limb Sounder (MLS). The purpose of the processing is to estimate the composition and temperature of the atmosphere versus altitude from .8 to .90 km. "Level-2" as used here is a specialists f term signifying both vertical profiles of geophysical parameters along the measurement track of the instrument and processing performed by this or other software to generate such profiles. Designed to be flexible, the program is controlled via a configuration file that defines all aspects of processing, including contents of state and measurement vectors, configurations of forward models, measurement and calibration data to be read, and the manner of inverting the models to obtain the desired estimates. The program can operate in a parallel form in which one instance of the program acts a master, coordinating the work of multiple slave instances on a cluster of computers, each slave operating on a portion of the data. Optionally, the configuration file can be made to instruct the software to produce files of simulated radiances based on state vectors formed from sets of geophysical data-product files taken as input.

State, Parameter, and Unknown Input Estimation Problems in Active Automotive Safety Applications

NASA Astrophysics Data System (ADS)

Phanomchoeng, Gridsada

A variety of driver assistance systems such as traction control, electronic stability control (ESC), rollover prevention and lane departure avoidance systems are being developed by automotive manufacturers to reduce driver burden, partially automate normal driving operations, and reduce accidents. The effectiveness of these driver assistance systems can be significant enhanced if the real-time values of several vehicle parameters and state variables, namely tire-road friction coefficient, slip angle, roll angle, and rollover index, can be known. Since there are no inexpensive sensors available to measure these variables, it is necessary to estimate them. However, due to the significant nonlinear dynamics in a vehicle, due to unknown and changing plant parameters, and due to the presence of unknown input disturbances, the design of estimation algorithms for this application is challenging. This dissertation develops a new approach to observer design for nonlinear systems in which the nonlinearity has a globally (or locally) bounded Jacobian. The developed approach utilizes a modified version of the mean value theorem to express the nonlinearity in the estimation error dynamics as a convex combination of known matrices with time varying coefficients. The observer gains are then obtained by solving linear matrix inequalities (LMIs). A number of illustrative examples are presented to show that the developed approach is less conservative and more useful than the standard Lipschitz assumption based nonlinear observer. The developed nonlinear observer is utilized for estimation of slip angle, longitudinal vehicle velocity, and vehicle roll angle. In order to predict and prevent vehicle rollovers in tripped situations, it is necessary to estimate the vertical tire forces in the presence of unknown road disturbance inputs. An approach to estimate unknown disturbance inputs in nonlinear systems using dynamic model inversion and a modified version of the mean value theorem is presented. The developed theory is used to estimate vertical tire forces and predict tripped rollovers in situations involving road bumps, potholes, and lateral unknown force inputs. To estimate the tire-road friction coefficients at each individual tire of the vehicle, algorithms to estimate longitudinal forces and slip ratios at each tire are proposed. Subsequently, tire-road friction coefficients are obtained using recursive least squares parameter estimators that exploit the relationship between longitudinal force and slip ratio at each tire. The developed approaches are evaluated through simulations with industry standard software, CARSIM, with experimental tests on a Volvo XC90 sport utility vehicle and with experimental tests on a 1/8th scaled vehicle. The simulation and experimental results show that the developed approaches can reliably estimate the vehicle parameters and state variables needed for effective ESC and rollover prevention applications.

Comparing Consider-Covariance Analysis with Sigma-Point Consider Filter and Linear-Theory Consider Filter Formulations

NASA Technical Reports Server (NTRS)

Lisano, Michael E.

2007-01-01

Recent literature in applied estimation theory reflects growing interest in the sigma-point (also called unscented ) formulation for optimal sequential state estimation, often describing performance comparisons with extended Kalman filters as applied to specific dynamical problems [c.f. 1, 2, 3]. Favorable attributes of sigma-point filters are described as including a lower expected error for nonlinear even non-differentiable dynamical systems, and a straightforward formulation not requiring derivation or implementation of any partial derivative Jacobian matrices. These attributes are particularly attractive, e.g. in terms of enabling simplified code architecture and streamlined testing, in the formulation of estimators for nonlinear spaceflight mechanics systems, such as filter software onboard deep-space robotic spacecraft. As presented in [4], the Sigma-Point Consider Filter (SPCF) algorithm extends the sigma-point filter algorithm to the problem of consider covariance analysis. Considering parameters in a dynamical system, while estimating its state, provides an upper bound on the estimated state covariance, which is viewed as a conservative approach to designing estimators for problems of general guidance, navigation and control. This is because, whether a parameter in the system model is observable or not, error in the knowledge of the value of a non-estimated parameter will increase the actual uncertainty of the estimated state of the system beyond the level formally indicated by the covariance of an estimator that neglects errors or uncertainty in that parameter. The equations for SPCF covariance evolution are obtained in a fashion similar to the derivation approach taken with standard (i.e. linearized or extended) consider parameterized Kalman filters (c.f. [5]). While in [4] the SPCF and linear-theory consider filter (LTCF) were applied to an illustrative linear dynamics/linear measurement problem, in the present work examines the SPCF as applied to nonlinear sequential consider covariance analysis, i.e. in the presence of nonlinear dynamics and nonlinear measurements. A simple SPCF for orbit determination, exemplifying an algorithm hosted in the guidance, navigation and control (GN&C) computer processor of a hypothetical robotic spacecraft, was implemented, and compared with an identically-parameterized (standard) extended, consider-parameterized Kalman filter. The onboard filtering scenario examined is a hypothetical spacecraft orbit about a small natural body with imperfectly-known mass. The formulations, relative complexities, and performances of the filters are compared and discussed.

Probabilistic Fatigue Damage Program (FATIG)

NASA Technical Reports Server (NTRS)

Michalopoulos, Constantine

2012-01-01

FATIG computes fatigue damage/fatigue life using the stress rms (root mean square) value, the total number of cycles, and S-N curve parameters. The damage is computed by the following methods: (a) traditional method using Miner s rule with stress cycles determined from a Rayleigh distribution up to 3*sigma; and (b) classical fatigue damage formula involving the Gamma function, which is derived from the integral version of Miner's rule. The integration is carried out over all stress amplitudes. This software solves the problem of probabilistic fatigue damage using the integral form of the Palmgren-Miner rule. The software computes fatigue life using an approach involving all stress amplitudes, up to N*sigma, as specified by the user. It can be used in the design of structural components subjected to random dynamic loading, or by any stress analyst with minimal training for fatigue life estimates of structural components.

Software reliability: Additional investigations into modeling with replicated experiments

NASA Technical Reports Server (NTRS)

Nagel, P. M.; Schotz, F. M.; Skirvan, J. A.

1984-01-01

The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.

Photovoltaic performance models: an evaluation with actual field data

NASA Astrophysics Data System (ADS)

TamizhMani, Govindasamy; Ishioye, John-Paul; Voropayev, Arseniy; Kang, Yi

2008-08-01

Prediction of energy production is crucial to the design and installation of the building integrated photovoltaic systems. This prediction should be attainable based on the commonly available parameters such as system size, orientation and tilt angle. Several commercially available as well as free downloadable software tools exist to predict energy production. Six software models have been evaluated in this study and they are: PV Watts, PVsyst, MAUI, Clean Power Estimator, Solar Advisor Model (SAM) and RETScreen. This evaluation has been done by comparing the monthly, seasonaly and annually predicted data with the actual, field data obtained over a year period on a large number of residential PV systems ranging between 2 and 3 kWdc. All the systems are located in Arizona, within the Phoenix metropolitan area which lies at latitude 33° North, and longitude 112 West, and are all connected to the electrical grid.

Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis.

PubMed

Sudell, Maria; Kolamunnage-Dona, Ruwanthi; Tudur-Smith, Catrin

2016-12-05

Joint models for longitudinal and time-to-event data are commonly used to simultaneously analyse correlated data in single study cases. Synthesis of evidence from multiple studies using meta-analysis is a natural next step but its feasibility depends heavily on the standard of reporting of joint models in the medical literature. During this review we aim to assess the current standard of reporting of joint models applied in the literature, and to determine whether current reporting standards would allow or hinder future aggregate data meta-analyses of model results. We undertook a literature review of non-methodological studies that involved joint modelling of longitudinal and time-to-event medical data. Study characteristics were extracted and an assessment of whether separate meta-analyses for longitudinal, time-to-event and association parameters were possible was made. The 65 studies identified used a wide range of joint modelling methods in a selection of software. Identified studies concerned a variety of disease areas. The majority of studies reported adequate information to conduct a meta-analysis (67.7% for longitudinal parameter aggregate data meta-analysis, 69.2% for time-to-event parameter aggregate data meta-analysis, 76.9% for association parameter aggregate data meta-analysis). In some cases model structure was difficult to ascertain from the published reports. Whilst extraction of sufficient information to permit meta-analyses was possible in a majority of cases, the standard of reporting of joint models should be maintained and improved. Recommendations for future practice include clear statement of model structure, of values of estimated parameters, of software used and of statistical methods applied.

REFLECT: Logiciel de restitution des reflectances au sol pour l'amelioration de la qualite de l'information extraite des images satellitales a haute resolution spatiale

NASA Astrophysics Data System (ADS)

Bouroubi, Mohamed Yacine

Multi-spectral satellite imagery, especially at high spatial resolution (finer than 30 m on the ground), represents an invaluable source of information for decision making in various domains in connection with natural resources management, environment preservation or urban planning and management. The mapping scales may range from local (finer resolution than 5 m) to regional (resolution coarser than 5m). The images are characterized by objects reflectance in the electromagnetic spectrum witch represents the key information in many applications. However, satellite sensor measurements are also affected by parasite input due to illumination and observation conditions, to the atmosphere, to topography and to sensor properties. Two questions have oriented this research. What is the best approach to retrieve surface reflectance with the measured values while taking into account these parasite factors? Is this retrieval a sine qua non condition for reliable image information extraction for the diverse domains of application for the images (mapping, environmental monitoring, landscape change detection, resources inventory, etc.)? The goals we have delineated for this research are as follow: (1) Develop software to retrieve ground reflectance while taking into account the aspects mentioned earlier. This software had to be modular enough to allow improvement and adaptation to diverse remote sensing application problems; and (2) Apply this software in various context (urban, agricultural, forest) and analyse results to evaluate the accuracy gain of extracted information from remote sensing imagery transformed in ground reflectance images to demonstrate the necessity of operating in this way, whatever the type of application. During this research, we have developed a tool to retrieve ground reflectance (the new version of the REFLECT software). This software is based on the formulas (and routines) of the 6S code (Second Simulation of Satellite Signal in the Solar Spectrum) and on the dark targets method to estimated the aerosol optical thickness, representing the most difficult factor to correct. Substantial improvements have been made to the existing models. These improvements essentially concern the aerosols properties (integration of a more recent model, improvement of the dark targets selection to estimate the AOD), the adjacency effect, the adaptation to most used high resolution (Landsat TM and ETM+, all HR SPOT 1 to 5, EO-1 ALI and ASTER) and very high resolution (QuickBird et Ikonos) sensors and the correction of topographic effects with a model that separate direct and diffuse solar radiation components and the adaptation of this model to forest canopy. Validation has shown that ground reflectance estimation with REFLECT is performed with an accuracy of approximately +/-0.01 in reflectance units (for in the visible, near-infrared and middle-infrared spectral bands) even for a surface with varying topography. This software has allowed demonstrating, through apparent reflectance simulations, how much parasite factors influencing numerical values of the images may alter the ground reflectance (errors ranging from 10 to 50%). REFLECT has also been used to examine the usefulness of ground reflectance instead of raw data for various common remote sensing applications in domains such as classification, change detection, agriculture and forestry. In most applications (multi-temporal change monitoring, use of vegetation indices, biophysical parameters estimation, etc.) image correction is a crucial step to obtain reliable results. From the computer environment standpoint, REFLECT is organized as a series of menus, corresponding to different steps of: input parameters introducing, gas transmittances calculation, AOD estimation, and finally image correction application, with the possibility of using the fast option witch process an image of 5000 by 5000 pixels in approximately 15 minutes. (Abstract shortened by UMI.)

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, A.; Künsch, H. R.; Schwierz, C.; Stahel, W. A.

2012-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outlying observations may results from errors (e.g. in data transcription) or from local perturbations in the processes that are responsible for a given pattern of spatial variation. As an example, the spatial distribution of some trace metal in the soils of a region may be distorted by emissions of local anthropogenic sources. Outliers affect the modelling of the large-scale spatial variation, the so-called external drift or trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) [2] proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) [1] for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation. Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and unsampled locations and kriging variances. The method has been implemented in an R package. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis of the Tarrawarra soil moisture data set [3].

Structural Identifiability of Dynamic Systems Biology Models

PubMed Central

Villaverde, Alejandro F.

2016-01-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas. PMID:27792726

Transforming parts of a differential equations system to difference equations as a method for run-time savings in NONMEM.

PubMed

Petersson, K J F; Friberg, L E; Karlsson, M O

2010-10-01

Computer models of biological systems grow more complex as computing power increase. Often these models are defined as differential equations and no analytical solutions exist. Numerical integration is used to approximate the solution; this can be computationally intensive, time consuming and be a large proportion of the total computer runtime. The performance of different integration methods depend on the mathematical properties of the differential equations system at hand. In this paper we investigate the possibility of runtime gains by calculating parts of or the whole differential equations system at given time intervals, outside of the differential equations solver. This approach was tested on nine models defined as differential equations with the goal to reduce runtime while maintaining model fit, based on the objective function value. The software used was NONMEM. In four models the computational runtime was successfully reduced (by 59-96%). The differences in parameter estimates, compared to using only the differential equations solver were less than 12% for all fixed effects parameters. For the variance parameters, estimates were within 10% for the majority of the parameters. Population and individual predictions were similar and the differences in OFV were between 1 and -14 units. When computational runtime seriously affects the usefulness of a model we suggest evaluating this approach for repetitive elements of model building and evaluation such as covariate inclusions or bootstraps.

Lesion size estimator of cardiac radiofrequency ablation at different common locations with different tip temperatures.

PubMed

Lai, Yu-Chi; Choy, Young Bin; Haemmerich, Dieter; Vorperian, Vicken R; Webster, John G

2004-10-01

Finite element method (FEM) analysis has become a common method to analyze the lesion formation during temperature-controlled radiofrequency (RF) cardiac ablation. We present a process of FEM modeling a system including blood, myocardium, and an ablation catheter with a thermistor embedded at the tip. The simulation used a simple proportional-integral (PI) controller to control the entire process operated in temperature-controlled mode. Several factors affect the lesion size such as target temperature, blood flow rate, and application time. We simulated the time response of RF ablation at different locations by using different target temperatures. The applied sites were divided into two groups each with a different convective heat transfer coefficient. The first group was high-flow such as the atrioventricular (AV) node and the atrial aspect of the AV annulus, and the other was low-flow such as beneath the valve or inside the coronary sinus. Results showed the change of lesion depth and lesion width with time, under different conditions. We collected data for all conditions and used it to create a database. We implemented a user-interface, the lesion size estimator, where the user enters set temperature and location. Based on the database, the software estimated lesion dimensions during different applied durations. This software could be used as a first-step predictor to help the electrophysiologist choose treatment parameters.

Correlation of serum uric acid with heart rate variability in hypertension.

PubMed

Kunikullaya, K U; Purushottam, N; Prakash, V; Mohan, S; Chinnaswamy, R

2015-01-01

Autonomic dysfunction with dominant sympathetic tone is a common finding among hypertensives and prehypertensives. Uric acid is one of the independent predictors of hypertension. There are very few studies which have shown a relationship between the autonomic tone and uric acid generation pathway among prehypertensives and hypertensives. Aim of the study was to estimate and correlate serum uric acid levels with autonomic function as measured by heart rate variability (HRV) among prehypertensives and hypertensives. Cross-sectional study of three groups, prehypertensives, hypertensives and normotensives, classified according to Joint National Committee VII criteria, with 35 subjects in each group were included in this study. Serum uric acid levels were estimated by using colorimetric assay kit. HRV was analyzed after recording lead II Electrocardiogram using RMS Vagus HRV software (RMS, India). One-way ANOVA and Pearson's correlation was done using SPSS 18.0 software. Mean uric acid levels were 5.62±2.21mg/dL in normal subjects, 7.06±2.87mg/dL in prehypertensives and 9.77±2.04mg/dL in hypertensives. There was statistically significant negative correlation between uric acid and time domain parameters of HRV in the whole sample and among prehypertensives and positive correlation with low frequency power (LF) in ms(2) and n.u. Serum uric acid levels were high in prehypertensives and hypertensives as compared to normal subjects. Further, there was statistically significant correlation seen between uric acid levels and sympathetic domain parameters particularly among prehypertensives. Copyright © 2015 SEHLELHA. Published by Elsevier España, S.L.U. All rights reserved.

Association of parameter, software, and hardware variation with large-scale behavior across 57,000 climate models

PubMed Central

Knight, Christopher G.; Knight, Sylvia H. E.; Massey, Neil; Aina, Tolu; Christensen, Carl; Frame, Dave J.; Kettleborough, Jamie A.; Martin, Andrew; Pascoe, Stephen; Sanderson, Ben; Stainforth, David A.; Allen, Myles R.

2007-01-01

In complex spatial models, as used to predict the climate response to greenhouse gas emissions, parameter variation within plausible bounds has major effects on model behavior of interest. Here, we present an unprecedentedly large ensemble of >57,000 climate model runs in which 10 parameters, initial conditions, hardware, and software used to run the model all have been varied. We relate information about the model runs to large-scale model behavior (equilibrium sensitivity of global mean temperature to a doubling of carbon dioxide). We demonstrate that effects of parameter, hardware, and software variation are detectable, complex, and interacting. However, we find most of the effects of parameter variation are caused by a small subset of parameters. Notably, the entrainment coefficient in clouds is associated with 30% of the variation seen in climate sensitivity, although both low and high values can give high climate sensitivity. We demonstrate that the effect of hardware and software is small relative to the effect of parameter variation and, over the wide range of systems tested, may be treated as equivalent to that caused by changes in initial conditions. We discuss the significance of these results in relation to the design and interpretation of climate modeling experiments and large-scale modeling more generally. PMID:17640921

Rapid Risk Evaluation (ER2) Using MS Excel Spreadsheet: a Case Study of Fredericton (new Brunswick, Canada)

NASA Astrophysics Data System (ADS)

McGrath, H.; Stefanakis, E.; Nastev, M.

2016-06-01

Conventional knowledge of the flood hazard alone (extent and frequency) is not sufficient for informed decision-making. The public safety community needs tools and guidance to adequately undertake flood hazard risk assessment in order to estimate respective damages and social and economic losses. While many complex computer models have been developed for flood risk assessment, they require highly trained personnel to prepare the necessary input (hazard, inventory of the built environment, and vulnerabilities) and analyze model outputs. As such, tools which utilize open-source software or are built within popular desktop software programs are appealing alternatives. The recently developed Rapid Risk Evaluation (ER2) application runs scenario based loss assessment analyses in a Microsoft Excel spreadsheet. User input is limited to a handful of intuitive drop-down menus utilized to describe the building type, age, occupancy and the expected water level. In anticipation of local depth damage curves and other needed vulnerability parameters, those from the U.S. FEMA's Hazus-Flood software have been imported and temporarily accessed in conjunction with user input to display exposure and estimated economic losses related to the structure and the content of the building. Building types and occupancies representative of those most exposed to flooding in Fredericton (New Brunswick) were introduced and test flood scenarios were run. The algorithm was successfully validated against results from the Hazus-Flood model for the same building types and flood depths.

Analysis of quality raw data of second generation sequencers with Quality Assessment Software.

PubMed

Ramos, Rommel Tj; Carneiro, Adriana R; Baumbach, Jan; Azevedo, Vasco; Schneider, Maria Pc; Silva, Artur

2011-04-18

Second generation technologies have advantages over Sanger; however, they have resulted in new challenges for the genome construction process, especially because of the small size of the reads, despite the high degree of coverage. Independent of the program chosen for the construction process, DNA sequences are superimposed, based on identity, to extend the reads, generating contigs; mismatches indicate a lack of homology and are not included. This process improves our confidence in the sequences that are generated. We developed Quality Assessment Software, with which one can review graphs showing the distribution of quality values from the sequencing reads. This software allow us to adopt more stringent quality standards for sequence data, based on quality-graph analysis and estimated coverage after applying the quality filter, providing acceptable sequence coverage for genome construction from short reads. Quality filtering is a fundamental step in the process of constructing genomes, as it reduces the frequency of incorrect alignments that are caused by measuring errors, which can occur during the construction process due to the size of the reads, provoking misassemblies. Application of quality filters to sequence data, using the software Quality Assessment, along with graphing analyses, provided greater precision in the definition of cutoff parameters, which increased the accuracy of genome construction.

A Decision Support System for Planning, Control and Auditing of DoD Software Cost Estimation.

DTIC Science & Technology

1986-03-01

is frequently used in U. S. Air Force software cost estimates. Barry Boehm’s Constructive Cost Estimation Model (COCOMO) was recently selected for use...are considered basic to the proper development of software. Pressman , [Ref. 11], addresses these basic elements in a manner which attempts to integrate...H., Jr., and Carlson, Eric D., Building E fective Decision SUDDOrt Systems, Prentice-Hal, EnglewoodNJ, 1982 11. Pressman , Roger S., o A Practioner’s A

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes

PubMed Central

2011-01-01

Background Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. Conclusions On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain. PMID:21605357

Methods for cost estimation in software project management

NASA Astrophysics Data System (ADS)

Briciu, C. V.; Filip, I.; Indries, I. I.

2016-02-01

The speed in which the processes used in software development field have changed makes it very difficult the task of forecasting the overall costs for a software project. By many researchers, this task has been considered unachievable, but there is a group of scientist for which this task can be solved using the already known mathematical methods (e.g. multiple linear regressions) and the new techniques as genetic programming and neural networks. The paper presents a solution for building a model for the cost estimation models in the software project management using genetic algorithms starting from the PROMISE datasets related COCOMO 81 model. In the first part of the paper, a summary of the major achievements in the research area of finding a model for estimating the overall project costs is presented together with the description of the existing software development process models. In the last part, a basic proposal of a mathematical model of a genetic programming is proposed including here the description of the chosen fitness function and chromosome representation. The perspective of model described it linked with the current reality of the software development considering as basis the software product life cycle and the current challenges and innovations in the software development area. Based on the author's experiences and the analysis of the existing models and product lifecycle it was concluded that estimation models should be adapted with the new technologies and emerging systems and they depend largely by the chosen software development method.

CrossTalk: The Journal of Defense Software Engineering. Volume 20, Number 6, June 2007

DTIC Science & Technology

2007-06-01

California. He has co-authored the book Software Cost Estimation With COCOMO II with Barry Boehm and others. Clark helped define the COCOMO II model...Software Engineering at the University of Southern California. She worked with Barry Boehm and Chris Abts to develop and calibrate a cost-estimation...2003/02/ schorsch.html>. 2. See “Software Engineering, A Practitioners Approach” by Roger Pressman for a good description of coupling, cohesion

Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer

NASA Technical Reports Server (NTRS)

Broderick, Daniel

2012-01-01

This software retrieves the surface and atmosphere parameters of multi-angle, multiband spectra. The synthetic spectra are generated by applying the modified Rahman-Pinty-Verstraete Bidirectional Reflectance Distribution Function (BRDF) model, and a single-scattering dominated atmosphere model to surface reflectance data from Multiangle Imaging SpectroRadiometer (MISR). The aerosol physical model uses a single scattering approximation using Rayleigh scattering molecules, and Henyey-Greenstein aerosols. The surface and atmosphere parameters of the models are retrieved using the Lavenberg-Marquardt algorithm. The software can retrieve the surface and atmosphere parameters with two different scales. The surface parameters are retrieved pixel-by-pixel while the atmosphere parameters are retrieved for a group of pixels where the same atmosphere model parameters are applied. This two-scale approach allows one to select the natural scale of the atmosphere properties relative to surface properties. The software also takes advantage of an intelligent initial condition given by the solution of the neighbor pixels.

Parameter Estimation for Compact Binaries with Ground-Based Gravitational-Wave Observations Using the LALInference

NASA Technical Reports Server (NTRS)

Veitch, J.; Raymond, V.; Farr, B.; Farr, W.; Graff, P.; Vitale, S.; Aylott, B.; Blackburn, K.; Christensen, N.; Coughlin, M.

2015-01-01

The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star (BNS), a neutron star - black hole binary (NSBH) and a binary black hole (BBH), where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence (CBC) parameter space.

Improving Software Engineering on NASA Projects

NASA Technical Reports Server (NTRS)

Crumbley, Tim; Kelly, John C.

2010-01-01

Software Engineering Initiative: Reduces risk of software failure -Increases mission safety. More predictable software cost estimates and delivery schedules. Smarter buyer of contracted out software. More defects found and removed earlier. Reduces duplication of efforts between projects. Increases ability to meet the challenges of evolving software technology.

Comparison of cyclic correlation and the wavelet method for symbol rate detection

NASA Astrophysics Data System (ADS)

Carr, Richard; Whitney, James

Software defined radio (SDR) is a relatively new technology that holds a great deal of promise in the communication field in general, and, in particular the area of space communications. Tra-ditional communication systems are comprised of a transmitter and a receiver, where through prior planning and scheduling, the transmitter and receiver are pre-configured for a particu-lar communication modality. For any particular modality the radio circuitry is configured to transmit, receive, and resolve one type of modulation at a certain data rate. Traditional radio's are limited by the fact that the circuitry is fixed. Software defined radios on the other hand do not suffer from this limitation. SDR's are comprised mainly of software modules which allow them to be flexible, in that they can resolve various types of modulation types that occur at different data rates. This ability is of very high importance in space where parameters of the communications link may need to be changed due to channel fading, reduced power, or other unforeseen events. In these cases the ability to autonomously change aspects of the radio's con-figuration becomes an absolute necessity in order to maintain communications. In order for the technology to work the receiver has to be able to determine the modulation type and the data rate of the signal. The data rate of the signal is one of the first parameters to be resolved, as it is needed to find the other signal parameters such as modulation type and the signal-to-noise ratio. There are a number of algorithms that have been developed to detect or estimate the data rate of a signal. This paper will investigate two of these algorithms, namely, the cyclic correlation algorithm and a wavelet-based detection algorithm. Both of these algorithms are feature-based algorithms, meaning that they make their estimations based on certain inherent features of the signals to which they are applied. The cyclic correlation algorithm takes advan-tage of the cyclostationary nature of MPSK signals, while the wavelet-based algorithms take advantage of the fact of being able to detect transient changes in the signal, i.e., transitions from `1' to'0'. Both of these algorithms are tested under various signal-to-noise conditions to see which has the better performance, and the results are presented in this paper.

Detecting SNPs and estimating allele frequencies in clonal bacterial populations by sequencing pooled DNA.

PubMed

Holt, Kathryn E; Teo, Yik Y; Li, Heng; Nair, Satheesh; Dougan, Gordon; Wain, John; Parkhill, Julian

2009-08-15

Here, we present a method for estimating the frequencies of SNP alleles present within pooled samples of DNA using high-throughput short-read sequencing. The method was tested on real data from six strains of the highly monomorphic pathogen Salmonella Paratyphi A, sequenced individually and in a pool. A variety of read mapping and quality-weighting procedures were tested to determine the optimal parameters, which afforded > or =80% sensitivity of SNP detection and strong correlation with true SNP frequency at poolwide read depth of 40x, declining only slightly at read depths 20-40x. The method was implemented in Perl and relies on the opensource software Maq for read mapping and SNP calling. The Perl script is freely available from ftp://ftp.sanger.ac.uk/pub/pathogens/pools/.

Software for X-Ray Images Calculation of Hydrogen Compression Device in Megabar Pressure Range

NASA Astrophysics Data System (ADS)

Egorov, Nikolay; Bykov, Alexander; Pavlov, Valery

2007-06-01

Software for x-ray images simulation is described. The software is a part of x-ray method used for investigation of an equation of state of hydrogen in a megabar pressure range. A graphical interface that clearly and simply allows users to input data for x-ray image calculation: properties of the studied device, parameters of the x-ray radiation source, parameters of the x-ray radiation recorder, the experiment geometry; to represent the calculation results and efficiently transmit them to other software for processing. The calculation time is minimized. This makes it possible to perform calculations in a dialogue regime. The software is written in ``MATLAB'' system.

Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

NASA Astrophysics Data System (ADS)

Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

2013-12-01

Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so-called mod06 results (Cloud Product) are assimilated twice a day (at 00 and 12 UTC) by DBCRAS. DBCRAS creates 72 hours long weather forecasts with 48 km horizontal resolution. DBCRAS is operational at the University since 2009 which means that by now sufficient data is available for the verification of the model. In the present study verification results for the DBCRAS total precipitable water forecasts are presented based on analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Numerical indices are calculated to quantify the performance of DBCRAS. During a limited time period DBCRAS was also ran without assimilating MODIS products which means that there is possibility to quantify the effect of assimilating MODIS physical products on the quality of the forecasts. For this limited time period verification indices are compared to decide whether MODIS data improves forecast quality or not.

Earth Core and Inner Core: What Can We Learn From a Bayesian Inversion of Combined Nutation and Surface Gravimetry Data?

NASA Astrophysics Data System (ADS)

Lambert, S. B.; Ziegler, Y.; Rosat, S.; Bizouard, C.

2017-12-01

Nutation time series derived from very long baseline interferometry (VLBI) and time varying surface gravity data recorded by superconducting gravimeters (SG) have long been used separately to assess the Earth's interior via the estimation of the free core and inner core resonance effects on nutation or tidal gravity. The results obtained from these two techniques have shown recently to be consistent, making relevant the combination of VLBI and SG observables and the estimation of Earth's interior parameters in a single inversion. We present here the results of combining nutation and surface gravity time series to improve estimates of the Earth's core and inner core resonant frequencies. We use VLBI nutation time series spanning 1984-2016 derived by several analysis centers affiliated to the International VLBI Service for Geodesy and Astrometry, together with surface gravity data from about 15 SG stations. We address the resonance model used for describing the Earth's interior response to tidal excitation, the data preparation consisting of the error recalibration and amplitude fitting to nutation data, and processing of SG time-varying gravity to remove any gaps, spikes, steps and other disturbances, followed by the tidal analysis with the ETERNA 3.4 software package. New estimates of the resonant periods are proposed and correlations between the parameters are investigated.

3D Reconstruction and Approximation of Vegetation Geometry for Modeling of Within-canopy Flows

NASA Astrophysics Data System (ADS)

Henderson, S. M.; Lynn, K.; Lienard, J.; Strigul, N.; Mullarney, J. C.; Norris, B. K.; Bryan, K. R.

2016-02-01

Aquatic vegetation can shelter coastlines from waves and currents, sometimes resulting in accretion of fine sediments. We developed a photogrammetric technique for estimating the key geometric vegetation parameters that are required for modeling of within-canopy flows. Accurate estimates of vegetation geometry and density are essential to refine hydrodynamic models, but accurate, convenient, and time-efficient methodologies for measuring complex canopy geometries have been lacking. The novel approach presented here builds on recent progress in photogrammetry and computer vision. We analyzed the geometry of aerial mangrove roots, called pneumatophores, in Vietnam's Mekong River Delta. Although comparatively thin, pneumatophores are more numerous than mangrove trunks, and thus influence near bed flow and sediment transport. Quadrats (1 m2) were placed at low tide among pneumatophores. Roots were counted and measured for height and diameter. Photos were taken from multiple angles around each quadrat. Relative camera locations and orientations were estimated from key features identified in multiple images using open-source software (VisualSfM). Next, a dense 3D point cloud was produced. Finally, algorithms were developed for automated estimation of pneumatophore geometry from the 3D point cloud. We found good agreement between hand-measured and photogrammetric estimates of key geometric parameters, including mean stem diameter, total number of stems, and frontal area density. These methods can reduce time spent measuring in the field, thereby enabling future studies to refine models of water flows and sediment transport within heterogenous vegetation canopies.

BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology.

PubMed

Villaverde, Alejandro F; Henriques, David; Smallbone, Kieran; Bongard, Sophia; Schmid, Joachim; Cicin-Sain, Damjan; Crombach, Anton; Saez-Rodriguez, Julio; Mauch, Klaus; Balsa-Canto, Eva; Mendes, Pedro; Jaeger, Johannes; Banga, Julio R

2015-02-20

Dynamic modelling is one of the cornerstones of systems biology. Many research efforts are currently being invested in the development and exploitation of large-scale kinetic models. The associated problems of parameter estimation (model calibration) and optimal experimental design are particularly challenging. The community has already developed many methods and software packages which aim to facilitate these tasks. However, there is a lack of suitable benchmark problems which allow a fair and systematic evaluation and comparison of these contributions. Here we present BioPreDyn-bench, a set of challenging parameter estimation problems which aspire to serve as reference test cases in this area. This set comprises six problems including medium and large-scale kinetic models of the bacterium E. coli, baker's yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The level of description includes metabolism, transcription, signal transduction, and development. For each problem we provide (i) a basic description and formulation, (ii) implementations ready-to-run in several formats, (iii) computational results obtained with specific solvers, (iv) a basic analysis and interpretation. This suite of benchmark problems can be readily used to evaluate and compare parameter estimation methods. Further, it can also be used to build test problems for sensitivity and identifiability analysis, model reduction and optimal experimental design methods. The suite, including codes and documentation, can be freely downloaded from the BioPreDyn-bench website, https://sites.google.com/site/biopredynbenchmarks/ .

Application of mathematical model methods for optimization tasks in construction materials technology

NASA Astrophysics Data System (ADS)

Fomina, E. V.; Kozhukhova, N. I.; Sverguzova, S. V.; Fomin, A. E.

2018-05-01

In this paper, the regression equations method for design of construction material was studied. Regression and polynomial equations representing the correlation between the studied parameters were proposed. The logic design and software interface of the regression equations method focused on parameter optimization to provide the energy saving effect at the stage of autoclave aerated concrete design considering the replacement of traditionally used quartz sand by coal mining by-product such as argillite. The mathematical model represented by a quadric polynomial for the design of experiment was obtained using calculated and experimental data. This allowed the estimation of relationship between the composition and final properties of the aerated concrete. The surface response graphically presented in a nomogram allowed the estimation of concrete properties in response to variation of composition within the x-space. The optimal range of argillite content was obtained leading to a reduction of raw materials demand, development of target plastic strength of aerated concrete as well as a reduction of curing time before autoclave treatment. Generally, this method allows the design of autoclave aerated concrete with required performance without additional resource and time costs.

Dose estimates for the solid waste performance assessment

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

Rittman, P.D.

1994-08-30

The Solid Waste Performance Assessment calculations by PNL in 1990 were redone to incorporate changes in methods and parameters since then. The ten scenarios found in their report were reduced to three, the Post-Drilling Resident, the Post-Excavation Resident, and an All Pathways Irrigator. In addition, estimates of population dose to people along the Columbia River are also included. The attached report describes the methods and parameters used in the calculations, and derives dose factors for each scenario. In addition, waste concentrations, ground water concentrations, and river water concentrations needed to reach the performance objectives of 100 mrem/yr and 500 person-rem/yrmore » are computed. Internal dose factors from DOE-0071 were applied when computing internal dose. External dose rate factors came from the GENII Version 1.485 software package. Dose calculations were carried out on a spreadsheet. The calculations are described in detail in the report for 63 nuclides, including 5 not presently in the GENII libraries. The spreadsheet calculations were checked by comparison with GENII, as described in Appendix D.« less

Anticoagulation therapy advisor: a decision-support system for heparin therapy during ECMO.

PubMed Central

Peverini, R. L.; Sale, M.; Rhine, W. D.; Fagan, L. M.; Lenert, L. A.

1992-01-01

We present a case study describing our development of a mathematical model to control a clinical parameter in a patient--in this case, the degree of anticoagulation during extracorporeal membrane oxygenation (ECMO) support. During ECMO therapy, an anticoagulant agent (heparin) is administered to prevent thrombosis. Under- or over-coagulation can have grave consequences. To improve control of anticoagulation, we developed a pharmacokinetic-pharmacodynamic (PK-PD) model that predicts activated clotting times (ACT) using the NONMEM program. We then integrated this model into a decision-support system, and validated it with an independent data set. The population model had a mean absolute error of prediction for ACT values of 33.5 seconds, with a mean bias in estimation of -14.3 seconds. Individualization of model-parameter estimates using nonlinear regression improved the absolute error prediction to 25.5 seconds, and lowered the mean bias to -3.1 seconds. The PK-PD model is coupled with software for heuristic interpretation of model results to provide a complete environment for the management of anticoagulation. PMID:1482937

Capture-recapture methodology

USGS Publications Warehouse

Gould, William R.; Kendall, William L.

2013-01-01

Capture-recapture methods were initially developed to estimate human population abundance, but since that time have seen widespread use for fish and wildlife populations to estimate and model various parameters of population, metapopulation, and disease dynamics. Repeated sampling of marked animals provides information for estimating abundance and tracking the fate of individuals in the face of imperfect detection. Mark types have evolved from clipping or tagging to use of noninvasive methods such as photography of natural markings and DNA collection from feces. Survival estimation has been emphasized more recently as have transition probabilities between life history states and/or geographical locations, even where some states are unobservable or uncertain. Sophisticated software has been developed to handle highly parameterized models, including environmental and individual covariates, to conduct model selection, and to employ various estimation approaches such as maximum likelihood and Bayesian approaches. With these user-friendly tools, complex statistical models for studying population dynamics have been made available to ecologists. The future will include a continuing trend toward integrating data types, both for tagged and untagged individuals, to produce more precise and robust population models.

Quantum chemical parameters in QSAR: what do I use when?

USGS Publications Warehouse

Hickey, James P.; Ostrander, Gary K.

1996-01-01

This chapter provides a brief overview of the numerous quantum chemical parameters that have been/are currently being used in quantitative structure activity relationships (QSAR), along with a representative bibliography. The parameters will be grouped according to their mechanistic interpretations, and representative biological and physical chemical applications will be mentioned. Parmater computation methods and the appropriate software are highlighted, as are sources for software.

SU-E-P-05: Electronic Brachytherapy: A Physics Perspective On Field Implementation

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

Pai, S; Ayyalasomayajula, S; Lee, S

2015-06-15

Purpose: We want to summarize our experience implementing a successful program of electronic brachytherapy at several dermatology clinics with the help of a cloud based software to help us define the key program parameters and capture physics QA aspects. Optimally developed software helps the physicist in peer review and qualify the physical parameters. Methods: Using the XOFT™ Axxent™ electronic brachytherapy system in conjunction with a cloud-based software, a process was setup to capture and record treatments. It was implemented initially at about 10 sites in California. For dosimetric purposes, the software facilitated storage of the physics parameters of surface applicatorsmore » used in treatment and other source calibration parameters. In addition, the patient prescription, pathology and other setup considerations were input by radiation oncologist and the therapist. This facilitated physics planning of the treatment parameters and also independent check of the dwell time. From 2013–2014, nearly1500 such calculation were completed by a group of physicists. A total of 800 patients with multiple lesions have been treated successfully during this period. The treatment log files have been uploaded and documented in the software which facilitated physics peer review of treatments per the standards in place by AAPM and ACR. Results: The program model was implemented successfully at multiple sites. The cloud based software allowed for proper peer review and compliance of the program at 10 clinical sites. Dosimtery was done on 800 patients and executed in a timely fashion to suit the clinical needs. Accumulated physics data in the software from the clinics allows for robust analysis and future development. Conclusion: Electronic brachytherapy implementation experience from a quality assurance perspective was greatly enhanced by using a cloud based software. The comprehensive database will pave the way for future developments to yield superior physics outcomes.« less

Utility of coupling nonlinear optimization methods with numerical modeling software

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

Murphy, M.J.

1996-08-05

Results of using GLO (Global Local Optimizer), a general purpose nonlinear optimization software package for investigating multi-parameter problems in science and engineering is discussed. The package consists of the modular optimization control system (GLO), a graphical user interface (GLO-GUI), a pre-processor (GLO-PUT), a post-processor (GLO-GET), and nonlinear optimization software modules, GLOBAL & LOCAL. GLO is designed for controlling and easy coupling to any scientific software application. GLO runs the optimization module and scientific software application in an iterative loop. At each iteration, the optimization module defines new values for the set of parameters being optimized. GLO-PUT inserts the new parametermore » values into the input file of the scientific application. GLO runs the application with the new parameter values. GLO-GET determines the value of the objective function by extracting the results of the analysis and comparing to the desired result. GLO continues to run the scientific application over and over until it finds the ``best`` set of parameters by minimizing (or maximizing) the objective function. An example problem showing the optimization of material model is presented (Taylor cylinder impact test).« less

Estimation and enhancement of real-time software reliability through mutation analysis

NASA Technical Reports Server (NTRS)

Geist, Robert; Offutt, A. J.; Harris, Frederick C., Jr.

1992-01-01

A simulation-based technique for obtaining numerical estimates of the reliability of N-version, real-time software is presented. An extended stochastic Petri net is employed to represent the synchronization structure of N versions of the software, where dependencies among versions are modeled through correlated sampling of module execution times. Test results utilizing specifications for NASA's planetary lander control software indicate that mutation-based testing could hold greater potential for enhancing reliability than the desirable but perhaps unachievable goal of independence among N versions.

The use of a genetic algorithm-based search strategy in geostatistics: application to a set of anisotropic piezometric head data

NASA Astrophysics Data System (ADS)

Abedini, M. J.; Nasseri, M.; Burn, D. H.

2012-04-01

In any geostatistical study, an important consideration is the choice of an appropriate, repeatable, and objective search strategy that controls the nearby samples to be included in the location-specific estimation procedure. Almost all geostatistical software available in the market puts the onus on the user to supply search strategy parameters in a heuristic manner. These parameters are solely controlled by geographical coordinates that are defined for the entire area under study, and the user has no guidance as to how to choose these parameters. The main thesis of the current study is that the selection of search strategy parameters has to be driven by data—both the spatial coordinates and the sample values—and cannot be chosen beforehand. For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed. The search capability of a genetic algorithm is exploited to search the feature space for appropriate, either local or global, search strategy parameters. Radius of circle/sphere and/or radii of standard or rotated ellipse/ellipsoid are considered as the decision variables to be optimized by GA. The superiority of GA-based ordinary kriging is demonstrated through application to the Wolfcamp Aquifer piezometric head data. Assessment of numerical results showed that definition of search strategy parameters based on both geographical coordinates and sample values improves cross-validation statistics when compared with that based on geographical coordinates alone. In the case of a variable search neighborhood for each estimation point, optimization of local search strategy parameters for an elliptical support domain—the orientation of which is dictated by anisotropic axes—via GA was able to capture the dynamics of piezometric head in west Texas/New Mexico in an efficient way.

FMT (Flight Software Memory Tracker) For Cassini Spacecraft-Software Engineering Using JAVA

NASA Technical Reports Server (NTRS)

Kan, Edwin P.; Uffelman, Hal; Wax, Allan H.

1997-01-01

The software engineering design of the Flight Software Memory Tracker (FMT) Tool is discussed in this paper. FMT is a ground analysis software set, consisting of utilities and procedures, designed to track the flight software, i.e., images of memory load and updatable parameters of the computers on-board Cassini spacecraft. FMT is implemented in Java.

Future Software Sizing Metrics and Estimation Challenges

DTIC Science & Technology

2011-07-01

systems 4. Ultrahigh software system assurance 5. Legacy maintenance and Brownfield development 6. Agile and Lean/ Kanban development. This paper...refined as the design of the maintenance modifications or Brownfield re-engineering is determined. VII. 6. AGILE AND LEAN/ KANBAN DEVELOPMENT The...difficulties of software maintenance estimation can often be mitigated by using lean workflow management techniques such as Kanban [25]. In Kanban

Software for marine ecological environment comprehensive monitoring system based on MCGS

NASA Astrophysics Data System (ADS)

Wang, X. H.; Ma, R.; Cao, X.; Cao, L.; Chu, D. Z.; Zhang, L.; Zhang, T. P.

2017-08-01

The automatic integrated monitoring software for marine ecological environment based on MCGS configuration software is designed and developed to realize real-time automatic monitoring of many marine ecological parameters. The DTU data transmission terminal performs network communication and transmits the data to the user data center in a timely manner. The software adopts the modular design and has the advantages of stable and flexible data structure, strong portability and scalability, clear interface, simple user operation and convenient maintenance. Continuous site comparison test of 6 months showed that, the relative error of the parameters monitored by the system such as temperature, salinity, turbidity, pH, dissolved oxygen was controlled within 5% with the standard method and the relative error of the nutrient parameters was within 15%. Meanwhile, the system had few maintenance times, low failure rate, stable and efficient continuous monitoring capabilities. The field application shows that the software is stable and the data communication is reliable, and it has a good application prospect in the field of marine ecological environment comprehensive monitoring.

Preparation of AgInS2 nanoparticles by a facile microwave heating technique; study of effective parameters, optical and photovoltaic characteristics

NASA Astrophysics Data System (ADS)

Tadjarodi, Azadeh; Cheshmekhavar, Amir Hossein; Imani, Mina

2012-12-01

In this work, AgInS2 (AIS) semiconductor nanoparticles were synthesized by an efficient and facile microwave heating technique using several sulfur sources and solvents in the different reaction times. The SEM images presented the particle morphology for all of the obtained products in the arranged reaction conditions. The particle size of 70 nm was obtained using thioacetamide (TAA), ethylene glycol (EG) as the sulfur source and solvent, respectively at the reaction time of 5 min. It was found that the change of the mentioned parameters lead to alter on the particle size of the resulting products. The average particle size was estimated using a microstructure measurement program and Minitab statistical software. The optical band gap energy of 1.96 eV for the synthesized AIS nanoparticles was determined by the diffuse reflectance spectroscopy (DRS). AgInS2/CdS/CuInSe2 heterojunction solar cell was constructed and photovoltaic parameters, i.e., open-circuit voltage (Voc), short-circuit current (Jsc) and fill factor (FF) were estimated by photocurrent-voltage (I-V) curve. The calculated fill factor of 30% and energy conversion efficiency of 1.58% revealed the capability of AIS nanoparticles to use in the solar cell devices.

Evapotranspiration based on equilibrated relative humidity (ETRHEQ): Evaluation over the continental U.S.

NASA Astrophysics Data System (ADS)

Rigden, Angela J.; Salvucci, Guido D.

2015-04-01

A novel method of estimating evapotranspiration (ET), referred to as the ETRHEQ method, is further developed, validated, and applied across the U.S. from 1961 to 2010. The ETRHEQ method estimates the surface conductance to water vapor transport, which is the key rate-limiting parameter of typical ET models, by choosing the surface conductance that minimizes the vertical variance of the calculated relative humidity profile averaged over the day. The ETRHEQ method, which was previously tested at five AmeriFlux sites, is modified for use at common weather stations and further validated at 20 AmeriFlux sites that span a wide range of climates and limiting factors. Averaged across all sites, the daily latent heat flux RMSE is ˜26 W·m-2 (or 15%). The method is applied across the U.S. at 305 weather stations and spatially interpolated using ANUSPLIN software. Gridded annual mean ETRHEQ ET estimates are compared with four data sets, including water balance-derived ET, machine-learning ET estimates based on FLUXNET data, North American Land Data Assimilation System project phase 2 ET, and a benchmark product that integrates 14 global ET data sets, with RMSEs ranging from 8.7 to 12.5 cm·yr-1. The ETRHEQ method relies only on data measured at weather stations, an estimate of vegetation height derived from land cover maps, and an estimate of soil thermal inertia. These data requirements allow it to have greater spatial coverage than direct measurements, greater historical coverage than satellite methods, significantly less parameter specification than most land surface models, and no requirement for calibration.

Sample size planning for composite reliability coefficients: accuracy in parameter estimation via narrow confidence intervals.

PubMed

Terry, Leann; Kelley, Ken

2012-11-01

Composite measures play an important role in psychology and related disciplines. Composite measures almost always have error. Correspondingly, it is important to understand the reliability of the scores from any particular composite measure. However, the point estimates of the reliability of composite measures are fallible and thus all such point estimates should be accompanied by a confidence interval. When confidence intervals are wide, there is much uncertainty in the population value of the reliability coefficient. Given the importance of reporting confidence intervals for estimates of reliability, coupled with the undesirability of wide confidence intervals, we develop methods that allow researchers to plan sample size in order to obtain narrow confidence intervals for population reliability coefficients. We first discuss composite reliability coefficients and then provide a discussion on confidence interval formation for the corresponding population value. Using the accuracy in parameter estimation approach, we develop two methods to obtain accurate estimates of reliability by planning sample size. The first method provides a way to plan sample size so that the expected confidence interval width for the population reliability coefficient is sufficiently narrow. The second method ensures that the confidence interval width will be sufficiently narrow with some desired degree of assurance (e.g., 99% assurance that the 95% confidence interval for the population reliability coefficient will be less than W units wide). The effectiveness of our methods was verified with Monte Carlo simulation studies. We demonstrate how to easily implement the methods with easy-to-use and freely available software. ©2011 The British Psychological Society.

Development of a score and probability estimate for detecting angle closure based on anterior segment optical coherence tomography.

PubMed

Nongpiur, Monisha E; Haaland, Benjamin A; Perera, Shamira A; Friedman, David S; He, Mingguang; Sakata, Lisandro M; Baskaran, Mani; Aung, Tin

2014-01-01

To develop a score along with an estimated probability of disease for detecting angle closure based on anterior segment optical coherence tomography (AS OCT) imaging. Cross-sectional study. A total of 2047 subjects 50 years of age and older were recruited from a community polyclinic in Singapore. All subjects underwent standardized ocular examination including gonioscopy and imaging by AS OCT (Carl Zeiss Meditec). Customized software (Zhongshan Angle Assessment Program) was used to measure AS OCT parameters. Complete data were available for 1368 subjects. Data from the right eyes were used for analysis. A stepwise logistic regression model with Akaike information criterion was used to generate a score that then was converted to an estimated probability of the presence of gonioscopic angle closure, defined as the inability to visualize the posterior trabecular meshwork for at least 180 degrees on nonindentation gonioscopy. Of the 1368 subjects, 295 (21.6%) had gonioscopic angle closure. The angle closure score was calculated from the shifted linear combination of the AS OCT parameters. The score can be converted to an estimated probability of having angle closure using the relationship: estimated probability = e(score)/(1 + e(score)), where e is the natural exponential. The score performed well in a second independent sample of 178 angle-closure subjects and 301 normal controls, with an area under the receiver operating characteristic curve of 0.94. A score derived from a single AS OCT image, coupled with an estimated probability, provides an objective platform for detection of angle closure. Copyright © 2014 Elsevier Inc. All rights reserved.

[Evaluation of Organ Dose Estimation from Indices of CT Dose Using Dose Index Registry].

PubMed

Iriuchijima, Akiko; Fukushima, Yasuhiro; Ogura, Akio

Direct measurement of each patient organ dose from computed tomography (CT) is not possible. Most methods to estimate patient organ dose is using Monte Carlo simulation with dedicated software. However, dedicated software is too expensive for small scale hospitals. Not every hospital can estimate organ dose with dedicated software. The purpose of this study was to evaluate the simple method of organ dose estimation using some common indices of CT dose. The Monte Carlo simulation software Radimetrics (Bayer) was used for calculating organ dose and analysis relationship between indices of CT dose and organ dose. Multidetector CT scanners were compared with those from two manufactures (LightSpeed VCT, GE Healthcare; SOMATOM Definition Flash, Siemens Healthcare). Using stored patient data from Radimetrics, the relationships between indices of CT dose and organ dose were indicated as each formula for estimating organ dose. The accuracy of estimation method of organ dose was compared with the results of Monte Carlo simulation using the Bland-Altman plots. In the results, SSDE was the feasible index for estimation organ dose in almost organs because it reflected each patient size. The differences of organ dose between estimation and simulation were within 23%. In conclusion, our estimation method of organ dose using indices of CT dose is convenient for clinical with accuracy.

Extracting data from figures with software was faster, with higher interrater reliability than manual extraction.

PubMed

Jelicic Kadic, Antonia; Vucic, Katarina; Dosenovic, Svjetlana; Sapunar, Damir; Puljak, Livia

2016-06-01

To compare speed and accuracy of graphical data extraction using manual estimation and open source software. Data points from eligible graphs/figures published in randomized controlled trials (RCTs) from 2009 to 2014 were extracted by two authors independently, both by manual estimation and with the Plot Digitizer, open source software. Corresponding authors of each RCT were contacted up to four times via e-mail to obtain exact numbers that were used to create graphs. Accuracy of each method was compared against the source data from which the original graphs were produced. Software data extraction was significantly faster, reducing time for extraction for 47%. Percent agreement between the two raters was 51% for manual and 53.5% for software data extraction. Percent agreement between the raters and original data was 66% vs. 75% for the first rater and 69% vs. 73% for the second rater, for manual and software extraction, respectively. Data extraction from figures should be conducted using software, whereas manual estimation should be avoided. Using software for data extraction of data presented only in figures is faster and enables higher interrater reliability. Copyright © 2016 Elsevier Inc. All rights reserved.

Software Development Cost Estimation Executive Summary

NASA Technical Reports Server (NTRS)

Hihn, Jairus M.; Menzies, Tim

2006-01-01

Identify simple fully validated cost models that provide estimation uncertainty with cost estimate. Based on COCOMO variable set. Use machine learning techniques to determine: a) Minimum number of cost drivers required for NASA domain based cost models; b) Minimum number of data records required and c) Estimation Uncertainty. Build a repository of software cost estimation information. Coordinating tool development and data collection with: a) Tasks funded by PA&E Cost Analysis; b) IV&V Effort Estimation Task and c) NASA SEPG activities.

Empirical Estimates of 0Day Vulnerabilities in Control Systems

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

Miles A. McQueen; Wayne F. Boyer; Sean M. McBride

2009-01-01

We define a 0Day vulnerability to be any vulnerability, in deployed software, which has been discovered by at least one person but has not yet been publicly announced or patched. These 0Day vulnerabilities are of particular interest when assessing the risk to well managed control systems which have already effectively mitigated the publicly known vulnerabilities. In these well managed systems the risk contribution from 0Days will have proportionally increased. To aid understanding of how great a risk 0Days may pose to control systems, an estimate of how many are in existence is needed. Consequently, using the 0Day definition given above,more » we developed and applied a method for estimating how many 0Day vulnerabilities are in existence on any given day. The estimate is made by: empirically characterizing the distribution of the lifespans, measured in days, of 0Day vulnerabilities; determining the number of vulnerabilities publicly announced each day; and applying a novel method for estimating the number of 0Day vulnerabilities in existence on any given day using the number of vulnerabilities publicly announced each day and the previously derived distribution of 0Day lifespans. The method was first applied to a general set of software applications by analyzing the 0Day lifespans of 491 software vulnerabilities and using the daily rate of vulnerability announcements in the National Vulnerability Database. This led to a conservative estimate that in the worst year there were, on average, 2500 0Day software related vulnerabilities in existence on any given day. Using a smaller but intriguing set of 15 0Day software vulnerability lifespans representing the actual time from discovery to public disclosure, we then made a more aggressive estimate. In this case, we estimated that in the worst year there were, on average, 4500 0Day software vulnerabilities in existence on any given day. We then proceeded to identify the subset of software applications likely to be used in some control systems, analyzed the associated subset of vulnerabilities, and characterized their lifespans. Using the previously developed method of analysis, we very conservatively estimated 250 control system related 0Day vulnerabilities in existence on any given day. While reasonable, this first order estimate for control systems is probably far more conservative than those made for general software systems since the estimate did not include vulnerabilities unique to control system specific components. These control system specific vulnerabilities were unable to be included in the estimate for a variety of reasons with the most problematic being that the public announcement of unique control system vulnerabilities is very sparse. Consequently, with the intent to improve the above 0Day estimate for control systems, we first identified the additional, unique to control systems, vulnerability estimation constraints and then investigated new mechanisms which may be useful for estimating the number of unique 0Day software vulnerabilities found in control system components. We proceeded to identify a number of new mechanisms and approaches for estimating and incorporating control system specific vulnerabilities into an improved 0Day estimation method. These new mechanisms and approaches appear promising and will be more rigorously evaluated during the course of the next year.« less

The Martian rotation from Doppler measurements: Simulations of future radioscience experiments

NASA Astrophysics Data System (ADS)

Péters, Marie-Julie; Yseboodt, Marie; Dehant, Véronique; Le Maistre, Sebastien; Marty, Jean-Charles

2016-10-01

The radioscience experiment onboard the future InSight and ExoMars missions consists in two-way Doppler shift measurement from a X-band radio link between a lander on Mars and the ground stations on Earth. The Doppler effect on the radio signal is related to the revolution of the planets around the Sun and to the variations of the orientation and the rotation of Mars. The variations of the orientation of the rotation axis are the precession and nutations, related to the deep interior of Mars and the variations of the rotation rate are the length-of-day variation, related to the dynamic of the atmosphere.We perform numerical simulations of the Doppler measurements in order to quantify the precision that can be achieved on the determination of the Mars rotation and orientation parameters (MOP). For this purpose, we use the GINS (Géodésie par Intégrations Numériques Simultanées) software developed by the CNES and further adapted at the Royal Observatory of Belgium for planetary geodesy applications. This software enables to simulate the relative motion of the lander at the surface of Mars relative to the ground stations and to compute the MOP signature on the Doppler shift. The signature is the difference between the Doppler observable estimated taking into account a MOP and the Doppler estimated without this parameter.The objective is to build a strategy to be applied to future data processing in order to improve our estimation of the MOP. We study the effect of the elevation of the Earth in the sky of the lander, of the tracking duration and number of pass per week, of the tracking time, of the lander position and of Doppler geometry on the signatures. Indeed, due to the geometry, the Doppler data are highly sensitive to the position variations along the line of sight.

Software risk estimation and management techniques at JPL

NASA Technical Reports Server (NTRS)

Hihn, J.; Lum, K.

2002-01-01

In this talk we will discuss how uncertainty has been incorporated into the JPL software model, probabilistic-based estimates, and how risk is addressed, how cost risk is currently being explored via a variety of approaches, from traditional risk lists, to detailed WBS-based risk estimates to the Defect Detection and Prevention (DDP) tool.

CrossTalk: The Journal of Defense Software Engineering. Volume 18, Number 4

DTIC Science & Technology

2005-04-01

older automated cost- estimating tools are no longer being actively marketed but are still in use such as CheckPoint, COCOMO, ESTIMACS, REVIC, and SPQR ...estimation tools: SPQR /20, Checkpoint, and Knowl- edgePlan. These software estimation tools pioneered the use of function point metrics for sizing and

MAPPING INDUCED POLARIZATION WITH NATURAL ELECTROMAGNETIC FIELDS FOR EXPLORATION AND RESOURCES CHARACTERIZATION BY THE MINING INDUSTRY

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

Edward Nichols

2002-05-03

In this quarter we continued the processing of the Safford IP survey data. The processing identified a time shift problem between the sites that was caused by a GPS firmware error. A software procedure was developed to identify and correct the shift, and this was applied to the data. Preliminary estimates were made of the remote referenced MT parameters, and initial data quality assessment showed the data quality was good for most of the line. The multi-site robust processing code of Egbert was linked to the new data and processing initiated.

Analysis of Electronic Densities and Integrated Doses in Multiform Glioblastomas Stereotactic Radiotherapy

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

Baron-Aznar, C.; Moreno-Jimenez, S.; Celis, M. A.

2008-08-11

Integrated dose is the total energy delivered in a radiotherapy target. This physical parameter could be a predictor for complications such as brain edema and radionecrosis after stereotactic radiotherapy treatments for brain tumors. Integrated Dose depends on the tissue density and volume. Using CT patients images from the National Institute of Neurology and Neurosurgery and BrainScan(c) software, this work presents the mean density of 21 multiform glioblastomas, comparative results for normal tissue and estimated integrated dose for each case. The relationship between integrated dose and the probability of complications is discussed.

Software Dependability Assessment Methods.

DTIC Science & Technology

1986-11-01

Maor.rldx TABLE ~~~~~~ ~ ~ .2.RVU OFWR ETBI1YMDL Goei Crot~Nor~ Nu wu.. Ps.~o, r1.~~j% 2-4 __ N App L,-caW L Nct A pp.cLL tc ReAAW -Ur e ’-cdtl L. Reaons I...bug is found and immediately removed. The model provides a good fit with data. The parameter estimates are reasonable for the data sets tested. 3.0...where n = the number of errors found to date. 6.3 Study Results The model provides a good fit with data. The model runs into slight trouble with its "no

Adjustment and validation of a simulation tool for CSP plants based on parabolic trough technology

NASA Astrophysics Data System (ADS)

García-Barberena, Javier; Ubani, Nora

2016-05-01

The present work presents the validation process carried out for a simulation tool especially designed for the energy yield assessment of concentrating solar plants based on parabolic through (PT) technology. The validation has been carried out by comparing the model estimations with real data collected from a commercial CSP plant. In order to adjust the model parameters used for the simulation, 12 different days were selected among one-year of operational data measured at the real plant. The 12 days were simulated and the estimations compared with the measured data, focusing on the most important variables from the simulation point of view: temperatures, pressures and mass flow of the solar field, gross power, parasitic power, and net power delivered by the plant. Based on these 12 days, the key parameters for simulating the model were properly fixed and the simulation of a whole year performed. The results obtained for a complete year simulation showed very good agreement for the gross and net electric total production. The estimations for these magnitudes show a 1.47% and 2.02% BIAS respectively. The results proved that the simulation software describes with great accuracy the real operation of the power plant and correctly reproduces its transient behavior.

[Microcytomorphometric video-image detection of nuclear chromatin in ovarian cancer].

PubMed

Grzonka, Dariusz; Kamiński, Kazimierz; Kaźmierczak, Wojciech

2003-09-01

Technology of detection of tissue preparates precisious evaluates contents of nuclear chromatine, largeness and shape of cellular nucleus, indicators of mitosis, DNA index, ploidy, phase-S fraction and other parameters. Methods of detection of picture are: microcytomorphometry video-image (MCMM-VI), flow, double flow and activated by fluorescence. Diagnostic methods of malignant neoplasm of ovary are still nonspecific and not precise, that is a reason of unsatisfied results of treatment. Evaluation of microcytomorphometric measurements of nuclear chromatine histopathologic tissue preparates (HP) of ovarian cancer and comparison to normal ovarian tissue. Estimated 10 paraffin embedded tissue preparates of serous ovarian cancer, 4 preparates mucinous cancer and 2 cases of tumor Kruckenberg patients operated in Clinic of Perinatology and Gynaecology Silesian Medical Academy in Zabrze in period 2001-2002, MCMM-VI estimation based on computer aided analysis system: microscope Axioscop 20, camera tv JVCTK-C 1380, CarlZeiss KS Vision 400 rel.3.0 software. Following MCMM-VI parameters assessed: count of pathologic nucleus, diameter of nucleus, area, min/max diameter ratio, equivalent circle diameter (Dcircle), mean of brightness (mean D), integrated optical density (IOD = area x mean D), DNA index and 2.5 c exceeding rate percentage (2.5 c ER%). MCMM-VI performed on the 160 areas of 16 preparates of cancer and 100 areas of normal ovarian tissue. Statistical analysis was performed by used t-Student test. We obtained stastistically significant higher values parameters of nuclear chromatine, DI, 2.5 c ER of mucinous cancer and tumor Kruckenberg comparison to serous cancer. MCMM-VI parameters of chromatine malignant ovarian neoplasm were statistically significantly higher than normal ovarian tissue. Cytometric and karyometric parametres of nuclear chromatine estimated MCMM-VI are useful in the diagnostics and prognosis of ovarian cancer.

Age estimation by dentin translucency measurement using digital method: An institutional study

PubMed Central

Gupta, Shalini; Chandra, Akhilesh; Agnihotri, Archana; Gupta, Om Prakash; Maurya, Niharika

2017-01-01

Aims: The aims of the present study were to measure translucency on sectioned teeth using available computer hardware and software, to correlate dimensions of root dentin translucency with age, and to assess whether translucency is reliable for age estimation. Materials and Methods: A pilot study was done on 62 freshly extracted single-rooted permanent teeth from 62 different individuals (35 males and 27 females) and their 250 μm thick sections were prepared by micromotor, carborundum disks, and Arkansas stone. Each tooth section was scanned and the images were opened in the Adobe Photoshop software. Measurement of root dentin translucency (TD length) was done on the scanned image by placing two guides (A and B) along the x-axis of ABFO NO. 2 scale. Unpaired t-test, regression analysis, and Pearson correlation coefficient were used as statistical tools. Results: A linear relationship was observed between TD length and age in the regression analysis. The Pearson correlation analysis showed that there was positive correlation (r = 0.52, P = 0.0001) between TD length and age. However, no significant (P > 0.05) difference was observed in the TD length between male (8.44 ± 2.92 mm) and female (7.80 ± 2.79 mm) samples. Conclusion: Translucency of the root dentin increases with age and it can be used as a reliable parameter for the age estimation. The method used here to digitally select and measure translucent root dentin is more refined, better correlated to age, and produce superior age estimation. PMID:28584476

A STUDY OF SOME SOFTWARE PARAMETERS IN TIME-SHARING SYSTEMS.

DTIC Science & Technology

A review is made of some existing time-sharing computer systems and an exploration of various software characteristics is conducted. This...of the various parameters upon the average response cycle time, the average number in the queue awaiting service , the average length of time a user is

Experimental Design for Stochastic Models of Nonlinear Signaling Pathways Using an Interval-Wise Linear Noise Approximation and State Estimation

PubMed Central

Zimmer, Christoph

2016-01-01

Background Computational modeling is a key technique for analyzing models in systems biology. There are well established methods for the estimation of the kinetic parameters in models of ordinary differential equations (ODE). Experimental design techniques aim at devising experiments that maximize the information encoded in the data. For ODE models there are well established approaches for experimental design and even software tools. However, data from single cell experiments on signaling pathways in systems biology often shows intrinsic stochastic effects prompting the development of specialized methods. While simulation methods have been developed for decades and parameter estimation has been targeted for the last years, only very few articles focus on experimental design for stochastic models. Methods The Fisher information matrix is the central measure for experimental design as it evaluates the information an experiment provides for parameter estimation. This article suggest an approach to calculate a Fisher information matrix for models containing intrinsic stochasticity and high nonlinearity. The approach makes use of a recently suggested multiple shooting for stochastic systems (MSS) objective function. The Fisher information matrix is calculated by evaluating pseudo data with the MSS technique. Results The performance of the approach is evaluated with simulation studies on an Immigration-Death, a Lotka-Volterra, and a Calcium oscillation model. The Calcium oscillation model is a particularly appropriate case study as it contains the challenges inherent to signaling pathways: high nonlinearity, intrinsic stochasticity, a qualitatively different behavior from an ODE solution, and partial observability. The computational speed of the MSS approach for the Fisher information matrix allows for an application in realistic size models. PMID:27583802

An update to the analysis of the Canadian Spatial Reference System

NASA Astrophysics Data System (ADS)

Ferland, R.; Piraszewski, M.; Craymer, M.

2015-12-01

The primary objective of the Canadian Spatial Reference System (CSRS) is to provide users access to a consistent geo-referencing infrastructure over the Canadian landmass. Global Navigation Satellite System (GNSS) positioning accuracy requirements ranges from meter level to mm level (e.g.: crustal deformation). The highest level of the Canadian infrastructure consist of a network of continually operating GPS and GNSS receivers, referred to as active control stations. The network includes all Canadian public active control stations, some bordering US CORS and Alaska stations, Greenland active control stations, as well as a selection of IGS reference frame stations. The Bernese analysis software is used for the daily processing and the combination into weekly solutions which form the basis for this analysis. IGS weekly final orbit, Earth Rotation parameters (ERP's) and coordinates products are used in the processing. For the more demanding users, the time dependant changes of station coordinates is often more important.All station coordinate estimates and related covariance information is used in this analysis. For each input solution, variance factor, translation, rotation and scale (and if needed their rates) or subsets of these are estimated. In the combination of these weekly solutions, station positions and velocities are estimated. Since the time series from the stations in these networks often experience changes in behavior, new (or reuse of) parameters are generally used in these situations. As is often the case with real data, unrealistic coordinates may occur. Automatic detection and removal of outliers is used in these cases. For the transformation, position and velocity parameters loose apriori estimates and uncertainties are provided. Alignment using the usual Helmert transformation to the latest IGb08 realization of ITRF is also performed during the adjustment.

Influence of ocean tides on the diurnal and semidiurnal earth rotation variations from VLBI observations

NASA Astrophysics Data System (ADS)

Gubanov, V. S.; Kurdubov, S. L.

2015-05-01

The International astrogeodetic standard IERS Conventions (2010) contains a model of the diurnal and semidiurnal variations in Earth rotation parameters (ERPs), the pole coordinates and the Universal Time, arising from lunisolar tides in the world ocean. This model was constructed in the mid-1990s through a global analysis of Topex/Poseidon altimetry. The goal of this study is to try to estimate the parameters of this model by processing all the available VLBI observations on a global network of stations over the last 35 years performed within the framework of IVS (International VLBI Service) geodetic programs. The complexity of the problemlies in the fact that the sought-for corrections to the parameters of this model lie within 1 mm and, thus, are at the limit of their detectability by all currently available methods of ground-based positional measurements. This requires applying universal software packages with a high accuracy of reduction calculations and a well-developed system of controlling the simultaneous adjustment of observational data to analyze long series of VLBI observations. This study has been performed with the QUASAR software package developed at the Institute of Applied Astronomy of the Russian Academy of Sciences. Although the results obtained, on the whole, confirm a high accuracy of the basic model in the IERS Conventions (2010), statistically significant corrections that allow this model to be refined have been detected for some harmonics of the ERP variations.

Software for Photometric and Astrometric Reduction of Video Meteors

NASA Astrophysics Data System (ADS)

Atreya, Prakash; Christou, Apostolos

2007-12-01

SPARVM is a Software for Photometric and Astrometric Reduction of Video Meteors being developed at Armagh Observatory. It is written in Interactive Data Language (IDL) and is designed to run primarily under Linux platform. The basic features of the software will be derivation of light curves, estimation of angular velocity and radiant position for single station data. For double station data, calculation of 3D coordinates of meteors, velocity, brightness, and estimation of meteoroid's orbit including uncertainties. Currently, the software supports extraction of time and date from video frames, estimation of position of cameras (Azimuth, Altitude), finding stellar sources in video frames and transformation of coordinates from video, frames to Horizontal coordinate system (Azimuth, Altitude), and Equatorial coordinate system (RA, Dec).

Study of the Seismic Source in the Jalisco Block

NASA Astrophysics Data System (ADS)

Gutierrez, Q. J.; Escudero, C. R.; Nunez-Cornu, F. J.; Ochoa, J.; Cruz, L. H.

2013-05-01

The direct measure of the earthquake fault dimension and the orientation, as well as the direction of slip represent a complicated task nevertheless a better approach is using the seismic waves spectrum and the direction of P-first motions observed at each station. With these methods we can estimate the seismic source parameters like the stress drop, the corner frequency which is linked to the rupture duration time, the fault radius (For the particular case of a circular fault), the rupture area, the seismic moment , the moment magnitude and the focal mechanisms. The study area where were estimated the source parameters comprises the complex tectonic configuration of Jalisco block, that is delimited by the mesoamerican trench at the west, the Colima grabben to the south, and the Tepic-Zacoalco to the north The data was recorded by the MARS network (Mapping the Riviera Subduction Zone) and the RESAJ network. MARS had 50 stations and settled in the Jalisco block; for a period of time, of January 1, 2006 until June, 2007, the magnitude range of these was between 3 to 6.5 MB. RESJAL has 10 stations and is within the state of Jalisco, began to record since October 2011 and continues to record. Before of apply the method we firs remove the trend, the mean and the instrument response and we corrected for attenuation; then manually chosen the S wave, the multitaper method was used to obtain the spectrum of this wave and so estimate the corner frequency and the spectra level. We substitute the obtained in the equations of the Brune model to calculate the source parameters. To calculate focal mechanisms HASH software was used which determines the most likely mechanism. The main propose of this study is estimate earthquake seismic source parameters with the objective of that helps to understand the physics of earthquake rupture mechanism in the area.

Testing Software Development Project Productivity Model

NASA Astrophysics Data System (ADS)

Lipkin, Ilya

Software development is an increasingly influential factor in today's business environment, and a major issue affecting software development is how an organization estimates projects. If the organization underestimates cost, schedule, and quality requirements, the end results will not meet customer needs. On the other hand, if the organization overestimates these criteria, resources that could have been used more profitably will be wasted. There is no accurate model or measure available that can guide an organization in a quest for software development, with existing estimation models often underestimating software development efforts as much as 500 to 600 percent. To address this issue, existing models usually are calibrated using local data with a small sample size, with resulting estimates not offering improved cost analysis. This study presents a conceptual model for accurately estimating software development, based on an extensive literature review and theoretical analysis based on Sociotechnical Systems (STS) theory. The conceptual model serves as a solution to bridge organizational and technological factors and is validated using an empirical dataset provided by the DoD. Practical implications of this study allow for practitioners to concentrate on specific constructs of interest that provide the best value for the least amount of time. This study outlines key contributing constructs that are unique for Software Size E-SLOC, Man-hours Spent, and Quality of the Product, those constructs having the largest contribution to project productivity. This study discusses customer characteristics and provides a framework for a simplified project analysis for source selection evaluation and audit task reviews for the customers and suppliers. Theoretical contributions of this study provide an initial theory-based hypothesized project productivity model that can be used as a generic overall model across several application domains such as IT, Command and Control, Simulation and etc... This research validates findings from previous work concerning software project productivity and leverages said results in this study. The hypothesized project productivity model provides statistical support and validation of expert opinions used by practitioners in the field of software project estimation.

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

NASA Technical Reports Server (NTRS)

Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric

2003-01-01

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been proposed by the Society of Automotive Engineers (SAE). The test cases compare different probabilistic methods within NESSUS because it is important that a user can have confidence that estimates of stochastic parameters of a response will be within an acceptable error limit. For each response, the mean, standard deviation, and 0.99 percentile, are repeatedly estimated which allows confidence statements to be made for each parameter estimated, and for each method. Thus, the ability of several stochastic methods to efficiently and accurately estimate density parameters is compared using four valid test cases. While all of the reliability methods used performed quite well, for the new LHS module within NESSUS it was found that it had a lower estimation error than MC when they were used to estimate the mean, standard deviation, and 0.99 percentile of the four different stochastic responses. Also, LHS required a smaller amount of calculations to obtain low error answers with a high amount of confidence than MC. It can therefore be stated that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ and the newest LHS module is a valuable new enhancement of the program.

GVIPS Models and Software

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Gendy, Atef; Saleeb, Atef F.; Mark, John; Wilt, Thomas E.

2007-01-01

Two reports discuss, respectively, (1) the generalized viscoplasticity with potential structure (GVIPS) class of mathematical models and (2) the Constitutive Material Parameter Estimator (COMPARE) computer program. GVIPS models are constructed within a thermodynamics- and potential-based theoretical framework, wherein one uses internal state variables and derives constitutive equations for both the reversible (elastic) and the irreversible (viscoplastic) behaviors of materials. Because of the underlying potential structure, GVIPS models not only capture a variety of material behaviors but also are very computationally efficient. COMPARE comprises (1) an analysis core and (2) a C++-language subprogram that implements a Windows-based graphical user interface (GUI) for controlling the core. The GUI relieves the user of the sometimes tedious task of preparing data for the analysis core, freeing the user to concentrate on the task of fitting experimental data and ultimately obtaining a set of material parameters. The analysis core consists of three modules: one for GVIPS material models, an analysis module containing a specialized finite-element solution algorithm, and an optimization module. COMPARE solves the problem of finding GVIPS material parameters in the manner of a design-optimization problem in which the parameters are the design variables.

Transformation of Galilean satellite parameters to J2000

NASA Astrophysics Data System (ADS)

Lieske, J. H.

1998-09-01

The so-called galsat software has the capability of computing Earth-equatorial coordinates of Jupiter's Galilean satellies in an arbitrary reference frame, not just that of B1950. The 50 parameters which define the theory of motion of the Galilean satellites (Lieske 1977, Astron. Astrophys. 56, 333--352) could also be transformed in a manner such that the same galsat computer program can be employed to compute rectangular coordinates with their values being in the J2000 system. One of the input parameters (varepsilon_ {27}) is related to the obliquity of the ecliptic and its value is normally zero in the B1950 frame. If that parameter is changed from 0 to -0.0002771, and if other input parameters are changed in a prescribed manner, then the same galsat software can be employed to produce ephemerides on the J2000 system for any of the ephemerides which employ the galsat parameters, such as those of Arlot (1982), Vasundhara (1994) and Lieske. In this paper we present the parameters whose values must be altered in order for the software to produce coordinates directly in the J2000 system.

Stochastic Inversion of 2D Magnetotelluric Data

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

Chen, Jinsong

2010-07-01

The algorithm is developed to invert 2D magnetotelluric (MT) data based on sharp boundary parametrization using a Bayesian framework. Within the algorithm, we consider the locations and the resistivity of regions formed by the interfaces are as unknowns. We use a parallel, adaptive finite-element algorithm to forward simulate frequency-domain MT responses of 2D conductivity structure. Those unknown parameters are spatially correlated and are described by a geostatistical model. The joint posterior probability distribution function is explored by Markov Chain Monte Carlo (MCMC) sampling methods. The developed stochastic model is effective for estimating the interface locations and resistivity. Most importantly, itmore » provides details uncertainty information on each unknown parameter. Hardware requirements: PC, Supercomputer, Multi-platform, Workstation; Software requirements C and Fortan; Operation Systems/version is Linux/Unix or Windows« less

iSEDfit: Bayesian spectral energy distribution modeling of galaxies

NASA Astrophysics Data System (ADS)

Moustakas, John

2017-08-01

iSEDfit uses Bayesian inference to extract the physical properties of galaxies from their observed broadband photometric spectral energy distribution (SED). In its default mode, the inputs to iSEDfit are the measured photometry (fluxes and corresponding inverse variances) and a measurement of the galaxy redshift. Alternatively, iSEDfit can be used to estimate photometric redshifts from the input photometry alone. After the priors have been specified, iSEDfit calculates the marginalized posterior probability distributions for the physical parameters of interest, including the stellar mass, star-formation rate, dust content, star formation history, and stellar metallicity. iSEDfit also optionally computes K-corrections and produces multiple "quality assurance" (QA) plots at each stage of the modeling procedure to aid in the interpretation of the prior parameter choices and subsequent fitting results. The software is distributed as part of the impro IDL suite.

A measurement system for large, complex software programs

NASA Technical Reports Server (NTRS)

Rone, Kyle Y.; Olson, Kitty M.; Davis, Nathan E.

1994-01-01

This paper describes measurement systems required to forecast, measure, and control activities for large, complex software development and support programs. Initial software cost and quality analysis provides the foundation for meaningful management decisions as a project evolves. In modeling the cost and quality of software systems, the relationship between the functionality, quality, cost, and schedule of the product must be considered. This explicit relationship is dictated by the criticality of the software being developed. This balance between cost and quality is a viable software engineering trade-off throughout the life cycle. Therefore, the ability to accurately estimate the cost and quality of software systems is essential to providing reliable software on time and within budget. Software cost models relate the product error rate to the percent of the project labor that is required for independent verification and validation. The criticality of the software determines which cost model is used to estimate the labor required to develop the software. Software quality models yield an expected error discovery rate based on the software size, criticality, software development environment, and the level of competence of the project and developers with respect to the processes being employed.

SELENA - An open-source tool for seismic risk and loss assessment using a logic tree computation procedure

NASA Astrophysics Data System (ADS)

Molina, S.; Lang, D. H.; Lindholm, C. D.

2010-03-01

The era of earthquake risk and loss estimation basically began with the seminal paper on hazard by Allin Cornell in 1968. Following the 1971 San Fernando earthquake, the first studies placed strong emphasis on the prediction of human losses (number of casualties and injured used to estimate the needs in terms of health care and shelters in the immediate aftermath of a strong event). In contrast to these early risk modeling efforts, later studies have focused on the disruption of the serviceability of roads, telecommunications and other important lifeline systems. In the 1990s, the National Institute of Building Sciences (NIBS) developed a tool (HAZUS ®99) for the Federal Emergency Management Agency (FEMA), where the goal was to incorporate the best quantitative methodology in earthquake loss estimates. Herein, the current version of the open-source risk and loss estimation software SELENA v4.1 is presented. While using the spectral displacement-based approach (capacity spectrum method), this fully self-contained tool analytically computes the degree of damage on specific building typologies as well as the associated economic losses and number of casualties. The earthquake ground shaking estimates for SELENA v4.1 can be calculated or provided in three different ways: deterministic, probabilistic or based on near-real-time data. The main distinguishing feature of SELENA compared to other risk estimation software tools is that it is implemented in a 'logic tree' computation scheme which accounts for uncertainties of any input (e.g., scenario earthquake parameters, ground-motion prediction equations, soil models) or inventory data (e.g., building typology, capacity curves and fragility functions). The data used in the analysis is assigned with a decimal weighting factor defining the weight of the respective branch of the logic tree. The weighting of the input parameters accounts for the epistemic and aleatoric uncertainties that will always follow the necessary parameterization of the different types of input data. Like previous SELENA versions, SELENA v4.1 is coded in MATLAB which allows for easy dissemination among the scientific-technical community. Furthermore, any user has access to the source code in order to adapt, improve or refine the tool according to his or her particular needs. The handling of SELENA's current version and the provision of input data is customized for an academic environment but which can then support decision-makers of local, state and regional governmental agencies in estimating possible losses from future earthquakes.

An overview of STRUCTURE: applications, parameter settings, and supporting software

PubMed Central

Porras-Hurtado, Liliana; Ruiz, Yarimar; Santos, Carla; Phillips, Christopher; Carracedo, Ángel; Lareu, Maria V.

2013-01-01

Objectives: We present an up-to-date review of STRUCTURE software: one of the most widely used population analysis tools that allows researchers to assess patterns of genetic structure in a set of samples. STRUCTURE can identify subsets of the whole sample by detecting allele frequency differences within the data and can assign individuals to those sub-populations based on analysis of likelihoods. The review covers STRUCTURE's most commonly used ancestry and frequency models, plus an overview of the main applications of the software in human genetics including case-control association studies (CCAS), population genetics, and forensic analysis. The review is accompanied by supplementary material providing a step-by-step guide to running STRUCTURE. Methods: With reference to a worked example, we explore the effects of changing the principal analysis parameters on STRUCTURE results when analyzing a uniform set of human genetic data. Use of the supporting software: CLUMPP and distruct is detailed and we provide an overview and worked example of STRAT software, applicable to CCAS. Conclusion: The guide offers a simplified view of how STRUCTURE, CLUMPP, distruct, and STRAT can be applied to provide researchers with an informed choice of parameter settings and supporting software when analyzing their own genetic data. PMID:23755071