Instrumental variables estimation under a structural Cox model
DEFF Research Database (Denmark)
Martinussen, Torben; Nørbo Sørensen, Ditte; Vansteelandt, Stijn
2017-01-01
Instrumental variable (IV) analysis is an increasingly popular tool for inferring the effect of an exposure on an outcome, as witnessed by the growing number of IV applications in epidemiology, for instance. The majority of IV analyses of time-to-event endpoints are, however, dominated by heurist...
Dai, James Y.; Chan, Kwun Chuen Gary; Hsu, Li
2014-01-01
Instrumental variable regression is one way to overcome unmeasured confounding and estimate causal effect in observational studies. Built on structural mean models, there has been considerale work recently developed for consistent estimation of causal relative risk and causal odds ratio. Such models can sometimes suffer from identification issues for weak instruments. This hampered the applicability of Mendelian randomization analysis in genetic epidemiology. When there are multiple genetic variants available as instrumental variables, and causal effect is defined in a generalized linear model in the presence of unmeasured confounders, we propose to test concordance between instrumental variable effects on the intermediate exposure and instrumental variable effects on the disease outcome, as a means to test the causal effect. We show that a class of generalized least squares estimators provide valid and consistent tests of causality. For causal effect of a continuous exposure on a dichotomous outcome in logistic models, the proposed estimators are shown to be asymptotically conservative. When the disease outcome is rare, such estimators are consistent due to the log-linear approximation of the logistic function. Optimality of such estimators relative to the well-known two-stage least squares estimator and the double-logistic structural mean model is further discussed. PMID:24863158
Martinussen, Torben; Vansteelandt, Stijn; Tchetgen Tchetgen, Eric J; Zucker, David M
2017-12-01
The use of instrumental variables for estimating the effect of an exposure on an outcome is popular in econometrics, and increasingly so in epidemiology. This increasing popularity may be attributed to the natural occurrence of instrumental variables in observational studies that incorporate elements of randomization, either by design or by nature (e.g., random inheritance of genes). Instrumental variables estimation of exposure effects is well established for continuous outcomes and to some extent for binary outcomes. It is, however, largely lacking for time-to-event outcomes because of complications due to censoring and survivorship bias. In this article, we make a novel proposal under a class of structural cumulative survival models which parameterize time-varying effects of a point exposure directly on the scale of the survival function; these models are essentially equivalent with a semi-parametric variant of the instrumental variables additive hazards model. We propose a class of recursive instrumental variable estimators for these exposure effects, and derive their large sample properties along with inferential tools. We examine the performance of the proposed method in simulation studies and illustrate it in a Mendelian randomization study to evaluate the effect of diabetes on mortality using data from the Health and Retirement Study. We further use the proposed method to investigate potential benefit from breast cancer screening on subsequent breast cancer mortality based on the HIP-study. © 2017, The International Biometric Society.
Borgen, Nicolai T
2014-11-01
This paper addresses the recent discussion on confounding in the returns to college quality literature using the Norwegian case. The main advantage of studying Norway is the quality of the data. Norwegian administrative data provide information on college applications, family relations and a rich set of control variables for all Norwegian citizens applying to college between 1997 and 2004 (N = 141,319) and their succeeding wages between 2003 and 2010 (676,079 person-year observations). With these data, this paper uses a subset of the models that have rendered mixed findings in the literature in order to investigate to what extent confounding biases the returns to college quality. I compare estimates obtained using standard regression models to estimates obtained using the self-revelation model of Dale and Krueger (2002), a sibling fixed effects model and the instrumental variable model used by Long (2008). Using these methods, I consistently find increasing returns to college quality over the course of students' work careers, with positive returns only later in students' work careers. I conclude that the standard regression estimate provides a reasonable estimate of the returns to college quality. Copyright © 2014 Elsevier Inc. All rights reserved.
Instrumental Variables in the Long Run
DEFF Research Database (Denmark)
Casey, Gregory; Klemp, Marc Patrick Brag
2017-01-01
In the study of long-run economic growth, it is common to use historical or geographical variables as instruments for contemporary endogenous regressors. We study the interpretation of these conventional instrumental variable (IV) regressions in a general, yet simple, framework. Our aim...... quantitative implications for the field of long-run economic growth. We also use our framework to examine related empirical techniques. We find that two prominent regression methodologies - using gravity-based instruments for trade and including ancestry-adjusted variables in linear regression models - have...... is to estimate the long-run causal effect of changes in the endogenous explanatory variable. We find that conventional IV regressions generally cannot recover this parameter of interest. To estimate this parameter, therefore, we develop an augmented IV estimator that combines the conventional regression...
Directory of Open Access Journals (Sweden)
Isa Mona
2016-01-01
Full Text Available This paper is a preliminary study on rationalising green office building investments in Malaysia. The aim of this paper is attempt to introduce the application of Rasch measurement model analysis to determine the validity and reliability of each construct in the questionnaire. In achieving this objective, a questionnaire survey was developed consists of 6 sections and a total of 106 responses were received from various investors who own and lease office buildings in Kuala Lumpur. The Rasch Measurement analysis is used to measure the quality control of item constructs in the instrument by measuring the specific objectivity within the same dimension, to reduce ambiguous measures, and a realistic estimation of precision and implicit quality. The Rasch analysis consists of the summary statistics, item unidimensionality and item measures. A result shows the items and respondent (person reliability is at 0.91 and 0.95 respectively.
DEFF Research Database (Denmark)
Martinussen, Torben; Vansteelandt, Stijn; Tchetgen Tchetgen, Eric J.
2017-01-01
The use of instrumental variables for estimating the effect of an exposure on an outcome is popular in econometrics, and increasingly so in epidemiology. This increasing popularity may be attributed to the natural occurrence of instrumental variables in observational studies that incorporate elem...
Cawley, John
2015-01-01
The method of instrumental variables (IV) is useful for estimating causal effects. Intuitively, it exploits exogenous variation in the treatment, sometimes called natural experiments or instruments. This study reviews the literature in health-services research and medical research that applies the method of instrumental variables, documents trends in its use, and offers examples of various types of instruments. A literature search of the PubMed and EconLit research databases for English-language journal articles published after 1990 yielded a total of 522 original research articles. Citations counts for each article were derived from the Web of Science. A selective review was conducted, with articles prioritized based on number of citations, validity and power of the instrument, and type of instrument. The average annual number of papers in health services research and medical research that apply the method of instrumental variables rose from 1.2 in 1991-1995 to 41.8 in 2006-2010. Commonly-used instruments (natural experiments) in health and medicine are relative distance to a medical care provider offering the treatment and the medical care provider's historic tendency to administer the treatment. Less common but still noteworthy instruments include randomization of treatment for reasons other than research, randomized encouragement to undertake the treatment, day of week of admission as an instrument for waiting time for surgery, and genes as an instrument for whether the respondent has a heritable condition. The use of the method of IV has increased dramatically in the past 20 years, and a wide range of instruments have been used. Applications of the method of IV have in several cases upended conventional wisdom that was based on correlations and led to important insights about health and healthcare. Future research should pursue new applications of existing instruments and search for new instruments that are powerful and valid.
Hoogerheide, L.F.; Kaashoek, J.F.; van Dijk, H.K.
2007-01-01
Likelihoods and posteriors of instrumental variable (IV) regression models with strong endogeneity and/or weak instruments may exhibit rather non-elliptical contours in the parameter space. This may seriously affect inference based on Bayesian credible sets. When approximating posterior
L.F. Hoogerheide (Lennart); J.F. Kaashoek (Johan); H.K. van Dijk (Herman)
2005-01-01
textabstractLikelihoods and posteriors of instrumental variable regression models with strong endogeneity and/or weak instruments may exhibit rather non-elliptical contours in the parameter space. This may seriously affect inference based on Bayesian credible sets. When approximating such contours
Ward, N. K.; Maureira, F.; Yourek, M. A.; Brooks, E. S.; Stockle, C. O.
2014-12-01
The current use of synthetic nitrogen fertilizers in agriculture has many negative environmental and economic costs, necessitating improved nitrogen management. In the highly heterogeneous landscape of the Palouse region in eastern Washington and northern Idaho, crop nitrogen needs vary widely within a field. Site-specific nitrogen management is a promising strategy to reduce excess nitrogen lost to the environment while maintaining current yields by matching crop needs with inputs. This study used in-situ hydrologic, nutrient, and crop yield data from a heavily instrumented field site in the high precipitation zone of the wheat-producing Palouse region to assess the performance of the MicroBasin model. MicroBasin is a high-resolution watershed-scale ecohydrologic model with nutrient cycling and cropping algorithms based on the CropSyst model. Detailed soil mapping conducted at the site was used to parameterize the model and the model outputs were evaluated with observed measurements. The calibrated MicroBasin model was then used to evaluate the impact of various nitrogen management strategies on crop yield and nitrate losses. The strategies include uniform application as well as delineating the field into multiple zones of varying nitrogen fertilizer rates to optimize nitrogen use efficiency. We present how coupled modeling and in-situ data sets can inform agricultural management and policy to encourage improved nitrogen management.
netherland hydrological modeling instrument
Hoogewoud, J. C.; de Lange, W. J.; Veldhuizen, A.; Prinsen, G.
2012-04-01
Netherlands Hydrological Modeling Instrument A decision support system for water basin management. J.C. Hoogewoud , W.J. de Lange ,A. Veldhuizen , G. Prinsen , The Netherlands Hydrological modeling Instrument (NHI) is the center point of a framework of models, to coherently model the hydrological system and the multitude of functions it supports. Dutch hydrological institutes Deltares, Alterra, Netherlands Environmental Assessment Agency, RWS Waterdienst, STOWA and Vewin are cooperating in enhancing the NHI for adequate decision support. The instrument is used by three different ministries involved in national water policy matters, for instance the WFD, drought management, manure policy and climate change issues. The basis of the modeling instrument is a state-of-the-art on-line coupling of the groundwater system (MODFLOW), the unsaturated zone (metaSWAP) and the surface water system (MOZART-DM). It brings together hydro(geo)logical processes from the column to the basin scale, ranging from 250x250m plots to the river Rhine and includes salt water flow. The NHI is validated with an eight year run (1998-2006) with dry and wet periods. For this run different parts of the hydrology have been compared with measurements. For instance, water demands in dry periods (e.g. for irrigation), discharges at outlets, groundwater levels and evaporation. A validation alone is not enough to get support from stakeholders. Involvement from stakeholders in the modeling process is needed. There fore to gain sufficient support and trust in the instrument on different (policy) levels a couple of actions have been taken: 1. a transparent evaluation of modeling-results has been set up 2. an extensive program is running to cooperate with regional waterboards and suppliers of drinking water in improving the NHI 3. sharing (hydrological) data via newly setup Modeling Database for local and national models 4. Enhancing the NHI with "local" information. The NHI is and has been used for many
On the Interpretation of Instrumental Variables in the Presence of Specification Errors
Directory of Open Access Journals (Sweden)
P.A.V.B. Swamy
2015-01-01
Full Text Available The method of instrumental variables (IV and the generalized method of moments (GMM, and their applications to the estimation of errors-in-variables and simultaneous equations models in econometrics, require data on a sufficient number of instrumental variables that are both exogenous and relevant. We argue that, in general, such instruments (weak or strong cannot exist.
Instrument Modeling and Synthesis
Horner, Andrew B.; Beauchamp, James W.
During the 1970s and 1980s, before synthesizers based on direct sampling of musical sounds became popular, replicating musical instruments using frequency modulation (FM) or wavetable synthesis was one of the “holy grails” of music synthesis. Synthesizers such as the Yamaha DX7 allowed users great flexibility in mixing and matching sounds, but were notoriously difficult to coerce into producing sounds like those of a given instrument. Instrument design wizards practiced the mysteries of FM instrument design.
Rassen, Jeremy A; Brookhart, M Alan; Glynn, Robert J; Mittleman, Murray A; Schneeweiss, Sebastian
2009-12-01
The gold standard of study design for treatment evaluation is widely acknowledged to be the randomized controlled trial (RCT). Trials allow for the estimation of causal effect by randomly assigning participants either to an intervention or comparison group; through the assumption of "exchangeability" between groups, comparing the outcomes will yield an estimate of causal effect. In the many cases where RCTs are impractical or unethical, instrumental variable (IV) analysis offers a nonexperimental alternative based on many of the same principles. IV analysis relies on finding a naturally varying phenomenon, related to treatment but not to outcome except through the effect of treatment itself, and then using this phenomenon as a proxy for the confounded treatment variable. This article demonstrates how IV analysis arises from an analogous but potentially impossible RCT design, and outlines the assumptions necessary for valid estimation. It gives examples of instruments used in clinical epidemiology and concludes with an outline on estimation of effects.
Falsification Testing of Instrumental Variables Methods for Comparative Effectiveness Research.
Pizer, Steven D
2016-04-01
To demonstrate how falsification tests can be used to evaluate instrumental variables methods applicable to a wide variety of comparative effectiveness research questions. Brief conceptual review of instrumental variables and falsification testing principles and techniques accompanied by an empirical application. Sample STATA code related to the empirical application is provided in the Appendix. Comparative long-term risks of sulfonylureas and thiazolidinediones for management of type 2 diabetes. Outcomes include mortality and hospitalization for an ambulatory care-sensitive condition. Prescribing pattern variations are used as instrumental variables. Falsification testing is an easily computed and powerful way to evaluate the validity of the key assumption underlying instrumental variables analysis. If falsification tests are used, instrumental variables techniques can help answer a multitude of important clinical questions. © Health Research and Educational Trust.
A review of instrumental variable estimators for Mendelian randomization.
Burgess, Stephen; Small, Dylan S; Thompson, Simon G
2017-10-01
Instrumental variable analysis is an approach for obtaining causal inferences on the effect of an exposure (risk factor) on an outcome from observational data. It has gained in popularity over the past decade with the use of genetic variants as instrumental variables, known as Mendelian randomization. An instrumental variable is associated with the exposure, but not associated with any confounder of the exposure-outcome association, nor is there any causal pathway from the instrumental variable to the outcome other than via the exposure. Under the assumption that a single instrumental variable or a set of instrumental variables for the exposure is available, the causal effect of the exposure on the outcome can be estimated. There are several methods available for instrumental variable estimation; we consider the ratio method, two-stage methods, likelihood-based methods, and semi-parametric methods. Techniques for obtaining statistical inferences and confidence intervals are presented. The statistical properties of estimates from these methods are compared, and practical advice is given about choosing a suitable analysis method. In particular, bias and coverage properties of estimators are considered, especially with weak instruments. Settings particularly relevant to Mendelian randomization are prioritized in the paper, notably the scenario of a continuous exposure and a continuous or binary outcome.
Instrumental variable methods in comparative safety and effectiveness research.
Brookhart, M Alan; Rassen, Jeremy A; Schneeweiss, Sebastian
2010-06-01
Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial.
Instrumental variable methods in comparative safety and effectiveness research†
Brookhart, M. Alan; Rassen, Jeremy A.; Schneeweiss, Sebastian
2010-01-01
Summary Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial. PMID:20354968
Evaluating disease management programme effectiveness: an introduction to instrumental variables.
Linden, Ariel; Adams, John L
2006-04-01
This paper introduces the concept of instrumental variables (IVs) as a means of providing an unbiased estimate of treatment effects in evaluating disease management (DM) programme effectiveness. Model development is described using zip codes as the IV. Three diabetes DM outcomes were evaluated: annual diabetes costs, emergency department (ED) visits and hospital days. Both ordinary least squares (OLS) and IV estimates showed a significant treatment effect for diabetes costs (P = 0.011) but neither model produced a significant treatment effect for ED visits. However, the IV estimate showed a significant treatment effect for hospital days (P = 0.006) whereas the OLS model did not. These results illustrate the utility of IV estimation when the OLS model is sensitive to the confounding effect of hidden bias.
Power calculator for instrumental variable analysis in pharmacoepidemiology.
Walker, Venexia M; Davies, Neil M; Windmeijer, Frank; Burgess, Stephen; Martin, Richard M
2017-10-01
Instrumental variable analysis, for example with physicians' prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysis, such as Mendelian randomization power calculators, do not allow for the structure of research questions in this field. This is because the analysis in pharmacoepidemiology will typically have stronger instruments and detect larger causal effects than in other fields. Consequently, there is a need for dedicated power calculators for pharmacoepidemiological research. The formula for calculating the power of a study using instrumental variable analysis in the context of pharmacoepidemiology is derived before being validated by a simulation study. The formula is applicable for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome. An online calculator, as well as packages in both R and Stata, are provided for the implementation of the formula by others. The statistical power of instrumental variable analysis in pharmacoepidemiological studies to detect a clinically meaningful treatment effect is an important consideration. Research questions in this field have distinct structures that must be accounted for when calculating power. The formula presented differs from existing instrumental variable power formulae due to its parametrization, which is designed specifically for ease of use by pharmacoepidemiologists. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association
Comparison of variance estimators for metaanalysis of instrumental variable estimates
Schmidt, A. F.; Hingorani, A. D.; Jefferis, B. J.; White, J.; Groenwold, R. H H; Dudbridge, F.; Ben-Shlomo, Y.; Chaturvedi, N.; Engmann, J.; Hughes, A.; Humphries, S.; Hypponen, E.; Kivimaki, M.; Kuh, D.; Kumari, M.; Menon, U.; Morris, R.; Power, C.; Price, J.; Wannamethee, G.; Whincup, P.
2016-01-01
Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two
Econometrics in outcomes research: the use of instrumental variables.
Newhouse, J P; McClellan, M
1998-01-01
We describe an econometric technique, instrumental variables, that can be useful in estimating the effectiveness of clinical treatments in situations when a controlled trial has not or cannot be done. This technique relies upon the existence of one or more variables that induce substantial variation in the treatment variable but have no direct effect on the outcome variable of interest. We illustrate the use of the technique with an application to aggressive treatment of acute myocardial infarction in the elderly.
Instrumental variable estimation in a survival context
DEFF Research Database (Denmark)
Tchetgen Tchetgen, Eric J; Walter, Stefan; Vansteelandt, Stijn
2015-01-01
for regression analysis in a survival context, primarily under an additive hazards model, for which we describe 2 simple methods for estimating causal effects. The first method is a straightforward 2-stage regression approach analogous to 2-stage least squares commonly used for IV analysis in linear regression....... The IV approach is very well developed in the context of linear regression and also for certain generalized linear models with a nonlinear link function. However, IV methods are not as well developed for regression analysis with a censored survival outcome. In this article, we develop the IV approach....... In this approach, the fitted value from a first-stage regression of the exposure on the IV is entered in place of the exposure in the second-stage hazard model to recover a valid estimate of the treatment effect of interest. The second method is a so-called control function approach, which entails adding...
Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.
Vansteelandt, Stijn; Walter, Stefan; Tchetgen Tchetgen, Eric
2018-07-01
Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.
The productivity of mental health care: an instrumental variable approach.
Lu, Mingshan
1999-06-01
BACKGROUND: Like many other medical technologies and treatments, there is a lack of reliable evidence on treatment effectiveness of mental health care. Increasingly, data from non-experimental settings are being used to study the effect of treatment. However, as in a number of studies using non-experimental data, a simple regression of outcome on treatment shows a puzzling negative and significant impact of mental health care on the improvement of mental health status, even after including a large number of potential control variables. The central problem in interpreting evidence from real-world or non-experimental settings is, therefore, the potential "selection bias" problem in observational data set. In other words, the choice/quantity of mental health care may be correlated with other variables, particularly unobserved variables, that influence outcome and this may lead to a bias in the estimate of the effect of care in conventional models. AIMS OF THE STUDY: This paper addresses the issue of estimating treatment effects using an observational data set. The information in a mental health data set obtained from two waves of data in Puerto Rico is explored. The results using conventional models - in which the potential selection bias is not controlled - and that from instrumental variable (IV) models - which is what was proposed in this study to correct for the contaminated estimation from conventional models - are compared. METHODS: Treatment effectiveness is estimated in a production function framework. Effectiveness is measured as the improvement in mental health status. To control for the potential selection bias problem, IV approaches are employed. The essence of the IV method is to use one or more instruments, which are observable factors that influence treatment but do not directly affect patient outcomes, to isolate the effect of treatment variation that is independent of unobserved patient characteristics. The data used in this study are the first (1992
Kowalski, Amanda
2016-01-02
Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member's injury to induce variation in an individual's own price. Across the conditional deciles of the expenditure distribution, I find elasticities that vary from -0.76 to -1.49, which are an order of magnitude larger than previous estimates.
Optimal Inference for Instrumental Variables Regression with non-Gaussian Errors
DEFF Research Database (Denmark)
Cattaneo, Matias D.; Crump, Richard K.; Jansson, Michael
This paper is concerned with inference on the coefficient on the endogenous regressor in a linear instrumental variables model with a single endogenous regressor, nonrandom exogenous regressors and instruments, and i.i.d. errors whose distribution is unknown. It is shown that under mild smoothness...
Instrument Variables for Reducing Noise in Parallel MRI Reconstruction
Directory of Open Access Journals (Sweden)
Yuchou Chang
2017-01-01
Full Text Available Generalized autocalibrating partially parallel acquisition (GRAPPA has been a widely used parallel MRI technique. However, noise deteriorates the reconstructed image when reduction factor increases or even at low reduction factor for some noisy datasets. Noise, initially generated from scanner, propagates noise-related errors during fitting and interpolation procedures of GRAPPA to distort the final reconstructed image quality. The basic idea we proposed to improve GRAPPA is to remove noise from a system identification perspective. In this paper, we first analyze the GRAPPA noise problem from a noisy input-output system perspective; then, a new framework based on errors-in-variables (EIV model is developed for analyzing noise generation mechanism in GRAPPA and designing a concrete method—instrument variables (IV GRAPPA to remove noise. The proposed EIV framework provides possibilities that noiseless GRAPPA reconstruction could be achieved by existing methods that solve EIV problem other than IV method. Experimental results show that the proposed reconstruction algorithm can better remove the noise compared to the conventional GRAPPA, as validated with both of phantom and in vivo brain data.
Variable importance in latent variable regression models
Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.
2014-01-01
The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable
Instrumental variable estimation of treatment effects for duration outcomes
G.E. Bijwaard (Govert)
2007-01-01
textabstractIn this article we propose and implement an instrumental variable estimation procedure to obtain treatment effects on duration outcomes. The method can handle the typical complications that arise with duration data of time-varying treatment and censoring. The treatment effect we
Sensitivity analysis and power for instrumental variable studies.
Wang, Xuran; Jiang, Yang; Zhang, Nancy R; Small, Dylan S
2018-03-31
In observational studies to estimate treatment effects, unmeasured confounding is often a concern. The instrumental variable (IV) method can control for unmeasured confounding when there is a valid IV. To be a valid IV, a variable needs to be independent of unmeasured confounders and only affect the outcome through affecting the treatment. When applying the IV method, there is often concern that a putative IV is invalid to some degree. We present an approach to sensitivity analysis for the IV method which examines the sensitivity of inferences to violations of IV validity. Specifically, we consider sensitivity when the magnitude of association between the putative IV and the unmeasured confounders and the direct effect of the IV on the outcome are limited in magnitude by a sensitivity parameter. Our approach is based on extending the Anderson-Rubin test and is valid regardless of the strength of the instrument. A power formula for this sensitivity analysis is presented. We illustrate its usage via examples about Mendelian randomization studies and its implications via a comparison of using rare versus common genetic variants as instruments. © 2018, The International Biometric Society.
Crown, William H
2014-02-01
This paper examines the use of propensity score matching in economic analyses of observational data. Several excellent papers have previously reviewed practical aspects of propensity score estimation and other aspects of the propensity score literature. The purpose of this paper is to compare the conceptual foundation of propensity score models with alternative estimators of treatment effects. References are provided to empirical comparisons among methods that have appeared in the literature. These comparisons are available for a subset of the methods considered in this paper. However, in some cases, no pairwise comparisons of particular methods are yet available, and there are no examples of comparisons across all of the methods surveyed here. Irrespective of the availability of empirical comparisons, the goal of this paper is to provide some intuition about the relative merits of alternative estimators in health economic evaluations where nonlinearity, sample size, availability of pre/post data, heterogeneity, and missing variables can have important implications for choice of methodology. Also considered is the potential combination of propensity score matching with alternative methods such as differences-in-differences and decomposition methods that have not yet appeared in the empirical literature.
Asteroid electrostatic instrumentation and modelling
Energy Technology Data Exchange (ETDEWEB)
Aplin, K L; Bowles, N E; Urbak, E [Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH (United Kingdom); Keane, D; Sawyer, E C, E-mail: k.aplin1@physics.ox.ac.uk [RAL Space, R25, Harwell Oxford, Didcot OX11 0QX (United Kingdom)
2011-06-23
Asteroid surface material is expected to become photoelectrically charged, and is likely to be transported through electrostatic levitation. Understanding any movement of the surface material is relevant to proposed space missions to return samples to Earth for detailed isotopic analysis. Motivated by preparations for the Marco Polo sample return mission, we present electrostatic modelling for a real asteroid, Itokawa, for which detailed shape information is available, and verify that charging effects are likely to be significant at the terminator and at the edges of shadow regions for the Marco Polo baseline asteroid, 1999JU3. We also describe the Asteroid Charge Experiment electric field instrumentation intended for Marco Polo. Finally, we find that the differing asteroid and spacecraft potentials on landing could perturb sample collection for the short landing time of 20min that is currently planned.
International Nuclear Information System (INIS)
Allafi, Walid; Uddin, Kotub; Zhang, Cheng; Mazuir Raja Ahsan Sha, Raja; Marco, James
2017-01-01
Highlights: •Off-line estimation approach for continuous-time domain for non-invertible function. •Model reformulated to multi-input-single-output; nonlinearity described by sigmoid. •Method directly estimates parameters of nonlinear ECM from the measured-data. •Iterative on-line technique leads to smoother convergence. •The model is validated off-line and on-line using NCA battery. -- Abstract: The accuracy of identifying the parameters of models describing lithium ion batteries (LIBs) in typical battery management system (BMS) applications is critical to the estimation of key states such as the state of charge (SoC) and state of health (SoH). In applications such as electric vehicles (EVs) where LIBs are subjected to highly demanding cycles of operation and varying environmental conditions leading to non-trivial interactions of ageing stress factors, this identification is more challenging. This paper proposes an algorithm that directly estimates the parameters of a nonlinear battery model from measured input and output data in the continuous time-domain. The simplified refined instrumental variable method is extended to estimate the parameters of a Wiener model where there is no requirement for the nonlinear function to be invertible. To account for nonlinear battery dynamics, in this paper, the typical linear equivalent circuit model (ECM) is enhanced by a block-oriented Wiener configuration where the nonlinear memoryless block following the typical ECM is defined to be a sigmoid static nonlinearity. The nonlinear Weiner model is reformulated in the form of a multi-input, single-output linear model. This linear form allows the parameters of the nonlinear model to be estimated using any linear estimator such as the well-established least squares (LS) algorithm. In this paper, the recursive least square (RLS) method is adopted for online parameter estimation. The approach was validated on experimental data measured from an 18650-type Graphite
Instrumented Impact Testing: Influence of Machine Variables and Specimen Position
Energy Technology Data Exchange (ETDEWEB)
Lucon, E.; McCowan, C. N.; Santoyo, R. A.
2008-09-15
An investigation has been conducted on the influence of impact machine variables and specimen positioning on characteristic forces and absorbed energies from instrumented Charpy tests. Brittle and ductile fracture behavior has been investigated by testing NIST reference samples of low, high and super-high energy levels. Test machine variables included tightness of foundation, anvil and striker bolts, and the position of the center of percussion with respect to the center of strike. For specimen positioning, we tested samples which had been moved away or sideways with respect to the anvils. In order to assess the influence of the various factors, we compared mean values in the reference (unaltered) and altered conditions; for machine variables, t-test analyses were also performed in order to evaluate the statistical significance of the observed differences. Our results indicate that the only circumstance which resulted in variations larger than 5 percent for both brittle and ductile specimens is when the sample is not in contact with the anvils. These findings should be taken into account in future revisions of instrumented Charpy test standards.
Instrumented Impact Testing: Influence of Machine Variables and Specimen Position
International Nuclear Information System (INIS)
Lucon, E.; McCowan, C. N.; Santoyo, R. A.
2008-01-01
An investigation has been conducted on the influence of impact machine variables and specimen positioning on characteristic forces and absorbed energies from instrumented Charpy tests. Brittle and ductile fracture behavior has been investigated by testing NIST reference samples of low, high and super-high energy levels. Test machine variables included tightness of foundation, anvil and striker bolts, and the position of the center of percussion with respect to the center of strike. For specimen positioning, we tested samples which had been moved away or sideways with respect to the anvils. In order to assess the influence of the various factors, we compared mean values in the reference (unaltered) and altered conditions; for machine variables, t-test analyses were also performed in order to evaluate the statistical significance of the observed differences. Our results indicate that the only circumstance which resulted in variations larger than 5 percent for both brittle and ductile specimens is when the sample is not in contact with the anvils. These findings should be taken into account in future revisions of instrumented Charpy test standards.
Directory of Open Access Journals (Sweden)
Gu NY
2008-12-01
Full Text Available There are limited studies on quantifying the impact of patient satisfaction with pharmacist consultation on patient medication adherence. Objectives: The objective of this study is to evaluate the effect of patient satisfaction with pharmacist consultation services on medication adherence in a large managed care organization. Methods: We analyzed data from a patient satisfaction survey of 6,916 patients who had used pharmacist consultation services in Kaiser Permanente Southern California from 1993 to 1996. We compared treating patient satisfaction as exogenous, in a single-equation probit model, with a bivariate probit model where patient satisfaction was treated as endogenous. Different sets of instrumental variables were employed, including measures of patients' emotional well-being and patients' propensity to fill their prescriptions at a non-Kaiser Permanente (KP pharmacy. The Smith-Blundell test was used to test whether patient satisfaction was endogenous. Over-identification tests were used to test the validity of the instrumental variables. The Staiger-Stock weak instrument test was used to evaluate the explanatory power of the instrumental variables. Results: All tests indicated that the instrumental variables method was valid and the instrumental variables used have significant explanatory power. The single equation probit model indicated that the effect of patient satisfaction with pharmacist consultation was significant (p<0.010. However, the bivariate probit models revealed that the marginal effect of pharmacist consultation on medication adherence was significantly greater than the single equation probit. The effect increased from 7% to 30% (p<0.010 after controlling for endogeneity bias. Conclusion: After appropriate adjustment for endogeneity bias, patients satisfied with their pharmacy services are substantially more likely to adhere to their medication. The results have important policy implications given the increasing focus
Statistical Analysis for Multisite Trials Using Instrumental Variables with Random Coefficients
Raudenbush, Stephen W.; Reardon, Sean F.; Nomi, Takako
2012-01-01
Multisite trials can clarify the average impact of a new program and the heterogeneity of impacts across sites. Unfortunately, in many applications, compliance with treatment assignment is imperfect. For these applications, we propose an instrumental variable (IV) model with person-specific and site-specific random coefficients. Site-specific IV…
Finite-sample instrumental variables inference using an asymptotically pivotal statistic
Bekker, Paul A.; Kleibergen, Frank
2001-01-01
The paper considers the K-statistic, Kleibergen’s (2000) adaptation of the Anderson-Rubin (AR) statistic in instrumental variables regression. Compared to the AR-statistic this K-statistic shows improved asymptotic efficiency in terms of degrees of freedom in overidenti?ed models and yet it shares,
Persson, Eva K; Dykes, Anna-Karin
2009-08-01
to evaluate dimensions of both parents' postnatal sense of security the first week after childbirth, and to determine associations between the PPSS instrument and different sociodemographic and situational background variables. evaluative, cross-sectional design. 113 mothers and 99 fathers with children live born at term, from five hospitals in southern Sweden. mothers and fathers had similar feelings concerning postnatal sense of security. Of the dimensions in the PPSS instrument, a sense of midwives'/nurses' empowering behaviour, a sense of one's own general well-being and a sense of the mother's well-being as experienced by the father were the most important dimensions for parents' experienced security. A sense of affinity within the family (for both parents) and a sense of manageable breast feeding (for mothers) were not significantly associated with their experienced security. A sense of participation during pregnancy and general anxiety were significantly associated background variables for postnatal sense of security for both parents. For the mothers, parity and a sense that the father was participating during pregnancy were also significantly associated. more focus on parents' participation during pregnancy as well as midwives'/nurses' empowering behaviour during the postnatal period will be beneficial for both parents' postnatal sense of security.
Instrumental variables estimates of peer effects in social networks.
An, Weihua
2015-03-01
Estimating peer effects with observational data is very difficult because of contextual confounding, peer selection, simultaneity bias, and measurement error, etc. In this paper, I show that instrumental variables (IVs) can help to address these problems in order to provide causal estimates of peer effects. Based on data collected from over 4000 students in six middle schools in China, I use the IV methods to estimate peer effects on smoking. My design-based IV approach differs from previous ones in that it helps to construct potentially strong IVs and to directly test possible violation of exogeneity of the IVs. I show that measurement error in smoking can lead to both under- and imprecise estimations of peer effects. Based on a refined measure of smoking, I find consistent evidence for peer effects on smoking. If a student's best friend smoked within the past 30 days, the student was about one fifth (as indicated by the OLS estimate) or 40 percentage points (as indicated by the IV estimate) more likely to smoke in the same time period. The findings are robust to a variety of robustness checks. I also show that sharing cigarettes may be a mechanism for peer effects on smoking. A 10% increase in the number of cigarettes smoked by a student's best friend is associated with about 4% increase in the number of cigarettes smoked by the student in the same time period. Copyright © 2014 Elsevier Inc. All rights reserved.
Model SH intelligent instrument for thickness measuring
International Nuclear Information System (INIS)
Liu Juntao; Jia Weizhuang; Zhao Yunlong
1995-01-01
The authors introduce Model SH Intelligent Instrument for thickness measuring by using principle of beta back-scattering and its application range, features, principle of operation, system design, calibration and specifications
Reardon, Sean F.; Unlu, Faith; Zhu, Pei; Bloom, Howard
2013-01-01
We explore the use of instrumental variables (IV) analysis with a multi-site randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, as assumption known in the instrumental variables literature as the…
26 CFR 1.1275-5 - Variable rate debt instruments.
2010-04-01
... nonpublicly traded property. A debt instrument (other than a tax-exempt obligation) that would otherwise... variations in the cost of newly borrowed funds in the currency in which the debt instrument is denominated... on the yield of actively traded personal property (within the meaning of section 1092(d)(1)). (ii...
The contextual effects of social capital on health: a cross-national instrumental variable analysis.
Kim, Daniel; Baum, Christopher F; Ganz, Michael L; Subramanian, S V; Kawachi, Ichiro
2011-12-01
Past research on the associations between area-level/contextual social capital and health has produced conflicting evidence. However, interpreting this rapidly growing literature is difficult because estimates using conventional regression are prone to major sources of bias including residual confounding and reverse causation. Instrumental variable (IV) analysis can reduce such bias. Using data on up to 167,344 adults in 64 nations in the European and World Values Surveys and applying IV and ordinary least squares (OLS) regression, we estimated the contextual effects of country-level social trust on individual self-rated health. We further explored whether these associations varied by gender and individual levels of trust. Using OLS regression, we found higher average country-level trust to be associated with better self-rated health in both women and men. Instrumental variable analysis yielded qualitatively similar results, although the estimates were more than double in size in both sexes when country population density and corruption were used as instruments. The estimated health effects of raising the percentage of a country's population that trusts others by 10 percentage points were at least as large as the estimated health effects of an individual developing trust in others. These findings were robust to alternative model specifications and instruments. Conventional regression and to a lesser extent IV analysis suggested that these associations are more salient in women and in women reporting social trust. In a large cross-national study, our findings, including those using instrumental variables, support the presence of beneficial effects of higher country-level trust on self-rated health. Previous findings for contextual social capital using traditional regression may have underestimated the true associations. Given the close linkages between self-rated health and all-cause mortality, the public health gains from raising social capital within and across
Robust best linear estimation for regression analysis using surrogate and instrumental variables.
Wang, C Y
2012-04-01
We investigate methods for regression analysis when covariates are measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies the classical measurement error model, but it may not have repeated measurements. In addition to the surrogate variables that are available among the subjects in the calibration sample, we assume that there is an instrumental variable (IV) that is available for all study subjects. An IV is correlated with the unobserved true exposure variable and hence can be useful in the estimation of the regression coefficients. We propose a robust best linear estimator that uses all the available data, which is the most efficient among a class of consistent estimators. The proposed estimator is shown to be consistent and asymptotically normal under very weak distributional assumptions. For Poisson or linear regression, the proposed estimator is consistent even if the measurement error from the surrogate or IV is heteroscedastic. Finite-sample performance of the proposed estimator is examined and compared with other estimators via intensive simulation studies. The proposed method and other methods are applied to a bladder cancer case-control study.
Discrete-time modelling of musical instruments
International Nuclear Information System (INIS)
Vaelimaeki, Vesa; Pakarinen, Jyri; Erkut, Cumhur; Karjalainen, Matti
2006-01-01
This article describes physical modelling techniques that can be used for simulating musical instruments. The methods are closely related to digital signal processing. They discretize the system with respect to time, because the aim is to run the simulation using a computer. The physics-based modelling methods can be classified as mass-spring, modal, wave digital, finite difference, digital waveguide and source-filter models. We present the basic theory and a discussion on possible extensions for each modelling technique. For some methods, a simple model example is chosen from the existing literature demonstrating a typical use of the method. For instance, in the case of the digital waveguide modelling technique a vibrating string model is discussed, and in the case of the wave digital filter technique we present a classical piano hammer model. We tackle some nonlinear and time-varying models and include new results on the digital waveguide modelling of a nonlinear string. Current trends and future directions in physical modelling of musical instruments are discussed
Variable-Structure Control of a Model Glider Airplane
Waszak, Martin R.; Anderson, Mark R.
2008-01-01
A variable-structure control system designed to enable a fuselage-heavy airplane to recover from spin has been demonstrated in a hand-launched, instrumented model glider airplane. Variable-structure control is a high-speed switching feedback control technique that has been developed for control of nonlinear dynamic systems.
Modelling the liquidity ratio as macroprudential instrument
Jan Willem van den End; Mark Kruidhof
2012-01-01
The Basel III Liquidity Coverage Ratio (LCR) is a microprudential instrument to strengthen the liquidity position of banks. However, if in extreme scenarios the LCR becomes a binding constraint, the interaction of bank behaviour with the regulatory rule can have negative externalities. We simulate the systemic implications of the LCR by a liquidity stress-testing model, which takes into account the impact of bank reactions on second round feedback effects. We show that a flexible approach of ...
Linear latent variable models: the lava-package
DEFF Research Database (Denmark)
Holst, Klaus Kähler; Budtz-Jørgensen, Esben
2013-01-01
are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation......An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...
Swanson, Sonja A; Labrecque, Jeremy; Hernán, Miguel A
2018-05-02
Sometimes instrumental variable methods are used to test whether a causal effect is null rather than to estimate the magnitude of a causal effect. However, when instrumental variable methods are applied to time-varying exposures, as in many Mendelian randomization studies, it is unclear what causal null hypothesis is tested. Here, we consider different versions of causal null hypotheses for time-varying exposures, show that the instrumental variable conditions alone are insufficient to test some of them, and describe additional assumptions that can be made to test a wider range of causal null hypotheses, including both sharp and average causal null hypotheses. Implications for interpretation and reporting of instrumental variable results are discussed.
Error-in-variables models in calibration
Lira, I.; Grientschnig, D.
2017-12-01
In many calibration operations, the stimuli applied to the measuring system or instrument under test are derived from measurement standards whose values may be considered to be perfectly known. In that case, it is assumed that calibration uncertainty arises solely from inexact measurement of the responses, from imperfect control of the calibration process and from the possible inaccuracy of the calibration model. However, the premise that the stimuli are completely known is never strictly fulfilled and in some instances it may be grossly inadequate. Then, error-in-variables (EIV) regression models have to be employed. In metrology, these models have been approached mostly from the frequentist perspective. In contrast, not much guidance is available on their Bayesian analysis. In this paper, we first present a brief summary of the conventional statistical techniques that have been developed to deal with EIV models in calibration. We then proceed to discuss the alternative Bayesian framework under some simplifying assumptions. Through a detailed example about the calibration of an instrument for measuring flow rates, we provide advice on how the user of the calibration function should employ the latter framework for inferring the stimulus acting on the calibrated device when, in use, a certain response is measured.
NASA Instrument Cost/Schedule Model
Habib-Agahi, Hamid; Mrozinski, Joe; Fox, George
2011-01-01
NASA's Office of Independent Program and Cost Evaluation (IPCE) has established a number of initiatives to improve its cost and schedule estimating capabilities. 12One of these initiatives has resulted in the JPL developed NASA Instrument Cost Model. NICM is a cost and schedule estimator that contains: A system level cost estimation tool; a subsystem level cost estimation tool; a database of cost and technical parameters of over 140 previously flown remote sensing and in-situ instruments; a schedule estimator; a set of rules to estimate cost and schedule by life cycle phases (B/C/D); and a novel tool for developing joint probability distributions for cost and schedule risk (Joint Confidence Level (JCL)). This paper describes the development and use of NICM, including the data normalization processes, data mining methods (cluster analysis, principal components analysis, regression analysis and bootstrap cross validation), the estimating equations themselves and a demonstration of the NICM tool suite.
Reardon, Sean F.; Unlu, Fatih; Zhu, Pei; Bloom, Howard S.
2014-01-01
We explore the use of instrumental variables (IV) analysis with a multisite randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, an assumption known in the IV literature as the exclusion restriction.…
DEFF Research Database (Denmark)
Burgess, Stephen; Thompson, Simon G; Thompson, Grahame
2010-01-01
Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context o...
STAMINA - Model description. Standard Model Instrumentation for Noise Assessments
Schreurs EM; Jabben J; Verheijen ENG; CMM; mev
2010-01-01
Deze rapportage beschrijft het STAMINA-model, dat staat voor Standard Model Instrumentation for Noise Assessments en door het RIVM is ontwikkeld. Het instituut gebruikt dit standaardmodel om omgevingsgeluid in Nederland in kaart te brengen. Het model is gebaseerd op de Standaard Karteringsmethode
International Nuclear Information System (INIS)
Umminger, K.
2008-01-01
A proper measurement of the relevant single and two-phase flow parameters is the basis for the understanding of many complex thermal-hydraulic processes. Reliable instrumentation is therefore necessary for the interaction between analysis and experiment especially in the field of nuclear safety research where postulated accident scenarios have to be simulated in experimental facilities and predicted by complex computer code systems. The so-called conventional instrumentation for the measurement of e. g. pressures, temperatures, pressure differences and single phase flow velocities is still a solid basis for the investigation and interpretation of many phenomena and especially for the understanding of the overall system behavior. Measurement data from such instrumentation still serves in many cases as a database for thermal-hydraulic system codes. However some special instrumentation such as online concentration measurement for boric acid in the water phase or for non-condensibles in steam atmosphere as well as flow visualization techniques were further developed and successfully applied during the recent years. Concerning the modeling needs for advanced thermal-hydraulic codes, significant advances have been accomplished in the last few years in the local instrumentation technology for two-phase flow by the application of new sensor techniques, optical or beam methods and electronic technology. This paper will give insight into the current state of instrumentation technology for safety-related thermohydraulic experiments. Advantages and limitations of some measurement processes and systems will be indicated as well as trends and possibilities for further development. Aspects of instrumentation in operating reactors will also be mentioned.
Fletcher, Jason M
2015-07-01
This paper provides some of the first evidence of peer effects in college enrollment decisions. There are several empirical challenges in assessing the influences of peers in this context, including the endogeneity of high school, shared group-level unobservables, and identifying policy-relevant parameters of social interactions models. This paper addresses these issues by using an instrumental variables/fixed effects approach that compares students in the same school but different grade-levels who are thus exposed to different sets of classmates. In particular, plausibly exogenous variation in peers' parents' college expectations are used as an instrument for peers' college choices. Preferred specifications indicate that increasing a student's exposure to college-going peers by ten percentage points is predicted to raise the student's probability of enrolling in college by 4 percentage points. This effect is roughly half the magnitude of growing up in a household with married parents (vs. an unmarried household). Copyright © 2015 Elsevier Inc. All rights reserved.
Psyche Mission: Scientific Models and Instrument Selection
Polanskey, C. A.; Elkins-Tanton, L. T.; Bell, J. F., III; Lawrence, D. J.; Marchi, S.; Park, R. S.; Russell, C. T.; Weiss, B. P.
2017-12-01
NASA has chosen to explore (16) Psyche with their 14th Discovery-class mission. Psyche is a 226-km diameter metallic asteroid hypothesized to be the exposed core of a planetesimal that was stripped of its rocky mantle by multiple hit and run collisions in the early solar system. The spacecraft launch is planned for 2022 with arrival at the asteroid in 2026 for 21 months of operations. The Psyche investigation has five primary scientific objectives: A. Determine whether Psyche is a core, or if it is unmelted material. B. Determine the relative ages of regions of Psyche's surface. C. Determine whether small metal bodies incorporate the same light elements as are expected in the Earth's high-pressure core. D. Determine whether Psyche was formed under conditions more oxidizing or more reducing than Earth's core. E. Characterize Psyche's topography. The mission's task was to select the appropriate instruments to meet these objectives. However, exploring a metal world, rather than one made of ice, rock, or gas, requires development of new scientific models for Psyche to support the selection of the appropriate instruments for the payload. If Psyche is indeed a planetary core, we expect that it should have a detectable magnetic field. However, the strength of the magnetic field can vary by orders of magnitude depending on the formational history of Psyche. The implications of both the extreme low-end and the high-end predictions impact the magnetometer and mission design. For the imaging experiment, what can the team expect for the morphology of a heavily impacted metal body? Efforts are underway to further investigate the differences in crater morphology between high velocity impacts into metal and rock to be prepared to interpret the images of Psyche when they are returned. Finally, elemental composition measurements at Psyche using nuclear spectroscopy encompass a new and unexplored phase space of gamma-ray and neutron measurements. We will present some end
Finite-sample instrumental variables inference using an asymptotically pivotal statistic
Bekker, P; Kleibergen, F
2003-01-01
We consider the K-statistic, Kleibergen's (2002, Econometrica 70, 1781-1803) adaptation of the Anderson-Rubin (AR) statistic in instrumental variables regression. Whereas Kleibergen (2002) especially analyzes the asymptotic behavior of the statistic, we focus on finite-sample properties in, a
Finite-sample instrumental variables Inference using an Asymptotically Pivotal Statistic
Bekker, P.; Kleibergen, F.R.
2001-01-01
The paper considers the K-statistic, Kleibergen’s (2000) adaptation ofthe Anderson-Rubin (AR) statistic in instrumental variables regression.Compared to the AR-statistic this K-statistic shows improvedasymptotic efficiency in terms of degrees of freedom in overidentifiedmodels and yet it shares,
Modeling the Variable Heliopause Location
Hensley, Kerry
2018-03-01
In 2012, Voyager 1 zipped across the heliopause. Five and a half years later, Voyager 2 still hasnt followed its twin into interstellar space. Can models of the heliopause location help determine why?How Far to the Heliopause?Artists conception of the heliosphere with the important structures and boundaries labeled. [NASA/Goddard/Walt Feimer]As our solar system travels through the galaxy, the solar outflow pushes against the surrounding interstellar medium, forming a bubble called the heliosphere. The edge of this bubble, the heliopause, is the outermost boundary of our solar system, where the solar wind and the interstellar medium meet. Since the solar outflow is highly variable, the heliopause is constantly moving with the motion driven by changes inthe Sun.NASAs twin Voyager spacecraft were poisedto cross the heliopause after completingtheir tour of the outer planets in the 1980s. In 2012, Voyager 1 registered a sharp increase in the density of interstellar particles, indicating that the spacecraft had passed out of the heliosphere and into the interstellar medium. The slower-moving Voyager 2 was set to pierce the heliopause along a different trajectory, but so far no measurements have shown that the spacecraft has bid farewell to oursolar system.In a recent study, ateam of scientists led by Haruichi Washimi (Kyushu University, Japan and CSPAR, University of Alabama-Huntsville) argues that models of the heliosphere can help explain this behavior. Because the heliopause location is controlled by factors that vary on many spatial and temporal scales, Washimiand collaborators turn to three-dimensional, time-dependent magnetohydrodynamics simulations of the heliosphere. In particular, they investigate how the position of the heliopause along the trajectories of Voyager 1 and Voyager 2 changes over time.Modeled location of the heliopause along the paths of Voyagers 1 (blue) and 2 (orange). Click for a closer look. The red star indicates the location at which Voyager
Evaluation of multivariate calibration models transferred between spectroscopic instruments
DEFF Research Database (Denmark)
Eskildsen, Carl Emil Aae; Hansen, Per W.; Skov, Thomas
2016-01-01
In a setting where multiple spectroscopic instruments are used for the same measurements it may be convenient to develop the calibration model on a single instrument and then transfer this model to the other instruments. In the ideal scenario, all instruments provide the same predictions for the ......In a setting where multiple spectroscopic instruments are used for the same measurements it may be convenient to develop the calibration model on a single instrument and then transfer this model to the other instruments. In the ideal scenario, all instruments provide the same predictions...... for the same samples using the transferred model. However, sometimes the success of a model transfer is evaluated by comparing the transferred model predictions with the reference values. This is not optimal, as uncertainties in the reference method will impact the evaluation. This paper proposes a new method...... for calibration model transfer evaluation. The new method is based on comparing predictions from different instruments, rather than comparing predictions and reference values. A total of 75 flour samples were available for the study. All samples were measured on ten near infrared (NIR) instruments from two...
Handbook of latent variable and related models
Lee, Sik-Yum
2011-01-01
This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.- Covers a wide class of important models- Models and statistical methods described provide tools for analyzing a wide spectrum of complicated data- Includes illustrative examples with real data sets from business, education, medicine, public health and sociology.- Demonstrates the use of a wide variety of statistical, computational, and mathematical techniques.
Energy Technology Data Exchange (ETDEWEB)
Miller, N. J.; Marriage, T. A.; Appel, J. W.; Bennett, C. L.; Eimer, J.; Essinger-Hileman, T.; Harrington, K.; Rostem, K.; Watts, D. J. [Department of Physics and Astronomy, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218 (United States); Chuss, D. T. [Department of Physics, Villanova University, 800 E Lancaster, Villanova, PA 19085 (United States); Wollack, E. J.; Fixsen, D. J.; Moseley, S. H.; Switzer, E. R., E-mail: Nathan.J.Miller@nasa.gov [Observational Cosmology Laboratory, Code 665, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)
2016-02-20
Variable-delay Polarization Modulators (VPMs) are currently being implemented in experiments designed to measure the polarization of the cosmic microwave background on large angular scales because of their capability for providing rapid, front-end polarization modulation and control over systematic errors. Despite the advantages provided by the VPM, it is important to identify and mitigate any time-varying effects that leak into the synchronously modulated component of the signal. In this paper, the effect of emission from a 300 K VPM on the system performance is considered and addressed. Though instrument design can greatly reduce the influence of modulated VPM emission, some residual modulated signal is expected. VPM emission is treated in the presence of rotational misalignments and temperature variation. Simulations of time-ordered data are used to evaluate the effect of these residual errors on the power spectrum. The analysis and modeling in this paper guides experimentalists on the critical aspects of observations using VPMs as front-end modulators. By implementing the characterizations and controls as described, front-end VPM modulation can be very powerful for mitigating 1/f noise in large angular scale polarimetric surveys. None of the systematic errors studied fundamentally limit the detection and characterization of B-modes on large scales for a tensor-to-scalar ratio of r = 0.01. Indeed, r < 0.01 is achievable with commensurately improved characterizations and controls.
The dynamic model of choosing an external funding instrument
Directory of Open Access Journals (Sweden)
Irena HONKOVA
2015-06-01
Full Text Available Making a decision about using a specific funding source is one of the most important tasks of financial management. The utilization of external sources features numerous advantages yet staying aware of diverse funding options is not easy for financial managers. Today it is crucial to quickly identify an optimum possibility and to make sure that all relevant criteria have been considered and no variant has been omitted. Over the long term it is also necessary to consider the category of time as changes made today do not affect only the current variables but they also have a significant impact on the future. This article aims to identify the most suitable model of choosing external funding sources that would describe the dynamics involved. The first part of the paper considers the theoretical background of external funding instrument and of decision criteria. The making of financial decisions is a process consisted of weighing the most suitable variants, selecting the best variant, and controlling the implementation of accepted proposals. The second part analyses results of the research - decisive weights of the criteria. Then it is created the model of the principal criteria Weighted Average Cost of Capital (Dynamic model WACC. Finally it is created the Dynamic Model of Choosing an External Funding Instrument. The created decision-making model facilitates the modeling of changes in time because it is crucial to know what future consequences lies in decisions made the contemporary turbulent world. Each variant features possible negative and positive changes of varying extent. The possibility to simulate these changes can illustrate an optimal variant to a decision-maker.
Generalized latent variable modeling multilevel, longitudinal, and structural equation models
Skrondal, Anders; Rabe-Hesketh, Sophia
2004-01-01
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models.
Institution, Financial Sector, and Economic Growth: Use The Institutions As An Instrument Variable
Albertus Girik Allo
2016-01-01
Institution has been investigated having indirect role on economic growth. This paper aims to evaluate whether the quality of institution matters for economic growth. By applying institution as instrumental variable at Foreign Direct Investment (FDI), quality of institution significantly influence economic growth. This study applies two set of data period, namely 1985-2013 and 2000-2013, available online in the World Bank (WB). The first data set, 1985-2013 is used to estimate the role of fin...
A Core Language for Separate Variability Modeling
DEFF Research Database (Denmark)
Iosif-Lazăr, Alexandru Florin; Wasowski, Andrzej; Schaefer, Ina
2014-01-01
Separate variability modeling adds variability to a modeling language without requiring modifications of the language or the supporting tools. We define a core language for separate variability modeling using a single kind of variation point to define transformations of software artifacts in object...... hierarchical dependencies between variation points via copying and flattening. Thus, we reduce a model with intricate dependencies to a flat executable model transformation consisting of simple unconditional local variation points. The core semantics is extremely concise: it boils down to two operational rules...
The XRF spectrometer and the selection of analysis conditions (instrumental variables)
International Nuclear Information System (INIS)
Willis, J.P.
2002-01-01
Full text: This presentation will begin with a brief discussion of EDXRF and flat- and curved-crystal WDXRF spectrometers, contrasting the major differences between the three types. The remainder of the presentation will contain a detailed overview of the choice and settings of the many instrumental variables contained in a modern WDXRF spectrometer, and will discuss critically the choices facing the analyst in setting up a WDXRF spectrometer for different elements and applications. In particular it will discuss the choice of tube target (when a choice is possible), the kV and mA settings, tube filters, collimator masks, collimators, analyzing crystals, secondary collimators, detectors, pulse height selection, X-ray path medium (air, nitrogen, vacuum or helium), counting times for peak and background positions and their effect on counting statistics and lower limit of detection (LLD). The use of Figure of Merit (FOM) calculations to objectively choose the best combination of instrumental variables also will be discussed. This presentation will be followed by a shorter session on a subsequent day entitled - A Selection of XRF Conditions - Practical Session, where participants will be given the opportunity to discuss in groups the selection of the best instrumental variables for three very diverse applications. Copyright (2002) Australian X-ray Analytical Association Inc
Latent variable models are network models.
Molenaar, Peter C M
2010-06-01
Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.
Latest NASA Instrument Cost Model (NICM): Version VI
Mrozinski, Joe; Habib-Agahi, Hamid; Fox, George; Ball, Gary
2014-01-01
The NASA Instrument Cost Model, NICM, is a suite of tools which allow for probabilistic cost estimation of NASA's space-flight instruments at both the system and subsystem level. NICM also includes the ability to perform cost by analogy as well as joint confidence level (JCL) analysis. The latest version of NICM, Version VI, was released in Spring 2014. This paper will focus on the new features released with NICM VI, which include: 1) The NICM-E cost estimating relationship, which is applicable for instruments flying on Explorer-like class missions; 2) The new cluster analysis ability which, alongside the results of the parametric cost estimation for the user's instrument, also provides a visualization of the user's instrument's similarity to previously flown instruments; and 3) includes new cost estimating relationships for in-situ instruments.
International Nuclear Information System (INIS)
Prieur, G.; Nadi, M.; Hedjiedj, A.; Weber, S.
1995-01-01
This second chapter on instrumentation gives little general consideration on history and classification of instrumentation, and two specific states of the art. The first one concerns NMR (block diagram of instrumentation chain with details on the magnets, gradients, probes, reception unit). The first one concerns precision instrumentation (optical fiber gyro-meter and scanning electron microscope), and its data processing tools (programmability, VXI standard and its history). The chapter ends with future trends on smart sensors and Field Emission Displays. (D.L.). Refs., figs
International Nuclear Information System (INIS)
Decreton, M.
2000-01-01
SCK-CEN's research and development programme on instrumentation aims at evaluating the potentials of new instrumentation technologies under the severe constraints of a nuclear application. It focuses on the tolerance of sensors to high radiation doses, including optical fibre sensors, and on the related intelligent data processing needed to cope with the nuclear constraints. Main achievements in these domains in 1999 are summarised
Energy Technology Data Exchange (ETDEWEB)
Decreton, M
2001-04-01
SCK-CEN's research and development programme on instrumentation involves the assessment and the development of sensitive measurement systems used within a radiation environment. Particular emphasis is on the assessment of optical fibre components and their adaptability to radiation environments. The evaluation of ageing processes of instrumentation in fission plants, the development of specific data evaluation strategies to compensate for ageing induced degradation of sensors and cable performance form part of these activities. In 2000, particular emphasis was on in-core reactor instrumentation applied to fusion, accelerator driven and water-cooled fission reactors. This involved the development of high performance instrumentation for irradiation experiments in the BR2 reactor in support of new instrumentation needs for MYRRHA, and for diagnostic systems for the ITER reactor.
International Nuclear Information System (INIS)
Decreton, M.
2001-01-01
SCK-CEN's research and development programme on instrumentation involves the assessment and the development of sensitive measurement systems used within a radiation environment. Particular emphasis is on the assessment of optical fibre components and their adaptability to radiation environments. The evaluation of ageing processes of instrumentation in fission plants, the development of specific data evaluation strategies to compensate for ageing induced degradation of sensors and cable performance form part of these activities. In 2000, particular emphasis was on in-core reactor instrumentation applied to fusion, accelerator driven and water-cooled fission reactors. This involved the development of high performance instrumentation for irradiation experiments in the BR2 reactor in support of new instrumentation needs for MYRRHA, and for diagnostic systems for the ITER reactor
LARF: Instrumental Variable Estimation of Causal Effects through Local Average Response Functions
Directory of Open Access Journals (Sweden)
Weihua An
2016-07-01
Full Text Available LARF is an R package that provides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument (i.e., the treatment inducement are binary. The method (Abadie 2003 involves two steps. First, pseudo-weights are constructed from the probability of receiving the treatment inducement. By default LARF estimates the probability by a probit regression. It also provides semiparametric power series estimation of the probability and allows users to employ other external methods to estimate the probability. Second, the pseudo-weights are used to estimate the local average response function conditional on treatment and covariates. LARF provides both least squares and maximum likelihood estimates of the conditional treatment effects.
The Effect of Birth Weight on Academic Performance: Instrumental Variable Analysis.
Lin, Shi Lin; Leung, Gabriel Matthew; Schooling, C Mary
2017-05-01
Observationally, lower birth weight is usually associated with poorer academic performance; whether this association is causal or the result of confounding is unknown. To investigate this question, we obtained an effect estimate, which can have a causal interpretation under specific assumptions, of birth weight on educational attainment using instrumental variable analysis based on single nucleotide polymorphisms determining birth weight combined with results from the Social Science Genetic Association Consortium study of 126,559 Caucasians. We similarly obtained an estimate of the effect of birth weight on academic performance in 4,067 adolescents from Hong Kong's (Chinese) Children of 1997 birth cohort (1997-2016), using twin status as an instrumental variable. Birth weight was not associated with years of schooling (per 100-g increase in birth weight, -0.006 years, 95% confidence interval (CI): -0.02, 0.01) or college completion (odds ratio = 1.00, 95% CI: 0.96, 1.03). Birth weight was also unrelated to academic performance in adolescents (per 100-g increase in birth weight, -0.004 grade, 95% CI: -0.04, 0.04) using instrumental variable analysis, although conventional regression gave a small positive association (0.02 higher grade, 95% CI: 0.01, 0.03). Observed associations of birth weight with academic performance may not be causal, suggesting that interventions should focus on the contextual factors generating this correlation. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
International Nuclear Information System (INIS)
Decreton, M.
2002-01-01
SCK-CEN's R and D programme on instrumentation involves the development of advanced instrumentation systems for nuclear applications as well as the assessment of the performance of these instruments in a radiation environment. Particular emphasis is on the use of optical fibres as umbilincal links of a remote handling unit for use during maintanance of a fusion reacor, studies on the radiation hardening of plasma diagnostic systems; investigations on new instrumentation for the future MYRRHA accelerator driven system; space applications related to radiation-hardened lenses; the development of new approaches for dose, temperature and strain measurements; the assessment of radiation-hardened sensors and motors for remote handling tasks and studies of dose measurement systems including the use of optical fibres. Progress and achievements in these areas for 2001 are described
Energy Technology Data Exchange (ETDEWEB)
Decreton, M
2002-04-01
SCK-CEN's R and D programme on instrumentation involves the development of advanced instrumentation systems for nuclear applications as well as the assessment of the performance of these instruments in a radiation environment. Particular emphasis is on the use of optical fibres as umbilincal links of a remote handling unit for use during maintanance of a fusion reacor, studies on the radiation hardening of plasma diagnostic systems; investigations on new instrumentation for the future MYRRHA accelerator driven system; space applications related to radiation-hardened lenses; the development of new approaches for dose, temperature and strain measurements; the assessment of radiation-hardened sensors and motors for remote handling tasks and studies of dose measurement systems including the use of optical fibres. Progress and achievements in these areas for 2001 are described.
Energy Technology Data Exchange (ETDEWEB)
Decreton, M
2000-07-01
SCK-CEN's research and development programme on instrumentation aims at evaluating the potentials of new instrumentation technologies under the severe constraints of a nuclear application. It focuses on the tolerance of sensors to high radiation doses, including optical fibre sensors, and on the related intelligent data processing needed to cope with the nuclear constraints. Main achievements in these domains in 1999 are summarised.
Pinna Model for Hearing Instrument Applications
DEFF Research Database (Denmark)
Kammersgaard, Nikolaj Peter Iversen; Kvist, Søren Helstrup; Thaysen, Jesper
2014-01-01
A novel model of the pinna (outer ear) is presented. This is to increase the understanding of the effect of the pinna on the on-body radiation pattern of an antenna placed inside the ear. Simulations of the model and of a realistically shaped ear are compared to validate the model. The radiation...
Eutrophication Modeling Using Variable Chlorophyll Approach
International Nuclear Information System (INIS)
Abdolabadi, H.; Sarang, A.; Ardestani, M.; Mahjoobi, E.
2016-01-01
In this study, eutrophication was investigated in Lake Ontario to identify the interactions among effective drivers. The complexity of such phenomenon was modeled using a system dynamics approach based on a consideration of constant and variable stoichiometric ratios. The system dynamics approach is a powerful tool for developing object-oriented models to simulate complex phenomena that involve feedback effects. Utilizing stoichiometric ratios is a method for converting the concentrations of state variables. During the physical segmentation of the model, Lake Ontario was divided into two layers, i.e., the epilimnion and hypolimnion, and differential equations were developed for each layer. The model structure included 16 state variables related to phytoplankton, herbivorous zooplankton, carnivorous zooplankton, ammonium, nitrate, dissolved phosphorus, and particulate and dissolved carbon in the epilimnion and hypolimnion during a time horizon of one year. The results of several tests to verify the model, close to 1 Nash-Sutcliff coefficient (0.98), the data correlation coefficient (0.98), and lower standard errors (0.96), have indicated well-suited model’s efficiency. The results revealed that there were significant differences in the concentrations of the state variables in constant and variable stoichiometry simulations. Consequently, the consideration of variable stoichiometric ratios in algae and nutrient concentration simulations may be applied in future modeling studies to enhance the accuracy of the results and reduce the likelihood of inefficient control policies.
Brown, C.; Carriquiry, M.; Souza Filho, F. A.
2006-12-01
Hydroclimatological variability presents acute challenges to urban water supply providers. The impact is often most severe in developing nations where hydrologic and climate variability can be very high, water demand is unmet and increasing, and the financial resources to mitigate the social effects of that variability are limited. Furthermore, existing urban water systems face a reduced solution space, constrained by competing and conflicting interests, such as irrigation demand, recreation and hydropower production, and new (relative to system design) demands to satisfy environmental flow requirements. These constraints magnify the impacts of hydroclimatic variability and increase the vulnerability of urban areas to climate change. The high economic and social costs of structural responses to hydrologic variability, such as groundwater utilization and the construction or expansion of dams, create a need for innovative alternatives. Advances in hydrologic and climate forecasting, and the increasing sophistication and acceptance of incentive-based mechanisms for achieving economically efficient water allocation offer potential for improving the resilience of existing water systems to the challenge of variable supply. This presentation will explore the performance of a system of climate informed economic instruments designed to facilitate the reduction of hydroclimatologic variability-induced impacts on water-sensitive stakeholders. The system is comprised of bulk water option contracts between urban water suppliers and agricultural users and insurance indexed on reservoir inflows designed to cover the financial needs of the water supplier in situations where the option is likely to be exercised. Contract and insurance parameters are linked to forecasts and the evolution of seasonal precipitation and streamflow and designed for financial and political viability. A simulation of system performance is presented based on ongoing work in Metro Manila, Philippines. The
Institution, Financial Sector, and Economic Growth: Use The Institutions As An Instrument Variable
Directory of Open Access Journals (Sweden)
Albertus Girik Allo
2016-06-01
Full Text Available Institution has been investigated having indirect role on economic growth. This paper aims to evaluate whether the quality of institution matters for economic growth. By applying institution as instrumental variable at Foreign Direct Investment (FDI, quality of institution significantly influence economic growth. This study applies two set of data period, namely 1985-2013 and 2000-2013, available online in the World Bank (WB. The first data set, 1985-2013 is used to estimate the role of financial sector on economic growth, focuses on 67 countries. The second data set, 2000-2013 determine the role of institution on financial sector and economic growth by applying 2SLS estimation method. We define institutional variables as set of indicators: Control of Corruption, Political Stability and Absence of Violence, and Voice and Accountability provide declining impact of FDI to economic growth.
Galactic models with variable spiral structure
International Nuclear Information System (INIS)
James, R.A.; Sellwood, J.A.
1978-01-01
A series of three-dimensional computer simulations of disc galaxies has been run in which the self-consistent potential of the disc stars is supplemented by that arising from a small uniform Population II sphere. The models show variable spiral structure, which is more pronounced for thin discs. In addition, the thin discs form weak bars. In one case variable spiral structure associated with this bar has been seen. The relaxed discs are cool outside resonance regions. (author)
International Nuclear Information System (INIS)
Buehrer, W.
1996-01-01
The present paper mediates a basic knowledge of the most commonly used experimental techniques. We discuss the principles and concepts necessary to understand what one is doing if one performs an experiment on a certain instrument. (author) 29 figs., 1 tab., refs
Gait variability: methods, modeling and meaning
Directory of Open Access Journals (Sweden)
Hausdorff Jeffrey M
2005-07-01
Full Text Available Abstract The study of gait variability, the stride-to-stride fluctuations in walking, offers a complementary way of quantifying locomotion and its changes with aging and disease as well as a means of monitoring the effects of therapeutic interventions and rehabilitation. Previous work has suggested that measures of gait variability may be more closely related to falls, a serious consequence of many gait disorders, than are measures based on the mean values of other walking parameters. The Current JNER series presents nine reports on the results of recent investigations into gait variability. One novel method for collecting unconstrained, ambulatory data is reviewed, and a primer on analysis methods is presented along with a heuristic approach to summarizing variability measures. In addition, the first studies of gait variability in animal models of neurodegenerative disease are described, as is a mathematical model of human walking that characterizes certain complex (multifractal features of the motor control's pattern generator. Another investigation demonstrates that, whereas both healthy older controls and patients with a higher-level gait disorder walk more slowly in reduced lighting, only the latter's stride variability increases. Studies of the effects of dual tasks suggest that the regulation of the stride-to-stride fluctuations in stride width and stride time may be influenced by attention loading and may require cognitive input. Finally, a report of gait variability in over 500 subjects, probably the largest study of this kind, suggests how step width variability may relate to fall risk. Together, these studies provide new insights into the factors that regulate the stride-to-stride fluctuations in walking and pave the way for expanded research into the control of gait and the practical application of measures of gait variability in the clinical setting.
Gaussian Mixture Model of Heart Rate Variability
Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario
2012-01-01
Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386
International Nuclear Information System (INIS)
Muehllehner, G.; Colsher, J.G.
1982-01-01
This chapter reviews the parameters which are important to positron-imaging instruments. It summarizes the options which various groups have explored in designing tomographs and the methods which have been developed to overcome some of the limitations inherent in the technique as well as in present instruments. The chapter is not presented as a defense of positron imaging versus single-photon or other imaging modality, neither does it contain a description of various existing instruments, but rather stresses their common properties and problems. Design parameters which are considered are resolution, sampling requirements, sensitivity, methods of eliminating scattered radiation, random coincidences and attenuation. The implementation of these parameters is considered, with special reference to sampling, choice of detector material, detector ring diameter and shielding and variations in point spread function. Quantitation problems discussed are normalization, and attenuation and random corrections. Present developments mentioned are noise reduction through time-of-flight-assisted tomography and signal to noise improvements through high intrinsic resolution. Extensive bibliography. (U.K.)
Confounding of three binary-variables counterfactual model
Liu, Jingwei; Hu, Shuang
2011-01-01
Confounding of three binary-variables counterfactual model is discussed in this paper. According to the effect between the control variable and the covariate variable, we investigate three counterfactual models: the control variable is independent of the covariate variable, the control variable has the effect on the covariate variable and the covariate variable affects the control variable. Using the ancillary information based on conditional independence hypotheses, the sufficient conditions...
Sharma, Nivita D
2017-09-01
Several explanations for the inconsistent results on the effects of breastfeeding on childhood asthma have been suggested. The purpose of this study was to investigate one unexplored explanation, which is the presence of a potential endogenous relationship between breastfeeding and childhood asthma. Endogeneity exists when an explanatory variable is correlated with the error term for reasons such as selection bias, reverse causality, and unmeasured confounders. Unadjusted endogeneity will bias the effect of breastfeeding on childhood asthma. To investigate potential endogeneity, a cross-sectional study of breastfeeding practices and incidence of childhood asthma in 87 pediatric patients in Georgia, the USA, was conducted using generalized linear modeling and a two-stage instrumental variable analysis. First, the relationship between breastfeeding and childhood asthma was analyzed without considering endogeneity. Second, tests for presence of endogeneity were performed and having detected endogeneity between breastfeeding and childhood asthma, a two-stage instrumental variable analysis was performed. The first stage of this analysis estimated the duration of breastfeeding and the second-stage estimated the risk of childhood asthma. When endogeneity was not taken into account, duration of breastfeeding was found to significantly increase the risk of childhood asthma (relative risk ratio [RR]=2.020, 95% confidence interval [CI]: [1.143-3.570]). After adjusting for endogeneity, duration of breastfeeding significantly reduced the risk of childhood asthma (RR=0.003, 95% CI: [0.000-0.240]). The findings suggest that researchers should consider evaluating how the presence of endogeneity could affect the relationship between duration of breastfeeding and the risk of childhood asthma. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.
Instrumentation of a prestressed concrete containment vessel model
International Nuclear Information System (INIS)
Hessheimer, M.F.; Rightley, M.J.; Matsumoto, T.
1995-01-01
A series of static overpressurization tests of scale models of nuclear containment structures is being conducted by Sandia National Laboratories for the Nuclear Power Engineering Corporation of Japan and the U.S. Nuclear Regulatory Commission. At present, two tests are being planned: a test of a model of a steel containment vessel (SCV) that is representative of an improved, boiling water reactor (BWR) Mark II design; and a test of a model of a prestressed concrete containment vessel (PCCV). This paper discusses plans and the results of a preliminary investigation of the instrumentation of the PCCV model. The instrumentation suite for this model will consist of approximately 2000 channels of data to record displacements, strains in the reinforcing steel, prestressing tendons, concrete, steel liner and liner anchors, as well as pressure and temperature. The instrumentation is being designed to monitor the response of the model during prestressing operations, during Structural Integrity and Integrated Leak Rate testing, and during test to failure of the model. Particular emphasis has been placed on instrumentation of the prestressing system in order to understand the behavior of the prestressing strands at design and beyond design pressure levels. Current plans are to place load cells at both ends of one third of the tendons in addition to placing strain measurement devices along the length of selected tendons. Strain measurements will be made using conventional bonded foil resistance gages and a wire resistance gage, known as a open-quotes Tensmegclose quotes reg-sign gage, specifically designed for use with seven-wire strand. The results of preliminary tests of both types of gages, in the laboratory and in a simulated model configuration, are reported and plans for instrumentation of the model are discussed
Variable selection and model choice in geoadditive regression models.
Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard
2009-06-01
Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.
Natural climate variability in a coupled model
International Nuclear Information System (INIS)
Zebiak, S.E.; Cane, M.A.
1990-01-01
Multi-century simulations with a simplified coupled ocean-atmosphere model are described. These simulations reveal an impressive range of variability on decadal and longer time scales, in addition to the dominant interannual el Nino/Southern Oscillation signal that the model originally was designed to simulate. Based on a very large sample of century-long simulations, it is nonetheless possible to identify distinct model parameter sensitivities that are described here in terms of selected indices. Preliminary experiments motivated by general circulation model results for increasing greenhouse gases suggest a definite sensitivity to model global warming. While these results are not definitive, they strongly suggest that coupled air-sea dynamics figure prominently in global change and must be included in models for reliable predictions
Pega, Frank
2016-05-01
Social epidemiologists are interested in determining the causal relationship between income and health. Natural experiments in which individuals or groups receive income randomly or quasi-randomly from financial credits (e.g., tax credits or cash transfers) are increasingly being analyzed using instrumental variable analysis. For example, in this issue of the Journal, Hamad and Rehkopf (Am J Epidemiol. 2016;183(9):775-784) used an in-work tax credit called the Earned Income Tax Credit as an instrument to estimate the association between income and child development. However, under certain conditions, the use of financial credits as instruments could violate 2 key instrumental variable analytic assumptions. First, some financial credits may directly influence health, for example, through increasing a psychological sense of welfare security. Second, financial credits and health may have several unmeasured common causes, such as politics, other social policies, and the motivation to maximize the credit. If epidemiologists pursue such instrumental variable analyses, using the amount of an unconditional, universal credit that an individual or group has received as the instrument may produce the most conceptually convincing and generalizable evidence. However, other natural income experiments (e.g., lottery winnings) and other methods that allow better adjustment for confounding might be more promising approaches for estimating the causal relationship between income and health. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
A Model for Positively Correlated Count Variables
DEFF Research Database (Denmark)
Møller, Jesper; Rubak, Ege Holger
2010-01-01
An α-permanental random field is briefly speaking a model for a collection of non-negative integer valued random variables with positive associations. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of α-permanental random fields...... and their potential applications. The purpose of this paper is to summarize useful probabilistic results, study stochastic constructions and simulation techniques, and discuss some examples of α-permanental random fields. This should provide a useful basis for discussing the statistical aspects in future work....
Wesołowska, Karolina; Elovainio, Marko; Hintsa, Taina; Jokela, Markus; Pulkki-Råback, Laura; Pitkänen, Niina; Lipsanen, Jari; Tukiainen, Janne; Lyytikäinen, Leo-Pekka; Lehtimäki, Terho; Juonala, Markus; Raitakari, Olli; Keltikangas-Järvinen, Liisa
2017-12-01
Type 2 diabetes (T2D) has been associated with depressive symptoms, but the causal direction of this association and the underlying mechanisms, such as increased glucose levels, remain unclear. We used instrumental-variable regression with a genetic instrument (Mendelian randomization) to examine a causal role of increased glucose concentrations in the development of depressive symptoms. Data were from the population-based Cardiovascular Risk in Young Finns Study (n = 1217). Depressive symptoms were assessed in 2012 using a modified Beck Depression Inventory (BDI-I). Fasting glucose was measured concurrently with depressive symptoms. A genetic risk score for fasting glucose (with 35 single nucleotide polymorphisms) was used as an instrumental variable for glucose. Glucose was not associated with depressive symptoms in the standard linear regression (B = -0.04, 95% CI [-0.12, 0.04], p = .34), but the instrumental-variable regression showed an inverse association between glucose and depressive symptoms (B = -0.43, 95% CI [-0.79, -0.07], p = .020). The difference between the estimates of standard linear regression and instrumental-variable regression was significant (p = .026) CONCLUSION: Our results suggest that the association between T2D and depressive symptoms is unlikely to be caused by increased glucose concentrations. It seems possible that T2D might be linked to depressive symptoms due to low glucose levels.
Study of parental models: building an instrument for their exploration
Directory of Open Access Journals (Sweden)
José Francisco Martínez Licona
2014-08-01
Full Text Available Objective: This research presents the construction of an attributional questionnaire concerning the different parental models and factors that are involved in family interactions. Method: A mixed methodology was used as a foundation to develop items and respective pilots that allowed checking the validity and internal consistency of the instrument using expert judgment. Results: An instrument of 36 statements was organized into 12 categories to explore the parental models according to the following factors: parental models, breeding patterns, attachment bonds and guidelines for success, and promoted inside family contexts. Analyzing these factors contributes to the children’s development within the familiar frown, and the opportunity for socio-educational intervention. Conclusion: It is assumed that the family context is as decisive as the school context; therefore, exploring the nature of parental models is required to understand the features and influences that contribute to the development of young people in any social context.
Quantifying measurement uncertainty and spatial variability in the context of model evaluation
Choukulkar, A.; Brewer, A.; Pichugina, Y. L.; Bonin, T.; Banta, R. M.; Sandberg, S.; Weickmann, A. M.; Djalalova, I.; McCaffrey, K.; Bianco, L.; Wilczak, J. M.; Newman, J. F.; Draxl, C.; Lundquist, J. K.; Wharton, S.; Olson, J.; Kenyon, J.; Marquis, M.
2017-12-01
In an effort to improve wind forecasts for the wind energy sector, the Department of Energy and the NOAA funded the second Wind Forecast Improvement Project (WFIP2). As part of the WFIP2 field campaign, a large suite of in-situ and remote sensing instrumentation was deployed to the Columbia River Gorge in Oregon and Washington from October 2015 - March 2017. The array of instrumentation deployed included 915-MHz wind profiling radars, sodars, wind- profiling lidars, and scanning lidars. The role of these instruments was to provide wind measurements at high spatial and temporal resolution for model evaluation and improvement of model physics. To properly determine model errors, the uncertainties in instrument-model comparisons need to be quantified accurately. These uncertainties arise from several factors such as measurement uncertainty, spatial variability, and interpolation of model output to instrument locations, to name a few. In this presentation, we will introduce a formalism to quantify measurement uncertainty and spatial variability. The accuracy of this formalism will be tested using existing datasets such as the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign. Finally, the uncertainties in wind measurement and the spatial variability estimates from the WFIP2 field campaign will be discussed to understand the challenges involved in model evaluation.
Instrumentation and testing of a prestressed concrete containment vessel model
International Nuclear Information System (INIS)
Hessheimer, M.F.; Pace, D.W.; Klamerus, E.W.
1997-01-01
Static overpressurization tests of two scale models of nuclear containment structures - a steel containment vessel (SCV) representative of an improved, boiling water reactor (BWR) Mark II design and a prestressed concrete containment vessel (PCCV) for pressurized water reactors (PWR) - are being conducted by Sandia National Laboratories for the Nuclear Power Engineering Corporation of Japan and the U.S. Nuclear Regulatory Commission. This paper discusses plans for instrumentation and testing of the PCCV model. 6 refs., 2 figs., 2 tabs
Assessing Mucoadhesion in Polymer Gels: The Effect of Method Type and Instrument Variables
Directory of Open Access Journals (Sweden)
Jéssica Bassi da Silva
2018-03-01
Full Text Available The process of mucoadhesion has been widely studied using a wide variety of methods, which are influenced by instrumental variables and experiment design, making the comparison between the results of different studies difficult. The aim of this work was to standardize the conditions of the detachment test and the rheological methods of mucoadhesion assessment for semisolids, and introduce a texture profile analysis (TPA method. A factorial design was developed to suggest standard conditions for performing the detachment force method. To evaluate the method, binary polymeric systems were prepared containing poloxamer 407 and Carbopol 971P®, Carbopol 974P®, or Noveon® Polycarbophil. The mucoadhesion of systems was evaluated, and the reproducibility of these measurements investigated. This detachment force method was demonstrated to be reproduceable, and gave different adhesion when mucin disk or ex vivo oral mucosa was used. The factorial design demonstrated that all evaluated parameters had an effect on measurements of mucoadhesive force, but the same was not observed for the work of adhesion. It was suggested that the work of adhesion is a more appropriate metric for evaluating mucoadhesion. Oscillatory rheology was more capable of investigating adhesive interactions than flow rheology. TPA method was demonstrated to be reproducible and can evaluate the adhesiveness interaction parameter. This investigation demonstrates the need for standardized methods to evaluate mucoadhesion and makes suggestions for a standard study design.
Duda, David P.; Stephens, Graeme L.; Cox, Stephen K.
1990-01-01
Measurements of longwave and shortwave radiation were made using an instrument package on the NASA tethered balloon during the FIRE Marine Stratocumulus experiment. Radiation data from two pairs of pyranometers were used to obtain vertical profiles of the near-infrared and total solar fluxes through the boundary layer, while a pair of pyrgeometers supplied measurements of the longwave fluxes in the cloud layer. The radiation observations were analyzed to determine heating rates and to measure the radiative energy budget inside the stratocumulus clouds during several tethered balloon flights. The radiation fields in the cloud layer were also simulated by a two-stream radiative transfer model, which used cloud optical properties derived from microphysical measurements and Mie scattering theory.
Agirdas, Cagdas; Krebs, Robert J; Yano, Masato
2018-01-08
One goal of the Affordable Care Act is to increase insurance coverage by improving competition and lowering premiums. To facilitate this goal, the federal government enacted online marketplaces in the 395 rating areas spanning 34 states that chose not to establish their own state-run marketplaces. Few multivariate regression studies analyzing the effects of competition on premiums suffer from endogeneity, due to simultaneity and omitted variable biases. However, United Healthcare's decision to enter these marketplaces in 2015 provides the researcher with an opportunity to address this endogeneity problem. Exploiting the variation caused by United Healthcare's entry decision as an instrument for competition, we study the impact of competition on premiums during the first 2 years of these marketplaces. Combining panel data from five different sources and controlling for 12 variables, we find that one more insurer in a rating area leads to a 6.97% reduction in the second-lowest-priced silver plan premium, which is larger than the estimated effects in existing literature. Furthermore, we run a threshold analysis and find that competition's effects on premiums become statistically insignificant if there are four or more insurers in a rating area. These findings are robust to alternative measures of premiums, inclusion of a non-linear term in the regression models and a county-level analysis.
Cassini Radar EQM Model: Instrument Description and Performance Status
Borgarelli, L.; Faustini, E. Zampolini; Im, E.; Johnson, W. T. K.
1996-01-01
The spaeccraft of the Cassini Mission is planned to be launched towards Saturn in October 1997. The mission is designed to study the physical structure and chemical composition of Titan. The results of the tests performed on the Cassini radar engineering qualification model (EQM) are summarized. The approach followed in the verification and evaluation of the performance of the radio frequency subsystem EQM is presented. The results show that the instrument satisfies the relevant mission requirements.
An instrumental electrode model for solving EIT forward problems.
Zhang, Weida; Li, David
2014-10-01
An instrumental electrode model (IEM) capable of describing the performance of electrical impedance tomography (EIT) systems in the MHz frequency range has been proposed. Compared with the commonly used Complete Electrode Model (CEM), which assumes ideal front-end interfaces, the proposed model considers the effects of non-ideal components in the front-end circuits. This introduces an extra boundary condition in the forward model and offers a more accurate modelling for EIT systems. We have demonstrated its performance using simple geometry structures and compared the results with the CEM and full Maxwell methods. The IEM can provide a significantly more accurate approximation than the CEM in the MHz frequency range, where the full Maxwell methods are favoured over the quasi-static approximation. The improved electrode model will facilitate the future characterization and front-end design of real-world EIT systems.
Elovainio, Marko; Heponiemi, Tarja; Kuusio, Hannamaria; Jokela, Markus; Aalto, Anna-Mari; Pekkarinen, Laura; Noro, Anja; Finne-Soveri, Harriet; Kivimäki, Mika; Sinervo, Timo
2015-02-01
The association between psychosocial work environment and employee wellbeing has repeatedly been shown. However, as environmental evaluations have typically been self-reported, the observed associations may be attributable to reporting bias. Applying instrumental-variable regression, we used staffing level (the ratio of staff to residents) as an unconfounded instrument for self-reported job demands and job strain to predict various indicators of wellbeing (perceived stress, psychological distress and sleeping problems) among 1525 registered nurses, practical nurses and nursing assistants working in elderly care wards. In ordinary regression, higher self-reported job demands and job strain were associated with increased risk of perceived stress, psychological distress and sleeping problems. The effect estimates for the associations of these psychosocial factors with perceived stress and psychological distress were greater, but less precisely estimated, in an instrumental-variables analysis which took into account only the variation in self-reported job demands and job strain that was explained by staffing level. No association between psychosocial factors and sleeping problems was observed with the instrumental-variable analysis. These results support a causal interpretation of high self-reported job demands and job strain being risk factors for employee wellbeing. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
Preliminary Multi-Variable Parametric Cost Model for Space Telescopes
Stahl, H. Philip; Hendrichs, Todd
2010-01-01
This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.
Dunn, Abe
2016-07-01
This paper takes a different approach to estimating demand for medical care that uses the negotiated prices between insurers and providers as an instrument. The instrument is viewed as a textbook "cost shifting" instrument that impacts plan offerings, but is unobserved by consumers. The paper finds a price elasticity of demand of around -0.20, matching the elasticity found in the RAND Health Insurance Experiment. The paper also studies within-market variation in demand for prescription drugs and other medical care services and obtains comparable price elasticity estimates. Published by Elsevier B.V.
Modeling variability in porescale multiphase flow experiments
Ling, Bowen; Bao, Jie; Oostrom, Mart; Battiato, Ilenia; Tartakovsky, Alexandre M.
2017-07-01
Microfluidic devices and porescale numerical models are commonly used to study multiphase flow in biological, geological, and engineered porous materials. In this work, we perform a set of drainage and imbibition experiments in six identical microfluidic cells to study the reproducibility of multiphase flow experiments. We observe significant variations in the experimental results, which are smaller during the drainage stage and larger during the imbibition stage. We demonstrate that these variations are due to sub-porescale geometry differences in microcells (because of manufacturing defects) and variations in the boundary condition (i.e., fluctuations in the injection rate inherent to syringe pumps). Computational simulations are conducted using commercial software STAR-CCM+, both with constant and randomly varying injection rates. Stochastic simulations are able to capture variability in the experiments associated with the varying pump injection rate.
How to get rid of W: a latent variables approach to modelling spatially lagged variables
Folmer, H.; Oud, J.
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
How to get rid of W : a latent variables approach to modelling spatially lagged variables
Folmer, Henk; Oud, Johan
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
Burns, Darren K; Jones, Andrew P; Goryakin, Yevgeniy; Suhrcke, Marc
2017-05-01
There is a scarcity of quantitative research into the effect of FDI on population health in low and middle income countries (LMICs). This paper investigates the relationship using annual panel data from 85 LMICs between 1974 and 2012. When controlling for time trends, country fixed effects, correlation between repeated observations, relevant covariates, and endogeneity via a novel instrumental variable approach, we find FDI to have a beneficial effect on overall health, proxied by life expectancy. When investigating age-specific mortality rates, we find a stronger beneficial effect of FDI on adult mortality, yet no association with either infant or child mortality. Notably, FDI effects on health remain undetected in all models which do not control for endogeneity. Exploring the effect of sector-specific FDI on health in LMICs, we provide preliminary evidence of a weak inverse association between secondary (i.e. manufacturing) sector FDI and overall life expectancy. Our results thus suggest that FDI has provided an overall benefit to population health in LMICs, particularly in adults, yet investments into the secondary sector could be harmful to health. Copyright © 2017 Elsevier Ltd. All rights reserved.
Woods, Thomas N.; Eparvier, Francis G.; Harder, Jerald; Snow, Martin
2018-05-01
The solar spectral irradiance (SSI) dataset is a key record for studying and understanding the energetics and radiation balance in Earth's environment. Understanding the long-term variations of the SSI over timescales of the 11-year solar activity cycle and longer is critical for many Sun-Earth research topics. Satellite measurements of the SSI have been made since the 1970s, most of them in the ultraviolet, but recently also in the visible and near-infrared. A limiting factor for the accuracy of previous solar variability results is the uncertainties for the instrument degradation corrections, which need fairly large corrections relative to the amount of solar cycle variability at some wavelengths. The primary objective of this investigation has been to separate out solar cycle variability and any residual uncorrected instrumental trends in the SSI measurements from the Solar Radiation and Climate Experiment (SORCE) mission and the Thermosphere, Mesosphere, Ionosphere, Energetic, and Dynamics (TIMED) mission. A new technique called the Multiple Same-Irradiance-Level (MuSIL) analysis has been developed, which examines an SSI time series at different levels of solar activity to provide long-term trends in an SSI record, and the most common result is a downward trend that most likely stems from uncorrected instrument degradation. This technique has been applied to each wavelength in the SSI records from SORCE (2003 - present) and TIMED (2002 - present) to provide new solar cycle variability results between 27 nm and 1600 nm with a resolution of about 1 nm at most wavelengths. This technique, which was validated with the highly accurate total solar irradiance (TSI) record, has an estimated relative uncertainty of about 5% of the measured solar cycle variability. The MuSIL results are further validated with the comparison of the new solar cycle variability results from different solar cycles.
Finite Difference Time Domain Modeling at USA Instruments, Inc.
Curtis, Richard
2003-10-01
Due to the competitive nature of the commercial MRI industry, it is essential for the financial health of a participating company to innovate new coil designs and bring product to market rapidly in response to ever-changing market conditions. However, the technology of MRI coil design is still early in its stage of development and its principles are yet evolving. As a result, it is not always possible to know the relevant electromagnetic effects of a given design since the interaction of coil elements is complex and often counter-intuitive. Even if the effects are known qualitatively, the quantitative results are difficult to obtain. At USA Instruments, Inc., the acquisition of the XFDTDâ electromagnetic simulation tool from REMCOM, Inc., has been helpful in determining the electromagnetic performance characteristics of existing coil designs in the prototype stage before the coils are released for production. In the ideal case, a coil design would be modeled earlier at the conceptual stage, so that only good designs will make it to the prototyping stage and the electromagnetic characteristics better understood very early in the design process and before the testing stage has begun. This paper is a brief overview of using FDTD modeling for MRI coil design at USA Instruments, Inc., and shows some of the highlights of recent FDTD modeling efforts on Birdcage coils, a staple of the MRI coil design portfolio.
Model instruments of effective segmentation of the fast food market
Directory of Open Access Journals (Sweden)
Mityaeva Tetyana L.
2013-03-01
Full Text Available The article presents results of optimisation step-type calculations of economic effectiveness of promotion of fast food with consideration of key parameters of assessment of efficiency of the marketing strategy of segmentation. The article justifies development of a mathematical model on the bases of 3D-presentations and three-dimensional system of management variables. The modern applied mathematical packages allow formation not only of one-dimensional and two-dimensional arrays and analyse links of variables, but also of three-dimensional, besides, the more links and parameters are taken into account, the more adequate and adaptive are results of modelling and, as a result, more informative and strategically valuable. The article shows modelling possibilities that allow taking into account strategies and reactions on formation of the marketing strategy under conditions of entering the fast food market segments.
Bayesian modeling of measurement error in predictor variables
Fox, Gerardus J.A.; Glas, Cornelis A.W.
2003-01-01
It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between
Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling
Raykov, Tenko; Marcoulides, George A.
2012-01-01
A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…
Puhani, Patrick A.; Weber, Andrea M.
2006-01-01
We estimate the effect of age of school entry on educational outcomes using two different data sets for Germany, sampling pupils at the end of primary school and in the middle of secondary school. Results are obtained based on instrumental variable estimation exploiting the exogenous variation in month of birth. We find robust and significant positive effects on educational outcomes for pupils who enter school at seven instead of six years of age: Test scores at the end of primary school incr...
Damé, Luc; Bolsée, David; Meftah, Mustapha; Irbah, Abdenour; Hauchecorne, Alain; Bekki, Slimane; Pereira, Nuno; Cessateur, Marchand; Gäel; , Marion; et al.
2016-10-01
Accurate measurements of Solar Spectral Irradiance (SSI) are of primary importance for a better understanding of solar physics and of the impact of solar variability on climate (via Earth's atmospheric photochemistry). The acquisition of a top of atmosphere reference solar spectrum and of its temporal and spectral variability during the unusual solar cycle 24 is of prime interest for these studies. These measurements are performed since April 2008 with the SOLSPEC spectro-radiometer from the far ultraviolet to the infrared (166 nm to 3088 nm). This instrument, developed under a fruitful LATMOS/BIRA-IASB collaboration, is part of the Solar Monitoring Observatory (SOLAR) payload, externally mounted on the Columbus module of the International Space Station (ISS). The SOLAR mission, with its actual 8 years duration, will cover almost the entire solar cycle 24. We present here the in-flight operations and performances of the SOLSPEC instrument, including the engineering corrections, calibrations and improved know-how procedure for aging corrections. Accordingly, a SSI reference spectrum from the UV to the NIR will be presented, together with its variability in the UV, as measured by SOLAR/SOLSPEC for 8 years. Uncertainties on these measurements and comparisons with other instruments will be briefly discussed.
Flyover Modeling of Planetary Pits - Undergraduate Student Instrument Project
Bhasin, N.; Whittaker, W.
2015-12-01
On the surface of the moon and Mars there are hundreds of skylights, which are collapsed holes that are believed to lead to underground caves. This research uses Vision, Inertial, and LIDAR sensors to build a high resolution model of a skylight as a landing vehicle flies overhead. We design and fabricate a pit modeling instrument to accomplish this task, implement software, and demonstrate sensing and modeling capability on a suborbital reusable launch vehicle flying over a simulated pit. Future missions on other planets and moons will explore pits and caves, led by the technology developed by this research. Sensor software utilizes modern graph-based optimization techniques to build 3D models using camera, LIDAR, and inertial data. The modeling performance was validated with a test flyover of a planetary skylight analog structure on the Masten Xombie sRLV. The trajectory profile closely follows that of autonomous planetary powered descent, including translational and rotational dynamics as well as shock and vibration. A hexagonal structure made of shipping containers provides a terrain feature that serves as an appropriate analog for the rim and upper walls of a cylindrical planetary skylight. The skylight analog floor, walls, and rim are modeled in elevation with a 96% coverage rate at 0.25m2 resolution. The inner skylight walls have 5.9cm2 color image resolution and the rims are 6.7cm2 with measurement precision superior to 1m. The multidisciplinary student team included students of all experience levels, with backgrounds in robotics, physics, computer science, systems, mechanical and electrical engineering. The team was commited to authentic scientific experimentation, and defined specific instrument requirements and measurable experiment objectives to verify successful completion.This work was made possible by the NASA Undergraduate Student Instrument Project Educational Flight Opportunity 2013 program. Additional support was provided by the sponsorship of an
Instrumental and ethical aspects of experimental research with animal models
Directory of Open Access Journals (Sweden)
Mirian Watanabe
2014-02-01
Full Text Available Experimental animal models offer possibilities of physiology knowledge, pathogenesis of disease and action of drugs that are directly related to quality nursing care. This integrative review describes the current state of the instrumental and ethical aspects of experimental research with animal models, including the main recommendations of ethics committees that focus on animal welfare and raises questions about the impact of their findings in nursing care. Data show that, in Brazil, the progress in ethics for the use of animals for scientific purposes was consolidated with Law No. 11.794/2008 establishing ethical procedures, attending health, genetic and experimental parameters. The application of ethics in handling of animals for scientific and educational purposes and obtaining consistent and quality data brings unquestionable contributions to the nurse, as they offer subsidies to relate pathophysiological mechanisms and the clinical aspect on the patient.
Model instruments of effective segmentation of the fast food market
Mityaeva Tetyana L.
2013-01-01
The article presents results of optimisation step-type calculations of economic effectiveness of promotion of fast food with consideration of key parameters of assessment of efficiency of the marketing strategy of segmentation. The article justifies development of a mathematical model on the bases of 3D-presentations and three-dimensional system of management variables. The modern applied mathematical packages allow formation not only of one-dimensional and two-dimensional arrays and analyse ...
Drag coefficient Variability and Thermospheric models
Moe, Kenneth
Satellite drag coefficients depend upon a variety of factors: The shape of the satellite, its altitude, the eccentricity of its orbit, the temperature and mean molecular mass of the ambient atmosphere, and the time in the sunspot cycle. At altitudes where the mean free path of the atmospheric molecules is large compared to the dimensions of the satellite, the drag coefficients can be determined from the theory of free-molecule flow. The dependence on altitude is caused by the concentration of atomic oxygen which plays an important role by its ability to adsorb on the satellite surface and thereby affect the energy loss of molecules striking the surface. The eccentricity of the orbit determines the satellite velocity at perigee, and therefore the energy of the incident molecules relative to the energy of adsorption of atomic oxygen atoms on the surface. The temperature of the ambient atmosphere determines the extent to which the random thermal motion of the molecules influences the momentum transfer to the satellite. The time in the sunspot cycle affects the ambient temperature as well as the concentration of atomic oxygen at a particular altitude. Tables and graphs will be used to illustrate the variability of drag coefficients. Before there were any measurements of gas-surface interactions in orbit, Izakov and Cook independently made an excellent estimate that the drag coefficient of satellites of compact shape would be 2.2. That numerical value, independent of altitude, was used by Jacchia to construct his model from the early measurements of satellite drag. Consequently, there is an altitude dependent bias in the model. From the sparce orbital experiments that have been done, we know that the molecules which strike satellite surfaces rebound in a diffuse angular distribution with an energy loss given by the energy accommodation coefficient. As more evidence accumulates on the energy loss, more realistic drag coefficients are being calculated. These improved drag
Directory of Open Access Journals (Sweden)
Johan Håkon Bjørngaard
Full Text Available While high body mass index is associated with an increased risk of depression and anxiety, cumulative evidence indicates that it is a protective factor for suicide. The associations from conventional observational studies of body mass index with mental health outcomes are likely to be influenced by reverse causality or confounding by ill-health. In the present study, we investigated the associations between offspring body mass index and parental anxiety, depression and suicide in order to avoid problems with reverse causality and confounding by ill-health.We used data from 32,457 mother-offspring and 27,753 father-offspring pairs from the Norwegian HUNT-study. Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale and suicide death from national registers. Associations between offspring and own body mass index and symptoms of anxiety and depression and suicide mortality were estimated using logistic and Cox regression. Causal effect estimates were estimated with a two sample instrument variable approach using offspring body mass index as an instrument for parental body mass index.Both own and offspring body mass index were positively associated with depression, while the results did not indicate any substantial association between body mass index and anxiety. Although precision was low, suicide mortality was inversely associated with own body mass index and the results from the analysis using offspring body mass index supported these results. Adjusted odds ratios per standard deviation body mass index from the instrumental variable analysis were 1.22 (95% CI: 1.05, 1.43 for depression, 1.10 (95% CI: 0.95, 1.27 for anxiety, and the instrumental variable estimated hazard ratios for suicide was 0.69 (95% CI: 0.30, 1.63.The present study's results indicate that suicide mortality is inversely associated with body mass index. We also found support for a positive association between body mass index and depression, but not
The sound of oscillating air jets: Physics, modeling and simulation in flute-like instruments
de La Cuadra, Patricio
Flute-like instruments share a common mechanism that consists of blowing across one open end of a resonator to produce an air jet that is directed towards a sharp edge. Analysis of its operation involves various research fields including fluid dynamics, aero-acoustics, and physics. An effort has been made in this study to extend this description from instruments with fixed geometry like recorders and organ pipes to flutes played by the lips. An analysis of the jet's response to a periodic excitation is the focus of this study, as are the parameters under the player's control in forming the jet. The jet is excited with a controlled excitation consisting of two loudspeakers in opposite phase. A Schlieren system is used to visualize the jet, and image detection algorithms are developed to extract quantitative information from the images. In order to study the behavior of jets observed in different flute-like instruments, several geometries of the excitation and jet shapes are studied. The obtained data is used to propose analytical models that correctly fit the observed measurements and can be used for simulations. The control exerted by the performer on the instrument is of crucial importance in the quality of the sound produced for a number of flute-like instruments. The case of the transverse flute is experimentally studied. An ensemble of control parameters are measured and visualized in order to describe some aspects of the subtle control attained by an experienced flautist. Contrasting data from a novice flautist are compared. As a result, typical values for several non-dimensional parameters that characterize the normal operation of the instrument have been measured, and data to feed simulations has been collected. The information obtained through experimentation is combined with research developed over the last decades to put together a time-domain simulation. The model proposed is one-dimensional and driven by a single physical input. All the variables in the
Creel, Scott; Creel, Michael
2009-11-01
1. Sampling error in annual estimates of population size creates two widely recognized problems for the analysis of population growth. First, if sampling error is mistakenly treated as process error, one obtains inflated estimates of the variation in true population trajectories (Staples, Taper & Dennis 2004). Second, treating sampling error as process error is thought to overestimate the importance of density dependence in population growth (Viljugrein et al. 2005; Dennis et al. 2006). 2. In ecology, state-space models are used to account for sampling error when estimating the effects of density and other variables on population growth (Staples et al. 2004; Dennis et al. 2006). In econometrics, regression with instrumental variables is a well-established method that addresses the problem of correlation between regressors and the error term, but requires fewer assumptions than state-space models (Davidson & MacKinnon 1993; Cameron & Trivedi 2005). 3. We used instrumental variables to account for sampling error and fit a generalized linear model to 472 annual observations of population size for 35 Elk Management Units in Montana, from 1928 to 2004. We compared this model with state-space models fit with the likelihood function of Dennis et al. (2006). We discuss the general advantages and disadvantages of each method. Briefly, regression with instrumental variables is valid with fewer distributional assumptions, but state-space models are more efficient when their distributional assumptions are met. 4. Both methods found that population growth was negatively related to population density and winter snow accumulation. Summer rainfall and wolf (Canis lupus) presence had much weaker effects on elk (Cervus elaphus) dynamics [though limitation by wolves is strong in some elk populations with well-established wolf populations (Creel et al. 2007; Creel & Christianson 2008)]. 5. Coupled with predictions for Montana from global and regional climate models, our results
Exploring mouthfeel in model wines: Sensory-to-instrumental approaches.
Laguna, Laura; Sarkar, Anwesha; Bryant, Michael G; Beadling, Andrew R; Bartolomé, Begoña; Victoria Moreno-Arribas, M
2017-12-01
Wine creates a group of oral-tactile stimulations not related to taste or aroma, such as astringency or fullness; better known as mouthfeel. During wine consumption, mouthfeel is affected by ethanol content, phenolic compounds and their interactions with the oral components. Mouthfeel arises through changes in the salivary film when wine is consumed. In order to understand the role of each wine component, eight different model wines with/without ethanol (8%), glycerol (10g/L) and commercial tannins (1g/L) were described using a trained panel. Descriptive analysis techniques were used to train the panel and measure the intensity of the mouthfeel attributes. Alongside, the suitability of different instrumental techniques (rheology, particle size, tribology and microstructure, using Transmission Electron Microscopy (TEM)) to measure wine mouthfeel sensation was investigated. Panelists discriminated samples based on their tactile-related components (ethanol, glycerol and tannins) at the levels found naturally in wine. Higher scores were found for all sensory attributes in the samples containing ethanol. Sensory astringency was associated mainly with the addition of tannins to the wine model and glycerol did not seem to play a discriminating role at the levels found in red wines. Visual viscosity was correlated with instrumental viscosity (R=0.815, p=0.014). Hydrodynamic diameter of saliva showed an increase in presence of tannins (almost 2.5-3-folds). However, presence of ethanol or glycerol decreased hydrodynamic diameter. These results were related with the sensory astringency and earthiness as well as with the formation of nano-complexes as observed by TEM. Rheologically, the most viscous samples were those containing glycerol or tannins. Tribology results showed that at a boundary lubrication regime, differences in traction coefficient lubrication were due by the presence of glycerol. However, no differences in traction coefficients were observed in presence
Generalized Network Psychometrics : Combining Network and Latent Variable Models
Epskamp, S.; Rhemtulla, M.; Borsboom, D.
2017-01-01
We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between
Variables influencing the use of derivatives in South Africa – the development of a conceptual model
Directory of Open Access Journals (Sweden)
Stefan Schwegler
2011-03-01
Full Text Available This paper, which is the first in a two-part series, sets out the development of a conceptual model on the variables influencing investors’ decisions to use derivatives in their portfolios. Investor-specific variables include: the investor’s needs, goals and return expectations, the investor’s knowledge of financial markets, familiarity with different asset classes including derivative instruments, and the investor’s level of wealth and level of risk tolerance. Market-specific variables include: the level of volatility, standardisation, regulation and liquidity in a market, the level of information available on derivatives, the transparency of price determination, taxes, brokerage costs and product availability.
Sound production in recorder-like instruments : II. a simulation model
Verge, M.P.; Hirschberg, A.; Causse, R.
1997-01-01
A simple one-dimensional representation of recorderlike instruments, that can be used for sound synthesis by physical modeling of flutelike instruments, is presented. This model combines the effects on the sound production by the instrument of the jet oscillations, vortex shedding at the edge of the
Clifton, G. T.; Merrill, J. T.; Johnson, B. J.; Oltmans, S. J.
2009-12-01
Ozonesondes provide information on the ozone distribution up to the middle stratosphere. Ozone profiles often feature layers, with vertically discrete maxima and minima in the mixing ratio. Layers are especially common in the UT/LS regions and originate from wave breaking, shearing and other transport processes. ECC sondes, however, have a moderate response time to significant changes in ozone. A sonde can ascend over 350 meters before it responds fully to a step change in ozone. This results in an overestimate of the altitude assigned to layers and an underestimate of the underlying variability in the amount of ozone. An estimate of the response time is made for each instrument during the preparation for flight, but the profile data are typically not processed to account for the response. Here we present a method of categorizing the response time of ECC instruments and an analysis of a low-pass filter approximation to the effects on profile data. Exponential functions were fit to the step-up and step-down responses using laboratory data. The resulting response time estimates were consistent with results from standard procedures, with the up-step response time exceeding the down-step value somewhat. A single-pole Butterworth filter that approximates the instrumental effect was used with synthetic layered profiles to make first-order estimates of the impact of the finite response time. Using a layer analysis program previously applied to observed profiles we find that instrumental effects can attenuate ozone variability by 20-45% in individual layers, but that the vertical offset in layer altitudes is moderate, up to about 150 meters. We will present results obtained using this approach, coupled with data on the distribution of layer characteristics found using the layer analysis procedure on profiles from Narragansett, Rhode Island and other US sites to quantify the impact on overall variability estimates given ambient distributions of layer occurrence, thickness
Predictor variable resolution governs modeled soil types
Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...
Modeling Coast Redwood Variable Retention Management Regimes
John-Pascal Berrill; Kevin O' Hara
2007-01-01
Variable retention is a flexible silvicultural system that provides forest managers with an alternative to clearcutting. While much of the standing volume is removed in one harvesting operation, residual stems are retained to provide structural complexity and wildlife habitat functions, or to accrue volume before removal during subsequent stand entries. The residual...
NASA Instrument Cost Model for Explorer-Like Mission Instruments (NICM-E)
Habib-Agahi, Hamid; Fox, George; Mrozinski, Joe; Ball, Gary
2013-01-01
NICM-E is a cost estimating relationship that supplements the traditional NICM System Level CERs for instruments flown on NASA Explorer-like missions that have the following three characteristics: 1) fly on Class C missions, 2) major development led and performed by universities or research foundations, and 3) have significant level of inheritance.
Variable Fidelity Aeroelastic Toolkit - Structural Model, Phase I
National Aeronautics and Space Administration — The proposed innovation is a methodology to incorporate variable fidelity structural models into steady and unsteady aeroelastic and aeroservoelastic analyses in...
Multi-wheat-model ensemble responses to interannual climatic variability
DEFF Research Database (Denmark)
Ruane, A C; Hudson, N I; Asseng, S
2016-01-01
We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we...... evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...
Instrument Response Modeling and Simulation for the GLAST Burst Monitor
International Nuclear Information System (INIS)
Kippen, R. M.; Hoover, A. S.; Wallace, M. S.; Pendleton, G. N.; Meegan, C. A.; Fishman, G. J.; Wilson-Hodge, C. A.; Kouveliotou, C.; Lichti, G. G.; Kienlin, A. von; Steinle, H.; Diehl, R.; Greiner, J.; Preece, R. D.; Connaughton, V.; Briggs, M. S.; Paciesas, W. S.; Bhat, P. N.
2007-01-01
The GLAST Burst Monitor (GBM) is designed to provide wide field of view observations of gamma-ray bursts and other fast transient sources in the energy range 10 keV to 30 MeV. The GBM is composed of several unshielded and uncollimated scintillation detectors (twelve NaI and two BGO) that are widely dispersed about the GLAST spacecraft. As a result, reconstructing source locations, energy spectra, and temporal properties from GBM data requires detailed knowledge of the detectors' response to both direct radiation as well as that scattered from the spacecraft and Earth's atmosphere. This full GBM instrument response will be captured in the form of a response function database that is derived from computer modeling and simulation. The simulation system is based on the GEANT4 Monte Carlo radiation transport simulation toolset, and is being extensively validated against calibrated experimental GBM data. We discuss the architecture of the GBM simulation and modeling system and describe how its products will be used for analysis of observed GBM data. Companion papers describe the status of validating the system
An instrument dedicated for modelling of pulmonary radiotherapy
International Nuclear Information System (INIS)
Niezink, Anne G.H.; Dollekamp, Nienke J.; Elzinga, Harriet J.; Borger, Denise; Boer, Eduard J.H.; Ubbels, Jan F.; Woltman-van Iersel, Marleen; Leest, Annija H.D. van der; Beijert, Max; Groen, Harry J.M.; Kraan, Jan; Hiltermann, Thijo J.N.; Wekken, Anthonie J. van der; Putten, John W.G. van; Rutgers, Steven R.; Pieterman, Remge M.; Hosson, Sander M. de; Roenhorst, Anke W.J.; Langendijk, Johannes A.; Widder, Joachim
2015-01-01
Background and purpose: Radiotherapy plays a pivotal role in lung cancer treatment. Selection of patients for new (radio)therapeutic options aiming at improving outcomes requires reliable and validated prediction models. We present the implementation of a prospective platform for evaluation and development of lung radiotherapy (proPED-LUNG) as an instrument enabling multidimensional predictive modelling. Materials and methods: ProPED-LUNG was designed to comprise relevant baseline and follow up data of patients receiving pulmonary radiotherapy with curative intent. Patient characteristics, diagnostic and staging information, treatment parameters including full dose–volume-histograms, tumour control, survival, and toxicity are scored. Besides physician-rated data, a range of patient-rated data regarding symptoms and health-related quality-of-life are collected. Results: After 18 months of accrual, 315 patients have been included (accrual rate, 18 per month). Of the first hundred patients included, 70 received conformal (chemo)radiotherapy and 30 underwent stereotactic radiotherapy. Compliance at 3 and 6 months follow-up was 96–100% for patient-rated, and 81–94% for physician-rated assessments. For data collection, 0.4 FTE were allocated in a 183 FTE department (0.2%). Conclusions: ProPED-LUNG is feasible with high compliance rates and yields a large amount of high quality prospective disease-related, treatment-related, patient- and physician-rated data which can be used to evaluate new developments in pulmonary radiotherapy
ABOUT PSYCHOLOGICAL VARIABLES IN APPLICATION SCORING MODELS
Directory of Open Access Journals (Sweden)
Pablo Rogers
2015-01-01
Full Text Available The purpose of this study is to investigate the contribution of psychological variables and scales suggested by Economic Psychology in predicting individuals’ default. Therefore, a sample of 555 individuals completed a self-completion questionnaire, which was composed of psychological variables and scales. By adopting the methodology of the logistic regression, the following psychological and behavioral characteristics were found associated with the group of individuals in default: a negative dimensions related to money (suffering, inequality and conflict; b high scores on the self-efficacy scale, probably indicating a greater degree of optimism and over-confidence; c buyers classified as compulsive; d individuals who consider it necessary to give gifts to children and friends on special dates, even though many people consider this a luxury; e problems of self-control identified by individuals who drink an average of more than four glasses of alcoholic beverage a day.
Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability
Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos
2016-01-01
We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.
Variable selection in Logistic regression model with genetic algorithm.
Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi
2018-02-01
Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.
A variable stiffness mechanism for steerable percutaneous instruments: integration in a needle.
De Falco, Iris; Culmone, Costanza; Menciassi, Arianna; Dankelman, Jenny; van den Dobbelsteen, John J
2018-06-04
Needles are advanced tools commonly used in minimally invasive medical procedures. The accurate manoeuvrability of flexible needles through soft tissues is strongly determined by variations in tissue stiffness, which affects the needle-tissue interaction and thus causes needle deflection. This work presents a variable stiffness mechanism for percutaneous needles capable of compensating for variations in tissue stiffness and undesirable trajectory changes. It is composed of compliant segments and rigid plates alternately connected in series and longitudinally crossed by four cables. The tensioning of the cables allows the omnidirectional steering of the tip and the stiffness tuning of the needle. The mechanism was tested separately under different working conditions, demonstrating a capability to exert up to 3.6 N. Afterwards, the mechanism was integrated into a needle, and the overall device was tested in gelatine phantoms simulating the stiffness of biological tissues. The needle demonstrated the capability to vary deflection (from 11.6 to 4.4 mm) and adapt to the inhomogeneity of the phantoms (from 21 to 80 kPa) depending on the activation of the variable stiffness mechanism. Graphical abstract ᅟ.
Fixed transaction costs and modelling limited dependent variables
Hempenius, A.L.
1994-01-01
As an alternative to the Tobit model, for vectors of limited dependent variables, I suggest a model, which follows from explicitly using fixed costs, if appropriate of course, in the utility function of the decision-maker.
Coevolution of variability models and related software artifacts
DEFF Research Database (Denmark)
Passos, Leonardo; Teixeira, Leopoldo; Dinztner, Nicolas
2015-01-01
models coevolve with other artifact types, we study a large and complex real-world variant-rich software system: the Linux kernel. Specifically, we extract variability-coevolution patterns capturing changes in the variability model of the Linux kernel with subsequent changes in Makefiles and C source...
Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables
Henson, Robert A.; Templin, Jonathan L.; Willse, John T.
2009-01-01
This paper uses log-linear models with latent variables (Hagenaars, in "Loglinear Models with Latent Variables," 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for…
Variable Selection for Regression Models of Percentile Flows
Fouad, G.
2017-12-01
Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high
Variability aware compact model characterization for statistical circuit design optimization
Qiao, Ying; Qian, Kun; Spanos, Costas J.
2012-03-01
Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose an efficient variabilityaware compact model characterization methodology based on the linear propagation of variance. Hierarchical spatial variability patterns of selected compact model parameters are directly calculated from transistor array test structures. This methodology has been implemented and tested using transistor I-V measurements and the EKV-EPFL compact model. Calculation results compare well to full-wafer direct model parameter extractions. Further studies are done on the proper selection of both compact model parameters and electrical measurement metrics used in the method.
Variable amplitude fatigue, modelling and testing
International Nuclear Information System (INIS)
Svensson, Thomas.
1993-01-01
Problems related to metal fatigue modelling and testing are here treated in four different papers. In the first paper different views of the subject are summarised in a literature survey. In the second paper a new model for fatigue life is investigated. Experimental results are established which are promising for further development of the mode. In the third paper a method is presented that generates a stochastic process, suitable to fatigue testing. The process is designed in order to resemble certain fatigue related features in service life processes. In the fourth paper fatigue problems in transport vibrations are treated
modelling relationship between rainfall variability and yields
African Journals Online (AJOL)
, S. and ... factors to rice yield. Adebayo and Adebayo (1997) developed double log multiple regression model to predict rice yield in Adamawa State, Nigeria. The general form of .... the second are the crop yield/values for millet and sorghum ...
Directory of Open Access Journals (Sweden)
Rafdzah Zaki
2013-06-01
Full Text Available Objective(s: Reliability measures precision or the extent to which test results can be replicated. This is the first ever systematic review to identify statistical methods used to measure reliability of equipment measuring continuous variables. This studyalso aims to highlight the inappropriate statistical method used in the reliability analysis and its implication in the medical practice. Materials and Methods: In 2010, five electronic databases were searched between 2007 and 2009 to look for reliability studies. A total of 5,795 titles were initially identified. Only 282 titles were potentially related, and finally 42 fitted the inclusion criteria. Results: The Intra-class Correlation Coefficient (ICC is the most popular method with 25 (60% studies having used this method followed by the comparing means (8 or 19%. Out of 25 studies using the ICC, only 7 (28% reported the confidence intervals and types of ICC used. Most studies (71% also tested the agreement of instruments. Conclusion: This study finds that the Intra-class Correlation Coefficient is the most popular method used to assess the reliability of medical instruments measuring continuous outcomes. There are also inappropriate applications and interpretations of statistical methods in some studies. It is important for medical researchers to be aware of this issue, and be able to correctly perform analysis in reliability studies.
Dynamic Models of Instruments Using Rotating Unbalanced Masses
Hung, John Y.; Gallaspy, Jason M.; Bishop, Carlee A.
1998-01-01
The motion of telescopes, satellites, and other flight bodies have been controlled by various means in the past. For example, gimbal mounted devices can use electric motors to produce pointing and scanning motions. Reaction wheels, control moment gyros, and propellant-charged reaction jets are other technologies that have also been used. Each of these methods has its advantages, but all actuator systems used in a flight environment face the challenges of minimizing weight, reducing energy consumption, and maximizing reliability. Recently, Polites invented and patented the Rotating Unbalanced Mass (RUM) device as a means for generation scanning motion on flight experiments. RUM devices together with traditional servomechanisms have been successfully used to generate various scanning motions: linear, raster, and circular. The basic principle can be described: A RUM rotating at constant angular velocity exerts a cyclic centrifugal force on the instrument or main body, thus producing a periodic scanning motion. A system of RUM devices exerts no reaction forces on the main body, requires very little energy to rotate the RUMS, and is simple to construct. These are significant advantages over electric motors, reaction wheels, and control moment gyroscopes. Although the RUM device very easily produces scanning motion, an auxiliary control system has been required to maintain the proper orientation, or pointing of the main body. It has been suggested that RUM devices can be used to control pointing dynamics, as well as generate the desired periodic scanning motion. The idea is that the RUM velocity will not be kept constant, but will vary over the period of one RUM rotation. The thought is that the changing angular velocity produces a centrifugal force having time-varying magnitude and direction. The scope of this ongoing research project is to study the pointing control concept, and recommend a direction of study for advanced pointing control using only RUM devices. This
The Standard, Power, and Color Model of Instrument Combination in Romantic-Era Symphonic Works
Directory of Open Access Journals (Sweden)
Randolph Johnson
2011-08-01
Full Text Available The Standard, Power, and Color (SPC model describes the nexus between musical instrument combination patterns and expressive goals in music. Instruments within each SPC group tend to attract each other and work as a functional unit to create orchestral gestures. Standard instruments establish a timbral groundwork; Power instruments create contrast through loud dynamic climaxes; and Color instruments catch listeners’ attention by means of their sparing use. Examples within these three groups include violin (Standard, piccolo (Power, and harp (Color. The SPC theory emerges from analyses of nineteenth-century symphonic works. Multidimensional scaling analysis of instrument combination frequencies maps instrument relationships; hierarchical clustering analysis indicates three SPC groups within the map. The SPC characterization is found to be moderately robust through the results of hypothesis testing: (1 Color instruments are included less often in symphonic works; (2 when Color instruments are included, they perform less often than the average instrument; and (3 Color and non-Color instruments have equal numbers of solo occurrences. Additionally, (4 Power instruments are positively associated with louder dynamic levels; and (5 when Power instruments are present in the musical texture, the pitch range spanned by the entire orchestra does not become more extreme.
Directory of Open Access Journals (Sweden)
Lara Gitto
2015-08-01
Full Text Available Background Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people’s quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression, might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Methods Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females, aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status and socio
Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez
2015-04-16
Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people's quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors (such as education
Glass, Alexis; Fukudome, Kimitoshi
2004-12-01
A sound recording of a plucked string instrument is encoded and resynthesized using two stages of prediction. In the first stage of prediction, a simple physical model of a plucked string is estimated and the instrument excitation is obtained. The second stage of prediction compensates for the simplicity of the model in the first stage by encoding either the instrument excitation or the model error using warped linear prediction. These two methods of compensation are compared with each other, and to the case of single-stage warped linear prediction, adjustments are introduced, and their applications to instrument synthesis and MPEG4's audio compression within the structured audio format are discussed.
A geometric model for magnetizable bodies with internal variables
Directory of Open Access Journals (Sweden)
Restuccia, L
2005-11-01
Full Text Available In a geometrical framework for thermo-elasticity of continua with internal variables we consider a model of magnetizable media previously discussed and investigated by Maugin. We assume as state variables the magnetization together with its space gradient, subjected to evolution equations depending on both internal and external magnetic fields. We calculate the entropy function and necessary conditions for its existence.
Yu, Ping; Qian, Siyu
2018-01-01
Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: system quality, information quality, service quality, use, user satisfaction and net benefits. Two variables training and self-efficacy were also incorporated into the model. A questionnaire survey instrument was designed to measure the eight variables in the model. After a pilot test, the measurement scale was used to collect data from 243 nursing staff members in 10 residential aged care homes belonging to three management groups in Australia. Partial least squares path modeling was conducted to validate the model. The validated EHR systems success model predicts the impact of the four antecedent variables-training, self-efficacy, system quality and information quality-on the net benefits, the indicator of EHR systems success, through the intermittent variables use and user satisfaction. A 24-item measurement scale was developed to quantitatively evaluate the performance of an EHR system. The parsimonious EHR systems success model and the measurement scale can be used to benchmark EHR systems success across organizations and units and over time.
Verification of models for ballistic movement time and endpoint variability.
Lin, Ray F; Drury, Colin G
2013-01-01
A hand control movement is composed of several ballistic movements. The time required in performing a ballistic movement and its endpoint variability are two important properties in developing movement models. The purpose of this study was to test potential models for predicting these two properties. Twelve participants conducted ballistic movements of specific amplitudes using a drawing tablet. The measured data of movement time and endpoint variability were then used to verify the models. This study was successful with Hoffmann and Gan's movement time model (Hoffmann, 1981; Gan and Hoffmann 1988) predicting more than 90.7% data variance for 84 individual measurements. A new theoretically developed ballistic movement variability model, proved to be better than Howarth, Beggs, and Bowden's (1971) model, predicting on average 84.8% of stopping-variable error and 88.3% of aiming-variable errors. These two validated models will help build solid theoretical movement models and evaluate input devices. This article provides better models for predicting end accuracy and movement time of ballistic movements that are desirable in rapid aiming tasks, such as keying in numbers on a smart phone. The models allow better design of aiming tasks, for example button sizes on mobile phones for different user populations.
Interdecadal variability in a global coupled model
International Nuclear Information System (INIS)
Storch, J.S. von.
1994-01-01
Interdecadal variations are studied in a 325-year simulation performed by a coupled atmosphere - ocean general circulation model. The patterns obtained in this study may be considered as characteristic patterns for interdecadal variations. 1. The atmosphere: Interdecadal variations have no preferred time scales, but reveal well-organized spatial structures. They appear as two modes, one is related with variations of the tropical easterlies and the other with the Southern Hemisphere westerlies. Both have red spectra. The amplitude of the associated wind anomalies is largest in the upper troposphere. The associated temperature anomalies are in thermal-wind balance with the zonal winds and are out-of-phase between the troposphere and the lower stratosphere. 2. The Pacific Ocean: The dominant mode in the Pacific appears to be wind-driven in the midlatitudes and is related to air-sea interaction processes during one stage of the oscillation in the tropics. Anomalies of this mode propagate westward in the tropics and the northward (southwestward) in the North (South) Pacific on a time scale of about 10 to 20 years. (orig.)
Spatial variability and parametric uncertainty in performance assessment models
International Nuclear Information System (INIS)
Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo
2011-01-01
The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)
Using structural equation modeling to investigate relationships among ecological variables
Malaeb, Z.A.; Kevin, Summers J.; Pugesek, B.H.
2000-01-01
Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude -0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0
Multiple Imputation of Predictor Variables Using Generalized Additive Models
de Jong, Roel; van Buuren, Stef; Spiess, Martin
2016-01-01
The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The
Higher-dimensional cosmological model with variable gravitational ...
Indian Academy of Sciences (India)
We have studied five-dimensional homogeneous cosmological models with variable and bulk viscosity in Lyra geometry. Exact solutions for the field equations have been obtained and physical properties of the models are discussed. It has been observed that the results of new models are well within the observational ...
A variable-order fractal derivative model for anomalous diffusion
Directory of Open Access Journals (Sweden)
Liu Xiaoting
2017-01-01
Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
Irincheeva, Irina
2012-08-03
We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.
2012-01-01
We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.
Preliminary Multi-Variable Cost Model for Space Telescopes
Stahl, H. Philip; Hendrichs, Todd
2010-01-01
Parametric cost models are routinely used to plan missions, compare concepts and justify technology investments. This paper reviews the methodology used to develop space telescope cost models; summarizes recently published single variable models; and presents preliminary results for two and three variable cost models. Some of the findings are that increasing mass reduces cost; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and technology development as a function of time reduces cost at the rate of 50% per 17 years.
Instrumental variable analysis
Stel, Vianda S.; Dekker, Friedo W.; Zoccali, Carmine; Jager, Kitty J.
2013-01-01
The main advantage of the randomized controlled trial (RCT) is the random assignment of treatment that prevents selection by prognosis. Nevertheless, only few RCTs can be performed given their high cost and the difficulties in conducting such studies. Therefore, several analytical methods for
Alvine, Gregory F; Swain, James M; Asher, Marc A; Burton, Douglas C
2004-08-01
The controversy of burst fracture surgical management is addressed in this retrospective case study and literature review. The series consisted of 40 consecutive patients, index included, with 41 fractures treated with stiff, limited segment transpedicular bone-anchored instrumentation and arthrodesis from 1987 through 1994. No major acute complications such as death, paralysis, or infection occurred. For the 30 fractures with pre- and postoperative computed tomography studies, spinal canal compromise was 61% and 32%, respectively. Neurologic function improved in 7 of 14 patients (50%) and did not worsen in any. The principal problem encountered was screw breakage, which occurred in 16 of the 41 (39%) instrumented fractures. As we have previously reported, transpedicular anterior bone graft augmentation significantly decreased variable screw placement (VSP) implant breakage. However, it did not prevent Isola implant breakage in two-motion segment constructs. Compared with VSP, Isola provided better sagittal plane realignment and constructs that have been found to be significantly stiffer. Unplanned reoperation was necessary in 9 of the 40 patients (23%). At 1- and 2-year follow-up, 95% and 79% of patients were available for study, and a satisfactory outcome was achieved in 84% and 79%, respectively. These satisfaction and reoperation rates are consistent with the literature of the time. Based on these observations and the loads to which implant constructs are exposed following posterior realignment and stabilization of burst fractures, we recommend that three- or four-motion segment constructs, rather than two motion, be used. To save valuable motion segments, planned construct shortening can be used. An alternative is sequential or staged anterior corpectomy and structural grafting.
Bayesian approach to errors-in-variables in regression models
Rozliman, Nur Aainaa; Ibrahim, Adriana Irawati Nur; Yunus, Rossita Mohammad
2017-05-01
In many applications and experiments, data sets are often contaminated with error or mismeasured covariates. When at least one of the covariates in a model is measured with error, Errors-in-Variables (EIV) model can be used. Measurement error, when not corrected, would cause misleading statistical inferences and analysis. Therefore, our goal is to examine the relationship of the outcome variable and the unobserved exposure variable given the observed mismeasured surrogate by applying the Bayesian formulation to the EIV model. We shall extend the flexible parametric method proposed by Hossain and Gustafson (2009) to another nonlinear regression model which is the Poisson regression model. We shall then illustrate the application of this approach via a simulation study using Markov chain Monte Carlo sampling methods.
Energy Technology Data Exchange (ETDEWEB)
Moberg, Anders; Gouirand, Isabelle; Schoning, Kristian; Wohlfarth, Barbara [Stockholm Univ. (Sweden). Dept. of Physical Geography and Quaternary Geology; Kjellstroem, Erik; Rummukainen, Markku [Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden). Rossby Centre; Jong, Rixt de [Lund Univ. (Sweden). Dept. of Quaternary Geology; Linderholm, Hans [Goeteborg Univ. (Sweden). Dept. of Earth Sciences; Zorita, Eduardo [GKSS Research Centre, Geesthacht (Germany)
2006-12-15
Knowledge about climatic variations is essential for SKB in its safety assessments of a geological repository for spent nuclear waste. There is therefore a need for information about possible future climatic variations under a range of possible climatic states. However, predictions of future climate in any deterministic sense are still beyond our reach. We can, nevertheless, try to estimate the magnitude of future climate variability and change due to natural forcing factors, by means of inferences drawn from natural climate variability in the past. Indeed, the climate of the future will be shaped by the sum of natural and anthropogenic climate forcing, as well as the internal climate variability. The aim here is to review and analyse the knowledge about Swedish climate variability, essentially during the past millennium. Available climate proxy data and long instrumental records provide empirical information on past climatic changes. We also demonstrate how climate modelling can be used to extend such knowledge. We use output from a global climate model driven with reconstructed radiative forcings (solar, volcanic and greenhouse gas forcing), to provide boundary conditions for a regional climate model. The regional model provides more details of the climate than the global model, and we develop a simulated climate history for Sweden that is complete in time and space and physically consistent. We use output from a regional model simulation for long periods in the last millennium, to study annual mean temperature, precipitation and runoff for the northern and southern parts of Sweden. The simulated data are used to place corresponding instrumental records for the 20th century into a plausible historical perspective. We also use output from the regional model to study how the frequency distribution of the daily temperature, precipitation, runoff and evaporation at Forsmark and Oskarshamn could have varied between unusually warm and cold 30-year periods during the
International Nuclear Information System (INIS)
Moberg, Anders; Gouirand, Isabelle; Schoning, Kristian; Wohlfarth, Barbara
2006-12-01
Knowledge about climatic variations is essential for SKB in its safety assessments of a geological repository for spent nuclear waste. There is therefore a need for information about possible future climatic variations under a range of possible climatic states. However, predictions of future climate in any deterministic sense are still beyond our reach. We can, nevertheless, try to estimate the magnitude of future climate variability and change due to natural forcing factors, by means of inferences drawn from natural climate variability in the past. Indeed, the climate of the future will be shaped by the sum of natural and anthropogenic climate forcing, as well as the internal climate variability. The aim here is to review and analyse the knowledge about Swedish climate variability, essentially during the past millennium. Available climate proxy data and long instrumental records provide empirical information on past climatic changes. We also demonstrate how climate modelling can be used to extend such knowledge. We use output from a global climate model driven with reconstructed radiative forcings (solar, volcanic and greenhouse gas forcing), to provide boundary conditions for a regional climate model. The regional model provides more details of the climate than the global model, and we develop a simulated climate history for Sweden that is complete in time and space and physically consistent. We use output from a regional model simulation for long periods in the last millennium, to study annual mean temperature, precipitation and runoff for the northern and southern parts of Sweden. The simulated data are used to place corresponding instrumental records for the 20th century into a plausible historical perspective. We also use output from the regional model to study how the frequency distribution of the daily temperature, precipitation, runoff and evaporation at Forsmark and Oskarshamn could have varied between unusually warm and cold 30-year periods during the
A model for AGN variability on multiple time-scales
Sartori, Lia F.; Schawinski, Kevin; Trakhtenbrot, Benny; Caplar, Neven; Treister, Ezequiel; Koss, Michael J.; Urry, C. Megan; Zhang, C. E.
2018-05-01
We present a framework to link and describe active galactic nuclei (AGN) variability on a wide range of time-scales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different time-scales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio (L/LEdd) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the L/LEdd distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different time-scales, therefore providing new insights into AGN variability and black hole growth phenomena.
Brazdil, Rudolf
2016-04-01
Hydrological and meteorological extremes (HMEs) in Central Europe during the past 500 years can be reconstructed based on instrumental and documentary data. Documentary data about weather and related phenomena represent the basic source of information for historical climatology and hydrology, dealing with reconstruction of past climate and HMEs, their perception and impacts on human society. The paper presents the basic distribution of documentary data on (i) direct descriptions of HMEs and their proxies on the one hand and on (ii) individual and institutional data sources on the other. Several groups of documentary evidence such as narrative written records (annals, chronicles, memoirs), visual daily weather records, official and personal correspondence, special prints, financial and economic records (with particular attention to taxation data), newspapers, pictorial documentation, chronograms, epigraphic data, early instrumental observations, early scientific papers and communications are demonstrated with respect to extraction of information about HMEs, which concerns usually of their occurrence, severity, seasonality, meteorological causes, perception and human impacts. The paper further presents the analysis of 500-year variability of floods, droughts and windstorms on the base of series, created by combination of documentary and instrumental data. Results, advantages and drawbacks of such approach are documented on the examples from the Czech Lands. The analysis of floods concentrates on the River Vltava (Prague) and the River Elbe (Děčín) which show the highest frequency of floods occurring in the 19th century (mainly of winter synoptic type) and in the second half of the 16th century (summer synoptic type). Reported are also the most disastrous floods (August 1501, March and August 1598, February 1655, June 1675, February 1784, March 1845, February 1862, September 1890, August 2002) and the European context of floods in the severe winter 1783/84. Drought
Flute-like musical instruments: A toy model investigated through numerical continuation
Terrien, Soizic; Vergez, Christophe; Fabre, Benoît
2013-07-01
Self-sustained musical instruments (bowed string, woodwind and brass instruments) can be modelled by nonlinear lumped dynamical systems. Among these instruments, flutes and flue organ pipes present the particularity to be modelled as a delay dynamical system. In this paper, such a system, a toy model of flute-like instruments, is studied using numerical continuation. Equilibrium and periodic solutions are explored with respect to the blowing pressure, with focus on amplitude and frequency evolutions along the different solution branches, as well as "jumps" between periodic solution branches. The influence of a second model parameter (namely the inharmonicity) on the behaviour of the system is addressed. It is shown that harmonicity plays a key role in the presence of hysteresis or quasiperiodic regime. Throughout the paper, experimental results on a real instrument are presented to illustrate various phenomena, and allow some qualitative comparisons with numerical results.
Loss given default models incorporating macroeconomic variables for credit cards
Crook, J.; Bellotti, T.
2012-01-01
Based on UK data for major retail credit cards, we build several models of Loss Given Default based on account level data, including Tobit, a decision tree model, a Beta and fractional logit transformation. We find that Ordinary Least Squares models with macroeconomic variables perform best for forecasting Loss Given Default at the account and portfolio levels on independent hold-out data sets. The inclusion of macroeconomic conditions in the model is important, since it provides a means to m...
Perception and Modeling of Affective Qualities of Musical Instrument Sounds across Pitch Registers.
McAdams, Stephen; Douglas, Chelsea; Vempala, Naresh N
2017-01-01
Composers often pick specific instruments to convey a given emotional tone in their music, partly due to their expressive possibilities, but also due to their timbres in specific registers and at given dynamic markings. Of interest to both music psychology and music informatics from a computational point of view is the relation between the acoustic properties that give rise to the timbre at a given pitch and the perceived emotional quality of the tone. Musician and nonmusician listeners were presented with 137 tones produced at a fixed dynamic marking (forte) playing tones at pitch class D# across each instrument's entire pitch range and with different playing techniques for standard orchestral instruments drawn from the brass, woodwind, string, and pitched percussion families. They rated each tone on six analogical-categorical scales in terms of emotional valence (positive/negative and pleasant/unpleasant), energy arousal (awake/tired), tension arousal (excited/calm), preference (like/dislike), and familiarity. Linear mixed models revealed interactive effects of musical training, instrument family, and pitch register, with non-linear relations between pitch register and several dependent variables. Twenty-three audio descriptors from the Timbre Toolbox were computed for each sound and analyzed in two ways: linear partial least squares regression (PLSR) and nonlinear artificial neural net modeling. These two analyses converged in terms of the importance of various spectral, temporal, and spectrotemporal audio descriptors in explaining the emotion ratings, but some differences also emerged. Different combinations of audio descriptors make major contributions to the three emotion dimensions, suggesting that they are carried by distinct acoustic properties. Valence is more positive with lower spectral slopes, a greater emergence of strong partials, and an amplitude envelope with a sharper attack and earlier decay. Higher tension arousal is carried by brighter sounds
Interacting ghost dark energy models with variable G and Λ
Sadeghi, J.; Khurshudyan, M.; Movsisyan, A.; Farahani, H.
2013-12-01
In this paper we consider several phenomenological models of variable Λ. Model of a flat Universe with variable Λ and G is accepted. It is well known, that varying G and Λ gives rise to modified field equations and modified conservation laws, which gives rise to many different manipulations and assumptions in literature. We will consider two component fluid, which parameters will enter to Λ. Interaction between fluids with energy densities ρ1 and ρ2 assumed as Q = 3Hb(ρ1+ρ2). We have numerical analyze of important cosmological parameters like EoS parameter of the composed fluid and deceleration parameter q of the model.
Variable selection for mixture and promotion time cure rate models.
Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng
2016-11-16
Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.
a modified intervention model for gross domestic product variable
African Journals Online (AJOL)
observations on a variable that have been measured at ... assumption that successive values in the data file ... these interventions, one may try to evaluate the effect of ... generalized series by comparing the distinct periods. A ... the process of checking for adequacy of the model based .... As a result, the model's forecast will.
Simple model for crop photosynthesis in terms of weather variables ...
African Journals Online (AJOL)
A theoretical mathematical model for describing crop photosynthetic rate in terms of the weather variables and crop characteristics is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of possible photosynthetic rate permitted by the different weather elements or crop architecture.
Model for expressing leaf photosynthesis in terms of weather variables
African Journals Online (AJOL)
A theoretical mathematical model for describing photosynthesis in individual leaves in terms of weather variables is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of potential photosynthetic rate permitted by the different environmental elements. These parameters are useful ...
Efficient Business Service Consumption by Customization with Variability Modelling
Directory of Open Access Journals (Sweden)
Michael Stollberg
2010-07-01
Full Text Available The establishment of service orientation in industry determines the need for efficient engineering technologies that properly support the whole life cycle of service provision and consumption. A central challenge is adequate support for the efficient employment of komplex services in their individual application context. This becomes particularly important for large-scale enterprise technologies where generic services are designed for reuse in several business scenarios. In this article we complement our work regarding Service Variability Modelling presented in a previous publication. There we presented an approach for the customization of services for individual application contexts by creating simplified variants, based on model-driven variability management. That work presents our revised service variability metamodel, new features of the variability tools and an applicability study, which reveals that substantial improvements on the efficiency of standard business service consumption under both usability and economic aspects can be achieved.
Staley, James R.
2017-01-01
ABSTRACT Mendelian randomization, the use of genetic variants as instrumental variables (IV), can test for and estimate the causal effect of an exposure on an outcome. Most IV methods assume that the function relating the exposure to the expected value of the outcome (the exposure‐outcome relationship) is linear. However, in practice, this assumption may not hold. Indeed, often the primary question of interest is to assess the shape of this relationship. We present two novel IV methods for investigating the shape of the exposure‐outcome relationship: a fractional polynomial method and a piecewise linear method. We divide the population into strata using the exposure distribution, and estimate a causal effect, referred to as a localized average causal effect (LACE), in each stratum of population. The fractional polynomial method performs metaregression on these LACE estimates. The piecewise linear method estimates a continuous piecewise linear function, the gradient of which is the LACE estimate in each stratum. Both methods were demonstrated in a simulation study to estimate the true exposure‐outcome relationship well, particularly when the relationship was a fractional polynomial (for the fractional polynomial method) or was piecewise linear (for the piecewise linear method). The methods were used to investigate the shape of relationship of body mass index with systolic blood pressure and diastolic blood pressure. PMID:28317167
Directory of Open Access Journals (Sweden)
Ching-Chih Lee
Full Text Available BACKGROUND: To compare the infection rates between cetuximab-treated patients with head and neck cancers (HNC and untreated patients. METHODOLOGY: A national cohort of 1083 HNC patients identified in 2010 from the Taiwan National Health Insurance Research Database was established. After patients were followed for one year, propensity score analysis and instrumental variable analysis were performed to assess the association between cetuximab therapy and the infection rates. RESULTS: HNC patients receiving cetuximab (n = 158 were older, had lower SES, and resided more frequently in rural areas as compared to those without cetuximab therapy. 125 patients, 32 (20.3% in the group using cetuximab and 93 (10.1% in the group not using it presented infections. The propensity score analysis revealed a 2.3-fold (adjusted odds ratio [OR] = 2.27; 95% CI, 1.46-3.54; P = 0.001 increased risk for infection in HNC patients treated with cetuximab. However, using IVA, the average treatment effect of cetuximab was not statistically associated with increased risk of infection (OR, 0.87; 95% CI, 0.61-1.14. CONCLUSIONS: Cetuximab therapy was not statistically associated with infection rate in HNC patients. However, older HNC patients using cetuximab may incur up to 33% infection rate during one year. Particular attention should be given to older HNC patients treated with cetuximab.
Modelling the effects of spatial variability on radionuclide migration
International Nuclear Information System (INIS)
1998-01-01
The NEA workshop reflect the present status in national waste management program, specifically in spatial variability and performance assessment of geologic disposal sites for deed repository system the four sessions were: Spatial Variability: Its Definition and Significance to Performance Assessment and Site Characterisation; Experience with the Modelling of Radionuclide Migration in the Presence of Spatial Variability in Various Geological Environments; New Areas for Investigation: Two Personal Views; What is Wanted and What is Feasible: Views and Future Plans in Selected Waste Management Organisations. The 26 papers presented on the four oral sessions and on the poster session have been abstracted and indexed individually for the INIS database. (R.P.)
From Transition Systems to Variability Models and from Lifted Model Checking Back to UPPAAL
DEFF Research Database (Denmark)
Dimovski, Aleksandar; Wasowski, Andrzej
2017-01-01
efficient lifted (family-based) model checking for real-time variability models. This reduces the cost of maintaining specialized family-based real-time model checkers. Real-time variability models can be model checked using the standard UPPAAL. We have implemented abstractions as syntactic source...
Internal variability of a 3-D ocean model
Directory of Open Access Journals (Sweden)
Bjarne Büchmann
2016-11-01
Full Text Available The Defence Centre for Operational Oceanography runs operational forecasts for the Danish waters. The core setup is a 60-layer baroclinic circulation model based on the General Estuarine Transport Model code. At intervals, the model setup is tuned to improve ‘model skill’ and overall performance. It has been an area of concern that the uncertainty inherent to the stochastical/chaotic nature of the model is unknown. Thus, it is difficult to state with certainty that a particular setup is improved, even if the computed model skill increases. This issue also extends to the cases, where the model is tuned during an iterative process, where model results are fed back to improve model parameters, such as bathymetry.An ensemble of identical model setups with slightly perturbed initial conditions is examined. It is found that the initial perturbation causes the models to deviate from each other exponentially fast, causing differences of several PSUs and several kelvin within a few days of simulation. The ensemble is run for a full year, and the long-term variability of salinity and temperature is found for different regions within the modelled area. Further, the developing time scale is estimated for each region, and great regional differences are found – in both variability and time scale. It is observed that periods with very high ensemble variability are typically short-term and spatially limited events.A particular event is examined in detail to shed light on how the ensemble ‘behaves’ in periods with large internal model variability. It is found that the ensemble does not seem to follow any particular stochastic distribution: both the ensemble variability (standard deviation or range as well as the ensemble distribution within that range seem to vary with time and place. Further, it is observed that a large spatial variability due to mesoscale features does not necessarily correlate to large ensemble variability. These findings bear
Understanding and forecasting polar stratospheric variability with statistical models
Directory of Open Access Journals (Sweden)
C. Blume
2012-07-01
Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely the multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. The period from 2005 to 2011 can be hindcasted to a certain extent, where MLP performs significantly better than the remaining models. However, variability remains that cannot be statistically hindcasted within the current framework, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a winter 2011/12 with warm and weak vortex conditions. A vortex breakdown is predicted for late January, early February 2012.
Liu, Xiufeng
2010-01-01
This book meets a demand in the science education community for a comprehensive and introductory measurement book in science education. It describes measurement instruments reported in refereed science education research journals, and introduces the Rasch modeling approach to developing measurement instruments in common science assessment domains,…
Directory of Open Access Journals (Sweden)
Buckley Norman
2010-10-01
Full Text Available Abstract Background The Internet is used increasingly by providers as a tool for disseminating pain-related health information and by patients as a resource about health conditions and treatment options. However, health information on the Internet remains unregulated and varies in quality, accuracy and readability. The objective of this study was to determine the quality of pain websites, and explain variability in quality and readability between pain websites. Methods Five key terms (pain, chronic pain, back pain, arthritis, and fibromyalgia were entered into the Google, Yahoo and MSN search engines. Websites were assessed using the DISCERN instrument as a quality index. Grade level readability ratings were assessed using the Flesch-Kincaid Readability Algorithm. Univariate (using alpha = 0.20 and multivariable regression (using alpha = 0.05 analyses were used to explain the variability in DISCERN scores and grade level readability using potential for commercial gain, health related seals of approval, language(s and multimedia features as independent variables. Results A total of 300 websites were assessed, 21 excluded in accordance with the exclusion criteria and 110 duplicate websites, leaving 161 unique sites. About 6.8% (11/161 websites of the websites offered patients' commercial products for their pain condition, 36.0% (58/161 websites had a health related seal of approval, 75.8% (122/161 websites presented information in English only and 40.4% (65/161 websites offered an interactive multimedia experience. In assessing the quality of the unique websites, of a maximum score of 80, the overall average DISCERN Score was 55.9 (13.6 and readability (grade level of 10.9 (3.9. The multivariable regressions demonstrated that website seals of approval (P = 0.015 and potential for commercial gain (P = 0.189 were contributing factors to higher DISCERN scores, while seals of approval (P = 0.168 and interactive multimedia (P = 0.244 contributed to
Mediterranean climate modelling: variability and climate change scenarios
International Nuclear Information System (INIS)
Somot, S.
2005-12-01
Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)
Plasticity models of material variability based on uncertainty quantification techniques
Energy Technology Data Exchange (ETDEWEB)
Jones, Reese E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Rizzi, Francesco [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Boyce, Brad [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Templeton, Jeremy Alan [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ostien, Jakob [Sandia National Lab. (SNL-CA), Livermore, CA (United States)
2017-11-01
The advent of fabrication techniques like additive manufacturing has focused attention on the considerable variability of material response due to defects and other micro-structural aspects. This variability motivates the development of an enhanced design methodology that incorporates inherent material variability to provide robust predictions of performance. In this work, we develop plasticity models capable of representing the distribution of mechanical responses observed in experiments using traditional plasticity models of the mean response and recently developed uncertainty quantification (UQ) techniques. Lastly, we demonstrate that the new method provides predictive realizations that are superior to more traditional ones, and how these UQ techniques can be used in model selection and assessing the quality of calibrated physical parameters.
Instrument evaluation no. 11. ESI nuclear model 271 C contamination monitor
International Nuclear Information System (INIS)
Burgess, P.H.; Iles, W.J.
1978-06-01
The various radiations encountered in radiological protection cover a wide range of energies and radiation measurements have to he carried out under an equally broad spectrum of environmental conditions. This report is one of a series intended to give information on the performance characteristics of radiological protection instruments, to assist in the selection of appropriate instruments for a given purpose, to interpret the results obtained with such instruments, and, in particular, to know the likely sources and magnitude of errors that might be associated with measurements in the field. The radiation, electrical and environmental characteristics of radiation protection instruments are considered together with those aspects of the construction which make an instrument convenient for routine use. To provide consistent criteria for instrument performance, the range of tests performed on any particular class of instrument, the test methods and the criteria of acceptable performance are based broadly on the appropriate Recommendations of the International Electrotechnical Commission. The radiations in the tests are, in general, selected from the range of reference radiations for instrument calibration being drawn up by the International Standards Organisation. Normally, each report deals with the capabilities and limitations of one model of instrument and no direct comparison with other instruments intended for similar purposes is made, since the significance of particular performance characteristics largely depends on the radiations and environmental conditions in which the instrument is to be used. The results quoted here have all been obtained from tests on instruments in routine production, with the appropriate measurements being made by the NRPB. This report deals with the ESI Nuclear Model 271 C; a general purpose contamination monitor, comprising a GM tube connected by a coiled extensible cable to a ratemeter
Modeling Turbulent Combustion for Variable Prandtl and Schmidt Number
Hassan, H. A.
2004-01-01
This report consists of two abstracts submitted for possible presentation at the AIAA Aerospace Science Meeting to be held in January 2005. Since the submittal of these abstracts we are continuing refinement of the model coefficients derived for the case of a variable Turbulent Prandtl number. The test cases being investigated are a Mach 9.2 flow over a degree ramp and a Mach 8.2 3-D calculation of crossing shocks. We have developed an axisymmetric code for treating axisymmetric flows. In addition the variable Schmidt number formulation was incorporated in the code and we are in the process of determining the model constants.
The Properties of Model Selection when Retaining Theory Variables
DEFF Research Database (Denmark)
Hendry, David F.; Johansen, Søren
Economic theories are often fitted directly to data to avoid possible model selection biases. We show that embedding a theory model that specifies the correct set of m relevant exogenous variables, x{t}, within the larger set of m+k candidate variables, (x{t},w{t}), then selection over the second...... set by their statistical significance can be undertaken without affecting the estimator distribution of the theory parameters. This strategy returns the theory-parameter estimates when the theory is correct, yet protects against the theory being under-specified because some w{t} are relevant....
Developing evaluation instrument based on CIPP models on the implementation of portfolio assessment
Kurnia, Feni; Rosana, Dadan; Supahar
2017-08-01
This study aimed to develop an evaluation instrument constructed by CIPP model on the implementation of portfolio assessment in science learning. This study used research and development (R & D) method; adapting 4-D by the development of non-test instrument, and the evaluation instrument constructed by CIPP model. CIPP is the abbreviation of Context, Input, Process, and Product. The techniques of data collection were interviews, questionnaires, and observations. Data collection instruments were: 1) the interview guidelines for the analysis of the problems and the needs, 2) questionnaire to see level of accomplishment of portfolio assessment instrument, and 3) observation sheets for teacher and student to dig up responses to the portfolio assessment instrument. The data obtained was quantitative data obtained from several validators. The validators consist of two lecturers as the evaluation experts, two practitioners (science teachers), and three colleagues. This paper shows the results of content validity obtained from the validators and the analysis result of the data obtained by using Aikens' V formula. The results of this study shows that the evaluation instrument based on CIPP models is proper to evaluate the implementation of portfolio assessment instruments. Based on the experts' judgments, practitioners, and colleagues, the Aikens' V coefficient was between 0.86-1,00 which means that it is valid and can be used in the limited trial and operational field trial.
Directory of Open Access Journals (Sweden)
F. S. R. Pausata
2009-09-01
Full Text Available Using four different climate models, we investigate sea level pressure variability in the extratropical North Atlantic in the preindustrial climate (1750 AD and at the Last Glacial Maximum (LGM, 21 kyrs before present in order to understand how changes in atmospheric circulation can affect signals recorded in climate proxies.
In general, the models exhibit a significant reduction in interannual variance of sea level pressure at the LGM compared to pre-industrial simulations and this reduction is concentrated in winter. For the preindustrial climate, all models feature a similar leading mode of sea level pressure variability that resembles the leading mode of variability in the instrumental record: the North Atlantic Oscillation (NAO. In contrast, the leading mode of sea level pressure variability at the LGM is model dependent, but in each model different from that in the preindustrial climate. In each model, the leading (NAO-like mode of variability explains a smaller fraction of the variance and also less absolute variance at the LGM than in the preindustrial climate.
The models show that the relationship between atmospheric variability and surface climate (temperature and precipitation variability change in different climates. Results are model-specific, but indicate that proxy signals at the LGM may be misinterpreted if changes in the spatial pattern and seasonality of surface climate variability are not taken into account.
Ocean carbon and heat variability in an Earth System Model
Thomas, J. L.; Waugh, D.; Gnanadesikan, A.
2016-12-01
Ocean carbon and heat content are very important for regulating global climate. Furthermore, due to lack of observations and dependence on parameterizations, there has been little consensus in the modeling community on the magnitude of realistic ocean carbon and heat content variability, particularly in the Southern Ocean. We assess the differences between global oceanic heat and carbon content variability in GFDL ESM2Mc using a 500-year, pre-industrial control simulation. The global carbon and heat content are directly out of phase with each other; however, in the Southern Ocean the heat and carbon content are in phase. The global heat mutli-decadal variability is primarily explained by variability in the tropics and mid-latitudes, while the variability in global carbon content is primarily explained by Southern Ocean variability. In order to test the robustness of this relationship, we use three additional pre-industrial control simulations using different mesoscale mixing parameterizations. Three pre-industrial control simulations are conducted with the along-isopycnal diffusion coefficient (Aredi) set to constant values of 400, 800 (control) and 2400 m2 s-1. These values for Aredi are within the range of parameter settings commonly used in modeling groups. Finally, one pre-industrial control simulation is conducted where the minimum in the Gent-McWilliams parameterization closure scheme (AGM) increased to 600 m2 s-1. We find that the different simulations have very different multi-decadal variability, especially in the Weddell Sea where the characteristics of deep convection are drastically changed. While the temporal frequency and amplitude global heat and carbon content changes significantly, the overall spatial pattern of variability remains unchanged between the simulations.
Boef, Anna G C; Souverein, Patrick C|info:eu-repo/dai/nl/243074948; Vandenbroucke, Jan P; van Hylckama Vlieg, Astrid; de Boer, Anthonius|info:eu-repo/dai/nl/075097346; le Cessie, Saskia; Dekkers, Olaf M
2016-01-01
PURPOSE: A potentially useful role for instrumental variable (IV) analysis may be as a complementary analysis to assess the presence of confounding when studying adverse drug effects. There has been discussion on whether the observed increased risk of venous thromboembolism (VTE) for
Vasilyev, Y. M.; Lagunov, L. F.
1973-01-01
The schematic diagram of a noise measuring device is presented that uses pulse expansion modeling according to the peak or any other measured values, to obtain instrument readings at a very low noise error.
2010-08-12
Strategies to Enhance Online Learning Teams Team Assessment and Diagnostics Instrument and Agent-based Modeling Tristan E. Johnson, Ph.D. Learning ...REPORT DATE AUG 2010 2. REPORT TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Strategies to Enhance Online Learning ...TeamsTeam Strategies to Enhance Online Learning Teams: Team Assessment and Diagnostics Instrument and Agent-based Modeling 5a. CONTRACT NUMBER 5b. GRANT
McMillan, Hilary; Srinivasan, Ms
2015-04-01
Hydrologists recognise the importance of vertical drainage and deep flow paths in runoff generation, even in headwater catchments. Both soil and groundwater stores are highly variable over multiple scales, and the distribution of water has a strong control on flow rates and timing. In this study, we instrumented an upland headwater catchment in New Zealand to measure the temporal and spatial variation in unsaturated and saturated-zone responses. In NZ, upland catchments are the source of much of the water used in lowland agriculture, but the hydrology of such catchments and their role in water partitioning, storage and transport is poorly understood. The study area is the Langs Gully catchment in the North Branch of the Waipara River, Canterbury: this catchment was chosen to be representative of the foothills environment, with lightly managed dryland pasture and native Matagouri shrub vegetation cover. Over a period of 16 months we measured continuous soil moisture at 32 locations and near-surface water table (versus hillslope locations, and convergent versus divergent hillslopes. We found that temporal variability is strongly controlled by the climatic seasonal cycle, for both soil moisture and water table, and for both the mean and extremes of their distributions. Groundwater is a larger water storage component than soil moisture, and the difference increases with catchment wetness. The spatial standard deviation of both soil moisture and groundwater is larger in winter than in summer. It peaks during rainfall events due to partial saturation of the catchment, and also rises in spring as different locations dry out at different rates. The most important controls on spatial variability are aspect and distance from stream. South-facing and near-stream locations have higher water tables and more, larger soil moisture wetting events. Typical hydrological models do not explicitly account for aspect, but our results suggest that it is an important factor in hillslope
Classification criteria of syndromes by latent variable models
DEFF Research Database (Denmark)
Petersen, Janne
2010-01-01
patient's characteristics. These methods may erroneously reduce multiplicity either by combining markers of different phenotypes or by mixing HALS with other processes such as aging. Latent class models identify homogenous groups of patients based on sets of variables, for example symptoms. As no gold......The thesis has two parts; one clinical part: studying the dimensions of human immunodeficiency virus associated lipodystrophy syndrome (HALS) by latent class models, and a more statistical part: investigating how to predict scores of latent variables so these can be used in subsequent regression...... standard exists for diagnosing HALS the normally applied diagnostic models cannot be used. Latent class models, which have never before been used to diagnose HALS, make it possible, under certain assumptions, to: statistically evaluate the number of phenotypes, test for mixing of HALS with other processes...
Internal variability in a regional climate model over West Africa
Energy Technology Data Exchange (ETDEWEB)
Vanvyve, Emilie; Ypersele, Jean-Pascal van [Universite catholique de Louvain, Institut d' astronomie et de geophysique Georges Lemaitre, Louvain-la-Neuve (Belgium); Hall, Nicholas [Laboratoire d' Etudes en Geophysique et Oceanographie Spatiales/Centre National d' Etudes Spatiales, Toulouse Cedex 9 (France); Messager, Christophe [University of Leeds, Institute for Atmospheric Science, Environment, School of Earth and Environment, Leeds (United Kingdom); Leroux, Stephanie [Universite Joseph Fourier, Laboratoire d' etude des Transferts en Hydrologie et Environnement, BP53, Grenoble Cedex 9 (France)
2008-02-15
Sensitivity studies with regional climate models are often performed on the basis of a few simulations for which the difference is analysed and the statistical significance is often taken for granted. In this study we present some simple measures of the confidence limits for these types of experiments by analysing the internal variability of a regional climate model run over West Africa. Two 1-year long simulations, differing only in their initial conditions, are compared. The difference between the two runs gives a measure of the internal variability of the model and an indication of which timescales are reliable for analysis. The results are analysed for a range of timescales and spatial scales, and quantitative measures of the confidence limits for regional model simulations are diagnosed for a selection of study areas for rainfall, low level temperature and wind. As the averaging period or spatial scale is increased, the signal due to internal variability gets smaller and confidence in the simulations increases. This occurs more rapidly for variations in precipitation, which appear essentially random, than for dynamical variables, which show some organisation on larger scales. (orig.)
Automatic Welding Control Using a State Variable Model.
1979-06-01
A-A10 610 NAVEAL POSTGRADUATE SCH4O.M CEAY CA0/ 13/ SAUTOMATIC WELDING CONTROL USING A STATE VARIABLE MODEL.W()JUN 79 W V "my UNCLASSIFIED...taverse Drive Unit // Jbint Path /Fixed Track 34 (servomotor positioning). Additional controls of heave (vertical), roll (angular rotation about the
Viscous cosmological models with a variable cosmological term ...
African Journals Online (AJOL)
Einstein's field equations for a Friedmann-Lamaitre Robertson-Walker universe filled with a dissipative fluid with a variable cosmological term L described by full Israel-Stewart theory are considered. General solutions to the field equations for the flat case have been obtained. The solution corresponds to the dust free model ...
Appraisal and Reliability of Variable Engagement Model Prediction ...
African Journals Online (AJOL)
The variable engagement model based on the stress - crack opening displacement relationship and, which describes the behaviour of randomly oriented steel fibres composite subjected to uniaxial tension has been evaluated so as to determine the safety indices associated when the fibres are subjected to pullout and with ...
Higher-dimensional cosmological model with variable gravitational ...
Indian Academy of Sciences (India)
variable G and bulk viscosity in Lyra geometry. Exact solutions for ... a comparative study of Robertson–Walker models with a constant deceleration .... where H is defined as H =(˙A/A)+(1/3)( ˙B/B) and β0,H0 are representing present values of β ...
Oscillating shells: A model for a variable cosmic object
Nunez, Dario
1997-01-01
A model for a possible variable cosmic object is presented. The model consists of a massive shell surrounding a compact object. The gravitational and self-gravitational forces tend to collapse the shell, but the internal tangential stresses oppose the collapse. The combined action of the two types of forces is studied and several cases are presented. In particular, we investigate the spherically symmetric case in which the shell oscillates radially around a central compact object.
Harris, Steve; Singer, Mervyn; Sanderson, Colin; Grieve, Richard; Harrison, David; Rowan, Kathryn
2018-05-07
To estimate the effect of prompt admission to critical care on mortality for deteriorating ward patients. We performed a prospective cohort study of consecutive ward patients assessed for critical care. Prompt admissions (within 4 h of assessment) were compared to a 'watchful waiting' cohort. We used critical care strain (bed occupancy) as a natural randomisation event that would predict prompt transfer to critical care. Strain was classified as low, medium or high (2+, 1 or 0 empty beds). This instrumental variable (IV) analysis was repeated for the subgroup of referrals with a recommendation for critical care once assessed. Risk-adjusted 90-day survival models were also constructed. A total of 12,380 patients from 48 hospitals were available for analysis. There were 2411 (19%) prompt admissions (median delay 1 h, IQR 1-2) and 9969 (81%) controls; 1990 (20%) controls were admitted later (median delay 11 h, IQR 6-26). Prompt admissions were less frequent (p care. In the risk-adjust survival model, 90-day mortality was similar. After allowing for unobserved prognostic differences between the groups, we find that prompt admission to critical care leads to lower 90-day mortality for patients assessed and recommended to critical care.
Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.
Ares I Scale Model Acoustic Tests Instrumentation for Acoustic and Pressure Measurements
Vargas, Magda B.; Counter, Douglas D.
2011-01-01
The Ares I Scale Model Acoustic Test (ASMAT) was a development test performed at the Marshall Space Flight Center (MSFC) East Test Area (ETA) Test Stand 116. The test article included a 5% scale Ares I vehicle model and tower mounted on the Mobile Launcher. Acoustic and pressure data were measured by approximately 200 instruments located throughout the test article. There were four primary ASMAT instrument suites: ignition overpressure (IOP), lift-off acoustics (LOA), ground acoustics (GA), and spatial correlation (SC). Each instrumentation suite incorporated different sensor models which were selected based upon measurement requirements. These requirements included the type of measurement, exposure to the environment, instrumentation check-outs and data acquisition. The sensors were attached to the test article using different mounts and brackets dependent upon the location of the sensor. This presentation addresses the observed effect of the sensors and mounts on the acoustic and pressure measurements.
Analysis models for variables associated with breastfeeding duration
Directory of Open Access Journals (Sweden)
Edson Theodoro dos S. Neto
2013-09-01
Full Text Available OBJECTIVE To analyze the factors associated with breastfeeding duration by two statistical models. METHODS A population-based cohort study was conducted with 86 mothers and newborns from two areas primary covered by the National Health System, with high rates of infant mortality in Vitória, Espírito Santo, Brazil. During 30 months, 67 (78% children and mothers were visited seven times at home by trained interviewers, who filled out survey forms. Data on food and sucking habits, socioeconomic and maternal characteristics were collected. Variables were analyzed by Cox regression models, considering duration of breastfeeding as the dependent variable, and logistic regression (dependent variables, was the presence of a breastfeeding child in different post-natal ages. RESULTS In the logistic regression model, the pacifier sucking (adjusted Odds Ratio: 3.4; 95%CI 1.2-9.55 and bottle feeding (adjusted Odds Ratio: 4.4; 95%CI 1.6-12.1 increased the chance of weaning a child before one year of age. Variables associated to breastfeeding duration in the Cox regression model were: pacifier sucking (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.3 and bottle feeding (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.5. However, protective factors (maternal age and family income differed between both models. CONCLUSIONS Risk and protective factors associated with cessation of breastfeeding may be analyzed by different models of statistical regression. Cox Regression Models are adequate to analyze such factors in longitudinal studies.
Two-step variable selection in quantile regression models
Directory of Open Access Journals (Sweden)
FAN Yali
2015-06-01
Full Text Available We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, pn is much larger than the sample size n. In the first step, we perform ℓ1 penalty, and we demonstrate that the first step penalized estimator with the LASSO penalty can reduce the model from an ultra-high dimensional to a model whose size has the same order as that of the true model, and the selected model can cover the true model. The second step excludes the remained irrelevant covariates by applying the adaptive LASSO penalty to the reduced model obtained from the first step. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. We conduct a simulation study and a real data analysis to evaluate the finite sample performance of the proposed approach.
Ensembling Variable Selectors by Stability Selection for the Cox Model
Directory of Open Access Journals (Sweden)
Qing-Yan Yin
2017-01-01
Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.
DEFF Research Database (Denmark)
Panduro, Toke Emil; Thorsen, Bo Jellesmark
2014-01-01
Hedonic models in environmental valuation studies have grown in terms of number of transactions and number of explanatory variables. We focus on the practical challenge of model reduction, when aiming for reliable parsimonious models, sensitive to omitted variable bias and multicollinearity. We...
Hidden Markov latent variable models with multivariate longitudinal data.
Song, Xinyuan; Xia, Yemao; Zhu, Hongtu
2017-03-01
Cocaine addiction is chronic and persistent, and has become a major social and health problem in many countries. Existing studies have shown that cocaine addicts often undergo episodic periods of addiction to, moderate dependence on, or swearing off cocaine. Given its reversible feature, cocaine use can be formulated as a stochastic process that transits from one state to another, while the impacts of various factors, such as treatment received and individuals' psychological problems on cocaine use, may vary across states. This article develops a hidden Markov latent variable model to study multivariate longitudinal data concerning cocaine use from a California Civil Addict Program. The proposed model generalizes conventional latent variable models to allow bidirectional transition between cocaine-addiction states and conventional hidden Markov models to allow latent variables and their dynamic interrelationship. We develop a maximum-likelihood approach, along with a Monte Carlo expectation conditional maximization (MCECM) algorithm, to conduct parameter estimation. The asymptotic properties of the parameter estimates and statistics for testing the heterogeneity of model parameters are investigated. The finite sample performance of the proposed methodology is demonstrated by simulation studies. The application to cocaine use study provides insights into the prevention of cocaine use. © 2016, The International Biometric Society.
Directory of Open Access Journals (Sweden)
Romain Michon
2017-12-01
Full Text Available Two concepts are presented, extended, and unified in this paper: mobile device augmentation towards musical instruments design and the concept of hybrid instruments. The first consists of using mobile devices at the heart of novel musical instruments. Smartphones and tablets are augmented with passive and active elements that can take part in the production of sound (e.g., resonators, exciter, etc., add new affordances to the device, or change its global aesthetics and shape. Hybrid instruments combine physical/acoustical and “physically informed” virtual/digital elements. Recent progress in physical modeling of musical instruments and digital fabrication is exploited to treat instrument parts in a multidimensional way, allowing any physical element to be substituted with a virtual one and vice versa (as long as it is physically possible. A wide range of tools to design mobile hybrid instruments is introduced and evaluated. Aesthetic and design considerations when making such instruments are also presented through a series of examples.
Environmental versus demographic variability in stochastic predator–prey models
International Nuclear Information System (INIS)
Dobramysl, U; Täuber, U C
2013-01-01
In contrast to the neutral population cycles of the deterministic mean-field Lotka–Volterra rate equations, including spatial structure and stochastic noise in models for predator–prey interactions yields complex spatio-temporal structures associated with long-lived erratic population oscillations. Environmental variability in the form of quenched spatial randomness in the predation rates results in more localized activity patches. Our previous study showed that population fluctuations in rare favorable regions in turn cause a remarkable increase in the asymptotic densities of both predators and prey. Very intriguing features are found when variable interaction rates are affixed to individual particles rather than lattice sites. Stochastic dynamics with demographic variability in conjunction with inheritable predation efficiencies generate non-trivial time evolution for the predation rate distributions, yet with overall essentially neutral optimization. (paper)
Pre-quantum mechanics. Introduction to models with hidden variables
International Nuclear Information System (INIS)
Grea, J.
1976-01-01
Within the context of formalism of hidden variable type, the author considers the models used to describe mechanical systems before the introduction of the quantum model. An account is given of the characteristics of the theoretical models and their relationships with experimental methodology. The models of analytical, pre-ergodic, stochastic and thermodynamic mechanics are studied in succession. At each stage the physical hypothesis is enunciated by postulate corresponding to the type of description of the reality of the model. Starting from this postulate, the physical propositions which are meaningful for the model under consideration are defined and their logical structure is indicated. It is then found that on passing from one level of description to another, one can obtain successively Boolean lattices embedded in lattices of continuous geometric type, which are themselves embedded in Boolean lattices. It is therefore possible to envisage a more detailed description than that given by the quantum lattice and to construct it by analogy. (Auth.)
Frequency-Zooming ARMA Modeling for Analysis of Noisy String Instrument Tones
Directory of Open Access Journals (Sweden)
Paulo A. A. Esquef
2003-09-01
Full Text Available This paper addresses model-based analysis of string instrument sounds. In particular, it reviews the application of autoregressive (AR modeling to sound analysis/synthesis purposes. Moreover, a frequency-zooming autoregressive moving average (FZ-ARMA modeling scheme is described. The performance of the FZ-ARMA method on modeling the modal behavior of isolated groups of resonance frequencies is evaluated for both synthetic and real string instrument tones immersed in background noise. We demonstrate that the FZ-ARMA modeling is a robust tool to estimate the decay time and frequency of partials of noisy tones. Finally, we discuss the use of the method in synthesis of string instrument sounds.
An Atmospheric Variability Model for Venus Aerobraking Missions
Tolson, Robert T.; Prince, Jill L. H.; Konopliv, Alexander A.
2013-01-01
Aerobraking has proven to be an enabling technology for planetary missions to Mars and has been proposed to enable low cost missions to Venus. Aerobraking saves a significant amount of propulsion fuel mass by exploiting atmospheric drag to reduce the eccentricity of the initial orbit. The solar arrays have been used as the primary drag surface and only minor modifications have been made in the vehicle design to accommodate the relatively modest aerothermal loads. However, if atmospheric density is highly variable from orbit to orbit, the mission must either accept higher aerothermal risk, a slower pace for aerobraking, or a tighter corridor likely with increased propulsive cost. Hence, knowledge of atmospheric variability is of great interest for the design of aerobraking missions. The first planetary aerobraking was at Venus during the Magellan mission. After the primary Magellan science mission was completed, aerobraking was used to provide a more circular orbit to enhance gravity field recovery. Magellan aerobraking took place between local solar times of 1100 and 1800 hrs, and it was found that the Venusian atmospheric density during the aerobraking phase had less than 10% 1 sigma orbit to orbit variability. On the other hand, at some latitudes and seasons, Martian variability can be as high as 40% 1 sigmaFrom both the MGN and PVO mission it was known that the atmosphere, above aerobraking altitudes, showed greater variability at night, but this variability was never quantified in a systematic manner. This paper proposes a model for atmospheric variability that can be used for aerobraking mission design until more complete data sets become available.
A new approach for modelling variability in residential construction projects
Directory of Open Access Journals (Sweden)
Mehrdad Arashpour
2013-06-01
Full Text Available The construction industry is plagued by long cycle times caused by variability in the supply chain. Variations or undesirable situations are the result of factors such as non-standard practices, work site accidents, inclement weather conditions and faults in design. This paper uses a new approach for modelling variability in construction by linking relative variability indicators to processes. Mass homebuilding sector was chosen as the scope of the analysis because data is readily available. Numerous simulation experiments were designed by varying size of capacity buffers in front of trade contractors, availability of trade contractors, and level of variability in homebuilding processes. The measurements were shown to lead to an accurate determination of relationships between these factors and production parameters. The variability indicator was found to dramatically affect the tangible performance measures such as home completion rates. This study provides for future analysis of the production homebuilding sector, which may lead to improvements in performance and a faster product delivery to homebuyers.
A new approach for modelling variability in residential construction projects
Directory of Open Access Journals (Sweden)
Mehrdad Arashpour
2013-06-01
Full Text Available The construction industry is plagued by long cycle times caused by variability in the supply chain. Variations or undesirable situations are the result of factors such as non-standard practices, work site accidents, inclement weather conditions and faults in design. This paper uses a new approach for modelling variability in construction by linking relative variability indicators to processes. Mass homebuilding sector was chosen as the scope of the analysis because data is readily available. Numerous simulation experiments were designed by varying size of capacity buffers in front of trade contractors, availability of trade contractors, and level of variability in homebuilding processes. The measurements were shown to lead to an accurate determination of relationships between these factors and production parameters. The variability indicator was found to dramatically affect the tangible performance measures such as home completion rates. This study provides for future analysis of the production homebuilding sector, which may lead to improvements in performance and a faster product delivery to homebuyers.
Multiscale thermohydrologic model: addressing variability and uncertainty at Yucca Mountain
International Nuclear Information System (INIS)
Buscheck, T; Rosenberg, N D; Gansemer, J D; Sun, Y
2000-01-01
Performance assessment and design evaluation require a modeling tool that simultaneously accounts for processes occurring at a scale of a few tens of centimeters around individual waste packages and emplacement drifts, and also on behavior at the scale of the mountain. Many processes and features must be considered, including non-isothermal, multiphase-flow in rock of variable saturation and thermal radiation in open cavities. Also, given the nature of the fractured rock at Yucca Mountain, a dual-permeability approach is needed to represent permeability. A monolithic numerical model with all these features requires too large a computational cost to be an effective simulation tool, one that is used to examine sensitivity to key model assumptions and parameters. We have developed a multi-scale modeling approach that effectively simulates 3D discrete-heat-source, mountain-scale thermohydrologic behavior at Yucca Mountain and captures the natural variability of the site consistent with what we know from site characterization and waste-package-to-waste-package variability in heat output. We describe this approach and present results examining the role of infiltration flux, the most important natural-system parameter with respect to how thermohydrologic behavior influences the performance of the repository
Zurweni, Wibawa, Basuki; Erwin, Tuti Nurian
2017-08-01
The framework for teaching and learning in the 21st century was prepared with 4Cs criteria. Learning providing opportunity for the development of students' optimal creative skills is by implementing collaborative learning. Learners are challenged to be able to compete, work independently to bring either individual or group excellence and master the learning material. Virtual laboratory is used for the media of Instrumental Analytical Chemistry (Vis, UV-Vis-AAS etc) lectures through simulations computer application and used as a substitution for the laboratory if the equipment and instruments are not available. This research aims to design and develop collaborative-creative learning model using virtual laboratory media for Instrumental Analytical Chemistry lectures, to know the effectiveness of this design model adapting the Dick & Carey's model and Hannafin & Peck's model. The development steps of this model are: needs analyze, design collaborative-creative learning, virtual laboratory media using macromedia flash, formative evaluation and test of learning model effectiveness. While, the development stages of collaborative-creative learning model are: apperception, exploration, collaboration, creation, evaluation, feedback. Development of collaborative-creative learning model using virtual laboratory media can be used to improve the quality learning in the classroom, overcome the limitation of lab instruments for the real instrumental analysis. Formative test results show that the Collaborative-Creative Learning Model developed meets the requirements. The effectiveness test of students' pretest and posttest proves significant at 95% confidence level, t-test higher than t-table. It can be concluded that this learning model is effective to use for Instrumental Analytical Chemistry lectures.
TSI Model 3936 Scanning Mobility Particle Spectrometer Instrument Handbook
Energy Technology Data Exchange (ETDEWEB)
Kuang, C. [Brookhaven National Lab. (BNL), Upton, NY (United States)
2016-02-01
The Model 3936 Scanning Mobility Particle Spectrometer (SMPS) measures the size distribution of aerosols ranging from 10 nm up to 1000 nm. The SMPS uses a bipolar aerosol charger to keep particles within a known charge distribution. Charged particles are classified according to their electrical mobility, using a long-column differential mobility analyzer (DMA). Particle concentration is measured with a condensation particle counter (CPC). The SMPS is well-suited for applications including: nanoparticle research, atmospheric aerosol studies, pollution studies, smog chamber evaluations, engine exhaust and combustion studies, materials synthesis, filter efficiency testing, nucleation/condensation studies, and rapidly changing aerosol systems.
Directory of Open Access Journals (Sweden)
Evropi Theodoratou
Full Text Available Vitamin D deficiency has been associated with several common diseases, including cancer and is being investigated as a possible risk factor for these conditions. We reported the striking prevalence of vitamin D deficiency in Scotland. Previous epidemiological studies have reported an association between low dietary vitamin D and colorectal cancer (CRC. Using a case-control study design, we tested the association between plasma 25-hydroxy-vitamin D (25-OHD and CRC (2,001 cases, 2,237 controls. To determine whether plasma 25-OHD levels are causally linked to CRC risk, we applied the control function instrumental variable (IV method of the mendelian randomization (MR approach using four single nucleotide polymorphisms (rs2282679, rs12785878, rs10741657, rs6013897 previously shown to be associated with plasma 25-OHD. Low plasma 25-OHD levels were associated with CRC risk in the crude model (odds ratio (OR: 0.76, 95% Confidence Interval (CI: 0.71, 0.81, p: 1.4×10(-14 and after adjusting for age, sex and other confounding factors. Using an allele score that combined all four SNPs as the IV, the estimated causal effect was OR 1.16 (95% CI 0.60, 2.23, whilst it was 0.94 (95% CI 0.46, 1.91 and 0.93 (0.53, 1.63 when using an upstream (rs12785878, rs10741657 and a downstream allele score (rs2282679, rs6013897, respectively. 25-OHD levels were inversely associated with CRC risk, in agreement with recent meta-analyses. The fact that this finding was not replicated when the MR approach was employed might be due to weak instruments, giving low power to demonstrate an effect (<0.35. The prevalence and degree of vitamin D deficiency amongst individuals living in northerly latitudes is of considerable importance because of its relationship to disease. To elucidate the effect of vitamin D on CRC cancer risk, additional large studies of vitamin D and CRC risk are required and/or the application of alternative methods that are less sensitive to weak instrument
Models and error analyses of measuring instruments in accountability systems in safeguards control
International Nuclear Information System (INIS)
Dattatreya, E.S.
1977-05-01
Essentially three types of measuring instruments are used in plutonium accountability systems: (1) the bubblers, for measuring the total volume of liquid in the holding tanks, (2) coulometers, titration apparatus and calorimeters, for measuring the concentration of plutonium; and (3) spectrometers, for measuring isotopic composition. These three classes of instruments are modeled and analyzed. Finally, the uncertainty in the estimation of total plutonium in the holding tank is determined
Explicit estimating equations for semiparametric generalized linear latent variable models
Ma, Yanyuan
2010-07-05
We study generalized linear latent variable models without requiring a distributional assumption of the latent variables. Using a geometric approach, we derive consistent semiparametric estimators. We demonstrate that these models have a property which is similar to that of a sufficient complete statistic, which enables us to simplify the estimating procedure and explicitly to formulate the semiparametric estimating equations. We further show that the explicit estimators have the usual root n consistency and asymptotic normality. We explain the computational implementation of our method and illustrate the numerical performance of the estimators in finite sample situations via extensive simulation studies. The advantage of our estimators over the existing likelihood approach is also shown via numerical comparison. We employ the method to analyse a real data example from economics. © 2010 Royal Statistical Society.
Speech-discrimination scores modeled as a binomial variable.
Thornton, A R; Raffin, M J
1978-09-01
Many studies have reported variability data for tests of speech discrimination, and the disparate results of these studies have not been given a simple explanation. Arguments over the relative merits of 25- vs 50-word tests have ignored the basic mathematical properties inherent in the use of percentage scores. The present study models performance on clinical tests of speech discrimination as a binomial variable. A binomial model was developed, and some of its characteristics were tested against data from 4120 scores obtained on the CID Auditory Test W-22. A table for determining significant deviations between scores was generated and compared to observed differences in half-list scores for the W-22 tests. Good agreement was found between predicted and observed values. Implications of the binomial characteristics of speech-discrimination scores are discussed.
Efficient family-based model checking via variability abstractions
DEFF Research Database (Denmark)
Dimovski, Aleksandar; Al-Sibahi, Ahmad Salim; Brabrand, Claus
2016-01-01
with the abstract model checking of the concrete high-level variational model. This allows the use of Spin with all its accumulated optimizations for efficient verification of variational models without any knowledge about variability. We have implemented the transformations in a prototype tool, and we illustrate......Many software systems are variational: they can be configured to meet diverse sets of requirements. They can produce a (potentially huge) number of related systems, known as products or variants, by systematically reusing common parts. For variational models (variational systems or families...... of related systems), specialized family-based model checking algorithms allow efficient verification of multiple variants, simultaneously, in a single run. These algorithms, implemented in a tool Snip, scale much better than ``the brute force'' approach, where all individual systems are verified using...
Habibov, Nazim; Cheung, Alex; Auchynnikava, Alena
2017-09-01
The purpose of this paper is to investigate the effect of social trust on the willingness to pay more taxes to improve public healthcare in post-communist countries. The well-documented association between higher levels of social trust and better health has traditionally been assumed to reflect the notion that social trust is positively associated with support for public healthcare system through its encouragement of cooperative behaviour, social cohesion, social solidarity, and collective action. Hence, in this paper, we have explicitly tested the notion that social trust contributes to an increase in willingness to financially support public healthcare. We use micro data from the 2010 Life-in-Transition survey (N = 29,526). Classic binomial probit and instrumental variables ivprobit regressions are estimated to model the relationship between social trust and paying more taxes to improve public healthcare. We found that an increase in social trust is associated with a greater willingness to pay more taxes to improve public healthcare. From the perspective of policy-making, healthcare administrators, policy-makers, and international donors should be aware that social trust is an important factor in determining the willingness of the population to provide much-needed financial resources to supporting public healthcare. From a theoretical perspective, we found that estimating the effect of trust on support for healthcare without taking confounding and measurement error problems into consideration will likely lead to an underestimation of the true effect of trust. Copyright © 2017 Elsevier Ltd. All rights reserved.
Dynamic Variables Fail to Predict Fluid Responsiveness in an Animal Model With Pericardial Effusion.
Broch, Ole; Renner, Jochen; Meybohm, Patrick; Albrecht, Martin; Höcker, Jan; Haneya, Assad; Steinfath, Markus; Bein, Berthold; Gruenewald, Matthias
2016-10-01
The reliability of dynamic and volumetric variables of fluid responsiveness in the presence of pericardial effusion is still elusive. The aim of the present study was to investigate their predictive power in a porcine model with hemodynamic relevant pericardial effusion. A single-center animal investigation. Twelve German domestic pigs. Pigs were studied before and during pericardial effusion. Instrumentation included a pulmonary artery catheter and a transpulmonary thermodilution catheter in the femoral artery. Hemodynamic variables like cardiac output (COPAC) and stroke volume (SVPAC) derived from pulmonary artery catheter, global end-diastolic volume (GEDV), stroke volume variation (SVV), and pulse-pressure variation (PPV) were obtained. At baseline, SVV, PPV, GEDV, COPAC, and SVPAC reliably predicted fluid responsiveness (area under the curve 0.81 [p = 0.02], 0.82 [p = 0.02], 0.74 [p = 0.07], 0.74 [p = 0.07], 0.82 [p = 0.02]). After establishment of pericardial effusion the predictive power of dynamic variables was impaired and only COPAC and SVPAC and GEDV allowed significant prediction of fluid responsiveness (area under the curve 0.77 [p = 0.04], 0.76 [p = 0.05], 0.83 [p = 0.01]) with clinically relevant changes in threshold values. In this porcine model, hemodynamic relevant pericardial effusion abolished the ability of dynamic variables to predict fluid responsiveness. COPAC, SVPAC, and GEDV enabled prediction, but their threshold values were significantly changed. Copyright © 2016 Elsevier Inc. All rights reserved.
Predictive modeling and reducing cyclic variability in autoignition engines
Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob
2016-08-30
Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.
Model Engine Performance Measurement From Force Balance Instrumentation
Jeracki, Robert J.
1998-01-01
A large scale model representative of a low-noise, high bypass ratio turbofan engine was tested for acoustics and performance in the NASA Lewis 9- by 15-Foot Low-Speed Wind Tunnel. This test was part of NASA's continuing Advanced Subsonic Technology Noise Reduction Program. The low tip speed fan, nacelle, and an un-powered core passage (with core inlet guide vanes) were simulated. The fan blades and hub are mounted on a rotating thrust and torque balance. The nacelle, bypass duct stators, and core passage are attached to a six component force balance. The two balance forces, when corrected for internal pressure tares, measure the total thrust-minus-drag of the engine simulator. Corrected for scaling and other effects, it is basically the same force that the engine supports would feel, operating at similar conditions. A control volume is shown and discussed, identifying the various force components of the engine simulator thrust and definitions of net thrust. Several wind tunnel runs with nearly the same hardware installed are compared, to identify the repeatability of the measured thrust-minus-drag. Other wind tunnel runs, with hardware changes that affected fan performance, are compared to the baseline configuration, and the thrust and torque effects are shown. Finally, a thrust comparison between the force balance and nozzle gross thrust methods is shown, and both yield very similar results.
Are revised models better models? A skill score assessment of regional interannual variability
Sperber, Kenneth R.; Participating AMIP Modelling Groups
1999-05-01
Various skill scores are used to assess the performance of revised models relative to their original configurations. The interannual variability of all-India, Sahel and Nordeste rainfall and summer monsoon windshear is examined in integrations performed under the experimental design of the Atmospheric Model Intercomparison Project. For the indices considered, the revised models exhibit greater fidelity at simulating the observed interannual variability. Interannual variability of all-India rainfall is better simulated by models that have a more realistic rainfall climatology in the vicinity of India, indicating the beneficial effect of reducing systematic model error.
A Variable Flow Modelling Approach To Military End Strength Planning
2016-12-01
function. The MLRPS is more complex than the variable flow model as it has to cater for a force structure that is much larger than just the MT branch...essential positions in a Ship’s complement, or by the biggest current deficit in forecast end strength. The model can be adjusted to cater for any of these...is unlikely that the RAN will be able to cater for such an increase in hires, so this scenario is not likely to solve their problem. Each transition
Variable sound speed in interacting dark energy models
Linton, Mark S.; Pourtsidou, Alkistis; Crittenden, Robert; Maartens, Roy
2018-04-01
We consider a self-consistent and physical approach to interacting dark energy models described by a Lagrangian, and identify a new class of models with variable dark energy sound speed. We show that if the interaction between dark energy in the form of quintessence and cold dark matter is purely momentum exchange this generally leads to a dark energy sound speed that deviates from unity. Choosing a specific sub-case, we study its phenomenology by investigating the effects of the interaction on the cosmic microwave background and linear matter power spectrum. We also perform a global fitting of cosmological parameters using CMB data, and compare our findings to ΛCDM.
Connolly, Joseph W.; Friedlander, David; Kopasakis, George
2015-01-01
This paper covers the development of an integrated nonlinear dynamic simulation for a variable cycle turbofan engine and nozzle that can be integrated with an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. A previously developed variable cycle turbofan engine model is used for this study and is enhanced here to include variable guide vanes allowing for operation across the supersonic flight regime. The primary focus of this study is to improve the fidelity of the model's thrust response by replacing the simple choked flow equation convergent-divergent nozzle model with a MacCormack method based quasi-1D model. The dynamic response of the nozzle model using the MacCormack method is verified by comparing it against a model of the nozzle using the conservation element/solution element method. A methodology is also presented for the integration of the MacCormack nozzle model with the variable cycle engine.
Habibov, Nazim
2016-03-01
There is the lack of consensus about the effect of corruption on healthcare satisfaction in transitional countries. Interpreting the burgeoning literature on this topic has proven difficult due to reverse causality and omitted variable bias. In this study, the effect of corruption on healthcare satisfaction is investigated in a set of 12 Post-Socialist countries using instrumental variable regression on the sample of 2010 Life in Transition survey (N = 8655). The results indicate that experiencing corruption significantly reduces healthcare satisfaction. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.
Quantifying intrinsic and extrinsic variability in stochastic gene expression models.
Singh, Abhyudai; Soltani, Mohammad
2013-01-01
Genetically identical cell populations exhibit considerable intercellular variation in the level of a given protein or mRNA. Both intrinsic and extrinsic sources of noise drive this variability in gene expression. More specifically, extrinsic noise is the expression variability that arises from cell-to-cell differences in cell-specific factors such as enzyme levels, cell size and cell cycle stage. In contrast, intrinsic noise is the expression variability that is not accounted for by extrinsic noise, and typically arises from the inherent stochastic nature of biochemical processes. Two-color reporter experiments are employed to decompose expression variability into its intrinsic and extrinsic noise components. Analytical formulas for intrinsic and extrinsic noise are derived for a class of stochastic gene expression models, where variations in cell-specific factors cause fluctuations in model parameters, in particular, transcription and/or translation rate fluctuations. Assuming mRNA production occurs in random bursts, transcription rate is represented by either the burst frequency (how often the bursts occur) or the burst size (number of mRNAs produced in each burst). Our analysis shows that fluctuations in the transcription burst frequency enhance extrinsic noise but do not affect the intrinsic noise. On the contrary, fluctuations in the transcription burst size or mRNA translation rate dramatically increase both intrinsic and extrinsic noise components. Interestingly, simultaneous fluctuations in transcription and translation rates arising from randomness in ATP abundance can decrease intrinsic noise measured in a two-color reporter assay. Finally, we discuss how these formulas can be combined with single-cell gene expression data from two-color reporter experiments for estimating model parameters.
Modeling key processes causing climate change and variability
Energy Technology Data Exchange (ETDEWEB)
Henriksson, S.
2013-09-01
Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are (1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, (2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, (3) identifying a power law shape S(f) {proportional_to} f-{alpha} for the spectrum of global mean temperature with {alpha} {approx} 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, (4) separating aerosol properties and climate effects in India by season and location (5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, (6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and (7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy
Testing of Environmental Satellite Bus-Instrument Interfaces Using Engineering Models
Gagnier, Donald; Hayner, Rick; Nosek, Thomas; Roza, Michael; Hendershot, James E.; Razzaghi, Andrea I.
2004-01-01
This paper discusses the formulation and execution of a laboratory test of the electrical interfaces between multiple atmospheric scientific instruments and the spacecraft bus that carries them. The testing, performed in 2002, used engineering models of the instruments and the Aura spacecraft bus electronics. Aura is one of NASA s Earth Observatory System missions. The test was designed to evaluate the complex interfaces in the command and data handling subsystems prior to integration of the complete flight instruments on the spacecraft. A problem discovered during the flight integration phase of the observatory can cause significant cost and schedule impacts. The tests successfully revealed problems and led to their resolution before the full-up integration phase, saving significant cost and schedule. This approach could be beneficial for future environmental satellite programs involving the integration of multiple, complex scientific instruments onto a spacecraft bus.
Geochemical Modeling Of F Area Seepage Basin Composition And Variability
International Nuclear Information System (INIS)
Millings, M.; Denham, M.; Looney, B.
2012-01-01
From the 1950s through 1989, the F Area Seepage Basins at the Savannah River Site (SRS) received low level radioactive wastes resulting from processing nuclear materials. Discharges of process wastes to the F Area Seepage Basins followed by subsequent mixing processes within the basins and eventual infiltration into the subsurface resulted in contamination of the underlying vadose zone and downgradient groundwater. For simulating contaminant behavior and subsurface transport, a quantitative understanding of the interrelated discharge-mixing-infiltration system along with the resulting chemistry of fluids entering the subsurface is needed. An example of this need emerged as the F Area Seepage Basins was selected as a key case study demonstration site for the Advanced Simulation Capability for Environmental Management (ASCEM) Program. This modeling evaluation explored the importance of the wide variability in bulk wastewater chemistry as it propagated through the basins. The results are intended to generally improve and refine the conceptualization of infiltration of chemical wastes from seepage basins receiving variable waste streams and to specifically support the ASCEM case study model for the F Area Seepage Basins. Specific goals of this work included: (1) develop a technically-based 'charge-balanced' nominal source term chemistry for water infiltrating into the subsurface during basin operations, (2) estimate the nature of short term and long term variability in infiltrating water to support scenario development for uncertainty quantification (i.e., UQ analysis), (3) identify key geochemical factors that control overall basin water chemistry and the projected variability/stability, and (4) link wastewater chemistry to the subsurface based on monitoring well data. Results from this study provide data and understanding that can be used in further modeling efforts of the F Area groundwater plume. As identified in this study, key geochemical factors affecting basin
Modelling the Spatial Isotope Variability of Precipitation in Syria
Energy Technology Data Exchange (ETDEWEB)
Kattan, Z.; Kattaa, B. [Department of Geology, Atomic Energy Commission of Syria (AECS), Damascus (Syrian Arab Republic)
2013-07-15
Attempts were made to model the spatial variability of environmental isotope ({sup 18}O, {sup 2}H and {sup 3}H) compositions of precipitation in syria. Rainfall samples periodically collected on a monthly basis from 16 different stations were used for processing and demonstrating the spatial distributions of these isotopes, together with those of deuterium excess (d) values. Mathematically, the modelling process was based on applying simple polynomial models that take into consideration the effects of major geographic factors (Lon.E., Lat.N., and altitude). The modelling results of spatial distribution of stable isotopes ({sup 18}O and {sup 2}H) were generally good, as shown from the high correlation coefficients (R{sup 2} = 0.7-0.8), calculated between the observed and predicted values. In the case of deuterium excess and tritium distributions, the results were most likely approximates (R{sup 2} = 0.5-0.6). Improving the simulation of spatial isotope variability probably requires the incorporation of other local meteorological factors, such as relative air humidity, precipitation amount and vapour pressure, which are supposed to play an important role in such an arid country. (author)
Seychelles Dome variability in a high resolution ocean model
Nyadjro, E. S.; Jensen, T.; Richman, J. G.; Shriver, J. F.
2016-02-01
The Seychelles-Chagos Thermocline Ridge (SCTR; 5ºS-10ºS, 50ºE-80ºE) in the tropical Southwest Indian Ocean (SWIO) has been recognized as a region of prominence with regards to climate variability in the Indian Ocean. Convective activities in this region have regional consequences as it affect socio-economic livelihood of the people especially in the countries along the Indian Ocean rim. The SCTR is characterized by a quasi-permanent upwelling that is often associated with thermocline shoaling. This upwelling affects sea surface temperature (SST) variability. We present results on the variability and dynamics of the SCTR as simulated by the 1/12º high resolution HYbrid Coordinate Ocean Model (HYCOM). It is observed that locally, wind stress affects SST via Ekman pumping of cooler subsurface waters, mixing and anomalous zonal advection. Remotely, wind stress curl in the eastern equatorial Indian Ocean generates westward-propagating Rossby waves that impacts the depth of the thermocline which in turn impacts SST variability in the SCTR region. The variability of the contributions of these processes, especially with regard to the Indian Ocean Dipole (IOD) are further examined. In a typical positive IOD (PIOD) year, the net vertical velocity in the SCTR is negative year-round as easterlies along the region are intensified leading to a strong positive curl. This vertical velocity is caused mainly by anomalous local Ekman downwelling (with peak during September-November), a direct opposite to the climatology scenario when local Ekman pumping is positive (upwelling favorable) year-round. The anomalous remote contribution to the vertical velocity changes is minimal especially during the developing and peak stages of PIOD events. In a typical negative IOD (NIOD) year, anomalous vertical velocity is positive almost year-round with peaks in May and October. The remote contribution is positive, in contrast to the climatology and most of the PIOD years.
Shared Variable Oriented Parallel Precompiler for SPMD Model
Institute of Scientific and Technical Information of China (English)
无
1995-01-01
For the moment,commercial parallel computer systems with distributed memory architecture are usually provided with parallel FORTRAN or parallel C compliers,which are just traditional sequential FORTRAN or C compilers expanded with communication statements.Programmers suffer from writing parallel programs with communication statements. The Shared Variable Oriented Parallel Precompiler (SVOPP) proposed in this paper can automatically generate appropriate communication statements based on shared variables for SPMD(Single Program Multiple Data) computation model and greatly ease the parallel programming with high communication efficiency.The core function of parallel C precompiler has been successfully verified on a transputer-based parallel computer.Its prominent performance shows that SVOPP is probably a break-through in parallel programming technique.
Geospatial models of climatological variables distribution over Colombian territory
International Nuclear Information System (INIS)
Baron Leguizamon, Alicia
2003-01-01
Diverse studies have dealt on the existing relation between the variables temperature about the air and precipitation with the altitude; nevertheless they have been precise analyses or by regions, but no of them has gotten to constitute itself in a tool that reproduces the space distribution, of the temperature or the precipitation, taking into account orography and allowing to obtain from her data on these variables in a certain place. Cradle in the raised relation and from the multi-annual monthly information of the temperature of the air and the precipitation, it was calculated the vertical gradients of temperature and the related the precipitation to the altitude. After it, with base in the data of altitude provided by the DEM, one calculated the values of temperature and precipitation, and those values were interpolated to generate geospatial models monthly
Results of the first tests of the SIDRA satellite-borne instrument breadboard model
International Nuclear Information System (INIS)
Dudnik, O.V.; Kurbatov, E.V.; Avilov, A.M.; Titov, K.G.; Prieto, M; Sanchez, S.; Spassky, A.V.; Sylwester, J.; Gburek, S.; Podgorski, P.
2013-01-01
In this work, the results of the calibration of the solid-state detectors and electronic channels of the SIDRA satellite borne energetic charged particle spectrometer-telescope breadboard model are presented. The block schemes and experimental equipment used to conduct the thermal vacuum and electromagnetic compatibility tests of the assemblies and modules of the compact satellite equipment are described. The results of the measured thermal conditions of operation of the signal analog and digital processing critical modules of the SIDRA instrument prototype are discussed. Finally, the levels of conducted interference generated by the instrument model in the primary vehicle-borne power circuits are presented.
Energy Technology Data Exchange (ETDEWEB)
Aldemir, T., E-mail: aldemir.1@osu.ed [Ohio State University, Nuclear Engineering Program, Columbus, OH 43210 (United States); Guarro, S. [ASCA, Inc., 1720 S. Catalina Avenue, Suite 220, Redondo Beach, CA 90277-5501 (United States); Mandelli, D. [Ohio State University, Nuclear Engineering Program, Columbus, OH 43210 (United States); Kirschenbaum, J. [Ohio State University, Department of Computer Science and Engineering, Columbus, OH 43210 (United States); Mangan, L.A. [Ohio State University, Nuclear Engineering Program, Columbus, OH 43210 (United States); Bucci, P. [Ohio State University, Department of Computer Science and Engineering, Columbus, OH 43210 (United States); Yau, M. [ASCA, Inc., 1720 S. Catalina Avenue, Suite 220, Redondo Beach, CA 90277-5501 (United States); Ekici, E. [Ohio State University, Department of Electrical and Computer Engineering, Columbus, OH 43210 (United States); Miller, D.W.; Sun, X. [Ohio State University, Nuclear Engineering Program, Columbus, OH 43210 (United States); Arndt, S.A. [U.S. Nuclear Regulatory Commission, Washington, DC 20555-0001 (United States)
2010-10-15
The Markov/cell-to-cell mapping technique (CCMT) and the dynamic flowgraph methodology (DFM) are two system logic modeling methodologies that have been proposed to address the dynamic characteristics of digital instrumentation and control (I and C) systems and provide risk-analytical capabilities that supplement those provided by traditional probabilistic risk assessment (PRA) techniques for nuclear power plants. Both methodologies utilize a discrete state, multi-valued logic representation of the digital I and C system. For probabilistic quantification purposes, both techniques require the estimation of the probabilities of basic system failure modes, including digital I and C software failure modes, that appear in the prime implicants identified as contributors to a given system event of interest. As in any other system modeling process, the accuracy and predictive value of the models produced by the two techniques, depend not only on the intrinsic features of the modeling paradigm, but also and to a considerable extent on information and knowledge available to the analyst, concerning the system behavior and operation rules under normal and off-nominal conditions, and the associated controlled/monitored process dynamics. The application of the two methodologies is illustrated using a digital feedwater control system (DFWCS) similar to that of an operating pressurized water reactor. This application was carried out to demonstrate how the use of either technique, or both, can facilitate the updating of an existing nuclear power plant PRA model following an upgrade of the instrumentation and control system from analog to digital. Because of scope limitations, the focus of the demonstration of the methodologies was intentionally limited to aspects of digital I and C system behavior for which probabilistic data was on hand or could be generated within the existing project bounds of time and resources. The data used in the probabilistic quantification portion of the
Initial CGE Model Results Summary Exogenous and Endogenous Variables Tests
Energy Technology Data Exchange (ETDEWEB)
Edwards, Brian Keith [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Boero, Riccardo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Rivera, Michael Kelly [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-08-07
The following discussion presents initial results of tests of the most recent version of the National Infrastructure Simulation and Analysis Center Dynamic Computable General Equilibrium (CGE) model developed by Los Alamos National Laboratory (LANL). The intent of this is to test and assess the model’s behavioral properties. The test evaluated whether the predicted impacts are reasonable from a qualitative perspective. This issue is whether the predicted change, be it an increase or decrease in other model variables, is consistent with prior economic intuition and expectations about the predicted change. One of the purposes of this effort is to determine whether model changes are needed in order to improve its behavior qualitatively and quantitatively.
Variable slip wind generator modeling for real-time simulation
Energy Technology Data Exchange (ETDEWEB)
Gagnon, R.; Brochu, J.; Turmel, G. [Hydro-Quebec, Varennes, PQ (Canada). IREQ
2006-07-01
A model of a wind turbine using a variable slip wound-rotor induction machine was presented. The model was created as part of a library of generic wind generator models intended for wind integration studies. The stator winding of the wind generator was connected directly to the grid and the rotor was driven by the turbine through a drive train. The variable resistors was synthesized by an external resistor in parallel with a diode rectifier. A forced-commutated power electronic device (IGBT) was connected to the wound rotor by slip rings and brushes. Simulations were conducted in a Matlab/Simulink environment using SimPowerSystems blocks to model power systems elements and Simulink blocks to model the turbine, control system and drive train. Detailed descriptions of the turbine, the drive train and the control system were provided. The model's implementation in the simulator was also described. A case study demonstrating the real-time simulation of a wind generator connected at the distribution level of a power system was presented. Results of the case study were then compared with results obtained from the SimPowerSystems off-line simulation. Results showed good agreement between the waveforms, demonstrating the conformity of the real-time and the off-line simulations. The capability of Hypersim for real-time simulation of wind turbines with power electronic converters in a distribution network was demonstrated. It was concluded that hardware-in-the-loop (HIL) simulation of wind turbine controllers for wind integration studies in power systems is now feasible. 5 refs., 1 tab., 6 figs.
Chamberlin, Phillip
2008-01-01
The Flare Irradiance Spectral Model (FISM) is an empirical model of the solar irradiance spectrum from 0.1 to 190 nm at 1 nm spectral resolution and on a 1-minute time cadence. The goal of FISM is to provide accurate solar spectral irradiances over the vacuum ultraviolet (VUV: 0-200 nm) range as input for ionospheric and thermospheric models. The seminar will begin with a brief overview of the FISM model, and also how the Solar Dynamics Observatory (SDO) EUV Variability Experiment (EVE) will contribute to improving FISM. Some current studies will then be presented that use FISM estimations of the solar VUV irradiance to quantify the contributions of the increased irradiance from flares to Earth's increased thermospheric and ionospheric densites. Initial results will also be presented from a study looking at the electron density increases in the Martian atmosphere during a solar flare. Results will also be shown quantifying the VUV contributions to the total flare energy budget for both the impulsive and gradual phases of solar flares. Lastly, an example of how FISM can be used to simplify the design of future solar VUV irradiance instruments will be discussed, using the future NOAA GOES-R Extreme Ultraviolet and X-Ray Sensors (EXIS) space weather instrument.
A decision model for financial assurance instruments in the upstream petroleum sector
International Nuclear Information System (INIS)
Ferreira, Doneivan; Suslick, Saul; Farley, Joshua; Costanza, Robert; Krivov, Sergey
2004-01-01
The main objective of this paper is to deepen the discussion regarding the application of financial assurance instruments, bonds, in the upstream oil sector. This paper will also attempt to explain the current choice of instruments within the sector. The concepts of environmental damages and internalization of environmental and regulatory costs will be briefly explored. Bonding mechanisms are presently being adopted by several governments with the objective of guaranteeing the availability of funds for end-of-leasing operations. Regulators are mainly concerned with the prospect of inheriting liabilities from lessees. Several forms of bonding instruments currently available were identified and a new instrument classification was proposed. Ten commonly used instruments were selected and analyzed under the perspective of both regulators and industry (surety, paid-in and periodic-payment collateral accounts, letters of credit, self-guarantees, investment grade securities, real estate collaterals, insurance policies, pools, and special funds). A multiattribute value function model was then proposed to examine current instrument preferences. Preliminary simulations confirm the current scenario where regulators are likely to require surety bonds, letters of credit, and periodic payment collateral account tools
Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability
Parsons, Luke Alexander
Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall
Estimation and variable selection for generalized additive partial linear models
Wang, Li
2011-08-01
We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.
Context Tree Estimation in Variable Length Hidden Markov Models
Dumont, Thierry
2011-01-01
We address the issue of context tree estimation in variable length hidden Markov models. We propose an estimator of the context tree of the hidden Markov process which needs no prior upper bound on the depth of the context tree. We prove that the estimator is strongly consistent. This uses information-theoretic mixture inequalities in the spirit of Finesso and Lorenzo(Consistent estimation of the order for Markov and hidden Markov chains(1990)) and E.Gassiat and S.Boucheron (Optimal error exp...
Remote sensing of the Canadian Arctic: Modelling biophysical variables
Liu, Nanfeng
It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodologies for monitoring and assessing Arctic vegetation over large areas. The goal of this research was to explore the potential of hyperspectral and high spatial resolution multispectral remote sensing data for modelling two important Arctic biophysical variables: Percent Vegetation Cover (PVC) and the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). A series of field experiments were conducted to collect PVC and fAPAR at three Canadian Arctic sites: (1) Sabine Peninsula, Melville Island, NU; (2) Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU; and (3) Apex River Watershed (ARW), Baffin Island, NU. Linear relationships between biophysical variables and Vegetation Indices (VIs) were examined at different spatial scales using field spectra (for the Sabine Peninsula site) and high spatial resolution satellite data (for the CBAWO and ARW sites). At the Sabine Peninsula site, hyperspectral VIs exhibited a better performance for modelling PVC than multispectral VIs due to their capacity for sampling fine spectral features. The optimal hyperspectral bands were located at important spectral features observed in Arctic vegetation spectra, including leaf pigment absorption in the red wavelengths and at the red-edge, leaf water absorption in the near infrared, and leaf cellulose and lignin absorption in the shortwave infrared. At the CBAWO and ARW sites, field PVC and fAPAR exhibited strong correlations (R2 > 0.70) with the NDVI (Normalized Difference Vegetation Index) derived from high-resolution WorldView-2 data. Similarly, high spatial resolution satellite-derived fAPAR was correlated to MODIS fAPAR (R2 = 0.68), with a systematic
Classification criteria of syndromes by latent variable models
DEFF Research Database (Denmark)
Petersen, Janne
2010-01-01
, although this is often desired. I have proposed a new method for predicting class membership that, in contrast to methods based on posterior probabilities of class membership, yields consistent estimates when regressed on explanatory variables in a subsequent analysis. There are four different basic models...... analyses. Part 1: HALS engages different phenotypic changes of peripheral lipoatrophy and central lipohypertrophy. There are several different definitions of HALS and no consensus on the number of phenotypes. Many of the definitions consist of counting fulfilled criteria on markers and do not include...
Modeling intraindividual variability with repeated measures data methods and applications
Hershberger, Scott L
2013-01-01
This book examines how individuals behave across time and to what degree that behavior changes, fluctuates, or remains stable.It features the most current methods on modeling repeated measures data as reported by a distinguished group of experts in the field. The goal is to make the latest techniques used to assess intraindividual variability accessible to a wide range of researchers. Each chapter is written in a ""user-friendly"" style such that even the ""novice"" data analyst can easily apply the techniques.Each chapter features:a minimum discussion of mathematical detail;an empirical examp
Variable recruitment fluidic artificial muscles: modeling and experiments
International Nuclear Information System (INIS)
Bryant, Matthew; Meller, Michael A; Garcia, Ephrahim
2014-01-01
We investigate taking advantage of the lightweight, compliant nature of fluidic artificial muscles to create variable recruitment actuators in the form of artificial muscle bundles. Several actuator elements at different diameter scales are packaged to act as a single actuator device. The actuator elements of the bundle can be connected to the fluidic control circuit so that different groups of actuator elements, much like individual muscle fibers, can be activated independently depending on the required force output and motion. This novel actuation concept allows us to save energy by effectively impedance matching the active size of the actuators on the fly based on the instantaneous required load. This design also allows a single bundled actuator to operate in substantially different force regimes, which could be valuable for robots that need to perform a wide variety of tasks and interact safely with humans. This paper proposes, models and analyzes the actuation efficiency of this actuator concept. The analysis shows that variable recruitment operation can create an actuator that reduces throttling valve losses to operate more efficiently over a broader range of its force–strain operating space. We also present preliminary results of the design, fabrication and experimental characterization of three such bioinspired variable recruitment actuator prototypes. (paper)
Quantifying uncertainty, variability and likelihood for ordinary differential equation models
LENUS (Irish Health Repository)
Weisse, Andrea Y
2010-10-28
Abstract Background In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space. Results The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability. Conclusions While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.
Uncertainty importance measure for models with correlated normal variables
International Nuclear Information System (INIS)
Hao, Wenrui; Lu, Zhenzhou; Wei, Pengfei
2013-01-01
In order to explore the contributions by correlated input variables to the variance of the model output, the contribution decomposition of the correlated input variables based on Mara's definition is investigated in detail. By taking the quadratic polynomial output without cross term as an illustration, the solution of the contribution decomposition is derived analytically using the statistical inference theory. After the correction of the analytical solution is validated by the numerical examples, they are employed to two engineering examples to show their wide application. The derived analytical solutions can directly be used to recognize the contributions by the correlated input variables in case of the quadratic or linear polynomial output without cross term, and the analytical inference method can be extended to the case of higher order polynomial output. Additionally, the origins of the interaction contribution of the correlated inputs are analyzed, and the comparisons of the existing contribution indices are completed, on which the engineer can select the suitable indices to know the necessary information. At last, the degeneration of the correlated inputs to the uncorrelated ones and some computational issues are discussed in concept
New earth system model for optical performance evaluation of space instruments.
Ryu, Dongok; Kim, Sug-Whan; Breault, Robert P
2017-03-06
In this study, a new global earth system model is introduced for evaluating the optical performance of space instruments. Simultaneous imaging and spectroscopic results are provided using this global earth system model with fully resolved spatial, spectral, and temporal coverage of sub-models of the Earth. The sun sub-model is a Lambertian scattering sphere with a 6-h scale and 295 lines of solar spectral irradiance. The atmospheric sub-model has a 15-layer three-dimensional (3D) ellipsoid structure. The land sub-model uses spectral bidirectional reflectance distribution functions (BRDF) defined by a semi-empirical parametric kernel model. The ocean is modeled with the ocean spectral albedo after subtracting the total integrated scattering of the sun-glint scatter model. A hypothetical two-mirror Cassegrain telescope with a 300-mm-diameter aperture and 21.504 mm × 21.504-mm focal plane imaging instrument is designed. The simulated image results are compared with observational data from HRI-VIS measurements during the EPOXI mission for approximately 24 h from UTC Mar. 18, 2008. Next, the defocus mapping result and edge spread function (ESF) measuring result show that the distance between the primary and secondary mirror increases by 55.498 μm from the diffraction-limited condition. The shift of the focal plane is determined to be 5.813 mm shorter than that of the defocused focal plane, and this result is confirmed through the estimation of point spread function (PSF) measurements. This study shows that the earth system model combined with an instrument model is a powerful tool that can greatly help the development phase of instrument missions.
Saragih, Sahat; Napitupulu, E. Elvis; Fauzi, Amin
2017-01-01
This research aims to develop a student-centered learning model based on local culture and instrument of mathematical higher order thinking of junior high school students in the frame of the 2013-Curriculum in North Sumatra, Indonesia. The subjects of the research are seventh graders which are taken proportionally random consisted of three public…
Realization of computer-controlled CAMAC model through the technology of virtual instrument
International Nuclear Information System (INIS)
Le Yi; Li Cheng; Liao Juanjuan; Zhou Xin
1997-01-01
The author is to introduce virtual instrument system and basic features of its typical software development platform, and show this system's superiority and fitness to physical experiments by the example of the CAMAC model ADC2249A, which is often used in nuclear physics experiments
Cost prediction model for various payloads and instruments for the Space Shuttle Orbiter
Hoffman, F. E.
1984-01-01
The following cost parameters of the space shuttle were undertaken: (1) to develop a cost prediction model for various payload classes of instruments and experiments for the Space Shuttle Orbiter; and (2) to show the implications of various payload classes on the cost of: reliability analysis, quality assurance, environmental design requirements, documentation, parts selection, and other reliability enhancing activities.
A mathematical model for describing the mechanical behaviour of root canal instruments.
Zhang, E W; Cheung, G S P; Zheng, Y F
2011-01-01
The purpose of this study was to establish a general mathematical model for describing the mechanical behaviour of root canal instruments by combining a theoretical analytical approach with a numerical finite-element method. Mathematical formulas representing the longitudinal (taper, helical angle and pitch) and cross-sectional configurations and area, the bending and torsional inertia, the curvature of the boundary point and the (geometry of) loading condition were derived. Torsional and bending stresses and the resultant deformation were expressed mathematically as a function of these geometric parameters, modulus of elasticity of the material and the applied load. As illustrations, three brands of NiTi endodontic files of different cross-sectional configurations (ProTaper, Hero 642, and Mani NRT) were analysed under pure torsion and pure bending situation by entering the model into a finite-element analysis package (ANSYS). Numerical results confirmed that mathematical models were a feasible method to analyse the mechanical properties and predict the stress and deformation for root canal instruments during root canal preparation. Mathematical and numerical model can be a suitable way to examine mechanical behaviours as a criterion of the instrument design and to predict the stress and strain experienced by the endodontic instruments during root canal preparation. © 2010 International Endodontic Journal.
The Scanning Theremin Microscope: A Model Scanning Probe Instrument for Hands-On Activities
Quardokus, Rebecca C.; Wasio, Natalie A.; Kandel, S. Alex
2014-01-01
A model scanning probe microscope, designed using similar principles of operation to research instruments, is described. Proximity sensing is done using a capacitance probe, and a mechanical linkage is used to scan this probe across surfaces. The signal is transduced as an audio tone using a heterodyne detection circuit analogous to that used in…
Understanding and Measuring Evaluation Capacity: A Model and Instrument Validation Study
Taylor-Ritzler, Tina; Suarez-Balcazar, Yolanda; Garcia-Iriarte, Edurne; Henry, David B.; Balcazar, Fabricio E.
2013-01-01
This study describes the development and validation of the Evaluation Capacity Assessment Instrument (ECAI), a measure designed to assess evaluation capacity among staff of nonprofit organizations that is based on a synthesis model of evaluation capacity. One hundred and sixty-nine staff of nonprofit organizations completed the ECAI. The 68-item…
Viscous dark energy models with variable G and Λ
International Nuclear Information System (INIS)
Arbab, Arbab I.
2008-01-01
We consider a cosmological model with bulk viscosity η and variable cosmological A ∝ ρ -α , alpha = const and gravitational G constants. The model exhibits many interesting cosmological features. Inflation proceeds due to the presence of bulk viscosity and dark energy without requiring the equation of state p=-ρ. During the inflationary era the energy density ρ does not remain constant, as in the de-Sitter type. Moreover, the cosmological and gravitational constants increase exponentially with time, whereas the energy density and viscosity decrease exponentially with time. The rate of mass creation during inflation is found to be very huge suggesting that all matter in the universe is created during inflation. (author)
Constrained variability of modeled T:ET ratio across biomes
Fatichi, Simone; Pappas, Christoforos
2017-07-01
A large variability (35-90%) in the ratio of transpiration to total evapotranspiration (referred here as T:ET) across biomes or even at the global scale has been documented by a number of studies carried out with different methodologies. Previous empirical results also suggest that T:ET does not covary with mean precipitation and has a positive dependence on leaf area index (LAI). Here we use a mechanistic ecohydrological model, with a refined process-based description of evaporation from the soil surface, to investigate the variability of T:ET across biomes. Numerical results reveal a more constrained range and higher mean of T:ET (70 ± 9%, mean ± standard deviation) when compared to observation-based estimates. T:ET is confirmed to be independent from mean precipitation, while it is found to be correlated with LAI seasonally but uncorrelated across multiple sites. Larger LAI increases evaporation from interception but diminishes ground evaporation with the two effects largely compensating each other. These results offer mechanistic model-based evidence to the ongoing research about the patterns of T:ET and the factors influencing its magnitude across biomes.
Modeling the variability of shapes of a human placenta.
Yampolsky, M; Salafia, C M; Shlakhter, O; Haas, D; Eucker, B; Thorp, J
2008-09-01
Placentas are generally round/oval in shape, but "irregular" shapes are common. In the Collaborative Perinatal Project data, irregular shapes were associated with lower birth weight for placental weight, suggesting variably shaped placentas have altered function. (I) Using a 3D one-parameter model of placental vascular growth based on Diffusion Limited Aggregation (an accepted model for generating highly branched fractals), models were run with a branching density growth parameter either fixed or perturbed at either 5-7% or 50% of model growth. (II) In a data set with detailed measures of 1207 placental perimeters, radial standard deviations of placental shapes were calculated from the umbilical cord insertion, and from the centroid of the shape (a biologically arbitrary point). These two were compared to the difference between the observed scaling exponent and the Kleiber scaling exponent (0.75), considered optimal for vascular fractal transport systems. Spearman's rank correlation considered pcentroid) was associated with differences from the Kleiber exponent (p=0.006). A dynamical DLA model recapitulates multilobate and "star" placental shapes via changing fractal branching density. We suggest that (1) irregular placental outlines reflect deformation of the underlying placental fractal vascular network, (2) such irregularities in placental outline indicate sub-optimal branching structure of the vascular tree, and (3) this accounts for the lower birth weight observed in non-round/oval placentas in the Collaborative Perinatal Project.
Methods and Models of Market Risk Stress-Testing of the Portfolio of Financial Instruments
Directory of Open Access Journals (Sweden)
Alexander M. Karminsky
2015-01-01
Full Text Available Amid instability of financial markets and macroeconomic situation the necessity of improving bank risk-management instrument arises. New economic reality defines the need for searching for more advanced approaches of estimating banks vulnerability to exceptional, but plausible events. Stress-testing belongs to such instruments. The paper reviews and compares the models of market risk stress-testing of the portfolio of different financial instruments. These days the topic of the paper is highly acute due to the fact that now stress-testing is becoming an integral part of anticrisis risk-management amid macroeconomic instability and appearance of new risks together with close interest to the problem of risk-aggregation. The paper outlines the notion of stress-testing and gives coverage of goals, functions of stress-tests and main criteria for market risk stress-testing classification. The paper also stresses special aspects of scenario analysis. Novelty of the research is explained by elaborating the programme of aggregated complex multifactor stress-testing of the portfolio risk based on scenario analysis. The paper highlights modern Russian and foreign models of stress-testing both on solo-basis and complex. The paper lays emphasis on the results of stress-testing and revaluations of positions for all three complex models: methodology of the Central Bank of stress-testing portfolio risk, model relying on correlations analysis and copula model. The models of stress-testing on solo-basis are different for each financial instrument. Parametric StressVaR model is applicable to shares and options stress-testing;model based on "Grek" indicators is used for options; for euroobligation regional factor model is used. Finally some theoretical recommendations about managing market risk of the portfolio are given.
Multi-scale climate modelling over Southern Africa using a variable-resolution global model
CSIR Research Space (South Africa)
Engelbrecht, FA
2011-12-01
Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...
Automatic creation of Markov models for reliability assessment of safety instrumented systems
International Nuclear Information System (INIS)
Guo Haitao; Yang Xianhui
2008-01-01
After the release of new international functional safety standards like IEC 61508, people care more for the safety and availability of safety instrumented systems. Markov analysis is a powerful and flexible technique to assess the reliability measurements of safety instrumented systems, but it is fallible and time-consuming to create Markov models manually. This paper presents a new technique to automatically create Markov models for reliability assessment of safety instrumented systems. Many safety related factors, such as failure modes, self-diagnostic, restorations, common cause and voting, are included in Markov models. A framework is generated first based on voting, failure modes and self-diagnostic. Then, repairs and common-cause failures are incorporated into the framework to build a complete Markov model. Eventual simplification of Markov models can be done by state merging. Examples given in this paper show how explosively the size of Markov model increases as the system becomes a little more complicated as well as the advancement of automatic creation of Markov models
A Method for Modeling the Virtual Instrument Automatic Test System Based on the Petri Net
Institute of Scientific and Technical Information of China (English)
MA Min; CHEN Guang-ju
2005-01-01
Virtual instrument is playing the important role in automatic test system. This paper introduces a composition of a virtual instrument automatic test system and takes the VXIbus based a test software platform which is developed by CAT lab of the UESTC as an example. Then a method to model this system based on Petri net is proposed. Through this method, we can analyze the test task scheduling to prevent the deadlock or resources conflict. At last, this paper analyzes the feasibility of this method.
Time variability of X-ray binaries: observations with INTEGRAL. Modeling
International Nuclear Information System (INIS)
Cabanac, Clement
2007-01-01
The exact origin of the observed X and Gamma ray variability in X-ray binaries is still an open debate in high energy astrophysics. Among others, these objects are showing aperiodic and quasi-periodic luminosity variations on timescales as small as the millisecond. This erratic behavior must put constraints on the proposed emission processes occurring in the vicinity of the neutrons star or the stellar mass black-hole held by these objects. We propose here to study their behavior following 3 different ways: first we examine the evolution of a particular X-ray source discovered by INTEGRAL, IGR J19140+0951. Using timing and spectral data given by different instruments, we show that the source type is plausibly consistent with a High Mass X-ray Binary hosting a neutrons star. Subsequently, we propose a new method dedicated to the study of timing data coming from coded mask aperture instruments. Using it on INTEGRAL/ISGRI real data, we detect the presence of periodic and quasi-periodic features in some pulsars and micro-quasars at energies as high as a hundred keV. Finally, we suggest a model designed to describe the low frequency variability of X-ray binaries in their hardest state. This model is based on thermal comptonization of soft photons by a warm corona in which a pressure wave is propagating in cylindrical geometry. By computing both numerical simulations and analytical solution, we show that this model should be suitable to describe some of the typical features observed in X-ray binaries power spectra in their hard state and their evolution such as aperiodic noise and low frequency quasi-periodic oscillations. (author) [fr
Transient modelling of a natural circulation loop under variable pressure
International Nuclear Information System (INIS)
Vianna, Andre L.B.; Faccini, Jose L.H.; Su, Jian; Instituto de Engenharia Nuclear
2017-01-01
The objective of the present work is to model the transient operation of a natural circulation loop, which is one-tenth scale in height to a typical Passive Residual Heat Removal system (PRHR) of an Advanced Pressurized Water Nuclear Reactor and was designed to meet the single and two-phase flow similarity criteria to it. The loop consists of a core barrel with electrically heated rods, upper and lower plena interconnected by hot and cold pipe legs to a seven-tube shell heat exchanger of countercurrent design, and an expansion tank with a descending tube. A long transient characterized the loop operation, during which a phenomenon of self-pressurization, without self-regulation of the pressure, was experimentally observed. This represented a unique situation, named natural circulation under variable pressure (NCVP). The self-pressurization was originated in the air trapped in the expansion tank and compressed by the loop water dilatation, as it heated up during each experiment. The mathematical model, initially oriented to the single-phase flow, included the heat capacity of the structure and employed a cubic polynomial approximation for the density, in the buoyancy term calculation. The heater was modelled taking into account the different heat capacities of the heating elements and the heater walls. The heat exchanger was modelled considering the coolant heating, during the heat exchanging process. The self-pressurization was modelled as an isentropic compression of a perfect gas. The whole model was computationally implemented via a set of finite difference equations. The corresponding computational algorithm of solution was of the explicit, marching type, as for the time discretization, in an upwind scheme, regarding the space discretization. The computational program was implemented in MATLAB. Several experiments were carried out in the natural circulation loop, having the coolant flow rate and the heating power as control parameters. The variables used in the
Transient modelling of a natural circulation loop under variable pressure
Energy Technology Data Exchange (ETDEWEB)
Vianna, Andre L.B.; Faccini, Jose L.H.; Su, Jian, E-mail: avianna@nuclear.ufrj.br, E-mail: sujian@nuclear.ufrj.br, E-mail: faccini@ien.gov.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear; Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil). Lab. de Termo-Hidraulica Experimental
2017-07-01
The objective of the present work is to model the transient operation of a natural circulation loop, which is one-tenth scale in height to a typical Passive Residual Heat Removal system (PRHR) of an Advanced Pressurized Water Nuclear Reactor and was designed to meet the single and two-phase flow similarity criteria to it. The loop consists of a core barrel with electrically heated rods, upper and lower plena interconnected by hot and cold pipe legs to a seven-tube shell heat exchanger of countercurrent design, and an expansion tank with a descending tube. A long transient characterized the loop operation, during which a phenomenon of self-pressurization, without self-regulation of the pressure, was experimentally observed. This represented a unique situation, named natural circulation under variable pressure (NCVP). The self-pressurization was originated in the air trapped in the expansion tank and compressed by the loop water dilatation, as it heated up during each experiment. The mathematical model, initially oriented to the single-phase flow, included the heat capacity of the structure and employed a cubic polynomial approximation for the density, in the buoyancy term calculation. The heater was modelled taking into account the different heat capacities of the heating elements and the heater walls. The heat exchanger was modelled considering the coolant heating, during the heat exchanging process. The self-pressurization was modelled as an isentropic compression of a perfect gas. The whole model was computationally implemented via a set of finite difference equations. The corresponding computational algorithm of solution was of the explicit, marching type, as for the time discretization, in an upwind scheme, regarding the space discretization. The computational program was implemented in MATLAB. Several experiments were carried out in the natural circulation loop, having the coolant flow rate and the heating power as control parameters. The variables used in the
Taylor, Fiona; Reasner, David S; Carson, Robyn T; Deal, Linda S; Foley, Catherine; Iovin, Ramon; Lundy, J Jason; Pompilus, Farrah; Shields, Alan L; Silberg, Debra G
2016-10-01
The aim was to document, from the perspective of the empirical literature, the primary symptoms of functional dyspepsia (FD), evaluate the extent to which existing questionnaires target those symptoms, and, finally, identify any missing evidence that would impact the questionnaires' use in regulated clinical trials to assess treatment efficacy claims intended for product labeling. A literature review was conducted to identify the primary symptoms of FD and existing symptom-based FD patient-reported outcome (PRO) instruments. Following a database search, abstracts were screened and articles were retrieved for review. The primary symptoms of FD were organized into a conceptual model and the PRO instruments were evaluated for conceptual coverage as well as compared against evidentiary requirements presented in the FDA's PRO Guidance for Industry. Fifty-six articles and 16 instruments assessing FD symptoms were reviewed. Concepts listed in the Rome III criteria for FD (n = 7), those assessed by existing FD instruments (n = 34), and symptoms reported by patients in published qualitative research (n = 6) were summarized in the FD conceptual model. Except for vomiting, all of the identified symptoms from the published qualitative research reports were also specified in the Rome III criteria. Only three of the 16 instruments, the Dyspepsia Symptom Severity Index (DSSI), Nepean Dyspepsia Index (NDI), and Short-Form Nepean Dyspepsia Index (SF-NDI), measure all seven FD symptoms defined by the Rome III criteria. Among these three, each utilizes a 2-week recall period and 5-point Likert-type scale, and had evidence of patient involvement in development. Despite their coverage, when these instruments were evaluated in light of regulatory expectations, several issues jeopardized their potential qualification for substantiation of a labeling claim. No existing PRO instruments that measured all seven symptoms adhered to the regulatory principles necessary to support product
Karkar , Sami; Vergez , Christophe; Cochelin , Bruno
2012-01-01
International audience; We propose a new approach based on numerical continuation and bifurcation analysis for the study of physical models of instruments that produce self- sustained oscillation. Numerical continuation consists in following how a given solution of a set of equations is modified when one (or several) parameter of these equations are allowed to vary. Several physical models (clarinet, saxophone, and violin) are formulated as nonlinear dynamical systems, whose periodic solution...
A simple model explaining super-resolution in absolute optical instruments
Leonhardt, Ulf; Sahebdivan, Sahar; Kogan, Alex; Tyc, Tomáš
2015-05-01
We develop a simple, one-dimensional model for super-resolution in absolute optical instruments that is able to describe the interplay between sources and detectors. Our model explains the subwavelength sensitivity of a point detector to a point source reported in previous computer simulations and experiments (Miñano 2011 New J. Phys.13 125009; Miñano 2014 New J. Phys.16 033015).
Directory of Open Access Journals (Sweden)
Laura Florence Harris
Full Text Available Conscientious objection to abortion, clinicians' refusal to perform legal abortions because of their religious or moral beliefs, has been the subject of increasing debate among bioethicists, policymakers, and public health advocates in recent years. Conscientious objection policies are intended to balance reproductive rights and clinicians' beliefs. However, in practice, clinician objection can act as a barrier to abortion access-impinging on reproductive rights, and increasing unsafe abortion and related morbidity and mortality. There is little information about conscientious objection from a medical or public health perspective. A quantitative instrument is needed to assess prevalence of conscientious objection and to provide insight on its practice. This paper describes the development of a survey instrument to measure conscientious objection to abortion provision.A literature review, and in-depth formative interviews with stakeholders in Colombia were used to develop a conceptual model of conscientious objection. This model led to the development of a survey, which was piloted, and then administered, in Ghana.The model posits three domains of conscientious objection that form the basis for the survey instrument: 1 beliefs about abortion and conscientious objection; 2 actions related to conscientious objection and abortion; and 3 self-identification as a conscientious objector.The instrument is intended to be used to assess prevalence among clinicians trained to provide abortions, and to gain insight on how conscientious objection is practiced in a variety of settings. Its results can inform more effective and appropriate strategies to regulate conscientious objection.
International Nuclear Information System (INIS)
Randol, B M; Christian, E R
2015-01-01
Using publicly available data from the Voyager Low Energy Charged Particle (LECP) instruments, we investigate the form of the solar wind ion suprathermal tail in the outer heliosphere inside the termination shock. This tail has a commonly observed form in the inner heliosphere, that is, a power law with a particular spectral index. The Voyager spacecraft have taken data beyond 100 AU, farther than any other spacecraft. However, during extended periods of time, the data appears to be mostly background. We have developed a technique to self-consistently estimate the background seen by LECP due to cosmic rays using data from the Voyager cosmic ray instruments and a simple, semi-analytical model of the LECP instruments
International Nuclear Information System (INIS)
Lecuyer, Oskar; Bibas, Ruben
2012-01-01
In addition to the already present Climate and Energy package, the European Union (EU) plans to include a binding target to reduce energy consumption. We analyze the rationales the EU invokes to justify such an overlapping and develop a minimal common framework to study interactions arising from the combination of instruments reducing emissions, promoting renewable energy (RE) production and reducing energy demand through energy efficiency (EE) investments. We find that although all instruments tend to reduce GHG emissions and although a price on carbon tends also to give the right incentives for RE and EE, the combination of more than one instrument leads to significant antagonisms regarding major objectives of the policy package. The model allows to show in a single framework and to quantify the antagonistic effects of the joint promotion of RE and EE. We also show and quantify the effects of this joint promotion on ETS permit price, on wholesale market price and on energy production levels. (authors)
Comparing proxy and model estimates of hydroclimate variability and change over the Common Era
Hydro2k Consortium, Pages
2017-12-01
Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform
Resolving structural variability in network models and the brain.
Directory of Open Access Journals (Sweden)
Florian Klimm
2014-03-01
Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful
On the explaining-away phenomenon in multivariate latent variable models.
van Rijn, Peter; Rijmen, Frank
2015-02-01
Many probabilistic models for psychological and educational measurements contain latent variables. Well-known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the 'explaining-away' phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well-known latent variable models by using both theoretical and real data examples. © 2014 The British Psychological Society.
International Nuclear Information System (INIS)
Shin, Ho Cheol; Park, Moon Ghu; You, Skin
2006-01-01
Recently, many on-line approaches to instrument channel surveillance (drift monitoring and fault detection) have been reported worldwide. On-line monitoring (OLM) method evaluates instrument channel performance by assessing its consistency with other plant indications through parametric or non-parametric models. The heart of an OLM system is the model giving an estimate of the true process parameter value against individual measurements. This model gives process parameter estimate calculated as a function of other plant measurements which can be used to identify small sensor drifts that would require the sensor to be manually calibrated or replaced. This paper describes an improvement of auto associative kernel regression (AAKR) by introducing a correlation coefficient weighting on kernel distances. The prediction performance of the developed method is compared with conventional auto-associative kernel regression
Total Variability Modeling using Source-specific Priors
DEFF Research Database (Denmark)
Shepstone, Sven Ewan; Lee, Kong Aik; Li, Haizhou
2016-01-01
sequence of an utterance. In both cases the prior for the latent variable is assumed to be non-informative, since for homogeneous datasets there is no gain in generality in using an informative prior. This work shows in the heterogeneous case, that using informative priors for com- puting the posterior......, can lead to favorable results. We focus on modeling the priors using minimum divergence criterion or fac- tor analysis techniques. Tests on the NIST 2008 and 2010 Speaker Recognition Evaluation (SRE) dataset show that our proposed method beats four baselines: For i-vector extraction using an already...... trained matrix, for the short2-short3 task in SRE’08, five out of eight female and four out of eight male common conditions, were improved. For the core-extended task in SRE’10, four out of nine female and six out of nine male common conditions were improved. When incorporating prior information...
Milner, Allison; Aitken, Zoe; Kavanagh, Anne; LaMontagne, Anthony D; Pega, Frank; Petrie, Dennis
2017-06-23
Previous studies suggest that poor psychosocial job quality is a risk factor for mental health problems, but they use conventional regression analytic methods that cannot rule out reverse causation, unmeasured time-invariant confounding and reporting bias. This study combines two quasi-experimental approaches to improve causal inference by better accounting for these biases: (i) linear fixed effects regression analysis and (ii) linear instrumental variable analysis. We extract 13 annual waves of national cohort data including 13 260 working-age (18-64 years) employees. The exposure variable is self-reported level of psychosocial job quality. The instruments used are two common workplace entitlements. The outcome variable is the Mental Health Inventory (MHI-5). We adjust for measured time-varying confounders. In the fixed effects regression analysis adjusted for time-varying confounders, a 1-point increase in psychosocial job quality is associated with a 1.28-point improvement in mental health on the MHI-5 scale (95% CI: 1.17, 1.40; P variable analysis, a 1-point increase psychosocial job quality is related to 1.62-point improvement on the MHI-5 scale (95% CI: -0.24, 3.48; P = 0.088). Our quasi-experimental results provide evidence to confirm job stressors as risk factors for mental ill health using methods that improve causal inference. © The Author 2017. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C
2017-08-22
The calibration performance of Partial Least Squares regression (PLS) can be improved by eliminating uninformative variables. For PLS, many variable elimination methods have been developed. One is the Uninformative-Variable Elimination for PLS (UVE-PLS). However, the number of variables retained by UVE-PLS is usually still large. In UVE-PLS, variable elimination is repeated as long as the root mean squared error of cross validation (RMSECV) is decreasing. The set of variables in this first local minimum is retained. In this paper, a modification of UVE-PLS is proposed and investigated, in which UVE is repeated until no further reduction in variables is possible, followed by a search for the global RMSECV minimum. The method is called Global-Minimum Error Uninformative-Variable Elimination for PLS, denoted as GME-UVE-PLS or simply GME-UVE. After each iteration, the predictive ability of the PLS model, built with the remaining variable set, is assessed by RMSECV. The variable set with the global RMSECV minimum is then finally selected. The goal is to obtain smaller sets of variables with similar or improved predictability than those from the classical UVE-PLS method. The performance of the GME-UVE-PLS method is investigated using four data sets, i.e. a simulated set, NIR and NMR spectra, and a theoretical molecular descriptors set, resulting in twelve profile-response (X-y) calibrations. The selective and predictive performances of the models resulting from GME-UVE-PLS are statistically compared to those from UVE-PLS and 1-step UVE, one-sided paired t-tests. The results demonstrate that variable reduction with the proposed GME-UVE-PLS method, usually eliminates significantly more variables than the classical UVE-PLS, while the predictive abilities of the resulting models are better. With GME-UVE-PLS, a lower number of uninformative variables, without a chemical meaning for the response, may be retained than with UVE-PLS. The selectivity of the classical UVE method
Modelling carbon and nitrogen turnover in variably saturated soils
Batlle-Aguilar, J.; Brovelli, A.; Porporato, A.; Barry, D. A.
2009-04-01
Natural ecosystems provide services such as ameliorating the impacts of deleterious human activities on both surface and groundwater. For example, several studies have shown that a healthy riparian ecosystem can reduce the nutrient loading of agricultural wastewater, thus protecting the receiving surface water body. As a result, in order to develop better protection strategies and/or restore natural conditions, there is a growing interest in understanding ecosystem functioning, including feedbacks and nonlinearities. Biogeochemical transformations in soils are heavily influenced by microbial decomposition of soil organic matter. Carbon and nutrient cycles are in turn strongly sensitive to environmental conditions, and primarily to soil moisture and temperature. These two physical variables affect the reaction rates of almost all soil biogeochemical transformations, including microbial and fungal activity, nutrient uptake and release from plants, etc. Soil water saturation and temperature are not constants, but vary both in space and time, thus further complicating the picture. In order to interpret field experiments and elucidate the different mechanisms taking place, numerical tools are beneficial. In this work we developed a 3D numerical reactive-transport model as an aid in the investigation the complex physical, chemical and biological interactions occurring in soils. The new code couples the USGS models (MODFLOW 2000-VSF, MT3DMS and PHREEQC) using an operator-splitting algorithm, and is a further development an existing reactive/density-dependent flow model PHWAT. The model was tested using simplified test cases. Following verification, a process-based biogeochemical reaction network describing the turnover of carbon and nitrogen in soils was implemented. Using this tool, we investigated the coupled effect of moisture content and temperature fluctuations on nitrogen and organic matter cycling in the riparian zone, in order to help understand the relative
Examples of EOS Variables as compared to the UMM-Var Data Model
Cantrell, Simon; Lynnes, Chris
2016-01-01
In effort to provide EOSDIS clients a way to discover and use variable data from different providers, a Unified Metadata Model for Variables is being created. This presentation gives an overview of the model and use cases we are handling.
Unified models of interactions with gauge-invariant variables
International Nuclear Information System (INIS)
Zet, Gheorghe
2000-01-01
A model of gauge theory is formulated in terms of gauge-invariant variables over a 4-dimensional space-time. Namely, we define a metric tensor g μν ( μ , ν = 0,1,2,3) starting with the components F μν a and F μν a tilde of the tensor associated to the Yang-Mills fields and its dual: g μν = 1/(3Δ 1/3 ) (ε abc F μα a F αβ b tilde F βν c ). Here Δ is a scale factor which can be chosen of a convenient form so that the theory may be self-dual or not. The components g μν are interpreted as new gauge-invariant variables. The model is applied to the case when the gauge group is SU(2). For the space-time we choose two different manifolds: (i) the space-time is R x S 3 , where R is the real line and S 3 is the three-dimensional sphere; (ii) the space-time is endowed with axial symmetry. We calculate the components g μν of the new metric for the two cases in terms of SU(2) gauge potentials. Imposing the supplementary condition that the new metric coincides with the initial metric of the space-time, we obtain the field equations (of the first order in derivatives) for the gauge fields. In addition, we determine the scale factor Δ which is introduced in the definition of g μν to ensure the property of self-duality for our SU(2) gauge theory, namely, 1/(2√g)(ε αβστ g μα g νβ F στ a = F μν a , g = det (g μν ). In the case (i) we show that the space-time R x S 3 is not compatible with a self-dual SU(2) gauge theory, but in the case (ii) the condition of self-duality is satisfied. The model developed in our work can be considered as a possible way to unification of general relativity and Yang-Mills theories. This means that the gauge theory can be formulated in the close analogy with the general relativity, i.e. the Yang-Mills equations are equivalent to Einstein equations with the right-hand side of a simple form. (authors)
White dwarf models of supernovae and cataclysmic variables
International Nuclear Information System (INIS)
Nomoto, K.; Hashimoto, M.
1986-01-01
If the accreting white dwarf increases its mass to the Chandrasekhar mass, it will either explode as a Type I supernova or collapse to form a neutron star. In fact, there is a good agreement between the exploding white dwarf model for Type I supernovae and observations. We describe various types of evolution of accreting white dwarfs as a function of binary parameters (i.e,. composition, mass, and age of the white dwarf, its companion star, and mass accretion rate), and discuss the conditions for the precursors of exploding or collapsing white dwarfs, and their relevance to cataclysmic variables. Particular attention is given to helium star cataclysmics which might be the precursors of some Type I supernovae or ultrashort period x-ray binaries. Finally we present new evolutionary calculations using the updated nuclear reaction rates for the formation of O+Ne+Mg white dwarfs, and discuss the composition structure and their relevance to the model for neon novae. 61 refs., 14 figs
Multidecadal Variability in Surface Albedo Feedback Across CMIP5 Models
Schneider, Adam; Flanner, Mark; Perket, Justin
2018-02-01
Previous studies quantify surface albedo feedback (SAF) in climate change, but few assess its variability on decadal time scales. Using the Coupled Model Intercomparison Project Version 5 (CMIP5) multimodel ensemble data set, we calculate time evolving SAF in multiple decades from surface albedo and temperature linear regressions. Results are meaningful when temperature change exceeds 0.5 K. Decadal-scale SAF is strongly correlated with century-scale SAF during the 21st century. Throughout the 21st century, multimodel ensemble mean SAF increases from 0.37 to 0.42 W m-2 K-1. These results suggest that models' mean decadal-scale SAFs are good estimates of their century-scale SAFs if there is at least 0.5 K temperature change. Persistent SAF into the late 21st century indicates ongoing capacity for Arctic albedo decline despite there being less sea ice. If the CMIP5 multimodel ensemble results are representative of the Earth, we cannot expect decreasing Arctic sea ice extent to suppress SAF in the 21st century.
Functional capabilities of the breadboard model of SIDRA satellite-borne instrument
International Nuclear Information System (INIS)
Dudnik, O.V.; Kurbatov, E.V.; Titov, K.G.; Prieto, M.; Sanchez, S.; Sylwester, J.; Gburek, S.; Podgorski, P.
2013-01-01
This paper presents the structure, principles of operation and functional capabilities of the breadboard model of SIDRA compact satellite-borne instrument. SIDRA is intended for monitoring fluxes of high-energy charged particles under outer-space conditions. We present the reasons to develop a particle spectrometer and we list the main objectives to be achieved with the help of this instrument. The paper describes the major specifications of the analog and digital signal processing units of the breadboard model. A specially designed and developed data processing module based on the Actel ProAsic3E A3PE3000 FPGA is presented and compared with the all-in one digital processing signal board based on the Xilinx Spartan 3 XC3S1500 FPGA.
Modeling and Simulation of Variable Mass, Flexible Structures
Tobbe, Patrick A.; Matras, Alex L.; Wilson, Heath E.
2009-01-01
The advent of the new Ares I launch vehicle has highlighted the need for advanced dynamic analysis tools for variable mass, flexible structures. This system is composed of interconnected flexible stages or components undergoing rapid mass depletion through the consumption of solid or liquid propellant. In addition to large rigid body configuration changes, the system simultaneously experiences elastic deformations. In most applications, the elastic deformations are compatible with linear strain-displacement relationships and are typically modeled using the assumed modes technique. The deformation of the system is approximated through the linear combination of the products of spatial shape functions and generalized time coordinates. Spatial shape functions are traditionally composed of normal mode shapes of the system or even constraint modes and static deformations derived from finite element models of the system. Equations of motion for systems undergoing coupled large rigid body motion and elastic deformation have previously been derived through a number of techniques [1]. However, in these derivations, the mode shapes or spatial shape functions of the system components were considered constant. But with the Ares I vehicle, the structural characteristics of the system are changing with the mass of the system. Previous approaches to solving this problem involve periodic updates to the spatial shape functions or interpolation between shape functions based on system mass or elapsed mission time. These solutions often introduce misleading or even unstable numerical transients into the system. Plus, interpolation on a shape function is not intuitive. This paper presents an approach in which the shape functions are held constant and operate on the changing mass and stiffness matrices of the vehicle components. Each vehicle stage or component finite element model is broken into dry structure and propellant models. A library of propellant models is used to describe the
Blonda, Palma; Maso, Joan; Bombelli, Antonio; Plag, Hans Peter; McCallum, Ian; Serral, Ivette; Nativi, Stefano Stefano
2016-04-01
ConnectinGEO (Coordinating an Observation Network of Networks EnCompassing saTellite and IN-situ to fill the Gaps in European Observations" is an H2020 Coordination and Support Action with the primary goal of linking existing Earth Observation networks with science and technology (S&T) communities, the industry sector, the Group on Earth Observations (GEO), and Copernicus. The project will end in February 2017. Essential Variables (EVs) are defined by ConnectinGEO as "a minimal set of variables that determine the system's state and developments, are crucial for predicting system developments, and allow us to define metrics that measure the trajectory of the system". . Specific application-dependent characteristics, such as spatial and temporal resolution of observations and data quality thresholds, are not generally included in the EV definition. This definition and the present status of EV developments in different societal benefit areas was elaborated at the ConnectinGEO workshop "Towards a sustainability process for GEOSS Essential Variables (EVs)," which was held in Bari on June 11-12, 2015 (http://www.gstss.org/2015_Bari/). Presentations and reports contributed by a wide range of communities provided important inputs from different sectors for assessing the status of the EV development. In most thematic areas, the development of sets of EVs is a community process leading to an agreement on what is essential for the goals of the community. While there are many differences across the communities in the details of the criteria, methodologies and processes used to develop sets of EVs, there is also a considerable common core across the communities, particularly those with a more advanced discussion. In particular, there is some level of overlap in different topics (e.g., Climate and Water), and there is a potential to develop an integrated set of EVs common to several thematic areas as well as specific ones that satisfy only one community. The thematic areas with
Modeling 13.3nm Fe XXIII Flare Emissions Using the GOES-R EXIS Instrument
Rook, H.; Thiemann, E.
2017-12-01
The solar EUV spectrum is dominated by atomic transitions in ionized atoms in the solar atmosphere. As solar flares evolve, plasma temperatures and densities change, influencing abundances of various ions, changing intensities of different EUV wavelengths observed from the sun. Quantifying solar flare spectral irradiance is important for constraining models of Earth's atmosphere, improving communications quality, and controlling satellite navigation. However, high time cadence measurements of flare irradiance across the entire EUV spectrum were not available prior to the launch of SDO. The EVE MEGS-A instrument aboard SDO collected 0.1nm EUV spectrum data from 2010 until 2014, when the instrument failed. No current or future instrument is capable of similar high resolution and time cadence EUV observation. This necessitates a full EUV spectrum model to study EUV phenomena at Earth. It has been recently demonstrated that one hot flare EUV line, such as the 13.3nm Fe XXIII line, can be used to model cooler flare EUV line emissions, filling the role of MEGS-A. Since unblended measurements of Fe XXIII are typically unavailable, a proxy for the Fe XXIII line must be found. In this study, we construct two models of this line, first using the GOES 0.1-0.8nm soft x-ray (SXR) channel as the Fe XXIII proxy, and second using a physics-based model dependent on GOES emission measure and temperature data. We determine that the more sophisticated physics-based model shows better agreement with Fe XXIII measurements, although the simple proxy model also performs well. We also conclude that the high correlation between Fe XXIII emissions and the GOES 0.1-0.8nm band is because both emissions tend to peak near the GOES emission measure peak despite large differences in their contribution functions.
Statistical Time Series Models of Pilot Control with Applications to Instrument Discrimination
Altschul, R. E.; Nagel, P. M.; Oliver, F.
1984-01-01
A general description of the methodology used in obtaining the transfer function models and verification of model fidelity, frequency domain plots of the modeled transfer functions, numerical results obtained from an analysis of poles and zeroes obtained from z plane to s-plane conversions of the transfer functions, and the results of a study on the sequential introduction of other variables, both exogenous and endogenous into the loop are contained.
Goal-directed behaviour and instrumental devaluation: a neural system-level computational model
Directory of Open Access Journals (Sweden)
Francesco Mannella
2016-10-01
Full Text Available Devaluation is the key experimental paradigm used to demonstrate the presence of instrumental behaviours guided by goals in mammals. We propose a neural system-level computational model to address the question of which brain mechanisms allow the current value of rewards to control instrumental actions. The model pivots on and shows the computational soundness of the hypothesis for which the internal representation of instrumental manipulanda (e.g., levers activate the representation of rewards (or `action-outcomes', e.g. foods while attributing to them a value which depends on the current internal state of the animal (e.g., satiation for some but not all foods. The model also proposes an initial hypothesis of the integrated system of key brain components supporting this process and allowing the recalled outcomes to bias action selection: (a the sub-system formed by the basolateral amygdala and insular cortex acquiring the manipulanda-outcomes associations and attributing the current value to the outcomes; (b the three basal ganglia-cortical loops selecting respectively goals, associative sensory representations, and actions; (c the cortico-cortical and striato-nigro-striatal neural pathways supporting the selection, and selection learning, of actions based on habits and goals. The model reproduces and integrates the results of different devaluation experiments carried out with control rats and rats with pre- and post-training lesions of the basolateral amygdala, the nucleus accumbens core, the prelimbic cortex, and the dorso-medial striatum. The results support the soundness of the hypotheses of the model and show its capacity to integrate, at the system-level, the operations of the key brain structures underlying devaluation. Based on its hypotheses and predictions, the model also represents an operational framework to support the design and analysis of new experiments on the motivational aspects of goal-directed behaviour.
ExoMars Trace Gas Orbiter Instrument Modelling Approach to Streamline Science Operations
Munoz Fernandez, Michela; Frew, David; Ashman, Michael; Cardesin Moinelo, Alejandro; Garcia Beteta, Juan Jose; Geiger, Bernhard; Metcalfe, Leo; Nespoli, Federico; Muniz Solaz, Carlos
2018-05-01
ExoMars Trace Gas Orbiter (TGO) science operations activities are centralised at ESAC's Science Operations Centre (SOC). The SOC receives the inputs from the principal investigators (PIs) in order to implement and deliver the spacecraft pointing requests and instrument timelines to the Mission Operations Centre (MOC). The high number of orbits per planning cycle has made it necessary to abstract the planning interactions between the SOC and the PI teams at the observation level. This paper describes the modelling approach we have conducted for TGOÃs instruments to streamline science operations. We have created dynamic observation types that scale to adapt to the conditions specified by the PI teams including observation timing, and pointing block parameters calculated from observation geometry. This approach is considered and improvement with respect to previous missions where the generation of the observation pointing and commanding requests was performed manually by the instrument teams. Automation software assists us to effectively handle the high density of planned orbits with increasing volume of scientific data and to successfully meet opportunistic scientific goals and objectives. Our planning tool combines the instrument observation definition files provided by the PIs together with the flight dynamics products to generate the Pointing Requests and the instrument timeline (ITL). The ITL contains all the validated commands at the TC sequence level and computes the resource envelopes (data rate, power, data volume) within the constraints. At the SOC, our main goal is to maximise the science output while minimising the number of iterations among the teams, ensuring that the timeline does not violate the state transitions allowed in the Mission Operations Rules and Constraints Document.
Francis, P; Eastwood, K W; Bodani, V; Looi, T; Drake, J M
2018-05-07
This work explores the feasibility of creating and accurately controlling an instrument for robotic surgery with a 2 mm diameter and a three degree-of-freedom (DoF) wrist which is compatible with the da Vinci platform. The instrument's wrist is composed of a two DoF bending notched-nitinol tube pattern, for which a kinematic model has been developed. A base mechanism for controlling the wrist is designed for integration with the da Vinci Research Kit. A basic teleoperation task is successfully performed using two of the miniature instruments. The performance and accuracy of the instrument suggest that creating and accurately controlling a 2 mm diameter instrument is feasible and the design and modelling proposed in this work provide a basis for future miniature instrument development.
VAM2D: Variably saturated analysis model in two dimensions
International Nuclear Information System (INIS)
Huyakorn, P.S.; Kool, J.B.; Wu, Y.S.
1991-10-01
This report documents a two-dimensional finite element model, VAM2D, developed to simulate water flow and solute transport in variably saturated porous media. Both flow and transport simulation can be handled concurrently or sequentially. The formulation of the governing equations and the numerical procedures used in the code are presented. The flow equation is approximated using the Galerkin finite element method. Nonlinear soil moisture characteristics and atmospheric boundary conditions (e.g., infiltration, evaporation and seepage face), are treated using Picard and Newton-Raphson iterations. Hysteresis effects and anisotropy in the unsaturated hydraulic conductivity can be taken into account if needed. The contaminant transport simulation can account for advection, hydrodynamic dispersion, linear equilibrium sorption, and first-order degradation. Transport of a single component or a multi-component decay chain can be handled. The transport equation is approximated using an upstream weighted residual method. Several test problems are presented to verify the code and demonstrate its utility. These problems range from simple one-dimensional to complex two-dimensional and axisymmetric problems. This document has been produced as a user's manual. It contains detailed information on the code structure along with instructions for input data preparation and sample input and printed output for selected test problems. Also included are instructions for job set up and restarting procedures. 44 refs., 54 figs., 24 tabs
Modeling Variable Phanerozoic Oxygen Effects on Physiology and Evolution.
Graham, Jeffrey B; Jew, Corey J; Wegner, Nicholas C
2016-01-01
Geochemical approximation of Earth's atmospheric O2 level over geologic time prompts hypotheses linking hyper- and hypoxic atmospheres to transformative events in the evolutionary history of the biosphere. Such correlations, however, remain problematic due to the relative imprecision of the timing and scope of oxygen change and the looseness of its overlay on the chronology of key biotic events such as radiations, evolutionary innovation, and extinctions. There are nevertheless general attributions of atmospheric oxygen concentration to key evolutionary changes among groups having a primary dependence upon oxygen diffusion for respiration. These include the occurrence of Devonian hypoxia and the accentuation of air-breathing dependence leading to the origin of vertebrate terrestriality, the occurrence of Carboniferous-Permian hyperoxia and the major radiation of early tetrapods and the origins of insect flight and gigantism, and the Mid-Late Permian oxygen decline accompanying the Permian extinction. However, because of variability between and error within different atmospheric models, there is little basis for postulating correlations outside the Late Paleozoic. Other problems arising in the correlation of paleo-oxygen with significant biological events include tendencies to ignore the role of blood pigment affinity modulation in maintaining homeostasis, the slow rates of O2 change that would have allowed for adaptation, and significant respiratory and circulatory modifications that can and do occur without changes in atmospheric oxygen. The purpose of this paper is thus to refocus thinking about basic questions central to the biological and physiological implications of O2 change over geological time.
Stochastic transport models for mixing in variable-density turbulence
Bakosi, J.; Ristorcelli, J. R.
2011-11-01
In variable-density (VD) turbulent mixing, where very-different- density materials coexist, the density fluctuations can be an order of magnitude larger than their mean. Density fluctuations are non-negligible in the inertia terms of the Navier-Stokes equation which has both quadratic and cubic nonlinearities. Very different mixing rates of different materials give rise to large differential accelerations and some fundamentally new physics that is not seen in constant-density turbulence. In VD flows material mixing is active in a sense far stronger than that applied in the Boussinesq approximation of buoyantly-driven flows: the mass fraction fluctuations are coupled to each other and to the fluid momentum. Statistical modeling of VD mixing requires accounting for basic constraints that are not important in the small-density-fluctuation passive-scalar-mixing approximation: the unit-sum of mass fractions, bounded sample space, and the highly skewed nature of the probability densities become essential. We derive a transport equation for the joint probability of mass fractions, equivalent to a system of stochastic differential equations, that is consistent with VD mixing in multi-component turbulence and consistently reduces to passive scalar mixing in constant-density flows.
Designing means and specifications for model FT-619 kidney function instrument
International Nuclear Information System (INIS)
Yu Yongding
1988-04-01
In this paper, it is pointed out that the model FT-619 Kidney Function Equipment is a new cost-effective nuclear medicine instrument, which takes the leading position in China. The performance of the model FT-619,especially the lead collimated scintillation detector has reached the same level as the advanced equipment in the world market. It is also described in this article in detail that the design of the lead collimator and the shielding as well as the detection efficiency have achieved the optimum level and that a comparison has been made with foreign products
Thermal Modeling of the Mars Reconnaissance Orbiter's Solar Panel and Instruments during Aerobraking
Dec, John A.; Gasbarre, Joseph F.; Amundsen, Ruth M.
2007-01-01
The Mars Reconnaissance Orbiter (MRO) launched on August 12, 2005 and started aerobraking at Mars in March 2006. During the spacecraft s design phase, thermal models of the solar panels and instruments were developed to determine which components would be the most limiting thermally during aerobraking. Having determined the most limiting components, thermal limits in terms of heat rate were established. Advanced thermal modeling techniques were developed utilizing Thermal Desktop and Patran Thermal. Heat transfer coefficients were calculated using a Direct Simulation Monte Carlo technique. Analysis established that the solar panels were the most limiting components during the aerobraking phase of the mission.
Variable Width Riparian Model Enhances Landscape and Watershed Condition
Abood, S. A.; Spencer, L.
2017-12-01
Riparian areas are ecotones that represent about 1% of USFS administered landscape and contribute to numerous valuable ecosystem functions such as wildlife habitat, stream water quality and flows, bank stability and protection against erosion, and values related to diversity, aesthetics and recreation. Riparian zones capture the transitional area between terrestrial and aquatic ecosystems with specific vegetation and soil characteristics which provide critical values/functions and are very responsive to changes in land management activities and uses. Two staff areas at the US Forest Service have coordinated on a two phase project to support the National Forests in their planning revision efforts and to address rangeland riparian business needs at the Forest Plan and Allotment Management Plan levels. The first part of the project will include a national fine scale (USGS HUC-12 digits watersheds) inventory of riparian areas on National Forest Service lands in western United States with riparian land cover, utilizing GIS capabilities and open source geospatial data. The second part of the project will include the application of riparian land cover change and assessment based on selected indicators to assess and monitor riparian areas on annual/5-year cycle basis.This approach recognizes the dynamic and transitional nature of riparian areas by accounting for hydrologic, geomorphic and vegetation data as inputs into the delineation process. The results suggest that incorporating functional variable width riparian mapping within watershed management planning can improve riparian protection and restoration. The application of Riparian Buffer Delineation Model (RBDM) approach can provide the agency Watershed Condition Framework (WCF) with observed riparian area condition on an annual basis and on multiple scales. The use of this model to map moderate to low gradient systems of sufficient width in conjunction with an understanding of the influence of distinctive landscape
Thermal Testing and Model Correlation for Advanced Topographic Laser Altimeter Instrument (ATLAS)
Patel, Deepak
2016-01-01
The Advanced Topographic Laser Altimeter System (ATLAS) part of the Ice Cloud and Land Elevation Satellite 2 (ICESat-2) is an upcoming Earth Science mission focusing on the effects of climate change. The flight instrument passed all environmental testing at GSFC (Goddard Space Flight Center) and is now ready to be shipped to the spacecraft vendor for integration and testing. This topic covers the analysis leading up to the test setup for ATLAS thermal testing as well as model correlation to flight predictions. Test setup analysis section will include areas where ATLAS could not meet flight like conditions and what were the limitations. Model correlation section will walk through changes that had to be made to the thermal model in order to match test results. The correlated model will then be integrated with spacecraft model for on-orbit predictions.
International Nuclear Information System (INIS)
Bucci, P.; Mangan, L. A.; Kirschenbaum, J.; Mandelli, D.; Aldemir, T.; Arndt, S. A.
2006-01-01
Markov models have the ability to capture the statistical dependence between failure events that can arise in the presence of complex dynamic interactions between components of digital instrumentation and control systems. One obstacle to the use of such models in an existing probabilistic risk assessment (PRA) is that most of the currently available PRA software is based on the static event-tree/fault-tree methodology which often cannot represent such interactions. We present an approach to the integration of Markov reliability models into existing PRAs by describing the Markov model of a digital steam generator feedwater level control system, how dynamic event trees (DETs) can be generated from the model, and how the DETs can be incorporated into an existing PRA with the SAPHIRE software. (authors)
Using the Rasch measurement model to design a report writing assessment instrument.
Carlson, Wayne R
2013-01-01
This paper describes how the Rasch measurement model was used to develop an assessment instrument designed to measure student ability to write law enforcement incident and investigative reports. The ability to write reports is a requirement of all law enforcement recruits in the state of Michigan and is a part of the state's mandatory basic training curriculum, which is promulgated by the Michigan Commission on Law Enforcement Standards (MCOLES). Recently, MCOLES conducted research to modernize its training and testing in the area of report writing. A structured validation process was used, which included: a) an examination of the job tasks of a patrol officer, b) input from content experts, c) a review of the professional research, and d) the creation of an instrument to measure student competency. The Rasch model addressed several measurement principles that were central to construct validity, which were particularly useful for assessing student performances. Based on the results of the report writing validation project, the state established a legitimate connectivity between the report writing standard and the essential job functions of a patrol officer in Michigan. The project also produced an authentic instrument for measuring minimum levels of report writing competency, which generated results that are valid for inferences of student ability. Ultimately, the state of Michigan must ensure the safety of its citizens by licensing only those patrol officers who possess a minimum level of core competency. Maintaining the validity and reliability of both the training and testing processes can ensure that the system for producing such candidates functions as intended.
Directory of Open Access Journals (Sweden)
Monique Rocha Peixoto dos Santos
Full Text Available Abstract Introduction: Pain is an individual experience influenced by multiple interacting factors. The “biopsychosocial” care model has gained popularity in response to growing research evidence indicating the influence of biological, psychological, and social factors on the pain experience. The implementation of this model is a challenge in the practice of the health professional. Objective: To perform the transcultural adaptation of the SCEBS method into Brazilian Portuguese. Methods: The instrument was translated and applied to 50 healthy subjects and 50 participants with non-specific chronic pain in the spine. The process of cross-cultural adaptation included the following steps: transcultural adaptation, content analysis of the scale, pre-test, revision, back-translation review, cross-cultural adaptation, revised text correction and final report. Results: The translated and adapted 51-item Portuguese version of the SCEBS method produced an instrument called SCEBS-BR. In the assessment by the target population, 50 adult users of the Brazilian Unified Health System answered the questionnaire and showed good understanding of the instrument on the verbal rating scale. Conclusion: The SCEBS-BR was proved to be easily understandable, showing good semantic validation regardless of schooling level or age, and can be considered adequate for clinical use.
Development and design of a late-model fitness test instrument based on LabView
Xie, Ying; Wu, Feiqing
2010-12-01
Undergraduates are pioneers of China's modernization program and undertake the historic mission of rejuvenating our nation in the 21st century, whose physical fitness is vital. A smart fitness test system can well help them understand their fitness and health conditions, thus they can choose more suitable approaches and make practical plans for exercising according to their own situation. following the future trends, a Late-model fitness test Instrument based on LabView has been designed to remedy defects of today's instruments. The system hardware consists of fives types of sensors with their peripheral circuits, an acquisition card of NI USB-6251 and a computer, while the system software, on the basis of LabView, includes modules of user register, data acquisition, data process and display, and data storage. The system, featured by modularization and an open structure, is able to be revised according to actual needs. Tests results have verified the system's stability and reliability.
Stratified flows with variable density: mathematical modelling and numerical challenges.
Murillo, Javier; Navas-Montilla, Adrian
2017-04-01
Stratified flows appear in a wide variety of fundamental problems in hydrological and geophysical sciences. They may involve from hyperconcentrated floods carrying sediment causing collapse, landslides and debris flows, to suspended material in turbidity currents where turbulence is a key process. Also, in stratified flows variable horizontal density is present. Depending on the case, density varies according to the volumetric concentration of different components or species that can represent transported or suspended materials or soluble substances. Multilayer approaches based on the shallow water equations provide suitable models but are not free from difficulties when moving to the numerical resolution of the governing equations. Considering the variety of temporal and spatial scales, transfer of mass and energy among layers may strongly differ from one case to another. As a consequence, in order to provide accurate solutions, very high order methods of proved quality are demanded. Under these complex scenarios it is necessary to observe that the numerical solution provides the expected order of accuracy but also converges to the physically based solution, which is not an easy task. To this purpose, this work will focus in the use of Energy balanced augmented solvers, in particular, the Augmented Roe Flux ADER scheme. References: J. Murillo , P. García-Navarro, Wave Riemann description of friction terms in unsteady shallow flows: Application to water and mud/debris floods. J. Comput. Phys. 231 (2012) 1963-2001. J. Murillo B. Latorre, P. García-Navarro. A Riemann solver for unsteady computation of 2D shallow flows with variable density. J. Comput. Phys.231 (2012) 4775-4807. A. Navas-Montilla, J. Murillo, Energy balanced numerical schemes with very high order. The Augmented Roe Flux ADER scheme. Application to the shallow water equations, J. Comput. Phys. 290 (2015) 188-218. A. Navas-Montilla, J. Murillo, Asymptotically and exactly energy balanced augmented flux
Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective
Energy Technology Data Exchange (ETDEWEB)
Cole, Wesley [National Renewable Energy Lab. (NREL), Golden, CO (United States); Frew, Bethany [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mai, Trieu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Blanford, Geoffrey [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Young, David [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Marcy, Cara [U.S. Energy Information Administration, Washington, DC (United States); Namovicz, Chris [U.S. Energy Information Administration, Washington, DC (United States); Edelman, Risa [US Environmental Protection Agency (EPA), Washington, DC (United States); Meroney, Bill [US Environmental Protection Agency (EPA), Washington, DC (United States); Sims, Ryan [US Environmental Protection Agency (EPA), Washington, DC (United States); Stenhouse, Jeb [US Environmental Protection Agency (EPA), Washington, DC (United States); Donohoo-Vallett, Paul [Dept. of Energy (DOE), Washington DC (United States)
2017-11-01
Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision-makers. With the recent surge in variable renewable energy (VRE) generators — primarily wind and solar photovoltaics — the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treating VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.
Estimating net present value variability for deterministic models
van Groenendaal, W.J.H.
1995-01-01
For decision makers the variability in the net present value (NPV) of an investment project is an indication of the project's risk. So-called risk analysis is one way to estimate this variability. However, risk analysis requires knowledge about the stochastic character of the inputs. For large,
Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed
2017-05-01
Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.
Modelling of XCO2 Surfaces Based on Flight Tests of TanSat Instruments
Directory of Open Access Journals (Sweden)
Li Li Zhang
2016-11-01
Full Text Available The TanSat carbon satellite is to be launched at the end of 2016. In order to verify the performance of its instruments, a flight test of TanSat instruments was conducted in Jilin Province in September, 2015. The flight test area covered a total area of about 11,000 km2 and the underlying surface cover included several lakes, forest land, grassland, wetland, farmland, a thermal power plant and numerous cities and villages. We modeled the column-average dry-air mole fraction of atmospheric carbon dioxide (XCO2 surface based on flight test data which measured the near- and short-wave infrared (NIR reflected solar radiation in the absorption bands at around 760 and 1610 nm. However, it is difficult to directly analyze the spatial distribution of XCO2 in the flight area using the limited flight test data and the approximate surface of XCO2, which was obtained by regression modeling, which is not very accurate either. We therefore used the high accuracy surface modeling (HASM platform to fill the gaps where there is no information on XCO2 in the flight test area, which takes the approximate surface of XCO2 as its driving field and the XCO2 observations retrieved from the flight test as its optimum control constraints. High accuracy surfaces of XCO2 were constructed with HASM based on the flight’s observations. The results showed that the mean XCO2 in the flight test area is about 400 ppm and that XCO2 over urban areas is much higher than in other places. Compared with OCO-2’s XCO2, the mean difference is 0.7 ppm and the standard deviation is 0.95 ppm. Therefore, the modelling of the XCO2 surface based on the flight test of the TanSat instruments fell within an expected and acceptable range.
International Nuclear Information System (INIS)
Kustas, W.P.; Prueger, J.H.; Hipps, L.E.; Hatfield, J.L.; Meek, D.
1998-01-01
Studies of surface energy and water balance generally require an accurate estimate of net radiation and its spatial distribution. A project quantifying both short term and seasonal water use of shrub and grass vegetation in the Jornada Experimental Range in New Mexico prompted a study to compare net radiation observations using two types of net radiometers currently being used in research. A set of 12 REBS net radiometers were compared with each other and one Swissteco, over wet and dry surfaces in an arid landscape under clear skies. The set of REBS exhibited significant differences in output over both surfaces. However, they could be cross calibrated to yield values within 10 W m −2 , on average. There was also a significant bias between the REBS and Swissteco over a dry surface, but not over a wet one. The two makes of instrument could be made to agree under the dry conditions by using regression or autoregression techniques. However, the resulting equations would induce bias for the wet surface condition. Thus, it is not possible to cross calibrate these two makes of radiometer over the range of environmental conditions observed. This result indicates that determination of spatial distribution of net radiation over a variable surface should be made with identical instruments which have been cross calibrated. The need still exists for development of a radiometer and calibration procedures which will produce accurate and consistent measurements over a range of surface conditions. (author)
Ares I Scale Model Acoustic Test Instrumentation for Acoustic and Pressure Measurements
Vargas, Magda B.; Counter, Douglas
2011-01-01
Ares I Scale Model Acoustic Test (ASMAT) is a 5% scale model test of the Ares I vehicle, launch pad and support structures conducted at MSFC to verify acoustic and ignition environments and evaluate water suppression systems Test design considerations 5% measurements must be scaled to full scale requiring high frequency measurements Users had different frequencies of interest Acoustics: 200 - 2,000 Hz full scale equals 4,000 - 40,000 Hz model scale Ignition Transient: 0 - 100 Hz full scale equals 0 - 2,000 Hz model scale Environment exposure Weather exposure: heat, humidity, thunderstorms, rain, cold and snow Test environments: Plume impingement heat and pressure, and water deluge impingement Several types of sensors were used to measure the environments Different instrument mounts were used according to the location and exposure to the environment This presentation addresses the observed effects of the selected sensors and mount design on the acoustic and pressure measurements
Directory of Open Access Journals (Sweden)
Márcia Guimarães de Mello Alves
2015-01-01
Full Text Available Demand-control has been the most widely used model to study job strain in various countries. However, researchers have used the model differently, thus hindering the comparison of results. Such heterogeneity appears in both the study instrument used and in the definition of the main exposure variable - high strain. This cross-sectional study aimed to assess differences between various ways of operationalizing job strain through association with prevalent hypertension in a cohort of workers (Pro-Health Study. No difference in the association between high job strain and hypertension was found according to the different ways of operationalizing exposure, even though prevalence varied widely, according to the adopted form, from 19.6% for quadrants to 42% for subtraction tertile. The authors recommend further studies to define the cutoff for exposure variables using combined subjective and objective data.
Sperber, K. R.; Palmer, T. N.
1996-11-01
The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall
Speidel, Stefanie; Sudra, Gunther; Senemaud, Julien; Drentschew, Maximilian; Müller-Stich, Beat Peter; Gutt, Carsten; Dillmann, Rüdiger
2008-03-01
Minimally invasive surgery has gained significantly in importance over the last decade due to the numerous advantages on patient-side. The surgeon has to adapt special operation-techniques and deal with difficulties like the complex hand-eye coordination, limited field of view and restricted mobility. To alleviate these constraints we propose to enhance the surgeon's capabilities by providing a context-aware assistance using augmented reality (AR) techniques. In order to generate a context-aware assistance it is necessary to recognize the current state of the intervention using intraoperatively gained sensor data and a model of the surgical intervention. In this paper we present the recognition of risk situations, the system warns the surgeon if an instrument gets too close to a risk structure. The context-aware assistance system starts with an image-based analysis to retrieve information from the endoscopic images. This information is classified and a semantic description is generated. The description is used to recognize the current state and launch an appropriate AR visualization. In detail we present an automatic vision-based instrument tracking to obtain the positions of the instruments. Situation recognition is performed using a knowledge representation based on a description logic system. Two augmented reality visualization programs are realized to warn the surgeon if a risk situation occurs.
Lai, Hanh; McJunkin, Timothy R.; Miller, Carla J.; Scott, Jill R.; Almirall, José R.
2008-09-01
The combined use of SIMION 7.0 and the statistical diffusion simulation (SDS) user program in conjunction with SolidWorks® with COSMSOSFloWorks® fluid dynamics software to model a complete, commercial ion mobility spectrometer (IMS) was demonstrated for the first time and compared to experimental results for tests using compounds of immediate interest in the security industry (e.g., 2,4,6-trinitrotoluene, 2,7-dinitrofluorene, and cocaine). The effort of this research was to evaluate the predictive power of SIMION/SDS for application to IMS instruments. The simulation was evaluated against experimental results in three studies: (1) a drift:carrier gas flow rates study assesses the ability of SIMION/SDS to correctly predict the ion drift times; (2) a drift gas composition study evaluates the accuracy in predicting the resolution; (3) a gate width study compares the simulated peak shape and peak intensity with the experimental values. SIMION/SDS successfully predicted the correct drift time, intensity, and resolution trends for the operating parameters studied. Despite the need for estimations and assumptions in the construction of the simulated instrument, SIMION/SDS was able to predict the resolution between two ion species in air within 3% accuracy. The preliminary success of IMS simulations using SIMION/SDS software holds great promise for the design of future instruments with enhanced performance.
Bauer, Daniel J.; Curran, Patrick J.
2004-01-01
Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…
Selecting candidate predictor variables for the modelling of post ...
African Journals Online (AJOL)
Objectives: The objective of this project was to determine the variables most likely to be associated with post- .... (as defined subjectively by the research team) in global .... ed on their lack of knowledge of wealth scoring tools. ... HIV serology.
DEFF Research Database (Denmark)
Moeller, Niels C; Korsholm, Lars; Kristensen, Peter L
2008-01-01
BACKGROUND: Potentially, unit-specific in-vitro calibration of accelerometers could increase field data quality and study power. However, reduced inter-unit variability would only be important if random instrument variability contributes considerably to the total variation in field data. Therefor...
Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O
2016-06-01
Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.
Modelling for Fuel Optimal Control of a Variable Compression Engine
Nilsson, Ylva
2007-01-01
Variable compression engines are a mean to meet the demand on lower fuel consumption. A high compression ratio results in high engine efficiency, but also increases the knock tendency. On conventional engines with fixed compression ratio, knock is avoided by retarding the ignition angle. The variable compression engine offers an extra dimension in knock control, since both ignition angle and compression ratio can be adjusted. The central question is thus for what combination of compression ra...
Exact solutions to a nonlinear dispersive model with variable coefficients
International Nuclear Information System (INIS)
Yin Jun; Lai Shaoyong; Qing Yin
2009-01-01
A mathematical technique based on an auxiliary differential equation and the symbolic computation system Maple is employed to investigate a prototypical and nonlinear K(n, n) equation with variable coefficients. The exact solutions to the equation are constructed analytically under various circumstances. It is shown that the variable coefficients and the exponent appearing in the equation determine the quantitative change in the physical structures of the solutions.
Modeling and designing of variable-period and variable-pole-number undulator
Directory of Open Access Journals (Sweden)
I. Davidyuk
2016-02-01
Full Text Available The concept of permanent-magnet variable-period undulator (VPU was proposed several years ago and has found few implementations so far. The VPUs have some advantages as compared with conventional undulators, e.g., a wider range of radiation wavelength tuning and the option to increase the number of poles for shorter periods. Both these advantages will be realized in the VPU under development now at Budker INP. In this paper, we present the results of 2D and 3D magnetic field simulations and discuss some design features of this VPU.
Using Enthalpy as a Prognostic Variable in Atmospheric Modelling with Variable Composition
2016-04-14
Sela, personal communication, 2005). These terms are also routinely neglected in models. In models with a limited number of gaseous tracers, such as...so-called energy- exchange term (second term on the left- hand side) in Equation (5). The finite-difference schemes in existing atmospheric models have...equation for the sum of enthalpy and kinetic energy of horizontal motion is solved. This eliminates the energy- exchange term and automatically
Alternative models developed for estimating acute systemic toxicity are generally evaluated using in vivo LD50 values. However, in vivo acute systemic toxicity studies can produce variable results, even when conducted according to accepted test guidelines. This variability can ma...
3CE Methodology for Conducting a Modeling, Simulation, and Instrumentation Tool Capability Analysis
2010-05-01
flRmurn I F )T:Ir,tir)l! MCr)lto.-lng DHin nttbli..’"Ollc:~ E,;m:a..liut .!,)’l’lt’Mn:l’lll.ll~ t Managemen t F unction a l Arem 1 .5 Toola na...a modeling, simulation, and instrumentation (MS&I) environment. This methodology uses the DoDAF product set to document operational and systems...engineering process were identified and resolved, such as duplication of data elements derived from DoDAF operational and system views used to
Out- and insourcing, an analysis model for use of instrumented techniques
DEFF Research Database (Denmark)
Bang, Henrik Peter; Grønbæk, Niels; Larsen, Claus Richard
2017-01-01
We sketch an outline of a model for analyzing the use of ICT-tools, in particular CAS, in teaching designs employed by ‘generic’ teachers. Our model uses the business economics concepts out- and insourcing as metaphors within the dialectics of tool and content in planning of teaching. Outsourcing...... is done in order to enhance outcome through external partners. The converse concept of insourcing refers to internal sourcing. We shall adhere to the framework of the anthropological theory of the didactic, viewing out- and insourcing primarily as decisions about the technology component of praxeologies....... We use the model on a concrete example from Danish upper secondary mathematics to uncover what underlies teachers’ decisions (deliberate or colloquial) on incorporating instrumented approaches....
International Nuclear Information System (INIS)
Torres-Echeverria, A.C.; Martorell, S.; Thompson, H.A.
2011-01-01
This paper addresses the modeling of probability of dangerous failure on demand and spurious trip rate of safety instrumented systems that include MooN voting redundancies in their architecture. MooN systems are a special case of k-out-of-n systems. The first part of the article is devoted to the development of a time-dependent probability of dangerous failure on demand model with capability of handling MooN systems. The model is able to model explicitly common cause failure and diagnostic coverage, as well as different test frequencies and strategies. It includes quantification of both detected and undetected failures, and puts emphasis on the quantification of common cause failure to the system probability of dangerous failure on demand as an additional component. In order to be able to accommodate changes in testing strategies, special treatment is devoted to the analysis of system reconfiguration (including common cause failure) during test of one of its components, what is then included in the model. Another model for spurious trip rate is also analyzed and extended under the same methodology in order to empower it with similar capabilities. These two models are powerful enough, but at the same time simple, to be suitable for handling of dependability measures in multi-objective optimization of both system design and test strategies for safety instrumented systems. The level of modeling detail considered permits compliance with the requirements of the standard IEC 61508. The two models are applied to brief case studies to demonstrate their effectiveness. The results obtained demonstrated that the first model is adequate to quantify time-dependent PFD of MooN systems during different system states (i.e. full operation, test and repair) and different MooN configurations, which values are averaged to obtain the PFD avg . Also, it was demonstrated that the second model is adequate to quantify STR including spurious trips induced by internal component failure and
Edmunson, J.; Gaskin, J. A.; Danilatos, G.; Doloboff, I. J.; Effinger, M. R.; Harvey, R. P.; Jerman, G. A.; Klein-Schoder, R.; Mackie, W.; Magera, B.;
2016-01-01
The Miniaturized Variable Pressure Scanning Electron Microscope(MVP-SEM) project, funded by the NASA Planetary Instrument Concepts for the Advancement of Solar System Observations (PICASSO) Research Opportunities in Space and Earth Science (ROSES), will build upon previous miniaturized SEM designs for lunar and International Space Station (ISS) applications and recent advancements in variable pressure SEM's to design and build a SEM to complete analyses of samples on the surface of Mars using the atmosphere as an imaging medium. By the end of the PICASSO work, a prototype of the primary proof-of-concept components (i.e., the electron gun, focusing optics and scanning system)will be assembled and preliminary testing in a Mars analog chamber at the Jet Propulsion Laboratory will be completed to partially fulfill Technology Readiness Level to 5 requirements for those components. The team plans to have Secondary Electron Imaging(SEI), Backscattered Electron (BSE) detection, and Energy Dispersive Spectroscopy (EDS) capabilities through the MVP-SEM.
A model of the demand for Islamic banks debt-based financing instrument
Jusoh, Mansor; Khalid, Norlin
2013-04-01
This paper presents a theoretical analysis of the demand for debt-based financing instruments of the Islamic banks. Debt-based financing, such as through baibithamanajil and al-murabahah, is by far the most prominent of the Islamic bank financing and yet it has been largely ignored in Islamic economics literature. Most studies instead have been focusing on equity-based financing of al-mudharabah and al-musyarakah. Islamic bank offers debt-based financing through various instruments derived under the principle of exchange (ukud al-mu'awadhat) or more specifically, the contract of deferred sale. Under such arrangement, Islamic debt is created when goods are purchased and the payments are deferred. Thus, unlike debt of the conventional bank which is a form of financial loan contract to facilitate demand for liquid assets, this Islamic debt is created in response to the demand to purchase goods by deferred payment. In this paper we set an analytical framework that is based on an infinitely lived representative agent model (ILRA model) to analyze the demand for goods to be purchased by deferred payment. The resulting demand will then be used to derive the demand for Islamic debt. We also investigate theoretically, factors that may have an impact on the demand for Islamic debt.
A Latent-Variable Causal Model of Faculty Reputational Ratings.
King, Suzanne; Wolfle, Lee M.
A reanalysis was conducted of Saunier's research (1985) on sources of variation in the National Research Council (NRC) reputational ratings of university faculty. Saunier conducted a stepwise regression analysis using 12 predictor variables. Due to problems with multicollinearity and because of the atheoretical nature of stepwise regression,…
Variability of four-dimensional computed tomography patient models
Sonke, Jan-Jakob; Lebesque, Joos; van Herk, Marcel
2008-01-01
PURPOSE: To quantify the interfractional variability in lung tumor trajectory and mean position during the course of radiation therapy. METHODS AND MATERIALS: Repeat four-dimensional (4D) cone-beam computed tomography (CBCT) scans (median, nine scans/patient) routinely acquired during the course of
Ferrari, G.; Kozarski, M.; Gu, Y. J.; De Lazzari, C.; Di Molfetta, A.; Palko, K. J.; Zielinski, K.; Gorczynska, K.; Darowski, M.; Rakhorst, G.
2008-01-01
Purpose: Application of a comprehensive, user-friendly, digital computer circulatory model to estimate hemodynamic and ventricular variables. Methods: The closed-loop lumped parameter circulatory model represents the circulation at the level of large vessels. A variable elastance model reproduces
International Nuclear Information System (INIS)
Ubbes, W.F.; Yow, J.L. Jr.
1988-01-01
Instrumentation is developed for the Civilian Radioactive Waste Management Program to meet several different (and sometimes conflicting) objectives. This paper addresses instrumentation development for data needs that are related either directly or indirectly to a repository site, but does not touch on instrumentation for work with waste forms or other materials. Consequently, this implies a relatively large scale for the measurements, and an in situ setting for instrument performance. In this context, instruments are needed for site characterization to define phenomena, develop models, and obtain parameter values, and for later design and performance confirmation testing in the constructed repository. The former set of applications is more immediate, and is driven by the needs of program design and performance assessment activities. A host of general technical and nontechnical issues have arisen to challenge instrumentation development. Instruments can be classed into geomechanical, geohydrologic, or other specialty categories, but these issues cut across artificial classifications. These issues are outlined. Despite this imposing list of issues, several case histories are cited to evaluate progress in the area
Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective
Energy Technology Data Exchange (ETDEWEB)
Cole, Wesley J. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Frew, Bethany A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mai, Trieu T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst., Palo Alto, CA (United States); Blanford, Geoffrey [Electric Power Research Inst., Palo Alto, CA (United States); Young, David [Electric Power Research Inst., Palo Alto, CA (United States); Marcy, Cara [Energy Information Administration, Washington, DC (United States); Namovicz, Chris [Energy Information Administration, Washington, DC (United States); Edelman, Risa [Environmental Protection Agency, Washington, DC (United States); Meroney, Bill [Environmental Protection Agency; Sims, Ryan [Environmental Protection Agency; Stenhouse, Jeb [Environmental Protection Agency; Donohoo-Vallett, Paul [U.S. Department of Energy
2017-11-03
Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision makers. With the recent surge in variable renewable energy (VRE) generators - primarily wind and solar photovoltaics - the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. To assess current best practices, share methods and data, and identify future research needs for VRE representation in capacity expansion models, four capacity expansion modeling teams from the Electric Power Research Institute, the U.S. Energy Information Administration, the U.S. Environmental Protection Agency, and the National Renewable Energy Laboratory conducted two workshops of VRE modeling for national-scale capacity expansion models. The workshops covered a wide range of VRE topics, including transmission and VRE resource data, VRE capacity value, dispatch and operational modeling, distributed generation, and temporal and spatial resolution. The objectives of the workshops were both to better understand these topics and to improve the representation of VRE across the suite of models. Given these goals, each team incorporated model updates and performed additional analyses between the first and second workshops. This report summarizes the analyses and model 'experiments' that were conducted as part of these workshops as well as the various methods for treating VRE among the four modeling teams. The report also reviews the findings and learnings from the two workshops. We emphasize the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making.
Model of the lines of sight for an off-axis optical instrument Pleiades
Sauvage, Dominique; Gaudin-Delrieu, Catherine; Tournier, Thierry
2017-11-01
The future Earth observation missions aim at delivering images with a high resolution and a large field of view. These images have to be processed to get a very accurate localisation. In that goal, the individual lines of sight of each photosensitive element must be evaluated according to the localisation of the pixels in the focal plane. But, with off-axis Korsch telescope (like PLEIADES), the classical model has to be adapted. This is possible by using optical ground measurements made after the integration of the instrument. The processing of these results leads to several parameters, which are function of the offsets of the focal plane and the real focal length. All this study which has been proposed for the PLEIADES mission leads to a more elaborated model which provides the relation between the lines of sight and the location of the pixels, with a very good accuracy, close to the pixel size.
Directory of Open Access Journals (Sweden)
Chenj Bo
2016-11-01
Full Text Available One of the main fields of training future music teachers in Ukrainian system of higher education is instrumental music one, such as skills of performing and interpretive activities. The aim of the article is to design a model of the future music teachers’ readiness to performing and interpretive activities in musical and instrumental training. The process of modelling is based on several interrelated scientific approaches, including systemic, personality-centered, reflective, competence, active and creative ones. While designing a model of music future teachers’ readinesses to musical interpretive activities, its philosophical, informative, interactive, hedonistic, creative functions are taken into account. Important theoretical and methodological factors are thought to be principles of musical and pedagogical education: culture correspondence and reflection; unity of emotional and conscious, artistic and technical items in musical education; purposeful interrelations and art and pedagogical communication between teachers and students; intensification of music and creative activity. Above-mentioned pedagogical phenomenon is subdivided into four components: motivation-oriented, cognitive-evaluating, performance-independent, creative and productive. For each component relevant criteria and indicators are identified. The stages of future music teachers’ readiness to performing interpretative activity are highlighted: information searching one, which contributes to the implementation of complex diagnostic methods (surveys, questionnaires, testing; regulative and performing one, which is characterized by future music teachers’ immersion into music performing and interpretative activities; operational and reflective stage, which involves activation of mechanisms of future music teachers’ self-knowledge, self-realization, formation of skills of independent artistic and expressive various music genres and styles interpretation; projective and
Modelling and Multi-Variable Control of Refrigeration Systems
DEFF Research Database (Denmark)
Larsen, Lars Finn Slot; Holm, J. R.
2003-01-01
In this paper a dynamic model of a 1:1 refrigeration system is presented. The main modelling effort has been concentrated on a lumped parameter model of a shell and tube condenser. The model has shown good resemblance with experimental data from a test rig, regarding as well the static as the dyn......In this paper a dynamic model of a 1:1 refrigeration system is presented. The main modelling effort has been concentrated on a lumped parameter model of a shell and tube condenser. The model has shown good resemblance with experimental data from a test rig, regarding as well the static...... as the dynamic behavior. Based on this model the effects of the cross couplings has been examined. The influence of the cross couplings on the achievable control performance has been investigated. A MIMO controller is designed and the performance is compared with the control performance achieved by using...
A Novel Approach to model EPIC variable background
Marelli, M.; De Luca, A.; Salvetti, D.; Belfiore, A.
2017-10-01
One of the main aim of the EXTraS (Exploring the X-ray Transient and variable Sky) project is to characterise the variability of serendipitous XMM-Newton sources within each single observation. Unfortunately, 164 Ms out of the 774 Ms of cumulative exposure considered (21%) are badly affected by soft proton flares, hampering any classical analysis of field sources. De facto, the latest releases of the 3XMM catalog, as well as most of the analysis in literature, simply exclude these 'high background' periods from analysis. We implemented a novel SAS-indipendent approach to produce background-subtracted light curves, which allows to treat the case of very faint sources and very bright proton flares. EXTraS light curves of 3XMM-DR5 sources will be soon released to the community, together with new tools we are developing.
Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.
2018-05-01
Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed
Application of a model of instrumental conditioning to mobile robot control
Saksida, Lisa M.; Touretzky, D. S.
1997-09-01
Instrumental conditioning is a psychological process whereby an animal learns to associate its actions with their consequences. This type of learning is exploited in animal training techniques such as 'shaping by successive approximations,' which enables trainers to gradually adjust the animal's behavior by giving strategically timed reinforcements. While this is similar in principle to reinforcement learning, the real phenomenon includes many subtle effects not considered in the machine learning literature. In addition, a good deal of domain information is utilized by an animal learning a new task; it does not start from scratch every time it learns a new behavior. For these reasons, it is not surprising that mobile robot learning algorithms have yet to approach the sophistication and robustness of animal learning. A serious attempt to model instrumental learning could prove fruitful for improving machine learning techniques. In the present paper, we develop a computational theory of shaping at a level appropriate for controlling mobile robots. The theory is based on a series of mechanisms for 'behavior editing,' in which pre-existing behaviors, either innate or previously learned, can be dramatically changed in magnitude, shifted in direction, or otherwise manipulated so as to produce new behavioral routines. We have implemented our theory on Amelia, an RWI B21 mobile robot equipped with a gripper and color video camera. We provide results from training Amelia on several tasks, all of which were constructed as variations of one innate behavior, object-pursuit.
Directory of Open Access Journals (Sweden)
Paula Furtună
2013-03-01
Full Text Available Climatic changes are representing one of the major challenges of our century, these being forcasted according to climate scenarios and models, which represent plausible and concrete images of future climatic conditions. The results of climate models comparison regarding future water resources and temperature regime trend can become a useful instrument for decision makers in choosing the most effective decisions regarding economic, social and ecologic levels. The aim of this article is the analysis of temperature and pluviometric variability at the closest grid point to Cluj-Napoca, based on data provided by six different regional climate models (RCMs. Analysed on 30 year periods (2001-2030,2031-2060 and 2061-2090, the mean temperature has an ascending general trend, with great varability between periods. The precipitation expressed trough percentage deviation shows a descending general trend, which is more emphazied during 2031-2060 and 2061-2090.
International Nuclear Information System (INIS)
Meisner, Aaron M.; Finkbeiner, Douglas P.
2015-01-01
We apply the Finkbeiner et al. two-component thermal dust emission model to the Planck High Frequency Instrument maps. This parameterization of the far-infrared dust spectrum as the sum of two modified blackbodies (MBBs) serves as an important alternative to the commonly adopted single-MBB dust emission model. Analyzing the joint Planck/DIRBE dust spectrum, we show that two-component models provide a better fit to the 100-3000 GHz emission than do single-MBB models, though by a lesser margin than found by Finkbeiner et al. based on FIRAS and DIRBE. We also derive full-sky 6.'1 resolution maps of dust optical depth and temperature by fitting the two-component model to Planck 217-857 GHz along with DIRBE/IRAS 100 μm data. Because our two-component model matches the dust spectrum near its peak, accounts for the spectrum's flattening at millimeter wavelengths, and specifies dust temperature at 6.'1 FWHM, our model provides reliable, high-resolution thermal dust emission foreground predictions from 100 to 3000 GHz. We find that, in diffuse sky regions, our two-component 100-217 GHz predictions are on average accurate to within 2.2%, while extrapolating the Planck Collaboration et al. single-MBB model systematically underpredicts emission by 18.8% at 100 GHz, 12.6% at 143 GHz, and 7.9% at 217 GHz. We calibrate our two-component optical depth to reddening, and compare with reddening estimates based on stellar spectra. We find the dominant systematic problems in our temperature/reddening maps to be zodiacal light on large angular scales and the cosmic infrared background anisotropy on small angular scales
Use of a life-size three-dimensional-printed spine model for pedicle screw instrumentation training.
Park, Hyun Jin; Wang, Chenyu; Choi, Kyung Ho; Kim, Hyong Nyun
2018-04-16
Training beginners of the pedicle screw instrumentation technique in the operating room is limited because of issues related to patient safety and surgical efficiency. Three-dimensional (3D) printing enables training or simulation surgery on a real-size replica of deformed spine, which is difficult to perform in the usual cadaver or surrogate plastic models. The purpose of this study was to evaluate the educational effect of using a real-size 3D-printed spine model for training beginners of the free-hand pedicle screw instrumentation technique. We asked whether the use of a 3D spine model can improve (1) screw instrumentation accuracy and (2) length of procedure. Twenty life-size 3D-printed lumbar spine models were made from 10 volunteers (two models for each volunteer). Two novice surgeons who had no experience of free-hand pedicle screw instrumentation technique were instructed by an experienced surgeon, and each surgeon inserted 10 pedicle screws for each lumbar spine model. Computed tomography scans of the spine models were obtained to evaluate screw instrumentation accuracy. The length of time in completing the procedure was recorded. The results of the latter 10 spine models were compared with those of the former 10 models to evaluate learning effect. A total of 37/200 screws (18.5%) perforated the pedicle cortex with a mean of 1.7 mm (range, 1.2-3.3 mm). However, the latter half of the models had significantly less violation than the former half (10/100 vs. 27/100, p 3D-printed spine model can be an excellent tool for training beginners of the free-hand pedicle screw instrumentation.
Latent variable modeling%建立隐性变量模型
Institute of Scientific and Technical Information of China (English)
蔡力
2012-01-01
@@ A latent variable model, as the name suggests,is a statistical model that contains latent, that is, unobserved, variables.Their roots go back to Spearman's 1904 seminal work[1] on factor analysis,which is arguably the first well-articulated latent variable model to be widely used in psychology, mental health research, and allied disciplines.Because of the association of factor analysis with early studies of human intelligence, the fact that key variables in a statistical model are, on occasion, unobserved has been a point of lingering contention and controversy.The reader is assured, however, that a latent variable,defined in the broadest manner, is no more mysterious than an error term in a normal theory linear regression model or a random effect in a mixed model.
Torque Modeling and Control of a Variable Compression Engine
Bergström, Andreas
2003-01-01
The SAAB variable compression engine is a new engine concept that enables the fuel consumption to be radically cut by varying the compression ratio. A challenge with this new engine concept is that the compression ratio has a direct influence on the output torque, which means that a change in compression ratio also leads to a change in the torque. A torque change may be felt as a jerk in the movement of the car, and this is an undesirable effect since the driver has no control over the compre...
Design and Modeling of a Variable Heat Rejection Radiator
Miller, Jennifer R.; Birur, Gajanana C.; Ganapathi, Gani B.; Sunada, Eric T.; Berisford, Daniel F.; Stephan, Ryan
2011-01-01
Variable Heat Rejection Radiator technology needed for future NASA human rated & robotic missions Primary objective is to enable a single loop architecture for human-rated missions (1) Radiators are typically sized for maximum heat load in the warmest continuous environment resulting in a large panel area (2) Large radiator area results in fluid being susceptible to freezing at low load in cold environment and typically results in a two-loop system (3) Dual loop architecture is approximately 18% heavier than single loop architecture (based on Orion thermal control system mass) (4) Single loop architecture requires adaptability to varying environments and heat loads
Models for turbulent flows with variable density and combustion
International Nuclear Information System (INIS)
Jones, W.P.
1980-01-01
Models for transport processes and combustion in turbulent flows are outlined with emphasis on the situation where the fuel and air are injected separately. Attention is restricted to relatively simple flames. The flows investigated are high Reynolds number, single-phase, turbulent high-temperature flames in which radiative heat transfer can be considered negligible. Attention is given to the lower order closure models, algebraic stress and flux models, the k-epsilon turbulence model, the diffusion flame approximation, and finite rate reaction mechanisms
Michoud, V.; Hansen, R. F.; Locoge, N.; Stevens, P. S.; Dusanter, S.
2015-04-01
The Hydroxyl radical (OH) is an important oxidant in the daytime troposphere that controls the lifetime of most trace gases, whose oxidation leads to the formation of harmful secondary pollutants such as ozone (O3) and Secondary Organic Aerosols (SOA). In spite of the importance of OH, uncertainties remain concerning its atmospheric budget and integrated measurements of the total sink of OH can help reducing these uncertainties. In this context, several methods have been developed to measure the first-order loss rate of ambient OH, called total OH reactivity. Among these techniques, the Comparative Reactivity Method (CRM) is promising and has already been widely used in the field and in atmospheric simulation chambers. This technique relies on monitoring competitive OH reactions between a reference molecule (pyrrole) and compounds present in ambient air inside a sampling reactor. However, artefacts and interferences exist for this method and a thorough characterization of the CRM technique is needed. In this study, we present a detailed characterization of a CRM instrument, assessing the corrections that need to be applied on ambient measurements. The main corrections are, in the order of their integration in the data processing: (1) a correction for a change in relative humidity between zero air and ambient air, (2) a correction for the formation of spurious OH when artificially produced HO2 react with NO in the sampling reactor, and (3) a correction for a deviation from pseudo first-order kinetics. The dependences of these artefacts to various measurable parameters, such as the pyrrole-to-OH ratio or the bimolecular reaction rate constants of ambient trace gases with OH are also studied. From these dependences, parameterizations are proposed to correct the OH reactivity measurements from the abovementioned artefacts. A comparison of experimental and simulation results is then discussed. The simulations were performed using a 0-D box model including either (1) a
International Nuclear Information System (INIS)
Malmberg, T.
1993-09-01
The objective of this study is to derive and investigate thermodynamic restrictions for a particular class of internal variable models. Their evolution equations consist of two contributions: the usual irreversible part, depending only on the present state, and a reversible but path dependent part, linear in the rates of the external variables (evolution equations of ''mixed type''). In the first instance the thermodynamic analysis is based on the classical Clausius-Duhem entropy inequality and the Coleman-Noll argument. The analysis is restricted to infinitesimal strains and rotations. The results are specialized and transferred to a general class of elastic-viscoplastic material models. Subsequently, they are applied to several viscoplastic models of ''mixed type'', proposed or discussed in the literature (Robinson et al., Krempl et al., Freed et al.), and it is shown that some of these models are thermodynamically inconsistent. The study is closed with the evaluation of the extended Clausius-Duhem entropy inequality (concept of Mueller) where the entropy flux is governed by an assumed constitutive equation in its own right; also the constraining balance equations are explicitly accounted for by the method of Lagrange multipliers (Liu's approach). This analysis is done for a viscoplastic material model with evolution equations of the ''mixed type''. It is shown that this approach is much more involved than the evaluation of the classical Clausius-Duhem entropy inequality with the Coleman-Noll argument. (orig.) [de
International Nuclear Information System (INIS)
Henderson, M.G.; Reeves, G.D.; Moore, K.R.; Spence, H.E.; Jorgensen, A.M.; Roelof, E.C.
1997-01-01
Although the primary function of the CEP-PAD/IPS instrument on Polar is the measurement of energetic ions in-situ, it has also proven to be a very capable Energetic neutral Atom (ENA) imager. Raw ENA images are currently being constructed on a routine basis with a temporal resolution of minutes during both active and quiet times. However, while analyses of these images by themselves provide much information on the spatial distribution and dynamics of the energetic ion population in the ring current, detailed modeling is required to extract the actual ion distributions. In this paper, the authors present the initial results of forward modeling an IPS ENA image obtained during a small geo-magnetic storm on June 9, 1997. The equatorial ion distribution inferred with this technique reproduces the expected large noon/midnight and dawn/dusk asymmetries. The limitations of the model are discussed and a number of modifications to the basic forward modeling technique are proposed which should significantly improve its performance in future studies
Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H
2017-07-01
Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in
Nobuoki, Eshima; Minoru, Tabata; Geng, Zhi; Department of Medical Information Analysis, Faculty of Medicine, Oita Medical University; Department of Applied Mathematics, Faculty of Engineering, Kobe University; Department of Probability and Statistics, Peking University
2001-01-01
This paper discusses path analysis of categorical variables with logistic regression models. The total, direct and indirect effects in fully recursive causal systems are considered by using model parameters. These effects can be explained in terms of log odds ratios, uncertainty differences, and an inner product of explanatory variables and a response variable. A study on food choice of alligators as a numerical exampleis reanalysed to illustrate the present approach.
European Model Company Act jako nowy instrument harmonizacji europejskiego prawa spółek
Możdżeń, Kamila
2016-01-01
Przedmiotem żywej dyskusji w dziedzinie harmonizacji europejskiego prawa spółek stał się ostatnio przełomowy szkic europejskiej ustawy modelowej o spółkach - European Model Company Act (EMCA), który po kilku latach prac najwybitniejszych ekspertów z całej Europy ujrzał światło dzienne. Modelowy europejski kodeks spółek handlowych, który państwa członkowskie będą mogły dobrowolnie implementować, ma pełnić rolę obiecującego dopełnienia dotychczasowych instrumentów harmonizacyjnych oraz inspirow...
Directory of Open Access Journals (Sweden)
A Moameni
2011-02-01
Full Text Available Abstract In Iran, the experimental plots under fertilizer trials are managed in such a way that the whole plot area uniformly receives agricultural inputs. This could lead to biased research results and hence to suppressing of the efforts made by the researchers. This research was conducted in a selected site belonging to the Gonbad Agricultural Research Station, located in the semiarid region, northeastern Iran. The aim was to characterize the short-range spatial variability of the inherent and management-depended soil properties and to determine if this variation is large and can be managed at practical scales. The soils were sampled using a grid 55 m apart. In total, 100 composite soil samples were collected from topsoil (0-30 cm and were analyzed for calcium carbonate equivalent, organic carbon, clay, available phosphorus, available potassium, iron, copper, zinc and manganese. Descriptive statistics were applied to check data trends. Geostatistical analysis was applied to variography, model fitting and contour mapping. Sampling at 55 m made it possible to split the area of the selected experimental plot into relatively uniform areas that allow application of agricultural inputs with variable rates. Keywords: Short-range soil variability, Within-field soil variability, Interpolation, Precision agriculture, Geostatistics
Latent variable models an introduction to factor, path, and structural equation analysis
Loehlin, John C
2004-01-01
This fourth edition introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. The book is intended for advanced students and researchers in the areas of social, educational, clinical, ind
Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...
Separation of uncertainty and interindividual variability in human exposure modeling.
Ragas, A.M.J.; Brouwer, F.P.E.; Buchner, F.L.; Hendriks, H.W.; Huijbregts, M.A.J.
2009-01-01
The NORMTOX model predicts the lifetime-averaged exposure to contaminants through multiple environmental media, that is, food, air, soil, drinking and surface water. The model was developed to test the coherence of Dutch environmental quality objectives (EQOs). A set of EQOs is called coherent if
Mediating Variables in a Transtheoretical Model Dietary Intervention Program
Di Noia, Jennifer; Prochaska, James O.
2010-01-01
This study identified mediators of a Transtheoretical Model (TTM) intervention to increase fruit and vegetable consumption among economically disadvantaged African American adolescents (N = 549). Single-and multiple-mediator models were used to determine whether pros, cons, self-efficacy, and stages of change satisfied four conclusions necessary…
Thomas E. Dilts; Peter J. Weisberg; Camie M. Dencker; Jeanne C. Chambers
2015-01-01
We have three goals. (1) To develop a suite of functionally relevant climate variables for modelling vegetation distribution on arid and semi-arid landscapes of the Great Basin, USA. (2) To compare the predictive power of vegetation distribution models based on mechanistically proximate factors (water deficit variables) and factors that are more mechanistically removed...
A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses
Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini
2012-01-01
The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…
Interannual modes of variability of Southern Hemisphere atmospheric circulation in CMIP3 models
International Nuclear Information System (INIS)
Grainger, S; Frederiksen, C S; Zheng, X
2010-01-01
The atmospheric circulation acts as a bridge between large-scale sources of climate variability, and climate variability on regional scales. Here a statistical method is applied to monthly mean Southern Hemisphere 500hPa geopotential height to separate the interannual variability of the seasonal mean into intraseasonal and slowly varying (time scales of a season or longer) components. Intraseasonal and slow modes of variability are estimated from realisations of models from the Coupled Model Intercomparison Project Phase 3 (CMIP3) twentieth century coupled climate simulation (20c3m) and are evaluated against those estimated from reanalysis data. The intraseasonal modes of variability are generally well reproduced across all CMIP3 20c3m models for both Southern Hemisphere summer and winter. The slow modes are in general less well reproduced than the intraseasonal modes, and there are larger differences between realisations than for the intraseasonal modes. New diagnostics are proposed to evaluate model variability. It is found that differences between realisations from each model are generally less than inter-model differences. Differences between model-mean diagnostics are found. The results obtained are applicable to assessing the reliability of changes in atmospheric circulation variability in CMIP3 models and for their suitability for further studies of regional climate variability.
Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent
2016-02-01
This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the
Instrument evaluation no. 11. ESI nuclear model 271 C contamination monitor
Burgess, P H
1978-01-01
The various radiations encountered in radiological protection cover a wide range of energies and radiation measurements have to he carried out under an equally broad spectrum of environmental conditions. This report is one of a series intended to give information on the performance characteristics of radiological protection instruments, to assist in the selection of appropriate instruments for a given purpose, to interpret the results obtained with such instruments, and, in particular, to know the likely sources and magnitude of errors that might be associated with measurements in the field. The radiation, electrical and environmental characteristics of radiation protection instruments are considered together with those aspects of the construction which make an instrument convenient for routine use. To provide consistent criteria for instrument performance, the range of tests performed on any particular class of instrument, the test methods and the criteria of acceptable performance are based broadly on the a...
Modeling Scramjet Flows with Variable Turbulent Prandtl and Schmidt Numbers
Xiao, X.; Hassan, H. A.; Baurle, R. A.
2006-01-01
A complete turbulence model, where the turbulent Prandtl and Schmidt numbers are calculated as part of the solution and where averages involving chemical source terms are modeled, is presented. The ability of avoiding the use of assumed or evolution Probability Distribution Functions (PDF's) results in a highly efficient algorithm for reacting flows. The predictions of the model are compared with two sets of experiments involving supersonic mixing and one involving supersonic combustion. The results demonstrate the need for consideration of turbulence/chemistry interactions in supersonic combustion. In general, good agreement with experiment is indicated.
Idealized digital models for conical reed instruments, with focus on the internal pressure waveform.
Kergomard, J; Guillemain, P; Silva, F; Karkar, S
2016-02-01
Two models for the generation of self-oscillations of reed conical woodwinds are presented. The models use the fewest parameters (of either the resonator or the exciter), whose influence can be quickly explored. The formulation extends iterated maps obtained for lossless cylindrical pipes without reed dynamics. It uses spherical wave variables in idealized resonators, with one parameter more than for cylinders: the missing length of the cone. The mouthpiece volume equals that of the missing part of the cone, and is implemented as either a cylindrical pipe (first model) or a lumped element (second model). Only the first model adds a length parameter for the mouthpiece and leads to the solving of an implicit equation. For the second model, any shape of nonlinear characteristic can be directly considered. The complex characteristic impedance for spherical waves requires sampling times smaller than a round trip in the resonator. The convergence of the two models is shown when the length of the cylindrical mouthpiece tends to zero. The waveform is in semi-quantitative agreement with experiment. It is concluded that the oscillations of the positive episode of the mouthpiece pressure are related to the length of the missing part, not to the reed dynamics.
Modelling the diurnal variability of SST and its vertical extent
DEFF Research Database (Denmark)
Karagali, Ioanna; Høyer, Jacob L.; Donlon, Craig J.
2014-01-01
of the water column where most of the heat is absorbed and where the exchange of heat and momentum with the atmosphere occurs. During day-time and under favourable conditions of low winds and high insolation, diurnal warming of the upper layer poses challenges for validating and calibrating satellite sensors......Sea Surface Temperature (SST) is a key variable in air-sea interactions, partly controlling the oceanic uptake of CO2 and the heat exchange between the ocean and the atmosphere, amongst others. Satellite SSTs are representative of skin and sub-skin temperature, i.e. in the upper millimetres...... and merging SST time series. When radiometer signals, typically from satellites, are validated with in situ measurements from drifting and moored buoys a general mismatch is found, associated with the different reference depth of each type of measurement. A generally preferred approach to bridge the gap...
modelling of hydropower reservoir variables for energy generation
African Journals Online (AJOL)
Osondu
the River Niger (Kainji and Jebba dams) in Nigeria for energy generation using multilayer ... coefficient showed that the networks are reliable for modeling energy generation as a function of ... water, like wind and sun, is a renewable resource.
Importance of predictor variables for models of chemical function
U.S. Environmental Protection Agency — Importance of random forest predictors for all classification models of chemical function. This dataset is associated with the following publication: Isaacs , K., M....
modelling of hydropower reservoir variables for energy generation
African Journals Online (AJOL)
Osondu
the River Niger (Kainji and Jebba dams) in Nigeria for energy generation using multilayer ... coefficient showed that the networks are reliable for modeling energy generation as a function of ... through turbines and electric generator system.
Influences of variables on ship collision probability in a Bayesian belief network model
International Nuclear Information System (INIS)
Hänninen, Maria; Kujala, Pentti
2012-01-01
The influences of the variables in a Bayesian belief network model for estimating the role of human factors on ship collision probability in the Gulf of Finland are studied for discovering the variables with the largest influences and for examining the validity of the network. The change in the so-called causation probability is examined while observing each state of the network variables and by utilizing sensitivity and mutual information analyses. Changing course in an encounter situation is the most influential variable in the model, followed by variables such as the Officer of the Watch's action, situation assessment, danger detection, personal condition and incapacitation. The least influential variables are the other distractions on bridge, the bridge view, maintenance routines and the officer's fatigue. In general, the methods are found to agree on the order of the model variables although some disagreements arise due to slightly dissimilar approaches to the concept of variable influence. The relative values and the ranking of variables based on the values are discovered to be more valuable than the actual numerical values themselves. Although the most influential variables seem to be plausible, there are some discrepancies between the indicated influences in the model and literature. Thus, improvements are suggested to the network.
Montgomery, D.R.; Schmidt, K.M.; Dietrich, W.E.; McKean, J.
2009-01-01
The middle of a hillslope hollow in the Oregon Coast Range failed and mobilized as a debris flow during heavy rainfall in November 1996. Automated pressure transducers recorded high spatial variability of pore water pressure within the area that mobilized as a debris flow, which initiated where local upward flow from bedrock developed into overlying colluvium. Postfailure observations of the bedrock surface exposed in the debris flow scar reveal a strong spatial correspondence between elevated piezometric response and water discharging from bedrock fractures. Measurements of apparent root cohesion on the basal (Cb) and lateral (Cl) scarp demonstrate substantial local variability, with areally weighted values of Cb = 0.1 and Cl = 4.6 kPa. Using measured soil properties and basal root strength, the widely used infinite slope model, employed assuming slope parallel groundwater flow, provides a poor prediction of hydrologie conditions at failure. In contrast, a model including lateral root strength (but neglecting lateral frictional strength) gave a predicted critical value of relative soil saturation that fell within the range defined by the arithmetic and geometric mean values at the time of failure. The 3-D slope stability model CLARA-W, used with locally observed pore water pressure, predicted small areas with lower factors of safety within the overall slide mass at sites consistent with field observations of where the failure initiated. This highly variable and localized nature of small areas of high pore pressure that can trigger slope failure means, however, that substantial uncertainty appears inevitable for estimating hydrologie conditions within incipient debris flows under natural conditions. Copyright 2009 by the American Geophysical Union.
Three-dimensional modeling of physiological tremor for hand-held surgical robotic instruments.
Tatinati, Sivanagaraja; Yan Naing Aye; Pual, Anand; Wei Tech Ang; Veluvolu, Kalyana C
2016-08-01
Hand-held robotic instruments are developed to compensate physiological tremor in real-time while augmenting the required precision and dexterity into normal microsurgical work-flow. The hardware (sensors and actuators) and software (causal linear filters) employed for tremor identification and filtering introduces time-varying unknown phase-delay that adversely affects the device performance. The current techniques that focus on three-dimensions (3D) tip position control involves modeling and canceling the tremor in 3-axes (x, y, and z axes) separately. Our analysis with the tremor data recorded from surgeons and novice subjects show that there exists significant correlation in tremor motion across the dimensions. Motivated by this, a new multi-dimensional modeling approach based on extreme learning machines (ELM) is proposed in this paper to correct the phase delay and to accurately model tremulous motion in three dimensions simultaneously. A study is conducted with tremor data recorded from the microsurgeons to analyze the suitability of proposed approach.
Directory of Open Access Journals (Sweden)
Mário Cesar da Silva Andrade
2015-12-01
Full Text Available This paper aimed to evaluate the method of making rational decision derived from the philosophy of Kant as a foundation paradigma of public decisions and, more specifically, of legal decisions. Based on the communicative action theory of Jürgen Habermas, the question is if the transcendental model of decision-making meets the democratic demands. Methodologically, the qualitative research was based on doctrinal sources about the theme, promoting a legal and critical analysis. Habermas' communicative bias raises the hypothesis that Kant's transcendental method, which influenced so much the theory of justice and Law, entails the adoption of an objective posture by the decision maker, something incompatible with the need for broad participation and the intersubjectivity prescribed by democracy . It was concluded that the public decision-making process must overcome the transcendental, decisionistic and instrumental models, adopting pragmatic model, which is more intersubjective and communicative, therefore more consistente with the participatory bias of democracy.
Energy Technology Data Exchange (ETDEWEB)
Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States)
2016-10-17
This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate through polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.
Dynamic modeling of fixed-bed adsorption of flue gas using a variable mass transfer model
International Nuclear Information System (INIS)
Park, Jehun; Lee, Jae W.
2016-01-01
This study introduces a dynamic mass transfer model for the fixed-bed adsorption of a flue gas. The derivation of the variable mass transfer coefficient is based on pore diffusion theory and it is a function of effective porosity, temperature, and pressure as well as the adsorbate composition. Adsorption experiments were done at four different pressures (1.8, 5, 10 and 20 bars) and three different temperatures (30, 50 and 70 .deg. C) with zeolite 13X as the adsorbent. To explain the equilibrium adsorption capacity, the Langmuir-Freundlich isotherm model was adopted, and the parameters of the isotherm equation were fitted to the experimental data for a wide range of pressures and temperatures. Then, dynamic simulations were performed using the system equations for material and energy balance with the equilibrium adsorption isotherm data. The optimal mass transfer and heat transfer coefficients were determined after iterative calculations. As a result, the dynamic variable mass transfer model can estimate the adsorption rate for a wide range of concentrations and precisely simulate the fixed-bed adsorption process of a flue gas mixture of carbon dioxide and nitrogen.
The necessity of connection structures in neural models of variable binding.
van der Velde, Frank; de Kamps, Marc
2015-08-01
In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other ('connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.
A Simple Model of the Variability of Soil Depths
Directory of Open Access Journals (Sweden)
Fang Yu
2017-06-01
Full Text Available Soil depth tends to vary from a few centimeters to several meters, depending on many natural and environmental factors. We hypothesize that the cumulative effect of these factors on soil depth, which is chiefly dependent on the process of biogeochemical weathering, is particularly affected by soil porewater (i.e., solute transport and infiltration from the land surface. Taking into account evidence for a non-Gaussian distribution of rock weathering rates, we propose a simple mathematical model to describe the relationship between soil depth and infiltration flux. The model was tested using several areas in mostly semi-arid climate zones. The application of this model demonstrates the use of fundamental principles of physics to quantify the coupled effects of the five principal soil-forming factors of Dokuchaev.
Instrumentation of the model in scaled 1:10 to prototype of the AquaBuOY wave energy converter
DEFF Research Database (Denmark)
Margheritini, Lucia; Frigaard, Peter
The objective of this report is to provide guidelines for the instrumentation of a model in scale 1:10 to prototype of the AquaBuOY wave energy converter. The model will be located in Nissum Bredning area: this is an important waterway already used by Aalborg University for real sea tests of wave...... energy converters....
Raphael, Dennis; And Others
1996-01-01
A conceptual model of quality of life, developed at the Centre for Health Promotion at the University of Toronto (Canada), and associated instrumentation for collecting data from persons with developmental disabilities are presented. Results from a preliminary study with 41 participants support the reliability and validity of the model's…
Bun, M.; de Haan, M.
2010-01-01
We analyze the usefulness of the first stage F-statistic for detecting weak instruments in the IV model with a nonscalar error covariance structure. More in particular, we question the validity of the rule of thumb of a first stage F-statistic of 10 or higher for models with correlated errors
Perturbative corrections for approximate inference in gaussian latent variable models
DEFF Research Database (Denmark)
Opper, Manfred; Paquet, Ulrich; Winther, Ole
2013-01-01
Expectation Propagation (EP) provides a framework for approximate inference. When the model under consideration is over a latent Gaussian field, with the approximation being Gaussian, we show how these approximations can systematically be corrected. A perturbative expansion is made of the exact b...... illustrate on tree-structured Ising model approximations. Furthermore, they provide a polynomial-time assessment of the approximation error. We also provide both theoretical and practical insights on the exactness of the EP solution. © 2013 Manfred Opper, Ulrich Paquet and Ole Winther....
Modelling of Station of Pumping by Variable Speed
Directory of Open Access Journals (Sweden)
Benretem A.
2016-05-01
Full Text Available An increased energetic efficiency will make it possible to decrease the factory operating costs and hence to increase productivity. The centrifugal pumps are largely used because of their relatively simple operation and of their purchase price. One analyses thorough requirements imposed by the pumping plants is decisive. It is important to keep in mind the fact that the pumps consume approximately 20% of energy in the world. They constitute the possibility for the most significant efficiency improvement. They can reach their maximum effectiveness only with one pressure and a given flow. The approach suggested makes it possible to adapt with accuracy and effectiveness of system output of the industrial process requirements. The variable speed drive is one of best and effective techniques studied to reach this objective. The appearance of this technique comes only after the evolution obtained in the field of power electronics systems precisely static inverters as well as the efforts made by the researchers in the field of electric drive systems. This work suggested is the result of an in-depth study on the effectiveness of this new technique applied for the centrifugal pumps.
Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C
2011-10-31
The calibration performance of partial least squares for one response variable (PLS1) can be improved by elimination of uninformative variables. Many methods are based on so-called predictive variable properties, which are functions of various PLS-model parameters, and which may change during the variable reduction process. In these methods variable reduction is made on the variables ranked in descending order for a given variable property. The methods start with full spectrum modelling. Iteratively, until a specified number of remaining variables is reached, the variable with the smallest property value is eliminated; a new PLS model is calculated, followed by a renewed ranking of the variables. The Stepwise Variable Reduction methods using Predictive-Property-Ranked Variables are denoted as SVR-PPRV. In the existing SVR-PPRV methods the PLS model complexity is kept constant during the variable reduction process. In this study, three new SVR-PPRV methods are proposed, in which a possibility for decreasing the PLS model complexity during the variable reduction process is build in. Therefore we denote our methods as PPRVR-CAM methods (Predictive-Property-Ranked Variable Reduction with Complexity Adapted Models). The selective and predictive abilities of the new methods are investigated and tested, using the absolute PLS regression coefficients as predictive property. They were compared with two modifications of existing SVR-PPRV methods (with constant PLS model complexity) and with two reference methods: uninformative variable elimination followed by either a genetic algorithm for PLS (UVE-GA-PLS) or an interval PLS (UVE-iPLS). The performance of the methods is investigated in conjunction with two data sets from near-infrared sources (NIR) and one simulated set. The selective and predictive performances of the variable reduction methods are compared statistically using the Wilcoxon signed rank test. The three newly developed PPRVR-CAM methods were able to retain
Modeling of carbon sequestration in coal-beds: A variable saturated simulation
International Nuclear Information System (INIS)
Liu Guoxiang; Smirnov, Andrei V.
2008-01-01
Storage of carbon dioxide in deep coal seams is a profitable method to reduce the concentration of green house gases in the atmosphere while the methane as a byproduct can be extracted during carbon dioxide injection into the coal seam. In this procedure, the key element is to keep carbon dioxide in the coal seam without escaping for a long term. It is depended on many factors such as properties of coal basin, fracture state, phase equilibrium, etc., especially the porosity, permeability and saturation of the coal seam. In this paper, a variable saturation model was developed to predict the capacity of carbon dioxide sequestration and coal-bed methane recovery. This variable saturation model can be used to track the saturation variability with the partial pressures change caused by carbon dioxide injection. Saturation variability is a key factor to predict the capacity of carbon dioxide storage and methane recovery. Based on this variable saturation model, a set of related variables including capillary pressure, relative permeability, porosity, coupled adsorption model, concentration and temperature equations were solved. From results of the simulation, historical data agree with the variable saturation model as well as the adsorption model constructed by Langmuir equations. The Appalachian basin, as an example, modeled the carbon dioxide sequestration in this paper. The results of the study and the developed models can provide the projections for the CO 2 sequestration and methane recovery in coal-beds within different regional specifics
QUANTIFYING SUBGRID POLLUTANT VARIABILITY IN EULERIAN AIR QUALITY MODELS
In order to properly assess human risk due to exposure to hazardous air pollutants or air toxics, detailed information is needed on the location and magnitude of ambient air toxic concentrations. Regional scale Eulerian air quality models are typically limited to relatively coar...
Modeling Selected Climatic Variables in Ibadan, Oyo State, Nigeria ...
African Journals Online (AJOL)
PROF. O. E. OSUAGWU
2013-09-01
Sep 1, 2013 ... The aim of this study was fitting the modified generalized burr density function to total rainfall and temperature data obtained from the meteorological unit in the Department of. Environmental Modelling and Management of the Forestry Research Institute of Nigeria. (FRIN) in Ibadan, Oyo State, Nigeria.
Exploratory and Creative Properties of Physical-Modeling-based Musical Instruments
DEFF Research Database (Denmark)
Gelineck, Steven
Digital musical instruments are developed to enable musicians to find new ways of expressing themselves. The development and evaluation of these instruments can be approached from many different perspectives depending on which capabilities one wants the musicians to have. This thesis attempts...... to approach development and evaluation of these instruments with the notion that instruments today are able to facilitate the creative process that is so crucial for creating music. The fundamental question pursued throughout the thesis is how creative work processes of composers of electronic music can...... be supported and even challenged by the instruments they use. What is it that makes one musical instrument more creatively inspiring than another, and how do we evaluate how well it succeeds? In order to present answers to these questions, the thesis focusses on the sound synthesis technique of physical...
Modelling the co-evolution of indirect genetic effects and inherited variability.
Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter
2018-03-28
When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of
Analytical Model for LLC Resonant Converter With Variable Duty-Cycle Control
DEFF Research Database (Denmark)
Shen, Yanfeng; Wang, Huai; Blaabjerg, Frede
2016-01-01
are identified and discussed. The proposed model enables a better understanding of the operation characteristics and fast parameter design of the LLC converter, which otherwise cannot be achieved by the existing simulation based methods and numerical models. The results obtained from the proposed model......In LLC resonant converters, the variable duty-cycle control is usually combined with a variable frequency control to widen the gain range, improve the light-load efficiency, or suppress the inrush current during start-up. However, a proper analytical model for the variable duty-cycle controlled LLC...... converter is still not available due to the complexity of operation modes and the nonlinearity of steady-state equations. This paper makes the efforts to develop an analytical model for the LLC converter with variable duty-cycle control. All possible operation models and critical operation characteristics...
Platow, Michael J; Eggins, Rachael A; Chattopadhyay, Rachana; Brewer, Greg; Hardwick, Lisa; Milsom, Laurin; Brocklebank, Jacinta; Lalor, Thérèse; Martin, Rowena; Quee, Michelle; Vassallo, Sara; Welsh, Jenny
2013-06-01
In both a laboratory experiment (in Australia) using university as the basis of group membership, and a scenario experiment (in India) using religion as the basis of group membership, we observe more favourable respect and fairness ratings in response to an in-group authority than an out-group authority who administers non-instrumental voice. Moreover, we observe in our second experiment that reported likelihood of protest (herein called "social-change voice") was relatively high following non-instrumental voice from an out-group authority, but relatively low following non-instrumental voice from an in-group authority. Our findings are consistent with relational models of procedural justice, and extend the work by examining likely use of alternative forms of voice as well as highlighting the relative importance of instrumentality. ©2012 The British Psychological Society.
Directory of Open Access Journals (Sweden)
Zhigang Wu
Full Text Available Conbercept is a genetically engineered homodimeric protein for the treatment of wet age-related macular degeneration (wet AMD that functions by blocking VEGF-family proteins. Its huge, highly variable architecture makes characterization and development of a functional assay difficult. In this study, the primary structure, number of disulfide linkages and glycosylation state of conbercept were characterized by high-performance liquid chromatography, mass spectrometry, and capillary electrophoresis. Molecular modeling was then applied to obtain the spatial structural model of the conbercept-VEGF-A complex, and to study its inter-atomic interactions and dynamic behavior. This work was incorporated into a platform useful for studying the structure of conbercept and its ligand binding functions.
Optical modelling of far-infrared astronomical instrumentation exploiting multimode horn antennas
O'Sullivan, Créidhe; Murphy, J. Anthony; Mc Auley, Ian; Wilson, Daniel; Gradziel, Marcin L.; Trappe, Neil; Cahill, Fiachra; Peacocke, T.; Savini, G.; Ganga, K.
2014-07-01
In this paper we describe the optical modelling of astronomical telescopes that exploit bolometric detectors fed by multimoded horn antennas. In cases where the horn shape is profiled rather than being a simple cone, we determine the beam at the horn aperture using an electromagnetic mode-matching technique. Bolometers, usually placed in an integrating cavity, can excite many hybrid modes in a corrugated horn; we usually assume they excite all modes equally. If the waveguide section feeding the horn is oversized these modes can propagate independently, thereby increasing the throughput of the system. We use an SVD analysis on the matrix that describes the scattering between waveguide (TE/TM) modes to recover the independent orthogonal fields (hybrid modes) and then propagate these to the sky independently where they are added in quadrature. Beam patterns at many frequencies across the band are then added with a weighting appropriate to the source spectrum. Here we describe simulations carried out on the highest-frequency (857-GHz) channel of the Planck HFI instrument. We concentrate in particular on the use of multimode feedhorns and consider the effects of possible manufacturing tolerances on the beam on the sky. We also investigate the feasibility of modelling far-out sidelobes across a wide band for electrically large structures and bolometers fed by multi-mode feedhorns. Our optical simulations are carried out using the industry-standard GRASP software package.
Studying and modelling variable density turbulent flows for industrial applications
Energy Technology Data Exchange (ETDEWEB)
Chabard, J.P.; Simonin, O.; Caruso, A.; Delalondre, C.; Dalsecco, S.; Mechitoua, N.
1996-07-01
Industrial applications are presented in the various fields of interest for EDF. A first example deals with transferred electric arcs couplings flow and thermal transfer in the arc and in the bath of metal and is related with applications of electricity. The second one is the combustion modelling in burners of fossil power plants. The last one comes from the nuclear power plants and concerns the stratified flows in a nuclear reactor building. (K.A.). 18 refs.
Studying and modelling variable density turbulent flows for industrial applications
International Nuclear Information System (INIS)
Chabard, J.P.; Simonin, O.; Caruso, A.; Delalondre, C.; Dalsecco, S.; Mechitoua, N.
1996-07-01
Industrial applications are presented in the various fields of interest for EDF. A first example deals with transferred electric arcs couplings flow and thermal transfer in the arc and in the bath of metal and is related with applications of electricity. The second one is the combustion modelling in burners of fossil power plants. The last one comes from the nuclear power plants and concerns the stratified flows in a nuclear reactor building. (K.A.)
Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable
Elhorst, J. Paul
2001-01-01
This paper surveys panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable. In particular, it focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the
AeroPropulsoServoElasticity: Dynamic Modeling of the Variable Cycle Propulsion System
Kopasakis, George
2012-01-01
This presentation was made at the 2012 Fundamental Aeronautics Program Technical Conference and it covers research work for the Dynamic Modeling of the Variable cycle Propulsion System that was done under the Supersonics Project, in the area of AeroPropulsoServoElasticity. The presentation covers the objective for the propulsion system dynamic modeling work, followed by the work that has been done so far to model the variable Cycle Engine, modeling of the inlet, the nozzle, the modeling that has been done to model the affects of flow distortion, and finally presenting some concluding remarks and future plans.
FinFET centric variability-aware compact model extraction and generation technology supporting DTCO
Wang, Xingsheng; Cheng, Binjie; Reid, David; Pender, Andrew; Asenov, Plamen; Millar, Campbell; Asenov, Asen
2015-01-01
In this paper, we present a FinFET-focused variability-aware compact model (CM) extraction and generation technology supporting design-technology co-optimization. The 14-nm CMOS technology generation silicon on insulator FinFETs are used as testbed transistors to illustrate our approach. The TCAD simulations include a long-range process-induced variability using a design of experiment approach and short-range purely statistical variability (mismatch). The CM extraction supports a hierarchical...
A Riccati model for Denmark Strait overflow variability
Käse, R. H.
2006-10-01
A controlled volume box model of the western basins of the Nordic Seas for water denser than 1027.8 kg m-3 is constructed, where accumulation in volume ($\\frac{dV}{dt) is driven by net imbalances between prescribed net inflow from the northern, eastern and top boundaries (Qs) and hydraulically limited outflow through the Denmark Strait. The resulting Riccati equation is solved analytically for filling and flushing experiments with constant Qs and numerically for stochastic forcing Qs(t). For small perturbations to Qs with white noise spectrum, the overflow response is red noise with a time scale between 5 and 15 years depending on the mean interface height and area. For Qs proportional to the NAO index, the overflow is positively correlated with the NAO. A 140 years integration reveals variations in the overflow between 2.5 Sv in the 1970s and a maximum of 4 Sv in the 1990s. Hydraulic transport calculations from hydrographic data north of Iceland show good agreement with the model hindcast.
OUTLIER DETECTION IN PARTIAL ERRORS-IN-VARIABLES MODEL
Directory of Open Access Journals (Sweden)
JUN ZHAO
Full Text Available The weighed total least square (WTLS estimate is very sensitive to the outliers in the partial EIV model. A new procedure for detecting outliers based on the data-snooping is presented in this paper. Firstly, a two-step iterated method of computing the WTLS estimates for the partial EIV model based on the standard LS theory is proposed. Secondly, the corresponding w-test statistics are constructed to detect outliers while the observations and coefficient matrix are contaminated with outliers, and a specific algorithm for detecting outliers is suggested. When the variance factor is unknown, it may be estimated by the least median squares (LMS method. At last, the simulated data and real data about two-dimensional affine transformation are analyzed. The numerical results show that the new test procedure is able to judge that the outliers locate in x component, y component or both components in coordinates while the observations and coefficient matrix are contaminated with outliers
Impulsive synchronization and parameter mismatch of the three-variable autocatalator model
International Nuclear Information System (INIS)
Li, Yang; Liao, Xiaofeng; Li, Chuandong; Huang, Tingwen; Yang, Degang
2007-01-01
The synchronization problems of the three-variable autocatalator model via impulsive control approach are investigated; several theorems on the stability of impulsive control systems are also investigated. These theorems are then used to find the conditions under which the three-variable autocatalator model can be asymptotically controlled to the equilibrium point. This Letter derives some sufficient conditions for the stabilization and synchronization of a three-variable autocatalator model via impulsive control with varying impulsive intervals. Furthermore, we address the chaos quasi-synchronization in the presence of single-parameter mismatch. To illustrate the effectiveness of the new scheme, several numerical examples are given
Vera, José Fernando; de Rooij, Mark; Heiser, Willem J
2014-11-01
In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low-dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented. © 2014 The British Psychological Society.
Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo
2017-03-01
The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the
On the Use of Variability Operations in the V-Modell XT Software Process Line
DEFF Research Database (Denmark)
Kuhrmann, Marco; Méndez Fernández, Daniel; Ternité, Thomas
2016-01-01
. In this article, we present a study on the feasibility of variability operations to support the development of software process lines in the context of the V-Modell XT. We analyze which variability operations are defined and practically used. We provide an initial catalog of variability operations...... as an improvement proposal for other process models. Our findings show that 69 variability operation types are defined across several metamodel versions of which, however, 25 remain unused. The found variability operations allow for systematically modifying the content of process model elements and the process......Software process lines provide a systematic approach to develop and manage software processes. It defines a reference process containing general process assets, whereas a well-defined customization approach allows process engineers to create new process variants, e.g., by extending or modifying...
Grace, J.B.; Bollen, K.A.
2008-01-01
Structural equation modeling (SEM) holds the promise of providing natural scientists the capacity to evaluate complex multivariate hypotheses about ecological systems. Building on its predecessors, path analysis and factor analysis, SEM allows for the incorporation of both observed and unobserved (latent) variables into theoretically-based probabilistic models. In this paper we discuss the interface between theory and data in SEM and the use of an additional variable type, the composite. In simple terms, composite variables specify the influences of collections of other variables and can be helpful in modeling heterogeneous concepts of the sort commonly of interest to ecologists. While long recognized as a potentially important element of SEM, composite variables have received very limited use, in part because of a lack of theoretical consideration, but also because of difficulties that arise in parameter estimation when using conventional solution procedures. In this paper we present a framework for discussing composites and demonstrate how the use of partially-reduced-form models can help to overcome some of the parameter estimation and evaluation problems associated with models containing composites. Diagnostic procedures for evaluating the most appropriate and effective use of composites are illustrated with an example from the ecological literature. It is argued that an ability to incorporate composite variables into structural equation models may be particularly valuable in the study of natural systems, where concepts are frequently multifaceted and the influence of suites of variables are often of interest. ?? Springer Science+Business Media, LLC 2007.
A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.
Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan
2017-01-01
Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.
A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method
Directory of Open Access Journals (Sweden)
Jun-He Yang
2017-01-01
Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.
A fully Bayesian method for jointly fitting instrumental calibration and X-ray spectral models
International Nuclear Information System (INIS)
Xu, Jin; Yu, Yaming; Van Dyk, David A.; Kashyap, Vinay L.; Siemiginowska, Aneta; Drake, Jeremy; Ratzlaff, Pete; Connors, Alanna; Meng, Xiao-Li
2014-01-01
Owing to a lack of robust principled methods, systematic instrumental uncertainties have generally been ignored in astrophysical data analysis despite wide recognition of the importance of including them. Ignoring calibration uncertainty can cause bias in the estimation of source model parameters and can lead to underestimation of the variance of these estimates. We previously introduced a pragmatic Bayesian method to address this problem. The method is 'pragmatic' in that it introduced an ad hoc technique that simplified computation by neglecting the potential information in the data for narrowing the uncertainty for the calibration product. Following that work, we use a principal component analysis to efficiently represent the uncertainty of the effective area of an X-ray (or γ-ray) telescope. Here, however, we leverage this representation to enable a principled, fully Bayesian method that coherently accounts for the calibration uncertainty in high-energy spectral analysis. In this setting, the method is compared with standard analysis techniques and the pragmatic Bayesian method. The advantage of the fully Bayesian method is that it allows the data to provide information not only for estimation of the source parameters but also for the calibration product—here the effective area, conditional on the adopted spectral model. In this way, it can yield more accurate and efficient estimates of the source parameters along with valid estimates of their uncertainty. Provided that the source spectrum can be accurately described by a parameterized model, this method allows rigorous inference about the effective area by quantifying which possible curves are most consistent with the data.
Micro-macro multilevel latent class models with multiple discrete individual-level variables
Bennink, M.; Croon, M.A.; Kroon, B.; Vermunt, J.K.
2016-01-01
An existing micro-macro method for a single individual-level variable is extended to the multivariate situation by presenting two multilevel latent class models in which multiple discrete individual-level variables are used to explain a group-level outcome. As in the univariate case, the
Theoretical investigations of the new Cokriging method for variable-fidelity surrogate modeling
DEFF Research Database (Denmark)
Zimmermann, Ralf; Bertram, Anna
2018-01-01
Cokriging is a variable-fidelity surrogate modeling technique which emulates a target process based on the spatial correlation of sampled data of different levels of fidelity. In this work, we address two theoretical questions associated with the so-called new Cokriging method for variable fidelity...
The use of vector bootstrapping to improve variable selection precision in Lasso models
Laurin, C.; Boomsma, D.I.; Lubke, G.H.
2016-01-01
The Lasso is a shrinkage regression method that is widely used for variable selection in statistical genetics. Commonly, K-fold cross-validation is used to fit a Lasso model. This is sometimes followed by using bootstrap confidence intervals to improve precision in the resulting variable selections.
Sensitivity Modeling of On-chip Capacitances : Parasitics Extraction for Manufacturing Variability
Bi, Y.
2012-01-01
With each new generation of IC process technologies, the impact of manufacturing variability is increasing. As such, design optimality is harder and harder to achieve and effective modeling tools and methods are needed to capture the effects of variability in such a way that it is understandable and
Skrypnyk, T.
2017-08-01
We study the problem of separation of variables for classical integrable Hamiltonian systems governed by non-skew-symmetric non-dynamical so(3)\\otimes so(3) -valued elliptic r-matrices with spectral parameters. We consider several examples of such models, and perform separation of variables for classical anisotropic one- and two-spin Gaudin-type models in an external magnetic field, and for Jaynes-Cummings-Dicke-type models without the rotating wave approximation.
Problems with radiological surveillance instrumentation
International Nuclear Information System (INIS)
Swinth, K.L.; Tanner, J.E.; Fleming, D.M.
1984-09-01
Many radiological surveillance instruments are in use at DOE facilities throughout the country. These instruments are an essential part of all health physics programs, and poor instrument performance can increase program costs or compromise program effectiveness. Generic data from simple tests on newly purchased instruments shows that many instruments will not meet requirements due to manufacturing defects. In other cases, lack of consideration of instrument use has resulted in poor acceptance of instruments and poor reliability. The performance of instruments is highly variable for electronic and mechanical performance, radiation response, susceptibility to interferences and response to environmental factors. Poor instrument performance in these areas can lead to errors or poor accuracy in measurements
Problems with radiological surveillance instrumentation
International Nuclear Information System (INIS)
Swinth, K.L.; Tanner, J.E.; Fleming, D.M.
1985-01-01
Many radiological surveillance instruments are in use at DOE facilities throughout the country. These instruments are an essential part of all health physics programs, and poor instrument performance can increase program costs or compromise program effectiveness. Generic data from simple tests on newly purchased instruments shows that many instruments will not meet requirements due to manufacturing defects. In other cases, lack of consideration of instrument use has resulted in poor acceptance of instruments and poor reliability. The performance of instruments is highly variable for electronic and mechanical performance, radiation response, susceptibility to interferences and response to environmental factors. Poor instrument performance in these areas can lead to errors or poor accuracy in measurements
Pal, S.; De Wekker, S.; Emmitt, G. D.
2013-12-01
We present first results of the spatio-temporal variability of atmospheric boundary layer depths obtained with a suite of ground-based and airborne instruments deployed during the first field phase of The Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program (http://www3.nd.edu/~dynamics/materhorn/index.php) at Dugway Proving Ground (DPG, Utah, USA) in Fall 2012. We mainly use high-resolution data collected on selected intensive observation periods obtained by Doppler lidars, ceilometer, and in-situ measurements from an unmanned aerial vehicle for the measurements of atmospheric boundary layer (ABL) depths. In particular, a Navy Twin Otter aircraft flew 6 missions of about 5 hours each during the daytime, collecting remotely sensed (Doppler lidar, TODWL) wind data in addition to in-situ turbulence measurements which allowed a detailed investigation of the spatial heterogeneity of the convective boundary layer turbulence features over a steep isolated mountain of a horizontal and vertical scale of about 10 km and 1 km, respectively. Additionally, we use data collected by (1) radiosonde systems at two sites of Granite Mountain area in DPG (Playa and Sagebrush), (2) sonic anemometers (CSAT-3D) for high resolution turbulence flux measurements near ground, (3) Pyranometer for incoming solar radiation, and (4) standard meteorological measurements (PTU) obtained near the surface. In this contribution, we discuss and address (1) composites obtained with lidar, ceilometer, micro-meteorological measurements, and radiosonde observations to determine the quasi-continuous regime of ABL depths, growth rates, maximum convective boundary layer (CBL) depths, etc., (2) the temporal variability in the ABL depths during entire diurnal cycle and the spatial heterogeneity in the daytime ABL depths triggered by the underlying orography in the experimental area to investigate the most possible mechanisms (e.g. combined effect of diurnal cycle and orographic trigger
Modeling of Mesoscale Variability in Biofilm Shear Behavior.
Directory of Open Access Journals (Sweden)
Pallab Barai
Full Text Available Formation of bacterial colonies as biofilm on the surface/interface of various objects has the potential to impact not only human health and disease but also energy and environmental considerations. Biofilms can be regarded as soft materials, and comprehension of their shear response to external forces is a key element to the fundamental understanding. A mesoscale model has been presented in this article based on digitization of a biofilm microstructure. Its response under externally applied shear load is analyzed. Strain stiffening type behavior is readily observed under high strain loads due to the unfolding of chains within soft polymeric substrate. Sustained shear loading of the biofilm network results in strain localization along the diagonal direction. Rupture of the soft polymeric matrix can potentially reduce the intercellular interaction between the bacterial cells. Evolution of stiffness within the biofilm network under shear reveals two regimes: a initial increase in stiffness due to strain stiffening of polymer matrix, and b eventual reduction in stiffness because of tear in polymeric substrate.
a Latent Variable Path Analysis Model of Secondary Physics Enrollments in New York State.
Sobolewski, Stanley John
The Percentage of Enrollment in Physics (PEP) at the secondary level nationally has been approximately 20% for the past few decades. For a more scientifically literate citizenry as well as specialists to continue scientific research and development, it is desirable that more students enroll in physics. Some of the predictor variables for physics enrollment and physics achievement that have been identified previously includes a community's socioeconomic status, the availability of physics, the sex of the student, the curriculum, as well as teacher and student data. This study isolated and identified predictor variables for PEP of secondary schools in New York. Data gathered by the State Education Department for the 1990-1991 school year was used. The source of this data included surveys completed by teachers and administrators on student characteristics and school facilities. A data analysis similar to that done by Bryant (1974) was conducted to determine if the relationships between a set of predictor variables related to physics enrollment had changed in the past 20 years. Variables which were isolated included: community, facilities, teacher experience, number of type of science courses, school size and school science facilities. When these variables were isolated, latent variable path diagrams were proposed and verified by the Linear Structural Relations computer modeling program (LISREL). These diagrams differed from those developed by Bryant in that there were more manifest variables used which included achievement scores in the form of Regents exam results. Two criterion variables were used, percentage of students enrolled in physics (PEP) and percent of students enrolled passing the Regents physics exam (PPP). The first model treated school and community level variables as exogenous while the second model treated only the community level variables as exogenous. The goodness of fit indices for the models was 0.77 for the first model and 0.83 for the second
Energy Technology Data Exchange (ETDEWEB)
Musial, W.; Lawson, M.; Rooney, S.
2013-02-01
The Marine and Hydrokinetic Technology (MHK) Instrumentation, Measurement, and Computer Modeling Workshop was hosted by the National Renewable Energy Laboratory (NREL) in Broomfield, Colorado, July 9-10, 2012. The workshop brought together over 60 experts in marine energy technologies to disseminate technical information to the marine energy community and collect information to help identify ways in which the development of a commercially viable marine energy industry can be accelerated. The workshop was comprised of plenary sessions that reviewed the state of the marine energy industry and technical sessions that covered specific topics of relevance. Each session consisted of presentations, followed by facilitated discussions. During the facilitated discussions, the session chairs posed several prepared questions to the presenters and audience to encourage communication and the exchange of ideas between technical experts. Following the workshop, attendees were asked to provide written feedback on their takeaways and their best ideas on how to accelerate the pace of marine energy technology development. The first four sections of this document give a general overview of the workshop format, provide presentation abstracts and discussion session notes, and list responses to the post-workshop questions. The final section presents key findings and conclusions from the workshop that suggest how the U.S. Department of Energy and national laboratory resources can be utilized to most effectively assist the marine energy industry.
Energy Technology Data Exchange (ETDEWEB)
Musial, W. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lawson, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Rooney, S. [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2013-02-01
The Marine and Hydrokinetic Technology (MHK) Instrumentation, Measurement, and Computer Modeling Workshop was hosted by the National Renewable Energy Laboratory (NREL) in Broomfield, Colorado, July 9–10, 2012. The workshop brought together over 60 experts in marine energy technologies to disseminate technical information to the marine energy community, and to collect information to help identify ways in which the development of a commercially viable marine energy industry can be accelerated. The workshop was comprised of plenary sessions that reviewed the state of the marine energy industry and technical sessions that covered specific topics of relevance. Each session consisted of presentations, followed by facilitated discussions. During the facilitated discussions, the session chairs posed several prepared questions to the presenters and audience to encourage communication and the exchange of ideas between technical experts. Following the workshop, attendees were asked to provide written feedback on their takeaways from the workshop and their best ideas on how to accelerate the pace of marine energy technology development. The first four sections of this document give a general overview of the workshop format, provide presentation abstracts, supply discussion session notes, and list responses to the post-workshop questions. The final section presents key findings and conclusions from the workshop that suggest what the most pressing MHK technology needs are and how the U.S. Department of Energy (DOE) and national laboratory resources can be utilized to assist the marine energy industry in the most effective manner.
Seismic variability of subduction thrust faults: Insights from laboratory models
Corbi, F.; Funiciello, F.; Faccenna, C.; Ranalli, G.; Heuret, A.
2011-06-01
Laboratory models are realized to investigate the role of interface roughness, driving rate, and pressure on friction dynamics. The setup consists of a gelatin block driven at constant velocity over sand paper. The interface roughness is quantified in terms of amplitude and wavelength of protrusions, jointly expressed by a reference roughness parameter obtained by their product. Frictional behavior shows a systematic dependence on system parameters. Both stick slip and stable sliding occur, depending on driving rate and interface roughness. Stress drop and frequency of slip episodes vary directly and inversely, respectively, with the reference roughness parameter, reflecting the fundamental role for the amplitude of protrusions. An increase in pressure tends to favor stick slip. Static friction is a steeply decreasing function of the reference roughness parameter. The velocity strengthening/weakening parameter in the state- and rate-dependent dynamic friction law becomes negative for specific values of the reference roughness parameter which are intermediate with respect to the explored range. Despite the simplifications of the adopted setup, which does not address the problem of off-fault fracturing, a comparison of the experimental results with the depth distribution of seismic energy release along subduction thrust faults leads to the hypothesis that their behavior is primarily controlled by the depth- and time-dependent distribution of protrusions. A rough subduction fault at shallow depths, unable to produce significant seismicity because of low lithostatic pressure, evolves into a moderately rough, velocity-weakening fault at intermediate depths. The magnitude of events in this range is calibrated by the interplay between surface roughness and subduction rate. At larger depths, the roughness further decreases and stable sliding becomes gradually more predominant. Thus, although interplate seismicity is ultimately controlled by tectonic parameters (velocity of
Predictive and Descriptive CoMFA Models: The Effect of Variable Selection.
Sepehri, Bakhtyar; Omidikia, Nematollah; Kompany-Zareh, Mohsen; Ghavami, Raouf
2018-01-01
Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Effect of climate variables on cocoa black pod incidence in Sabah using ARIMAX model
Ling Sheng Chang, Albert; Ramba, Haya; Mohd. Jaaffar, Ahmad Kamil; Kim Phin, Chong; Chong Mun, Ho
2016-06-01
Cocoa black pod disease is one of the major diseases affecting the cocoa production in Malaysia and also around the world. Studies have shown that the climate variables have influenced the cocoa black pod disease incidence and it is important to quantify the black pod disease variation due to the effect of climate variables. Application of time series analysis especially auto-regressive moving average (ARIMA) model has been widely used in economics study and can be used to quantify the effect of climate variables on black pod incidence to forecast the right time to control the incidence. However, ARIMA model does not capture some turning points in cocoa black pod incidence. In order to improve forecasting performance, other explanatory variables such as climate variables should be included into ARIMA model as ARIMAX model. Therefore, this paper is to study the effect of climate variables on the cocoa black pod disease incidence using ARIMAX model. The findings of the study showed ARIMAX model using MA(1) and relative humidity at lag 7 days, RHt - 7 gave better R square value compared to ARIMA model using MA(1) which could be used to forecast the black pod incidence to assist the farmers determine timely application of fungicide spraying and culture practices to control the black pod incidence.
Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc
2017-01-01
Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780
Razafindrakoto, Hoby
2015-04-22
Finite-fault earthquake source inversion is an ill-posed inverse problem leading to non-unique solutions. In addition, various fault parametrizations and input data may have been used by different researchers for the same earthquake. Such variability leads to large intra-event variability in the inferred rupture models. One way to understand this problem is to develop robust metrics to quantify model variability. We propose a Multi Dimensional Scaling (MDS) approach to compare rupture models quantitatively. We consider normalized squared and grey-scale metrics that reflect the variability in the location, intensity and geometry of the source parameters. We test the approach on two-dimensional random fields generated using a von Kármán autocorrelation function and varying its spectral parameters. The spread of points in the MDS solution indicates different levels of model variability. We observe that the normalized squared metric is insensitive to variability of spectral parameters, whereas the grey-scale metric is sensitive to small-scale changes in geometry. From this benchmark, we formulate a similarity scale to rank the rupture models. As case studies, we examine inverted models from the Source Inversion Validation (SIV) exercise and published models of the 2011 Mw 9.0 Tohoku earthquake, allowing us to test our approach for a case with a known reference model and one with an unknown true solution. The normalized squared and grey-scale metrics are respectively sensitive to the overall intensity and the extension of the three classes of slip (very large, large, and low). Additionally, we observe that a three-dimensional MDS configuration is preferable for models with large variability. We also find that the models for the Tohoku earthquake derived from tsunami data and their corresponding predictions cluster with a systematic deviation from other models. We demonstrate the stability of the MDS point-cloud using a number of realizations and jackknife tests, for
Razafindrakoto, Hoby; Mai, Paul Martin; Genton, Marc G.; Zhang, Ling; Thingbaijam, Kiran Kumar
2015-01-01
Finite-fault earthquake source inversion is an ill-posed inverse problem leading to non-unique solutions. In addition, various fault parametrizations and input data may have been used by different researchers for the same earthquake. Such variability leads to large intra-event variability in the inferred rupture models. One way to understand this problem is to develop robust metrics to quantify model variability. We propose a Multi Dimensional Scaling (MDS) approach to compare rupture models quantitatively. We consider normalized squared and grey-scale metrics that reflect the variability in the location, intensity and geometry of the source parameters. We test the approach on two-dimensional random fields generated using a von Kármán autocorrelation function and varying its spectral parameters. The spread of points in the MDS solution indicates different levels of model variability. We observe that the normalized squared metric is insensitive to variability of spectral parameters, whereas the grey-scale metric is sensitive to small-scale changes in geometry. From this benchmark, we formulate a similarity scale to rank the rupture models. As case studies, we examine inverted models from the Source Inversion Validation (SIV) exercise and published models of the 2011 Mw 9.0 Tohoku earthquake, allowing us to test our approach for a case with a known reference model and one with an unknown true solution. The normalized squared and grey-scale metrics are respectively sensitive to the overall intensity and the extension of the three classes of slip (very large, large, and low). Additionally, we observe that a three-dimensional MDS configuration is preferable for models with large variability. We also find that the models for the Tohoku earthquake derived from tsunami data and their corresponding predictions cluster with a systematic deviation from other models. We demonstrate the stability of the MDS point-cloud using a number of realizations and jackknife tests, for
Energy Technology Data Exchange (ETDEWEB)
Deque, M.; Somot, S. [Meteo-France, Centre National de Recherches Meteorologiques, CNRS/GAME, Toulouse Cedex 01 (France); Sanchez-Gomez, E. [Cerfacs/CNRS, SUC URA1875, Toulouse Cedex 01 (France); Goodess, C.M. [University of East Anglia, Climatic Research Unit, Norwich (United Kingdom); Jacob, D. [Max Planck Institute for Meteorology, Hamburg (Germany); Lenderink, G. [KNMI, Postbus 201, De Bilt (Netherlands); Christensen, O.B. [Danish Meteorological Institute, Copenhagen Oe (Denmark)
2012-03-15
Various combinations of thirteen regional climate models (RCM) and six general circulation models (GCM) were used in FP6-ENSEMBLES. The response to the SRES-A1B greenhouse gas concentration scenario over Europe, calculated as the difference between the 2021-2050 and the 1961-1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance explained for temperature and precipitation changes over eight European sub-areas. Three sources of uncertainty can be evaluated from the ENSEMBLES database. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30) despite a non-negligible interannual variability. Regional model uncertainty is due to the fact that the RCMs use different techniques to discretize the equations and to represent sub-grid effects. Global model uncertainty is due to the fact that the RCMs have been driven by different GCMs. Two methods are presented to fill the many empty cells of the ENSEMBLES RCM x GCM matrix. The first one is based on the same approach as in FP5-PRUDENCE. The second one uses the concept of weather regimes to attempt to separate the contribution of the GCM and the RCM. The variance of the climate response is analyzed with respect to the contribution of the GCM and the RCM. The two filling methods agree that the main contributor to the spread is the choice of the GCM, except for summer precipitation where the choice of the RCM dominates the uncertainty. Of course the implication of the GCM to the spread varies with the region, being maximum in the South-western part of Europe, whereas the continental parts are more sensitive to the choice of the RCM. The third cause of spread is systematically the interannual variability. The total uncertainty about temperature is not large enough to mask the 2021-2050 response which shows a similar pattern to the one obtained for 2071-2100 in PRUDENCE. The uncertainty
Can Geostatistical Models Represent Nature's Variability? An Analysis Using Flume Experiments
Scheidt, C.; Fernandes, A. M.; Paola, C.; Caers, J.
2015-12-01
The lack of understanding in the Earth's geological and physical processes governing sediment deposition render subsurface modeling subject to large uncertainty. Geostatistics is often used to model uncertainty because of its capability to stochastically generate spatially varying realizations of the subsurface. These methods can generate a range of realizations of a given pattern - but how representative are these of the full natural variability? And how can we identify the minimum set of images that represent this natural variability? Here we use this minimum set to define the geostatistical prior model: a set of training images that represent the range of patterns generated by autogenic variability in the sedimentary environment under study. The proper definition of the prior model is essential in capturing the variability of the depositional patterns. This work starts with a set of overhead images from an experimental basin that showed ongoing autogenic variability. We use the images to analyze the essential characteristics of this suite of patterns. In particular, our goal is to define a prior model (a minimal set of selected training images) such that geostatistical algorithms, when applied to this set, can reproduce the full measured variability. A necessary prerequisite is to define a measure of variability. In this study, we measure variability using a dissimilarity distance between the images. The distance indicates whether two snapshots contain similar depositional patterns. To reproduce the variability in the images, we apply an MPS algorithm to the set of selected snapshots of the sedimentary basin that serve as training images. The training images are chosen from among the initial set by using the distance measure to ensure that only dissimilar images are chosen. Preliminary investigations show that MPS can reproduce fairly accurately the natural variability of the experimental depositional system. Furthermore, the selected training images provide
Lamadrid-Figueroa, Héctor; Téllez-Rojo, Martha M; Angeles, Gustavo; Hernández-Ávila, Mauricio; Hu, Howard
2011-01-01
In-vivo measurement of bone lead by means of K-X-ray fluorescence (KXRF) is the preferred biological marker of chronic exposure to lead. Unfortunately, considerable measurement error associated with KXRF estimations can introduce bias in estimates of the effect of bone lead when this variable is included as the exposure in a regression model. Estimates of uncertainty reported by the KXRF instrument reflect the variance of the measurement error and, although they can be used to correct the measurement error bias, they are seldom used in epidemiological statistical analyzes. Errors-in-variables regression (EIV) allows for correction of bias caused by measurement error in predictor variables, based on the knowledge of the reliability of such variables. The authors propose a way to obtain reliability coefficients for bone lead measurements from uncertainty data reported by the KXRF instrument and compare, by the use of Monte Carlo simulations, results obtained using EIV regression models vs. those obtained by the standard procedures. Results of the simulations show that Ordinary Least Square (OLS) regression models provide severely biased estimates of effect, and that EIV provides nearly unbiased estimates. Although EIV effect estimates are more imprecise, their mean squared error is much smaller than that of OLS estimates. In conclusion, EIV is a better alternative than OLS to estimate the effect of bone lead when measured by KXRF. Copyright Â© 2010 Elsevier Inc. All rights reserved.
A novel methodology improves reservoir characterization models using geologic fuzzy variables
Energy Technology Data Exchange (ETDEWEB)
Soto B, Rodolfo [DIGITOIL, Maracaibo (Venezuela); Soto O, David A. [Texas A and M University, College Station, TX (United States)
2004-07-01
One of the research projects carried out in Cusiana field to explain its rapid decline during the last years was to get better permeability models. The reservoir of this field has a complex layered system that it is not easy to model using conventional methods. The new technique included the development of porosity and permeability maps from cored wells following the same trend of the sand depositions for each facie or layer according to the sedimentary facie and the depositional system models. Then, we used fuzzy logic to reproduce those maps in three dimensions as geologic fuzzy variables. After multivariate statistical and factor analyses, we found independence and a good correlation coefficient between the geologic fuzzy variables and core permeability and porosity. This means, the geologic fuzzy variable could explain the fabric, the grain size and the pore geometry of the reservoir rock trough the field. Finally, we developed a neural network permeability model using porosity, gamma ray and the geologic fuzzy variable as input variables. This model has a cross-correlation coefficient of 0.873 and average absolute error of 33% compared with the actual model with a correlation coefficient of 0.511 and absolute error greater than 250%. We tested different methodologies, but this new one showed dramatically be a promiser way to get better permeability models. The use of the models have had a high impact in the explanation of well performance and workovers, and reservoir simulation models. (author)
International Nuclear Information System (INIS)
Seo, In Yong; Ha, Bok Nam; Lee, Sung Woo; Shin, Chang Hoon; Kim, Seong Jun
2010-01-01
In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method
Deckers, Dave L.E.H.; Booij, Martijn J.; Rientjes, T.H.M.; Krol, Martinus S.
2010-01-01
This study attempts to examine if catchment variability favours regionalisation by principles of catchment similarity. Our work combines calibration of a simple conceptual model for multiple objectives and multi-regression analyses to establish a regional model between model sensitive parameters and
Pek, Jolynn; Losardo, Diane; Bauer, Daniel J.
2011-01-01
Compared to parametric models, nonparametric and semiparametric approaches to modeling nonlinearity between latent variables have the advantage of recovering global relationships of unknown functional form. Bauer (2005) proposed an indirect application of finite mixtures of structural equation models where latent components are estimated in the…
Variable selection for modelling effects of eutrophication on stream and river ecosystems
Nijboer, R.C.; Verdonschot, P.F.M.
2004-01-01
Models are needed for forecasting the effects of eutrophication on stream and river ecosystems. Most of the current models do not include differences in local stream characteristics and effects on the biota. To define the most important variables that should be used in a stream eutrophication model,
Generalized Density-Corrected Model for Gas Diffusivity in Variably Saturated Soils
DEFF Research Database (Denmark)
Chamindu, Deepagoda; Møldrup, Per; Schjønning, Per
2011-01-01
models. The GDC model was further extended to describe two-region (bimodal) soils and could describe and predict Dp/Do well for both different soil aggregate size fractions and variably compacted volcanic ash soils. A possible use of the new GDC model is engineering applications such as the design...... of highly compacted landfill site caps....
BehavePlus fire modeling system, version 5.0: Variables
Patricia L. Andrews
2009-01-01
This publication has been revised to reflect updates to version 4.0 of the BehavePlus software. It was originally published as the BehavePlus fire modeling system, version 4.0: Variables in July, 2008.The BehavePlus fire modeling system is a computer program based on mathematical models that describe wildland fire behavior and effects and the...
Dondeynaz, C.; Lopez-Puga, J.; Carmona-Moreno, C.
2012-04-01
Improving Water and Sanitation Services (WSS), being a complex and interdisciplinary issue, passes through collaboration and coordination of different sectors (environment, health, economic activities, governance, and international cooperation). This inter-dependency has been recognised with the adoption of the "Integrated Water Resources Management" principles that push for the integration of these various dimensions involved in WSS delivery to ensure an efficient and sustainable management. The understanding of these interrelations appears as crucial for decision makers in the water sector in particular in developing countries where WSS still represent an important leverage for livelihood improvement. In this framework, the Joint Research Centre of the European Commission has developed a coherent database (WatSan4Dev database) containing 29 indicators from environmental, socio-economic, governance and financial aid flows data focusing on developing countries (Celine et al, 2011 under publication). The aim of this work is to model the WatSan4Dev dataset using probabilistic models to identify the key variables influencing or being influenced by the water supply and sanitation access levels. Bayesian Network Models are suitable to map the conditional dependencies between variables and also allows ordering variables by level of influence on the dependent variable. Separated models have been built for water supply and for sanitation because of different behaviour. The models are validated if complying with statistical criteria but either with scientific knowledge and literature. A two steps approach has been adopted to build the structure of the model; Bayesian network is first built for each thematic cluster of variables (e.g governance, agricultural pressure, or human development) keeping a detailed level for interpretation later one. A global model is then built based on significant indicators of each cluster being previously modelled. The structure of the
International Nuclear Information System (INIS)
Tagziria, H.; Tanner, R.J.; Bartlett, D.T.; Thomas, D.J.
2004-01-01
All available measured data for the response characteristics of the Leake counter have been gathered together. These data, augmented by previously unpublished work, have been compared to Monte Carlo simulations of the instrument's response characteristics in the energy range from thermal to 20 MeV. A response function has been derived, which is recommended as the best currently available for the instrument. Folding this function with workplace energy distributions has enabled an assessment of the impact of this new response function to be made. Similar work, which will be published separately, has been carried out for the NM2 and the Studsvik 2202D neutron area survey instruments
A New Bi-Directional Projection Model Based on Pythagorean Uncertain Linguistic Variable
Huidong Wang; Shifan He; Xiaohong Pan
2018-01-01
To solve the multi-attribute decision making (MADM) problems with Pythagorean uncertain linguistic variable, an extended bi-directional projection method is proposed. First, we utilize the linguistic scale function to convert uncertain linguistic variable and provide a new projection model, subsequently. Then, to depict the bi-directional projection method, the formative vectors of alternatives and ideal alternatives are defined. Furthermore, a comparative analysis with projection model is co...
Schmidtmann, I; Elsäßer, A; Weinmann, A; Binder, H
2014-12-30
For determining a manageable set of covariates potentially influential with respect to a time-to-event endpoint, Cox proportional hazards models can be combined with variable selection techniques, such as stepwise forward selection or backward elimination based on p-values, or regularized regression techniques such as component-wise boosting. Cox regression models have also been adapted for dealing with more complex event patterns, for example, for competing risks settings with separate, cause-specific hazard models for each event type, or for determining the prognostic effect pattern of a variable over different landmark times, with one conditional survival model for each landmark. Motivated by a clinical cancer registry application, where complex event patterns have to be dealt with and variable selection is needed at the same time, we propose a general approach for linking variable selection between several Cox models. Specifically, we combine score statistics for each covariate across models by Fisher's method as a basis for variable selection. This principle is implemented for a stepwise forward selection approach as well as for a regularized regression technique. In an application to data from hepatocellular carcinoma patients, the coupled stepwise approach is seen to facilitate joint interpretation of the different cause-specific Cox models. In conditional survival models at landmark times, which address updates of prediction as time progresses and both treatment and other potential explanatory variables may change, the coupled regularized regression approach identifies potentially important, stably selected covariates together with their effect time pattern, despite having only a small number of events. These results highlight the promise of the proposed approach for coupling variable selection between Cox models, which is particularly relevant for modeling for clinical cancer registries with their complex event patterns. Copyright © 2014 John Wiley & Sons
gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework
Hofner, Benjamin; Mayr, Andreas; Schmid, Matthias
2014-01-01
Generalized additive models for location, scale and shape are a flexible class of regression models that allow to model multiple parameters of a distribution function, such as the mean and the standard deviation, simultaneously. With the R package gamboostLSS, we provide a boosting method to fit these models. Variable selection and model choice are naturally available within this regularized regression framework. To introduce and illustrate the R package gamboostLSS and its infrastructure, we...
McDermott, Shana M; Irwin, Rebecca E; Taylor, Brad W
2013-07-01
Economic growth is recognized as an important factor associated with species invasions. Consequently, there is increasing need to develop solutions that combine economics and ecology to inform invasive species management. We developed a model combining economic, ecological, and sociological factors to assess the degree to which economic policies can be used to control invasive plants. Because invasive plants often spread across numerous properties, we explored whether property owners should manage invaders cooperatively as a group by incorporating the negative effects of invader spread in management decisions (collective management) or independently, whereby the negative effects of invasive plant spread are ignored (independent management). Our modeling approach used a dynamic optimization framework, and we applied the model to invader spread using Linaria vulgaris. Model simulations allowed us to determine the optimal management strategy based on net benefits for a range of invader densities. We found that optimal management strategies varied as a function of initial plant densities. At low densities, net benefits were high for both collective and independent management to eradicate the invader, suggesting the importance of early detection and eradication. At moderate densities, collective management led to faster and more frequent invader eradication compared to independent management. When we used a financial penalty to ensure that independent properties were managed collectively, we found that the penalty would be most feasible when levied on a property's perimeter boundary to control spread among properties. At the highest densities, the optimal management strategy was "do nothing" because the economic costs of removal were too high relative to the benefits of removal. Spatial variation in L. vulgaris densities resulted in different optimal management strategies for neighboring properties, making a formal economic policy to encourage invasive species removal
Model Predictive Control of a Nonlinear System with Known Scheduling Variable
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2012-01-01
Model predictive control (MPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Consequently...... the control problem of the nonlinear system is simplied into a quadratic programming. Wind turbine is chosen as the case study and we choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....
Toni, Tina; Tidor, Bruce
2013-01-01
Biological systems are inherently variable, with their dynamics influenced by intrinsic and extrinsic sources. These systems are often only partially characterized, with large uncertainties about specific sources of extrinsic variability and biochemical properties. Moreover, it is not yet well understood how different sources of variability combine and affect biological systems in concert. To successfully design biomedical therapies or synthetic circuits with robust performance, it is crucial to account for uncertainty and effects of variability. Here we introduce an efficient modeling and simulation framework to study systems that are simultaneously subject to multiple sources of variability, and apply it to make design decisions on small genetic networks that play a role of basic design elements of synthetic circuits. Specifically, the framework was used to explore the effect of transcriptional and post-transcriptional autoregulation on fluctuations in protein expression in simple genetic networks. We found that autoregulation could either suppress or increase the output variability, depending on specific noise sources and network parameters. We showed that transcriptional autoregulation was more successful than post-transcriptional in suppressing variability across a wide range of intrinsic and extrinsic magnitudes and sources. We derived the following design principles to guide the design of circuits that best suppress variability: (i) high protein cooperativity and low miRNA cooperativity, (ii) imperfect complementarity between miRNA and mRNA was preferred to perfect complementarity, and (iii) correlated expression of mRNA and miRNA – for example, on the same transcript – was best for suppression of protein variability. Results further showed that correlations in kinetic parameters between cells affected the ability to suppress variability, and that variability in transient states did not necessarily follow the same principles as variability in the steady
Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.
2016-12-01
One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.
Trani, Jean-Francois; Bakhshi, Parul; Brown, Derek; Lopez, Dominique; Gall, Fiona
2018-05-25
The capability approach pioneered by Amartya Sen and Martha Nussbaum offers a new paradigm to examine disability, poverty and their complex associations. Disability is hence defined as a situation in which a person with an impairment faces various forms of restrictions in functionings and capabilities. Additionally, poverty is not the mere absence of income but a lack of ability to achieve essential functionings; disability is consequently the poverty of capabilities of persons with impairment. It is the lack of opportunities in a given context and agency that leads to persons with disabilities being poorer than other social groups. Consequently, poverty of people with disabilities comprises of complex processes of social exclusion and disempowerment. Despite growing evidence that persons with disabilities face higher levels of poverty, the literature from low and middle-income countries that analyzes the causal link between disability and poverty, remains limited. Drawing on data from a large case control field survey carried out between December 24th , 2013 and February 16th , 2014 in Tunisia and between November 4th , 2013 and June 12th , 2014 in Morocco, we examined the effect of impairment on various basic capabilities, health related quality of life and multidimensional poverty - indicators of poor wellbeing-in Morocco and Tunisia. To demonstrate a causal link between impairment and deprivation of capabilities, we used instrumental variable regression analyses. In both countries, we found lower access to jobs for persons with impairment. Health related quality of life was also lower for this group who also faced a higher risk of multidimensional poverty. There was no significant direct effect of impairment on access to school and acquiring literacy in both countries, and on access to health care and expenses in Tunisia, while having an impairment reduced access to healthcare facilities in Morocco and out of pocket expenditures. These results suggest that
Slizovskaia, Olga; Gómez, Emilia; Haro, Gloria
2017-01-01
This work aims at investigating cross-modal connections between audio and video sources in the task of musical instrument recognition. We also address in this work the understanding of the representations learned by convolutional neural networks (CNNs) and we study feature correspondence between audio and visual components of a multimodal CNN architecture. For each instrument category, we select the most activated neurons and investigate exist- ing cross-correlations between neurons from the ...
DEFF Research Database (Denmark)
Köster, Fritz; Hinrichsen, H.H.; St. John, Michael
2001-01-01
We investigate whether a process-oriented approach based on the results of field, laboratory, and modelling studies can be used to develop a stock-environment-recruitment model for Central Baltic cod (Gadus morhua). Based on exploratory statistical analysis, significant variables influencing...... cod in these areas, suggesting that key biotic and abiotic processes can be successfully incorporated into recruitment models....... survival of early life stages and varying systematically among spawning sites were incorporated into stock-recruitment models, first for major cod spawning sites and then combined for the entire Central Baltic. Variables identified included potential egg production by the spawning stock, abiotic conditions...
Dons, Evi; Van Poppel, Martine; Kochan, Bruno; Wets, Geert; Int Panis, Luc
2013-08-01
Land use regression (LUR) modeling is a statistical technique used to determine exposure to air pollutants in epidemiological studies. Time-activity diaries can be combined with LUR models, enabling detailed exposure estimation and limiting exposure misclassification, both in shorter and longer time lags. In this study, the traffic related air pollutant black carbon was measured with μ-aethalometers on a 5-min time base at 63 locations in Flanders, Belgium. The measurements show that hourly concentrations vary between different locations, but also over the day. Furthermore the diurnal pattern is different for street and background locations. This suggests that annual LUR models are not sufficient to capture all the variation. Hourly LUR models for black carbon are developed using different strategies: by means of dummy variables, with dynamic dependent variables and/or with dynamic and static independent variables. The LUR model with 48 dummies (weekday hours and weekend hours) performs not as good as the annual model (explained variance of 0.44 compared to 0.77 in the annual model). The dataset with hourly concentrations of black carbon can be used to recalibrate the annual model, resulting in many of the original explaining variables losing their statistical significance, and certain variables having the wrong direction of effect. Building new independent hourly models, with static or dynamic covariates, is proposed as the best solution to solve these issues. R2 values for hourly LUR models are mostly smaller than the R2 of the annual model, ranging from 0.07 to 0.8. Between 6 a.m. and 10 p.m. on weekdays the R2 approximates the annual model R2. Even though models of consecutive hours are developed independently, similar variables turn out to be significant. Using dynamic covariates instead of static covariates, i.e. hourly traffic intensities and hourly population densities, did not significantly improve the models' performance.
Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.
2017-01-01
Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable
International Nuclear Information System (INIS)
Cordoba Maquilon, Jorge E; Gonzalez Calderon, Carlos A; Posada Henao, John J
2011-01-01
A study using revealed preference surveys and psychological tests was conducted. Key psychological variables of behavior involved in the choice of transportation mode in a population sample of the Metropolitan Area of the Valle de Aburra were detected. The experiment used the random utility theory for discrete choice models and reasoned action in order to assess beliefs. This was used as a tool for analysis of the psychological variables using the sixteen personality factor questionnaire (16PF test). In addition to the revealed preference surveys, two other surveys were carried out: one with socio-economic characteristics and the other with latent indicators. This methodology allows for an integration of discrete choice models and latent variables. The integration makes the model operational and quantifies the unobservable psychological variables. The most relevant result obtained was that anxiety affects the choice of urban transportation mode and shows that physiological alterations, as well as problems in perception and beliefs, can affect the decision-making process.
Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models
DEFF Research Database (Denmark)
Kock, Anders Bredahl
This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular we show that the Bridge estimator is oracle efficient. It can correctly distinguish between relevant...... and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation. In the case of more explanatory variables than observations......, we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables. We do this without restricting the dependence between covariates and without assuming sub Gaussianity of the error terms thereby generalizing the results...
Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan
2017-10-01
Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.
How ocean lateral mixing changes Southern Ocean variability in coupled climate models
Pradal, M. A. S.; Gnanadesikan, A.; Thomas, J. L.
2016-02-01
The lateral mixing of tracers represents a major uncertainty in the formulation of coupled climate models. The mixing of tracers along density surfaces in the interior and horizontally within the mixed layer is often parameterized using a mixing coefficient ARedi. The models used in the Coupled Model Intercomparison Project 5 exhibit more than an order of magnitude range in the values of this coefficient used within the Southern Ocean. The impacts of such uncertainty on Southern Ocean variability have remained unclear, even as recent work has shown that this variability differs between different models. In this poster, we change the lateral mixing coefficient within GFDL ESM2Mc, a coarse-resolution Earth System model that nonetheless has a reasonable circulation within the Southern Ocean. As the coefficient varies from 400 to 2400 m2/s the amplitude of the variability varies significantly. The low-mixing case shows strong decadal variability with an annual mean RMS temperature variability exceeding 1C in the Circumpolar Current. The highest-mixing case shows a very similar spatial pattern of variability, but with amplitudes only about 60% as large. The suppression of mixing is larger in the Atlantic Sector of the Southern Ocean relatively to the Pacific sector. We examine the salinity budgets of convective regions, paying particular attention to the extent to which high mixing prevents the buildup of low-saline waters that are capable of shutting off deep convection entirely.
Troy, Tara J.; Ines, Amor V. M.; Lall, Upmanu; Robertson, Andrew W.
2013-04-01
Large-scale hydrologic models, such as the Variable Infiltration Capacity (VIC) model, are used for a variety of studies, from drought monitoring to projecting the potential impact of climate change on the hydrologic cycle decades in advance. The majority of these models simulates the natural hydrological cycle and neglects the effects of human activities such as irrigation, which can result in streamflow withdrawals and increased evapotranspiration. In some parts of the world, these activities do not significantly affect the hydrologic cycle, but this is not the case in south Asia where irrigated agriculture has a large water footprint. To address this gap, we incorporate a crop growth model and irrigation model into the VIC model in order to simulate the impacts of irrigated and rainfed agriculture on the hydrologic cycle over south Asia (Indus, Ganges, and Brahmaputra basin and peninsular India). The crop growth model responds to climate signals, including temperature and water stress, to simulate the growth of maize, wheat, rice, and millet. For the primarily rainfed maize crop, the crop growth model shows good correlation with observed All-India yields (0.7) with lower correlations for the irrigated wheat and rice crops (0.4). The difference in correlation is because irrigation provides a buffer against climate conditions, so that rainfed crop growth is more tied to climate than irrigated crop growth. The irrigation water demands induce hydrologic water stress in significant parts of the region, particularly in the Indus, with the streamflow unable to meet the irrigation demands. Although rainfall can vary significantly in south Asia, we find that water scarcity is largely chronic due to the irrigation demands rather than being intermittent due to climate variability.
Optical modeling of waveguide coupled TES detectors towards the SAFARI instrument for SPICA
Trappe, N.; Bracken, C.; Doherty, S.; Gao, J. R.; Glowacka, D.; Goldie, D.; Griffin, D.; Hijmering, R.; Jackson, B.; Khosropanah, P.; Mauskopf, P.; Morozov, D.; Murphy, A.; O'Sullivan, C.; Ridder, M.; Withington, S.
2012-09-01
The next generation of space missions targeting far-infrared wavelengths will require large-format arrays of extremely sensitive detectors. The development of Transition Edge Sensor (TES) array technology is being developed for future Far-Infrared (FIR) space applications such as the SAFARI instrument for SPICA where low-noise and high sensitivity is required to achieve ambitious science goals. In this paper we describe a modal analysis of multi-moded horn antennas feeding integrating cavities housing TES detectors with superconducting film absorbers. In high sensitivity TES detector technology the ability to control the electromagnetic and thermo-mechanical environment of the detector is critical. Simulating and understanding optical behaviour of such detectors at far IR wavelengths is difficult and requires development of existing analysis tools. The proposed modal approach offers a computationally efficient technique to describe the partial coherent response of the full pixel in terms of optical efficiency and power leakage between pixels. Initial wok carried out as part of an ESA technical research project on optical analysis is described and a prototype SAFARI pixel design is analyzed where the optical coupling between the incoming field and the pixel containing horn, cavity with an air gap, and thin absorber layer are all included in the model to allow a comprehensive optical characterization. The modal approach described is based on the mode matching technique where the horn and cavity are described in the traditional way while a technique to include the absorber was developed. Radiation leakage between pixels is also included making this a powerful analysis tool.
Importance analysis for models with correlated variables and its sparse grid solution
International Nuclear Information System (INIS)
Li, Luyi; Lu, Zhenzhou
2013-01-01
For structural models involving correlated input variables, a novel interpretation for variance-based importance measures is proposed based on the contribution of the correlated input variables to the variance of the model output. After the novel interpretation of the variance-based importance measures is compared with the existing ones, two solutions of the variance-based importance measures of the correlated input variables are built on the sparse grid numerical integration (SGI): double-loop nested sparse grid integration (DSGI) method and single loop sparse grid integration (SSGI) method. The DSGI method solves the importance measure by decreasing the dimensionality of the input variables procedurally, while SSGI method performs importance analysis through extending the dimensionality of the inputs. Both of them can make full use of the advantages of the SGI, and are well tailored for different situations. By analyzing the results of several numerical and engineering examples, it is found that the novel proposed interpretation about the importance measures of the correlated input variables is reasonable, and the proposed methods for solving importance measures are efficient and accurate. -- Highlights: •The contribution of correlated variables to the variance of the output is analyzed. •A novel interpretation for variance-based indices of correlated variables is proposed. •Two solutions for variance-based importance measures of correlated variables are built
International Nuclear Information System (INIS)
De Larrard, Th.
2010-09-01
Evaluating structures durability requires taking into account the variability of material properties. The thesis has two main aspects: on the one hand, an experimental campaign aimed at quantifying the variability of many indicators of concrete behaviour; on the other hand, a simple numerical model for calcium leaching is developed in order to implement probabilistic methods so as to estimate the lifetime of structures such as those related to radioactive waste disposal. The experimental campaign consisted in following up two real building sites, and quantifying the variability of these indicators, studying their correlation, and characterising the random fields variability for the considered variables (especially the correlation length). To draw any conclusion from the accelerated leaching tests with ammonium nitrate by overcoming the effects of temperature, an inverse analysis tool based on the theory of artificial neural networks was developed. Simple numerical tools are presented to investigate the propagation of variability in durability issues, quantify the influence of this variability on the lifespan of structures and explain the variability of the input parameters of the numerical model and the physical measurable quantities of the material. (author)
Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models
Directory of Open Access Journals (Sweden)
Hui Wang
2017-10-01
Full Text Available Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the selection of input variables, which can have significant impacts on forecasting performance. This paper presents an input variable selection method for wind speed forecasting models. The candidate input variables for various leading periods are selected and random forests (RF is employed to evaluate the importance of all variable as features. The feature subset with the best evaluation performance is selected as the optimal feature set. Then, kernel-based extreme learning machine is constructed to evaluate the performance of input variables selection based on RF. The results of the case study show that by removing the uncorrelated and redundant features, RF effectively extracts the most strongly correlated set of features from the candidate input variables. By finding the optimal feature combination to represent the original information, RF simplifies the structure of the wind speed forecasting model, shortens the training time required, and substantially improves the model’s accuracy and generalization ability, demonstrating that the input variables selected by RF are effective.
Kawase, Mitsuhiro; Bang, Bohyun
2013-12-01
A three-dimensional hydrodynamic model is used to study seasonal variability of circulation and hydrography in Hood Canal, Washington, United States, an estuarine fjord that develops seasonally hypoxic conditions. The model is validated with data from year 2006, and is shown to be capable of quantitatively realistic simulation of hydrographic variability. Sensitivity experiments show the largest cause of seasonal variability to be that of salinity at the mouth of the fjord, which drives an annual deep water renewal in late summer-early autumn. Variability of fresh water input from the watershed also causes significant but secondary changes, especially in winter. Local wind stress has little effect over the seasonal timescale. Further experiments, in which one forcing parameter is abruptly altered while others are kept constant, show that outside salinity change induces an immediate response in the exchange circulation that, however, decays as a transient as the system equilibrates. In contrast, a change in the river input initiates gradual adjustment towards a new equilibrium value for the exchange transport. It is hypothesized that the spectral character of the system response to river variability will be redder than to salinity variability. This is demonstrated with a stochastically forced, semi-analytical model of fjord exchange circulation. While the exchange circulation in Hood Canal appears less sensitive to the river variability than to the outside hydrography at seasonal timescales, at decadal and longer timescales both could become significant factors in affecting the exchange circulation.
Directory of Open Access Journals (Sweden)
Dirk Temme
2008-12-01
Full Text Available Integrated choice and latent variable (ICLV models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.
Global model of the upper atmosphere with a variable step of integration in latitude
International Nuclear Information System (INIS)
Namgaladze, A.A.; Martynenko, O.V.; Namgaladze, A.N.
1996-01-01
New version of model for the Earth thermosphere, ionosphere and protonosphere with increased spatial distribution, realized at personal computer, is developed. Numerical solution algorithm for modeling equations solution, which makes it possible to apply variable (depending on latitude) integrating pitch by latitude and to increase hereby the model latitude resolutions in the latitude zones of interest. Comparison of the model calculational results of ionosphere and thermosphere parameters, accomplished with application of different integrating pitches by geomagnetic latitude, is conducted. 10 refs.; 3 figs
Muller, Benjamin J.; Cade, Brian S.; Schwarzkoph, Lin
2018-01-01
Many different factors influence animal activity. Often, the value of an environmental variable may influence significantly the upper or lower tails of the activity distribution. For describing relationships with heterogeneous boundaries, quantile regressions predict a quantile of the conditional distribution of the dependent variable. A quantile count model extends linear quantile regression methods to discrete response variables, and is useful if activity is quantified by trapping, where there may be many tied (equal) values in the activity distribution, over a small range of discrete values. Additionally, different environmental variables in combination may have synergistic or antagonistic effects on activity, so examining their effects together, in a modeling framework, is a useful approach. Thus, model selection on quantile counts can be used to determine the relative importance of different variables in determining activity, across the entire distribution of capture results. We conducted model selection on quantile count models to describe the factors affecting activity (numbers of captures) of cane toads (Rhinella marina) in response to several environmental variables (humidity, temperature, rainfall, wind speed, and moon luminosity) over eleven months of trapping. Environmental effects on activity are understudied in this pest animal. In the dry season, model selection on quantile count models suggested that rainfall positively affected activity, especially near the lower tails of the activity distribution. In the wet season, wind speed limited activity near the maximum of the distribution, while minimum activity increased with minimum temperature. This statistical methodology allowed us to explore, in depth, how environmental factors influenced activity across the entire distribution, and is applicable to any survey or trapping regime, in which environmental variables affect activity.
Beauregard, Frieda; de Blois, Sylvie
2014-01-01
Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential
Directory of Open Access Journals (Sweden)
Frieda Beauregard
Full Text Available Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839 covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study
Hadzaman, N. A. H.; Takim, R.; Nawawi, A. H.; Mohamad Yusuwan, N.
2018-04-01
BIM governance assessment instrument is a process of analysing the importance in developing BIM governance solution to tackle the existing problems during team collaboration in BIM-based projects. Despite the deployment of integrative technologies in construction industry particularly BIM, it is still insufficient compare to other sectors. Several studies have been established the requirements of BIM implementation concerning all technical and non-technical BIM adoption issues. However, the data are regarded as inadequate to develop a BIM governance framework. Hence, the objective of the paper is to evaluate the content validity of the BIM governance instrument prior to the main data collection. Two methods were employed in the form of literature review and questionnaire survey. Based on the literature review, 273 items with six main constructs are suggested to be incorporated in the BIM governance instrument. The Content Validity Ratio (CVR) scores revealed that 202 out of 273 items are considered as the utmost critical by the content experts. The findings for Item Level Content Validity Index (I-CVI) and Modified Kappa Coefficient however revealed that 257 items in BIM governance instrument are appropriate and excellent. The instrument is highly reliable for future strategies and the development of BIM projects in Malaysia.
Jones, Brendon R; Brouwers, Luke B; Van Tonder, Warren D; Dippenaar, Matthys A
2017-05-01
The vadose zone typically comprises soil underlain by fractured rock. Often, surface water and groundwater parameters are readily available, but variably saturated flow through soil and rock are oversimplified or estimated as input for hydrological models. In this paper, a series of geotechnical centrifuge experiments are conducted to contribute to the knowledge gaps in: (i) variably saturated flow and dispersion in soil and (ii) variably saturated flow in discrete vertical and horizontal fractures. Findings from the research show that the hydraulic gradient, and not the hydraulic conductivity, is scaled for seepage flow in the geotechnical centrifuge. Furthermore, geotechnical centrifuge modelling has been proven as a viable experimental tool for the modelling of hydrodynamic dispersion as well as the replication of similar flow mechanisms for unsaturated fracture flow, as previously observed in literature. Despite the imminent challenges of modelling variable saturation in the vadose zone, the geotechnical centrifuge offers a powerful experimental tool to physically model and observe variably saturated flow. This can be used to give valuable insight into mechanisms associated with solid-fluid interaction problems under these conditions. Findings from future research can be used to validate current numerical modelling techniques and address the subsequent influence on aquifer recharge and vulnerability, contaminant transport, waste disposal, dam construction, slope stability and seepage into subsurface excavations.
Directory of Open Access Journals (Sweden)
Liu Yufeng
2011-01-01
Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA
Internal and external North Atlantic Sector variability in the Kiel climate model
Energy Technology Data Exchange (ETDEWEB)
Latif, Mojib; Park, Wonsun; Ding, Hui; Keenlyside, Noel S. [Leibniz-Inst. fuer Meereswissenschaften, Kiel (Germany)
2009-08-15
The internal and external North Atlantic Sector variability is investigated by means of a multimillennial control run and forced experiments with the Kiel Climate Model (KCM). The internal variability is studied by analyzing the control run. The externally forced variability is investigated in a run with periodic millennial solar forcing and in greenhouse warming experiments with enhanced carbon dioxide concentrations. The surface air temperature (SAT) averaged over the Northern Hemisphere simulated in the control run displays enhanced variability relative to the red background at decadal, centennial, and millennial timescales. Special emphasis is given to the variability of the Meridional Overturning Circulation (MOC). The MOC plays an important role in the generation of internal climate modes. Furthermore, the MOC provides a strong negative feedback on the Northern Hemisphere SAT in both the solar and greenhouse warming experiments, thereby moderating the direct effects of the external forcing in the North Atlantic. The implications of the results for decadal predictability are discussed. (orig.)
DEFF Research Database (Denmark)
Krøigård, Thomas; Gaist, David; Otto, Marit
2014-01-01
SUMMARY: The reproducibility of variables commonly included in studies of peripheral nerve conduction in healthy individuals has not previously been analyzed using a random effects regression model. We examined the temporal changes and variability of standard nerve conduction measures in the leg...... reexamined after 2 and 26 weeks. There was no change in the variables except for a minor decrease in sural nerve sensory action potential amplitude and a minor increase in tibial nerve minimal F-wave latency. Reproducibility was best for peroneal nerve distal motor latency and motor conduction velocity......, sural nerve sensory conduction velocity, and tibial nerve minimal F-wave latency. Between-subject variability was greater than within-subject variability. Sample sizes ranging from 21 to 128 would be required to show changes twice the magnitude of the spontaneous changes observed in this study. Nerve...
Analysis of Design Variables of Annular Linear Induction Electromagnetic Pump using an MHD Model
Energy Technology Data Exchange (ETDEWEB)
Kwak, Jae Sik; Kim, Hee Reyoung [Ulsan National Institute of Science and Technology, Ulsan (Korea, Republic of)
2015-05-15
The generated force is affected by lots of factors including electrical input, hydrodynamic flow, geometrical shape, and so on. These factors, which are the design variables of an ALIP, should be suitably analyzed to optimally design an ALIP. Analysis on the developed pressure and efficiency of the ALIP according to the change of design variables is required for the ALIP satisfying requirements. In this study, the design variables of the ALIP are analyzed by using ideal MHD analysis model. Electromagnetic force and efficiency are derived by analyzing the main design variables such as pump core length, inner core diameter, flow gap and turns of coils. The developed pressure and efficiency of the ALIP were derived and analyzed on the change of the main variables such as pump core length, inner core diameter, flow gap, and turns of coils of the ALIP.
Directory of Open Access Journals (Sweden)
Şaban YURTÇU
2006-02-01
Full Text Available In this study, modeling of the effect of rainfall, flow and evaporation as independent variables on the change of underground water levels as dependent variables were investigated by fuzzy logic (FL. In the study, total 396 values taken from six observation stations belong to Afyon inferior basin in Akarçay from 1977 to 1989 years were used. Using the monthly average values of stations, the change of underground water level was modeled by FL. It is observed that the results obtained from FL and the observations are compatible with each other. This shows FL modeling can be used to estimate groundwater levels from the appropriate meteorological value.
International Nuclear Information System (INIS)
Ebel, P.E.; Godfrey, W.L.; Henry, J.L.; Postles, R.L.
1983-09-01
An extensive computer model describing the mass balance and economic characteristics of radioactive waste disposal systems was exercised in a series of runs designed using linear statistical methods. The most economically important variables were identified, their behavior characterized, and a simplified computer model prepared which runs on desk-top minicomputers. This simplified model allows the investigation of the effects of the seven most significant variables in each of four waste areas: Liquid Waste Storage, Liquid Waste Solidification, General Process Trash Handling, and Hulls Handling. 8 references, 1 figure, 12 tables
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2012-01-01
Robust model predictive control (RMPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Because...... of the special structure of the problem, uncertainty is only in the B matrix (gain) of the state space model. Therefore by taking advantage of this structure, we formulate a tractable minimax optimization problem to solve robust model predictive control problem. Wind turbine is chosen as the case study and we...... choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....
Directory of Open Access Journals (Sweden)
Hideki Katagiri
2017-10-01
Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.
Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver
Kang, Ling; Zhou, Liwei
2018-02-01
Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.
Incorporating additional tree and environmental variables in a lodgepole pine stem profile model
John C. Byrne
1993-01-01
A new variable-form segmented stem profile model is developed for lodgepole pine (Pinus contorta) trees from the northern Rocky Mountains of the United States. I improved estimates of stem diameter by predicting two of the model coefficients with linear equations using a measure of tree form, defined as a ratio of dbh and total height. Additional improvements were...
GY SAMPLING THEORY AND GEOSTATISTICS: ALTERNATE MODELS OF VARIABILITY IN CONTINUOUS MEDIA
In the sampling theory developed by Pierre Gy, sample variability is modeled as the sum of a set of seven discrete error components. The variogram used in geostatisties provides an alternate model in which several of Gy's error components are combined in a continuous mode...
The Matrix model, a driven state variables approach to non-equilibrium thermodynamics
Jongschaap, R.J.J.
2001-01-01
One of the new approaches in non-equilibrium thermodynamics is the so-called matrix model of Jongschaap. In this paper some features of this model are discussed. We indicate the differences with the more common approach based upon internal variables and the more sophisticated Hamiltonian and GENERIC
Kim, Seohyun; Lu, Zhenqiu; Cohen, Allan S.
2018-01-01
Bayesian algorithms have been used successfully in the social and behavioral sciences to analyze dichotomous data particularly with complex structural equation models. In this study, we investigate the use of the Polya-Gamma data augmentation method with Gibbs sampling to improve estimation of structural equation models with dichotomous variables.…
A Second-Order Conditionally Linear Mixed Effects Model with Observed and Latent Variable Covariates
Harring, Jeffrey R.; Kohli, Nidhi; Silverman, Rebecca D.; Speece, Deborah L.
2012-01-01
A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a…
Estimating structural equation models with non-normal variables by using transformations
Montfort, van K.; Mooijaart, A.; Meijerink, F.
2009-01-01
We discuss structural equation models for non-normal variables. In this situation the maximum likelihood and the generalized least-squares estimates of the model parameters can give incorrect estimates of the standard errors and the associated goodness-of-fit chi-squared statistics. If the sample
Modeling and fabrication of an RF MEMS variable capacitor with a fractal geometry
Elshurafa, Amro M.
2013-08-16
In this paper, we model, fabricate, and measure an electrostatically actuated MEMS variable capacitor that utilizes a fractal geometry and serpentine-like suspension arms. Explicitly, a variable capacitor that possesses a top suspended plate with a specific fractal geometry and also possesses a bottom fixed plate complementary in shape to the top plate has been fabricated in the PolyMUMPS process. An important benefit that was achieved from using the fractal geometry in designing the MEMS variable capacitor is increasing the tuning range of the variable capacitor beyond the typical ratio of 1.5. The modeling was carried out using the commercially available finite element software COMSOL to predict both the tuning range and pull-in voltage. Measurement results show that the tuning range is 2.5 at a maximum actuation voltage of 10V.
Directory of Open Access Journals (Sweden)
Sabine eDemotes-Mainard
2013-10-01
Full Text Available Bush rose architecture, among other factors, such as plant health, determines plant visual quality. The commercial product is the individual plant and interplant variability may be high within a crop. Thus, both mean plant architecture and interplant variability should be studied. Expansion is an important feature of architecture, but it has been little studied at the level of individual organs in bush roses. We investigated the expansion kinetics of primary shoot organs, to develop a model reproducing the organ expansion of real crops from non destructive input variables. We took interplant variability in expansion kinetics and the model’s ability to simulate this variability into account. Changes in leaflet and internode dimensions over thermal time were recorded for primary shoot expansion, on 83 plants from three crops grown in different climatic conditions and densities. An empirical model was developed, to reproduce organ expansion kinetics for individual plants of a real crop of bush rose primary shoots. Leaflet or internode length was simulated as a logistic function of thermal time. The model was evaluated by cross-validation. We found that differences in leaflet or internode expansion kinetics between phytomer positions and between plants at a given phytomer position were due mostly to large differences in time of organ expansion and expansion rate, rather than differences in expansion duration. Thus, in the model, the parameters linked to expansion duration were predicted by values common to all plants, whereas variability in final size and organ expansion time was captured by input data. The model accurately simulated leaflet and internode expansion for individual plants (RMSEP = 7.3% and 10.2% of final length, respectively. Thus, this study defines the measurements required to simulate expansion and provides the first model simulating organ expansion in rosebush to capture interplant variability.