Validation of vision-based obstacle detection algorithms for low-altitude helicopter flight

NASA Technical Reports Server (NTRS)

Suorsa, Raymond; Sridhar, Banavar

1991-01-01

A validation facility being used at the NASA Ames Research Center is described which is aimed at testing vision based obstacle detection and range estimation algorithms suitable for low level helicopter flight. The facility is capable of processing hundreds of frames of calibrated multicamera 6 degree-of-freedom motion image sequencies, generating calibrated multicamera laboratory images using convenient window-based software, and viewing range estimation results from different algorithms along with truth data using powerful window-based visualization software.

Criterion-Related Validity of the Distance- and Time-Based Walk/Run Field Tests for Estimating Cardiorespiratory Fitness: A Systematic Review and Meta-Analysis.

PubMed

Mayorga-Vega, Daniel; Bocanegra-Parrilla, Raúl; Ornelas, Martha; Viciana, Jesús

2016-01-01

The main purpose of the present meta-analysis was to examine the criterion-related validity of the distance- and time-based walk/run tests for estimating cardiorespiratory fitness among apparently healthy children and adults. Relevant studies were searched from seven electronic bibliographic databases up to August 2015 and through other sources. The Hunter-Schmidt's psychometric meta-analysis approach was conducted to estimate the population criterion-related validity of the following walk/run tests: 5,000 m, 3 miles, 2 miles, 3,000 m, 1.5 miles, 1 mile, 1,000 m, ½ mile, 600 m, 600 yd, ¼ mile, 15 min, 12 min, 9 min, and 6 min. From the 123 included studies, a total of 200 correlation values were analyzed. The overall results showed that the criterion-related validity of the walk/run tests for estimating maximum oxygen uptake ranged from low to moderate (rp = 0.42-0.79), with the 1.5 mile (rp = 0.79, 0.73-0.85) and 12 min walk/run tests (rp = 0.78, 0.72-0.83) having the higher criterion-related validity for distance- and time-based field tests, respectively. The present meta-analysis also showed that sex, age and maximum oxygen uptake level do not seem to affect the criterion-related validity of the walk/run tests. When the evaluation of an individual's maximum oxygen uptake attained during a laboratory test is not feasible, the 1.5 mile and 12 min walk/run tests represent useful alternatives for estimating cardiorespiratory fitness. As in the assessment with any physical fitness field test, evaluators must be aware that the performance score of the walk/run field tests is simply an estimation and not a direct measure of cardiorespiratory fitness.

Psychometric instrumentation: reliability and validity of instruments used for clinical practice, evidence-based practice projects and research studies.

PubMed

Mayo, Ann M

2015-01-01

It is important for CNSs and other APNs to consider the reliability and validity of instruments chosen for clinical practice, evidence-based practice projects, or research studies. Psychometric testing uses specific research methods to evaluate the amount of error associated with any particular instrument. Reliability estimates explain more about how well the instrument is designed, whereas validity estimates explain more about scores that are produced by the instrument. An instrument may be architecturally sound overall (reliable), but the same instrument may not be valid. For example, if a specific group does not understand certain well-constructed items, then the instrument does not produce valid scores when used with that group. Many instrument developers may conduct reliability testing only once, yet continue validity testing in different populations over many years. All CNSs should be advocating for the use of reliable instruments that produce valid results. Clinical nurse specialists may find themselves in situations where reliability and validity estimates for some instruments that are being utilized are unknown. In such cases, CNSs should engage key stakeholders to sponsor nursing researchers to pursue this most important work.

Center of pressure based segment inertial parameters validation

PubMed Central

Rezzoug, Nasser; Gorce, Philippe; Isableu, Brice; Venture, Gentiane

2017-01-01

By proposing efficient methods for estimating Body Segment Inertial Parameters’ (BSIP) estimation and validating them with a force plate, it is possible to improve the inverse dynamic computations that are necessary in multiple research areas. Until today a variety of studies have been conducted to improve BSIP estimation but to our knowledge a real validation has never been completely successful. In this paper, we propose a validation method using both kinematic and kinetic parameters (contact forces) gathered from optical motion capture system and a force plate respectively. To compare BSIPs, we used the measured contact forces (Force plate) as the ground truth, and reconstructed the displacements of the Center of Pressure (COP) using inverse dynamics from two different estimation techniques. Only minor differences were seen when comparing the estimated segment masses. Their influence on the COP computation however is large and the results show very distinguishable patterns of the COP movements. Improving BSIP techniques is crucial and deviation from the estimations can actually result in large errors. This method could be used as a tool to validate BSIP estimation techniques. An advantage of this approach is that it facilitates the comparison between BSIP estimation methods and more specifically it shows the accuracy of those parameters. PMID:28662090

A semi-automatic method for left ventricle volume estimate: an in vivo validation study

NASA Technical Reports Server (NTRS)

Corsi, C.; Lamberti, C.; Sarti, A.; Saracino, G.; Shiota, T.; Thomas, J. D.

2001-01-01

This study aims to the validation of the left ventricular (LV) volume estimates obtained by processing volumetric data utilizing a segmentation model based on level set technique. The validation has been performed by comparing real-time volumetric echo data (RT3DE) and magnetic resonance (MRI) data. A validation protocol has been defined. The validation protocol was applied to twenty-four estimates (range 61-467 ml) obtained from normal and pathologic subjects, which underwent both RT3DE and MRI. A statistical analysis was performed on each estimate and on clinical parameters as stroke volume (SV) and ejection fraction (EF). Assuming MRI estimates (x) as a reference, an excellent correlation was found with volume measured by utilizing the segmentation procedure (y) (y=0.89x + 13.78, r=0.98). The mean error on SV was 8 ml and the mean error on EF was 2%. This study demonstrated that the segmentation technique is reliably applicable on human hearts in clinical practice.

Accelerated Aging in Electrolytic Capacitors for Prognostics

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Kulkarni, Chetan; Saha, Sankalita; Biswas, Gautam; Goebel, Kai Frank

2012-01-01

The focus of this work is the analysis of different degradation phenomena based on thermal overstress and electrical overstress accelerated aging systems and the use of accelerated aging techniques for prognostics algorithm development. Results on thermal overstress and electrical overstress experiments are presented. In addition, preliminary results toward the development of physics-based degradation models are presented focusing on the electrolyte evaporation failure mechanism. An empirical degradation model based on percentage capacitance loss under electrical overstress is presented and used in: (i) a Bayesian-based implementation of model-based prognostics using a discrete Kalman filter for health state estimation, and (ii) a dynamic system representation of the degradation model for forecasting and remaining useful life (RUL) estimation. A leave-one-out validation methodology is used to assess the validity of the methodology under the small sample size constrain. The results observed on the RUL estimation are consistent through the validation tests comparing relative accuracy and prediction error. It has been observed that the inaccuracy of the model to represent the change in degradation behavior observed at the end of the test data is consistent throughout the validation tests, indicating the need of a more detailed degradation model or the use of an algorithm that could estimate model parameters on-line. Based on the observed degradation process under different stress intensity with rest periods, the need for more sophisticated degradation models is further supported. The current degradation model does not represent the capacitance recovery over rest periods following an accelerated aging stress period.

Testing survey-based methods for rapid monitoring of child mortality, with implications for summary birth history data.

PubMed

Brady, Eoghan; Hill, Kenneth

2017-01-01

Under-five mortality estimates are increasingly used in low and middle income countries to target interventions and measure performance against global development goals. Two new methods to rapidly estimate under-5 mortality based on Summary Birth Histories (SBH) were described in a previous paper and tested with data available. This analysis tests the methods using data appropriate to each method from 5 countries that lack vital registration systems. SBH data are collected across many countries through censuses and surveys, and indirect methods often rely upon their quality to estimate mortality rates. The Birth History Imputation method imputes data from a recent Full Birth History (FBH) onto the birth, death and age distribution of the SBH to produce estimates based on the resulting distribution of child mortality. DHS FBHs and MICS SBHs are used for all five countries. In the implementation, 43 of 70 estimates are within 20% of validation estimates (61%). Mean Absolute Relative Error is 17.7.%. 1 of 7 countries produces acceptable estimates. The Cohort Change method considers the differences in births and deaths between repeated Summary Birth Histories at 1 or 2-year intervals to estimate the mortality rate in that period. SBHs are taken from Brazil's PNAD Surveys 2004-2011 and validated against IGME estimates. 2 of 10 estimates are within 10% of validation estimates. Mean absolute relative error is greater than 100%. Appropriate testing of these new methods demonstrates that they do not produce sufficiently good estimates based on the data available. We conclude this is due to the poor quality of most SBH data included in the study. This has wider implications for the next round of censuses and future household surveys across many low- and middle- income countries.

Evaluating a Pivot-Based Approach for Bilingual Lexicon Extraction

PubMed Central

Kim, Jae-Hoon; Kwon, Hong-Seok; Seo, Hyeong-Won

2015-01-01

A pivot-based approach for bilingual lexicon extraction is based on the similarity of context vectors represented by words in a pivot language like English. In this paper, in order to show validity and usability of the pivot-based approach, we evaluate the approach in company with two different methods for estimating context vectors: one estimates them from two parallel corpora based on word association between source words (resp., target words) and pivot words and the other estimates them from two parallel corpora based on word alignment tools for statistical machine translation. Empirical results on two language pairs (e.g., Korean-Spanish and Korean-French) have shown that the pivot-based approach is very promising for resource-poor languages and this approach observes its validity and usability. Furthermore, for words with low frequency, our method is also well performed. PMID:25983745

Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables

ERIC Educational Resources Information Center

Johnson, Matthew T.; Lipscomb, Stephen; Gill, Brian

2015-01-01

Teacher value-added models (VAMs) must isolate teachers' contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added estimates under different models based on whether they…

Validating a new methodology for strain estimation from cardiac cine MRI

NASA Astrophysics Data System (ADS)

Elnakib, Ahmed; Beache, Garth M.; Gimel'farb, Georgy; Inanc, Tamer; El-Baz, Ayman

2013-10-01

This paper focuses on validating a novel framework for estimating the functional strain from cine cardiac magnetic resonance imaging (CMRI). The framework consists of three processing steps. First, the left ventricle (LV) wall borders are segmented using a level-set based deformable model. Second, the points on the wall borders are tracked during the cardiac cycle based on solving the Laplace equation between the LV edges. Finally, the circumferential and radial strains are estimated at the inner, mid-wall, and outer borders of the LV wall. The proposed framework is validated using synthetic phantoms of the material strains that account for the physiological features and the LV response during the cardiac cycle. Experimental results on simulated phantom images confirm the accuracy and robustness of our method.

Approximate Confidence Intervals for Moment-Based Estimators of the Between-Study Variance in Random Effects Meta-Analysis

ERIC Educational Resources Information Center

Jackson, Dan; Bowden, Jack; Baker, Rose

2015-01-01

Moment-based estimators of the between-study variance are very popular when performing random effects meta-analyses. This type of estimation has many advantages including computational and conceptual simplicity. Furthermore, by using these estimators in large samples, valid meta-analyses can be performed without the assumption that the treatment…

Nonlinear finite element model updating for damage identification of civil structures using batch Bayesian estimation

NASA Astrophysics Data System (ADS)

Ebrahimian, Hamed; Astroza, Rodrigo; Conte, Joel P.; de Callafon, Raymond A.

2017-02-01

This paper presents a framework for structural health monitoring (SHM) and damage identification of civil structures. This framework integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of the structure of interest. The framework uses input excitation and dynamic response of the structure and updates a nonlinear FE model of the structure to minimize the discrepancies between predicted and measured response time histories. The updated FE model can then be interrogated to detect, localize, classify, and quantify the state of damage and predict the remaining useful life of the structure. As opposed to recursive estimation methods, in the batch Bayesian estimation approach, the entire time history of the input excitation and output response of the structure are used as a batch of data to estimate the FE model parameters through a number of iterations. In the case of non-informative prior, the batch Bayesian method leads to an extended maximum likelihood (ML) estimation method to estimate jointly time-invariant model parameters and the measurement noise amplitude. The extended ML estimation problem is solved efficiently using a gradient-based interior-point optimization algorithm. Gradient-based optimization algorithms require the FE response sensitivities with respect to the model parameters to be identified. The FE response sensitivities are computed accurately and efficiently using the direct differentiation method (DDM). The estimation uncertainties are evaluated based on the Cramer-Rao lower bound (CRLB) theorem by computing the exact Fisher Information matrix using the FE response sensitivities with respect to the model parameters. The accuracy of the proposed uncertainty quantification approach is verified using a sampling approach based on the unscented transformation. Two validation studies, based on realistic structural FE models of a bridge pier and a moment resisting steel frame, are performed to validate the performance and accuracy of the presented nonlinear FE model updating approach and demonstrate its application to SHM. These validation studies show the excellent performance of the proposed framework for SHM and damage identification even in the presence of high measurement noise and/or way-out initial estimates of the model parameters. Furthermore, the detrimental effects of the input measurement noise on the performance of the proposed framework are illustrated and quantified through one of the validation studies.

Comparing UK, USA and Australian values for EQ-5D as a health utility measure of oral health.

PubMed

Brennan, D S; Teusner, D N

2015-09-01

Using generic measures to examine outcomes of oral disorders can add additional information relating to health utility. However, different algorithms are available to generate health states. The aim was to assess UK-, US- and Australian-based algorithms for the EuroQol (EQ-5D) in relation to their discriminative and convergent validity. Methods: Data were collected from adults in Australia aged 30-61 years by mailed survey in 2009-10, including the EQ-5D and a range of self-reported oral health variables, and self-rated oral and general health. Responses were collected from n=1,093 persons (response rate 39.1%). UK-based EQ-5D estimates were lower (0.85) than the USA and Australian estimates (0.91). EQ-5D was associated (p<0.01) with all seven oral health variables, with differences in utility scores ranging from 0.03 to 0.06 for the UK, from 0.04 to 0.07 for the USA, and from 0.05 to 0.08 for the Australian-based estimates. The effect sizes (ESs) of the associations with all seven oral health variables were similar for the UK (ES=0.26 to 0.49), USA (ES=0.31 to 0.48) and Australian-based (ES=0.31 to 0.46) estimates. EQ-5D was correlated with global dental health for the UK (rho=0.29), USA (rho=0.30) and Australian-based estimates (rho=0.30), and correlations with global general health were the same (rho=0.42) for the UK, USA and Australian-based estimates. EQ-5D exhibited equivalent discriminative validity and convergent validity in relation to oral health variables for the UK, USA and Australian-based estimates.

The predictive validity of quality of evidence grades for the stability of effect estimates was low: a meta-epidemiological study.

PubMed

Gartlehner, Gerald; Dobrescu, Andreea; Evans, Tammeka Swinson; Bann, Carla; Robinson, Karen A; Reston, James; Thaler, Kylie; Skelly, Andrea; Glechner, Anna; Peterson, Kimberly; Kien, Christina; Lohr, Kathleen N

2016-02-01

To determine the predictive validity of the U.S. Evidence-based Practice Center (EPC) approach to GRADE (Grading of Recommendations Assessment, Development and Evaluation). Based on Cochrane reports with outcomes graded as high quality of evidence (QOE), we prepared 160 documents which represented different levels of QOE. Professional systematic reviewers dually graded the QOE. For each document, we determined whether estimates were concordant with high QOE estimates of the Cochrane reports. We compared the observed proportion of concordant estimates with the expected proportion from an international survey. To determine the predictive validity, we used the Hosmer-Lemeshow test to assess calibration and the C (concordance) index to assess discrimination. The predictive validity of the EPC approach to GRADE was limited. Estimates graded as high QOE were less likely, estimates graded as low or insufficient QOE more likely to remain stable than expected. The EPC approach to GRADE could not reliably predict the likelihood that individual bodies of evidence remain stable as new evidence becomes available. C-indices ranged between 0.56 (95% CI, 0.47 to 0.66) and 0.58 (95% CI, 0.50 to 0.67) indicating a low discriminatory ability. The limited predictive validity of the EPC approach to GRADE seems to reflect a mismatch between expected and observed changes in treatment effects as bodies of evidence advance from insufficient to high QOE. Copyright © 2016 Elsevier Inc. All rights reserved.

Criterion-Related Validity of the Distance- and Time-Based Walk/Run Field Tests for Estimating Cardiorespiratory Fitness: A Systematic Review and Meta-Analysis

PubMed Central

Mayorga-Vega, Daniel; Bocanegra-Parrilla, Raúl; Ornelas, Martha; Viciana, Jesús

2016-01-01

Objectives The main purpose of the present meta-analysis was to examine the criterion-related validity of the distance- and time-based walk/run tests for estimating cardiorespiratory fitness among apparently healthy children and adults. Materials and Methods Relevant studies were searched from seven electronic bibliographic databases up to August 2015 and through other sources. The Hunter-Schmidt’s psychometric meta-analysis approach was conducted to estimate the population criterion-related validity of the following walk/run tests: 5,000 m, 3 miles, 2 miles, 3,000 m, 1.5 miles, 1 mile, 1,000 m, ½ mile, 600 m, 600 yd, ¼ mile, 15 min, 12 min, 9 min, and 6 min. Results From the 123 included studies, a total of 200 correlation values were analyzed. The overall results showed that the criterion-related validity of the walk/run tests for estimating maximum oxygen uptake ranged from low to moderate (rp = 0.42–0.79), with the 1.5 mile (rp = 0.79, 0.73–0.85) and 12 min walk/run tests (rp = 0.78, 0.72–0.83) having the higher criterion-related validity for distance- and time-based field tests, respectively. The present meta-analysis also showed that sex, age and maximum oxygen uptake level do not seem to affect the criterion-related validity of the walk/run tests. Conclusions When the evaluation of an individual’s maximum oxygen uptake attained during a laboratory test is not feasible, the 1.5 mile and 12 min walk/run tests represent useful alternatives for estimating cardiorespiratory fitness. As in the assessment with any physical fitness field test, evaluators must be aware that the performance score of the walk/run field tests is simply an estimation and not a direct measure of cardiorespiratory fitness. PMID:26987118

The Validity of the Comparative Interrupted Time Series Design for Evaluating the Effect of School-Level Interventions.

PubMed

Jacob, Robin; Somers, Marie-Andree; Zhu, Pei; Bloom, Howard

2016-06-01

In this article, we examine whether a well-executed comparative interrupted time series (CITS) design can produce valid inferences about the effectiveness of a school-level intervention. This article also explores the trade-off between bias reduction and precision loss across different methods of selecting comparison groups for the CITS design and assesses whether choosing matched comparison schools based only on preintervention test scores is sufficient to produce internally valid impact estimates. We conduct a validation study of the CITS design based on the federal Reading First program as implemented in one state using results from a regression discontinuity design as a causal benchmark. Our results contribute to the growing base of evidence regarding the validity of nonexperimental designs. We demonstrate that the CITS design can, in our example, produce internally valid estimates of program impacts when multiple years of preintervention outcome data (test scores in the present case) are available and when a set of reasonable criteria are used to select comparison organizations (schools in the present case). © The Author(s) 2016.

Estimating and validating ground-based timber harvesting production through computer simulation

Treesearch

Jingxin Wang; Chris B. LeDoux

2003-01-01

Estimating ground-based timber harvesting systems production with an object oriented methodology was investigated. The estimation model developed generates stands of trees, simulates chain saw, drive-to-tree feller-buncher, swing-to-tree single-grip harvester felling, and grapple skidder and forwarder extraction activities, and analyzes costs and productivity. It also...

Wechsler Adult Intelligence Scale-IV Dyads for Estimating Global Intelligence.

PubMed

Girard, Todd A; Axelrod, Bradley N; Patel, Ronak; Crawford, John R

2015-08-01

All possible two-subtest combinations of the core Wechsler Adult Intelligence Scale-IV (WAIS-IV) subtests were evaluated as possible viable short forms for estimating full-scale IQ (FSIQ). Validity of the dyads was evaluated relative to FSIQ in a large clinical sample (N = 482) referred for neuropsychological assessment. Sample validity measures included correlations, mean discrepancies, and levels of agreement between dyad estimates and FSIQ scores. In addition, reliability and validity coefficients were derived from WAIS-IV standardization data. The Coding + Information dyad had the strongest combination of reliability and validity data. However, several other dyads yielded comparable psychometric performance, albeit with some variability in their particular strengths. We also observed heterogeneity between validity coefficients from the clinical and standardization-based estimates for several dyads. Thus, readers are encouraged to also consider the individual psychometric attributes, their clinical or research goals, and client or sample characteristics when selecting among the dyadic short forms. © The Author(s) 2014.

Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation.

PubMed

Wahl, Simone; Boulesteix, Anne-Laure; Zierer, Astrid; Thorand, Barbara; van de Wiel, Mark A

2016-10-26

Missing values are a frequent issue in human studies. In many situations, multiple imputation (MI) is an appropriate missing data handling strategy, whereby missing values are imputed multiple times, the analysis is performed in every imputed data set, and the obtained estimates are pooled. If the aim is to estimate (added) predictive performance measures, such as (change in) the area under the receiver-operating characteristic curve (AUC), internal validation strategies become desirable in order to correct for optimism. It is not fully understood how internal validation should be combined with multiple imputation. In a comprehensive simulation study and in a real data set based on blood markers as predictors for mortality, we compare three combination strategies: Val-MI, internal validation followed by MI on the training and test parts separately, MI-Val, MI on the full data set followed by internal validation, and MI(-y)-Val, MI on the full data set omitting the outcome followed by internal validation. Different validation strategies, including bootstrap und cross-validation, different (added) performance measures, and various data characteristics are considered, and the strategies are evaluated with regard to bias and mean squared error of the obtained performance estimates. In addition, we elaborate on the number of resamples and imputations to be used, and adopt a strategy for confidence interval construction to incomplete data. Internal validation is essential in order to avoid optimism, with the bootstrap 0.632+ estimate representing a reliable method to correct for optimism. While estimates obtained by MI-Val are optimistically biased, those obtained by MI(-y)-Val tend to be pessimistic in the presence of a true underlying effect. Val-MI provides largely unbiased estimates, with a slight pessimistic bias with increasing true effect size, number of covariates and decreasing sample size. In Val-MI, accuracy of the estimate is more strongly improved by increasing the number of bootstrap draws rather than the number of imputations. With a simple integrated approach, valid confidence intervals for performance estimates can be obtained. When prognostic models are developed on incomplete data, Val-MI represents a valid strategy to obtain estimates of predictive performance measures.

Validating fatty acid intake as estimated by an FFQ: how does the 24 h recall perform as reference method compared with the duplicate portion?

PubMed

Trijsburg, Laura; de Vries, Jeanne Hm; Hollman, Peter Ch; Hulshof, Paul Jm; van 't Veer, Pieter; Boshuizen, Hendriek C; Geelen, Anouk

2018-05-08

To compare the performance of the commonly used 24 h recall (24hR) with the more distinct duplicate portion (DP) as reference method for validation of fatty acid intake estimated with an FFQ. Intakes of SFA, MUFA, n-3 fatty acids and linoleic acid (LA) were estimated by chemical analysis of two DP and by on average five 24hR and two FFQ. Plasma n-3 fatty acids and LA were used to objectively compare ranking of individuals based on DP and 24hR. Multivariate measurement error models were used to estimate validity coefficients and attenuation factors for the FFQ with the DP and 24hR as reference methods. Wageningen, the Netherlands. Ninety-two men and 106 women (aged 20-70 years). Validity coefficients for the fatty acid estimates by the FFQ tended to be lower when using the DP as reference method compared with the 24hR. Attenuation factors for the FFQ tended to be slightly higher based on the DP than those based on the 24hR as reference method. Furthermore, when using plasma fatty acids as reference, the DP showed comparable to slightly better ranking of participants according to their intake of n-3 fatty acids (0·33) and n-3:LA (0·34) than the 24hR (0·22 and 0·24, respectively). The 24hR gives only slightly different results compared with the distinctive but less feasible DP, therefore use of the 24hR seems appropriate as the reference method for FFQ validation of fatty acid intake.

Comparing Mapped Plot Estimators

Treesearch

Paul C. Van Deusen

2006-01-01

Two alternative derivations of estimators for mean and variance from mapped plots are compared by considering the models that support the estimators and by simulation. It turns out that both models lead to the same estimator for the mean but lead to very different variance estimators. The variance estimators based on the least valid model assumptions are shown to...

Low-cost extrapolation method for maximal LTE radio base station exposure estimation: test and validation.

PubMed

Verloock, Leen; Joseph, Wout; Gati, Azeddine; Varsier, Nadège; Flach, Björn; Wiart, Joe; Martens, Luc

2013-06-01

An experimental validation of a low-cost method for extrapolation and estimation of the maximal electromagnetic-field exposure from long-term evolution (LTE) radio base station installations are presented. No knowledge on downlink band occupation or service characteristics is required for the low-cost method. The method is applicable in situ. It only requires a basic spectrum analyser with appropriate field probes without the need of expensive dedicated LTE decoders. The method is validated both in laboratory and in situ, for a single-input single-output antenna LTE system and a 2×2 multiple-input multiple-output system, with low deviations in comparison with signals measured using dedicated LTE decoders.

Novel Equations for Estimating Lean Body Mass in Patients With Chronic Kidney Disease.

PubMed

Tian, Xue; Chen, Yuan; Yang, Zhi-Kai; Qu, Zhen; Dong, Jie

2018-05-01

Simplified methods to estimate lean body mass (LBM), an important nutritional measure representing muscle mass and somatic protein, are lacking in nondialyzed patients with chronic kidney disease (CKD). We developed and tested 2 reliable equations for estimation of LBM in daily clinical practice. The development and validation groups both included 150 nondialyzed patients with CKD Stages 3 to 5. Two equations for estimating LBM based on mid-arm muscle circumference (MAMC) or handgrip strength (HGS) were developed and validated in CKD patients with dual-energy x-ray absorptiometry as referenced gold method. We developed and validated 2 equations for estimating LBM based on HGS and MAMC. These equations, which also incorporated sex, height, and weight, were developed and validated in CKD patients. The new equations were found to exhibit only small biases when compared with dual-energy x-ray absorptiometry, with median differences of 0.94 and 0.46 kg observed in the HGS and MAMC equations, respectively. Good precision and accuracy were achieved for both equations, as reflected by small interquartile ranges in the differences and in the percentages of estimates that were 20% of measured LBM. The bias, precision, and accuracy of each equation were found to be similar when it was applied to groups of patients divided by the median measured LBM, the median ratio of extracellular to total body water, and the stages of CKD. LBM estimated from MAMC or HGS were found to provide accurate estimates of LBM in nondialyzed patients with CKD. Copyright © 2017 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Validation of one-mile walk equations for the estimation of aerobic fitness in British military personnel under the age of 40 years.

PubMed

Lunt, Heather; Roiz De Sa, Daniel; Roiz De Sa, Julia; Allsopp, Adrian

2013-07-01

To provide an accurate estimate of peak oxygen uptake (VO2 peak) for British Royal Navy Personnel aged between 18 and 39, comparing a gold standard treadmill based maximal exercise test with a submaximal one-mile walk test. Two hundred military personnel consented to perform a treadmill-based VO2 peak test and two one-mile walk tests round an athletics track. The estimated VO2 peak values from three different one-mile walk equations were compared to directly measured VO2 peak values from the treadmill-based test. One hundred participants formed a validation group from which a new equation was derived and the other 100 participants formed the cross-validation group. Existing equations underestimated the VO2 peak values of the fittest personnel and overestimated the VO2 peak of the least aerobically fit by between 2% and 18%. The new equation derived from the validation group has less bias, the highest correlation with the measured values (r = 0.83), and classified the most people correctly according to the Royal Navy's Fitness Test standards, producing the fewest false positives and false negatives combined (9%). The new equation will provide a more accurate estimate of VO2 peak for a British military population aged 18 to 39. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Reliability and Validity of the Evidence-Based Practice Confidence (EPIC) Scale

ERIC Educational Resources Information Center

Salbach, Nancy M.; Jaglal, Susan B.; Williams, Jack I.

2013-01-01

Introduction: The reliability, minimal detectable change (MDC), and construct validity of the evidence-based practice confidence (EPIC) scale were evaluated among physical therapists (PTs) in clinical practice. Methods: A longitudinal mail survey was conducted. Internal consistency and test-retest reliability were estimated using Cronbach's alpha…

Reliability and Validity of Inferences about Teachers Based on Student Scores. William H. Angoff Memorial Lecture Series

ERIC Educational Resources Information Center

Haertel, Edward H.

2013-01-01

Policymakers and school administrators have embraced value-added models of teacher effectiveness as tools for educational improvement. Teacher value-added estimates may be viewed as complicated scores of a certain kind. This suggests using a test validation model to examine their reliability and validity. Validation begins with an interpretive…

Software Development Cost Estimation Executive Summary

NASA Technical Reports Server (NTRS)

Hihn, Jairus M.; Menzies, Tim

2006-01-01

Identify simple fully validated cost models that provide estimation uncertainty with cost estimate. Based on COCOMO variable set. Use machine learning techniques to determine: a) Minimum number of cost drivers required for NASA domain based cost models; b) Minimum number of data records required and c) Estimation Uncertainty. Build a repository of software cost estimation information. Coordinating tool development and data collection with: a) Tasks funded by PA&E Cost Analysis; b) IV&V Effort Estimation Task and c) NASA SEPG activities.

Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer.

PubMed

Petersen, Japke F; Stuiver, Martijn M; Timmermans, Adriana J; Chen, Amy; Zhang, Hongzhen; O'Neill, James P; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T; Koch, Wayne; van den Brekel, Michiel W M

2018-05-01

TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442 patients with T3T4N0N+M0 larynx cancer. The model was internally validated using bootstrapping samples and externally validated on patient data from five external centers (n = 770). The main outcome was performance of the model as tested by discrimination, calibration, and the ability to distinguish risk groups based on tertiles from the derivation dataset. The model performance was compared to a model based on T and N classification only. We included age, gender, T and N classification, and subsite as prognostic variables in the standard model. After external validation, the standard model had a significantly better fit than a model based on T and N classification alone (C statistic, 0.59 vs. 0.55, P < .001). The model was able to distinguish well among three risk groups based on tertiles of the risk score. Adding treatment modality to the model did not decrease the predictive power. As a post hoc analysis, we tested the added value of comorbidity as scored by American Society of Anesthesiologists score in a subsample, which increased the C statistic to 0.68. A risk prediction model for patients with advanced larynx cancer, consisting of readily available clinical variables, gives more accurate estimations of the estimated 5-year survival rate when compared to a model based on T and N classification alone. 2c. Laryngoscope, 128:1140-1145, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

[A method to estimate the short-term fractal dimension of heart rate variability based on wavelet transform].

PubMed

Zhonggang, Liang; Hong, Yan

2006-10-01

A new method of calculating fractal dimension of short-term heart rate variability signals is presented. The method is based on wavelet transform and filter banks. The implementation of the method is: First of all we pick-up the fractal component from HRV signals using wavelet transform. Next, we estimate the power spectrum distribution of fractal component using auto-regressive model, and we estimate parameter 7 using the least square method. Finally according to formula D = 2- (gamma-1)/2 estimate fractal dimension of HRV signal. To validate the stability and reliability of the proposed method, using fractional brown movement simulate 24 fractal signals that fractal value is 1.6 to validate, the result shows that the method has stability and reliability.

Design, Implementation and Validation of the Three-Wheel Holonomic Motion System of the Assistant Personal Robot (APR).

PubMed

Moreno, Javier; Clotet, Eduard; Lupiañez, Ruben; Tresanchez, Marcel; Martínez, Dani; Pallejà, Tomàs; Casanovas, Jordi; Palacín, Jordi

2016-10-10

This paper presents the design, implementation and validation of the three-wheel holonomic motion system of a mobile robot designed to operate in homes. The holonomic motion system is described in terms of mechanical design and electronic control. The paper analyzes the kinematics of the motion system and validates the estimation of the trajectory comparing the displacement estimated with the internal odometry of the motors and the displacement estimated with a SLAM procedure based on LIDAR information. Results obtained in different experiments have shown a difference on less than 30 mm between the position estimated with the SLAM and odometry, and a difference in the angular orientation of the mobile robot lower than 5° in absolute displacements up to 1000 mm.

Design, Implementation and Validation of the Three-Wheel Holonomic Motion System of the Assistant Personal Robot (APR)

PubMed Central

Moreno, Javier; Clotet, Eduard; Lupiañez, Ruben; Tresanchez, Marcel; Martínez, Dani; Pallejà, Tomàs; Casanovas, Jordi; Palacín, Jordi

2016-01-01

This paper presents the design, implementation and validation of the three-wheel holonomic motion system of a mobile robot designed to operate in homes. The holonomic motion system is described in terms of mechanical design and electronic control. The paper analyzes the kinematics of the motion system and validates the estimation of the trajectory comparing the displacement estimated with the internal odometry of the motors and the displacement estimated with a SLAM procedure based on LIDAR information. Results obtained in different experiments have shown a difference on less than 30 mm between the position estimated with the SLAM and odometry, and a difference in the angular orientation of the mobile robot lower than 5° in absolute displacements up to 1000 mm. PMID:27735857

Genome-based prediction of test cross performance in two subsequent breeding cycles.

PubMed

Hofheinz, Nina; Borchardt, Dietrich; Weissleder, Knuth; Frisch, Matthias

2012-12-01

Genome-based prediction of genetic values is expected to overcome shortcomings that limit the application of QTL mapping and marker-assisted selection in plant breeding. Our goal was to study the genome-based prediction of test cross performance with genetic effects that were estimated using genotypes from the preceding breeding cycle. In particular, our objectives were to employ a ridge regression approach that approximates best linear unbiased prediction of genetic effects, compare cross validation with validation using genetic material of the subsequent breeding cycle, and investigate the prospects of genome-based prediction in sugar beet breeding. We focused on the traits sugar content and standard molasses loss (ML) and used a set of 310 sugar beet lines to estimate genetic effects at 384 SNP markers. In cross validation, correlations >0.8 between observed and predicted test cross performance were observed for both traits. However, in validation with 56 lines from the next breeding cycle, a correlation of 0.8 could only be observed for sugar content, for standard ML the correlation reduced to 0.4. We found that ridge regression based on preliminary estimates of the heritability provided a very good approximation of best linear unbiased prediction and was not accompanied with a loss in prediction accuracy. We conclude that prediction accuracy assessed with cross validation within one cycle of a breeding program can not be used as an indicator for the accuracy of predicting lines of the next cycle. Prediction of lines of the next cycle seems promising for traits with high heritabilities.

Classification based upon gene expression data: bias and precision of error rates.

PubMed

Wood, Ian A; Visscher, Peter M; Mengersen, Kerrie L

2007-06-01

Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean. Reporting an optimal estimated error rate incurs an optimization bias. Downward bias of 3-5% was found in an existing study of classification based on gene expression data and may be endemic in similar studies. Using a simulated non-informative dataset and two example datasets from existing studies, we show how bias can be detected through the use of label permutations and avoided using two-level external cross-validation. Some studies avoid optimization bias by using single-level cross-validation and a test set, but error rates can be more accurately estimated via two-level cross-validation. In addition to estimating the simple overall error rate, we recommend reporting class error rates plus where possible the conditional risk incorporating prior class probabilities and a misclassification cost matrix. We also describe baseline error rates derived from three trivial classifiers which ignore the predictors. R code which implements two-level external cross-validation with the PAMR package, experiment code, dataset details and additional figures are freely available for non-commercial use from http://www.maths.qut.edu.au/profiles/wood/permr.jsp

SU-E-T-129: Are Knowledge-Based Planning Dose Estimates Valid for Distensible Organs?

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

Lalonde, R; Heron, D; Huq, M

2015-06-15

Purpose: Knowledge-based planning programs have become available to assist treatment planning in radiation therapy. Such programs can be used to generate estimated DVHs and planning constraints for organs at risk (OARs), based upon a model generated from previous plans. These estimates are based upon the planning CT scan. However, for distensible OARs like the bladder and rectum, daily variations in volume may make the dose estimates invalid. The purpose of this study is to determine whether knowledge-based DVH dose estimates may be valid for distensible OARs. Methods: The Varian RapidPlan™ knowledge-based planning module was used to generate OAR dose estimatesmore » and planning objectives for 10 prostate cases previously planned with VMAT, and final plans were calculated for each. Five weekly setup CBCT scans of each patient were then downloaded and contoured (assuming no change in size and shape of the target volume), and rectum and bladder DVHs were recalculated for each scan. Dose volumes were then compared at 75, 60,and 40 Gy for the bladder and rectum between the planning scan and the CBCTs. Results: Plan doses and estimates matched well at all dose points., Volumes of the rectum and bladder varied widely between planning CT and the CBCTs, ranging from 0.46 to 2.42 for the bladder and 0.71 to 2.18 for the rectum, causing relative dose volumes to vary between planning CT and CBCT, but absolute dose volumes were more consistent. The overall ratio of CBCT/plan dose volumes was 1.02 ±0.27 for rectum and 0.98 ±0.20 for bladder in these patients. Conclusion: Knowledge-based planning dose volume estimates for distensible OARs are still valid, in absolute volume terms, between treatment planning scans and CBCT’s taken during daily treatment. Further analysis of the data is being undertaken to determine how differences depend upon rectum and bladder filling state. This work has been supported by Varian Medical Systems.« less

A Bayesian Approach to Determination of F, D, and Z Values Used in Steam Sterilization Validation.

PubMed

Faya, Paul; Stamey, James D; Seaman, John W

2017-01-01

For manufacturers of sterile drug products, steam sterilization is a common method used to provide assurance of the sterility of manufacturing equipment and products. The validation of sterilization processes is a regulatory requirement and relies upon the estimation of key resistance parameters of microorganisms. Traditional methods have relied upon point estimates for the resistance parameters. In this paper, we propose a Bayesian method for estimation of the well-known D T , z , and F o values that are used in the development and validation of sterilization processes. A Bayesian approach allows the uncertainty about these values to be modeled using probability distributions, thereby providing a fully risk-based approach to measures of sterility assurance. An example is given using the survivor curve and fraction negative methods for estimation of resistance parameters, and we present a means by which a probabilistic conclusion can be made regarding the ability of a process to achieve a specified sterility criterion. LAY ABSTRACT: For manufacturers of sterile drug products, steam sterilization is a common method used to provide assurance of the sterility of manufacturing equipment and products. The validation of sterilization processes is a regulatory requirement and relies upon the estimation of key resistance parameters of microorganisms. Traditional methods have relied upon point estimates for the resistance parameters. In this paper, we propose a Bayesian method for estimation of the critical process parameters that are evaluated in the development and validation of sterilization processes. A Bayesian approach allows the uncertainty about these parameters to be modeled using probability distributions, thereby providing a fully risk-based approach to measures of sterility assurance. An example is given using the survivor curve and fraction negative methods for estimation of resistance parameters, and we present a means by which a probabilistic conclusion can be made regarding the ability of a process to achieve a specified sterility criterion. © PDA, Inc. 2017.

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

NASA Astrophysics Data System (ADS)

Guo, T. H.; Musgrave, J.

1992-11-01

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Musgrave, J.

1992-01-01

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

Using multi-source satellite data for lake level modelling in ungauged basins: A case study for Lake Turkana, East Africa

USGS Publications Warehouse

Velpuri, N.M.; Senay, G.B.; Asante, K.O.

2011-01-01

Managing limited surface water resources is a great challenge in areas where ground-based data are either limited or unavailable. Direct or indirect measurements of surface water resources through remote sensing offer several advantages of monitoring in ungauged basins. A physical based hydrologic technique to monitor lake water levels in ungauged basins using multi-source satellite data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, a digital elevation model, and other data is presented. This approach is applied to model Lake Turkana water levels from 1998 to 2009. Modelling results showed that the model can reasonably capture all the patterns and seasonal variations of the lake water level fluctuations. A composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data is used for model calibration (1998-2000) and model validation (2001-2009). Validation results showed that model-based lake levels are in good agreement with observed satellite altimetry data. Compared to satellite altimetry data, the Pearson's correlation coefficient was found to be 0.81 during the validation period. The model efficiency estimated using NSCE is found to be 0.93, 0.55 and 0.66 for calibration, validation and combined periods, respectively. Further, the model-based estimates showed a root mean square error of 0.62 m and mean absolute error of 0.46 m with a positive mean bias error of 0.36 m for the validation period (2001-2009). These error estimates were found to be less than 15 % of the natural variability of the lake, thus giving high confidence on the modelled lake level estimates. The approach presented in this paper can be used to (a) simulate patterns of lake water level variations in data scarce regions, (b) operationally monitor lake water levels in ungauged basins, (c) derive historical lake level information using satellite rainfall and evapotranspiration data, and (d) augment the information provided by the satellite altimetry systems on changes in lake water levels. ?? Author(s) 2011.

Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

NASA Astrophysics Data System (ADS)

Hamzeh, S.; Naseri, A. A.; AlaviPanah, S. K.; Mojaradi, B.; Bartholomeus, H. M.; Clevers, J. G. P. W.; Behzad, M.

2013-04-01

The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.

Modeling and validating the cost and clinical pathway of colorectal cancer.

PubMed

Joranger, Paal; Nesbakken, Arild; Hoff, Geir; Sorbye, Halfdan; Oshaug, Arne; Aas, Eline

2015-02-01

Cancer is a major cause of morbidity and mortality, and colorectal cancer (CRC) is the third most common cancer in the world. The estimated costs of CRC treatment vary considerably, and if CRC costs in a model are based on empirically estimated total costs of stage I, II, III, or IV treatments, then they lack some flexibility to capture future changes in CRC treatment. The purpose was 1) to describe how to model CRC costs and survival and 2) to validate the model in a transparent and reproducible way. We applied a semi-Markov model with 70 health states and tracked age and time since specific health states (using tunnels and 3-dimensional data matrix). The model parameters are based on an observational study at Oslo University Hospital (2049 CRC patients), the National Patient Register, literature, and expert opinion. The target population was patients diagnosed with CRC. The model followed the patients diagnosed with CRC from the age of 70 until death or 100 years. The study focused on the perspective of health care payers. The model was validated for face validity, internal and external validity, and cross-validity. The validation showed a satisfactory match with other models and empirical estimates for both cost and survival time, without any preceding calibration of the model. The model can be used to 1) address a range of CRC-related themes (general model) like survival and evaluation of the cost of treatment and prevention measures; 2) make predictions from intermediate to final outcomes; 3) estimate changes in resource use and costs due to changing guidelines; and 4) adjust for future changes in treatment and trends over time. The model is adaptable to other populations. © The Author(s) 2014.

Task based exposure assessment in ergonomic epidemiology: a study of upper arm elevation in the jobs of machinists, car mechanics, and house painters

PubMed Central

Svendsen, S; Mathiassen, S; Bonde, J

2005-01-01

Aims: To explore the precision of task based estimates of upper arm elevation in three occupational groups, compared to direct measurements of job exposure. Methods: Male machinists (n = 26), car mechanics (n = 23), and house painters (n = 23) were studied. Whole day recordings of upper arm elevation were obtained for four consecutive working days, and associated task information was collected in diaries. For each individual, task based estimates of job exposure were calculated by weighting task exposures from a collective database by task proportions according to the diaries. These estimates were validated against directly measured job exposures using linear regression. The performance of the task based approach was expressed through the gain in precision of occupational group mean exposures that could be obtained by adding subjects with task based estimates to a group of subjects with measured job exposures in a "validation" design. Results: In all three occupations, tasks differed in mean exposure, and task proportions varied between individuals. Task based estimation proved inefficient, with squared correlation coefficients only occasionally exceeding 0.2 for the relation between task based and measured job exposures. Consequently, it was not possible to substantially improve the precision of an estimated group mean by including subjects whose job exposures were based on task information. Conclusions: Task based estimates of mechanical job exposure can be very imprecise, and only marginally better than estimates based on occupation. It is recommended that investigators in ergonomic epidemiology consider the prospects of task based exposure assessment carefully before placing resources at obtaining task information. Strategies disregarding tasks may be preferable in many cases. PMID:15613604

Flight data acquisition methodology for validation of passive ranging algorithms for obstacle avoidance

NASA Technical Reports Server (NTRS)

Smith, Phillip N.

1990-01-01

The automation of low-altitude rotorcraft flight depends on the ability to detect, locate, and navigate around obstacles lying in the rotorcraft's intended flightpath. Computer vision techniques provide a passive method of obstacle detection and range estimation, for obstacle avoidance. Several algorithms based on computer vision methods have been developed for this purpose using laboratory data; however, further development and validation of candidate algorithms require data collected from rotorcraft flight. A data base containing low-altitude imagery augmented with the rotorcraft and sensor parameters required for passive range estimation is not readily available. Here, the emphasis is on the methodology used to develop such a data base from flight-test data consisting of imagery, rotorcraft and sensor parameters, and ground-truth range measurements. As part of the data preparation, a technique for obtaining the sensor calibration parameters is described. The data base will enable the further development of algorithms for computer vision-based obstacle detection and passive range estimation, as well as provide a benchmark for verification of range estimates against ground-truth measurements.

Evaluation of TRMM Ground-Validation Radar-Rain Errors Using Rain Gauge Measurements

NASA Technical Reports Server (NTRS)

Wang, Jianxin; Wolff, David B.

2009-01-01

Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) spaced-based rain estimates, and hence, quantitative evaluation of the GV radar-rain product error characteristics is vital. This study uses quality-controlled gauge data to compare with TRMM GV radar rain rates in an effort to provide such error characteristics. The results show that significant differences of concurrent radar-gauge rain rates exist at various time scales ranging from 5 min to 1 day, despite lower overall long-term bias. However, the differences between the radar area-averaged rain rates and gauge point rain rates cannot be explained as due to radar error only. The error variance separation method is adapted to partition the variance of radar-gauge differences into the gauge area-point error variance and radar rain estimation error variance. The results provide relatively reliable quantitative uncertainty evaluation of TRMM GV radar rain estimates at various times scales, and are helpful to better understand the differences between measured radar and gauge rain rates. It is envisaged that this study will contribute to better utilization of GV radar rain products to validate versatile spaced-based rain estimates from TRMM, as well as the proposed Global Precipitation Measurement, and other satellites.

Derivation and validation of simple anthropometric equations to predict adipose tissue mass and total fat mass with MRI as the reference method

PubMed Central

Al-Gindan, Yasmin Y.; Hankey, Catherine R.; Govan, Lindsay; Gallagher, Dympna; Heymsfield, Steven B.; Lean, Michael E. J.

2017-01-01

The reference organ-level body composition measurement method is MRI. Practical estimations of total adipose tissue mass (TATM), total adipose tissue fat mass (TATFM) and total body fat are valuable for epidemiology, but validated prediction equations based on MRI are not currently available. We aimed to derive and validate new anthropometric equations to estimate MRI-measured TATM/TATFM/total body fat and compare them with existing prediction equations using older methods. The derivation sample included 416 participants (222 women), aged between 18 and 88 years with BMI between 15·9 and 40·8 (kg/m2). The validation sample included 204 participants (110 women), aged between 18 and 86 years with BMI between 15·7 and 36·4 (kg/m2). Both samples included mixed ethnic/racial groups. All the participants underwent whole-body MRI to quantify TATM (dependent variable) and anthropometry (independent variables). Prediction equations developed using stepwise multiple regression were further investigated for agreement and bias before validation in separate data sets. Simplest equations with optimal R2 and Bland–Altman plots demonstrated good agreement without bias in the validation analyses: men: TATM (kg) = 0·198 weight (kg) + 0·478 waist (cm) − 0·147 height (cm) − 12·8 (validation: R2 0·79, CV = 20 %, standard error of the estimate (SEE)=3·8 kg) and women: TATM (kg)=0·789 weight (kg) + 0·0786 age (years) − 0·342 height (cm) + 24·5 (validation: R2 0·84, CV = 13 %, SEE = 3·0 kg). Published anthropometric prediction equations, based on MRI and computed tomographic scans, correlated strongly with MRI-measured TATM: (R2 0·70 – 0·82). Estimated TATFM correlated well with published prediction equations for total body fat based on underwater weighing (R2 0·70–0·80), with mean bias of 2·5–4·9 kg, correctable with log-transformation in most equations. In conclusion, new equations, using simple anthropometric measurements, estimated MRI-measured TATM with correlations and agreements suitable for use in groups and populations across a wide range of fatness. PMID:26435103

Application of the Combination Approach for Estimating Evapotranspiration in Puerto Rico

NASA Technical Reports Server (NTRS)

Harmsen, Eric; Luvall, Jeffrey; Gonzalez, Jorge

2005-01-01

The ability to estimate short-term fluxes of water vapor from the land surface is important for validating latent heat flux estimates from high resolution remote sensing techniques. A new, relatively inexpensive method is presented for estimating t h e ground-based values of the surface latent heat flux or evapotranspiration.

On using sample selection methods in estimating the price elasticity of firms' demand for insurance.

PubMed

Marquis, M Susan; Louis, Thomas A

2002-01-01

We evaluate a technique based on sample selection models that has been used by health economists to estimate the price elasticity of firms' demand for insurance. We demonstrate that, this technique produces inflated estimates of the price elasticity. We show that alternative methods lead to valid estimates.

METAPHOR: Probability density estimation for machine learning based photometric redshifts

NASA Astrophysics Data System (ADS)

Amaro, V.; Cavuoti, S.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.

2017-06-01

We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method able to provide a reliable PDF for photometric galaxy redshifts estimated through empirical techniques. METAPHOR is a modular workflow, mainly based on the MLPQNA neural network as internal engine to derive photometric galaxy redshifts, but giving the possibility to easily replace MLPQNA with any other method to predict photo-z's and their PDF. We present here the results about a validation test of the workflow on the galaxies from SDSS-DR9, showing also the universality of the method by replacing MLPQNA with KNN and Random Forest models. The validation test include also a comparison with the PDF's derived from a traditional SED template fitting method (Le Phare).

Optically-derived estimates of phytoplankton size class and taxonomic group biomass in the Eastern Subarctic Pacific Ocean

NASA Astrophysics Data System (ADS)

Zeng, Chen; Rosengard, Sarah Z.; Burt, William; Peña, M. Angelica; Nemcek, Nina; Zeng, Tao; Arrigo, Kevin R.; Tortell, Philippe D.

2018-06-01

We evaluate several algorithms for the estimation of phytoplankton size class (PSC) and functional type (PFT) biomass from ship-based optical measurements in the Subarctic Northeast Pacific Ocean. Using underway measurements of particulate absorption and backscatter in surface waters, we derived estimates of PSC/PFT based on chlorophyll-a concentrations (Chl-a), particulate absorption spectra and the wavelength dependence of particulate backscatter. Optically-derived [Chl-a] and phytoplankton absorption measurements were validated against discrete calibration samples, while the derived PSC/PFT estimates were validated using size-fractionated Chl-a measurements and HPLC analysis of diagnostic photosynthetic pigments (DPA). Our results showflo that PSC/PFT algorithms based on [Chl-a] and particulate absorption spectra performed significantly better than the backscatter slope approach. These two more successful algorithms yielded estimates of phytoplankton size classes that agreed well with HPLC-derived DPA estimates (RMSE = 12.9%, and 16.6%, respectively) across a range of hydrographic and productivity regimes. Moreover, the [Chl-a] algorithm produced PSC estimates that agreed well with size-fractionated [Chl-a] measurements, and estimates of the biomass of specific phytoplankton groups that were consistent with values derived from HPLC. Based on these results, we suggest that simple [Chl-a] measurements should be more fully exploited to improve the classification of phytoplankton assemblages in the Northeast Pacific Ocean.

The Reliability and Validity of Salivation as a Measure of Individual Differences in Intrinsic Arousal. Report from the Project on Motivation and Individual Differences in Learning and Retention.

ERIC Educational Resources Information Center

Farley, Frank H.; And Others

Two studies were reported which attempted to estimate the stability and construct validity of human salivary response as a measure of individual differences (IDs) in physiological arousal. Twenty-second base line estimates and 20-second response levels to four drops of lemon juice were measured, with the former value being removed from the latter…

On the validity of within-nuclear-family genetic association analysis in samples of extended families.

PubMed

Bureau, Alexandre; Duchesne, Thierry

2015-12-01

Splitting extended families into their component nuclear families to apply a genetic association method designed for nuclear families is a widespread practice in familial genetic studies. Dependence among genotypes and phenotypes of nuclear families from the same extended family arises because of genetic linkage of the tested marker with a risk variant or because of familial specificity of genetic effects due to gene-environment interaction. This raises concerns about the validity of inference conducted under the assumption of independence of the nuclear families. We indeed prove theoretically that, in a conditional logistic regression analysis applicable to disease cases and their genotyped parents, the naive model-based estimator of the variance of the coefficient estimates underestimates the true variance. However, simulations with realistic effect sizes of risk variants and variation of this effect from family to family reveal that the underestimation is negligible. The simulations also show the greater efficiency of the model-based variance estimator compared to a robust empirical estimator. Our recommendation is therefore, to use the model-based estimator of variance for inference on effects of genetic variants.

Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

NASA Astrophysics Data System (ADS)

Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

2018-01-01

Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

Confidence in outcome estimates from systematic reviews used in informed consent.

PubMed

Fritz, Robert; Bauer, Janet G; Spackman, Sue S; Bains, Amanjyot K; Jetton-Rangel, Jeanette

2016-12-01

Evidence-based dentistry now guides informed consent in which clinicians are obliged to provide patients with the most current, best evidence, or best estimates of outcomes, of regimens, therapies, treatments, procedures, materials, and equipment or devices when developing personal oral health care, treatment plans. Yet, clinicians require that the estimates provided from systematic reviews be verified to their validity, reliability, and contextualized as to performance competency so that clinicians may have confidence in explaining outcomes to patients in clinical practice. The purpose of this paper was to describe types of informed estimates from which clinicians may have confidence in their capacity to assist patients in competent decision-making, one of the most important concepts of informed consent. Using systematic review methodology, researchers provide clinicians with valid best estimates of outcomes regarding a subject of interest from best evidence. Best evidence is verified through critical appraisals using acceptable sampling methodology either by scoring instruments (Timmer analysis) or checklist (grade), a Cochrane Collaboration standard that allows transparency in open reviews. These valid best estimates are then tested for reliability using large databases. Finally, valid and reliable best estimates are assessed for meaning using quantification of margins and uncertainties. Through manufacturer and researcher specifications, quantification of margins and uncertainties develops a performance competency continuum by which valid, reliable best estimates may be contextualized for their performance competency: at a lowest margin performance competency (structural failure), high margin performance competency (estimated true value of success), or clinically determined critical values (clinical failure). Informed consent may be achieved when clinicians are confident of their ability to provide useful and accurate best estimates of outcomes regarding regimens, therapies, treatments, and equipment or devices to patients in their clinical practices and when developing personal, oral health care, treatment plans. Copyright © 2016 Elsevier Inc. All rights reserved.

Development of a Reference Data Set (RDS) for dental age estimation (DAE) and testing of this with a separate Validation Set (VS) in a southern Chinese population.

PubMed

Jayaraman, Jayakumar; Wong, Hai Ming; King, Nigel M; Roberts, Graham J

2016-10-01

Many countries have recently experienced a rapid increase in the demand for forensic age estimates of unaccompanied minors. Hong Kong is a major tourist and business center where there has been an increase in the number of people intercepted with false travel documents. An accurate estimation of age is only possible when a dataset for age estimation that has been derived from the corresponding ethnic population. Thus, the aim of this study was to develop and validate a Reference Data Set (RDS) for dental age estimation for southern Chinese. A total of 2306 subjects were selected from the patient archives of a large dental hospital and the chronological age for each subject was recorded. This age was assigned to each specific stage of dental development for each tooth to create a RDS. To validate this RDS, a further 484 subjects were randomly chosen from the patient archives and their dental age was assessed based on the scores from the RDS. Dental age was estimated using meta-analysis command corresponding to random effects statistical model. Chronological age (CA) and Dental Age (DA) were compared using the paired t-test. The overall difference between the chronological and dental age (CA-DA) was 0.05 years (2.6 weeks) for males and 0.03 years (1.6 weeks) for females. The paired t-test indicated that there was no statistically significant difference between the chronological and dental age (p > 0.05). The validated southern Chinese reference dataset based on dental maturation accurately estimated the chronological age. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Estimate of the uncertainty in measurement for the determination of mercury in seafood by TDA AAS.

PubMed

Torres, Daiane Placido; Olivares, Igor R B; Queiroz, Helena Müller

2015-01-01

An approach for the estimate of the uncertainty in measurement considering the individual sources related to the different steps of the method under evaluation as well as the uncertainties estimated from the validation data for the determination of mercury in seafood by using thermal decomposition/amalgamation atomic absorption spectrometry (TDA AAS) is proposed. The considered method has been fully optimized and validated in an official laboratory of the Ministry of Agriculture, Livestock and Food Supply of Brazil, in order to comply with national and international food regulations and quality assurance. The referred method has been accredited under the ISO/IEC 17025 norm since 2010. The approach of the present work in order to reach the aim of estimating of the uncertainty in measurement was based on six sources of uncertainty for mercury determination in seafood by TDA AAS, following the validation process, which were: Linear least square regression, Repeatability, Intermediate precision, Correction factor of the analytical curve, Sample mass, and Standard reference solution. Those that most influenced the uncertainty in measurement were sample weight, repeatability, intermediate precision and calibration curve. The obtained result for the estimate of uncertainty in measurement in the present work reached a value of 13.39%, which complies with the European Regulation EC 836/2011. This figure represents a very realistic estimate of the routine conditions, since it fairly encompasses the dispersion obtained from the value attributed to the sample and the value measured by the laboratory analysts. From this outcome, it is possible to infer that the validation data (based on calibration curve, recovery and precision), together with the variation on sample mass, can offer a proper estimate of uncertainty in measurement.

Estimating and validating harvesting system production through computer simulation

Treesearch

John E. Baumgras; Curt C. Hassler; Chris B. LeDoux

1993-01-01

A Ground Based Harvesting System Simulation model (GB-SIM) has been developed to estimate stump-to-truck production rates and multiproduct yields for conventional ground-based timber harvesting systems in Appalachian hardwood stands. Simulation results reflect inputs that define harvest site and timber stand attributes, wood utilization options, and key attributes of...

Novel Equations for Estimating Lean Body Mass in Peritoneal Dialysis Patients

PubMed Central

Dong, Jie; Li, Yan-Jun; Xu, Rong; Yang, Zhi-Kai; Zheng, Ying-Dong

2015-01-01

♦ Objectives: To develop and validate equations for estimating lean body mass (LBM) in peritoneal dialysis (PD) patients. ♦ Methods: Two equations for estimating LBM, one based on mid-arm muscle circumference (MAMC) and hand grip strength (HGS), i.e., LBM-M-H, and the other based on HGS, i.e., LBM-H, were developed and validated with LBM obtained by dual-energy X-ray absorptiometry (DEXA). The developed equations were compared to LBM estimated from creatinine kinetics (LBM-CK) and anthropometry (LBM-A) in terms of bias, precision, and accuracy. The prognostic values of LBM estimated from the equations in all-cause mortality risk were assessed. ♦ Results: The developed equations incorporated gender, height, weight, and dialysis duration. Compared to LBM-DEXA, the bias of the developed equations was lower than that of LBM-CK and LBM-A. Additionally, LBM-M-H and LBM-H had better accuracy and precision. The prognostic values of LBM in all-cause mortality risk based on LBM-M-H, LBM-H, LBM-CK, and LBM-A were similar. ♦ Conclusions: Lean body mass estimated by the new equations based on MAMC and HGS was correlated with LBM obtained by DEXA and may serve as practical surrogate markers of LBM in PD patients. PMID:26293839

Novel Equations for Estimating Lean Body Mass in Peritoneal Dialysis Patients.

PubMed

Dong, Jie; Li, Yan-Jun; Xu, Rong; Yang, Zhi-Kai; Zheng, Ying-Dong

2015-12-01

♦ To develop and validate equations for estimating lean body mass (LBM) in peritoneal dialysis (PD) patients. ♦ Two equations for estimating LBM, one based on mid-arm muscle circumference (MAMC) and hand grip strength (HGS), i.e., LBM-M-H, and the other based on HGS, i.e., LBM-H, were developed and validated with LBM obtained by dual-energy X-ray absorptiometry (DEXA). The developed equations were compared to LBM estimated from creatinine kinetics (LBM-CK) and anthropometry (LBM-A) in terms of bias, precision, and accuracy. The prognostic values of LBM estimated from the equations in all-cause mortality risk were assessed. ♦ The developed equations incorporated gender, height, weight, and dialysis duration. Compared to LBM-DEXA, the bias of the developed equations was lower than that of LBM-CK and LBM-A. Additionally, LBM-M-H and LBM-H had better accuracy and precision. The prognostic values of LBM in all-cause mortality risk based on LBM-M-H, LBM-H, LBM-CK, and LBM-A were similar. ♦ Lean body mass estimated by the new equations based on MAMC and HGS was correlated with LBM obtained by DEXA and may serve as practical surrogate markers of LBM in PD patients. Copyright © 2015 International Society for Peritoneal Dialysis.

Validation of an aggregate exposure model for substances in consumer products: a case study of diethyl phthalate in personal care products

PubMed Central

Delmaar, Christiaan; Bokkers, Bas; ter Burg, Wouter; Schuur, Gerlienke

2015-01-01

As personal care products (PCPs) are used in close contact with a person, they are a major source of consumer exposure to chemical substances contained in these products. The estimation of realistic consumer exposure to substances in PCPs is currently hampered by the lack of appropriate data and methods. To estimate aggregate exposure of consumers to substances contained in PCPs, a person-oriented consumer exposure model has been developed (the Probabilistic Aggregate Consumer Exposure Model, PACEM). The model simulates daily exposure in a population based on product use data collected from a survey among the Dutch population. The model is validated by comparing diethyl phthalate (DEP) dose estimates to dose estimates based on biomonitoring data. It was found that the model's estimates compared well with the estimates based on biomonitoring data. This suggests that the person-oriented PACEM model is a practical tool for assessing realistic aggregate exposures to substances in PCPs. In the future, PACEM will be extended with use pattern data on other product groups. This will allow for assessing aggregate exposure to substances in consumer products across different product groups. PMID:25352161

OLYMPEX Data Workshop: GPM View

NASA Technical Reports Server (NTRS)

Petersen, W.

2017-01-01

OLYMPEX Primary Objectives: Datasets to enable: (1) Direct validation over complex terrain at multiple scales, liquid and frozen precip types, (a) Do we capture terrain and synoptic regime transitions, orographic enhancements/structure, full range of precipitation intensity (e.g., very light to heavy) and types, spatial variability? (b) How well can we estimate space/time-accumulated precipitation over terrain (liquid + frozen)? (2) Physical validation of algorithms in mid-latitude cold season frontal systems over ocean and complex terrain, (a) What are the column properties of frozen, melting, liquid hydrometeors-their relative contributions to estimated surface precipitation, transition under the influence of terrain gradients, and systematic variability as a function of synoptic regime? (3) Integrated hydrologic validation in complex terrain, (a) Can satellite estimates be combined with modeling over complex topography to drive improved products (assimilation, downscaling) [Level IV products] (b) What are capabilities and limitations for use of satellite-based precipitation estimates in stream/river flow forecasting?

Validating a biometric authentication system: sample size requirements.

PubMed

Dass, Sarat C; Zhu, Yongfang; Jain, Anil K

2006-12-01

Authentication systems based on biometric features (e.g., fingerprint impressions, iris scans, human face images, etc.) are increasingly gaining widespread use and popularity. Often, vendors and owners of these commercial biometric systems claim impressive performance that is estimated based on some proprietary data. In such situations, there is a need to independently validate the claimed performance levels. System performance is typically evaluated by collecting biometric templates from n different subjects, and for convenience, acquiring multiple instances of the biometric for each of the n subjects. Very little work has been done in 1) constructing confidence regions based on the ROC curve for validating the claimed performance levels and 2) determining the required number of biometric samples needed to establish confidence regions of prespecified width for the ROC curve. To simplify the analysis that address these two problems, several previous studies have assumed that multiple acquisitions of the biometric entity are statistically independent. This assumption is too restrictive and is generally not valid. We have developed a validation technique based on multivariate copula models for correlated biometric acquisitions. Based on the same model, we also determine the minimum number of samples required to achieve confidence bands of desired width for the ROC curve. We illustrate the estimation of the confidence bands as well as the required number of biometric samples using a fingerprint matching system that is applied on samples collected from a small population.

Fetal QRS detection and heart rate estimation: a wavelet-based approach.

PubMed

Almeida, Rute; Gonçalves, Hernâni; Bernardes, João; Rocha, Ana Paula

2014-08-01

Fetal heart rate monitoring is used for pregnancy surveillance in obstetric units all over the world but in spite of recent advances in analysis methods, there are still inherent technical limitations that bound its contribution to the improvement of perinatal indicators. In this work, a previously published wavelet transform based QRS detector, validated over standard electrocardiogram (ECG) databases, is adapted to fetal QRS detection over abdominal fetal ECG. Maternal ECG waves were first located using the original detector and afterwards a version with parameters adapted for fetal physiology was applied to detect fetal QRS, excluding signal singularities associated with maternal heartbeats. Single lead (SL) based marks were combined in a single annotator with post processing rules (SLR) from which fetal RR and fetal heart rate (FHR) measures can be computed. Data from PhysioNet with reference fetal QRS locations was considered for validation, with SLR outperforming SL including ICA based detections. The error in estimated FHR using SLR was lower than 20 bpm for more than 80% of the processed files. The median error in 1 min based FHR estimation was 0.13 bpm, with a correlation between reference and estimated FHR of 0.48, which increased to 0.73 when considering only records for which estimated FHR > 110 bpm. This allows us to conclude that the proposed methodology is able to provide a clinically useful estimation of the FHR.

Validation analysis of probabilistic models of dietary exposure to food additives.

PubMed

Gilsenan, M B; Thompson, R L; Lambe, J; Gibney, M J

2003-10-01

The validity of a range of simple conceptual models designed specifically for the estimation of food additive intakes using probabilistic analysis was assessed. Modelled intake estimates that fell below traditional conservative point estimates of intake and above 'true' additive intakes (calculated from a reference database at brand level) were considered to be in a valid region. Models were developed for 10 food additives by combining food intake data, the probability of an additive being present in a food group and additive concentration data. Food intake and additive concentration data were entered as raw data or as a lognormal distribution, and the probability of an additive being present was entered based on the per cent brands or the per cent eating occasions within a food group that contained an additive. Since the three model components assumed two possible modes of input, the validity of eight (2(3)) model combinations was assessed. All model inputs were derived from the reference database. An iterative approach was employed in which the validity of individual model components was assessed first, followed by validation of full conceptual models. While the distribution of intake estimates from models fell below conservative intakes, which assume that the additive is present at maximum permitted levels (MPLs) in all foods in which it is permitted, intake estimates were not consistently above 'true' intakes. These analyses indicate the need for more complex models for the estimation of food additive intakes using probabilistic analysis. Such models should incorporate information on market share and/or brand loyalty.

Validity of eyeball estimation for range of motion during the cervical flexion rotation test compared to an ultrasound-based movement analysis system.

PubMed

Schäfer, Axel; Lüdtke, Kerstin; Breuel, Franziska; Gerloff, Nikolas; Knust, Maren; Kollitsch, Christian; Laukart, Alex; Matej, Laura; Müller, Antje; Schöttker-Königer, Thomas; Hall, Toby

2018-08-01

Headache is a common and costly health problem. Although pathogenesis of headache is heterogeneous, one reported contributing factor is dysfunction of the upper cervical spine. The flexion rotation test (FRT) is a commonly used diagnostic test to detect upper cervical movement impairment. The aim of this cross-sectional study was to investigate concurrent validity of detecting high cervical ROM impairment during the FRT by comparing measurements established by an ultrasound-based system (gold standard) with eyeball estimation. Secondary aim was to investigate intra-rater reliability of FRT ROM eyeball estimation. The examiner (6 years experience) was blinded to the data from the ultrasound-based device and to the symptoms of the patients. FRT test result (positive or negative) was based on visual estimation of range of rotation less than 34° to either side. Concurrently, range of rotation was evaluated using the ultrasound-based device. A total of 43 subjects with headache (79% female), mean age of 35.05 years (SD 13.26) were included. According to the International Headache Society Classification 23 subjects had migraine, 4 tension type headache, and 16 multiple headache forms. Sensitivity and specificity were 0.96 and 0.89 for combined rotation, indicating good concurrent reliability. The area under the ROC curve was 0.95 (95% CI 0.91-0.98) for rotation to both sides. Intra-rater reliability for eyeball estimation was excellent with Fleiss Kappa 0.79 for right rotation and left rotation. The results of this study indicate that the FRT is a valid and reliable test to detect impairment of upper cervical ROM in patients with headache.

Testing the convergent validity of the contingent valuation and travel cost methods in valuing the benefits of health care.

PubMed

Clarke, Philip M

2002-03-01

In this study, the convergent validity of the contingent valuation method (CVM) and travel cost method (TCM) is tested by comparing estimates of the willingness to pay (WTP) for improving access to mammographic screening in rural areas of Australia. It is based on a telephone survey of 458 women in 19 towns, in which they were asked about their recent screening behaviour and their WTP to have a mobile screening unit visit their nearest town. After eliminating missing data and other non-usable responses the contingent valuation experiment and travel cost model were based on information from 372 and 319 women, respectively. Estimates of the maximum WTP for the use of mobile screening units were derived using both methods and compared. The highest mean WTP estimated using the TCM was $83.10 (95% C.I. $99.06-$68.53), which is significantly less than the estimate of $148.09 ($131.13-$166.60) using the CVM. This could be due to the CVM estimates also reflecting non-use values such as altruism, or a range of potential biases that are known to affect both methods. Further tests of validity are required in order to gain a greater understanding of the relationship between these two methods of estimating WTP. Copyright 2001 John Wiley & Sons, Ltd.

Joint Estimation of Time-Frequency Signature and DOA Based on STFD for Multicomponent Chirp Signals

PubMed Central

Zhao, Ziyue; Liu, Congfeng

2014-01-01

In the study of the joint estimation of time-frequency signature and direction of arrival (DOA) for multicomponent chirp signals, an estimation method based on spatial time-frequency distributions (STFDs) is proposed in this paper. Firstly, array signal model for multicomponent chirp signals is presented and then array processing is applied in time-frequency analysis to mitigate cross-terms. According to the results of the array processing, Hough transform is performed and the estimation of time-frequency signature is obtained. Subsequently, subspace method for DOA estimation based on STFD matrix is achieved. Simulation results demonstrate the validity of the proposed method. PMID:27382610

Joint Estimation of Time-Frequency Signature and DOA Based on STFD for Multicomponent Chirp Signals.

PubMed

Zhao, Ziyue; Liu, Congfeng

2014-01-01

In the study of the joint estimation of time-frequency signature and direction of arrival (DOA) for multicomponent chirp signals, an estimation method based on spatial time-frequency distributions (STFDs) is proposed in this paper. Firstly, array signal model for multicomponent chirp signals is presented and then array processing is applied in time-frequency analysis to mitigate cross-terms. According to the results of the array processing, Hough transform is performed and the estimation of time-frequency signature is obtained. Subsequently, subspace method for DOA estimation based on STFD matrix is achieved. Simulation results demonstrate the validity of the proposed method.

Estimation of AUC or Partial AUC under Test-Result-Dependent Sampling.

PubMed

Wang, Xiaofei; Ma, Junling; George, Stephen; Zhou, Haibo

2012-01-01

The area under the ROC curve (AUC) and partial area under the ROC curve (pAUC) are summary measures used to assess the accuracy of a biomarker in discriminating true disease status. The standard sampling approach used in biomarker validation studies is often inefficient and costly, especially when ascertaining the true disease status is costly and invasive. To improve efficiency and reduce the cost of biomarker validation studies, we consider a test-result-dependent sampling (TDS) scheme, in which subject selection for determining the disease state is dependent on the result of a biomarker assay. We first estimate the test-result distribution using data arising from the TDS design. With the estimated empirical test-result distribution, we propose consistent nonparametric estimators for AUC and pAUC and establish the asymptotic properties of the proposed estimators. Simulation studies show that the proposed estimators have good finite sample properties and that the TDS design yields more efficient AUC and pAUC estimates than a simple random sampling (SRS) design. A data example based on an ongoing cancer clinical trial is provided to illustrate the TDS design and the proposed estimators. This work can find broad applications in design and analysis of biomarker validation studies.

Development and validation of a melanoma risk score based on pooled data from 16 case-control studies

PubMed Central

Davies, John R; Chang, Yu-mei; Bishop, D Timothy; Armstrong, Bruce K; Bataille, Veronique; Bergman, Wilma; Berwick, Marianne; Bracci, Paige M; Elwood, J Mark; Ernstoff, Marc S; Green, Adele; Gruis, Nelleke A; Holly, Elizabeth A; Ingvar, Christian; Kanetsky, Peter A; Karagas, Margaret R; Lee, Tim K; Le Marchand, Loïc; Mackie, Rona M; Olsson, Håkan; Østerlind, Anne; Rebbeck, Timothy R; Reich, Kristian; Sasieni, Peter; Siskind, Victor; Swerdlow, Anthony J; Titus, Linda; Zens, Michael S; Ziegler, Andreas; Gallagher, Richard P.; Barrett, Jennifer H; Newton-Bishop, Julia

2015-01-01

Background We report the development of a cutaneous melanoma risk algorithm based upon 7 factors; hair colour, skin type, family history, freckling, nevus count, number of large nevi and history of sunburn, intended to form the basis of a self-assessment webtool for the general public. Methods Predicted odds of melanoma were estimated by analysing a pooled dataset from 16 case-control studies using logistic random coefficients models. Risk categories were defined based on the distribution of the predicted odds in the controls from these studies. Imputation was used to estimate missing data in the pooled datasets. The 30th, 60th and 90th centiles were used to distribute individuals into four risk groups for their age, sex and geographic location. Cross-validation was used to test the robustness of the thresholds for each group by leaving out each study one by one. Performance of the model was assessed in an independent UK case-control study dataset. Results Cross-validation confirmed the robustness of the threshold estimates. Cases and controls were well discriminated in the independent dataset (area under the curve 0.75, 95% CI 0.73-0.78). 29% of cases were in the highest risk group compared with 7% of controls, and 43% of controls were in the lowest risk group compared with 13% of cases. Conclusion We have identified a composite score representing an estimate of relative risk and successfully validated this score in an independent dataset. Impact This score may be a useful tool to inform members of the public about their melanoma risk. PMID:25713022

Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values.

PubMed

McMillan, Kyle; Bostani, Maryam; Cagnon, Christopher H; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H; McNitt-Gray, Michael F

2017-08-01

The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose. Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating patient organ doses, Monte Carlo simulations were performed by creating voxelized models of each patient, identifying key organs and incorporating tube current values into the simulations to estimate dose to the lungs and breasts (females only) for chest scans and the liver, kidney, and spleen for abdomen/pelvis scans. Organ doses from simulations using the actual tube current values were compared to those using each of the estimated tube current values (actual-topo and sim-topo). When compared to the actual tube current values, the average error for tube current values estimated from the actual topogram (actual-topo) and simulated topogram (sim-topo) was 3.9% and 5.8% respectively. For Monte Carlo simulations of chest CT exams using the actual tube current values and estimated tube current values (based on the actual-topo and sim-topo methods), the average differences for lung and breast doses ranged from 3.4% to 6.6%. For abdomen/pelvis exams, the average differences for liver, kidney, and spleen doses ranged from 4.2% to 5.3%. Strong agreement between organ doses estimated using actual and estimated tube current values provides validation of both methods for estimating tube current values based on data provided in the topogram or simulated from image data. © 2017 American Association of Physicists in Medicine.

Modification of the random forest algorithm to avoid statistical dependence problems when classifying remote sensing imagery

NASA Astrophysics Data System (ADS)

Cánovas-García, Fulgencio; Alonso-Sarría, Francisco; Gomariz-Castillo, Francisco; Oñate-Valdivieso, Fernando

2017-06-01

Random forest is a classification technique widely used in remote sensing. One of its advantages is that it produces an estimation of classification accuracy based on the so called out-of-bag cross-validation method. It is usually assumed that such estimation is not biased and may be used instead of validation based on an external data-set or a cross-validation external to the algorithm. In this paper we show that this is not necessarily the case when classifying remote sensing imagery using training areas with several pixels or objects. According to our results, out-of-bag cross-validation clearly overestimates accuracy, both overall and per class. The reason is that, in a training patch, pixels or objects are not independent (from a statistical point of view) of each other; however, they are split by bootstrapping into in-bag and out-of-bag as if they were really independent. We believe that putting whole patch, rather than pixels/objects, in one or the other set would produce a less biased out-of-bag cross-validation. To deal with the problem, we propose a modification of the random forest algorithm to split training patches instead of the pixels (or objects) that compose them. This modified algorithm does not overestimate accuracy and has no lower predictive capability than the original. When its results are validated with an external data-set, the accuracy is not different from that obtained with the original algorithm. We analysed three remote sensing images with different classification approaches (pixel and object based); in the three cases reported, the modification we propose produces a less biased accuracy estimation.

Is self-reporting workplace activity worthwhile? Validity and reliability of occupational sitting and physical activity questionnaire in desk-based workers.

PubMed

Pedersen, Scott J; Kitic, Cecilia M; Bird, Marie-Louise; Mainsbridge, Casey P; Cooley, P Dean

2016-08-19

With the advent of workplace health and wellbeing programs designed to address prolonged occupational sitting, tools to measure behaviour change within this environment should derive from empirical evidence. In this study we measured aspects of validity and reliability for the Occupational Sitting and Physical Activity Questionnaire that asks employees to recount the percentage of work time they spend in the seated, standing, and walking postures during a typical workday. Three separate cohort samples (N = 236) were drawn from a population of government desk-based employees across several departmental agencies. These volunteers were part of a larger state-wide intervention study. Workplace sitting and physical activity behaviour was measured both subjectively against the International Physical Activity Questionnaire, and objectively against ActivPal accelerometers before the intervention began. Criterion validity and concurrent validity for each of the three posture categories were assessed using Spearman's rank correlation coefficients, and a bias comparison with 95 % limits of agreement. Test-retest reliability of the survey was reported with intraclass correlation coefficients. Criterion validity for this survey was strong for sitting and standing estimates, but weak for walking. Participants significantly overestimated the amount of walking they did at work. Concurrent validity was moderate for sitting and standing, but low for walking. Test-retest reliability of this survey proved to be questionable for our sample. Based on our findings we must caution occupational health and safety professionals about the use of employee self-report data to estimate workplace physical activity. While the survey produced accurate measurements for time spent sitting at work it was more difficult for employees to estimate their workplace physical activity.

Nomograms for predicting graft function and survival in living donor kidney transplantation based on the UNOS Registry.

PubMed

Tiong, H Y; Goldfarb, D A; Kattan, M W; Alster, J M; Thuita, L; Yu, C; Wee, A; Poggio, E D

2009-03-01

We developed nomograms that predict transplant renal function at 1 year (Modification of Diet in Renal Disease equation [estimated glomerular filtration rate]) and 5-year graft survival after living donor kidney transplantation. Data for living donor renal transplants were obtained from the United Network for Organ Sharing registry for 2000 to 2003. Nomograms were designed using linear or Cox regression models to predict 1-year estimated glomerular filtration rate and 5-year graft survival based on pretransplant information including demographic factors, immunosuppressive therapy, immunological factors and organ procurement technique. A third nomogram was constructed to predict 5-year graft survival using additional information available by 6 months after transplantation. These data included delayed graft function, any treated rejection episodes and the 6-month estimated glomerular filtration rate. The nomograms were internally validated using 10-fold cross-validation. The renal function nomogram had an r-square value of 0.13. It worked best when predicting estimated glomerular filtration rate values between 50 and 70 ml per minute per 1.73 m(2). The 5-year graft survival nomograms had a concordance index of 0.71 for the pretransplant nomogram and 0.78 for the 6-month posttransplant nomogram. Calibration was adequate for all nomograms. Nomograms based on data from the United Network for Organ Sharing registry have been validated to predict the 1-year estimated glomerular filtration rate and 5-year graft survival. These nomograms may facilitate individualized patient care in living donor kidney transplantation.

Evaluating Cardiovascular Health Disparities Using Estimated Race/Ethnicity: A Validation Study.

PubMed

Bykov, Katsiaryna; Franklin, Jessica M; Toscano, Michele; Rawlins, Wayne; Spettell, Claire M; McMahill-Walraven, Cheryl N; Shrank, William H; Choudhry, Niteesh K

2015-12-01

Methods of estimating race/ethnicity using administrative data are increasingly used to examine and target disparities; however, there has been no validation of these methods using clinically relevant outcomes. To evaluate the validity of the indirect method of race/ethnicity identification based on place of residence and surname for assessing clinically relevant outcomes. A total of 2387 participants in the Post-MI Free Rx Event and Economic Evaluation (MI FREEE) trial who had both self-reported and Bayesian Improved Surname Geocoding method (BISG)-estimated race/ethnicity information available. We used tests of interaction to compare differences in the effect of providing full drug coverage for post-MI medications on adherence and rates of major vascular events or revascularization for white and nonwhite patients based upon self-reported and indirect racial/ethnic assignment. The impact of full coverage on clinical events differed substantially when based upon self-identified race (HR=0.97 for whites, HR=0.65 for nonwhites; interaction P-value=0.05); however, it did not differ among race/ethnicity groups classified using indirect methods (HR=0.87 for white and nonwhites; interaction P-value=0.83). The impact on adherence was the same for self-reported and BISG-estimated race/ethnicity for 2 of the 3 medication classes studied. Quantitatively and qualitatively different results were obtained when indirectly estimated race/ethnicity was used, suggesting that these techniques may not accurately describe aspects of race/ethnicity related to actual health behaviors.

Three validation metrics for automated probabilistic image segmentation of brain tumours

PubMed Central

Zou, Kelly H.; Wells, William M.; Kikinis, Ron; Warfield, Simon K.

2005-01-01

SUMMARY The validity of brain tumour segmentation is an important issue in image processing because it has a direct impact on surgical planning. We examined the segmentation accuracy based on three two-sample validation metrics against the estimated composite latent gold standard, which was derived from several experts’ manual segmentations by an EM algorithm. The distribution functions of the tumour and control pixel data were parametrically assumed to be a mixture of two beta distributions with different shape parameters. We estimated the corresponding receiver operating characteristic curve, Dice similarity coefficient, and mutual information, over all possible decision thresholds. Based on each validation metric, an optimal threshold was then computed via maximization. We illustrated these methods on MR imaging data from nine brain tumour cases of three different tumour types, each consisting of a large number of pixels. The automated segmentation yielded satisfactory accuracy with varied optimal thresholds. The performances of these validation metrics were also investigated via Monte Carlo simulation. Extensions of incorporating spatial correlation structures using a Markov random field model were considered. PMID:15083482

Nonparametric estimation of the heterogeneity of a random medium using compound Poisson process modeling of wave multiple scattering.

PubMed

Le Bihan, Nicolas; Margerin, Ludovic

2009-07-01

In this paper, we present a nonparametric method to estimate the heterogeneity of a random medium from the angular distribution of intensity of waves transmitted through a slab of random material. Our approach is based on the modeling of forward multiple scattering using compound Poisson processes on compact Lie groups. The estimation technique is validated through numerical simulations based on radiative transfer theory.

Intelligence in Bali--A Case Study on Estimating Mean IQ for a Population Using Various Corrections Based on Theory and Empirical Findings

ERIC Educational Resources Information Center

Rindermann, Heiner; te Nijenhuis, Jan

2012-01-01

A high-quality estimate of the mean IQ of a country requires giving a well-validated test to a nationally representative sample, which usually is not feasible in developing countries. So, we used a convenience sample and four corrections based on theory and empirical findings to arrive at a good-quality estimate of the mean IQ in Bali. Our study…

The Effects of Baseline Estimation on the Reliability, Validity, and Precision of CBM-R Growth Estimates

ERIC Educational Resources Information Center

Van Norman, Ethan R.; Christ, Theodore J.; Zopluoglu, Cengiz

2013-01-01

This study examined the effect of baseline estimation on the quality of trend estimates derived from Curriculum Based Measurement of Oral Reading (CBM-R) progress monitoring data. The authors used a linear mixed effects regression (LMER) model to simulate progress monitoring data for schedules ranging from 6-20 weeks for datasets with high and low…

Manifold absolute pressure estimation using neural network with hybrid training algorithm

PubMed Central

Selamat, Hazlina; Alimin, Ahmad Jais; Haniff, Mohamad Fadzli

2017-01-01

In a modern small gasoline engine fuel injection system, the load of the engine is estimated based on the measurement of the manifold absolute pressure (MAP) sensor, which took place in the intake manifold. This paper present a more economical approach on estimating the MAP by using only the measurements of the throttle position and engine speed, resulting in lower implementation cost. The estimation was done via two-stage multilayer feed-forward neural network by combining Levenberg-Marquardt (LM) algorithm, Bayesian Regularization (BR) algorithm and Particle Swarm Optimization (PSO) algorithm. Based on the results found in 20 runs, the second variant of the hybrid algorithm yields a better network performance than the first variant of hybrid algorithm, LM, LM with BR and PSO by estimating the MAP closely to the simulated MAP values. By using a valid experimental training data, the estimator network that trained with the second variant of the hybrid algorithm showed the best performance among other algorithms when used in an actual retrofit fuel injection system (RFIS). The performance of the estimator was also validated in steady-state and transient condition by showing a closer MAP estimation to the actual value. PMID:29190779

Assessing genomic selection prediction accuracy in a dynamic barley breeding

USDA-ARS?s Scientific Manuscript database

Genomic selection is a method to improve quantitative traits in crops and livestock by estimating breeding values of selection candidates using phenotype and genome-wide marker data sets. Prediction accuracy has been evaluated through simulation and cross-validation, however validation based on prog...

Multilevel model to estimate county-level untreated dental caries among US children aged 6-9years using the National Health and Nutrition Examination Survey.

PubMed

Lin, Mei; Zhang, Xingyou; Holt, James B; Robison, Valerie; Li, Chien-Hsun; Griffin, Susan O

2018-06-01

Because conducting population-based oral health screening is resource intensive, oral health data at small-area levels (e.g., county-level) are not commonly available. We applied the multilevel logistic regression and poststratification method to estimate county-level prevalence of untreated dental caries among children aged 6-9years in the United States using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2010 linked with various area-level data at census tract, county and state levels. We validated model-based national estimates against direct estimates from NHANES. We also compared model-based estimates with direct estimates from select State Oral Health Surveys (SOHS) at state and county levels. The model with individual-level covariates only and the model with individual-, census tract- and county-level covariates explained 7.2% and 96.3% respectively of overall county-level variation in untreated caries. Model-based county-level prevalence estimates ranged from 4.9% to 65.2% with median of 22.1%. The model-based national estimate (19.9%) matched the NHANES direct estimate (19.8%). We found significantly positive correlations between model-based estimates for 8-year-olds and direct estimates from the third-grade State Oral Health Surveys (SOHS) at state level for 34 states (Pearson coefficient: 0.54, P=0.001) and SOHS estimates at county level for 53 New York counties (Pearson coefficient: 0.38, P=0.006). This methodology could be a useful tool to characterize county-level disparities in untreated dental caries among children aged 6-9years and complement oral health surveillance to inform public health programs especially when local-level data are not available although the lack of external validation due to data unavailability should be acknowledged. Published by Elsevier Inc.

Testing of the SEE and OEE post-hip fracture.

PubMed

Resnick, Barbara; Orwig, Denise; Zimmerman, Sheryl; Hawkes, William; Golden, Justine; Werner-Bronzert, Michelle; Magaziner, Jay

2006-08-01

The purpose of this study was to test the reliability and validity of the Self-Efficacy for Exercise (SEE) and the Outcome Expectations for Exercise (OEE) scales in a sample of 166 older women post-hip fracture. There was some evidence of validity of the SEE and OEE based on confirmatory factor analysis and Rasch model testing, criterion based and convergent validity, and evidence of internal consistency based on alpha coefficients and separation indices and reliability based on R2 estimates. Rasch model testing demonstrated that some items had high variability. Based on these findings suggestions are made for how items could be revised and the scales improved for future use.

Development and validation of a new population-based simulation model of osteoarthritis in New Zealand.

PubMed

Wilson, R; Abbott, J H

2018-04-01

To describe the construction and preliminary validation of a new population-based microsimulation model developed to analyse the health and economic burden and cost-effectiveness of treatments for knee osteoarthritis (OA) in New Zealand (NZ). We developed the New Zealand Management of Osteoarthritis (NZ-MOA) model, a discrete-time state-transition microsimulation model of the natural history of radiographic knee OA. In this article, we report on the model structure, derivation of input data, validation of baseline model parameters against external data sources, and validation of model outputs by comparison of the predicted population health loss with previous estimates. The NZ-MOA model simulates both the structural progression of radiographic knee OA and the stochastic development of multiple disease symptoms. Input parameters were sourced from NZ population-based data where possible, and from international sources where NZ-specific data were not available. The predicted distributions of structural OA severity and health utility detriments associated with OA were externally validated against other sources of evidence, and uncertainty resulting from key input parameters was quantified. The resulting lifetime and current population health-loss burden was consistent with estimates of previous studies. The new NZ-MOA model provides reliable estimates of the health loss associated with knee OA in the NZ population. The model structure is suitable for analysis of the effects of a range of potential treatments, and will be used in future work to evaluate the cost-effectiveness of recommended interventions within the NZ healthcare system. Copyright © 2018 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Mixed group validation: a method to address the limitations of criterion group validation in research on malingering detection.

PubMed

Frederick, R I

2000-01-01

Mixed group validation (MGV) is offered as an alternative to criterion group validation (CGV) to estimate the true positive and false positive rates of tests and other diagnostic signs. CGV requires perfect confidence about each research participant's status with respect to the presence or absence of pathology. MGV determines diagnostic efficiencies based on group data; knowing an individual's status with respect to pathology is not required. MGV can use relatively weak indicators to validate better diagnostic signs, whereas CGV requires perfect diagnostic signs to avoid error in computing true positive and false positive rates. The process of MGV is explained, and a computer simulation demonstrates the soundness of the procedure. MGV of the Rey 15-Item Memory Test (Rey, 1958) for 723 pre-trial criminal defendants resulted in higher estimates of true positive rates and lower estimates of false positive rates as compared with prior research conducted with CGV. The author demonstrates how MGV addresses all the criticisms Rogers (1997b) outlined for differential prevalence designs in malingering detection research. Copyright 2000 John Wiley & Sons, Ltd.

Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

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

O’Shea, Tuathan P., E-mail: tuathan.oshea@icr.ac.uk; Bamber, Jeffrey C.; Harris, Emma J.

Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison withmore » normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking performance. A future study will investigate spatial uniformity of motion and its effect on the motion estimation errors.« less

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model

PubMed Central

Jang, Cheongjae; Ha, Junhyoung; Dupont, Pierre E.; Park, Frank Chongwoo

2017-01-01

Although existing mechanics-based models of concentric tube robots have been experimentally demonstrated to approximate the actual kinematics, determining accurate estimates of model parameters remains difficult due to the complex relationship between the parameters and available measurements. Further, because the mechanics-based models neglect some phenomena like friction, nonlinear elasticity, and cross section deformation, it is also not clear if model error is due to model simplification or to parameter estimation errors. The parameters of the superelastic materials used in these robots can be slowly time-varying, necessitating periodic re-estimation. This paper proposes a method for estimating the mechanics-based model parameters using an extended Kalman filter as a step toward on-line parameter estimation. Our methodology is validated through both simulation and experiments. PMID:28717554

Patient-specific lean body mass can be estimated from limited-coverage computed tomography images.

PubMed

Devriese, Joke; Beels, Laurence; Maes, Alex; van de Wiele, Christophe; Pottel, Hans

2018-06-01

In PET/CT, quantitative evaluation of tumour metabolic activity is possible through standardized uptake values, usually normalized for body weight (BW) or lean body mass (LBM). Patient-specific LBM can be estimated from whole-body (WB) CT images. As most clinical indications only warrant PET/CT examinations covering head to midthigh, the aim of this study was to develop a simple and reliable method to estimate LBM from limited-coverage (LC) CT images and test its validity. Head-to-toe PET/CT examinations were retrospectively retrieved and semiautomatically segmented into tissue types based on thresholding of CT Hounsfield units. LC was obtained by omitting image slices. Image segmentation was validated on the WB CT examinations by comparing CT-estimated BW with actual BW, and LBM estimated from LC images were compared with LBM estimated from WB images. A direct method and an indirect method were developed and validated on an independent data set. Comparing LBM estimated from LC examinations with estimates from WB examinations (LBMWB) showed a significant but limited bias of 1.2 kg (direct method) and nonsignificant bias of 0.05 kg (indirect method). This study demonstrates that LBM can be estimated from LC CT images with no significant difference from LBMWB.

A robust vision-based sensor fusion approach for real-time pose estimation.

PubMed

Assa, Akbar; Janabi-Sharifi, Farrokh

2014-02-01

Object pose estimation is of great importance to many applications, such as augmented reality, localization and mapping, motion capture, and visual servoing. Although many approaches based on a monocular camera have been proposed, only a few works have concentrated on applying multicamera sensor fusion techniques to pose estimation. Higher accuracy and enhanced robustness toward sensor defects or failures are some of the advantages of these schemes. This paper presents a new Kalman-based sensor fusion approach for pose estimation that offers higher accuracy and precision, and is robust to camera motion and image occlusion, compared to its predecessors. Extensive experiments are conducted to validate the superiority of this fusion method over currently employed vision-based pose estimation algorithms.

Application of wavelet-based multi-model Kalman filters to real-time flood forecasting

NASA Astrophysics Data System (ADS)

Chou, Chien-Ming; Wang, Ru-Yih

2004-04-01

This paper presents the application of a multimodel method using a wavelet-based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real-time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet-based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state-estimates, each of which is weighted by its possibility that is also determined on-line, are combined to form an optimal estimate. Validations conducted for the Wu-Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time-varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall-runoff process in the Wu-Tu watershed.

Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements

NASA Astrophysics Data System (ADS)

Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.

2012-12-01

The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some validation experiments demonstrated that the models yield accurate estimates at flux measurement sites, the question remains whether they are performing well over the broader landscape. Moreover, a large number of RS_ET products have been released in recent years. Thus, we also pay attention to the cross-validation method of RS_ET derived from multi-source models. "The Multi-scale Observation Experiment on Evapotranspiration over Heterogeneous Land Surfaces: Flux Observation Matrix" campaign is carried out at the middle reaches of the Heihe River Basin, China in 2012. Flux measurements from an observation matrix composed of 22 EC and 4 LAS are acquired to investigate the cross-validation of multi-source models over different landscapes. In this case, six remote sensing models, including the empirical statistical model, the one-source and two-source models, the Penman-Monteith equation based model, the Priestley-Taylor equation based model, and the complementary relationship based model, are used to perform an intercomparison. All the results from the two cases of RS_ET validation showed that the proposed validation methods are reasonable and feasible.

Reliability and validity of Arabic Rapid Estimate of Adult Literacy in Dentistry (AREALD-30) in Saudi Arabia.

PubMed

Tadakamadla, Santosh Kumar; Quadri, Mir Faeq Ali; Pakpour, Amir H; Zailai, Abdulaziz M; Sayed, Mohammed E; Mashyakhy, Mohammed; Inamdar, Aadil S; Tadakamadla, Jyothi

2014-09-29

To evaluate the reliability and validity of Arabic Rapid Estimate of Adult Literacy in Dentistry (AREALD-30) in Saudi Arabia. A convenience sample of 200 subjects was approached, of which 177 agreed to participate giving a response rate of 88.5%. Rapid Estimate of Adult Literacy in Dentistry (REALD-99), was translated into Arabic to prepare the longer and shorter versions of Arabic Rapid Estimate of Adult Literacy in Dentistry (AREALD-99 and AREALD-30). Each participant was provided with AREALD-99 which also includes words from AREALD-30. A questionnaire containing socio-behavioral information and Arabic Oral Health Impact Profile (A-OHIP-14) was also administered. Reliability of the AREALD-30 was assessed by re-administering it to 20 subjects after two weeks. Convergent and predictive validity of AREALD-30 was evaluated by its correlations with AREALD-99 and self-perceived oral health status, dental visiting habits and A-OHIP-14 respectively. Discriminant validity was assessed in relation to the educational level while construct validity was evaluated by confirmatory factor analysis (CFA). Reliability of AREALD-30 was excellent with intraclass correlation coefficient of 0.99. It exhibited good convergent and discriminant validity but poor predictive validity. CFA showed presence of two factors and infit mean-square statistics for AREALD-30 were all within the desired range of 0.50 - 2.0 in Rasch analysis. AREALD-30 showed excellent reliability, good convergent and concurrent validity, but failed to predict the differences between the subjects categorized based on their oral health outcomes.

Official statistics and claims data records indicate non-response and recall bias within survey-based estimates of health care utilization in the older population

PubMed Central

2013-01-01

Background The validity of survey-based health care utilization estimates in the older population has been poorly researched. Owing to data protection legislation and a great number of different health care insurance providers, the assessment of recall and non-response bias is challenging to impossible in many countries. The objective of our study was to compare estimates from a population-based study in older German adults with external secondary data. Methods We used data from the German KORA-Age study, which included 4,127 people aged 65–94 years. Self-report questions covered the utilization of long-term care services, inpatient services, outpatient services, and pharmaceuticals. We calculated age- and sex-standardized mean utilization rates in each domain and compared them with the corresponding estimates derived from official statistics and independent statutory health insurance data. Results The KORA-Age study underestimated the use of long-term care services (−52%), in-hospital days (−21%) and physician visits (−70%). In contrast, the assessment of drug consumption by postal self-report questionnaires yielded similar estimates to the analysis of insurance claims data (−9%). Conclusion Survey estimates based on self-report tend to underestimate true health care utilization in the older population. Direct validation studies are needed to disentangle the impact of recall and non-response bias. PMID:23286781

Construct Validity Evidence for Single-Response Items to Estimate Physical Activity Levels in Large Sample Studies

ERIC Educational Resources Information Center

Jackson, Allen W.; Morrow, James R., Jr.; Bowles, Heather R.; FitzGerald, Shannon J.; Blair, Steven N.

2007-01-01

Valid measurement of physical activity is important for studying the risks for morbidity and mortality. The purpose of this study was to examine evidence of construct validity of two similar single-response items assessing physical activity via self-report. Both items are based on the stages of change model. The sample was 687 participants (men =…

Using Neural Networks for Sensor Validation

NASA Technical Reports Server (NTRS)

Mattern, Duane L.; Jaw, Link C.; Guo, Ten-Huei; Graham, Ronald; McCoy, William

1998-01-01

This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a model-based approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component analysis on a set of redundant sensors to provide an estimate for a single failed sensor. The approaches are demonstrated using a nonlinear simulation of a turbofan engine. The fault detection and sensor estimation results are presented and the training of the auto-associative neural network to provide sensor estimates is discussed.

Validation of Ground-based Optical Estimates of Auroral Electron Precipitation Energy Deposition

NASA Astrophysics Data System (ADS)

Hampton, D. L.; Grubbs, G. A., II; Conde, M.; Lynch, K. A.; Michell, R.; Zettergren, M. D.; Samara, M.; Ahrns, M. J.

2017-12-01

One of the major energy inputs into the high latitude ionosphere and mesosphere is auroral electron precipitation. Not only does the kinetic energy get deposited, the ensuing ionization in the E and F-region ionosphere modulates parallel and horizontal currents that can dissipate in the form of Joule heating. Global models to simulate these interactions typically use electron precipitation models that produce a poor representation of the spatial and temporal complexity of auroral activity as observed from the ground. This is largely due to these precipitation models being based on averages of multiple satellite overpasses separated by periods much longer than typical auroral feature durations. With the development of regional and continental observing networks (e.g. THEMIS ASI), the possibility of ground-based optical observations producing quantitative estimates of energy deposition with temporal and spatial scales comparable to those known to be exhibited in auroral activity become a real possibility. Like empirical precipitation models based on satellite overpasses such optics-based estimates are subject to assumptions and uncertainties, and therefore require validation. Three recent sounding rocket missions offer such an opportunity. The MICA (2012), GREECE (2014) and Isinglass (2017) missions involved detailed ground based observations of auroral arcs simultaneously with extensive on-board instrumentation. These have afforded an opportunity to examine the results of three optical methods of determining auroral electron energy flux, namely 1) ratio of auroral emissions, 2) green line temperature vs. emission altitude, and 3) parametric estimates using white-light images. We present comparisons from all three methods for all three missions and summarize the temporal and spatial scales and coverage over which each is valid.

Estimating Rooftop Suitability for PV: A Review of Methods, Patents, and Validation Techniques

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

Melius, J.; Margolis, R.; Ong, S.

2013-12-01

A number of methods have been developed using remote sensing data to estimate rooftop area suitable for the installation of photovoltaics (PV) at various geospatial resolutions. This report reviews the literature and patents on methods for estimating rooftop-area appropriate for PV, including constant-value methods, manual selection methods, and GIS-based methods. This report also presents NREL's proposed method for estimating suitable rooftop area for PV using Light Detection and Ranging (LiDAR) data in conjunction with a GIS model to predict areas with appropriate slope, orientation, and sunlight. NREL's method is validated against solar installation data from New Jersey, Colorado, and Californiamore » to compare modeled results to actual on-the-ground measurements.« less

Validity of a Semi-Quantitative Food Frequency Questionnaire for Collegiate Athletes

PubMed Central

Sasaki, Kazuto; Suzuki, Yoshio; Oguma, Nobuhide; Ishihara, Junko; Nakai, Ayumi; Yasuda, Jun; Yokoyama, Yuri; Yoshizaki, Takahiro; Tada, Yuki; Hida, Azumi; Kawano, Yukari

2016-01-01

Background Food frequency questionnaires (FFQs) have been developed and validated for various populations. To our knowledge, however, no FFQ has been validated for young athletes. Here, we investigated whether an FFQ that was developed and validated to estimate dietary intake in middle-aged persons was also valid for estimating that in young athletes. Methods We applied an FFQ that had been developed for the Japan Public Health Center-based Prospective Cohort Study with modification to the duration of recollection. A total of 156 participants (92 males) completed the FFQ and a 3-day non-consecutive 24-hour dietary recall (24hDR). Validity of the mean estimates was evaluated by calculating the percentage differences between the 24hDR and FFQ. Ranking estimation was validated using Spearman’s correlation coefficient (CC), and the degree of miscategorization was determined by joint classification. Results The FFQ underestimated energy intake by approximately 10% for both males and females. For 35 nutrients, the median (range) deattenuated CC was 0.30 (0.10 to 0.57) for males and 0.32 (−0.08 to 0.62) for females. For 19 food groups, the median (range) deattenuated CC was 0.32 (0.17 to 0.72) for males and 0.34 (−0.11 to 0.58) for females. For both nutrient and food group intakes, cross-classification analysis indicated extreme miscategorization rates of 3% to 5%. Conclusions An FFQ developed and validated for middle-aged persons had comparable validity among young athletes. This FFQ might be useful for assessing habitual dietary intake in collegiate athletes, especially for calcium, vitamin C, vegetables, fruits, and milk and dairy products. PMID:26902164

Using twig diameters to estimate browse utilization on three shrub species in southeastern Montana

Treesearch

Mark A. Rumble

1987-01-01

Browse utilization estimates based on twig length and twig weight were compared for skunkbush sumac, wax currant, and chokecherry. Linear regression analysis was valid for twig length data; twig weight equations are nonlinear. Estimates of twig weight are more accurate. Problems encountered during development of a utilization model are discussed.

Are early first trimester weights valid proxies for preconception weight?

USDA-ARS?s Scientific Manuscript database

An accurate estimate of preconception weight is necessary for providing a gestational weight gain range based on the Institute of Medicine’s guidelines; however, an accurate and proximal preconception weight is not available for most women. We examined the validity of first trimester weights for est...

Surface smoothness: cartilage biomarkers for knee OA beyond the radiologist

NASA Astrophysics Data System (ADS)

Tummala, Sudhakar; Dam, Erik B.

2010-03-01

Fully automatic imaging biomarkers may allow quantification of patho-physiological processes that a radiologist would not be able to assess reliably. This can introduce new insight but is problematic to validate due to lack of meaningful ground truth expert measurements. Rather than quantification accuracy, such novel markers must therefore be validated against clinically meaningful end-goals such as the ability to allow correct diagnosis. We present a method for automatic cartilage surface smoothness quantification in the knee joint. The quantification is based on a curvature flow method used on tibial and femoral cartilage compartments resulting from an automatic segmentation scheme. These smoothness estimates are validated for their ability to diagnose osteoarthritis and compared to smoothness estimates based on manual expert segmentations and to conventional cartilage volume quantification. We demonstrate that the fully automatic markers eliminate the time required for radiologist annotations, and in addition provide a diagnostic marker superior to the evaluated semi-manual markers.

Factor structure of a standards-based inventory of competencies in social work with groups.

PubMed

Macgowan, Mark J; Dillon, Frank R; Spadola, Christine E

2018-01-01

This study extends previous findings on a measure of competencies based on Standards for Social Work Practice with Groups. The Inventory of Competencies in Social Work with Groups (ICSWG) measures confidence in performing the Standards. This study examines the latent structure of the Inventory, while illuminating the underlying structure of the Standards. A multinational sample of 586 persons completed the ICSWG. Exploratory factor analysis (EFA), reliability estimates, standard error of measurement estimates, and a range of validity tests were conducted. The EFA yielded a six-factor solution consisting of core values, mutuality/connectivity, collaboration, and three phases of group development (planning, beginnings/middles, endings). The alphas were .98 for the scale and ranged from .85 to .95 for the subscales. Correlations between the subscales and validators supported evidence of construct validity. The findings suggest key group work domains that should be taught and practiced in social work with groups.

Reconstruction and analysis of cesium-137 fallout deposition patterns in the Marshall Islands

NASA Astrophysics Data System (ADS)

Whitcomb, Robert Cleckley, Jr.

Estimates of 137Cs deposition due to fallout originating from nuclear weapons testing in the Marshall Islands have been made for several locations in the Marshall Islands. These retrospective estimates were based primarily on historical exposure rate and gummed film measurements. The methods used to reconstruct these deposition estimates are specific for six of the Pacific tests. These methods are also similar to those used in the National Cancer Institute study for reconstructing 131I deposition from the Nevada Test Site. Reconstructed cumulative deposition estimates are validated against contemporary measurements of 137Cs concentration in soil. This validation work also includes an accounting for estimated global fallout contributions. These validations show that the overall geometric bias in predicted-to-observed (P/O) ratios is 1.0 (indicating excellent agreement). The 5th and 95th percentile range of this distribution is 0.35--2.95. The P/O ratios for estimates using historical gummed film measurements tend to slightly over-predict more than estimates using exposure rate measurements. The methods produce reasonable estimates of deposition confirming that radioactive fallout occurred at atolls further south of the four northern atolls recognized by the Department of Energy as being affected by fallout. The deposition estimate methods, supported by the very good agreement between estimates and measurements, suggest that these methods can be used for other weapons testing fallout radionuclides with confidence.

Large-scale precipitation estimation using Kalpana-1 IR measurements and its validation using GPCP and GPCC data

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mahesh, C.; Gairola, Rakesh M.

2011-12-01

Large-scale precipitation estimation is very important for climate science because precipitation is a major component of the earth's water and energy cycles. In the present study, the GOES precipitation index technique has been applied to the Kalpana-1 satellite infrared (IR) images of every three-hourly, i.e., of 0000, 0300, 0600,…., 2100 hours UTC, for rainfall estimation as a preparatory to the INSAT-3D. After the temperatures of all the pixels in a grid are known, they are distributed to generate a three-hourly 24-class histogram of brightness temperatures of IR (10.5-12.5 μm) images for a 1.0° × 1.0° latitude/longitude box. The daily, monthly, and seasonal rainfall have been estimated using these three-hourly rain estimates for the entire south-west monsoon period of 2009 in the present study. To investigate the potential of these rainfall estimates, the validation of monthly and seasonal rainfall estimates has been carried out using the Global Precipitation Climatology Project and Global Precipitation Climatology Centre data. The validation results show that the present technique works very well for the large-scale precipitation estimation qualitatively as well as quantitatively. The results also suggest that the simple IR-based estimation technique can be used to estimate rainfall for tropical areas at a larger temporal scale for climatological applications.

SAMICS Validation. SAMICS Support Study, Phase 3

NASA Technical Reports Server (NTRS)

1979-01-01

SAMICS provides a consistent basis for estimating array costs and compares production technology costs. A review and a validation of the SAMICS model are reported. The review had the following purposes: (1) to test the computational validity of the computer model by comparison with preliminary hand calculations based on conventional cost estimating techniques; (2) to review and improve the accuracy of the cost relationships being used by the model: and (3) to provide an independent verification to users of the model's value in decision making for allocation of research and developement funds and for investment in manufacturing capacity. It is concluded that the SAMICS model is a flexible, accurate, and useful tool for managerial decision making.

Software risk management through independent verification and validation

NASA Technical Reports Server (NTRS)

Callahan, John R.; Zhou, Tong C.; Wood, Ralph

1995-01-01

Software project managers need tools to estimate and track project goals in a continuous fashion before, during, and after development of a system. In addition, they need an ability to compare the current project status with past project profiles to validate management intuition, identify problems, and then direct appropriate resources to the sources of problems. This paper describes a measurement-based approach to calculating the risk inherent in meeting project goals that leverages past project metrics and existing estimation and tracking models. We introduce the IV&V Goal/Questions/Metrics model, explain its use in the software development life cycle, and describe our attempts to validate the model through the reverse engineering of existing projects.

Validation of Pooled Whole-Genome Re-Sequencing in Arabidopsis lyrata.

PubMed

Fracassetti, Marco; Griffin, Philippa C; Willi, Yvonne

2015-01-01

Sequencing pooled DNA of multiple individuals from a population instead of sequencing individuals separately has become popular due to its cost-effectiveness and simple wet-lab protocol, although some criticism of this approach remains. Here we validated a protocol for pooled whole-genome re-sequencing (Pool-seq) of Arabidopsis lyrata libraries prepared with low amounts of DNA (1.6 ng per individual). The validation was based on comparing single nucleotide polymorphism (SNP) frequencies obtained by pooling with those obtained by individual-based Genotyping By Sequencing (GBS). Furthermore, we investigated the effect of sample number, sequencing depth per individual and variant caller on population SNP frequency estimates. For Pool-seq data, we compared frequency estimates from two SNP callers, VarScan and Snape; the former employs a frequentist SNP calling approach while the latter uses a Bayesian approach. Results revealed concordance correlation coefficients well above 0.8, confirming that Pool-seq is a valid method for acquiring population-level SNP frequency data. Higher accuracy was achieved by pooling more samples (25 compared to 14) and working with higher sequencing depth (4.1× per individual compared to 1.4× per individual), which increased the concordance correlation coefficient to 0.955. The Bayesian-based SNP caller produced somewhat higher concordance correlation coefficients, particularly at low sequencing depth. We recommend pooling at least 25 individuals combined with sequencing at a depth of 100× to produce satisfactory frequency estimates for common SNPs (minor allele frequency above 0.05).

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

DOE PAGES

Ye, Xin; Garikapati, Venu M.; You, Daehyun; ...

2017-11-08

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

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

Ye, Xin; Garikapati, Venu M.; You, Daehyun

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less

Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species

USGS Publications Warehouse

Then, Amy Y.; Hoenig, John M; Hall, Norman G.; Hewitt, David A.

2015-01-01

Many methods have been developed in the last 70 years to predict the natural mortality rate, M, of a stock based on empirical evidence from comparative life history studies. These indirect or empirical methods are used in most stock assessments to (i) obtain estimates of M in the absence of direct information, (ii) check on the reasonableness of a direct estimate of M, (iii) examine the range of plausible M estimates for the stock under consideration, and (iv) define prior distributions for Bayesian analyses. The two most cited empirical methods have appeared in the literature over 2500 times to date. Despite the importance of these methods, there is no consensus in the literature on how well these methods work in terms of prediction error or how their performance may be ranked. We evaluate estimators based on various combinations of maximum age (tmax), growth parameters, and water temperature by seeing how well they reproduce >200 independent, direct estimates of M. We use tenfold cross-validation to estimate the prediction error of the estimators and to rank their performance. With updated and carefully reviewed data, we conclude that a tmax-based estimator performs the best among all estimators evaluated. The tmax-based estimators in turn perform better than the Alverson–Carney method based on tmax and the von Bertalanffy K coefficient, Pauly’s method based on growth parameters and water temperature and methods based just on K. It is possible to combine two independent methods by computing a weighted mean but the improvement over the tmax-based methods is slight. Based on cross-validation prediction error, model residual patterns, model parsimony, and biological considerations, we recommend the use of a tmax-based estimator (M=4.899tmax−0.916">M=4.899t−0.916maxM=4.899tmax−0.916, prediction error = 0.32) when possible and a growth-based method (M=4.118K0.73L∞−0.33">M=4.118K0.73L−0.33∞M=4.118K0.73L∞−0.33 , prediction error = 0.6, length in cm) otherwise.

Calibration and Validation of Landsat Tree Cover in the Taiga-Tundra Ecotone

NASA Technical Reports Server (NTRS)

Montesano, Paul Mannix; Neigh, Christopher S. R.; Sexton, Joseph; Feng, Min; Channan, Saurabh; Ranson, Kenneth J.; Townshend, John R.

2016-01-01

Monitoring current forest characteristics in the taiga-tundra ecotone (TTE) at multiple scales is critical for understanding its vulnerability to structural changes. A 30 m spatial resolution Landsat-based tree canopy cover map has been calibrated and validated in the TTE with reference tree cover data from airborne LiDAR and high resolution spaceborne images across the full range of boreal forest tree cover. This domain-specific calibration model used estimates of forest height to determine reference forest cover that best matched Landsat estimates. The model removed the systematic under-estimation of tree canopy cover greater than 80% and indicated that Landsat estimates of tree canopy cover more closely matched canopies at least 2 m in height rather than 5 m. The validation improved estimates of uncertainty in tree canopy cover in discontinuous TTE forests for three temporal epochs (2000, 2005, and 2010) by reducing systematic errors, leading to increases in tree canopy cover uncertainty. Average pixel-level uncertainties in tree canopy cover were 29.0%, 27.1% and 31.1% for the 2000, 2005 and 2010 epochs, respectively. Maps from these calibrated data improve the uncertainty associated with Landsat tree canopy cover estimates in the discontinuous forests of the circumpolar TTE.

The relationship between DXA-based and anthropometric measures of visceral fat and morbidity in women

PubMed Central

2013-01-01

Background Excess accumulation of visceral fat is a prominent risk factor for cardiovascular and metabolic morbidity. While computed tomography (CT) is the gold standard to measure visceral adiposity, this is often not possible for large studies - thus valid, but less expensive and intrusive proxy measures of visceral fat are required such as dual-energy X-ray absorptiometry (DXA). Study aims were to a) identify a valid DXA-based measure of visceral adipose tissue (VAT), b) estimate VAT heritability and c) assess visceral fat association with morbidity in relation to body fat distribution. Methods A validation sample of 54 females measured for detailed body fat composition - assessed using CT, DXA and anthropometry – was used to evaluate previously published predictive models of CT-measured visceral fat. Based upon a validated model, we realised an out-of-sample estimate of abdominal VAT area for a study sample of 3457 female volunteer twins and estimated VAT area heritability using a classical twin study design. Regression and residuals analyses were used to assess the relationship between adiposity and morbidity. Results Published models applied to the validation sample explained >80% of the variance in CT-measured visceral fat. While CT visceral fat was best estimated using a linear regression for waist circumference, CT body cavity area and total abdominal fat (R2 = 0.91), anthropometric measures alone predicted VAT almost equally well (CT body cavity area and waist circumference, R2 = 0.86). Narrow sense VAT area heritability for the study sample was estimated to be 58% (95% CI: 51-66%) with a shared familial component of 24% (17-30%). VAT area is strongly associated with type 2 diabetes (T2D), hypertension (HT), subclinical atherosclerosis and liver function tests. In particular, VAT area is associated with T2D, HT and liver function (alanine transaminase) independent of DXA total abdominal fat and body mass index (BMI). Conclusions DXA and anthropometric measures can be utilised to derive estimates of visceral fat as a reliable alternative to CT. Visceral fat is heritable and appears to mediate the association between body adiposity and morbidity. This observation is consistent with hypotheses that suggest excess visceral adiposity is causally related to cardiovascular and metabolic disease. PMID:23552273

Applications of computerized adaptive testing (CAT) to the assessment of headache impact.

PubMed

Ware, John E; Kosinski, Mark; Bjorner, Jakob B; Bayliss, Martha S; Batenhorst, Alice; Dahlöf, Carl G H; Tepper, Stewart; Dowson, Andrew

2003-12-01

To evaluate the feasibility of computerized adaptive testing (CAT) and the reliability and validity of CAT-based estimates of headache impact scores in comparison with 'static' surveys. Responses to the 54-item Headache Impact Test (HIT) were re-analyzed for recent headache sufferers (n = 1016) who completed telephone interviews during the National Survey of Headache Impact (NSHI). Item response theory (IRT) calibrations and the computerized dynamic health assessment (DYNHA) software were used to simulate CAT assessments by selecting the most informative items for each person and estimating impact scores according to pre-set precision standards (CAT-HIT). Results were compared with IRT estimates based on all items (total-HIT), computerized 6-item dynamic estimates (CAT-HIT-6), and a developmental version of a 'static' 6-item form (HIT-6-D). Analyses focused on: respondent burden (survey length and administration time), score distributions ('ceiling' and 'floor' effects), reliability and standard errors, and clinical validity (diagnosis, level of severity). A random sample (n = 245) was re-assessed to test responsiveness. A second study (n = 1103) compared actual CAT surveys and an improved 'static' HIT-6 among current headache sufferers sampled on the Internet. Respondents completed measures from the first study and the generic SF-8 Health Survey; some (n = 540) were re-tested on the Internet after 2 weeks. In the first study, simulated CAT-HIT and total-HIT scores were highly correlated (r = 0.92) without 'ceiling' or 'floor' effects and with a substantial reduction (90.8%) in respondent burden. Six of the 54 items accounted for the great majority of item administrations (3603/5028, 77.6%). CAT-HIT reliability estimates were very high (0.975-0.992) in the range where 95% of respondents scored, and relative validity (RV) coefficients were high for diagnosis (RV = 0.87) and severity (RV = 0.89); patient-level classifications were accurate 91.3% for a diagnosis of migraine. For all three criteria of change, CAT-HIT scores were more responsive than all other measures. In the second study, estimates of respondent burden, item usage, reliability and clinical validity were replicated. The test-retest reliability of CAT-HIT was 0.79 and alternate forms coefficients ranged from 0.85 to 0.91. All correlations with the generic SF-8 were negative. CAT-based administrations of headache impact items achieved very large reductions in respondent burden without compromising validity for purposes of patient screening or monitoring changes in headache impact over time. IRT models and CAT-based dynamic health assessments warrant testing among patients with other conditions.

PHEV Energy Use Estimation: Validating the Gamma Distribution for Representing the Random Daily Driving Distance

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

Lin, Zhenhong; Dong, Jing; Liu, Changzheng

2012-01-01

The petroleum and electricity consumptions of plug-in hybrid electric vehicles (PHEVs) are sensitive to the variation of daily vehicle miles traveled (DVMT). Some studies assume DVMT to follow a Gamma distribution, but such a Gamma assumption is yet to be validated. This study finds the Gamma assumption valid in the context of PHEV energy analysis, based on continuous GPS travel data of 382 vehicles, each tracked for at least 183 days. The validity conclusion is based on the found small prediction errors, resulting from the Gamma assumption, in PHEV petroleum use, electricity use, and energy cost. The finding that themore » Gamma distribution is valid and reliable is important. It paves the way for the Gamma distribution to be assumed for analyzing energy uses of PHEVs in the real world. The Gamma distribution can be easily specified with very few pieces of driver information and is relatively easy for mathematical manipulation. Given the validation in this study, the Gamma distribution can now be used with better confidence in a variety of applications, such as improving vehicle consumer choice models, quantifying range anxiety for battery electric vehicles, investigating roles of charging infrastructure, and constructing online calculators that provide personal estimates of PHEV energy use.« less

Correction for FDG PET dose extravasations: Monte Carlo validation and quantitative evaluation of patient studies.

PubMed

Silva-Rodríguez, Jesús; Aguiar, Pablo; Sánchez, Manuel; Mosquera, Javier; Luna-Vega, Víctor; Cortés, Julia; Garrido, Miguel; Pombar, Miguel; Ruibal, Alvaro

2014-05-01

Current procedure guidelines for whole body [18F]fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography (PET) state that studies with visible dose extravasations should be rejected for quantification protocols. Our work is focused on the development and validation of methods for estimating extravasated doses in order to correct standard uptake value (SUV) values for this effect in clinical routine. One thousand three hundred sixty-seven consecutive whole body FDG-PET studies were visually inspected looking for extravasation cases. Two methods for estimating the extravasated dose were proposed and validated in different scenarios using Monte Carlo simulations. All visible extravasations were retrospectively evaluated using a manual ROI based method. In addition, the 50 patients with higher extravasated doses were also evaluated using a threshold-based method. Simulation studies showed that the proposed methods for estimating extravasated doses allow us to compensate the impact of extravasations on SUV values with an error below 5%. The quantitative evaluation of patient studies revealed that paravenous injection is a relatively frequent effect (18%) with a small fraction of patients presenting considerable extravasations ranging from 1% to a maximum of 22% of the injected dose. A criterion based on the extravasated volume and maximum concentration was established in order to identify this fraction of patients that might be corrected for paravenous injection effect. The authors propose the use of a manual ROI based method for estimating the effectively administered FDG dose and then correct SUV quantification in those patients fulfilling the proposed criterion.

Correction for FDG PET dose extravasations: Monte Carlo validation and quantitative evaluation of patient studies

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

Silva-Rodríguez, Jesús, E-mail: jesus.silva.rodriguez@sergas.es; Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es; Servicio de Medicina Nuclear, Complexo Hospitalario Universidade de Santiago de Compostela

Purpose: Current procedure guidelines for whole body [18F]fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography (PET) state that studies with visible dose extravasations should be rejected for quantification protocols. Our work is focused on the development and validation of methods for estimating extravasated doses in order to correct standard uptake value (SUV) values for this effect in clinical routine. Methods: One thousand three hundred sixty-seven consecutive whole body FDG-PET studies were visually inspected looking for extravasation cases. Two methods for estimating the extravasated dose were proposed and validated in different scenarios using Monte Carlo simulations. All visible extravasations were retrospectively evaluated using a manualmore » ROI based method. In addition, the 50 patients with higher extravasated doses were also evaluated using a threshold-based method. Results: Simulation studies showed that the proposed methods for estimating extravasated doses allow us to compensate the impact of extravasations on SUV values with an error below 5%. The quantitative evaluation of patient studies revealed that paravenous injection is a relatively frequent effect (18%) with a small fraction of patients presenting considerable extravasations ranging from 1% to a maximum of 22% of the injected dose. A criterion based on the extravasated volume and maximum concentration was established in order to identify this fraction of patients that might be corrected for paravenous injection effect. Conclusions: The authors propose the use of a manual ROI based method for estimating the effectively administered FDG dose and then correct SUV quantification in those patients fulfilling the proposed criterion.« less

A Simulation Study of Threats to Validity in Quasi-Experimental Designs: Interrelationship between Design, Measurement, and Analysis.

PubMed

Holgado-Tello, Fco P; Chacón-Moscoso, Salvador; Sanduvete-Chaves, Susana; Pérez-Gil, José A

2016-01-01

The Campbellian tradition provides a conceptual framework to assess threats to validity. On the other hand, different models of causal analysis have been developed to control estimation biases in different research designs. However, the link between design features, measurement issues, and concrete impact estimation analyses is weak. In order to provide an empirical solution to this problem, we use Structural Equation Modeling (SEM) as a first approximation to operationalize the analytical implications of threats to validity in quasi-experimental designs. Based on the analogies established between the Classical Test Theory (CTT) and causal analysis, we describe an empirical study based on SEM in which range restriction and statistical power have been simulated in two different models: (1) A multistate model in the control condition (pre-test); and (2) A single-trait-multistate model in the control condition (post-test), adding a new mediator latent exogenous (independent) variable that represents a threat to validity. Results show, empirically, how the differences between both the models could be partially or totally attributed to these threats. Therefore, SEM provides a useful tool to analyze the influence of potential threats to validity.

A Simulation Study of Threats to Validity in Quasi-Experimental Designs: Interrelationship between Design, Measurement, and Analysis

PubMed Central

Holgado-Tello, Fco. P.; Chacón-Moscoso, Salvador; Sanduvete-Chaves, Susana; Pérez-Gil, José A.

2016-01-01

The Campbellian tradition provides a conceptual framework to assess threats to validity. On the other hand, different models of causal analysis have been developed to control estimation biases in different research designs. However, the link between design features, measurement issues, and concrete impact estimation analyses is weak. In order to provide an empirical solution to this problem, we use Structural Equation Modeling (SEM) as a first approximation to operationalize the analytical implications of threats to validity in quasi-experimental designs. Based on the analogies established between the Classical Test Theory (CTT) and causal analysis, we describe an empirical study based on SEM in which range restriction and statistical power have been simulated in two different models: (1) A multistate model in the control condition (pre-test); and (2) A single-trait-multistate model in the control condition (post-test), adding a new mediator latent exogenous (independent) variable that represents a threat to validity. Results show, empirically, how the differences between both the models could be partially or totally attributed to these threats. Therefore, SEM provides a useful tool to analyze the influence of potential threats to validity. PMID:27378991

Validity of the Remote Food Photography Method (RFPM) for estimating energy and nutrient intake in near real-time.

PubMed

Martin, Corby K; Correa, John B; Han, Hongmei; Allen, H Raymond; Rood, Jennifer C; Champagne, Catherine M; Gunturk, Bahadir K; Bray, George A

2012-04-01

Two studies are reported; a pilot study to demonstrate feasibility followed by a larger validity study. Study 1's objective was to test the effect of two ecological momentary assessment (EMA) approaches that varied in intensity on the validity/accuracy of estimating energy intake (EI) with the Remote Food Photography Method (RFPM) over 6 days in free-living conditions. When using the RFPM, Smartphones are used to capture images of food selection and plate waste and to send the images to a server for food intake estimation. Consistent with EMA, prompts are sent to the Smartphones reminding participants to capture food images. During Study 1, EI estimated with the RFPM and the gold standard, doubly labeled water (DLW), were compared. Participants were assigned to receive Standard EMA Prompts (n = 24) or Customized Prompts (n = 16) (the latter received more reminders delivered at personalized meal times). The RFPM differed significantly from DLW at estimating EI when Standard (mean ± s.d. = -895 ± 770 kcal/day, P < 0.0001), but not Customized Prompts (-270 ± 748 kcal/day, P = 0.22) were used. Error (EI from the RFPM minus that from DLW) was significantly smaller with Customized vs. Standard Prompts. The objectives of Study 2 included testing the RFPM's ability to accurately estimate EI in free-living adults (N = 50) over 6 days, and energy and nutrient intake in laboratory-based meals. The RFPM did not differ significantly from DLW at estimating free-living EI (-152 ± 694 kcal/day, P = 0.16). During laboratory-based meals, estimating energy and macronutrient intake with the RFPM did not differ significantly compared to directly weighed intake.

Validity of the Remote Food Photography Method (RFPM) for estimating energy and nutrient intake in near real-time

PubMed Central

Martin, C. K.; Correa, J. B.; Han, H.; Allen, H. R.; Rood, J.; Champagne, C. M.; Gunturk, B. K.; Bray, G. A.

2014-01-01

Two studies are reported; a pilot study to demonstrate feasibility followed by a larger validity study. Study 1’s objective was to test the effect of two ecological momentary assessment (EMA) approaches that varied in intensity on the validity/accuracy of estimating energy intake with the Remote Food Photography Method (RFPM) over six days in free-living conditions. When using the RFPM, Smartphones are used to capture images of food selection and plate waste and to send the images to a server for food intake estimation. Consistent with EMA, prompts are sent to the Smartphones reminding participants to capture food images. During Study 1, energy intake estimated with the RFPM and the gold standard, doubly labeled water (DLW), were compared. Participants were assigned to receive Standard EMA Prompts (n=24) or Customized Prompts (n=16) (the latter received more reminders delivered at personalized meal times). The RFPM differed significantly from DLW at estimating energy intake when Standard (mean±SD = −895±770 kcal/day, p<.0001), but not Customized Prompts (−270±748 kcal/day, p=.22) were used. Error (energy intake from the RFPM minus that from DLW) was significantly smaller with Customized vs. Standard Prompts. The objectives of Study 2 included testing the RFPM’s ability to accurately estimate energy intake in free-living adults (N=50) over six days, and energy and nutrient intake in laboratory-based meals. The RFPM did not differ significantly from DLW at estimating free-living energy intake (−152±694 kcal/day, p=0.16). During laboratory-based meals, estimating energy and macronutrient intake with the RFPM did not differ significantly compared to directly weighed intake. PMID:22134199

Self-rated health: small area large area comparisons amongst older adults at the state, district and sub-district level in India.

PubMed

Hirve, Siddhivinayak; Vounatsou, Penelope; Juvekar, Sanjay; Blomstedt, Yulia; Wall, Stig; Chatterji, Somnath; Ng, Nawi

2014-03-01

We compared prevalence estimates of self-rated health (SRH) derived indirectly using four different small area estimation methods for the Vadu (small) area from the national Study on Global AGEing (SAGE) survey with estimates derived directly from the Vadu SAGE survey. The indirect synthetic estimate for Vadu was 24% whereas the model based estimates were 45.6% and 45.7% with smaller prediction errors and comparable to the direct survey estimate of 50%. The model based techniques were better suited to estimate the prevalence of SRH than the indirect synthetic method. We conclude that a simplified mixed effects regression model can produce valid small area estimates of SRH. © 2013 Published by Elsevier Ltd.

Adjustment and validation of a simulation tool for CSP plants based on parabolic trough technology

NASA Astrophysics Data System (ADS)

García-Barberena, Javier; Ubani, Nora

2016-05-01

The present work presents the validation process carried out for a simulation tool especially designed for the energy yield assessment of concentrating solar plants based on parabolic through (PT) technology. The validation has been carried out by comparing the model estimations with real data collected from a commercial CSP plant. In order to adjust the model parameters used for the simulation, 12 different days were selected among one-year of operational data measured at the real plant. The 12 days were simulated and the estimations compared with the measured data, focusing on the most important variables from the simulation point of view: temperatures, pressures and mass flow of the solar field, gross power, parasitic power, and net power delivered by the plant. Based on these 12 days, the key parameters for simulating the model were properly fixed and the simulation of a whole year performed. The results obtained for a complete year simulation showed very good agreement for the gross and net electric total production. The estimations for these magnitudes show a 1.47% and 2.02% BIAS respectively. The results proved that the simulation software describes with great accuracy the real operation of the power plant and correctly reproduces its transient behavior.

Precipitable water vapour content from ESR/SKYNET sun-sky radiometers: validation against GNSS/GPS and AERONET over three different sites in Europe

NASA Astrophysics Data System (ADS)

Campanelli, Monica; Mascitelli, Alessandra; Sanò, Paolo; Diémoz, Henri; Estellés, Victor; Federico, Stefano; Iannarelli, Anna Maria; Fratarcangeli, Francesca; Mazzoni, Augusto; Realini, Eugenio; Crespi, Mattia; Bock, Olivier; Martínez-Lozano, Jose A.; Dietrich, Stefano

2018-01-01

The estimation of the precipitable water vapour content (W) with high temporal and spatial resolution is of great interest to both meteorological and climatological studies. Several methodologies based on remote sensing techniques have been recently developed in order to obtain accurate and frequent measurements of this atmospheric parameter. Among them, the relative low cost and easy deployment of sun-sky radiometers, or sun photometers, operating in several international networks, allowed the development of automatic estimations of W from these instruments with high temporal resolution. However, the great problem of this methodology is the estimation of the sun-photometric calibration parameters. The objective of this paper is to validate a new methodology based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance at 940 nm are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site. To obtain the calibration parameters some simultaneously seasonal measurements of W, from independent sources, taken over a large range of solar zenith angle and covering a wide range of W, are needed. In this work yearly GNSS/GPS datasets were used for obtaining a table of photometric calibration constants and the methodology was applied and validated in three European ESR-SKYNET network sites, characterized by different atmospheric and climatic conditions: Rome, Valencia and Aosta. Results were validated against the GNSS/GPS and AErosol RObotic NETwork (AERONET) W estimations. In both the validations the agreement was very high, with a percentage RMSD of about 6, 13 and 8 % in the case of GPS intercomparison at Rome, Aosta and Valencia, respectively, and of 8 % in the case of AERONET comparison in Valencia. Analysing the results by W classes, the present methodology was found to clearly improve W estimation at low W content when compared against AERONET in terms of % bias, bringing the agreement with the GPS (considered the reference one) from a % bias of 5.76 to 0.52.

Estimation of Particulate Mass and Manganese Exposure Levels among Welders

PubMed Central

Hobson, Angela; Seixas, Noah; Sterling, David; Racette, Brad A.

2011-01-01

Background: Welders are frequently exposed to Manganese (Mn), which may increase the risk of neurological impairment. Historical exposure estimates for welding-exposed workers are needed for epidemiological studies evaluating the relationship between welding and neurological or other health outcomes. The objective of this study was to develop and validate a multivariate model to estimate quantitative levels of welding fume exposures based on welding particulate mass and Mn concentrations reported in the published literature. Methods: Articles that described welding particulate and Mn exposures during field welding activities were identified through a comprehensive literature search. Summary measures of exposure and related determinants such as year of sampling, welding process performed, type of ventilation used, degree of enclosure, base metal, and location of sampling filter were extracted from each article. The natural log of the reported arithmetic mean exposure level was used as the dependent variable in model building, while the independent variables included the exposure determinants. Cross-validation was performed to aid in model selection and to evaluate the generalizability of the models. Results: A total of 33 particulate and 27 Mn means were included in the regression analysis. The final model explained 76% of the variability in the mean exposures and included welding process and degree of enclosure as predictors. There was very little change in the explained variability and root mean squared error between the final model and its cross-validation model indicating the final model is robust given the available data. Conclusions: This model may be improved with more detailed exposure determinants; however, the relatively large amount of variance explained by the final model along with the positive generalizability results of the cross-validation increases the confidence that the estimates derived from this model can be used for estimating welder exposures in absence of individual measurement data. PMID:20870928

Quantification of construction waste prevented by BIM-based design validation: Case studies in South Korea.

PubMed

Won, Jongsung; Cheng, Jack C P; Lee, Ghang

2016-03-01

Waste generated in construction and demolition processes comprised around 50% of the solid waste in South Korea in 2013. Many cases show that design validation based on building information modeling (BIM) is an effective means to reduce the amount of construction waste since construction waste is mainly generated due to improper design and unexpected changes in the design and construction phases. However, the amount of construction waste that could be avoided by adopting BIM-based design validation has been unknown. This paper aims to estimate the amount of construction waste prevented by a BIM-based design validation process based on the amount of construction waste that might be generated due to design errors. Two project cases in South Korea were studied in this paper, with 381 and 136 design errors detected, respectively during the BIM-based design validation. Each design error was categorized according to its cause and the likelihood of detection before construction. The case studies show that BIM-based design validation could prevent 4.3-15.2% of construction waste that might have been generated without using BIM. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating the Classification Efficiency of a Test Battery.

ERIC Educational Resources Information Center

De Corte, Wilfried

2000-01-01

Shows how a theorem proven by H. Brogden (1951, 1959) can be used to estimate the allocation average (a predictor based classification of a test battery) assuming that the predictor intercorrelations and validities are known and that the predictor variables have a joint multivariate normal distribution. (SLD)

Vehicle Lateral State Estimation Based on Measured Tyre Forces

PubMed Central

Tuononen, Ari J.

2009-01-01

Future active safety systems need more accurate information about the state of vehicles. This article proposes a method to evaluate the lateral state of a vehicle based on measured tyre forces. The tyre forces of two tyres are estimated from optically measured tyre carcass deflections and transmitted wirelessly to the vehicle body. The two remaining tyres are so-called virtual tyre sensors, the forces of which are calculated from the real tyre sensor estimates. The Kalman filter estimator for lateral vehicle state based on measured tyre forces is presented, together with a simple method to define adaptive measurement error covariance depending on the driving condition of the vehicle. The estimated yaw rate and lateral velocity are compared with the validation sensor measurements. PMID:22291535

Using Appendicitis to Improve Estimates of Childhood Medicaid Participation Rates.

PubMed

Silber, Jeffrey H; Zeigler, Ashley E; Reiter, Joseph G; Hochman, Lauren L; Ludwig, Justin M; Wang, Wei; Calhoun, Shawna R; Pati, Susmita

2018-03-23

Administrative data are often used to estimate state Medicaid/Children's Health Insurance Program duration of enrollment and insurance continuity, but they are generally not used to estimate participation (the fraction of eligible children enrolled) because administrative data do not include reasons for disenrollment and cannot observe eligible never-enrolled children, causing estimates of eligible unenrolled to be inaccurate. Analysts are therefore forced to either utilize survey information that is not generally linkable to administrative claims or rely on duration and continuity measures derived from administrative data and forgo estimating claims-based participation. We introduce appendectomy-based participation (ABP) to estimate statewide participation rates using claims by taking advantage of a natural experiment around statewide appendicitis admissions to improve the accuracy of participation rate estimates. We used Medicaid Analytic eXtract (MAX) for 2008-2010; and the American Community Survey for 2008-2010 from 43 states to calculate ABP, continuity ratio, duration, and participation based on the American Community Survey (ACS). In the validation study, median participation rate using ABP was 86% versus 87% for ACS-based participation estimates using logical edits and 84% without logical edits. Correlations between ABP and ACS with or without logical edits was 0.86 (P < .0001). Using regression analysis, ABP alone was a significant predictor of ACS (P < .0001) with or without logical edits, and adding duration and/or the continuity ratio did not significantly improve the model. Using the ABP rate derived from administrative claims (MAX) is a valid method to estimate statewide public insurance participation rates in children. Copyright © 2018 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Variables influencing wearable sensor outcome estimates in individuals with stroke and incomplete spinal cord injury: a pilot investigation validating two research grade sensors.

PubMed

Jayaraman, Chandrasekaran; Mummidisetty, Chaithanya Krishna; Mannix-Slobig, Alannah; McGee Koch, Lori; Jayaraman, Arun

2018-03-13

Monitoring physical activity and leveraging wearable sensor technologies to facilitate active living in individuals with neurological impairment has been shown to yield benefits in terms of health and quality of living. In this context, accurate measurement of physical activity estimates from these sensors are vital. However, wearable sensor manufacturers generally only provide standard proprietary algorithms based off of healthy individuals to estimate physical activity metrics which may lead to inaccurate estimates in population with neurological impairment like stroke and incomplete spinal cord injury (iSCI). The main objective of this cross-sectional investigation was to evaluate the validity of physical activity estimates provided by standard proprietary algorithms for individuals with stroke and iSCI. Two research grade wearable sensors used in clinical settings were chosen and the outcome metrics estimated using standard proprietary algorithms were validated against designated golden standard measures (Cosmed K4B2 for energy expenditure and metabolic equivalent and manual tallying for step counts). The influence of sensor location, sensor type and activity characteristics were also studied. 28 participants (Healthy (n = 10); incomplete SCI (n = 8); stroke (n = 10)) performed a spectrum of activities in a laboratory setting using two wearable sensors (ActiGraph and Metria-IH1) at different body locations. Manufacturer provided standard proprietary algorithms estimated the step count, energy expenditure (EE) and metabolic equivalent (MET). These estimates were compared with the estimates from gold standard measures. For verifying validity, a series of Kruskal Wallis ANOVA tests (Games-Howell multiple comparison for post-hoc analyses) were conducted to compare the mean rank and absolute agreement of outcome metrics estimated by each of the devices in comparison with the designated gold standard measurements. The sensor type, sensor location, activity characteristics and the population specific condition influences the validity of estimation of physical activity metrics using standard proprietary algorithms. Implementing population specific customized algorithms accounting for the influences of sensor location, type and activity characteristics for estimating physical activity metrics in individuals with stroke and iSCI could be beneficial.

Individual Differences in Base Rate Neglect: A Fuzzy Processing Preference Index

PubMed Central

Wolfe, Christopher R.; Fisher, Christopher R.

2013-01-01

Little is known about individual differences in integrating numeric base-rates and qualitative text in making probability judgments. Fuzzy-Trace Theory predicts a preference for fuzzy processing. We conducted six studies to develop the FPPI, a reliable and valid instrument assessing individual differences in this fuzzy processing preference. It consists of 19 probability estimation items plus 4 "M-Scale" items that distinguish simple pattern matching from “base rate respect.” Cronbach's Alpha was consistently above 0.90. Validity is suggested by significant correlations between FPPI scores and three other measurers: "Rule Based" Process Dissociation Procedure scores; the number of conjunction fallacies in joint probability estimation; and logic index scores on syllogistic reasoning. Replicating norms collected in a university study with a web-based study produced negligible differences in FPPI scores, indicating robustness. The predicted relationships between individual differences in base rate respect and both conjunction fallacies and syllogistic reasoning were partially replicated in two web-based studies. PMID:23935255

Evaluation of Weighted Scale Reliability and Criterion Validity: A Latent Variable Modeling Approach

ERIC Educational Resources Information Center

Raykov, Tenko

2007-01-01

A method is outlined for evaluating the reliability and criterion validity of weighted scales based on sets of unidimensional measures. The approach is developed within the framework of latent variable modeling methodology and is useful for point and interval estimation of these measurement quality coefficients in counseling and education…

48 CFR 1852.245-73 - Financial reporting of NASA property in the custody of contractors.

Code of Federal Regulations, 2013 CFR

2013-10-01

... due. However, contractors' procedures must document the process for developing these estimates based... shall have formal policies and procedures, which address the validation of NF 1018 data, including data... validation is to ensure that information reported is accurate and in compliance with the NASA FAR Supplement...

48 CFR 1852.245-73 - Financial reporting of NASA property in the custody of contractors.

Code of Federal Regulations, 2012 CFR

2012-10-01

... due. However, contractors' procedures must document the process for developing these estimates based... shall have formal policies and procedures, which address the validation of NF 1018 data, including data... validation is to ensure that information reported is accurate and in compliance with the NASA FAR Supplement...

Calibration and validation of the COSMOS rover for surface soil moisture

USDA-ARS?s Scientific Manuscript database

The mobile COsmic-ray Soil Moisture Observing System (COSMOS) rover may be useful for validating satellite-based estimates of near surface soil moisture, but the accuracy with which the rover can measure 0-5 cm soil moisture has not been previously determined. Our objectives were to calibrate and va...

R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

PRIMsrc is a novel implementation of a non-parametric bump hunting procedure, based on the Patient Rule Induction Method (PRIM), offering a unified treatment of outcome variables, including censored time-to-event (Survival), continuous (Regression) and discrete (Classification) responses. To fit the model, it uses a recursive peeling procedure with specific peeling criteria and stopping rules depending on the response. To validate the model, it provides an objective function based on prediction-error or other specific statistic, as well as two alternative cross-validation techniques, adapted to the task of decision-rule making and estimation in the three types of settings. PRIMsrc comes as an open source R package, including at this point: (i) a main function for fitting a Survival Bump Hunting model with various options allowing cross-validated model selection to control model size (#covariates) and model complexity (#peeling steps) and generation of cross-validated end-point estimates; (ii) parallel computing; (iii) various S3-generic and specific plotting functions for data visualization, diagnostic, prediction, summary and display of results. It is available on CRAN and GitHub. PMID:26798326

Optimal Combinations of Diagnostic Tests Based on AUC.

PubMed

Huang, Xin; Qin, Gengsheng; Fang, Yixin

2011-06-01

When several diagnostic tests are available, one can combine them to achieve better diagnostic accuracy. This article considers the optimal linear combination that maximizes the area under the receiver operating characteristic curve (AUC); the estimates of the combination's coefficients can be obtained via a nonparametric procedure. However, for estimating the AUC associated with the estimated coefficients, the apparent estimation by re-substitution is too optimistic. To adjust for the upward bias, several methods are proposed. Among them the cross-validation approach is especially advocated, and an approximated cross-validation is developed to reduce the computational cost. Furthermore, these proposed methods can be applied for variable selection to select important diagnostic tests. The proposed methods are examined through simulation studies and applications to three real examples. © 2010, The International Biometric Society.

Aeroservoelastic Model Validation and Test Data Analysis of the F/A-18 Active Aeroelastic Wing

NASA Technical Reports Server (NTRS)

Brenner, Martin J.; Prazenica, Richard J.

2003-01-01

Model validation and flight test data analysis require careful consideration of the effects of uncertainty, noise, and nonlinearity. Uncertainty prevails in the data analysis techniques and results in a composite model uncertainty from unmodeled dynamics, assumptions and mechanics of the estimation procedures, noise, and nonlinearity. A fundamental requirement for reliable and robust model development is an attempt to account for each of these sources of error, in particular, for model validation, robust stability prediction, and flight control system development. This paper is concerned with data processing procedures for uncertainty reduction in model validation for stability estimation and nonlinear identification. F/A-18 Active Aeroelastic Wing (AAW) aircraft data is used to demonstrate signal representation effects on uncertain model development, stability estimation, and nonlinear identification. Data is decomposed using adaptive orthonormal best-basis and wavelet-basis signal decompositions for signal denoising into linear and nonlinear identification algorithms. Nonlinear identification from a wavelet-based Volterra kernel procedure is used to extract nonlinear dynamics from aeroelastic responses, and to assist model development and uncertainty reduction for model validation and stability prediction by removing a class of nonlinearity from the uncertainty.

Validation of PROMIS ® Physical Function computerized adaptive tests for orthopaedic foot and ankle outcome research.

PubMed

Hung, Man; Baumhauer, Judith F; Latt, L Daniel; Saltzman, Charles L; SooHoo, Nelson F; Hunt, Kenneth J

2013-11-01

In 2012, the American Orthopaedic Foot & Ankle Society(®) established a national network for collecting and sharing data on treatment outcomes and improving patient care. One of the network's initiatives is to explore the use of computerized adaptive tests (CATs) for patient-level outcome reporting. We determined whether the CAT from the NIH Patient Reported Outcome Measurement Information System(®) (PROMIS(®)) Physical Function (PF) item bank provides efficient, reliable, valid, precise, and adequately covered point estimates of patients' physical function. After informed consent, 288 patients with a mean age of 51 years (range, 18-81 years) undergoing surgery for common foot and ankle problems completed a web-based questionnaire. Efficiency was determined by time for test administration. Reliability was assessed with person and item reliability estimates. Validity evaluation included content validity from expert review and construct validity measured against the PROMIS(®) Pain CAT and patient responses based on tradeoff perceptions. Precision was assessed by standard error of measurement (SEM) across patients' physical function levels. Instrument coverage was based on a person-item map. Average time of test administration was 47 seconds. Reliability was 0.96 for person and 0.99 for item. Construct validity against the Pain CAT had an r value of -0.657 (p < 0.001). Precision had an SEM of less than 3.3 (equivalent to a Cronbach's alpha of ≥ 0.90) across a broad range of function. Concerning coverage, the ceiling effect was 0.32% and there was no floor effect. The PROMIS(®) PF CAT appears to be an excellent method for measuring outcomes for patients with foot and ankle surgery. Further validation of the PROMIS(®) item banks may ultimately provide a valid and reliable tool for measuring patient-reported outcomes after injuries and treatment.

Reconstruction and analysis of 137Cs fallout deposition patterns in the Marshall Islands.

PubMed

Whitcomb, Robert C

2002-03-01

Estimates of 137Cs deposition caused by fallout originating from nuclear weapons testing in the Marshall Islands have been estimated for several locations in the Marshall Islands. These retrospective estimates are based primarily on historical exposure rate and gummed film measurements. The methods used to reconstruct these deposition estimates are similar to those used in the National Cancer Institute study for reconstructing 131I deposition from the Nevada Test Site. Reconstructed cumulative deposition estimates are validated against contemporary measurements of 137Cs concentration in soil with account taken for estimated global fallout contributions. These validations show that the overall geometric bias in predicted-to-observed (P:O) ratios is 1.0 (indicating excellent agreement). The 5th to 95th percentile range of this distribution is 0.35-2.95. The P:O ratios for estimates using historical gummed film measurements tend to slightly overpredict more than estimates using exposure rate measurements. The deposition estimate methods, supported by the agreement between estimates and measurements, suggest that these methods can be used with confidence for other weapons testing fallout radionuclides.

NASA GPM GV Science Implementation

NASA Technical Reports Server (NTRS)

Petersen, W. A.

2009-01-01

Pre-launch algorithm development & post-launch product evaluation: The GPM GV paradigm moves beyond traditional direct validation/comparison activities by incorporating improved algorithm physics & model applications (end-to-end validation) in the validation process. Three approaches: 1) National Network (surface): Operational networks to identify and resolve first order discrepancies (e.g., bias) between satellite and ground-based precipitation estimates. 2) Physical Process (vertical column): Cloud system and microphysical studies geared toward testing and refinement of physically-based retrieval algorithms. 3) Integrated (4-dimensional): Integration of satellite precipitation products into coupled prediction models to evaluate strengths/limitations of satellite precipitation producers.

Evaluation of a watershed model for estimating daily flow using limited flow measurements

USDA-ARS?s Scientific Manuscript database

The Soil and Water Assessment Tool (SWAT) model was evaluated for estimation of continuous daily flow based on limited flow measurements in the Upper Oyster Creek (UOC) watershed. SWAT was calibrated against limited measured flow data and then validated. The Nash-Sutcliffe model Efficiency (NSE) and...

On the multiple imputation variance estimator for control-based and delta-adjusted pattern mixture models.

PubMed

Tang, Yongqiang

2017-12-01

Control-based pattern mixture models (PMM) and delta-adjusted PMMs are commonly used as sensitivity analyses in clinical trials with non-ignorable dropout. These PMMs assume that the statistical behavior of outcomes varies by pattern in the experimental arm in the imputation procedure, but the imputed data are typically analyzed by a standard method such as the primary analysis model. In the multiple imputation (MI) inference, Rubin's variance estimator is generally biased when the imputation and analysis models are uncongenial. One objective of the article is to quantify the bias of Rubin's variance estimator in the control-based and delta-adjusted PMMs for longitudinal continuous outcomes. These PMMs assume the same observed data distribution as the mixed effects model for repeated measures (MMRM). We derive analytic expressions for the MI treatment effect estimator and the associated Rubin's variance in these PMMs and MMRM as functions of the maximum likelihood estimator from the MMRM analysis and the observed proportion of subjects in each dropout pattern when the number of imputations is infinite. The asymptotic bias is generally small or negligible in the delta-adjusted PMM, but can be sizable in the control-based PMM. This indicates that the inference based on Rubin's rule is approximately valid in the delta-adjusted PMM. A simple variance estimator is proposed to ensure asymptotically valid MI inferences in these PMMs, and compared with the bootstrap variance. The proposed method is illustrated by the analysis of an antidepressant trial, and its performance is further evaluated via a simulation study. © 2017, The International Biometric Society.

Development and validation of risk models to select ever-smokers for CT lung-cancer screening

PubMed Central

Katki, Hormuzd A.; Kovalchik, Stephanie A.; Berg, Christine D.; Cheung, Li C.; Chaturvedi, Anil K.

2016-01-01

Importance The US Preventive Services Task Force (USPSTF) recommends computed-tomography (CT) lung-cancer screening for ever-smokers ages 55-80 years who smoked at least 30 pack-years with no more than 15 years since quitting. However, selecting ever-smokers for screening using individualized lung-cancer risk calculations may be more effective and efficient than current USPSTF recommendations. Objective Comparison of modeled outcomes from risk-based CT lung-screening strategies versus USPSTF recommendations. Design/Setting/Participants Empirical risk models for lung-cancer incidence and death in the absence of CT screening using data on ever-smokers from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO; 1993-2009) control group. Covariates included age, education, sex, race, smoking intensity/duration/quit-years, Body Mass Index, family history of lung-cancer, and self-reported emphysema. Model validation in the chest radiography groups of the PLCO and the National Lung Screening Trial (NLST; 2002-2009), with additional validation of the death model in the National Health Interview Survey (NHIS; 1997-2001), a representative sample of the US. Models applied to US ever-smokers ages 50-80 (NHIS 2010-2012) to estimate outcomes of risk-based selection for CT lung-screening, assuming screening for all ever-smokers yields the percent changes in lung-cancer detection and death observed in the NLST. Exposure Annual CT lung-screening for 3 years. Main Outcomes and Measures Model validity: calibration (number of model-predicted cases divided by number of observed cases (Estimated/Observed)) and discrimination (Area-Under-Curve (AUC)). Modeled screening outcomes: estimated number of screen-avertable lung-cancer deaths, estimated screening effectiveness (number needed to screen (NNS) to prevent 1 lung-cancer death). Results Lung-cancer incidence and death risk models were well-calibrated in PLCO and NLST. The lung-cancer death model calibrated and discriminated well for US ever-smokers ages 50-80 (NHIS 1997-2001: Estimated/Observed=0.94, 95%CI=0.84-1.05; AUC=0.78, 95%CI=0.76-0.80). Under USPSTF recommendations, the models estimated 9.0 million US ever-smokers would qualify for lung-cancer screening and 46,488 (95%CI=43,924-49,053) lung-cancer deaths were estimated as screen-avertable over 5 years (estimated NNS=194, 95%CI=187-201). In contrast, risk-based selection screening the same number of ever-smokers (9.0 million) at highest 5-year lung-cancer risk (≥1.9%), was estimated to avert 20% more deaths (55,717; 95%CI=53,033-58,400) and was estimated to reduce the estimated NNS by 17% (NNS=162, 95%CI=157-166). Conclusions and Relevance Among a cohort of US ever-smokers age 50-80 years, application of a risk-based model for CT screening for lung cancer compared with a model based on USPSTF recommendations was estimated to be associated with a greater number of lung-cancer deaths prevented over 5 years along with a lower NNS to prevent 1 lung-cancer death. PMID:27179989

Development and Validation of Risk Models to Select Ever-Smokers for CT Lung Cancer Screening.

PubMed

Katki, Hormuzd A; Kovalchik, Stephanie A; Berg, Christine D; Cheung, Li C; Chaturvedi, Anil K

2016-06-07

The US Preventive Services Task Force (USPSTF) recommends computed tomography (CT) lung cancer screening for ever-smokers aged 55 to 80 years who have smoked at least 30 pack-years with no more than 15 years since quitting. However, selecting ever-smokers for screening using individualized lung cancer risk calculations may be more effective and efficient than current USPSTF recommendations. Comparison of modeled outcomes from risk-based CT lung-screening strategies vs USPSTF recommendations. Empirical risk models for lung cancer incidence and death in the absence of CT screening using data on ever-smokers from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO; 1993-2009) control group. Covariates included age; education; sex; race; smoking intensity, duration, and quit-years; body mass index; family history of lung cancer; and self-reported emphysema. Model validation in the chest radiography groups of the PLCO and the National Lung Screening Trial (NLST; 2002-2009), with additional validation of the death model in the National Health Interview Survey (NHIS; 1997-2001), a representative sample of the United States. Models were applied to US ever-smokers aged 50 to 80 years (NHIS 2010-2012) to estimate outcomes of risk-based selection for CT lung screening, assuming screening for all ever-smokers, yield the percent changes in lung cancer detection and death observed in the NLST. Annual CT lung screening for 3 years beginning at age 50 years. For model validity: calibration (number of model-predicted cases divided by number of observed cases [estimated/observed]) and discrimination (area under curve [AUC]). For modeled screening outcomes: estimated number of screen-avertable lung cancer deaths and estimated screening effectiveness (number needed to screen [NNS] to prevent 1 lung cancer death). Lung cancer incidence and death risk models were well calibrated in PLCO and NLST. The lung cancer death model calibrated and discriminated well for US ever-smokers aged 50 to 80 years (NHIS 1997-2001: estimated/observed = 0.94 [95%CI, 0.84-1.05]; AUC, 0.78 [95%CI, 0.76-0.80]). Under USPSTF recommendations, the models estimated 9.0 million US ever-smokers would qualify for lung cancer screening and 46,488 (95% CI, 43,924-49,053) lung cancer deaths were estimated as screen-avertable over 5 years (estimated NNS, 194 [95% CI, 187-201]). In contrast, risk-based selection screening of the same number of ever-smokers (9.0 million) at highest 5-year lung cancer risk (≥1.9%) was estimated to avert 20% more deaths (55,717 [95% CI, 53,033-58,400]) and was estimated to reduce the estimated NNS by 17% (NNS, 162 [95% CI, 157-166]). Among a cohort of US ever-smokers aged 50 to 80 years, application of a risk-based model for CT screening for lung cancer compared with a model based on USPSTF recommendations was estimated to be associated with a greater number of lung cancer deaths prevented over 5 years, along with a lower NNS to prevent 1 lung cancer death.

Cost-Value Analysis and the SAVE: A Work in Progress, But an Option for Localised Decision Making?

PubMed

Karnon, Jonathan; Partington, Andrew

2015-12-01

Cost-value analysis aims to address the limitations of the quality-adjusted life-year (QALY) by incorporating the strength of public concerns for fairness in the allocation of scarce health care resources. To date, the measurement of value has focused on equity weights to reflect societal preferences for the allocation of QALY gains. Another approach is to use a non-QALY-based measure of value, such as an outcome 'equivalent to saving the life of a young person' (a SAVE). This paper assesses the feasibility and validity of using the SAVE as a measure of value for the economic evaluation of health care technologies. A web-based person trade-off (PTO) survey was designed and implemented to estimate equivalent SAVEs for outcome events associated with the progression and treatment of early-stage breast cancer. The estimated equivalent SAVEs were applied to the outputs of an existing decision analytic model for early breast cancer. The web-based PTO survey was undertaken by 1094 respondents. Validation tests showed that 68 % of eligible responses revealed consistent ordering of responses and 32 % displayed ordinal transitivity, while 37 % of respondents showing consistency and ordinal transitivity approached cardinal transitivity. Using consistent and ordinally transitive responses, the mean incremental cost per SAVE gained was £ 3.72 million. Further research is required to improve the validity of the SAVE, which may include a simpler web-based survey format or a face-to-face format to facilitate more informed responses. A validated method for estimating equivalent SAVEs is unlikely to replace the QALY as the globally preferred measure of outcome, but the SAVE may provide a useful alternative for localized decision makers with relatively small, constrained budgets-for example, in programme budgeting and marginal analysis.

Self-esteem among nursing assistants: reliability and validity of the Rosenberg Self-Esteem Scale.

PubMed

McMullen, Tara; Resnick, Barbara

2013-01-01

To establish the reliability and validity of the Rosenberg Self-Esteem Scale (RSES) when used with nursing assistants (NAs). Testing the RSES used baseline data from a randomized controlled trial testing the Res-Care Intervention. Female NAs were recruited from nursing homes (n = 508). Validity testing for the positive and negative subscales of the RSES was based on confirmatory factor analysis (CFA) using structural equation modeling and Rasch analysis. Estimates of reliability were based on Rasch analysis and the person separation index. Evidence supports the reliability and validity of the RSES in NAs although we recommend minor revisions to the measure for subsequent use. Establishing reliable and valid measures of self-esteem in NAs will facilitate testing of interventions to strengthen workplace self-esteem, job satisfaction, and retention.

Improving LiDAR Biomass Model Uncertainty through Non-Destructive Allometry and Plot-level 3D Reconstruction with Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Stovall, A. E.; Shugart, H. H., Jr.

2017-12-01

Future NASA and ESA satellite missions plan to better quantify global carbon through detailed observations of forest structure, but ultimately rely on uncertain ground measurement approaches for calibration and validation. A significant amount of the uncertainty in estimating plot-level biomass can be attributed to inadequate and unrepresentative allometric relationships used to convert plot-level tree measurements to estimates of aboveground biomass. These allometric equations are known to have high errors and biases, particularly in carbon rich forests because they were calibrated with small and often biased samples of destructively harvested trees. To overcome this issue, a non-destructive methodology for estimating tree and plot-level biomass has been proposed through the use of Terrestrial Laser Scanning (TLS). We investigated the potential for using TLS as a ground validation approach in LiDAR-based biomass mapping though virtual plot-level tree volume reconstruction and biomass estimation. Plot-level biomass estimates were compared on the Virginia-based Smithsonian Conservation Biology Institute's SIGEO forest with full 3D reconstruction, TLS allometry, and Jenkins et al. (2003) allometry. On average, full 3D reconstruction ultimately provided the lowest uncertainty estimate of plot-level biomass (9.6%), followed by TLS allometry (16.9%) and the national equations (20.2%). TLS offered modest improvements to the airborne LiDAR empirical models, reducing RMSE from 16.2% to 14%. Our findings suggest TLS plot acquisitions and non-destructive allometry can play a vital role for reducing uncertainty in calibration and validation data for biomass mapping in the upcoming NASA and ESA missions.

Application of cognitive diagnosis models to competency-based situational judgment tests.

PubMed

García, Pablo Eduardo; Olea, Julio; De la Torre, Jimmy

2014-01-01

Profiling of jobs in terms of competency requirements has increasingly been applied in many organizational settings. Testing these competencies through situational judgment tests (SJTs) leads to validity problems because it is not usually clear which constructs SJTs measure. The primary purpose of this paper is to evaluate whether the application of cognitive diagnosis models (CDM) to competency-based SJTs can ascertain the underlying competencies measured by the items, and whether these competencies can be estimated precisely. The generalized deterministic inputs, noisy "and" gate (G-DINA) model was applied to 26 situational judgment items measuring professional competencies based on the great eight model. These items were applied to 485 employees of a Spanish financial company. The fit of the model to the data and the convergent validity between the estimated competencies and personality dimensions were examined. The G-DINA showed a good fit to the data and the estimated competency factors, adapting and coping and interacting and presenting were positively related to emotional stability and extraversion, respectively. This work indicates that CDM can be a useful tool when measuring professional competencies through SJTs. CDM can clarify the competencies being measured and provide precise estimates of these competencies.

Quantifying Soiling Loss Directly From PV Yield

DOE PAGES

Deceglie, Michael G.; Micheli, Leonardo; Muller, Matthew

2018-01-23

Soiling of photovoltaic (PV) panels is typically quantified through the use of specialized sensors. Here, we describe and validate a method for estimating soiling loss experienced by PV systems directly from system yield without the need for precipitation data. The method, termed the stochastic rate and recovery (SRR) method, automatically detects soiling intervals in a dataset, then stochastically generates a sample of possible soiling profiles based on the observed characteristics of each interval. In this paper, we describe the method, validate it against soiling station measurements, and compare it with other PV-yield-based soiling estimation methods. The broader application of themore » SRR method will enable the fleet scale assessment of soiling loss to facilitate mitigation planning and risk assessment.« less

Quantifying Soiling Loss Directly From PV Yield

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

Deceglie, Michael G.; Micheli, Leonardo; Muller, Matthew

Soiling of photovoltaic (PV) panels is typically quantified through the use of specialized sensors. Here, we describe and validate a method for estimating soiling loss experienced by PV systems directly from system yield without the need for precipitation data. The method, termed the stochastic rate and recovery (SRR) method, automatically detects soiling intervals in a dataset, then stochastically generates a sample of possible soiling profiles based on the observed characteristics of each interval. In this paper, we describe the method, validate it against soiling station measurements, and compare it with other PV-yield-based soiling estimation methods. The broader application of themore » SRR method will enable the fleet scale assessment of soiling loss to facilitate mitigation planning and risk assessment.« less

Using Ground-Based Measurements and Retrievals to Validate Satellite Data

NASA Technical Reports Server (NTRS)

Dong, Xiquan

2002-01-01

The proposed research is to use the DOE ARM ground-based measurements and retrievals as the ground-truth references for validating satellite cloud results and retrieving algorithms. This validation effort includes four different ways: (1) cloud properties on different satellites, therefore different sensors, TRMM VIRS and TERRA MODIS; (2) cloud properties at different climatic regions, such as DOE ARM SGP, NSA, and TWP sites; (3) different cloud types, low and high level cloud properties; and (4) day and night retrieving algorithms. Validation of satellite-retrieved cloud properties is very difficult and a long-term effort because of significant spatial and temporal differences between the surface and satellite observing platforms. The ground-based measurements and retrievals, only carefully analyzed and validated, can provide a baseline for estimating errors in the satellite products. Even though the validation effort is so difficult, a significant progress has been made during the proposed study period, and the major accomplishments are summarized in the follow.

Comparison of 3 estimation methods of mycophenolic acid AUC based on a limited sampling strategy in renal transplant patients.

PubMed

Hulin, Anne; Blanchet, Benoît; Audard, Vincent; Barau, Caroline; Furlan, Valérie; Durrbach, Antoine; Taïeb, Fabrice; Lang, Philippe; Grimbert, Philippe; Tod, Michel

2009-04-01

A significant relationship between mycophenolic acid (MPA) area under the plasma concentration-time curve (AUC) and the risk for rejection has been reported. Based on 3 concentration measurements, 3 approaches have been proposed for the estimation of MPA AUC, involving either a multilinear regression approach model (MLRA) or a Bayesian estimation using either gamma absorption or zero-order absorption population models. The aim of the study was to compare the 3 approaches for the estimation of MPA AUC in 150 renal transplant patients treated with mycophenolate mofetil and tacrolimus. The population parameters were determined in 77 patients (learning study). The AUC estimation methods were compared in the learning population and in 73 patients from another center (validation study). In the latter study, the reference AUCs were estimated by the trapezoidal rule on 8 measurements. MPA concentrations were measured by liquid chromatography. The gamma absorption model gave the best fit. In the learning study, the AUCs estimated by both Bayesian methods were very similar, whereas the multilinear approach was highly correlated but yielded estimates about 20% lower than Bayesian methods. This resulted in dosing recommendations differing by 250 mg/12 h or more in 27% of cases. In the validation study, AUC estimates based on the Bayesian method with gamma absorption model and multilinear regression approach model were, respectively, 12% higher and 7% lower than the reference values. To conclude, the bicompartmental model with gamma absorption rate gave the best fit. The 3 AUC estimation methods are highly correlated but not concordant. For a given patient, the same estimation method should always be used.

Is Earth-based scaling a valid procedure for calculating heat flows for Mars?

NASA Astrophysics Data System (ADS)

Ruiz, Javier; Williams, Jean-Pierre; Dohm, James M.; Fernández, Carlos; López, Valle

2013-09-01

Heat flow is a very important parameter for constraining the thermal evolution of a planetary body. Several procedures for calculating heat flows for Mars from geophysical or geological proxies have been used, which are valid for the time when the structures used as indicators were formed. The more common procedures are based on estimates of lithospheric strength (the effective elastic thickness of the lithosphere or the depth to the brittle-ductile transition). On the other hand, several works by Kargel and co-workers have estimated martian heat flows from scaling the present-day terrestrial heat flow to Mars, but the so-obtained values are much higher than those deduced from lithospheric strength. In order to explain the discrepancy, a recent paper by Rodriguez et al. (Rodriguez, J.A.P., Kargel, J.S., Tanaka, K.L., Crown, D.A., Berman, D.C., Fairén, A.G., Baker, V.R., Furfaro, R., Candelaria, P., Sasaki, S. [2011]. Icarus 213, 150-194) criticized the heat flow calculations for ancient Mars presented by Ruiz et al. (Ruiz, J., Williams, J.-P., Dohm, J.M., Fernández, C., López, V. [2009]. Icarus 207, 631-637) and other studies calculating ancient martian heat flows from lithospheric strength estimates, and casted doubts on the validity of the results obtained by these works. Here however we demonstrate that the discrepancy is due to computational and conceptual errors made by Kargel and co-workers, and we conclude that the scaling from terrestrial heat flow values is not a valid procedure for estimating reliable heat flows for Mars.

A mathematical method for verifying the validity of measured information about the flows of energy resources based on the state estimation theory

NASA Astrophysics Data System (ADS)

Pazderin, A. V.; Sof'in, V. V.; Samoylenko, V. O.

2015-11-01

Efforts aimed at improving energy efficiency in all branches of the fuel and energy complex shall be commenced with setting up a high-tech automated system for monitoring and accounting energy resources. Malfunctions and failures in the measurement and information parts of this system may distort commercial measurements of energy resources and lead to financial risks for power supplying organizations. In addition, measurement errors may be connected with intentional distortion of measurements for reducing payment for using energy resources on the consumer's side, which leads to commercial loss of energy resource. The article presents a universal mathematical method for verifying the validity of measurement information in networks for transporting energy resources, such as electricity and heat, petroleum, gas, etc., based on the state estimation theory. The energy resource transportation network is represented by a graph the nodes of which correspond to producers and consumers, and its branches stand for transportation mains (power lines, pipelines, and heat network elements). The main idea of state estimation is connected with obtaining the calculated analogs of energy resources for all available measurements. Unlike "raw" measurements, which contain inaccuracies, the calculated flows of energy resources, called estimates, will fully satisfy the suitability condition for all state equations describing the energy resource transportation network. The state equations written in terms of calculated estimates will be already free from residuals. The difference between a measurement and its calculated analog (estimate) is called in the estimation theory an estimation remainder. The obtained large values of estimation remainders are an indicator of high errors of particular energy resource measurements. By using the presented method it is possible to improve the validity of energy resource measurements, to estimate the transportation network observability, to eliminate the energy resource flows measurement imbalances, and to filter invalid measurements at the data acquisition and processing stage in performing monitoring of an automated energy resource monitoring and accounting system.

Application of a mechanistic model as a tool for on-line monitoring of pilot scale filamentous fungal fermentation processes-The importance of evaporation effects.

PubMed

Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Sin, Gürkan; Gernaey, Krist V

2017-03-01

A mechanistic model-based soft sensor is developed and validated for 550L filamentous fungus fermentations operated at Novozymes A/S. The soft sensor is comprised of a parameter estimation block based on a stoichiometric balance, coupled to a dynamic process model. The on-line parameter estimation block models the changing rates of formation of product, biomass, and water, and the rate of consumption of feed using standard, available on-line measurements. This parameter estimation block, is coupled to a mechanistic process model, which solves the current states of biomass, product, substrate, dissolved oxygen and mass, as well as other process parameters including k L a, viscosity and partial pressure of CO 2 . State estimation at this scale requires a robust mass model including evaporation, which is a factor not often considered at smaller scales of operation. The model is developed using a historical data set of 11 batches from the fermentation pilot plant (550L) at Novozymes A/S. The model is then implemented on-line in 550L fermentation processes operated at Novozymes A/S in order to validate the state estimator model on 14 new batches utilizing a new strain. The product concentration in the validation batches was predicted with an average root mean sum of squared error (RMSSE) of 16.6%. In addition, calculation of the Janus coefficient for the validation batches shows a suitably calibrated model. The robustness of the model prediction is assessed with respect to the accuracy of the input data. Parameter estimation uncertainty is also carried out. The application of this on-line state estimator allows for on-line monitoring of pilot scale batches, including real-time estimates of multiple parameters which are not able to be monitored on-line. With successful application of a soft sensor at this scale, this allows for improved process monitoring, as well as opening up further possibilities for on-line control algorithms, utilizing these on-line model outputs. Biotechnol. Bioeng. 2017;114: 589-599. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

On validation of the rain climatic zone designations for Nigeria

NASA Astrophysics Data System (ADS)

Obiyemi, O. O.; Ibiyemi, T. S.; Ojo, J. S.

2017-07-01

In this paper, validation of rain climatic zone classifications for Nigeria is presented based on global radio-climatic models by the International Telecommunication Union-Radiocommunication (ITU-R) and Crane. Rain rate estimates deduced from several ground-based measurements and those earlier estimated from the precipitation index on the Tropical Rain Measurement Mission (TRMM) were employed for the validation exercise. Although earlier classifications indicated that Nigeria falls into zones P, Q, N, and K for the ITU-R designations, and zones E and H for Crane's climatic zone designations, the results however confirmed that the rain climatic zones across Nigeria can only be classified into four, namely P, Q, M, and N for the ITU-R designations, while the designations by Crane exhibited only three zones, namely E, G, and H. The ITU-R classification was found to be more suitable for planning microwave and millimeter wave links across Nigeria. The research outcomes are vital in boosting the confidence level of system designers in using the ITU-R designations as presented in the map developed for the rain zone designations for estimating the attenuation induced by rain along satellite and terrestrial microwave links over Nigeria.

Policy evaluation in diabetes prevention and treatment using a population-based macro simulation model: the MICADO model.

PubMed

van der Heijden, A A W A; Feenstra, T L; Hoogenveen, R T; Niessen, L W; de Bruijne, M C; Dekker, J M; Baan, C A; Nijpels, G

2015-12-01

To test a simulation model, the MICADO model, for estimating the long-term effects of interventions in people with and without diabetes. The MICADO model includes micro- and macrovascular diseases in relation to their risk factors. The strengths of this model are its population scope and the possibility to assess parameter uncertainty using probabilistic sensitivity analyses. Outcomes include incidence and prevalence of complications, quality of life, costs and cost-effectiveness. We externally validated MICADO's estimates of micro- and macrovascular complications in a Dutch cohort with diabetes (n = 498,400) by comparing these estimates with national and international empirical data. For the annual number of people undergoing amputations, MICADO's estimate was 592 (95% interquantile range 291-842), which compared well with the registered number of people with diabetes-related amputations in the Netherlands (728). The incidence of end-stage renal disease estimated using the MICADO model was 247 people (95% interquartile range 120-363), which was also similar to the registered incidence in the Netherlands (277 people). MICADO performed well in the validation of macrovascular outcomes of population-based cohorts, while it had more difficulty in reflecting a highly selected trial population. Validation by comparison with independent empirical data showed that the MICADO model simulates the natural course of diabetes and its micro- and macrovascular complications well. As a population-based model, MICADO can be applied for projections as well as scenario analyses to evaluate the long-term (cost-)effectiveness of population-level interventions targeting diabetes and its complications in the Netherlands or similar countries. © 2015 The Authors. Diabetic Medicine © 2015 Diabetes UK.

Validation of a Formula for Assigning Continuing Education Credit to Printed Home Study Courses

PubMed Central

Hanson, Alan L.

2007-01-01

Objectives To reevaluate and validate the use of a formula for calculating the amount of continuing education credit to be awarded for printed home study courses. Methods Ten home study courses were selected for inclusion in a study to validate the formula, which is based on the number of words, number of final examination questions, and estimated difficulty level of the course. The amount of estimated credit calculated using the a priori formula was compared to the average amount of time required to complete each article based on pharmacists' self-reporting. Results A strong positive relationship between the amount of time required to complete the home study courses based on the a priori calculation and the times reported by pharmacists completing the 10 courses was found (p < 0.001). The correlation accounted for 86.2% of the total variability in the average pharmacist reported completion times (p < 0.001). Conclusions The formula offers an efficient and accurate means of determining the amount of continuing education credit that should be assigned to printed home study courses. PMID:19503705

A conceptual guide to detection probability for point counts and other count-based survey methods

Treesearch

D. Archibald McCallum

2005-01-01

Accurate and precise estimates of numbers of animals are vitally needed both to assess population status and to evaluate management decisions. Various methods exist for counting birds, but most of those used with territorial landbirds yield only indices, not true estimates of population size. The need for valid density estimates has spawned a number of models for...

Validating the use of 137Cs and 210Pbex measurements to estimate rates of soil loss from cultivated land in southern Italy.

PubMed

Porto, Paolo; Walling, Des E

2012-04-01

Soil erosion represents an important threat to the long-term sustainability of agriculture and forestry in many areas of the world, including southern Italy. Numerous models and prediction procedures have been developed to estimate rates of soil loss and soil redistribution, based on the local topography, hydrometeorology, soil type and land management. However, there remains an important need for empirical measurements to provide a basis for validating and calibrating such models and prediction procedures as well as to support specific investigations and experiments. In this context, erosion plots provide useful information on gross rates of soil loss, but are unable to document the efficiency of the onward transfer of the eroded sediment within a field and towards the stream system, and thus net rates of soil loss from larger areas. The use of environmental radionuclides, particularly caesium-137 ((137)Cs) and excess lead-210 ((210)Pb(ex)), as a means of estimating rates of soil erosion and deposition has attracted increasing attention in recent years and the approach has now been recognised as possessing several important advantages. In order to provide further confirmation of the validity of the estimates of longer-term erosion and soil redistribution rates provided by (137)Cs and (210)Pb(ex) measurements, there is a need for studies aimed explicitly at validating the results obtained. In this context, the authors directed attention to the potential offered by a set of small erosion plots located near Reggio Calabria in southern Italy, for validating estimates of soil loss provided by (137)Cs and (210)Pb(ex) measurements. A preliminary assessment suggested that, notwithstanding the limitations and constraints involved, a worthwhile investigation aimed at validating the use of (137)Cs and (210)Pb(ex) measurements to estimate rates of soil loss from cultivated land could be undertaken. The results demonstrate a close consistency between the measured rates of soil loss and the estimates provided by the (137)Cs and (210)Pb(ex) measurements and can therefore been seen as validating the use of these fallout radionuclides to document soil erosion rates in that environment. Further studies are clearly required to exploit other opportunities for validation in contrasting environments and under different land use conditions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Position Estimation for Switched Reluctance Motor Based on the Single Threshold Angle

NASA Astrophysics Data System (ADS)

Zhang, Lei; Li, Pang; Yu, Yue

2017-05-01

This paper presents a position estimate model of switched reluctance motor based on the single threshold angle. In view of the relationship of between the inductance and rotor position, the position is estimated by comparing the real-time dynamic flux linkage with the threshold angle position flux linkage (7.5° threshold angle, 12/8SRM). The sensorless model is built by Maltab/Simulink, the simulation are implemented under the steady state and transient state different condition, and verified its validity and feasibility of the method..

Evolving Improvements to TRMM Ground Validation Rainfall Estimates

NASA Technical Reports Server (NTRS)

Robinson, M.; Kulie, M. S.; Marks, D. A.; Wolff, D. B.; Ferrier, B. S.; Amitai, E.; Silberstein, D. S.; Fisher, B. L.; Wang, J.; Einaudi, Franco (Technical Monitor)

2000-01-01

The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. Since the successful 1997 launch of the TRMM satellite, GV rainfall estimates have demonstrated systematic improvements directly related to improved radar and rain gauge data, modified science techniques, and software revisions. Improved rainfall estimates have resulted in higher quality GV rainfall products and subsequently, much improved evaluation products for the satellite-based precipitation estimates from TRMM. This presentation will demonstrate how TRMM GV rainfall products created in a semi-automated, operational environment have evolved and improved through successive generations. Monthly rainfall maps and rainfall accumulation statistics for each primary site will be presented for each stage of GV product development. Contributions from individual product modifications involving radar reflectivity (Ze)-rain rate (R) relationship refinements, improvements in rain gauge bulk-adjustment and data quality control processes, and improved radar and gauge data will be discussed. Finally, it will be demonstrated that as GV rainfall products have improved, rainfall estimation comparisons between GV and satellite have converged, lending confidence to the satellite-derived precipitation measurements from TRMM.

Natural Forest Biomass Estimation Based on Plantation Information Using PALSAR Data

PubMed Central

Avtar, Ram; Suzuki, Rikie; Sawada, Haruo

2014-01-01

Forests play a vital role in terrestrial carbon cycling; therefore, monitoring forest biomass at local to global scales has become a challenging issue in the context of climate change. In this study, we investigated the backscattering properties of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data in cashew and rubber plantation areas of Cambodia. The PALSAR backscattering coefficient (σ0) had different responses in the two plantation types because of differences in biophysical parameters. The PALSAR σ0 showed a higher correlation with field-based measurements and lower saturation in cashew plants compared with rubber plants. Multiple linear regression (MLR) models based on field-based biomass of cashew (C-MLR) and rubber (R-MLR) plants with PALSAR σ0 were created. These MLR models were used to estimate natural forest biomass in Cambodia. The cashew plant-based MLR model (C-MLR) produced better results than the rubber plant-based MLR model (R-MLR). The C-MLR-estimated natural forest biomass was validated using forest inventory data for natural forests in Cambodia. The validation results showed a strong correlation (R2 = 0.64) between C-MLR-estimated natural forest biomass and field-based biomass, with RMSE  = 23.2 Mg/ha in deciduous forests. In high-biomass regions, such as dense evergreen forests, this model had a weaker correlation because of the high biomass and the multiple-story tree structure of evergreen forests, which caused saturation of the PALSAR signal. PMID:24465908

Assessment of dietary sodium intake using a food frequency questionnaire and 24-hour urinary sodium excretion: a systematic literature review.

PubMed

McLean, Rachael M; Farmer, Victoria L; Nettleton, Alice; Cameron, Claire M; Cook, Nancy R; Campbell, Norman R C

2017-12-01

Food frequency questionnaires (FFQs) are often used to assess dietary sodium intake, although 24-hour urinary excretion is the most accurate measure of intake. The authors conducted a systematic review to investigate whether FFQs are a reliable and valid way of measuring usual dietary sodium intake. Results from 18 studies are described in this review, including 16 validation studies. The methods of study design and analysis varied widely with respect to FFQ instrument, number of 24-hour urine collections collected per participant, methods used to assess completeness of urine collections, and statistical analysis. Overall, there was poor agreement between estimates from FFQ and 24-hour urine. The authors suggest a framework for validation and reporting based on a consensus statement (2004), and recommend that all FFQs used to estimate dietary sodium intake undergo validation against multiple 24-hour urine collections. ©2017 Wiley Periodicals, Inc.

Optimal combining of ground-based sensors for the purpose of validating satellite-based rainfall estimates

NASA Technical Reports Server (NTRS)

Krajewski, Witold F.; Rexroth, David T.; Kiriaki, Kiriakie

1991-01-01

Two problems related to radar rainfall estimation are described. The first part is a description of a preliminary data analysis for the purpose of statistical estimation of rainfall from multiple (radar and raingage) sensors. Raingage, radar, and joint radar-raingage estimation is described, and some results are given. Statistical parameters of rainfall spatial dependence are calculated and discussed in the context of optimal estimation. Quality control of radar data is also described. The second part describes radar scattering by ellipsoidal raindrops. An analytical solution is derived for the Rayleigh scattering regime. Single and volume scattering are presented. Comparison calculations with the known results for spheres and oblate spheroids are shown.

[Estimating heavy metal concentrations in topsoil from vegetation reflectance spectra of Hyperion images: A case study of Yushu County, Qinghai, China.

PubMed

Yang, Ling Yu; Gao, Xiao Hong; Zhang, Wei; Shi, Fei Fei; He, Lin Hua; Jia, Wei

2016-06-01

In this study, we explored the feasibility of estimating the soil heavy metal concentrations using the hyperspectral satellite image. The concentration of As, Pb, Zn and Cd elements in 48 topsoil samples collected from the field in Yushu County of the Sanjiangyuan regions was measured in the laboratory. We then extracted 176 vegetation spectral reflectance bands of 48 soil samples as well as five vegetation indices from two Hyperion images. Following that, the partial least squares regression (PLSR) method was employed to estimate the soil heavy metal concentrations using the above two independent sets of Hyperion-derived variables, separately constructed the estimation model between the 176 vegetation spectral reflectance bands and the soil heavy metal concentrations (called the vegetation spectral reflectance-based estimation model), and between the five vegetation indices being used as the independent variable and the soil heavy metal concentrations (called synthetic vegetation index-based estimation model). Using RPD (the ratio of standard deviation from the 4 heavy metals measured values of the validation samples to RMSE) as the validation criteria, the RPDs of As and Pb concentrations from the two models were both less than 1.4, which suggested that both models were incapable of roughly estimating As and Pb concentrations; whereas the RPDs of Zn and Cd were 1.53, 1.46 and 1.46, 1.42, respectively, which implied that both models had the ability for rough estimation of Zn and Cd concentrations. Based on those results, the vegetation spectral-based estimation model was selected to obtain the spatial distribution map of Zn concentration in combination with the Hyperion image. The estimated Zn map showed that the zones with high Zn concentrations were distributed near the provincial road 308, national road 214 and towns, which could be influenced by human activities. Our study proved that the spectral reflectance of Hyperion image was useful in estimating the soil concentrations of Zn and Cd.

Human papillomavirus (HPV) vaccination coverage in young Australian women is higher than previously estimated: independent estimates from a nationally representative mobile phone survey.

PubMed

Brotherton, Julia M L; Liu, Bette; Donovan, Basil; Kaldor, John M; Saville, Marion

2014-01-23

Accurate estimates of coverage are essential for estimating the population effectiveness of human papillomavirus (HPV) vaccination. Australia has a purpose built National HPV Vaccination Program Register for monitoring coverage, however notification of doses administered to young women in the community during the national catch-up program (2007-2009) was not compulsory. In 2011, we undertook a population-based mobile phone survey of young women to independently estimate HPV vaccination coverage. Randomly generated mobile phone numbers were dialed to recruit women aged 22-30 (age eligible for HPV vaccination) to complete a computer assisted telephone interview. Consent was sought to validate self reported HPV vaccination status against the national register. Coverage rates were calculated based on self report and weighted to the age and state of residence structure of the Australian female population. These were compared with coverage estimates from the register using Australian Bureau of Statistics estimated resident populations as the denominator. Among the 1379 participants, the national estimate for self reported HPV vaccination coverage for doses 1/2/3, respectively, weighted for age and state of residence, was 64/59/53%. This compares with coverage of 55/45/32% and 49/40/28% based on register records, using 2007 and 2011 population data as the denominators respectively. Some significant differences in coverage between the states were identified. 20% (223) of women returned a consent form allowing validation of doses against the register and provider records: among these women 85.6% (538) of self reported doses were confirmed. We confirmed that coverage rates for young women vaccinated in the community (at age 18-26 years) are underestimated by the national register and that under-notification is greater for second and third doses. Using 2011 population estimates, rather than estimates contemporaneous with the program rollout, reduces register-based coverage estimates further because of large population increases due to immigration since the program. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analyzing self-controlled case series data when case confirmation rates are estimated from an internal validation sample.

PubMed

Xu, Stanley; Clarke, Christina L; Newcomer, Sophia R; Daley, Matthew F; Glanz, Jason M

2018-05-16

Vaccine safety studies are often electronic health record (EHR)-based observational studies. These studies often face significant methodological challenges, including confounding and misclassification of adverse event. Vaccine safety researchers use self-controlled case series (SCCS) study design to handle confounding effect and employ medical chart review to ascertain cases that are identified using EHR data. However, for common adverse events, limited resources often make it impossible to adjudicate all adverse events observed in electronic data. In this paper, we considered four approaches for analyzing SCCS data with confirmation rates estimated from an internal validation sample: (1) observed cases, (2) confirmed cases only, (3) known confirmation rate, and (4) multiple imputation (MI). We conducted a simulation study to evaluate these four approaches using type I error rates, percent bias, and empirical power. Our simulation results suggest that when misclassification of adverse events is present, approaches such as observed cases, confirmed case only, and known confirmation rate may inflate the type I error, yield biased point estimates, and affect statistical power. The multiple imputation approach considers the uncertainty of estimated confirmation rates from an internal validation sample, yields a proper type I error rate, largely unbiased point estimate, proper variance estimate, and statistical power. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Head movement compensation in real-time magnetoencephalographic recordings.

PubMed

Little, Graham; Boe, Shaun; Bardouille, Timothy

2014-01-01

Neurofeedback- and brain-computer interface (BCI)-based interventions can be implemented using real-time analysis of magnetoencephalographic (MEG) recordings. Head movement during MEG recordings, however, can lead to inaccurate estimates of brain activity, reducing the efficacy of the intervention. Most real-time applications in MEG have utilized analyses that do not correct for head movement. Effective means of correcting for head movement are needed to optimize the use of MEG in such applications. Here we provide preliminary validation of a novel analysis technique, real-time source estimation (rtSE), that measures head movement and generates corrected current source time course estimates in real-time. rtSE was applied while recording a calibrated phantom to determine phantom position localization accuracy and source amplitude estimation accuracy under stationary and moving conditions. Results were compared to off-line analysis methods to assess validity of the rtSE technique. The rtSE method allowed for accurate estimation of current source activity at the source-level in real-time, and accounted for movement of the source due to changes in phantom position. The rtSE technique requires modifications and specialized analysis of the following MEG work flow steps.•Data acquisition•Head position estimation•Source localization•Real-time source estimation This work explains the technical details and validates each of these steps.

A Simple Tool for Diet Evaluation in Primary Health Care: Validation of a 16-Item Food Intake Questionnaire

PubMed Central

Hemiö, Katri; Pölönen, Auli; Ahonen, Kirsti; Kosola, Mikko; Viitasalo, Katriina; Lindström, Jaana

2014-01-01

Our aim was to validate a 16-item food intake questionnaire (16-FIQ) and create an easy to use method to estimate patients’ nutrient intake in primary health care. Participants (52 men, 25 women) completed a 7-day food record and a 16-FIQ. Food and nutrient intakes were calculated and compared using Spearman correlation. Further, nutrient intakes were compared using kappa-statistics and exact and opposite agreement of intake tertiles. The results indicated that the 16-FIQ reliably categorized individuals according to their nutrient intakes. Methods to estimate nutrient intake based on the answers given in 16-FIQ were created. In linear regression models nutrient intake estimates from the food records were used as the dependent variables and sum variables derived from the 16-FIQ were used as the independent variables. Valid regression models were created for the energy proportion of fat, saturated fat, and sucrose and the amount of fibre (g), vitamin C (mg), iron (mg), and vitamin D (μg) intake. The 16-FIQ is a valid method for estimating nutrient intakes in group level. In addition, the 16-FIQ could be a useful tool to facilitate identification of people in need of dietary counselling and to monitor the effect of counselling in primary health care. PMID:24599042

Modeling apple surface temperature dynamics based on weather data.

PubMed

Li, Lei; Peters, Troy; Zhang, Qin; Zhang, Jingjin; Huang, Danfeng

2014-10-27

The exposure of fruit surfaces to direct sunlight during the summer months can result in sunburn damage. Losses due to sunburn damage are a major economic problem when marketing fresh apples. The objective of this study was to develop and validate a model for simulating fruit surface temperature (FST) dynamics based on energy balance and measured weather data. A series of weather data (air temperature, humidity, solar radiation, and wind speed) was recorded for seven hours between 11:00-18:00 for two months at fifteen minute intervals. To validate the model, the FSTs of "Fuji" apples were monitored using an infrared camera in a natural orchard environment. The FST dynamics were measured using a series of thermal images. For the apples that were completely exposed to the sun, the RMSE of the model for estimating FST was less than 2.0 °C. A sensitivity analysis of the emissivity of the apple surface and the conductance of the fruit surface to water vapour showed that accurate estimations of the apple surface emissivity were important for the model. The validation results showed that the model was capable of accurately describing the thermal performances of apples under different solar radiation intensities. Thus, this model could be used to more accurately estimate the FST relative to estimates that only consider the air temperature. In addition, this model provides useful information for sunburn protection management.

Modeling Apple Surface Temperature Dynamics Based on Weather Data

PubMed Central

Li, Lei; Peters, Troy; Zhang, Qin; Zhang, Jingjin; Huang, Danfeng

2014-01-01

The exposure of fruit surfaces to direct sunlight during the summer months can result in sunburn damage. Losses due to sunburn damage are a major economic problem when marketing fresh apples. The objective of this study was to develop and validate a model for simulating fruit surface temperature (FST) dynamics based on energy balance and measured weather data. A series of weather data (air temperature, humidity, solar radiation, and wind speed) was recorded for seven hours between 11:00–18:00 for two months at fifteen minute intervals. To validate the model, the FSTs of “Fuji” apples were monitored using an infrared camera in a natural orchard environment. The FST dynamics were measured using a series of thermal images. For the apples that were completely exposed to the sun, the RMSE of the model for estimating FST was less than 2.0 °C. A sensitivity analysis of the emissivity of the apple surface and the conductance of the fruit surface to water vapour showed that accurate estimations of the apple surface emissivity were important for the model. The validation results showed that the model was capable of accurately describing the thermal performances of apples under different solar radiation intensities. Thus, this model could be used to more accurately estimate the FST relative to estimates that only consider the air temperature. In addition, this model provides useful information for sunburn protection management. PMID:25350507

Measurement of acoustic velocity components in a turbulent flow using LDV and high-repetition rate PIV

NASA Astrophysics Data System (ADS)

Léon, Olivier; Piot, Estelle; Sebbane, Delphine; Simon, Frank

2017-06-01

The present study provides theoretical details and experimental validation results to the approach proposed by Minotti et al. (Aerosp Sci Technol 12(5):398-407, 2008) for measuring amplitudes and phases of acoustic velocity components (AVC) that are waveform parameters of each component of velocity induced by an acoustic wave, in fully turbulent duct flows carrying multi-tone acoustic waves. Theoretical results support that the turbulence rejection method proposed, based on the estimation of cross power spectra between velocity measurements and a reference signal such as a wall pressure measurement, provides asymptotically efficient estimators with respect to the number of samples. Furthermore, it is shown that the estimator uncertainties can be simply estimated, accounting for the characteristics of the measured flow turbulence spectra. Two laser-based measurement campaigns were conducted in order to validate the acoustic velocity estimation approach and the uncertainty estimates derived. While in previous studies estimates were obtained using laser Doppler velocimetry (LDV), it is demonstrated that high-repetition rate particle image velocimetry (PIV) can also be successfully employed. The two measurement techniques provide very similar acoustic velocity amplitude and phase estimates for the cases investigated, that are of practical interest for acoustic liner studies. In a broader sense, this approach may be beneficial for non-intrusive sound emission studies in wind tunnel testings.

Decorrelation of the true and estimated classifier errors in high-dimensional settings.

PubMed

Hanczar, Blaise; Hua, Jianping; Dougherty, Edward R

2007-01-01

The aim of many microarray experiments is to build discriminatory diagnosis and prognosis models. Given the huge number of features and the small number of examples, model validity which refers to the precision of error estimation is a critical issue. Previous studies have addressed this issue via the deviation distribution (estimated error minus true error), in particular, the deterioration of cross-validation precision in high-dimensional settings where feature selection is used to mitigate the peaking phenomenon (overfitting). Because classifier design is based upon random samples, both the true and estimated errors are sample-dependent random variables, and one would expect a loss of precision if the estimated and true errors are not well correlated, so that natural questions arise as to the degree of correlation and the manner in which lack of correlation impacts error estimation. We demonstrate the effect of correlation on error precision via a decomposition of the variance of the deviation distribution, observe that the correlation is often severely decreased in high-dimensional settings, and show that the effect of high dimensionality on error estimation tends to result more from its decorrelating effects than from its impact on the variance of the estimated error. We consider the correlation between the true and estimated errors under different experimental conditions using both synthetic and real data, several feature-selection methods, different classification rules, and three error estimators commonly used (leave-one-out cross-validation, k-fold cross-validation, and .632 bootstrap). Moreover, three scenarios are considered: (1) feature selection, (2) known-feature set, and (3) all features. Only the first is of practical interest; however, the other two are needed for comparison purposes. We will observe that the true and estimated errors tend to be much more correlated in the case of a known feature set than with either feature selection or using all features, with the better correlation between the latter two showing no general trend, but differing for different models.

URANS simulations of the tip-leakage cavitating flow with verification and validation procedures

NASA Astrophysics Data System (ADS)

Cheng, Huai-yu; Long, Xin-ping; Liang, Yun-zhi; Long, Yun; Ji, Bin

2018-04-01

In the present paper, the Vortex Identified Zwart-Gerber-Belamri (VIZGB) cavitation model coupled with the SST-CC turbulence model is used to investigate the unsteady tip-leakage cavitating flow induced by a NACA0009 hydrofoil. A qualitative comparison between the numerical and experimental results is made. In order to quantitatively evaluate the reliability of the numerical data, the verification and validation (V&V) procedures are used in the present paper. Errors of numerical results are estimated with seven error estimators based on the Richardson extrapolation method. It is shown that though a strict validation cannot be achieved, a reasonable prediction of the gross characteristics of the tip-leakage cavitating flow can be obtained. Based on the numerical results, the influence of the cavitation on the tip-leakage vortex (TLV) is discussed, which indicates that the cavitation accelerates the fusion of the TLV and the tip-separation vortex (TSV). Moreover, the trajectory of the TLV, when the cavitation occurs, is close to the side wall.

Validity test and its consistency in the construction of patient loyalty model

NASA Astrophysics Data System (ADS)

Yanuar, Ferra

2016-04-01

The main objective of this present study is to demonstrate the estimation of validity values and its consistency based on structural equation model. The method of estimation was then implemented to an empirical data in case of the construction the patient loyalty model. In the hypothesis model, service quality, patient satisfaction and patient loyalty were determined simultaneously, each factor were measured by any indicator variables. The respondents involved in this study were the patients who ever got healthcare at Puskesmas in Padang, West Sumatera. All 394 respondents who had complete information were included in the analysis. This study found that each construct; service quality, patient satisfaction and patient loyalty were valid. It means that all hypothesized indicator variables were significant to measure their corresponding latent variable. Service quality is the most measured by tangible, patient satisfaction is the most mesured by satisfied on service and patient loyalty is the most measured by good service quality. Meanwhile in structural equation, this study found that patient loyalty was affected by patient satisfaction positively and directly. Service quality affected patient loyalty indirectly with patient satisfaction as mediator variable between both latent variables. Both structural equations were also valid. This study also proved that validity values which obtained here were also consistence based on simulation study using bootstrap approach.

Toward quantitative estimation of material properties with dynamic mode atomic force microscopy: a comparative study.

PubMed

Ghosal, Sayan; Gannepalli, Anil; Salapaka, Murti

2017-08-11

In this article, we explore methods that enable estimation of material properties with the dynamic mode atomic force microscopy suitable for soft matter investigation. The article presents the viewpoint of casting the system, comprising of a flexure probe interacting with the sample, as an equivalent cantilever system and compares a steady-state analysis based method with a recursive estimation technique for determining the parameters of the equivalent cantilever system in real time. The steady-state analysis of the equivalent cantilever model, which has been implicitly assumed in studies on material property determination, is validated analytically and experimentally. We show that the steady-state based technique yields results that quantitatively agree with the recursive method in the domain of its validity. The steady-state technique is considerably simpler to implement, however, slower compared to the recursive technique. The parameters of the equivalent system are utilized to interpret storage and dissipative properties of the sample. Finally, the article identifies key pitfalls that need to be avoided toward the quantitative estimation of material properties.

Noise stochastic corrected maximum a posteriori estimator for birefringence imaging using polarization-sensitive optical coherence tomography

PubMed Central

Kasaragod, Deepa; Makita, Shuichi; Hong, Young-Joo; Yasuno, Yoshiaki

2017-01-01

This paper presents a noise-stochastic corrected maximum a posteriori estimator for birefringence imaging using Jones matrix optical coherence tomography. The estimator described in this paper is based on the relationship between probability distribution functions of the measured birefringence and the effective signal to noise ratio (ESNR) as well as the true birefringence and the true ESNR. The Monte Carlo method is used to numerically describe this relationship and adaptive 2D kernel density estimation provides the likelihood for a posteriori estimation of the true birefringence. Improved estimation is shown for the new estimator with stochastic model of ESNR in comparison to the old estimator, both based on the Jones matrix noise model. A comparison with the mean estimator is also done. Numerical simulation validates the superiority of the new estimator. The superior performance of the new estimator was also shown by in vivo measurement of optic nerve head. PMID:28270974

NMR permeability estimators in 'chalk' carbonate rocks obtained under different relaxation times and MICP size scalings

NASA Astrophysics Data System (ADS)

Rios, Edmilson Helton; Figueiredo, Irineu; Moss, Adam Keith; Pritchard, Timothy Neil; Glassborow, Brent Anthony; Guedes Domingues, Ana Beatriz; Bagueira de Vasconcellos Azeredo, Rodrigo

2016-07-01

The effect of the selection of different nuclear magnetic resonance (NMR) relaxation times for permeability estimation is investigated for a set of fully brine-saturated rocks acquired from Cretaceous carbonate reservoirs in the North Sea and Middle East. Estimators that are obtained from the relaxation times based on the Pythagorean means are compared with estimators that are obtained from the relaxation times based on the concept of a cumulative saturation cut-off. Select portions of the longitudinal (T1) and transverse (T2) relaxation-time distributions are systematically evaluated by applying various cut-offs, analogous to the Winland-Pittman approach for mercury injection capillary pressure (MICP) curves. Finally, different approaches to matching the NMR and MICP distributions using different mean-based scaling factors are validated based on the performance of the related size-scaled estimators. The good results that were obtained demonstrate possible alternatives to the commonly adopted logarithmic mean estimator and reinforce the importance of NMR-MICP integration to improving carbonate permeability estimates.

Development and validation of a Markov microsimulation model for the economic evaluation of treatments in osteoporosis.

PubMed

Hiligsmann, Mickaël; Ethgen, Olivier; Bruyère, Olivier; Richy, Florent; Gathon, Henry-Jean; Reginster, Jean-Yves

2009-01-01

Markov models are increasingly used in economic evaluations of treatments for osteoporosis. Most of the existing evaluations are cohort-based Markov models missing comprehensive memory management and versatility. In this article, we describe and validate an original Markov microsimulation model to accurately assess the cost-effectiveness of prevention and treatment of osteoporosis. We developed a Markov microsimulation model with a lifetime horizon and a direct health-care cost perspective. The patient history was recorded and was used in calculations of transition probabilities, utilities, and costs. To test the internal consistency of the model, we carried out an example calculation for alendronate therapy. Then, external consistency was investigated by comparing absolute lifetime risk of fracture estimates with epidemiologic data. For women at age 70 years, with a twofold increase in the fracture risk of the average population, the costs per quality-adjusted life-year gained for alendronate therapy versus no treatment were estimated at €9105 and €15,325, respectively, under full and realistic adherence assumptions. All the sensitivity analyses in terms of model parameters and modeling assumptions were coherent with expected conclusions and absolute lifetime risk of fracture estimates were within the range of previous estimates, which confirmed both internal and external consistency of the model. Microsimulation models present some major advantages over cohort-based models, increasing the reliability of the results and being largely compatible with the existing state of the art, evidence-based literature. The developed model appears to be a valid model for use in economic evaluations in osteoporosis.

Geographic Model and Biomarker-Derived Measures of Pesticide Exposure and Parkinson’s Disease

PubMed Central

RITZ, BEATE; COSTELLO, SADIE

2013-01-01

For more than two decades, reports have suggested that pesticides and herbicides may be an etiologic factor in idiopathic Parkinson’s disease (PD). To date, no clear associations with any specific pesticide have been demonstrated from epidemiological studies perhaps, in part, because methods of reliably estimating exposures are lacking. We tested the validity of a Geographic Information Systems (GIS)-based exposure assessment model that estimates potential environmental exposures at residences from pesticide applications to agricultural crops based on California Pesticide Use Reports (PUR). Using lipid-adjusted dichlorodiphenyldichloroethylene (DDE) serum levels as the “gold standard” for pesticide exposure, we conducted a validation study in a sample taken from an ongoing, population-based case–control study of PD in Central California. Residential, occupational, and other risk factor data were collected for 22 cases and 24 controls from Kern county, California. Environmental GIS–PUR-based organochlorine (OC) estimates were derived for each subject and compared to lipid-adjusted DDE serum levels. Relying on a linear regression model, we predicted log-transformed lipid-adjusted DDE serum levels. GIS–PUR-derived OC measure, body mass index, age, gender, mixing and loading pesticides by hand, and using pesticides in the home, together explained 47% of the DDE serum level variance (adjusted r2 = 0.47). The specificity of using our environmental GIS–PUR-derived OC measures to identify those with high-serum DDE levels was reasonably good (87%). Our environmental GIS–PUR-based approach appears to provide a valid model for assessing residential exposures to agricultural pesticides. PMID:17119217

A systematic review of validated methods for identifying anaphylaxis, including anaphylactic shock and angioneurotic edema, using administrative and claims data.

PubMed

Schneider, Gary; Kachroo, Sumesh; Jones, Natalie; Crean, Sheila; Rotella, Philip; Avetisyan, Ruzan; Reynolds, Matthew W

2012-01-01

The Food and Drug Administration's Mini-Sentinel pilot program initially aims to conduct active surveillance to refine safety signals that emerge for marketed medical products. A key facet of this surveillance is to develop and understand the validity of algorithms for identifying health outcomes of interest from administrative and claims data. This article summarizes the process and findings of the algorithm review of anaphylaxis. PubMed and Iowa Drug Information Service searches were conducted to identify citations applicable to the anaphylaxis health outcome of interest. Level 1 abstract reviews and Level 2 full-text reviews were conducted to find articles using administrative and claims data to identify anaphylaxis and including validation estimates of the coding algorithms. Our search revealed limited literature focusing on anaphylaxis that provided administrative and claims data-based algorithms and validation estimates. Only four studies identified via literature searches provided validated algorithms; however, two additional studies were identified by Mini-Sentinel collaborators and were incorporated. The International Classification of Diseases, Ninth Revision, codes varied, as did the positive predictive value, depending on the cohort characteristics and the specific codes used to identify anaphylaxis. Research needs to be conducted on designing validation studies to test anaphylaxis algorithms and estimating their predictive power, sensitivity, and specificity. Copyright © 2012 John Wiley & Sons, Ltd.

Deflection-Based Aircraft Structural Loads Estimation with Comparison to Flight

NASA Technical Reports Server (NTRS)

Lizotte, Andrew M.; Lokos, William A.

2005-01-01

Traditional techniques in structural load measurement entail the correlation of a known load with strain-gage output from the individual components of a structure or machine. The use of strain gages has proved successful and is considered the standard approach for load measurement. However, remotely measuring aerodynamic loads using deflection measurement systems to determine aeroelastic deformation as a substitute to strain gages may yield lower testing costs while improving aircraft performance through reduced instrumentation weight. With a reliable strain and structural deformation measurement system this technique was examined. The objective of this study was to explore the utility of a deflection-based load estimation, using the active aeroelastic wing F/A-18 aircraft. Calibration data from ground tests performed on the aircraft were used to derive left wing-root and wing-fold bending-moment and torque load equations based on strain gages, however, for this study, point deflections were used to derive deflection-based load equations. Comparisons between the strain-gage and deflection-based methods are presented. Flight data from the phase-1 active aeroelastic wing flight program were used to validate the deflection-based load estimation method. Flight validation revealed a strong bending-moment correlation and slightly weaker torque correlation. Development of current techniques, and future studies are discussed.

Deflection-Based Structural Loads Estimation From the Active Aeroelastic Wing F/A-18 Aircraft

NASA Technical Reports Server (NTRS)

Lizotte, Andrew M.; Lokos, William A.

2005-01-01

Traditional techniques in structural load measurement entail the correlation of a known load with strain-gage output from the individual components of a structure or machine. The use of strain gages has proved successful and is considered the standard approach for load measurement. However, remotely measuring aerodynamic loads using deflection measurement systems to determine aeroelastic deformation as a substitute to strain gages may yield lower testing costs while improving aircraft performance through reduced instrumentation weight. This technique was examined using a reliable strain and structural deformation measurement system. The objective of this study was to explore the utility of a deflection-based load estimation, using the active aeroelastic wing F/A-18 aircraft. Calibration data from ground tests performed on the aircraft were used to derive left wing-root and wing-fold bending-moment and torque load equations based on strain gages, however, for this study, point deflections were used to derive deflection-based load equations. Comparisons between the strain-gage and deflection-based methods are presented. Flight data from the phase-1 active aeroelastic wing flight program were used to validate the deflection-based load estimation method. Flight validation revealed a strong bending-moment correlation and slightly weaker torque correlation. Development of current techniques, and future studies are discussed.

Robust estimators for speech enhancement in real environments

NASA Astrophysics Data System (ADS)

Sandoval-Ibarra, Yuma; Diaz-Ramirez, Victor H.; Kober, Vitaly

2015-09-01

Common statistical estimators for speech enhancement rely on several assumptions about stationarity of speech signals and noise. These assumptions may not always valid in real-life due to nonstationary characteristics of speech and noise processes. We propose new estimators based on existing estimators by incorporation of computation of rank-order statistics. The proposed estimators are better adapted to non-stationary characteristics of speech signals and noise processes. Through computer simulations we show that the proposed estimators yield a better performance in terms of objective metrics than that of known estimators when speech signals are contaminated with airport, babble, restaurant, and train-station noise.

Model-Based Method for Sensor Validation

NASA Technical Reports Server (NTRS)

Vatan, Farrokh

2012-01-01

Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

Are cannabis prevalence estimates comparable across countries and regions? A cross-cultural validation using search engine query data.

PubMed

Steppan, Martin; Kraus, Ludwig; Piontek, Daniela; Siciliano, Valeria

2013-01-01

Prevalence estimation of cannabis use is usually based on self-report data. Although there is evidence on the reliability of this data source, its cross-cultural validity is still a major concern. External objective criteria are needed for this purpose. In this study, cannabis-related search engine query data are used as an external criterion. Data on cannabis use were taken from the 2007 European School Survey Project on Alcohol and Other Drugs (ESPAD). Provincial data came from three Italian nation-wide studies using the same methodology (2006-2008; ESPAD-Italia). Information on cannabis-related search engine query data was based on Google search volume indices (GSI). (1) Reliability analysis was conducted for GSI. (2) Latent measurement models of "true" cannabis prevalence were tested using perceived availability, web-based cannabis searches and self-reported prevalence as indicators. (3) Structure models were set up to test the influences of response tendencies and geographical position (latitude, longitude). In order to test the stability of the models, analyses were conducted on country level (Europe, US) and on provincial level in Italy. Cannabis-related GSI were found to be highly reliable and constant over time. The overall measurement model was highly significant in both data sets. On country level, no significant effects of response bias indicators and geographical position on perceived availability, web-based cannabis searches and self-reported prevalence were found. On provincial level, latitude had a significant positive effect on availability indicating that perceived availability of cannabis in northern Italy was higher than expected from the other indicators. Although GSI showed weaker associations with cannabis use than perceived availability, the findings underline the external validity and usefulness of search engine query data as external criteria. The findings suggest an acceptable relative comparability of national (provincial) prevalence estimates of cannabis use that are based on a common survey methodology. Search engine query data are a too weak indicator to base prevalence estimations on this source only, but in combination with other sources (waste water analysis, sales of cigarette paper) they may provide satisfactory estimates. Copyright © 2012. Published by Elsevier B.V.

Validation databases for simulation models: aboveground biomass and net primary productive, (NPP) estimation using eastwide FIA data

Treesearch

Jennifer C. Jenkins; Richard A. Birdsey

2000-01-01

As interest grows in the role of forest growth in the carbon cycle, and as simulation models are applied to predict future forest productivity at large spatial scales, the need for reliable and field-based data for evaluation of model estimates is clear. We created estimates of potential forest biomass and annual aboveground production for the Chesapeake Bay watershed...

Comparison of anthropometric-based equations for estimation of body fat percentage in a normal-weight and overweight female cohort: validation via air-displacement plethysmography.

PubMed

Temple, Derry; Denis, Romain; Walsh, Marianne C; Dicker, Patrick; Byrne, Annette T

2015-02-01

To evaluate the accuracy of the most commonly used anthropometric-based equations in the estimation of percentage body fat (%BF) in both normal-weight and overweight women using air-displacement plethysmography (ADP) as the criterion measure. A comparative study in which the equations of Durnin and Womersley (1974; DW) and Jackson, Pollock and Ward (1980) at three, four and seven sites (JPW₃, JPW₄ and JPW₇) were validated against ADP in three groups. Group 1 included all participants, group 2 included participants with a BMI <25·0 kg/m² and group 3 included participants with a BMI ≥25·0 kg/m². Human Performance Laboratory, Institute for Sport and Health, University College Dublin, Republic of Ireland. Forty-three female participants aged between 18 and 55 years. In all three groups, the %BF values estimated from the DW equation were closer to the criterion measure (i.e. ADP) than those estimated from the other equations. Of the three JPW equations, JPW₃ provided the most accurate estimation of %BF when compared with ADP in all three groups. In comparison to ADP, these findings suggest that the DW equation is the most accurate anthropometric method for the estimation of %BF in both normal-weight and overweight females.

An Approach for Validating Actinide and Fission Product Burnup Credit Criticality Safety Analyses: Criticality (k eff) Predictions

DOE PAGES

Scaglione, John M.; Mueller, Don E.; Wagner, John C.

2014-12-01

One of the most important remaining challenges associated with expanded implementation of burnup credit in the United States is the validation of depletion and criticality calculations used in the safety evaluation—in particular, the availability and use of applicable measured data to support validation, especially for fission products (FPs). Applicants and regulatory reviewers have been constrained by both a scarcity of data and a lack of clear technical basis or approach for use of the data. In this study, this paper describes a validation approach for commercial spent nuclear fuel (SNF) criticality safety (k eff) evaluations based on best-available data andmore » methods and applies the approach for representative SNF storage and transport configurations/conditions to demonstrate its usage and applicability, as well as to provide reference bias results. The criticality validation approach utilizes not only available laboratory critical experiment (LCE) data from the International Handbook of Evaluated Criticality Safety Benchmark Experiments and the French Haut Taux de Combustion program to support validation of the principal actinides but also calculated sensitivities, nuclear data uncertainties, and limited available FP LCE data to predict and verify individual biases for relevant minor actinides and FPs. The results demonstrate that (a) sufficient critical experiment data exist to adequately validate k eff calculations via conventional validation approaches for the primary actinides, (b) sensitivity-based critical experiment selection is more appropriate for generating accurate application model bias and uncertainty, and (c) calculated sensitivities and nuclear data uncertainties can be used for generating conservative estimates of bias for minor actinides and FPs. Results based on the SCALE 6.1 and the ENDF/B-VII.0 cross-section libraries indicate that a conservative estimate of the bias for the minor actinides and FPs is 1.5% of their worth within the application model. Finally, this paper provides a detailed description of the approach and its technical bases, describes the application of the approach for representative pressurized water reactor and boiling water reactor safety analysis models, and provides reference bias results based on the prerelease SCALE 6.1 code package and ENDF/B-VII nuclear cross-section data.« less

An Approach for Validating Actinide and Fission Product Burnup Credit Criticality Safety Analyses-Isotopic Composition Predictions

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

Radulescu, Georgeta; Gauld, Ian C; Ilas, Germina

2011-01-01

The expanded use of burnup credit in the United States (U.S.) for storage and transport casks, particularly in the acceptance of credit for fission products, has been constrained by the availability of experimental fission product data to support code validation. The U.S. Nuclear Regulatory Commission (NRC) staff has noted that the rationale for restricting the Interim Staff Guidance on burnup credit for storage and transportation casks (ISG-8) to actinide-only is based largely on the lack of clear, definitive experiments that can be used to estimate the bias and uncertainty for computational analyses associated with using burnup credit. To address themore » issues of burnup credit criticality validation, the NRC initiated a project with the Oak Ridge National Laboratory to (1) develop and establish a technically sound validation approach for commercial spent nuclear fuel (SNF) criticality safety evaluations based on best-available data and methods and (2) apply the approach for representative SNF storage and transport configurations/conditions to demonstrate its usage and applicability, as well as to provide reference bias results. The purpose of this paper is to describe the isotopic composition (depletion) validation approach and resulting observations and recommendations. Validation of the criticality calculations is addressed in a companion paper at this conference. For isotopic composition validation, the approach is to determine burnup-dependent bias and uncertainty in the effective neutron multiplication factor (keff) due to bias and uncertainty in isotopic predictions, via comparisons of isotopic composition predictions (calculated) and measured isotopic compositions from destructive radiochemical assay utilizing as much assay data as is available, and a best-estimate Monte Carlo based method. This paper (1) provides a detailed description of the burnup credit isotopic validation approach and its technical bases, (2) describes the application of the approach for representative pressurized water reactor and boiling water reactor safety analysis models to demonstrate its usage and applicability, (3) provides reference bias and uncertainty results based on a quality-assurance-controlled prerelease version of the Scale 6.1 code package and the ENDF/B-VII nuclear cross section data.« less

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Robust Estimation of Electron Density From Anatomic Magnetic Resonance Imaging of the Brain Using a Unifying Multi-Atlas Approach

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

Ren, Shangjie; Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, California; Hara, Wendy

Purpose: To develop a reliable method to estimate electron density based on anatomic magnetic resonance imaging (MRI) of the brain. Methods and Materials: We proposed a unifying multi-atlas approach for electron density estimation based on standard T1- and T2-weighted MRI. First, a composite atlas was constructed through a voxelwise matching process using multiple atlases, with the goal of mitigating effects of inherent anatomic variations between patients. Next we computed for each voxel 2 kinds of conditional probabilities: (1) electron density given its image intensity on T1- and T2-weighted MR images; and (2) electron density given its spatial location in a referencemore » anatomy, obtained by deformable image registration. These were combined into a unifying posterior probability density function using the Bayesian formalism, which provided the optimal estimates for electron density. We evaluated the method on 10 patients using leave-one-patient-out cross-validation. Receiver operating characteristic analyses for detecting different tissue types were performed. Results: The proposed method significantly reduced the errors in electron density estimation, with a mean absolute Hounsfield unit error of 119, compared with 140 and 144 (P<.0001) using conventional T1-weighted intensity and geometry-based approaches, respectively. For detection of bony anatomy, the proposed method achieved an 89% area under the curve, 86% sensitivity, 88% specificity, and 90% accuracy, which improved upon intensity and geometry-based approaches (area under the curve: 79% and 80%, respectively). Conclusion: The proposed multi-atlas approach provides robust electron density estimation and bone detection based on anatomic MRI. If validated on a larger population, our work could enable the use of MRI as a primary modality for radiation treatment planning.« less

Blind Source Parameters for Performance Evaluation of Despeckling Filters.

PubMed

Biradar, Nagashettappa; Dewal, M L; Rohit, ManojKumar; Gowre, Sanjaykumar; Gundge, Yogesh

2016-01-01

The speckle noise is inherent to transthoracic echocardiographic images. A standard noise-free reference echocardiographic image does not exist. The evaluation of filters based on the traditional parameters such as peak signal-to-noise ratio, mean square error, and structural similarity index may not reflect the true filter performance on echocardiographic images. Therefore, the performance of despeckling can be evaluated using blind assessment metrics like the speckle suppression index, speckle suppression and mean preservation index (SMPI), and beta metric. The need for noise-free reference image is overcome using these three parameters. This paper presents a comprehensive analysis and evaluation of eleven types of despeckling filters for echocardiographic images in terms of blind and traditional performance parameters along with clinical validation. The noise is effectively suppressed using the logarithmic neighborhood shrinkage (NeighShrink) embedded with Stein's unbiased risk estimation (SURE). The SMPI is three times more effective compared to the wavelet based generalized likelihood estimation approach. The quantitative evaluation and clinical validation reveal that the filters such as the nonlocal mean, posterior sampling based Bayesian estimation, hybrid median, and probabilistic patch based filters are acceptable whereas median, anisotropic diffusion, fuzzy, and Ripplet nonlinear approximation filters have limited applications for echocardiographic images.

Blind Source Parameters for Performance Evaluation of Despeckling Filters

PubMed Central

Biradar, Nagashettappa; Dewal, M. L.; Rohit, ManojKumar; Gowre, Sanjaykumar; Gundge, Yogesh

2016-01-01

The speckle noise is inherent to transthoracic echocardiographic images. A standard noise-free reference echocardiographic image does not exist. The evaluation of filters based on the traditional parameters such as peak signal-to-noise ratio, mean square error, and structural similarity index may not reflect the true filter performance on echocardiographic images. Therefore, the performance of despeckling can be evaluated using blind assessment metrics like the speckle suppression index, speckle suppression and mean preservation index (SMPI), and beta metric. The need for noise-free reference image is overcome using these three parameters. This paper presents a comprehensive analysis and evaluation of eleven types of despeckling filters for echocardiographic images in terms of blind and traditional performance parameters along with clinical validation. The noise is effectively suppressed using the logarithmic neighborhood shrinkage (NeighShrink) embedded with Stein's unbiased risk estimation (SURE). The SMPI is three times more effective compared to the wavelet based generalized likelihood estimation approach. The quantitative evaluation and clinical validation reveal that the filters such as the nonlocal mean, posterior sampling based Bayesian estimation, hybrid median, and probabilistic patch based filters are acceptable whereas median, anisotropic diffusion, fuzzy, and Ripplet nonlinear approximation filters have limited applications for echocardiographic images. PMID:27298618

GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation

PubMed Central

Li, Hong; Lu, Mingquan

2017-01-01

Spoofing attacks are threatening the global navigation satellite system (GNSS). The maximum likelihood estimation (MLE)-based positioning technique is a direct positioning method originally developed for multipath rejection and weak signal processing. We find this method also has a potential ability for GNSS anti-spoofing since a spoofing attack that misleads the positioning and timing result will cause distortion to the MLE cost function. Based on the method, an estimation-cancellation approach is presented to detect spoofing attacks and recover the navigation solution. A statistic is derived for spoofing detection with the principle of the generalized likelihood ratio test (GLRT). Then, the MLE cost function is decomposed to further validate whether the navigation solution obtained by MLE-based positioning is formed by consistent signals. Both formulae and simulations are provided to evaluate the anti-spoofing performance. Experiments with recordings in real GNSS spoofing scenarios are also performed to validate the practicability of the approach. Results show that the method works even when the code phase differences between the spoofing and authentic signals are much less than one code chip, which can improve the availability of GNSS service greatly under spoofing attacks. PMID:28665318

GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation.

PubMed

Wang, Fei; Li, Hong; Lu, Mingquan

2017-06-30

Spoofing attacks are threatening the global navigation satellite system (GNSS). The maximum likelihood estimation (MLE)-based positioning technique is a direct positioning method originally developed for multipath rejection and weak signal processing. We find this method also has a potential ability for GNSS anti-spoofing since a spoofing attack that misleads the positioning and timing result will cause distortion to the MLE cost function. Based on the method, an estimation-cancellation approach is presented to detect spoofing attacks and recover the navigation solution. A statistic is derived for spoofing detection with the principle of the generalized likelihood ratio test (GLRT). Then, the MLE cost function is decomposed to further validate whether the navigation solution obtained by MLE-based positioning is formed by consistent signals. Both formulae and simulations are provided to evaluate the anti-spoofing performance. Experiments with recordings in real GNSS spoofing scenarios are also performed to validate the practicability of the approach. Results show that the method works even when the code phase differences between the spoofing and authentic signals are much less than one code chip, which can improve the availability of GNSS service greatly under spoofing attacks.

A Statistical Method of Identifying Interactions in Neuron–Glia Systems Based on Functional Multicell Ca2+ Imaging

PubMed Central

Nakae, Ken; Ikegaya, Yuji; Ishikawa, Tomoe; Oba, Shigeyuki; Urakubo, Hidetoshi; Koyama, Masanori; Ishii, Shin

2014-01-01

Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron–glia network. We attempted to identify neuron–glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron–glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron–glia systems. PMID:25393874

Dietary Compositions and Their Seasonal Shifts in Japanese Resident Birds, Estimated from the Analysis of Volunteer Monitoring Data

PubMed Central

Yoshikawa, Tetsuro; Osada, Yutaka

2015-01-01

Determining the composition of a bird’s diet and its seasonal shifts are fundamental for understanding the ecology and ecological functions of a species. Various methods have been used to estimate the dietary compositions of birds, which have their own advantages and disadvantages. In this study, we examined the possibility of using long-term volunteer monitoring data as the source of dietary information for 15 resident bird species in Kanagawa Prefecture, Japan. The data were collected from field observations reported by volunteers of regional naturalist groups. Based on these monitoring data, we calculated the monthly dietary composition of each bird species directly, and we also estimated unidentified items within the reported foraging episodes using Bayesian models that contained additional information regarding foraging locations. Next, to examine the validity of the estimated dietary compositions, we compared them with the dietary information for focal birds based on stomach analysis methods, collected from past literatures. The dietary trends estimated from the monitoring data were largely consistent with the general food habits determined from the previous studies of focal birds. Thus, the estimates based on the volunteer monitoring data successfully detected noticeable seasonal shifts in many of the birds from plant materials to animal diets during spring—summer. Comparisons with stomach analysis data supported the qualitative validity of the monitoring-based dietary information and the effectiveness of the Bayesian models for improving the estimates. This comparison suggests that one advantage of using monitoring data is its ability to detect dietary items such as fleshy fruits, flower nectar, and vertebrates. These results emphasize the potential importance of observation data collecting and mining by citizens, especially free descriptive observation data, for use in bird ecology studies. PMID:25723544

Robust estimation of the proportion of treatment effect explained by surrogate marker information.

PubMed

Parast, Layla; McDermott, Mary M; Tian, Lu

2016-05-10

In randomized treatment studies where the primary outcome requires long follow-up of patients and/or expensive or invasive obtainment procedures, the availability of a surrogate marker that could be used to estimate the treatment effect and could potentially be observed earlier than the primary outcome would allow researchers to make conclusions regarding the treatment effect with less required follow-up time and resources. The Prentice criterion for a valid surrogate marker requires that a test for treatment effect on the surrogate marker also be a valid test for treatment effect on the primary outcome of interest. Based on this criterion, methods have been developed to define and estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on the surrogate marker. These methods aim to identify useful statistical surrogates that capture a large proportion of the treatment effect. However, current methods to estimate this proportion usually require restrictive model assumptions that may not hold in practice and thus may lead to biased estimates of this quantity. In this paper, we propose a nonparametric procedure to estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on a potential surrogate marker and extend this procedure to a setting with multiple surrogate markers. We compare our approach with previously proposed model-based approaches and propose a variance estimation procedure based on a perturbation-resampling method. Simulation studies demonstrate that the procedure performs well in finite samples and outperforms model-based procedures when the specified models are not correct. We illustrate our proposed procedure using a data set from a randomized study investigating a group-mediated cognitive behavioral intervention for peripheral artery disease participants. Copyright © 2015 John Wiley & Sons, Ltd.

Ocean Surface Carbon Dioxide Fugacity Observed from Space

NASA Technical Reports Server (NTRS)

Liu, W. Timothy; Xie, Xiaosu

2014-01-01

We have developed and validated a statistical model to estimate the fugacity (or partial pressure) of carbon dioxide (CO2) at sea surface (pCO2sea) from space-based observations of sea surface temperature (SST), chlorophyll, and salinity. More than a quarter million in situ measurements coincident with satellite data were compiled to train and validate the model. We have produced and made accessible 9 years (2002-2010) of the pCO2sea at 0.5 degree resolutions daily over the global ocean. The results help to identify uncertainties in current JPL Carbon Monitoring System (CMS) model-based and bottom-up estimates over the ocean. The utility of the data to reveal multi-year and regional variability of the fugacity in relation to prevalent oceanic parameters is demonstrated.

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

NASA Technical Reports Server (NTRS)

Wolff, David B.; Fisher, Brad L.

2010-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25 terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSRE over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products. 3

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

NASA Technical Reports Server (NTRS)

Wolff, David B.; Fisher, Brad L.

2011-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSR-E over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products.

Percent body fat estimations in college men using field and laboratory methods: a three-compartment model approach.

PubMed

Moon, Jordan R; Tobkin, Sarah E; Smith, Abbie E; Roberts, Michael D; Ryan, Eric D; Dalbo, Vincent J; Lockwood, Chris M; Walter, Ashley A; Cramer, Joel T; Beck, Travis W; Stout, Jeffrey R

2008-04-21

Methods used to estimate percent body fat can be classified as a laboratory or field technique. However, the validity of these methods compared to multiple-compartment models has not been fully established. The purpose of this study was to determine the validity of field and laboratory methods for estimating percent fat (%fat) in healthy college-age men compared to the Siri three-compartment model (3C). Thirty-one Caucasian men (22.5 +/- 2.7 yrs; 175.6 +/- 6.3 cm; 76.4 +/- 10.3 kg) had their %fat estimated by bioelectrical impedance analysis (BIA) using the BodyGram computer program (BIA-AK) and population-specific equation (BIA-Lohman), near-infrared interactance (NIR) (Futrex(R) 6100/XL), four circumference-based military equations [Marine Corps (MC), Navy and Air Force (NAF), Army (A), and Friedl], air-displacement plethysmography (BP), and hydrostatic weighing (HW). All circumference-based military equations (MC = 4.7% fat, NAF = 5.2% fat, A = 4.7% fat, Friedl = 4.7% fat) along with NIR (NIR = 5.1% fat) produced an unacceptable total error (TE). Both laboratory methods produced acceptable TE values (HW = 2.5% fat; BP = 2.7% fat). The BIA-AK, and BIA-Lohman field methods produced acceptable TE values (2.1% fat). A significant difference was observed for the MC and NAF equations compared to both the 3C model and HW (p < 0.006). Results indicate that the BP and HW are valid laboratory methods when compared to the 3C model to estimate %fat in college-age Caucasian men. When the use of a laboratory method is not feasible, BIA-AK, and BIA-Lohman are acceptable field methods to estimate %fat in this population.

Percent body fat estimations in college men using field and laboratory methods: A three-compartment model approach

PubMed Central

Moon, Jordan R; Tobkin, Sarah E; Smith, Abbie E; Roberts, Michael D; Ryan, Eric D; Dalbo, Vincent J; Lockwood, Chris M; Walter, Ashley A; Cramer, Joel T; Beck, Travis W; Stout, Jeffrey R

2008-01-01

Background Methods used to estimate percent body fat can be classified as a laboratory or field technique. However, the validity of these methods compared to multiple-compartment models has not been fully established. The purpose of this study was to determine the validity of field and laboratory methods for estimating percent fat (%fat) in healthy college-age men compared to the Siri three-compartment model (3C). Methods Thirty-one Caucasian men (22.5 ± 2.7 yrs; 175.6 ± 6.3 cm; 76.4 ± 10.3 kg) had their %fat estimated by bioelectrical impedance analysis (BIA) using the BodyGram™ computer program (BIA-AK) and population-specific equation (BIA-Lohman), near-infrared interactance (NIR) (Futrex® 6100/XL), four circumference-based military equations [Marine Corps (MC), Navy and Air Force (NAF), Army (A), and Friedl], air-displacement plethysmography (BP), and hydrostatic weighing (HW). Results All circumference-based military equations (MC = 4.7% fat, NAF = 5.2% fat, A = 4.7% fat, Friedl = 4.7% fat) along with NIR (NIR = 5.1% fat) produced an unacceptable total error (TE). Both laboratory methods produced acceptable TE values (HW = 2.5% fat; BP = 2.7% fat). The BIA-AK, and BIA-Lohman field methods produced acceptable TE values (2.1% fat). A significant difference was observed for the MC and NAF equations compared to both the 3C model and HW (p < 0.006). Conclusion Results indicate that the BP and HW are valid laboratory methods when compared to the 3C model to estimate %fat in college-age Caucasian men. When the use of a laboratory method is not feasible, BIA-AK, and BIA-Lohman are acceptable field methods to estimate %fat in this population. PMID:18426582

Validation of Bayesian analysis of compartmental kinetic models in medical imaging.

PubMed

Sitek, Arkadiusz; Li, Quanzheng; El Fakhri, Georges; Alpert, Nathaniel M

2016-10-01

Kinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated. The closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach. Posteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P>0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P<0.0001). The results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Mapping 2000 2010 Impervious Surface Change in India Using Global Land Survey Landsat Data

NASA Technical Reports Server (NTRS)

Wang, Panshi; Huang, Chengquan; Brown De Colstoun, Eric C.

2017-01-01

Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 200-02010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approach An independent validation dataset was also developed using Google Earth imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 +/- 7.84 sq km.

An estimation of the main wetting branch of the soil water retention curve based on its main drying branch using the machine learning method

NASA Astrophysics Data System (ADS)

Lamorski, Krzysztof; Šimūnek, Jiří; Sławiński, Cezary; Lamorska, Joanna

2017-02-01

In this paper, we estimated using the machine learning methodology the main wetting branch of the soil water retention curve based on the knowledge of the main drying branch and other, optional, basic soil characteristics (particle size distribution, bulk density, organic matter content, or soil specific surface). The support vector machine algorithm was used for the models' development. The data needed by this algorithm for model training and validation consisted of 104 different undisturbed soil core samples collected from the topsoil layer (A horizon) of different soil profiles in Poland. The main wetting and drying branches of SWRC, as well as other basic soil physical characteristics, were determined for all soil samples. Models relying on different sets of input parameters were developed and validated. The analysis showed that taking into account other input parameters (i.e., particle size distribution, bulk density, organic matter content, or soil specific surface) than information about the drying branch of the SWRC has essentially no impact on the models' estimations. Developed models are validated and compared with well-known models that can be used for the same purpose, such as the Mualem (1977) (M77) and Kool and Parker (1987) (KP87) models. The developed models estimate the main wetting SWRC branch with estimation errors (RMSE = 0.018 m3/m3) that are significantly lower than those for the M77 (RMSE = 0.025 m3/m3) or KP87 (RMSE = 0. 047 m3/m3) models.

Validation of Diagnostic Groups Based on Health Care Utilization Data Should Adjust for Sampling Strategy.

PubMed

Cadieux, Geneviève; Tamblyn, Robyn; Buckeridge, David L; Dendukuri, Nandini

2017-08-01

Valid measurement of outcomes such as disease prevalence using health care utilization data is fundamental to the implementation of a "learning health system." Definitions of such outcomes can be complex, based on multiple diagnostic codes. The literature on validating such data demonstrates a lack of awareness of the need for a stratified sampling design and corresponding statistical methods. We propose a method for validating the measurement of diagnostic groups that have: (1) different prevalences of diagnostic codes within the group; and (2) low prevalence. We describe an estimation method whereby: (1) low-prevalence diagnostic codes are oversampled, and the positive predictive value (PPV) of the diagnostic group is estimated as a weighted average of the PPV of each diagnostic code; and (2) claims that fall within a low-prevalence diagnostic group are oversampled relative to claims that are not, and bias-adjusted estimators of sensitivity and specificity are generated. We illustrate our proposed method using an example from population health surveillance in which diagnostic groups are applied to physician claims to identify cases of acute respiratory illness. Failure to account for the prevalence of each diagnostic code within a diagnostic group leads to the underestimation of the PPV, because low-prevalence diagnostic codes are more likely to be false positives. Failure to adjust for oversampling of claims that fall within the low-prevalence diagnostic group relative to those that do not leads to the overestimation of sensitivity and underestimation of specificity.

A Novel Tool Improves Existing Estimates of Recent Tuberculosis Transmission in Settings of Sparse Data Collection.

PubMed

Kasaie, Parastu; Mathema, Barun; Kelton, W David; Azman, Andrew S; Pennington, Jeff; Dowdy, David W

2015-01-01

In any setting, a proportion of incident active tuberculosis (TB) reflects recent transmission ("recent transmission proportion"), whereas the remainder represents reactivation. Appropriately estimating the recent transmission proportion has important implications for local TB control, but existing approaches have known biases, especially where data are incomplete. We constructed a stochastic individual-based model of a TB epidemic and designed a set of simulations (derivation set) to develop two regression-based tools for estimating the recent transmission proportion from five inputs: underlying TB incidence, sampling coverage, study duration, clustered proportion of observed cases, and proportion of observed clusters in the sample. We tested these tools on a set of unrelated simulations (validation set), and compared their performance against that of the traditional 'n-1' approach. In the validation set, the regression tools reduced the absolute estimation bias (difference between estimated and true recent transmission proportion) in the 'n-1' technique by a median [interquartile range] of 60% [9%, 82%] and 69% [30%, 87%]. The bias in the 'n-1' model was highly sensitive to underlying levels of study coverage and duration, and substantially underestimated the recent transmission proportion in settings of incomplete data coverage. By contrast, the regression models' performance was more consistent across different epidemiological settings and study characteristics. We provide one of these regression models as a user-friendly, web-based tool. Novel tools can improve our ability to estimate the recent TB transmission proportion from data that are observable (or estimable) by public health practitioners with limited available molecular data.

A Novel Tool Improves Existing Estimates of Recent Tuberculosis Transmission in Settings of Sparse Data Collection

PubMed Central

Kasaie, Parastu; Mathema, Barun; Kelton, W. David; Azman, Andrew S.; Pennington, Jeff; Dowdy, David W.

2015-01-01

In any setting, a proportion of incident active tuberculosis (TB) reflects recent transmission (“recent transmission proportion”), whereas the remainder represents reactivation. Appropriately estimating the recent transmission proportion has important implications for local TB control, but existing approaches have known biases, especially where data are incomplete. We constructed a stochastic individual-based model of a TB epidemic and designed a set of simulations (derivation set) to develop two regression-based tools for estimating the recent transmission proportion from five inputs: underlying TB incidence, sampling coverage, study duration, clustered proportion of observed cases, and proportion of observed clusters in the sample. We tested these tools on a set of unrelated simulations (validation set), and compared their performance against that of the traditional ‘n-1’ approach. In the validation set, the regression tools reduced the absolute estimation bias (difference between estimated and true recent transmission proportion) in the ‘n-1’ technique by a median [interquartile range] of 60% [9%, 82%] and 69% [30%, 87%]. The bias in the ‘n-1’ model was highly sensitive to underlying levels of study coverage and duration, and substantially underestimated the recent transmission proportion in settings of incomplete data coverage. By contrast, the regression models’ performance was more consistent across different epidemiological settings and study characteristics. We provide one of these regression models as a user-friendly, web-based tool. Novel tools can improve our ability to estimate the recent TB transmission proportion from data that are observable (or estimable) by public health practitioners with limited available molecular data. PMID:26679499

Estimating the Population of Survivors of Suicide: Seeking an Evidence Base

ERIC Educational Resources Information Center

Berman, Alan L.

2011-01-01

Shneidman (1973) derived an estimate of six survivors for every suicide that, in the ensuing years, has become an assumed fact underlying public health messaging campaigns in support of suicide prevention and postvention programs worldwide, in spite of it lacking either empirical testing or validation. This report offers a first test designed to…

Estimating and validating surface energy fluxes at field scale over a heterogeneous land surfaces based on two-source energy balance model (TSEB)

USDA-ARS?s Scientific Manuscript database

Accurate estimation of surface energy fluxes at field scale over large areas has the potential to improve agricultural water management in arid and semiarid watersheds. Remote sensing may be the only viable approach for mapping fluxes over heterogeneous landscapes. The Two-Source Energy Balance mode...

Estimating the Reliability of a Test Battery Composite or a Test Score Based on Weighted Item Scoring

ERIC Educational Resources Information Center

Feldt, Leonard S.

2004-01-01

In some settings, the validity of a battery composite or a test score is enhanced by weighting some parts or items more heavily than others in the total score. This article describes methods of estimating the total score reliability coefficient when differential weights are used with items or parts.

A phase match based frequency estimation method for sinusoidal signals

NASA Astrophysics Data System (ADS)

Shen, Yan-Lin; Tu, Ya-Qing; Chen, Lin-Jun; Shen, Ting-Ao

2015-04-01

Accurate frequency estimation affects the ranging precision of linear frequency modulated continuous wave (LFMCW) radars significantly. To improve the ranging precision of LFMCW radars, a phase match based frequency estimation method is proposed. To obtain frequency estimation, linear prediction property, autocorrelation, and cross correlation of sinusoidal signals are utilized. The analysis of computational complex shows that the computational load of the proposed method is smaller than those of two-stage autocorrelation (TSA) and maximum likelihood. Simulations and field experiments are performed to validate the proposed method, and the results demonstrate the proposed method has better performance in terms of frequency estimation precision than methods of Pisarenko harmonic decomposition, modified covariance, and TSA, which contribute to improving the precision of LFMCW radars effectively.

Validation of Suomi-NPP VIIRS sea ice concentration with very high-resolution satellite and airborne camera imagery

NASA Astrophysics Data System (ADS)

Baldwin, Daniel; Tschudi, Mark; Pacifici, Fabio; Liu, Yinghui

2017-08-01

Two independent VIIRS-based Sea Ice Concentration (SIC) products are validated against SIC as estimated from Very High Spatial Resolution Imagery for several VIIRS overpasses. The 375 m resolution VIIRS SIC from the Interface Data Processing Segment (IDPS) SIC algorithm is compared against estimates made from 2 m DigitalGlobe (DG) WorldView-2 imagery and also against estimates created from 10 cm Digital Mapping System (DMS) camera imagery. The 750 m VIIRS SIC from the Enterprise SIC algorithm is compared against DG imagery. The IDPS vs. DG comparisons reveal that, due to algorithm issues, many of the IDPS SIC retrievals were falsely assigned ice-free values when the pixel was clearly over ice. These false values increased the validation bias and RMS statistics. The IDPS vs. DMS comparisons were largely over ice-covered regions and did not demonstrate the false retrieval issue. The validation results show that products from both the IDPS and Enterprise algorithms were within or very close to the 10% accuracy (bias) specifications in both the non-melting and melting conditions, but only products from the Enterprise algorithm met the 25% specifications for the uncertainty (RMS).

Variable-image videoconfrontation as a method of assessing body image: a technical report and comparison with similar techniques.

PubMed

McCrea, C; Neil, W J; Flanigan, J W; Summerfield, A B

1988-08-01

In this study a new modified videosystem, designed for measuring body-image, was evaluated alongside the major size-estimation measure, namely, the visual size-estimation apparatus. The advantages afforded by a videosystem which allows independent adjustment of size and height/width proportions were highlighted, and its validity and reliability were examined, based on estimates made by obese, normal weight, and pregnant groups.

The Novel Nonlinear Adaptive Doppler Shift Estimation Technique and the Coherent Doppler Lidar System Validation Lidar

NASA Technical Reports Server (NTRS)

Beyon, Jeffrey Y.; Koch, Grady J.

2006-01-01

The signal processing aspect of a 2-m wavelength coherent Doppler lidar system under development at NASA Langley Research Center in Virginia is investigated in this paper. The lidar system is named VALIDAR (validation lidar) and its signal processing program estimates and displays various wind parameters in real-time as data acquisition occurs. The goal is to improve the quality of the current estimates such as power, Doppler shift, wind speed, and wind direction, especially in low signal-to-noise-ratio (SNR) regime. A novel Nonlinear Adaptive Doppler Shift Estimation Technique (NADSET) is developed on such behalf and its performance is analyzed using the wind data acquired over a long period of time by VALIDAR. The quality of Doppler shift and power estimations by conventional Fourier-transform-based spectrum estimation methods deteriorates rapidly as SNR decreases. NADSET compensates such deterioration in the quality of wind parameter estimates by adaptively utilizing the statistics of Doppler shift estimate in a strong SNR range and identifying sporadic range bins where good Doppler shift estimates are found. The authenticity of NADSET is established by comparing the trend of wind parameters with and without NADSET applied to the long-period lidar return data.

Further development and construct validation of MMPI-2-RF indices of global psychopathy, fearless-dominance, and impulsive-antisociality in a sample of incarcerated women.

PubMed

Phillips, Tasha R; Sellbom, Martin; Ben-Porath, Yossef S; Patrick, Christopher J

2014-02-01

Replicating and extending research by Sellbom et al. (M. Sellbom, Y. S. Ben-Porath, C. J. Patrick, D. B. Wygant, D. M. Gartland, & K. P. Stafford, 2012, Development and Construct Validation of the MMPI-2-RF Measures of Global Psychopathy, Fearless-Dominance, and Impulsive-Antisociality, Personality Disorders: Theory, Research, and Treatment, 3, 17-38), the current study examined the criterion-related validity of three self-report indices of psychopathy that were derived from scores on the Minnesota Multiphasic Personality Inventory (MMPI)-2-Restructured Form (MMPI-2-RF; Y. S. Ben-Porath & A. Tellegen, 2008, Minnesota Multiphasic Personality Inventory-2-Restructured Form: Manual for Administration, Scoring, and Interpretation, Minneapolis, MN: University of Minnesota Press). We estimated psychopathy indices by regressing scores from the Psychopathic Personality Inventory (PPI; S. O. Lilienfeld & B. P. Andrews, 1996, Development and Preliminary Validation of a Self-Report Measure of Psychopathic Personality Traits in Noncriminal Populations, Journal of Personality Assessment, 66, 488-524) and its two distinct facets, Fearless-Dominance and Impulsive-Antisociality, onto conceptually selected MMPI-2-RF scales. Data for a newly collected sample of 230 incarcerated women were combined with existing data from Sellbom et al.'s (2012) male correctional and mixed-gender college samples to establish regression equations with optimal generalizability. Correlation and regression analyses were then used to examine associations between the MMPI-2-RF-based estimates of PPI psychopathy and criterion measures (i.e., other well-established measures of psychopathy and conceptually related personality traits), and to evaluate whether gender moderated these associations. The MMPI-2-RF-based psychopathy indices correlated as expected with criterion measures and showed only one significant moderating effect for gender, namely, in the association between psychopathy and narcissism. These results provide further support for the validity of the MMPI-2-RF-based estimates of PPI psychopathy, and encourage their use in research and clinical contexts.

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China

PubMed Central

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-01-01

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762

Development and validation of a nomogram to estimate the pretest probability of cancer in Chinese patients with solid solitary pulmonary nodules: A multi-institutional study.

PubMed

She, Yunlang; Zhao, Lilan; Dai, Chenyang; Ren, Yijiu; Jiang, Gening; Xie, Huikang; Zhu, Huiyuan; Sun, Xiwen; Yang, Ping; Chen, Yongbing; Shi, Shunbin; Shi, Weirong; Yu, Bing; Xie, Dong; Chen, Chang

2017-11-01

To develop and validate a nomogram to estimate the pretest probability of malignancy in Chinese patients with solid solitary pulmonary nodule (SPN). A primary cohort of 1798 patients with pathologically confirmed solid SPNs after surgery was retrospectively studied at five institutions from January 2014 to December 2015. A nomogram based on independent prediction factors of malignant solid SPN was developed. Predictive performance also was evaluated using the calibration curve and the area under the receiver operating characteristic curve (AUC). The mean age of the cohort was 58.9 ± 10.7 years. In univariate and multivariate analysis, age; history of cancer; the log base 10 transformations of serum carcinoembryonic antigen value; nodule diameter; the presence of spiculation, pleural indentation, and calcification remained the predictive factors of malignancy. A nomogram was developed, and the AUC value (0.85; 95%CI, 0.83-0.88) was significantly higher than other three models. The calibration cure showed optimal agreement between the malignant probability as predicted by nomogram and the actual probability. We developed and validated a nomogram that can estimate the pretest probability of malignant solid SPNs, which can assist clinical physicians to select and interpret the results of subsequent diagnostic tests. © 2017 Wiley Periodicals, Inc.

Hybrid optimal design of the eco-hydrological wireless sensor network in the middle reach of the Heihe River Basin, China.

PubMed

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-10-14

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.

Validation of ELDO approaches for retrospective assessment of cumulative eye lens doses of interventional cardiologists-results from DoReMi project.

PubMed

Domienik, J; Farah, J; Struelens, L

2016-12-01

The first validation results of the two approaches developed in the ELDO project for retrospective assessment of eye lens doses for interventional cardiologists (ICs) are presented in this paper. The first approach (a) is based on both the readings from the routine whole body dosimeter worn above the lead apron and procedure-dependent conversion coefficients, while the second approach (b) is based on detailed information related to the occupational exposure history of the ICs declared in a questionnaire and eye lens dose records obtained from the relevant literature. The latter approach makes use of various published eye lens doses per procedure as well as the appropriate correction factors which account for the use of radiation protective tools designed to protect the eye lens. To validate both methodologies, comprehensive measurements were performed in several Polish clinics among recruited physicians. Two dosimeters measuring whole body and eye lens doses were worn by every physician for at least two months. The estimated cumulative eye lens doses, calculated from both approaches, were then compared against the measured eye lens dose value for every physician separately. Both approaches results in comparable estimates of eye lens doses and tend to overestimate rather than underestimate the eye lens doses. The measured and estimated doses do not differ, on average, by a factor higher than 2.0 in 85% and 62% of the cases used to validate approach (a) and (b), respectively. In specific cases, however, the estimated doses differ from the measured ones by as much as a factor of 2.7 and 5.1 for method (a) and (b), respectively. As such, the two approaches can be considered accurate when retrospectively estimating the eye lens doses for ICs and will be of great benefit for ongoing epidemiological studies.

Estimation model for habitual 24-hour urinary-sodium excretion using simple questionnaires from normotensive Koreans.

PubMed

Kong, Ji-Sook; Lee, Yeon-Kyung; Kim, Mi Kyung; Choi, Mi-Kyeong; Heo, Young-Ran; Hyun, Taisun; Kim, Sun Mee; Lyu, Eun-Soon; Oh, Se-Young; Park, Hae-Ryun; Rhee, Moo-Yong; Ro, Hee-Kyong; Song, Mi Kyung

2018-01-01

This study was conducted to develop an equation for estimation of 24-h urinary-sodium excretion that can serve as an alternative to 24-h dietary recall and 24-h urine collection for normotensive Korean adults. In total, data on 640 healthy Korean adults aged 19 to 69 years from 4 regions of the country were collected as a training set. In order to externally validate the equation developed from that training set, 200 subjects were recruited independently as a validation set. Due to heterogeneity by gender, we constructed a gender-specific equation for estimation of 24-h urinary-sodium excretion by using a multivariable linear regression model and assessed the performance of the developed equation in validation set. The best model consisted of age, body weight, dietary behavior ('eating salty food', 'Kimchi consumption', 'Korean soup or stew consumption', 'soy sauce or red pepper paste consumption'), and smoking status in men, and age, body weight, dietary behavior ('salt preference', 'eating salty food', 'checking sodium content for processed foods', 'nut consumption'), and smoking status in women, respectively. When this model was tested in the external validation set, the mean bias between the measured and estimated 24-h urinary-sodium excretion from Bland-Altman plots was -1.92 (95% CI: -113, 110) mmol/d for men and -1.51 (95% CI: -90.6, 87.6) mmol/d for women. The cut-points of sodium intake calculated based on the equations were ≥4,000 mg/d for men and ≥3,500 mg/d for women, with 89.8 and 76.6% sensitivity and 29.3 and 64.2% specificity, respectively. In this study, a habitual 24-hour urinary-sodium-excretion-estimation model of normotensive Korean adults based on anthropometric and lifestyle factors was developed and showed feasibility for an asymptomatic population.

Estimation model for habitual 24-hour urinary-sodium excretion using simple questionnaires from normotensive Koreans

PubMed Central

Choi, Mi-Kyeong; Heo, Young-Ran; Hyun, Taisun; Kim, Sun Mee; Lyu, Eun-Soon; Oh, Se-Young; Park, Hae-Ryun; Rhee, Moo-Yong; Ro, Hee-Kyong; Song, Mi Kyung

2018-01-01

This study was conducted to develop an equation for estimation of 24-h urinary-sodium excretion that can serve as an alternative to 24-h dietary recall and 24-h urine collection for normotensive Korean adults. In total, data on 640 healthy Korean adults aged 19 to 69 years from 4 regions of the country were collected as a training set. In order to externally validate the equation developed from that training set, 200 subjects were recruited independently as a validation set. Due to heterogeneity by gender, we constructed a gender-specific equation for estimation of 24-h urinary-sodium excretion by using a multivariable linear regression model and assessed the performance of the developed equation in validation set. The best model consisted of age, body weight, dietary behavior (‘eating salty food’, ‘Kimchi consumption’, ‘Korean soup or stew consumption’, ‘soy sauce or red pepper paste consumption’), and smoking status in men, and age, body weight, dietary behavior (‘salt preference’, ‘eating salty food’, ‘checking sodium content for processed foods’, ‘nut consumption’), and smoking status in women, respectively. When this model was tested in the external validation set, the mean bias between the measured and estimated 24-h urinary-sodium excretion from Bland-Altman plots was -1.92 (95% CI: -113, 110) mmol/d for men and -1.51 (95% CI: -90.6, 87.6) mmol/d for women. The cut-points of sodium intake calculated based on the equations were ≥4,000 mg/d for men and ≥3,500 mg/d for women, with 89.8 and 76.6% sensitivity and 29.3 and 64.2% specificity, respectively. In this study, a habitual 24-hour urinary-sodium-excretion-estimation model of normotensive Korean adults based on anthropometric and lifestyle factors was developed and showed feasibility for an asymptomatic population. PMID:29447201

Prevalence of Female Urinary Incontinence in the General Population According to Different Definitions and Study Designs.

PubMed

Bedretdinova, Dina; Fritel, Xavier; Panjo, Henri; Ringa, Virginie

2016-02-01

Estimates of the prevalence of female urinary incontinence (UI) vary widely. To estimate UI prevalence among women in France using data from five national surveys and analyse prevalence differences among the surveys according to their design (representative sample or not, survey focused on UI or not) and UI definition (based on symptoms or disease perception). Data came from two representative telephone surveys, Fecond (5017 women aged 15-49 yr) and Barometer (3089 women aged 40-85 yr), general and urinary postal surveys of the GAZEL cohort (3098 women aged 54-69 yr), and the web-based NutriNet survey (85,037 women aged 18-87 yr). Definitions of UI based on the International Conference on Incontinence Questionnaire UI short form (ICIQ-UI-SF) and on a list of health problems were considered. We compared age-adjusted prevalence rates among studies via logistic regression and generalised linear models. Overall, 13% of the women in Fecond, 24% in Barometer, 15% in the GAZEL general survey, 39% in the GAZEL urinary survey, and 1.5% in the NutriNet survey reported any UI. Prevalence rates in representative samples with the same UI definition (ICIQ-UI-SF) were concordant. UI prevalence in the representative samples was 17%. The estimated number of women in France with UI was 5.35 million (95% confidence interval [CI] 5.34-5.36 million) for any UI and 1.54 million (95% CI 1.53-1.55 million) for daily UI. For the GAZEL sample, UI prevalence was lower but UI severity was greater for responses to a questionnaire with the list-based UI definition rather than to a questionnaire with the ICIQ-UI-SF-based definition. In all surveys, information about UI was self-reported and was not validated by objective measurements. UI definitions and sampling strategies influence estimates of UI prevalence among women. Precise estimates of UI prevalence should be based on non-UI-focused surveys among representative samples and using a validated standardised symptom-based questionnaire. We looked at estimates of urinary incontinence (UI) prevalence in studies with different designs and different UI definitions in a large population of French women. We found that estimates varied with the definition and the design. We conclude that the most precise estimates of UI prevalence are obtained in studies of representative populations that are not focused on UI and use a validated international standard questionnaire with sufficient details to allow grading of UI severity. Most women reported rare urine leakages involving small amounts of urine with little impact on their quality of life. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

BME Estimation of Residential Exposure to Ambient PM10 and Ozone at Multiple Time Scales

PubMed Central

Yu, Hwa-Lung; Chen, Jiu-Chiuan; Christakos, George; Jerrett, Michael

2009-01-01

Background Long-term human exposure to ambient pollutants can be an important contributing or etiologic factor of many chronic diseases. Spatiotemporal estimation (mapping) of long-term exposure at residential areas based on field observations recorded in the U.S. Environmental Protection Agency’s Air Quality System often suffer from missing data issues due to the scarce monitoring network across space and the inconsistent recording periods at different monitors. Objective We developed and compared two upscaling methods: UM1 (data aggregation followed by exposure estimation) and UM2 (exposure estimation followed by data aggregation) for the long-term PM10 (particulate matter with aerodynamic diameter ≤ 10 μm) and ozone exposure estimations and applied them in multiple time scales to estimate PM and ozone exposures for the residential areas of the Health Effects of Air Pollution on Lupus (HEAPL) study. Method We used Bayesian maximum entropy (BME) analysis for the two upscaling methods. We performed spatiotemporal cross-validations at multiple time scales by UM1 and UM2 to assess the estimation accuracy across space and time. Results Compared with the kriging method, the integration of soft information by the BME method can effectively increase the estimation accuracy for both pollutants. The spatiotemporal distributions of estimation errors from UM1 and UM2 were similar. The cross-validation results indicated that UM2 is generally better than UM1 in exposure estimations at multiple time scales in terms of predictive accuracy and lack of bias. For yearly PM10 estimations, both approaches have comparable performance, but the implementation of UM1 is associated with much lower computation burden. Conclusion BME-based upscaling methods UM1 and UM2 can assimilate core and site-specific knowledge bases of different formats for long-term exposure estimation. This study shows that UM1 can perform reasonably well when the aggregation process does not alter the spatiotemporal structure of the original data set; otherwise, UM2 is preferable. PMID:19440491

Design and validation of diffusion MRI models of white matter

NASA Astrophysics Data System (ADS)

Jelescu, Ileana O.; Budde, Matthew D.

2017-11-01

Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the “biological accuracy” of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus.

A score to estimate the likelihood of detecting advanced colorectal neoplasia at colonoscopy

PubMed Central

Kaminski, Michal F; Polkowski, Marcin; Kraszewska, Ewa; Rupinski, Maciej; Butruk, Eugeniusz; Regula, Jaroslaw

2014-01-01

Objective This study aimed to develop and validate a model to estimate the likelihood of detecting advanced colorectal neoplasia in Caucasian patients. Design We performed a cross-sectional analysis of database records for 40-year-old to 66-year-old patients who entered a national primary colonoscopy-based screening programme for colorectal cancer in 73 centres in Poland in the year 2007. We used multivariate logistic regression to investigate the associations between clinical variables and the presence of advanced neoplasia in a randomly selected test set, and confirmed the associations in a validation set. We used model coefficients to develop a risk score for detection of advanced colorectal neoplasia. Results Advanced colorectal neoplasia was detected in 2544 of the 35 918 included participants (7.1%). In the test set, a logistic-regression model showed that independent risk factors for advanced colorectal neoplasia were: age, sex, family history of colorectal cancer, cigarette smoking (p<0.001 for these four factors), and Body Mass Index (p=0.033). In the validation set, the model was well calibrated (ratio of expected to observed risk of advanced neoplasia: 1.00 (95% CI 0.95 to 1.06)) and had moderate discriminatory power (c-statistic 0.62). We developed a score that estimated the likelihood of detecting advanced neoplasia in the validation set, from 1.32% for patients scoring 0, to 19.12% for patients scoring 7–8. Conclusions Developed and internally validated score consisting of simple clinical factors successfully estimates the likelihood of detecting advanced colorectal neoplasia in asymptomatic Caucasian patients. Once externally validated, it may be useful for counselling or designing primary prevention studies. PMID:24385598

A score to estimate the likelihood of detecting advanced colorectal neoplasia at colonoscopy.

PubMed

Kaminski, Michal F; Polkowski, Marcin; Kraszewska, Ewa; Rupinski, Maciej; Butruk, Eugeniusz; Regula, Jaroslaw

2014-07-01

This study aimed to develop and validate a model to estimate the likelihood of detecting advanced colorectal neoplasia in Caucasian patients. We performed a cross-sectional analysis of database records for 40-year-old to 66-year-old patients who entered a national primary colonoscopy-based screening programme for colorectal cancer in 73 centres in Poland in the year 2007. We used multivariate logistic regression to investigate the associations between clinical variables and the presence of advanced neoplasia in a randomly selected test set, and confirmed the associations in a validation set. We used model coefficients to develop a risk score for detection of advanced colorectal neoplasia. Advanced colorectal neoplasia was detected in 2544 of the 35,918 included participants (7.1%). In the test set, a logistic-regression model showed that independent risk factors for advanced colorectal neoplasia were: age, sex, family history of colorectal cancer, cigarette smoking (p<0.001 for these four factors), and Body Mass Index (p=0.033). In the validation set, the model was well calibrated (ratio of expected to observed risk of advanced neoplasia: 1.00 (95% CI 0.95 to 1.06)) and had moderate discriminatory power (c-statistic 0.62). We developed a score that estimated the likelihood of detecting advanced neoplasia in the validation set, from 1.32% for patients scoring 0, to 19.12% for patients scoring 7-8. Developed and internally validated score consisting of simple clinical factors successfully estimates the likelihood of detecting advanced colorectal neoplasia in asymptomatic Caucasian patients. Once externally validated, it may be useful for counselling or designing primary prevention studies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Design and validation of diffusion MRI models of white matter

PubMed Central

Jelescu, Ileana O.; Budde, Matthew D.

2018-01-01

Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the “biological accuracy” of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus. PMID:29755979

Adaptive local linear regression with application to printer color management.

PubMed

Gupta, Maya R; Garcia, Eric K; Chin, Erika

2008-06-01

Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of neighbors used in estimation is fixed to be a global "optimal" value, chosen by cross validation. This paper proposes adapting the number of neighbors used for estimation to the local geometry of the data, without need for cross validation. The term enclosing neighborhood is introduced to describe a set of neighbors whose convex hull contains the test point when possible. It is proven that enclosing neighborhoods yield bounded estimation variance under some assumptions. Three such enclosing neighborhood definitions are presented: natural neighbors, natural neighbors inclusive, and enclosing k-NN. The effectiveness of these neighborhood definitions with local linear regression is tested for estimating lookup tables for color management. Significant improvements in error metrics are shown, indicating that enclosing neighborhoods may be a promising adaptive neighborhood definition for other local learning tasks as well, depending on the density of training samples.

Six-minute-walk test in idiopathic pulmonary fibrosis: test validation and minimal clinically important difference.

PubMed

du Bois, Roland M; Weycker, Derek; Albera, Carlo; Bradford, Williamson Z; Costabel, Ulrich; Kartashov, Alex; Lancaster, Lisa; Noble, Paul W; Sahn, Steven A; Szwarcberg, Javier; Thomeer, Michiel; Valeyre, Dominique; King, Talmadge E

2011-05-01

The 6-minute-walk test (6MWT) is a practical and clinically meaningful measure of exercise tolerance with favorable performance characteristics in various cardiac and pulmonary diseases. Performance characteristics in patients with idiopathic pulmonary fibrosis (IPF) have not been systematically evaluated. To assess the reliability, validity, and responsiveness of the 6MWT and estimate the minimal clinically important difference (MCID) in patients with IPF. The study population included all subjects completing a 6MWT in a clinical trial evaluating interferon gamma-1b (n = 822). Six-minute walk distance (6MWD) and other parameters were measured at baseline and at 24-week intervals using a standardized protocol. Parametric and distribution-independent correlation coefficients were used to assess the strength of the relationships between 6MWD and measures of pulmonary function, dyspnea, and health-related quality of life. Both distribution-based and anchor-based methods were used to estimate the MCID. Comparison of two proximal measures of 6MWD (mean interval, 24 d) demonstrated good reliability (coefficient = 0.83; P < 0.001). 6MWD was weakly correlated with measures of physiologic function and health-related quality of life; however, values were consistently and significantly lower for patients with the poorest functional status, suggesting good construct validity. Importantly, change in 6MWD was highly predictive of mortality; a 24-week decline of greater than 50 m was associated with a fourfold increase in risk of death at 1 year (hazard ratio, 4.27; 95% confidence interval, 2.57- 7.10; P < 0.001). The estimated MCID was 24-45 m. The 6MWT is a reliable, valid, and responsive measure of disease status and a valid endpoint for clinical trials in IPF.

The validity of a web-based FFQ assessed by doubly labelled water and multiple 24-h recalls.

PubMed

Medin, Anine C; Carlsen, Monica H; Hambly, Catherine; Speakman, John R; Strohmaier, Susanne; Andersen, Lene F

2017-12-01

The aim of this study was to validate the estimated habitual dietary intake from a newly developed web-based FFQ (WebFFQ), for use in an adult population in Norway. In total, ninety-two individuals were recruited. Total energy expenditure (TEE) measured by doubly labelled water was used as the reference method for energy intake (EI) in a subsample of twenty-nine women, and multiple 24-h recalls (24HR) were used as the reference method for the relative validation of macronutrients and food groups in the entire sample. Absolute differences, ratios, crude and deattenuated correlations, cross-classifications, Bland-Altman plot and plots between misreporting of EI (EI-TEE) and the relative misreporting of food groups (WebFFQ-24HR) were used to assess the validity. Results showed that EI on group level was not significantly different from TEE measured by doubly labelled water (0·7 MJ/d), but ranking abilities were poor (r -0·18). The relative validation showed an overestimation for the majority of the variables using absolute intakes, especially for the food groups 'vegetables' and 'fish and shellfish', but an improved agreement between the test and reference tool was observed for energy adjusted intakes. Deattenuated correlation coefficients were between 0·22 and 0·89, and low levels of grossly misclassified individuals (0-3 %) were observed for the majority of the energy adjusted variables for macronutrients and food groups. In conclusion, energy estimates from the WebFFQ should be used with caution, but the estimated absolute intakes on group level and ranking abilities seem acceptable for macronutrients and most food groups.

Equations based on anthropometry to predict body fat measured by absorptiometry in schoolchildren and adolescents.

PubMed

Ortiz-Hernández, Luis; Vega López, A Valeria; Ramos-Ibáñez, Norma; Cázares Lara, L Joana; Medina Gómez, R Joab; Pérez-Salgado, Diana

To develop and validate equations to estimate the percentage of body fat of children and adolescents from Mexico using anthropometric measurements. A cross-sectional study was carried out with 601 children and adolescents from Mexico aged 5-19 years. The participants were randomly divided into the following two groups: the development sample (n=398) and the validation sample (n=203). The validity of previously published equations (e.g., Slaughter) was also assessed. The percentage of body fat was estimated by dual-energy X-ray absorptiometry. The anthropometric measurements included height, sitting height, weight, waist and arm circumferences, skinfolds (triceps, biceps, subscapular, supra-iliac, and calf), and elbow and bitrochanteric breadth. Linear regression models were estimated with the percentage of body fat as the dependent variable and the anthropometric measurements as the independent variables. Equations were created based on combinations of six to nine anthropometric variables and had coefficients of determination (r 2 ) equal to or higher than 92.4% for boys and 85.8% for girls. In the validation sample, the developed equations had high r 2 values (≥85.6% in boys and ≥78.1% in girls) in all age groups, low standard errors (SE≤3.05% in boys and ≤3.52% in girls), and the intercepts were not different from the origin (p>0.050). Using the previously published equations, the coefficients of determination were lower, and/or the intercepts were different from the origin. The equations developed in this study can be used to assess the percentage of body fat of Mexican schoolchildren and adolescents, as they demonstrate greater validity and lower error compared with previously published equations. Copyright © 2017 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Web-based Food Behaviour Questionnaire: validation with grades six to eight students.

PubMed

Hanning, Rhona M; Royall, Dawna; Toews, Jenn E; Blashill, Lindsay; Wegener, Jessica; Driezen, Pete

2009-01-01

The web-based Food Behaviour Questionnaire (FBQ) includes a 24-hour diet recall, a food frequency questionnaire, and questions addressing knowledge, attitudes, intentions, and food-related behaviours. The survey has been revised since it was developed and initially validated. The current study was designed to obtain qualitative feedback and to validate the FBQ diet recall. "Think aloud" techniques were used in cognitive interviews with dietitian experts (n=11) and grade six students (n=21). Multi-ethnic students (n=201) in grades six to eight at urban southern Ontario schools completed the FBQ and, subsequently, one-on-one diet recall interviews with trained dietitians. Food group and nutrient intakes were compared. Users provided positive feedback on the FBQ. Suggestions included adding more foods, more photos for portion estimation, and online student feedback. Energy and nutrient intakes were positively correlated between FBQ and dietitian interviews, overall and by gender and grade (all p<0.001). Intraclass correlation coefficients were ≥0.5 for energy and macro-nutrients, although the web-based survey underestimated energy (10.5%) and carbohydrate (-15.6%) intakes (p<0.05). Under-estimation of rice and pasta portions on the web accounted for 50% of this discrepancy. The FBQ is valid, relative to 24-hour recall interviews, for dietary assessment in diverse populations of Ontario children in grades six to eight.

The development and validation of the On-the-job Learning Styles Questionnaire for the Nursing Profession.

PubMed

Berings, Marjolein G M C; Poell, Rob F; Simons, P Robert-Jan; van Veldhoven, Marc J P M

2007-06-01

This paper is a report of a study to develop and test the psychometric properties of the On-the-job Learning Style Questionnaire for the Nursing Profession. Although numerous questionnaires measuring learning styles have been developed, none are suitable for working environments. Existing instruments do not meet the requirements for use in workplace settings and tend to ignore the influence of different learning situations. The questionnaire was constructed using a situation-response design, measuring learning activities in different on-the-job learning situations. Content validity was ensured by basing the questionnaire on interview studies. The questionnaire was distributed to 912 Registered Nurses working in different departments of 13 general hospitals in the Netherlands at the end of 2005. The response rate was 41% (372 questionnaires). The internal factor structure of the questionnaire was partly based on the learning activities in which nurses participate and partly on the learning situation in which they are performed. The internal consistency was good. The situation-response design of the questionnaire demonstrated its added value. Construct validity was estimated using intercorrelations between the scales, and criterion validity was estimated based on the relationships of the scales with perceived professional competence. The On-the-job Learning Styles Questionnaire for the Nursing Profession is well suited to describing nurses' learning styles in on-the-job settings and has satisfactory psychometric properties.

Republic of Georgia estimates for prevalence of drug use: Randomized response techniques suggest under-estimation.

PubMed

Kirtadze, Irma; Otiashvili, David; Tabatadze, Mzia; Vardanashvili, Irina; Sturua, Lela; Zabransky, Tomas; Anthony, James C

2018-06-01

Validity of responses in surveys is an important research concern, especially in emerging market economies where surveys in the general population are a novelty, and the level of social control is traditionally higher. The Randomized Response Technique (RRT) can be used as a check on response validity when the study aim is to estimate population prevalence of drug experiences and other socially sensitive and/or illegal behaviors. To apply RRT and to study potential under-reporting of drug use in a nation-scale, population-based general population survey of alcohol and other drug use. For this first-ever household survey on addictive substances for the Country of Georgia, we used the multi-stage probability sampling of 18-to-64-year-old household residents of 111 urban and 49 rural areas. During the interviewer-administered assessments, RRT involved pairing of sensitive and non-sensitive questions about drug experiences. Based upon the standard household self-report survey estimate, an estimated 17.3% [95% confidence interval, CI: 15.5%, 19.1%] of Georgian household residents have tried cannabis. The corresponding RRT estimate was 29.9% [95% CI: 24.9%, 34.9%]. The RRT estimates for other drugs such as heroin also were larger than the standard self-report estimates. We remain unsure about what is the "true" value for prevalence of using illegal psychotropic drugs in the Republic of Georgia study population. Our RRT results suggest that standard non-RRT approaches might produce 'under-estimates' or at best, highly conservative, lower-end estimates. Copyright © 2018 Elsevier B.V. All rights reserved.

Estimating Number of People Using Calibrated Monocular Camera Based on Geometrical Analysis of Surface Area

NASA Astrophysics Data System (ADS)

Arai, Hiroyuki; Miyagawa, Isao; Koike, Hideki; Haseyama, Miki

We propose a novel technique for estimating the number of people in a video sequence; it has the advantages of being stable even in crowded situations and needing no ground-truth data. By analyzing the geometrical relationships between image pixels and their intersection volumes in the real world quantitatively, a foreground image directly indicates the number of people. Because foreground detection is possible even in crowded situations, the proposed method can be applied in such situations. Moreover, it can estimate the number of people in an a priori manner, so it needs no ground-truth data unlike existing feature-based estimation techniques. Experiments show the validity of the proposed method.

Supervised local error estimation for nonlinear image registration using convolutional neural networks

NASA Astrophysics Data System (ADS)

Eppenhof, Koen A. J.; Pluim, Josien P. W.

2017-02-01

Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation of a registration error map for nonlinear image registration. The method is based on a convolutional neural network that estimates the norm of the residual deformation from patches around each pixel in two registered images. This norm is interpreted as the registration error, and is defined for every pixel in the image domain. The network is trained using a set of artificially deformed images. Each training example is a pair of images: the original image, and a random deformation of that image. No manually labeled ground truth error is required. At test time, only the two registered images are required as input. We train and validate the network on registrations in a set of 2D digital subtraction angiography sequences, such that errors up to eight pixels can be estimated. We show that for this range of errors the convolutional network is able to learn the registration error in pairs of 2D registered images at subpixel precision. Finally, we present a proof of principle for the extension to 3D registration problems in chest CTs, showing that the method has the potential to estimate errors in 3D registration problems.

Physical Validation of TRMM TMI and PR Monthly Rain Products Over Oklahoma

NASA Technical Reports Server (NTRS)

Fisher, Brad L.

2004-01-01

The Tropical Rainfall Measuring Mission (TRMM) provides monthly rainfall estimates using data collected by the TRMM satellite. These estimates cover a substantial fraction of the earth's surface. The physical validation of TRMM estimates involves corroborating the accuracy of spaceborne estimates of areal rainfall by inferring errors and biases from ground-based rain estimates. The TRMM error budget consists of two major sources of error: retrieval and sampling. Sampling errors are intrinsic to the process of estimating monthly rainfall and occur because the satellite extrapolates monthly rainfall from a small subset of measurements collected only during satellite overpasses. Retrieval errors, on the other hand, are related to the process of collecting measurements while the satellite is overhead. One of the big challenges confronting the TRMM validation effort is how to best estimate these two main components of the TRMM error budget, which are not easily decoupled. This four-year study computed bulk sampling and retrieval errors for the TRMM microwave imager (TMI) and the precipitation radar (PR) by applying a technique that sub-samples gauge data at TRMM overpass times. Gridded monthly rain estimates are then computed from the monthly bulk statistics of the collected samples, providing a sensor-dependent gauge rain estimate that is assumed to include a TRMM equivalent sampling error. The sub-sampled gauge rain estimates are then used in conjunction with the monthly satellite and gauge (without sub- sampling) estimates to decouple retrieval and sampling errors. The computed mean sampling errors for the TMI and PR were 5.9% and 7.796, respectively, in good agreement with theoretical predictions. The PR year-to-year retrieval biases exceeded corresponding TMI biases, but it was found that these differences were partially due to negative TMI biases during cold months and positive TMI biases during warm months.

A technique for global monitoring of net solar irradiance at the ocean surface. II - Validation

NASA Technical Reports Server (NTRS)

Chertock, Beth; Frouin, Robert; Gautier, Catherine

1992-01-01

The generation and validation of the first satellite-based long-term record of surface solar irradiance over the global oceans are addressed. The record is generated using Nimbus-7 earth radiation budget (ERB) wide-field-of-view plentary-albedo data as input to a numerical algorithm designed and implemented based on radiative transfer theory. The mean monthly values of net surface solar irradiance are computed on a 9-deg latitude-longitude spatial grid for November 1978-October 1985. The new data set is validated in comparisons with short-term, regional, high-resolution, satellite-based records. The ERB-based values of net surface solar irradiance are compared with corresponding values based on radiance measurements taken by the Visible-Infrared Spin Scan Radiometer aboard GOES series satellites. Errors in the new data set are estimated to lie between 10 and 20 W/sq m on monthly time scales.

Improved Sectional Image Analysis Technique for Evaluating Fiber Orientations in Fiber-Reinforced Cement-Based Materials.

PubMed

Lee, Bang Yeon; Kang, Su-Tae; Yun, Hae-Bum; Kim, Yun Yong

2016-01-12

The distribution of fiber orientation is an important factor in determining the mechanical properties of fiber-reinforced concrete. This study proposes a new image analysis technique for improving the evaluation accuracy of fiber orientation distribution in the sectional image of fiber-reinforced concrete. A series of tests on the accuracy of fiber detection and the estimation performance of fiber orientation was performed on artificial fiber images to assess the validity of the proposed technique. The validation test results showed that the proposed technique estimates the distribution of fiber orientation more accurately than the direct measurement of fiber orientation by image analysis.

Improved Sectional Image Analysis Technique for Evaluating Fiber Orientations in Fiber-Reinforced Cement-Based Materials

PubMed Central

Lee, Bang Yeon; Kang, Su-Tae; Yun, Hae-Bum; Kim, Yun Yong

2016-01-01

The distribution of fiber orientation is an important factor in determining the mechanical properties of fiber-reinforced concrete. This study proposes a new image analysis technique for improving the evaluation accuracy of fiber orientation distribution in the sectional image of fiber-reinforced concrete. A series of tests on the accuracy of fiber detection and the estimation performance of fiber orientation was performed on artificial fiber images to assess the validity of the proposed technique. The validation test results showed that the proposed technique estimates the distribution of fiber orientation more accurately than the direct measurement of fiber orientation by image analysis. PMID:28787839

Validating GPM-based Multi-satellite IMERG Products Over South Korea

NASA Astrophysics Data System (ADS)

Wang, J.; Petersen, W. A.; Wolff, D. B.; Ryu, G. H.

2017-12-01

Accurate precipitation estimates derived from space-borne satellite measurements are critical for a wide variety of applications such as water budget studies, and prevention or mitigation of natural hazards caused by extreme precipitation events. This study validates the near-real-time Early Run, Late Run and the research-quality Final Run Integrated Multi-Satellite Retrievals for GPM (IMERG) using Korean Quantitative Precipitation Estimation (QPE). The Korean QPE data are at a 1-hour temporal resolution and 1-km by 1-km spatial resolution, and were developed by Korea Meteorological Administration (KMA) from a Real-time ADjusted Radar-AWS (Automatic Weather Station) Rainrate (RAD-RAR) system utilizing eleven radars over the Republic of Korea. The validation is conducted by comparing Version-04A IMERG (Early, Late and Final Runs) with Korean QPE over the area (124.5E-130.5E, 32.5N-39N) at various spatial and temporal scales during March 2014 through November 2016. The comparisons demonstrate the reasonably good ability of Version-04A IMERG products in estimating precipitation over South Korea's complex topography that consists mainly of hills and mountains, as well as large coastal plains. Based on this data, the Early Run, Late Run and Final Run IMERG precipitation estimates higher than 0.1mm h-1 are about 20.1%, 7.5% and 6.1% higher than Korean QPE at 0.1o and 1-hour resolutions. Detailed comparison results are available at https://wallops-prf.gsfc.nasa.gov/KoreanQPE.V04/index.html

A new age-based formula for estimating weight of Korean children.

PubMed

Park, Jungho; Kwak, Young Ho; Kim, Do Kyun; Jung, Jae Yun; Lee, Jin Hee; Jang, Hye Young; Kim, Hahn Bom; Hong, Ki Jeong

2012-09-01

The objective of this study was to develop and validate a new age-based formula for estimating body weights of Korean children. We obtained body weight and age data from a survey conducted in 2005 by the Korean Pediatric Society that was performed to establish normative values for Korean children. Children aged 0-14 were enrolled, and they were divided into three groups according to age: infants (<12 months), preschool-aged (1-4 years) and school-aged children (5-14 years). Seventy-five percent of all subjects were randomly selected to make a derivation set. Regression analysis was performed in order to produce equations that predict the weight from the age for each group. The linear equations derived from this analysis were simplified to create a weight estimating formula for Korean children. This formula was then validated using the remaining 25% of the study subjects with mean percentage error and absolute error. To determine whether a new formula accurately predicts actual weights of Korean children, we also compared this new formula to other weight estimation methods (APLS, Shann formula, Leffler formula, Nelson formula and Broselow tape). A total of 124,095 children's data were enrolled, and 19,854 (16.0%), 40,612 (32.7%) and 63,629 (51.3%) were classified as infants, preschool-aged and school-aged groups, respectively. Three equations, (age in months+9)/2, 2×(age in years)+9 and 4×(age in years)-1 were derived for infants, pre-school and school-aged groups, respectively. When these equations were applied to the validation set, the actual average weight of those children was 0.4kg heavier than our estimated weight (95% CI=0.37-0.43, p<0.001). The mean percentage error of our model (+0.9%) was lower than APLS (-11.5%), Shann formula (-8.6%), Leffler formula (-1.7%), Nelson formula (-10.0%), Best Guess formula (+5.0%) and Broselow tape (-4.8%) for all age groups. We developed and validated a simple formula to estimate body weight from the age of Korean children and found that this new formula was more accurate than other weight estimating methods. However, care should be taken when applying this formula to older children because of a large standard deviation of estimated weight. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

The Motivational Value Systems Questionnaire (MVSQ): Psychometric Analysis Using a Forced Choice Thurstonian IRT Model

PubMed Central

Merk, Josef; Schlotz, Wolff; Falter, Thomas

2017-01-01

This study presents a new measure of value systems, the Motivational Value Systems Questionnaire (MVSQ), which is based on a theory of value systems by psychologist Clare W. Graves. The purpose of the instrument is to help people identify their personal hierarchies of value systems and thus become more aware of what motivates and demotivates them in work-related contexts. The MVSQ is a forced-choice (FC) measure, making it quicker to complete and more difficult to intentionally distort, but also more difficult to assess its psychometric properties due to ipsativity of FC data compared to rating scales. To overcome limitations of ipsative data, a Thurstonian IRT (TIRT) model was fitted to the questionnaire data, based on a broad sample of N = 1,217 professionals and students. Comparison of normative (IRT) scale scores and ipsative scores suggested that MVSQ IRT scores are largely freed from restrictions due to ipsativity and thus allow interindividual comparison of scale scores. Empirical reliability was estimated using a sample-based simulation approach which showed acceptable and good estimates and, on average, slightly higher test-retest reliabilities. Further, validation studies provided evidence on both construct validity and criterion-related validity. Scale score correlations and associations of scores with both age and gender were largely in line with theoretically- and empirically-based expectations, and results of a multitrait-multimethod analysis supports convergent and discriminant construct validity. Criterion validity was assessed by examining the relation of value system preferences to departmental affiliation which revealed significant relations in line with prior hypothesizing. These findings demonstrate the good psychometric properties of the MVSQ and support its application in the assessment of value systems in work-related contexts. PMID:28979228

The Motivational Value Systems Questionnaire (MVSQ): Psychometric Analysis Using a Forced Choice Thurstonian IRT Model.

PubMed

Merk, Josef; Schlotz, Wolff; Falter, Thomas

2017-01-01

This study presents a new measure of value systems, the Motivational Value Systems Questionnaire (MVSQ), which is based on a theory of value systems by psychologist Clare W. Graves. The purpose of the instrument is to help people identify their personal hierarchies of value systems and thus become more aware of what motivates and demotivates them in work-related contexts. The MVSQ is a forced-choice (FC) measure, making it quicker to complete and more difficult to intentionally distort, but also more difficult to assess its psychometric properties due to ipsativity of FC data compared to rating scales. To overcome limitations of ipsative data, a Thurstonian IRT (TIRT) model was fitted to the questionnaire data, based on a broad sample of N = 1,217 professionals and students. Comparison of normative (IRT) scale scores and ipsative scores suggested that MVSQ IRT scores are largely freed from restrictions due to ipsativity and thus allow interindividual comparison of scale scores. Empirical reliability was estimated using a sample-based simulation approach which showed acceptable and good estimates and, on average, slightly higher test-retest reliabilities. Further, validation studies provided evidence on both construct validity and criterion-related validity. Scale score correlations and associations of scores with both age and gender were largely in line with theoretically- and empirically-based expectations, and results of a multitrait-multimethod analysis supports convergent and discriminant construct validity. Criterion validity was assessed by examining the relation of value system preferences to departmental affiliation which revealed significant relations in line with prior hypothesizing. These findings demonstrate the good psychometric properties of the MVSQ and support its application in the assessment of value systems in work-related contexts.

Quality and rigor of the concept mapping methodology: a pooled study analysis.

PubMed

Rosas, Scott R; Kane, Mary

2012-05-01

The use of concept mapping in research and evaluation has expanded dramatically over the past 20 years. Researchers in academic, organizational, and community-based settings have applied concept mapping successfully without the benefit of systematic analyses across studies to identify the features of a methodologically sound study. Quantitative characteristics and estimates of quality and rigor that may guide for future studies are lacking. To address this gap, we conducted a pooled analysis of 69 concept mapping studies to describe characteristics across study phases, generate specific indicators of validity and reliability, and examine the relationship between select study characteristics and quality indicators. Individual study characteristics and estimates were pooled and quantitatively summarized, describing the distribution, variation and parameters for each. In addition, variation in the concept mapping data collection in relation to characteristics and estimates was examined. Overall, results suggest concept mapping yields strong internal representational validity and very strong sorting and rating reliability estimates. Validity and reliability were consistently high despite variation in participation and task completion percentages across data collection modes. The implications of these findings as a practical reference to assess the quality and rigor for future concept mapping studies are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Formal Approach to Empirical Dynamic Model Optimization and Validation

NASA Technical Reports Server (NTRS)

Crespo, Luis G; Morelli, Eugene A.; Kenny, Sean P.; Giesy, Daniel P.

2014-01-01

A framework was developed for the optimization and validation of empirical dynamic models subject to an arbitrary set of validation criteria. The validation requirements imposed upon the model, which may involve several sets of input-output data and arbitrary specifications in time and frequency domains, are used to determine if model predictions are within admissible error limits. The parameters of the empirical model are estimated by finding the parameter realization for which the smallest of the margins of requirement compliance is as large as possible. The uncertainty in the value of this estimate is characterized by studying the set of model parameters yielding predictions that comply with all the requirements. Strategies are presented for bounding this set, studying its dependence on admissible prediction error set by the analyst, and evaluating the sensitivity of the model predictions to parameter variations. This information is instrumental in characterizing uncertainty models used for evaluating the dynamic model at operating conditions differing from those used for its identification and validation. A practical example based on the short period dynamics of the F-16 is used for illustration.

Validation of the physical and RBE-weighted dose estimator based on PHITS coupled with a microdosimetric kinetic model for proton therapy.

PubMed

Takada, Kenta; Sato, Tatsuhiko; Kumada, Hiroaki; Koketsu, Junichi; Takei, Hideyuki; Sakurai, Hideyuki; Sakae, Takeji

2018-01-01

The microdosimetric kinetic model (MKM) is widely used for estimating relative biological effectiveness (RBE)-weighted doses for various radiotherapies because it can determine the surviving fraction of irradiated cells based on only the lineal energy distribution, and it is independent of the radiation type and ion species. However, the applicability of the method to proton therapy has not yet been investigated thoroughly. In this study, we validated the RBE-weighted dose calculated by the MKM in tandem with the Monte Carlo code PHITS for proton therapy by considering the complete simulation geometry of the clinical proton beam line. The physical dose, lineal energy distribution, and RBE-weighted dose for a 155 MeV mono-energetic and spread-out Bragg peak (SOBP) beam of 60 mm width were evaluated. In estimating the physical dose, the calculated depth dose distribution by irradiating the mono-energetic beam using PHITS was consistent with the data measured by a diode detector. A maximum difference of 3.1% in the depth distribution was observed for the SOBP beam. In the RBE-weighted dose validation, the calculated lineal energy distributions generally agreed well with the published measurement data. The calculated and measured RBE-weighted doses were in excellent agreement, except at the Bragg peak region of the mono-energetic beam, where the calculation overestimated the measured data by ~15%. This research has provided a computational microdosimetric approach based on a combination of PHITS and MKM for typical clinical proton beams. The developed RBE-estimator function has potential application in the treatment planning system for various radiotherapies. © The Author 2017. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Validation of the physical and RBE-weighted dose estimator based on PHITS coupled with a microdosimetric kinetic model for proton therapy

PubMed Central

Sato, Tatsuhiko; Kumada, Hiroaki; Koketsu, Junichi; Takei, Hideyuki; Sakurai, Hideyuki; Sakae, Takeji

2018-01-01

Abstract The microdosimetric kinetic model (MKM) is widely used for estimating relative biological effectiveness (RBE)-weighted doses for various radiotherapies because it can determine the surviving fraction of irradiated cells based on only the lineal energy distribution, and it is independent of the radiation type and ion species. However, the applicability of the method to proton therapy has not yet been investigated thoroughly. In this study, we validated the RBE-weighted dose calculated by the MKM in tandem with the Monte Carlo code PHITS for proton therapy by considering the complete simulation geometry of the clinical proton beam line. The physical dose, lineal energy distribution, and RBE-weighted dose for a 155 MeV mono-energetic and spread-out Bragg peak (SOBP) beam of 60 mm width were evaluated. In estimating the physical dose, the calculated depth dose distribution by irradiating the mono-energetic beam using PHITS was consistent with the data measured by a diode detector. A maximum difference of 3.1% in the depth distribution was observed for the SOBP beam. In the RBE-weighted dose validation, the calculated lineal energy distributions generally agreed well with the published measurement data. The calculated and measured RBE-weighted doses were in excellent agreement, except at the Bragg peak region of the mono-energetic beam, where the calculation overestimated the measured data by ~15%. This research has provided a computational microdosimetric approach based on a combination of PHITS and MKM for typical clinical proton beams. The developed RBE-estimator function has potential application in the treatment planning system for various radiotherapies. PMID:29087492

Accelerometer-based measures in physical activity surveillance: current practices and issues.

PubMed

Pedišić, Željko; Bauman, Adrian

2015-02-01

Self-reports of physical activity (PA) have been the mainstay of measurement in most non-communicable disease (NCD) surveillance systems. To these, other measures are added to summate to a comprehensive PA surveillance system. Recently, some national NCD surveillance systems have started using accelerometers as a measure of PA. The purpose of this paper was specifically to appraise the suitability and role of accelerometers for population-level PA surveillance. A thorough literature search was conducted to examine aspects of the generalisability, reliability, validity, comprehensiveness and between-study comparability of accelerometer estimates, and to gauge the simplicity, cost-effectiveness, adaptability and sustainability of their use in NCD surveillance. Accelerometer data collected in PA surveillance systems may not provide estimates that are generalisable to the target population. Accelerometer-based estimates have adequate reliability for PA surveillance, but there are still several issues associated with their validity. Accelerometer-based prevalence estimates are largely dependent on the investigators' choice of intensity cut-off points. Maintaining standardised accelerometer data collections in long-term PA surveillance systems is difficult, which may cause discontinuity in time-trend data. The use of accelerometers does not necessarily produce useful between-study and international comparisons due to lack of standardisation of data collection and processing methods. To conclude, it appears that accelerometers still have limitations regarding generalisability, validity, comprehensiveness, simplicity, affordability, adaptability, between-study comparability and sustainability. Therefore, given the current evidence, it seems that the widespread adoption of accelerometers specifically for large-scale PA surveillance systems may be premature. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Analytical Formulation for Sizing and Estimating the Dimensions and Weight of Wind Turbine Hub and Drivetrain Components

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

Guo, Y.; Parsons, T.; King, R.

This report summarizes the theory, verification, and validation of a new sizing tool for wind turbine drivetrain components, the Drivetrain Systems Engineering (DriveSE) tool. DriveSE calculates the dimensions and mass properties of the hub, main shaft, main bearing(s), gearbox, bedplate, transformer if up-tower, and yaw system. The level of fi¬ delity for each component varies depending on whether semiempirical parametric or physics-based models are used. The physics-based models have internal iteration schemes based on system constraints and design criteria. Every model is validated against available industry data or finite-element analysis. The verification and validation results show that the models reasonablymore » capture primary drivers for the sizing and design of major drivetrain components.« less

Correspondence between ion-cluster and bulk thermodynamics: on the validity of the cluster pair approximation

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

Vlcek, Lukas; Chialvo, Ariel; Simonson, J Michael

2013-01-01

Molecular models and experimental estimates based on the cluster pair approximation (CPA) provide inconsistent predictions of absolute single-ion hydration properties. To understand the origin of this discrepancy we used molecular simulations to study the transition between hydration of alkali metal and halide ions in small aqueous clusters and bulk water. The results demonstrate that the assumptions underlying the CPA are not generally valid as a result of a significant shift in the ion hydration free energies (~15 kJ/mol) and enthalpies (~47 kJ/mol) in the intermediate range of cluster sizes. When this effect is accounted for, the systematic differences between modelsmore » and experimental predictions disappear, and the value of absolute proton hydration enthalpy based on the CPA gets in closer agreement with other estimates.« less

Assessing the Relative Performance of Microwave-based Satellite Rain Rate Retrievals using TRMM Ground Validation Data

NASA Technical Reports Server (NTRS)

Wolff, David B.; Fisher, Brad L.

2008-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecast of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (AQUA) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparison with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellites is examined via comparisons with GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25 terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSRE over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm hr-1. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products.

Two-Tiered Violence Risk Estimates: a validation study of an integrated-actuarial risk assessment instrument.

PubMed

Mills, Jeremy F; Gray, Andrew L

2013-11-01

This study is an initial validation study of the Two-Tiered Violence Risk Estimates instrument (TTV), a violence risk appraisal instrument designed to support an integrated-actuarial approach to violence risk assessment. The TTV was scored retrospectively from file information on a sample of violent offenders. Construct validity was examined by comparing the TTV with instruments that have shown utility to predict violence that were prospectively scored: The Historical-Clinical-Risk Management-20 (HCR-20) and Lifestyle Criminality Screening Form (LCSF). Predictive validity was examined through a long-term follow-up of 12.4 years with a sample of 78 incarcerated offenders. Results show the TTV to be highly correlated with the HCR-20 and LCSF. The base rate for violence over the follow-up period was 47.4%, and the TTV was equally predictive of violent recidivism relative to the HCR-20 and LCSF. Discussion centers on the advantages of an integrated-actuarial approach to the assessment of violence risk.

Validation of the Regicor Short Physical Activity Questionnaire for the Adult Population

PubMed Central

Molina, Luis; Sarmiento, Manuel; Peñafiel, Judith; Donaire, David; Garcia-Aymerich, Judith; Gomez, Miquel; Ble, Mireia; Ruiz, Sonia; Frances, Albert; Schröder, Helmut; Marrugat, Jaume; Elosua, Roberto

2017-01-01

Objective To develop and validate a short questionnaire to estimate physical activity (PA) practice and sedentary behavior for the adult population. Methods The short questionnaire was developed using data from a cross-sectional population-based survey (n = 6352) that included the Minnesota leisure-time PA questionnaire. Activities that explained a significant proportion of the variability of population PA practice were identified. Validation of the short questionnaire included a cross-sectional component to assess validity with respect to the data collected by accelerometers and a longitudinal component to assess reliability and sensitivity to detect changes (n = 114, aged 35 to 74 years). Results Six types of activities that accounted for 87% of population variability in PA estimated with the Minnesota questionnaire were selected. The short questionnaire estimates energy expenditure in total PA and by intensity (light, moderate, vigorous), and includes 2 questions about sedentary behavior and a question about occupational PA. The short questionnaire showed high reliability, with intraclass correlation coefficients ranging between 0.79 to 0.95. The Spearman correlation coefficients between estimated energy expenditure obtained with the questionnaire and the number of steps detected by the accelerometer were as follows: 0.36 for total PA, 0.40 for moderate intensity, and 0.26 for vigorous intensity. The questionnaire was sensitive to detect changes in moderate and vigorous PA (correlation coefficients ranging from 0.26 to 0.34). Conclusion The REGICOR short questionnaire is reliable, valid, and sensitive to detect changes in moderate and vigorous PA. This questionnaire could be used in daily clinical practice and epidemiological studies. PMID:28085886

Predictors of validity and reliability of a physical activity record in adolescents

PubMed Central

2013-01-01

Background Poor to moderate validity of self-reported physical activity instruments is commonly observed in young people in low- and middle-income countries. However, the reasons for such low validity have not been examined in detail. We tested the validity of a self-administered daily physical activity record in adolescents and assessed if personal characteristics or the convenience level of reporting physical activity modified the validity estimates. Methods The study comprised a total of 302 adolescents from an urban and rural area in Ecuador. Validity was evaluated by comparing the record with accelerometer recordings for seven consecutive days. Test-retest reliability was examined by comparing registrations from two records administered three weeks apart. Time spent on sedentary (SED), low (LPA), moderate (MPA) and vigorous (VPA) intensity physical activity was estimated. Bland Altman plots were used to evaluate measurement agreement. We assessed if age, sex, urban or rural setting, anthropometry and convenience of completing the record explained differences in validity estimates using a linear mixed model. Results Although the record provided higher estimates for SED and VPA and lower estimates for LPA and MPA compared to the accelerometer, it showed an overall fair measurement agreement for validity. There was modest reliability for assessing physical activity in each intensity level. Validity was associated with adolescents’ personal characteristics: sex (SED: P = 0.007; LPA: P = 0.001; VPA: P = 0.009) and setting (LPA: P = 0.000; MPA: P = 0.047). Reliability was associated with the convenience of completing the physical activity record for LPA (low convenience: P = 0.014; high convenience: P = 0.045). Conclusions The physical activity record provided acceptable estimates for reliability and validity on a group level. Sex and setting were associated with validity estimates, whereas convenience to fill out the record was associated with better reliability estimates for LPA. This tendency of improved reliability estimates for adolescents reporting higher convenience merits further consideration. PMID:24289296

A 45-Second Self-Test for Cardiorespiratory Fitness: Heart Rate-Based Estimation in Healthy Individuals

PubMed Central

Bonato, Matteo; Papini, Gabriele; Bosio, Andrea; Mohammed, Rahil A.; Bonomi, Alberto G.; Moore, Jonathan P.; Merati, Giampiero; La Torre, Antonio; Kubis, Hans-Peter

2016-01-01

Cardio-respiratory fitness (CRF) is a widespread essential indicator in Sports Science as well as in Sports Medicine. This study aimed to develop and validate a prediction model for CRF based on a 45 second self-test, which can be conducted anywhere. Criterion validity, test re-test study was set up to accomplish our objectives. Data from 81 healthy volunteers (age: 29 ± 8 years, BMI: 24.0 ± 2.9), 18 of whom females, were used to validate this test against gold standard. Nineteen volunteers repeated this test twice in order to evaluate its repeatability. CRF estimation models were developed using heart rate (HR) features extracted from the resting, exercise, and the recovery phase. The most predictive HR feature was the intercept of the linear equation fitting the HR values during the recovery phase normalized for the height2 (r2 = 0.30). The Ruffier-Dickson Index (RDI), which was originally developed for this squat test, showed a negative significant correlation with CRF (r = -0.40), but explained only 15% of the variability in CRF. A multivariate model based on RDI and sex, age and height increased the explained variability up to 53% with a cross validation (CV) error of 0.532 L ∙ min-1 and substantial repeatability (ICC = 0.91). The best predictive multivariate model made use of the linear intercept of HR at the beginning of the recovery normalized for height2 and age2; this had an adjusted r2 = 0. 59, a CV error of 0.495 L·min-1 and substantial repeatability (ICC = 0.93). It also had a higher agreement in classifying CRF levels (κ = 0.42) than RDI-based model (κ = 0.29). In conclusion, this simple 45 s self-test can be used to estimate and classify CRF in healthy individuals with moderate accuracy and large repeatability when HR recovery features are included. PMID:27959935

A 45-Second Self-Test for Cardiorespiratory Fitness: Heart Rate-Based Estimation in Healthy Individuals.

PubMed

Sartor, Francesco; Bonato, Matteo; Papini, Gabriele; Bosio, Andrea; Mohammed, Rahil A; Bonomi, Alberto G; Moore, Jonathan P; Merati, Giampiero; La Torre, Antonio; Kubis, Hans-Peter

2016-01-01

Cardio-respiratory fitness (CRF) is a widespread essential indicator in Sports Science as well as in Sports Medicine. This study aimed to develop and validate a prediction model for CRF based on a 45 second self-test, which can be conducted anywhere. Criterion validity, test re-test study was set up to accomplish our objectives. Data from 81 healthy volunteers (age: 29 ± 8 years, BMI: 24.0 ± 2.9), 18 of whom females, were used to validate this test against gold standard. Nineteen volunteers repeated this test twice in order to evaluate its repeatability. CRF estimation models were developed using heart rate (HR) features extracted from the resting, exercise, and the recovery phase. The most predictive HR feature was the intercept of the linear equation fitting the HR values during the recovery phase normalized for the height2 (r2 = 0.30). The Ruffier-Dickson Index (RDI), which was originally developed for this squat test, showed a negative significant correlation with CRF (r = -0.40), but explained only 15% of the variability in CRF. A multivariate model based on RDI and sex, age and height increased the explained variability up to 53% with a cross validation (CV) error of 0.532 L ∙ min-1 and substantial repeatability (ICC = 0.91). The best predictive multivariate model made use of the linear intercept of HR at the beginning of the recovery normalized for height2 and age2; this had an adjusted r2 = 0. 59, a CV error of 0.495 L·min-1 and substantial repeatability (ICC = 0.93). It also had a higher agreement in classifying CRF levels (κ = 0.42) than RDI-based model (κ = 0.29). In conclusion, this simple 45 s self-test can be used to estimate and classify CRF in healthy individuals with moderate accuracy and large repeatability when HR recovery features are included.

Validation of vision-based range estimation algorithms using helicopter flight data

NASA Technical Reports Server (NTRS)

Smith, Phillip N.

1993-01-01

The objective of this research was to demonstrate the effectiveness of an optic flow method for passive range estimation using a Kalman-filter implementation with helicopter flight data. This paper is divided into the following areas: (1) ranging algorithm; (2) flight experiment; (3) analysis methodology; (4) results; and (5) concluding remarks. The discussion is presented in viewgraph format.

Statistical uncertainty of eddy flux-based estimates of gross ecosystem carbon exchange at Howland Forest, Maine

Treesearch

S.C. Hagen; B.H. Braswell; E. Linder; S. Frolking; A.D. Richardson; David Hollinger. D.Y; Hollinger. D.Y

2006-01-01

We present an uncertainty analysis of gross ecosystem carbon exchange (GEE) estimates derived from 7 years of continuous eddy covariance measurements of forest atmosphere CO2 fluxes at Howland Forest, Maine, USA. These data, which have high temporal resolution, can be used to validate process modeling analyses, remote sensing assessments, and field surveys. However,...

Optimized Free Energies from Bidirectional Single-Molecule Force Spectroscopy

NASA Astrophysics Data System (ADS)

Minh, David D. L.; Adib, Artur B.

2008-05-01

An optimized method for estimating path-ensemble averages using data from processes driven in opposite directions is presented. Based on this estimator, bidirectional expressions for reconstructing free energies and potentials of mean force from single-molecule force spectroscopy—valid for biasing potentials of arbitrary stiffness—are developed. Numerical simulations on a model potential indicate that these methods perform better than unidirectional strategies.

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

NASA Astrophysics Data System (ADS)

Ma, Zhisai; Liu, Li; Zhou, Sida; Naets, Frank; Heylen, Ward; Desmet, Wim

2017-03-01

The problem of linear time-varying(LTV) system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the "frozen-time" assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stability-preserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system's stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam experimental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides a new way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

Locally Weighted Score Estimation for Quantile Classification in Binary Regression Models

PubMed Central

Rice, John D.; Taylor, Jeremy M. G.

2016-01-01

One common use of binary response regression methods is classification based on an arbitrary probability threshold dictated by the particular application. Since this is given to us a priori, it is sensible to incorporate the threshold into our estimation procedure. Specifically, for the linear logistic model, we solve a set of locally weighted score equations, using a kernel-like weight function centered at the threshold. The bandwidth for the weight function is selected by cross validation of a novel hybrid loss function that combines classification error and a continuous measure of divergence between observed and fitted values; other possible cross-validation functions based on more common binary classification metrics are also examined. This work has much in common with robust estimation, but diers from previous approaches in this area in its focus on prediction, specifically classification into high- and low-risk groups. Simulation results are given showing the reduction in error rates that can be obtained with this method when compared with maximum likelihood estimation, especially under certain forms of model misspecification. Analysis of a melanoma data set is presented to illustrate the use of the method in practice. PMID:28018492

Impact of sample collection participation on the validity of estimated measures of association in the National Birth Defects Prevention Study when assessing gene-environment interactions.

PubMed

Jenkins, Mary M; Reefhuis, Jennita; Herring, Amy H; Honein, Margaret A

2017-12-01

To better understand the impact that nonresponse for specimen collection has on the validity of estimates of association, we examined associations between self-reported maternal periconceptional smoking, folic acid use, or pregestational diabetes mellitus and six birth defects among families who did and did not submit buccal cell samples for DNA following a telephone interview as part of the National Birth Defects Prevention Study (NBDPS). Analyses included control families with live born infants who had no birth defects (N = 9,465), families of infants with anorectal atresia or stenosis (N = 873), limb reduction defects (N = 1,037), gastroschisis (N = 1,090), neural tube defects (N = 1,764), orofacial clefts (N = 3,836), or septal heart defects (N = 4,157). Estimated dates of delivery were between 1997 and 2009. For each exposure and birth defect, odds ratios and 95% confidence intervals were calculated using logistic regression stratified by race-ethnicity and sample collection status. Tests for interaction were applied to identify potential differences between estimated measures of association based on sample collection status. Significant differences in estimated measures of association were observed in only four of 48 analyses with sufficient sample sizes. Despite lower than desired participation rates in buccal cell sample collection, this validation provides some reassurance that the estimates obtained for sample collectors and noncollectors are comparable. These findings support the validity of observed associations in gene-environment interaction studies for the selected exposures and birth defects among NBDPS participants who submitted DNA samples. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Implications of GRACE Satellite Gravity Measurements for Diverse Hydrological Applications

NASA Astrophysics Data System (ADS)

Yirdaw-Zeleke, Sitotaw

Soil moisture plays a major role in the hydrologic water balance and is the basis for most hydrological models. It influences the partitioning of energy and moisture inputs at the land surface. Because of its importance, it has been used as a key variable for many hydrological studies such as flood forecasting, drought studies and the determination of groundwater recharge. Therefore, spatially distributed soil moisture with reasonable temporal resolution is considered a valuable source of information for hydrological model parameterization and validation. Unfortunately, soil moisture is difficult to measure and remains essentially unmeasured over spatial and temporal scales needed for a number of hydrological model applications. In 2002, the Gravity Recovery And Climate Experiment (GRACE) satellite platform was launched to measure, among other things, the gravitational field of the earth. Over its life span, these orbiting satellites have produced time series of mass changes of the earth-atmosphere system. The subsequent outcome of this, after integration over a number of years, is a time series of highly refined images of the earth's mass distribution. In addition to quantifying the static distribution of mass, the month-to-month variation in the earth's gravitational field are indicative of the integrated value of the subsurface total water storage for specific catchments. Utilization of these natural changes in the earth's gravitational field entails the transformation of the derived GRACE geopotential spherical harmonic coefficients into spatially varying time series estimates of total water storage. These remotely sensed basin total water storage estimates can be routinely validated against independent estimates of total water storage from an atmospheric-based water balance approach or from well calibrated macroscale hydrologic models. The hydrological relevance and implications of remotely estimated GRACE total water storage over poorly gauged, wetland-dominated watershed as well as over a deltaic region underlain by a thick sand aquifer in Western Canada are the focus of this thesis. The domain of the first case study was the Mackenzie River Basin wherein the GRACE total water storage estimates were successfully inter-compared and validated with the atmospheric based water balance. These were then used to assess the WAT-CLASS hydrological model estimates of total water storage. The outcome of this inter-comparison revealed the potential application of the GRACE-based approach for the closure of the hydrological water balance of the Mackenzie River Basin as well as a dependable source of data for the calibration of traditional hydrological models. The Mackenzie River Basin result led to a second case study where the GRACE-based total water storage was validated using storage estimated from the atmospheric-based water balance P--E computations in conjunction with the measured streamflow records for the Saskatchewan River Basin at its Grand Rapids outlet in Manitoba. The fallout from this comparison was then applied to the characterization of the Prairie-wide 2002/2003 drought enabling the development of a new drought index now known as the Total Storage Deficit Index (TSDI). This study demonstrated the potential application of the GRACE-based technique as a tool for drought characterization in the Canadian Prairies. Finally, the hydroinformatic approach based on the artificial neural network (ANN) enabled the downscaling of the groundwater component from the total water storage estimate from the remote sensing satellite, GRACE. This was subsequently explored as an alternate source of calibration and validation for a hydrological modeling application over the Assiniboine Delta Aquifer in Manitoba. Interestingly, a high correlation exists between the simulated groundwater storage from the coupled hydrological model, CLM-PF and the downscaled groundwater time series storage from the remote sensing satellite GRACE over this 4,000 km2 deltaic basin in Canada.

Evaluation of a Moderate Resolution, Satellite-Based Impervious Surface Map Using an Independent, High-Resolution Validation Dataset

EPA Science Inventory

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data ...

Application of a Tenax Model to Assess Bioavailability of Polychlorinated Biphenyls in Field Sediments

EPA Science Inventory

Recent literature has shown that bioavailability-based techniques, such as Tenax extraction, can estimate sediment exposure to benthos. In a previous study by the authors,Tenax extraction was used to create and validate a literature-based Tenax model to predict oligochaete bioac...

Effect of non-Poisson samples on turbulence spectra from laser velocimetry

NASA Technical Reports Server (NTRS)

Sree, Dave; Kjelgaard, Scott O.; Sellers, William L., III

1994-01-01

Spectral analysis of laser velocimetry (LV) data plays an important role in characterizing a turbulent flow and in estimating the associated turbulence scales, which can be helpful in validating theoretical and numerical turbulence models. The determination of turbulence scales is critically dependent on the accuracy of the spectral estimates. Spectral estimations from 'individual realization' laser velocimetry data are typically based on the assumption of a Poisson sampling process. What this Note has demonstrated is that the sampling distribution must be considered before spectral estimates are used to infer turbulence scales.

A weight modification sequential method for VSC-MTDC power system state estimation

NASA Astrophysics Data System (ADS)

Yang, Xiaonan; Zhang, Hao; Li, Qiang; Guo, Ziming; Zhao, Kun; Li, Xinpeng; Han, Feng

2017-06-01

This paper presents an effective sequential approach based on weight modification for VSC-MTDC power system state estimation, called weight modification sequential method. The proposed approach simplifies the AC/DC system state estimation algorithm through modifying the weight of state quantity to keep the matrix dimension constant. The weight modification sequential method can also make the VSC-MTDC system state estimation calculation results more ccurate and increase the speed of calculation. The effectiveness of the proposed weight modification sequential method is demonstrated and validated in modified IEEE 14 bus system.

Use of the forced-oscillation technique to estimate spirometry values.

PubMed

Yamamoto, Shoichiro; Miyoshi, Seigo; Katayama, Hitoshi; Okazaki, Mikio; Shigematsu, Hisayuki; Sano, Yoshifumi; Matsubara, Minoru; Hamaguchi, Naohiko; Okura, Takafumi; Higaki, Jitsuo

2017-01-01

Spirometry is sometimes difficult to perform in elderly patients and in those with severe respiratory distress. The forced-oscillation technique (FOT) is a simple and noninvasive method of measuring respiratory impedance. The aim of this study was to determine if FOT data reflect spirometric indices. Patients underwent both FOT and spirometry procedures prior to inclusion in development (n=1,089) and validation (n=552) studies. Multivariate linear regression analysis was performed to identify FOT parameters predictive of vital capacity (VC), forced VC (FVC), and forced expiratory volume in 1 second (FEV 1 ). A regression equation was used to calculate estimated VC, FVC, and FEV 1 . We then determined whether the estimated data reflected spirometric indices. Agreement between actual and estimated spirometry data was assessed by Bland-Altman analysis. Significant correlations were observed between actual and estimated VC, FVC, and FEV 1 values (all r >0.8 and P <0.001). These results were deemed robust by a separate validation study (all r >0.8 and P <0.001). Bias between the actual data and estimated data for VC, FVC, and FEV 1 in the development study was 0.007 L (95% limits of agreement [LOA] 0.907 and -0.893 L), -0.064 L (95% LOA 0.843 and -0.971 L), and -0.039 L (95% LOA 0.735 and -0.814 L), respectively. On the other hand, bias between the actual data and estimated data for VC, FVC, and FEV 1 in the validation study was -0.201 L (95% LOA 0.62 and -1.022 L), -0.262 L (95% LOA 0.582 and -1.106 L), and -0.174 L (95% LOA 0.576 and -0.923 L), respectively, suggesting that the estimated data in the validation study did not have high accuracy. Further studies are needed to generate more accurate regression equations for spirometric indices based on FOT measurements.

Testing Software Development Project Productivity Model

NASA Astrophysics Data System (ADS)

Lipkin, Ilya

Software development is an increasingly influential factor in today's business environment, and a major issue affecting software development is how an organization estimates projects. If the organization underestimates cost, schedule, and quality requirements, the end results will not meet customer needs. On the other hand, if the organization overestimates these criteria, resources that could have been used more profitably will be wasted. There is no accurate model or measure available that can guide an organization in a quest for software development, with existing estimation models often underestimating software development efforts as much as 500 to 600 percent. To address this issue, existing models usually are calibrated using local data with a small sample size, with resulting estimates not offering improved cost analysis. This study presents a conceptual model for accurately estimating software development, based on an extensive literature review and theoretical analysis based on Sociotechnical Systems (STS) theory. The conceptual model serves as a solution to bridge organizational and technological factors and is validated using an empirical dataset provided by the DoD. Practical implications of this study allow for practitioners to concentrate on specific constructs of interest that provide the best value for the least amount of time. This study outlines key contributing constructs that are unique for Software Size E-SLOC, Man-hours Spent, and Quality of the Product, those constructs having the largest contribution to project productivity. This study discusses customer characteristics and provides a framework for a simplified project analysis for source selection evaluation and audit task reviews for the customers and suppliers. Theoretical contributions of this study provide an initial theory-based hypothesized project productivity model that can be used as a generic overall model across several application domains such as IT, Command and Control, Simulation and etc... This research validates findings from previous work concerning software project productivity and leverages said results in this study. The hypothesized project productivity model provides statistical support and validation of expert opinions used by practitioners in the field of software project estimation.

Screening for cognitive impairment in older individuals. Validation study of a computer-based test.

PubMed

Green, R C; Green, J; Harrison, J M; Kutner, M H

1994-08-01

This study examined the validity of a computer-based cognitive test that was recently designed to screen the elderly for cognitive impairment. Criterion-related validity was examined by comparing test scores of impaired patients and normal control subjects. Construct-related validity was computed through correlations between computer-based subtests and related conventional neuropsychological subtests. University center for memory disorders. Fifty-two patients with mild cognitive impairment by strict clinical criteria and 50 unimpaired, age- and education-matched control subjects. Control subjects were rigorously screened by neurological, neuropsychological, imaging, and electrophysiological criteria to identify and exclude individuals with occult abnormalities. Using a cut-off total score of 126, this computer-based instrument had a sensitivity of 0.83 and a specificity of 0.96. Using a prevalence estimate of 10%, predictive values, positive and negative, were 0.70 and 0.96, respectively. Computer-based subtests correlated significantly with conventional neuropsychological tests measuring similar cognitive domains. Thirteen (17.8%) of 73 volunteers with normal medical histories were excluded from the control group, with unsuspected abnormalities on standard neuropsychological tests, electroencephalograms, or magnetic resonance imaging scans. Computer-based testing is a valid screening methodology for the detection of mild cognitive impairment in the elderly, although this particular test has important limitations. Broader applications of computer-based testing will require extensive population-based validation. Future studies should recognize that normal control subjects without a history of disease who are typically used in validation studies may have a high incidence of unsuspected abnormalities on neurodiagnostic studies.

Validation of Statistical Models for Estimating Hospitalization Associated with Influenza and Other Respiratory Viruses

PubMed Central

Chan, King-Pan; Chan, Kwok-Hung; Wong, Wilfred Hing-Sang; Peiris, J. S. Malik; Wong, Chit-Ming

2011-01-01

Background Reliable estimates of disease burden associated with respiratory viruses are keys to deployment of preventive strategies such as vaccination and resource allocation. Such estimates are particularly needed in tropical and subtropical regions where some methods commonly used in temperate regions are not applicable. While a number of alternative approaches to assess the influenza associated disease burden have been recently reported, none of these models have been validated with virologically confirmed data. Even fewer methods have been developed for other common respiratory viruses such as respiratory syncytial virus (RSV), parainfluenza and adenovirus. Methods and Findings We had recently conducted a prospective population-based study of virologically confirmed hospitalization for acute respiratory illnesses in persons <18 years residing in Hong Kong Island. Here we used this dataset to validate two commonly used models for estimation of influenza disease burden, namely the rate difference model and Poisson regression model, and also explored the applicability of these models to estimate the disease burden of other respiratory viruses. The Poisson regression models with different link functions all yielded estimates well correlated with the virologically confirmed influenza associated hospitalization, especially in children older than two years. The disease burden estimates for RSV, parainfluenza and adenovirus were less reliable with wide confidence intervals. The rate difference model was not applicable to RSV, parainfluenza and adenovirus and grossly underestimated the true burden of influenza associated hospitalization. Conclusion The Poisson regression model generally produced satisfactory estimates in calculating the disease burden of respiratory viruses in a subtropical region such as Hong Kong. PMID:21412433

Discovering new PI3Kα inhibitors with a strategy of combining ligand-based and structure-based virtual screening

NASA Astrophysics Data System (ADS)

Yu, Miao; Gu, Qiong; Xu, Jun

2018-02-01

PI3Kα is a promising drug target for cancer chemotherapy. In this paper, we report a strategy of combing ligand-based and structure-based virtual screening to identify new PI3Kα inhibitors. First, naïve Bayesian (NB) learning models and a 3D-QSAR pharmacophore model were built based upon known PI3Kα inhibitors. Then, the SPECS library was screened by the best NB model. This resulted in virtual hits, which were validated by matching the structures against the pharmacophore models. The pharmacophore matched hits were then docked into PI3Kα crystal structures to form ligand-receptor complexes, which are further validated by the Glide-XP program to result in structural validated hits. The structural validated hits were examined by PI3Kα inhibitory assay. With this screening protocol, ten PI3Kα inhibitors with new scaffolds were discovered with IC50 values ranging 0.44-31.25 μM. The binding affinities for the most active compounds 33 and 74 were estimated through molecular dynamics simulations and MM-PBSA analyses.

Polarization impacts on the water-leaving radiance retrieval from above-water radiometric measurements.

PubMed

Harmel, Tristan; Gilerson, Alexander; Tonizzo, Alberto; Chowdhary, Jacek; Weidemann, Alan; Arnone, Robert; Ahmed, Sam

2012-12-10

Above-water measurements of water-leaving radiance are widely used for water-quality monitoring and ocean-color satellite data validation. Reflected skylight in above-water radiometry needs to be accurately estimated prior to derivation of water-leaving radiance. Up-to-date methods to estimate reflection of diffuse skylight on rough sea surfaces are based on radiative transfer simulations and sky radiance measurements. But these methods neglect the polarization state of the incident skylight, which is generally highly polarized. In this paper, the effects of polarization on the sea surface reflectance and the subsequent water-leaving radiance estimation are investigated. We show that knowledge of the polarization field of the diffuse skylight significantly improves above-water radiometry estimates, in particular in the blue part of the spectrum where the reflected skylight is dominant. A newly developed algorithm based on radiative transfer simulations including polarization is described. Its application to the standard Aerosol Robotic Network-Ocean Color and hyperspectral radiometric measurements of the 1.5-year dataset acquired at the Long Island Sound site demonstrates the noticeable importance of considering polarization for water-leaving radiance estimation. In particular it is shown, based on time series of collocated data acquired in coastal waters, that the azimuth range of measurements leading to good-quality data is significantly increased, and that these estimates are improved by more than 12% at 413 nm. Full consideration of polarization effects is expected to significantly improve the quality of the field data utilized for satellite data validation or potential vicarious calibration purposes.

Infrasound Waveform Inversion and Mass Flux Validation from Sakurajima Volcano, Japan

NASA Astrophysics Data System (ADS)

Fee, D.; Kim, K.; Yokoo, A.; Izbekov, P. E.; Lopez, T. M.; Prata, F.; Ahonen, P.; Kazahaya, R.; Nakamichi, H.; Iguchi, M.

2015-12-01

Recent advances in numerical wave propagation modeling and station coverage have permitted robust inversion of infrasound data from volcanic explosions. Complex topography and crater morphology have been shown to substantially affect the infrasound waveform, suggesting that homogeneous acoustic propagation assumptions are invalid. Infrasound waveform inversion provides an exciting tool to accurately characterize emission volume and mass flux from both volcanic and non-volcanic explosions. Mass flux, arguably the most sought-after parameter from a volcanic eruption, can be determined from the volume flux using infrasound waveform inversion if the volcanic flow is well-characterized. Thus far, infrasound-based volume and mass flux estimates have yet to be validated. In February 2015 we deployed six infrasound stations around the explosive Sakurajima Volcano, Japan for 8 days. Here we present our full waveform inversion method and volume and mass flux estimates of numerous high amplitude explosions using a high resolution DEM and 3-D Finite Difference Time Domain modeling. Application of this technique to volcanic eruptions may produce realistic estimates of mass flux and plume height necessary for volcanic hazard mitigation. Several ground-based instruments and methods are used to independently determine the volume, composition, and mass flux of individual volcanic explosions. Specifically, we use ground-based ash sampling, multispectral infrared imagery, UV spectrometry, and multigas data to estimate the plume composition and flux. Unique tiltmeter data from underground tunnels at Sakurajima also provides a way to estimate the volume and mass of each explosion. In this presentation we compare the volume and mass flux estimates derived from the different methods and discuss sources of error and future improvements.

Validation of abundance estimates from mark–recapture and removal techniques for rainbow trout captured by electrofishing in small streams

USGS Publications Warehouse

Rosenberger, Amanda E.; Dunham, Jason B.

2005-01-01

Estimation of fish abundance in streams using the removal model or the Lincoln - Peterson mark - recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams. For one-, two-, three-, and four-pass sampling effort in closed sites, we evaluated the influences of fish size and habitat characteristics on sampling efficiency and the accuracy of removal abundance estimates. We also examined the use of models to generate unbiased estimates of fish abundance through adjustment of total catch or biased removal estimates. Our results suggested that the assumptions of the mark - recapture model were satisfied and that abundance estimates based on this approach were unbiased. In contrast, the removal model assumptions were not met. Decreasing sampling efficiencies over removal passes resulted in underestimated population sizes and overestimates of sampling efficiency. This bias decreased, but was not eliminated, with increased sampling effort. Biased removal estimates based on different levels of effort were highly correlated with each other but were less correlated with unbiased mark - recapture estimates. Stream size decreased sampling efficiency, and stream size and instream wood increased the negative bias of removal estimates. We found that reliable estimates of population abundance could be obtained from models of sampling efficiency for different levels of effort. Validation of abundance estimates requires extra attention to routine sampling considerations but can help fisheries biologists avoid pitfalls associated with biased data and facilitate standardized comparisons among studies that employ different sampling methods.

Estimating the spatial distribution of field-applied mushroom compost in the Brandywine-Christina River Basin using multispectral remote sensing

NASA Astrophysics Data System (ADS)

Moxey, Kelsey A.

The world's greatest concentration of mushroom farms is settled within the Brandywine-Christina River Basin in Chester County in southeastern Pennsylvania. This industry produces a nutrient-rich byproduct known as spent mushroom compost, which has been traditionally applied to local farm fields as an organic fertilizer and soil amendment. While mushroom compost has beneficial properties, the possible over-application to farm fields could potentially degrade stream water quality. The goal of this study was to estimate the spatial extent and intensity of field-applied mushroom compost. We applied a remote sensing approach using Landsat multispectral imagery. We utilized the soil line technique, using the red and near-infrared bands, to estimate differences in soil wetness as a result of increased soil organic matter content from mushroom compost. We validated soil wetness estimates by examining the spectral response of references sites. We performed a second independent validation analysis using expert knowledge from agricultural extension agents. Our results showed that the soil line based wetness index worked well. The spectral validation illustrated that compost changes the spectral response of soil because of changes in wetness. The independent expert validation analysis produced a strong significant correlation between our remotely-sensed wetness estimates and the empirical ratings of compost application intensities. Overall, the methodology produced realistic spatial distributions of field-applied compost application intensities across the study area. These spatial distributions will be used for follow-up studies to assess the effect of spent mushroom compost on stream water quality.

Comparison of medicine availability measurements at health facilities: evidence from Service Provision Assessment surveys in five sub-Saharan African countries.

PubMed

Choi, Yoonjoung; Ametepi, Paul

2013-07-09

With growing emphasis on health systems strengthening in global health, various health facility assessment methods have been used increasingly to measure medicine and commodity availability. However, few studies have systematically compared estimates of availability based on different definitions. The objective of this study was to compare estimates of medicine availability based on different definitions. A secondary data analysis was conducted using data from the Service Provision Assessment (SPA)--a nationally representative sample survey of health facilities--conducted in five countries: Kenya SPA 2010, Namibia SPA 2009, Rwanda SPA 2007, Tanzania SPA 2006, and Uganda SPA 2007. For 32 medicines, percent of facilities having the medicine were estimated using five definitions: four for current availability and one for six-month period availability. 'Observed availability of at least one valid unit' was used as a reference definition, and ratios between the reference and each of the other four estimates were calculated. Summary statistics of the ratios among the 32 medicines were calculated by country. The ratios were compared further between public and non-public facilities within each country. Across five countries, compared to current observed availability of at least one valid unit, 'reported availability without observation' was on average 6% higher (ranging from 3% in Rwanda to 8% in Namibia), 'observed availability where all units were valid' was 11% lower (ranging from 2% in Tanzania to 19% in Uganda), and 'six-month period availability' was 14% lower (ranging from 5% in Namibia to 25% in Uganda). Medicine availability estimates vary substantially across definitions, and need to be interpreted with careful consideration of the methods used.

Independent evaluation of the SNODAS snow depth product using regional scale LiDAR-derived measurements

NASA Astrophysics Data System (ADS)

Hedrick, A.; Marshall, H.-P.; Winstral, A.; Elder, K.; Yueh, S.; Cline, D.

2014-06-01

Repeated Light Detection and Ranging (LiDAR) surveys are quickly becoming the de facto method for measuring spatial variability of montane snowpacks at high resolution. This study examines the potential of a 750 km2 LiDAR-derived dataset of snow depths, collected during the 2007 northern Colorado Cold Lands Processes Experiment (CLPX-2), as a validation source for an operational hydrologic snow model. The SNOw Data Assimilation System (SNODAS) model framework, operated by the US National Weather Service, combines a physically-based energy-and-mass-balance snow model with satellite, airborne and automated ground-based observations to provide daily estimates of snowpack properties at nominally 1 km resolution over the coterminous United States. Independent validation data is scarce due to the assimilating nature of SNODAS, compelling the need for an independent validation dataset with substantial geographic coverage. Within twelve distinctive 500 m × 500 m study areas located throughout the survey swath, ground crews performed approximately 600 manual snow depth measurements during each of the CLPX-2 LiDAR acquisitions. This supplied a dataset for constraining the uncertainty of upscaled LiDAR estimates of snow depth at the 1 km SNODAS resolution, resulting in a root-mean-square difference of 13 cm. Upscaled LiDAR snow depths were then compared to the SNODAS-estimates over the entire study area for the dates of the LiDAR flights. The remotely-sensed snow depths provided a more spatially continuous comparison dataset and agreed more closely to the model estimates than that of the in situ measurements alone. Finally, the results revealed three distinct areas where the differences between LiDAR observations and SNODAS estimates were most drastic, suggesting natural processes specific to these regions as causal influences on model uncertainty.

Independent evaluation of the SNODAS snow depth product using regional-scale lidar-derived measurements

NASA Astrophysics Data System (ADS)

Hedrick, A.; Marshall, H.-P.; Winstral, A.; Elder, K.; Yueh, S.; Cline, D.

2015-01-01

Repeated light detection and ranging (lidar) surveys are quickly becoming the de facto method for measuring spatial variability of montane snowpacks at high resolution. This study examines the potential of a 750 km2 lidar-derived data set of snow depths, collected during the 2007 northern Colorado Cold Lands Processes Experiment (CLPX-2), as a validation source for an operational hydrologic snow model. The SNOw Data Assimilation System (SNODAS) model framework, operated by the US National Weather Service, combines a physically based energy-and-mass-balance snow model with satellite, airborne and automated ground-based observations to provide daily estimates of snowpack properties at nominally 1 km resolution over the conterminous United States. Independent validation data are scarce due to the assimilating nature of SNODAS, compelling the need for an independent validation data set with substantial geographic coverage. Within 12 distinctive 500 × 500 m study areas located throughout the survey swath, ground crews performed approximately 600 manual snow depth measurements during each of the CLPX-2 lidar acquisitions. This supplied a data set for constraining the uncertainty of upscaled lidar estimates of snow depth at the 1 km SNODAS resolution, resulting in a root-mean-square difference of 13 cm. Upscaled lidar snow depths were then compared to the SNODAS estimates over the entire study area for the dates of the lidar flights. The remotely sensed snow depths provided a more spatially continuous comparison data set and agreed more closely to the model estimates than that of the in situ measurements alone. Finally, the results revealed three distinct areas where the differences between lidar observations and SNODAS estimates were most drastic, providing insight into the causal influences of natural processes on model uncertainty.

Filtering data from the collaborative initial glaucoma treatment study for improved identification of glaucoma progression.

PubMed

Schell, Greggory J; Lavieri, Mariel S; Stein, Joshua D; Musch, David C

2013-12-21

Open-angle glaucoma (OAG) is a prevalent, degenerate ocular disease which can lead to blindness without proper clinical management. The tests used to assess disease progression are susceptible to process and measurement noise. The aim of this study was to develop a methodology which accounts for the inherent noise in the data and improve significant disease progression identification. Longitudinal observations from the Collaborative Initial Glaucoma Treatment Study (CIGTS) were used to parameterize and validate a Kalman filter model and logistic regression function. The Kalman filter estimates the true value of biomarkers associated with OAG and forecasts future values of these variables. We develop two logistic regression models via generalized estimating equations (GEE) for calculating the probability of experiencing significant OAG progression: one model based on the raw measurements from CIGTS and another model based on the Kalman filter estimates of the CIGTS data. Receiver operating characteristic (ROC) curves and associated area under the ROC curve (AUC) estimates are calculated using cross-fold validation. The logistic regression model developed using Kalman filter estimates as data input achieves higher sensitivity and specificity than the model developed using raw measurements. The mean AUC for the Kalman filter-based model is 0.961 while the mean AUC for the raw measurements model is 0.889. Hence, using the probability function generated via Kalman filter estimates and GEE for logistic regression, we are able to more accurately classify patients and instances as experiencing significant OAG progression. A Kalman filter approach for estimating the true value of OAG biomarkers resulted in data input which improved the accuracy of a logistic regression classification model compared to a model using raw measurements as input. This methodology accounts for process and measurement noise to enable improved discrimination between progression and nonprogression in chronic diseases.

Single-snapshot DOA estimation by using Compressed Sensing

NASA Astrophysics Data System (ADS)

Fortunati, Stefano; Grasso, Raffaele; Gini, Fulvio; Greco, Maria S.; LePage, Kevin

2014-12-01

This paper deals with the problem of estimating the directions of arrival (DOA) of multiple source signals from a single observation vector of an array data. In particular, four estimation algorithms based on the theory of compressed sensing (CS), i.e., the classical ℓ 1 minimization (or Least Absolute Shrinkage and Selection Operator, LASSO), the fast smooth ℓ 0 minimization, and the Sparse Iterative Covariance-Based Estimator, SPICE and the Iterative Adaptive Approach for Amplitude and Phase Estimation, IAA-APES algorithms, are analyzed, and their statistical properties are investigated and compared with the classical Fourier beamformer (FB) in different simulated scenarios. We show that unlike the classical FB, a CS-based beamformer (CSB) has some desirable properties typical of the adaptive algorithms (e.g., Capon and MUSIC) even in the single snapshot case. Particular attention is devoted to the super-resolution property. Theoretical arguments and simulation analysis provide evidence that a CS-based beamformer can achieve resolution beyond the classical Rayleigh limit. Finally, the theoretical findings are validated by processing a real sonar dataset.

View Estimation Based on Value System

NASA Astrophysics Data System (ADS)

Takahashi, Yasutake; Shimada, Kouki; Asada, Minoru

Estimation of a caregiver's view is one of the most important capabilities for a child to understand the behavior demonstrated by the caregiver, that is, to infer the intention of behavior and/or to learn the observed behavior efficiently. We hypothesize that the child develops this ability in the same way as behavior learning motivated by an intrinsic reward, that is, he/she updates the model of the estimated view of his/her own during the behavior imitated from the observation of the behavior demonstrated by the caregiver based on minimizing the estimation error of the reward during the behavior. From this view, this paper shows a method for acquiring such a capability based on a value system from which values can be obtained by reinforcement learning. The parameters of the view estimation are updated based on the temporal difference error (hereafter TD error: estimation error of the state value), analogous to the way such that the parameters of the state value of the behavior are updated based on the TD error. Experiments with simple humanoid robots show the validity of the method, and the developmental process parallel to young children's estimation of its own view during the imitation of the observed behavior of the caregiver is discussed.

Development of Flight-Test Performance Estimation Techniques for Small Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

McCrink, Matthew Henry

This dissertation provides a flight-testing framework for assessing the performance of fixed-wing, small-scale unmanned aerial systems (sUAS) by leveraging sub-system models of components unique to these vehicles. The development of the sub-system models, and their links to broader impacts on sUAS performance, is the key contribution of this work. The sub-system modeling and analysis focuses on the vehicle's propulsion, navigation and guidance, and airframe components. Quantification of the uncertainty in the vehicle's power available and control states is essential for assessing the validity of both the methods and results obtained from flight-tests. Therefore, detailed propulsion and navigation system analyses are presented to validate the flight testing methodology. Propulsion system analysis required the development of an analytic model of the propeller in order to predict the power available over a range of flight conditions. The model is based on the blade element momentum (BEM) method. Additional corrections are added to the basic model in order to capture the Reynolds-dependent scale effects unique to sUAS. The model was experimentally validated using a ground based testing apparatus. The BEM predictions and experimental analysis allow for a parameterized model relating the electrical power, measurable during flight, to the power available required for vehicle performance analysis. Navigation system details are presented with a specific focus on the sensors used for state estimation, and the resulting uncertainty in vehicle state. Uncertainty quantification is provided by detailed calibration techniques validated using quasi-static and hardware-in-the-loop (HIL) ground based testing. The HIL methods introduced use a soft real-time flight simulator to provide inertial quality data for assessing overall system performance. Using this tool, the uncertainty in vehicle state estimation based on a range of sensors, and vehicle operational environments is presented. The propulsion and navigation system models are used to evaluate flight-testing methods for evaluating fixed-wing sUAS performance. A brief airframe analysis is presented to provide a foundation for assessing the efficacy of the flight-test methods. The flight-testing presented in this work is focused on validating the aircraft drag polar, zero-lift drag coefficient, and span efficiency factor. Three methods are detailed and evaluated for estimating these design parameters. Specific focus is placed on the influence of propulsion and navigation system uncertainty on the resulting performance data. Performance estimates are used in conjunction with the propulsion model to estimate the impact sensor and measurement uncertainty on the endurance and range of a fixed-wing sUAS. Endurance and range results for a simplistic power available model are compared to the Reynolds-dependent model presented in this work. Additional parameter sensitivity analysis related to state estimation uncertainties encountered in flight-testing are presented. Results from these analyses indicate that the sub-system models introduced in this work are of first-order importance, on the order of 5-10% change in range and endurance, in assessing the performance of a fixed-wing sUAS.

Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

We introduce a framework to build a survival/risk bump hunting model with a censored time-to-event response. Our Survival Bump Hunting (SBH) method is based on a recursive peeling procedure that uses a specific survival peeling criterion derived from non/semi-parametric statistics such as the hazards-ratio, the log-rank test or the Nelson--Aalen estimator. To optimize the tuning parameter of the model and validate it, we introduce an objective function based on survival or prediction-error statistics, such as the log-rank test and the concordance error rate. We also describe two alternative cross-validation techniques adapted to the joint task of decision-rule making by recursive peeling and survival estimation. Numerical analyses show the importance of replicated cross-validation and the differences between criteria and techniques in both low and high-dimensional settings. Although several non-parametric survival models exist, none addresses the problem of directly identifying local extrema. We show how SBH efficiently estimates extreme survival/risk subgroups unlike other models. This provides an insight into the behavior of commonly used models and suggests alternatives to be adopted in practice. Finally, our SBH framework was applied to a clinical dataset. In it, we identified subsets of patients characterized by clinical and demographic covariates with a distinct extreme survival outcome, for which tailored medical interventions could be made. An R package PRIMsrc (Patient Rule Induction Method in Survival, Regression and Classification settings) is available on CRAN (Comprehensive R Archive Network) and GitHub. PMID:27034730

Applicability of Monte Carlo cross validation technique for model development and validation using generalised least squares regression

NASA Astrophysics Data System (ADS)

Haddad, Khaled; Rahman, Ataur; A Zaman, Mohammad; Shrestha, Surendra

2013-03-01

SummaryIn regional hydrologic regression analysis, model selection and validation are regarded as important steps. Here, the model selection is usually based on some measurements of goodness-of-fit between the model prediction and observed data. In Regional Flood Frequency Analysis (RFFA), leave-one-out (LOO) validation or a fixed percentage leave out validation (e.g., 10%) is commonly adopted to assess the predictive ability of regression-based prediction equations. This paper develops a Monte Carlo Cross Validation (MCCV) technique (which has widely been adopted in Chemometrics and Econometrics) in RFFA using Generalised Least Squares Regression (GLSR) and compares it with the most commonly adopted LOO validation approach. The study uses simulated and regional flood data from the state of New South Wales in Australia. It is found that when developing hydrologic regression models, application of the MCCV is likely to result in a more parsimonious model than the LOO. It has also been found that the MCCV can provide a more realistic estimate of a model's predictive ability when compared with the LOO.

Towards combining GPM and MFG observations to monitor near real time heavy precipitation at fine scale over India and nearby oceanic regions

NASA Astrophysics Data System (ADS)

Mishra, Anoop; Rafiq, Mohammd

2017-12-01

This is the first attempt to merge highly accurate precipitation estimates from Global Precipitation Measurement (GPM) with gap free satellite observations from Meteosat to develop a regional rainfall monitoring algorithm to estimate heavy rainfall over India and nearby oceanic regions. Rainfall signature is derived from Meteosat observations and is co-located against rainfall from GPM to establish a relationship between rainfall and signature for various rainy seasons. This relationship can be used to monitor rainfall over India and nearby oceanic regions. Performance of this technique was tested by applying it to monitor heavy precipitation over India. It is reported that our algorithm is able to detect heavy rainfall. It is also reported that present algorithm overestimates rainfall areal spread as compared to rain gauge based rainfall product. This deficiency may arise from various factors including uncertainty caused by use of different sensors from different platforms (difference in viewing geometry from MFG and GPM), poor relationship between warm rain (light rain) and IR brightness temperature, and weak characterization of orographic rain from IR signature. We validated hourly rainfall estimated from the present approach with independent observations from GPM. We also validated daily rainfall from this approach with rain gauge based product from India Meteorological Department (IMD). Present technique shows a Correlation Coefficient (CC) of 0.76, a bias of -2.72 mm, a Root Mean Square Error (RMSE) of 10.82 mm, Probability of Detection (POD) of 0.74, False Alarm Ratio (FAR) of 0.34 and a Skill score of 0.36 with daily rainfall from rain gauge based product of IMD at 0.25° resolution. However, FAR reduces to 0.24 for heavy rainfall events. Validation results with rain gauge observations reveal that present technique outperforms available satellite based rainfall estimates for monitoring heavy rainfall over Indian region.

A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China

PubMed Central

Li, Huashan; Cao, Fei; Wang, Xianlong; Ma, Weibin

2014-01-01

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China. PMID:24605046

Error vector magnitude based parameter estimation for digital filter back-propagation mitigating SOA distortions in 16-QAM.

PubMed

Amiralizadeh, Siamak; Nguyen, An T; Rusch, Leslie A

2013-08-26

We investigate the performance of digital filter back-propagation (DFBP) using coarse parameter estimation for mitigating SOA nonlinearity in coherent communication systems. We introduce a simple, low overhead method for parameter estimation for DFBP based on error vector magnitude (EVM) as a figure of merit. The bit error rate (BER) penalty achieved with this method has negligible penalty as compared to DFBP with fine parameter estimation. We examine different bias currents for two commercial SOAs used as booster amplifiers in our experiments to find optimum operating points and experimentally validate our method. The coarse parameter DFBP efficiently compensates SOA-induced nonlinearity for both SOA types in 80 km propagation of 16-QAM signal at 22 Gbaud.

Age, year‐class strength variability, and partial age validation of Kiyis from Lake Superior

USGS Publications Warehouse

Lepak, Taylor A.; Ogle, Derek H.; Vinson, Mark

2017-01-01

ge estimates of Lake Superior Kiyis Coregonus kiyi from scales and otoliths were compared and 12 years (2003–2014) of length frequency data were examined to assess year‐class strength and validate age estimates. Ages estimated from otoliths were precise and were consistently older than ages estimated from scales. Maximum otolith‐derived ages were 20 years for females and 12 years for males. Age estimates showed high numbers of fish of ages 5, 6, and 11 in 2014, corresponding to the 2009, 2008, and 2003 year‐classes, respectively. Strong 2003 and 2009 year‐classes, along with the 2005 year‐class, were also evident based on distinct modes of age‐1 fish (<110 mm) in the length frequency distributions from 2004, 2010, and 2006, respectively. Modes from these year‐classes were present as progressively larger fish in subsequent years. Few to no age‐1 fish (<110 mm) were present in all other years. Ages estimated from otoliths were generally within 1 year of the ages corresponding to strong year‐classes, at least for age‐5 and older fish, suggesting that Kiyi age may be reliably estimated to within 1 year by careful examination of thin‐sectioned otoliths.

Development of the Quality of Australian Nursing Documentation in Aged Care (QANDAC) instrument to assess paper-based and electronic resident records.

PubMed

Wang, Ning; Björvell, Catrin; Hailey, David; Yu, Ping

2014-12-01

To develop an Australian nursing documentation in aged care (Quality of Australian Nursing Documentation in Aged Care (QANDAC)) instrument to measure the quality of paper-based and electronic resident records. The instrument was based on the nursing process model and on three attributes of documentation quality identified in a systematic review. The development process involved five phases following approaches to designing criterion-referenced measures. The face and content validities and the inter-rater reliability of the instrument were estimated using a focus group approach and consensus model. The instrument contains 34 questions in three sections: completion of nursing history and assessment, description of care process and meeting the requirements of data entry. Estimates of the validity and inter-rater reliability of the instrument gave satisfactory results. The QANDAC instrument may be a useful audit tool for quality improvement and research in aged care documentation. © 2013 ACOTA.

An adaptive state of charge estimation approach for lithium-ion series-connected battery system

NASA Astrophysics Data System (ADS)

Peng, Simin; Zhu, Xuelai; Xing, Yinjiao; Shi, Hongbing; Cai, Xu; Pecht, Michael

2018-07-01

Due to the incorrect or unknown noise statistics of a battery system and its cell-to-cell variations, state of charge (SOC) estimation of a lithium-ion series-connected battery system is usually inaccurate or even divergent using model-based methods, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). To resolve this problem, an adaptive unscented Kalman filter (AUKF) based on a noise statistics estimator and a model parameter regulator is developed to accurately estimate the SOC of a series-connected battery system. An equivalent circuit model is first built based on the model parameter regulator that illustrates the influence of cell-to-cell variation on the battery system. A noise statistics estimator is then used to attain adaptively the estimated noise statistics for the AUKF when its prior noise statistics are not accurate or exactly Gaussian. The accuracy and effectiveness of the SOC estimation method is validated by comparing the developed AUKF and UKF when model and measurement statistics noises are inaccurate, respectively. Compared with the UKF and EKF, the developed method shows the highest SOC estimation accuracy.

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

Evaluation of a moderate resolution, satellite-based impervious surface map using an independent, high-resolution validation data set

USGS Publications Warehouse

Jones, J.W.; Jarnagin, T.

2009-01-01

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data products high quality, independently derived validation data are needed. High-resolution data were collected across a gradient of development within the Mid-Atlantic region to assess the accuracy of National Land Cover Data (NLCD) Landsat-based ISA estimates. Absolute error (satellite predicted area - "reference area") and relative error [satellite (predicted area - "reference area")/ "reference area"] were calculated for each of 240 sample regions that are each more than 15 Landsat pixels on a side. The ability to compile and examine ancillary data in a geographic information system environment provided for evaluation of both validation and NLCD data and afforded efficient exploration of observed errors. In a minority of cases, errors could be explained by temporal discontinuities between the date of satellite image capture and validation source data in rapidly changing places. In others, errors were created by vegetation cover over impervious surfaces and by other factors that bias the satellite processing algorithms. On average in the Mid-Atlantic region, the NLCD product underestimates ISA by approximately 5%. While the error range varies between 2 and 8%, this underestimation occurs regardless of development intensity. Through such analyses the errors, strengths, and weaknesses of particular satellite products can be explored to suggest appropriate uses for regional, satellite-based data in rapidly developing areas of environmental significance. ?? 2009 ASCE.

Electric Power Consumption Coefficients for U.S. Industries: Regional Estimation and Analysis

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

Boero, Riccardo

Economic activity relies on electric power provided by electrical generation, transmission, and distribution systems. This paper presents a method developed at Los Alamos National Laboratory to estimate electric power consumption by different industries in the United States. Results are validated through comparisons with existing literature and benchmarking data sources. We also discuss the limitations and applications of the presented method, such as estimating indirect electric power consumption and assessing the economic impact of power outages based on input-output economic models.

Bias-correction of PERSIANN-CDR Extreme Precipitation Estimates Over the United States

NASA Astrophysics Data System (ADS)

Faridzad, M.; Yang, T.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Ground-based precipitation measurements can be sparse or even nonexistent over remote regions which make it difficult for extreme event analysis. PERSIANN-CDR (CDR), with 30+ years of daily rainfall information, provides an opportunity to study precipitation for regions where ground measurements are limited. In this study, the use of CDR annual extreme precipitation for frequency analysis of extreme events over limited/ungauged basins is explored. The adjustment of CDR is implemented in two steps: (1) Calculated CDR bias correction factor at limited gauge locations based on the linear regression analysis of gauge and CDR annual maxima precipitation; and (2) Extend the bias correction factor to the locations where gauges are not available. The correction factors are estimated at gauge sites over various catchments, elevation zones, and climate regions and the results were generalized to ungauged sites based on regional and climatic similarity. Case studies were conducted on 20 basins with diverse climate and altitudes in the Eastern and Western US. Cross-validation reveals that the bias correction factors estimated on limited calibration data can be extended to regions with similar characteristics. The adjusted CDR estimates also outperform gauge interpolation on validation sites consistently. It is suggested that the CDR with bias adjustment has a potential for study frequency analysis of extreme events, especially for regions with limited gauge observations.

Estimating Global Ecosystem Isohydry/Anisohydry Using Active and Passive Microwave Satellite Data

NASA Astrophysics Data System (ADS)

Li, Yan; Guan, Kaiyu; Gentine, Pierre; Konings, Alexandra G.; Meinzer, Frederick C.; Kimball, John S.; Xu, Xiangtao; Anderegg, William R. L.; McDowell, Nate G.; Martinez-Vilalta, Jordi; Long, David G.; Good, Stephen P.

2017-12-01

The concept of isohydry/anisohydry describes the degree to which plants regulate their water status, operating from isohydric with strict regulation to anisohydric with less regulation. Though some species level measures of isohydry/anisohydry exist at a few locations, ecosystem-scale information is still largely unavailable. In this study, we use diurnal observations from active (Ku-Band backscatter from QuikSCAT) and passive (X-band vegetation optical depth (VOD) from Advanced Microwave Scanning Radiometer on EOS Aqua) microwave satellite data to estimate global ecosystem isohydry/anisohydry. Here diurnal observations from both satellites approximate predawn and midday plant canopy water contents, which are used to estimate isohydry/anisohydry. The two independent estimates from radar backscatter and VOD show reasonable agreement at low and middle latitudes but diverge at high latitudes. Grasslands, croplands, wetlands, and open shrublands are more anisohydric, whereas evergreen broadleaf and deciduous broadleaf forests are more isohydric. The direct validation with upscaled in situ species isohydry/anisohydry estimates indicates that the VOD-based estimates have much better agreement than the backscatter-based estimates. The indirect validation with prior knowledge suggests that both estimates are generally consistent in that vegetation water status of anisohydric ecosystems more closely tracks environmental fluctuations of water availability and demand than their isohydric counterparts. However, uncertainties still exist in the isohydry/anisohydry estimate, primarily arising from the remote sensing data and, to a lesser extent, from the methodology. The comprehensive assessment in this study can help us better understand the robustness, limitation, and uncertainties of the satellite-derived isohydry/anisohydry estimates. The ecosystem isohydry/anisohydry has the potential to reveal new insights into spatiotemporal ecosystem response to droughts.

Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement.

PubMed

Nguyen, N; Milanfar, P; Golub, G

2001-01-01

In many image restoration/resolution enhancement applications, the blurring process, i.e., point spread function (PSF) of the imaging system, is not known or is known only to within a set of parameters. We estimate these PSF parameters for this ill-posed class of inverse problem from raw data, along with the regularization parameters required to stabilize the solution, using the generalized cross-validation method (GCV). We propose efficient approximation techniques based on the Lanczos algorithm and Gauss quadrature theory, reducing the computational complexity of the GCV. Data-driven PSF and regularization parameter estimation experiments with synthetic and real image sequences are presented to demonstrate the effectiveness and robustness of our method.

Validation and reliability of the sex estimation of the human os coxae using freely available DSP2 software for bioarchaeology and forensic anthropology.

PubMed

Brůžek, Jaroslav; Santos, Frédéric; Dutailly, Bruno; Murail, Pascal; Cunha, Eugenia

2017-10-01

A new tool for skeletal sex estimation based on measurements of the human os coxae is presented using skeletons from a metapopulation of identified adult individuals from twelve independent population samples. For reliable sex estimation, a posterior probability greater than 0.95 was considered to be the classification threshold: below this value, estimates are considered indeterminate. By providing free software, we aim to develop an even more disseminated method for sex estimation. Ten metric variables collected from 2,040 ossa coxa of adult subjects of known sex were recorded between 1986 and 2002 (reference sample). To test both the validity and reliability, a target sample consisting of two series of adult ossa coxa of known sex (n = 623) was used. The DSP2 software (Diagnose Sexuelle Probabiliste v2) is based on Linear Discriminant Analysis, and the posterior probabilities are calculated using an R script. For the reference sample, any combination of four dimensions provides a correct sex estimate in at least 99% of cases. The percentage of individuals for whom sex can be estimated depends on the number of dimensions; for all ten variables it is higher than 90%. Those results are confirmed in the target sample. Our posterior probability threshold of 0.95 for sex estimate corresponds to the traditional sectioning point used in osteological studies. DSP2 software is replacing the former version that should not be used anymore. DSP2 is a robust and reliable technique for sexing adult os coxae, and is also user friendly. © 2017 Wiley Periodicals, Inc.

An improved procedure for the validation of satellite-based precipitation estimates

NASA Astrophysics Data System (ADS)

Tang, Ling; Tian, Yudong; Yan, Fang; Habib, Emad

2015-09-01

The objective of this study is to propose and test a new procedure to improve the validation of remote-sensing, high-resolution precipitation estimates. Our recent studies show that many conventional validation measures do not accurately capture the unique error characteristics in precipitation estimates to better inform both data producers and users. The proposed new validation procedure has two steps: 1) an error decomposition approach to separate the total retrieval error into three independent components: hit error, false precipitation and missed precipitation; and 2) the hit error is further analyzed based on a multiplicative error model. In the multiplicative error model, the error features are captured by three model parameters. In this way, the multiplicative error model separates systematic and random errors, leading to more accurate quantification of the uncertainties. The proposed procedure is used to quantitatively evaluate the recent two versions (Version 6 and 7) of TRMM's Multi-sensor Precipitation Analysis (TMPA) real-time and research product suite (3B42 and 3B42RT) for seven years (2005-2011) over the continental United States (CONUS). The gauge-based National Centers for Environmental Prediction (NCEP) Climate Prediction Center (CPC) near-real-time daily precipitation analysis is used as the reference. In addition, the radar-based NCEP Stage IV precipitation data are also model-fitted to verify the effectiveness of the multiplicative error model. The results show that winter total bias is dominated by the missed precipitation over the west coastal areas and the Rocky Mountains, and the false precipitation over large areas in Midwest. The summer total bias is largely coming from the hit bias in Central US. Meanwhile, the new version (V7) tends to produce more rainfall in the higher rain rates, which moderates the significant underestimation exhibited in the previous V6 products. Moreover, the error analysis from the multiplicative error model provides a clear and concise picture of the systematic and random errors, with both versions of 3B42RT have higher errors in varying degrees than their research (post-real-time) counterparts. The new V7 algorithm shows obvious improvements in reducing random errors in both winter and summer seasons, compared to its predecessors V6. Stage IV, as expected, surpasses the satellite-based datasets in all the metrics over CONUS. Based on the results, we recommend the new procedure be adopted for routine validation of satellite-based precipitation datasets, and we expect the procedure will work effectively for higher resolution data to be produced in the Global Precipitation Measurement (GPM) era.

Ka-Band Wide-Bandgap Solid-State Power Amplifier: Hardware Validation

NASA Technical Reports Server (NTRS)

Epp, L.; Khan, P.; Silva, A.

2005-01-01

Motivated by recent advances in wide-bandgap (WBG) gallium nitride (GaN) semiconductor technology, there is considerable interest in developing efficient solid-state power amplifiers (SSPAs) as an alternative to the traveling-wave tube amplifier (TWTA) for space applications. This article documents proof-of-concept hardware used to validate power-combining technologies that may enable a 120-W, 40 percent power-added efficiency (PAE) SSPA. Results in previous articles [1-3] indicate that architectures based on at least three power combiner designs are likely to enable the target SSPA. Previous architecture performance analyses and estimates indicate that the proposed architectures can power combine 16 to 32 individual monolithic microwave integrated circuits (MMICs) with >80 percent combining efficiency. This combining efficiency would correspond to MMIC requirements of 5- to 10-W output power and >48 percent PAE. In order to validate the performance estimates of the three proposed architectures, measurements of proof-of-concept hardware are reported here.

Validation of a partial coherence interferometry method for estimating retinal shape

PubMed Central

Verkicharla, Pavan K.; Suheimat, Marwan; Pope, James M.; Sepehrband, Farshid; Mathur, Ankit; Schmid, Katrina L.; Atchison, David A.

2015-01-01

To validate a simple partial coherence interferometry (PCI) based retinal shape method, estimates of retinal shape were determined in 60 young adults using off-axis PCI, with three stages of modeling using variants of the Le Grand model eye, and magnetic resonance imaging (MRI). Stage 1 and 2 involved a basic model eye without and with surface ray deviation, respectively and Stage 3 used model with individual ocular biometry and ray deviation at surfaces. Considering the theoretical uncertainty of MRI (12-14%), the results of the study indicate good agreement between MRI and all three stages of PCI modeling with <4% and <7% differences in retinal shapes along horizontal and vertical meridians, respectively. Stage 2 and Stage 3 gave slightly different retinal co-ordinates than Stage 1 and we recommend the intermediate Stage 2 as providing a simple and valid method of determining retinal shape from PCI data. PMID:26417496

Validation of a partial coherence interferometry method for estimating retinal shape.

PubMed

Verkicharla, Pavan K; Suheimat, Marwan; Pope, James M; Sepehrband, Farshid; Mathur, Ankit; Schmid, Katrina L; Atchison, David A

2015-09-01

To validate a simple partial coherence interferometry (PCI) based retinal shape method, estimates of retinal shape were determined in 60 young adults using off-axis PCI, with three stages of modeling using variants of the Le Grand model eye, and magnetic resonance imaging (MRI). Stage 1 and 2 involved a basic model eye without and with surface ray deviation, respectively and Stage 3 used model with individual ocular biometry and ray deviation at surfaces. Considering the theoretical uncertainty of MRI (12-14%), the results of the study indicate good agreement between MRI and all three stages of PCI modeling with <4% and <7% differences in retinal shapes along horizontal and vertical meridians, respectively. Stage 2 and Stage 3 gave slightly different retinal co-ordinates than Stage 1 and we recommend the intermediate Stage 2 as providing a simple and valid method of determining retinal shape from PCI data.

Validation of PV-RPM Code in the System Advisor Model.

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

Klise, Geoffrey Taylor; Lavrova, Olga; Freeman, Janine

2017-04-01

This paper describes efforts made by Sandia National Laboratories (SNL) and the National Renewable Energy Laboratory (NREL) to validate the SNL developed PV Reliability Performance Model (PV - RPM) algorithm as implemented in the NREL System Advisor Model (SAM). The PV - RPM model is a library of functions that estimates component failure and repair in a photovoltaic system over a desired simulation period. The failure and repair distributions in this paper are probabilistic representations of component failure and repair based on data collected by SNL for a PV power plant operating in Arizona. The validation effort focuses on whethermore » the failure and repair dist ributions used in the SAM implementation result in estimated failures that match the expected failures developed in the proof - of - concept implementation. Results indicate that the SAM implementation of PV - RPM provides the same results as the proof - of - concep t implementation, indicating the algorithms were reproduced successfully.« less

Stochastic models to demonstrate the effect of motivated testing on HIV incidence estimates using the serological testing algorithm for recent HIV seroconversion (STARHS).

PubMed

White, Edward W; Lumley, Thomas; Goodreau, Steven M; Goldbaum, Gary; Hawes, Stephen E

2010-12-01

To produce valid seroincidence estimates, the serological testing algorithm for recent HIV seroconversion (STARHS) assumes independence between infection and testing, which may be absent in clinical data. STARHS estimates are generally greater than cohort-based estimates of incidence from observable person-time and diagnosis dates. The authors constructed a series of partial stochastic models to examine whether testing motivated by suspicion of infection could bias STARHS. One thousand Monte Carlo simulations of 10,000 men who have sex with men were generated using parameters for HIV incidence and testing frequency from data from a clinical testing population in Seattle. In one set of simulations, infection and testing dates were independent. In another set, some intertest intervals were abbreviated to reflect the distribution of intervals between suspected HIV exposure and testing in a group of Seattle men who have sex with men recently diagnosed as having HIV. Both estimation methods were applied to the simulated datasets. Both cohort-based and STARHS incidence estimates were calculated using the simulated data and compared with previously calculated, empirical cohort-based and STARHS seroincidence estimates from the clinical testing population. Under simulated independence between infection and testing, cohort-based and STARHS incidence estimates resembled cohort estimates from the clinical dataset. Under simulated motivated testing, cohort-based estimates remained unchanged, but STARHS estimates were inflated similar to empirical STARHS estimates. Varying motivation parameters appreciably affected STARHS incidence estimates, but not cohort-based estimates. Cohort-based incidence estimates are robust against dependence between testing and acquisition of infection, whereas STARHS incidence estimates are not.

The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2018-01-01

Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

Two- and three-dimensional CT measurements of urinary calculi length and width: a comparative study.

PubMed

Lidén, Mats; Thunberg, Per; Broxvall, Mathias; Geijer, Håkan

2015-04-01

The standard imaging procedure for a patient presenting with renal colic is unenhanced computed tomography (CT). The CT measured size has a close correlation to the estimated prognosis for spontaneous passage of a ureteral calculus. Size estimations of urinary calculi in CT images are still based on two-dimensional (2D) reformats. To develop and validate a calculus oriented three-dimensional (3D) method for measuring the length and width of urinary calculi and to compare the calculus oriented measurements of the length and width with corresponding 2D measurements obtained in axial and coronal reformats. Fifty unenhanced CT examinations demonstrating urinary calculi were included. A 3D symmetric segmentation algorithm was validated against reader size estimations. The calculus oriented size from the segmentation was then compared to the estimated size in axial and coronal 2D reformats. The validation showed 0.1 ± 0.7 mm agreement against reference measure. There was a 0.4 mm median bias for 3D estimated calculus length compared to 2D (P < 0.001), but no significant bias for 3D width compared to 2D. The length of a calculus in axial and coronal reformats becomes underestimated compared to 3D if its orientation is not aligned to the image planes. Future studies aiming to correlate calculus size with patient outcome should use a calculus oriented size estimation. © The Foundation Acta Radiologica 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Quantifying uncertainty in geoacoustic inversion. II. Application to broadband, shallow-water data.

PubMed

Dosso, Stan E; Nielsen, Peter L

2002-01-01

This paper applies the new method of fast Gibbs sampling (FGS) to estimate the uncertainties of seabed geoacoustic parameters in a broadband, shallow-water acoustic survey, with the goal of interpreting the survey results and validating the method for experimental data. FGS applies a Bayesian approach to geoacoustic inversion based on sampling the posterior probability density to estimate marginal probability distributions and parameter covariances. This requires knowledge of the statistical distribution of the data errors, including both measurement and theory errors, which is generally not available. Invoking the simplifying assumption of independent, identically distributed Gaussian errors allows a maximum-likelihood estimate of the data variance and leads to a practical inversion algorithm. However, it is necessary to validate these assumptions, i.e., to verify that the parameter uncertainties obtained represent meaningful estimates. To this end, FGS is applied to a geoacoustic experiment carried out at a site off the west coast of Italy where previous acoustic and geophysical studies have been performed. The parameter uncertainties estimated via FGS are validated by comparison with: (i) the variability in the results of inverting multiple independent data sets collected during the experiment; (ii) the results of FGS inversion of synthetic test cases designed to simulate the experiment and data errors; and (iii) the available geophysical ground truth. Comparisons are carried out for a number of different source bandwidths, ranges, and levels of prior information, and indicate that FGS provides reliable and stable uncertainty estimates for the geoacoustic inverse problem.

Validation of SMAP Surface Soil Moisture Products with Core Validation Sites

NASA Technical Reports Server (NTRS)

Colliander, A.; Jackson, T. J.; Bindlish, R.; Chan, S.; Das, N.; Kim, S. B.; Cosh, M. H.; Dunbar, R. S.; Dang, L.; Pashaian, L.;

Compositional descriptor-based recommender system for the materials discovery

NASA Astrophysics Data System (ADS)

Seko, Atsuto; Hayashi, Hiroyuki; Tanaka, Isao

2018-06-01

Structures and properties of many inorganic compounds have been collected historically. However, it only covers a very small portion of possible inorganic crystals, which implies the presence of numerous currently unknown compounds. A powerful machine-learning strategy is mandatory to discover new inorganic compounds from all chemical combinations. Herein we propose a descriptor-based recommender-system approach to estimate the relevance of chemical compositions where crystals can be formed [i.e., chemically relevant compositions (CRCs)]. In addition to data-driven compositional similarity used in the literature, the use of compositional descriptors as a prior knowledge is helpful for the discovery of new compounds. We validate our recommender systems in two ways. First, one database is used to construct a model, while another is used for the validation. Second, we estimate the phase stability for compounds at expected CRCs using density functional theory calculations.

Validity of a Self-Report Recall Tool for Estimating Sedentary Behavior in Adults.

PubMed

Gomersall, Sjaan R; Pavey, Toby G; Clark, Bronwyn K; Jasman, Adib; Brown, Wendy J

2015-11-01

Sedentary behavior is continuing to emerge as an important target for health promotion. The purpose of this study was to determine the validity of a self-report use of time recall tool, the Multimedia Activity Recall for Children and Adults (MARCA) in estimating time spent sitting/lying, compared with a device-based measure. Fifty-eight participants (48% female, [mean ± standard deviation] 28 ± 7.4 years of age, 23.9 ± 3.05 kg/m(2)) wore an activPAL device for 24-h and the following day completed the MARCA. Pearson correlation coefficients (r) were used to analyze convergent validity of the adult MARCA compared with activPAL estimates of total sitting/lying time. Agreement was examined using Bland-Altman plots. According to activPAL estimates, participants spent 10.4 hr/day [standard deviation (SD) = 2.06] sitting or lying down while awake. The correlation between MARCA and activPAL estimates of total sit/lie time was r = .77 (95% confidence interval = 0.64-0.86; P < .001). Bland-Altman analyses revealed a mean bias of +0.59 hr/day with moderately wide limits of agreement (-2.35 hr to +3.53 hr/day). This study found a moderate to strong agreement between the adult MARCA and the activPAL, suggesting that the MARCA is an appropriate tool for the measurement of time spent sitting or lying down in an adult population.

Evaluation of methods for calculating maximum allowable standing height in amputees competing in Paralympic athletics.

PubMed

Connick, M J; Beckman, E; Ibusuki, T; Malone, L; Tweedy, S M

2016-11-01

The International Paralympic Committee has a maximum allowable standing height (MASH) rule that limits stature to a pre-trauma estimation. The MASH rule reduces the probability that bilateral lower limb amputees use disproportionately long prostheses in competition. Although there are several methods for estimating stature, the validity of these methods has not been compared. To identify the most appropriate method for the MASH rule, this study aimed to compare the criterion validity of estimations resulting from the current method, the Contini method, and four Canda methods (Canda-1, Canda-2, Canda-3, and Canda-4). Stature, ulna length, demispan, sitting height, thigh length, upper arm length, and forearm length measurements in 31 males and 30 females were used to calculate the respective estimation for each method. Results showed that Canda-1 (based on four anthropometric variables) produced the smallest error and best fitted the data in males and females. The current method was associated with the largest error of those tests because it increasingly overestimated height in people with smaller stature. The results suggest that the set of Canda equations provide a more valid MASH estimation in people with a range of upper limb and bilateral lower limb amputations compared with the current method. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Two-dimensional radial laser scanning for circular marker detection and external mobile robot tracking.

PubMed

Teixidó, Mercè; Pallejà, Tomàs; Font, Davinia; Tresanchez, Marcel; Moreno, Javier; Palacín, Jordi

2012-11-28

This paper presents the use of an external fixed two-dimensional laser scanner to detect cylindrical targets attached to moving devices, such as a mobile robot. This proposal is based on the detection of circular markers in the raw data provided by the laser scanner by applying an algorithm for outlier avoidance and a least-squares circular fitting. Some experiments have been developed to empirically validate the proposal with different cylindrical targets in order to estimate the location and tracking errors achieved, which are generally less than 20 mm in the area covered by the laser sensor. As a result of the validation experiments, several error maps have been obtained in order to give an estimate of the uncertainty of any location computed. This proposal has been validated with a medium-sized mobile robot with an attached cylindrical target (diameter 200 mm). The trajectory of the mobile robot was estimated with an average location error of less than 15 mm, and the real location error in each individual circular fitting was similar to the error estimated with the obtained error maps. The radial area covered in this validation experiment was up to 10 m, a value that depends on the radius of the cylindrical target and the radial density of the distance range points provided by the laser scanner but this area can be increased by combining the information of additional external laser scanners.

Validity of Various Methods for Determining Velocity, Force, and Power in the Back Squat.

PubMed

Banyard, Harry G; Nosaka, Ken; Sato, Kimitake; Haff, G Gregory

2017-10-01

To examine the validity of 2 kinematic systems for assessing mean velocity (MV), peak velocity (PV), mean force (MF), peak force (PF), mean power (MP), and peak power (PP) during the full-depth free-weight back squat performed with maximal concentric effort. Ten strength-trained men (26.1 ± 3.0 y, 1.81 ± 0.07 m, 82.0 ± 10.6 kg) performed three 1-repetition-maximum (1RM) trials on 3 separate days, encompassing lifts performed at 6 relative intensities including 20%, 40%, 60%, 80%, 90%, and 100% of 1RM. Each repetition was simultaneously recorded by a PUSH band and commercial linear position transducer (LPT) (GymAware [GYM]) and compared with measurements collected by a laboratory-based testing device consisting of 4 LPTs and a force plate. Trials 2 and 3 were used for validity analyses. Combining all 120 repetitions indicated that the GYM was highly valid for assessing all criterion variables while the PUSH was only highly valid for estimations of PF (r = .94, CV = 5.4%, ES = 0.28, SEE = 135.5 N). At each relative intensity, the GYM was highly valid for assessing all criterion variables except for PP at 20% (ES = 0.81) and 40% (ES = 0.67) of 1RM. Moreover, the PUSH was only able to accurately estimate PF across all relative intensities (r = .92-.98, CV = 4.0-8.3%, ES = 0.04-0.26, SEE = 79.8-213.1 N). PUSH accuracy for determining MV, PV, MF, MP, and PP across all 6 relative intensities was questionable for the back squat, yet the GYM was highly valid at assessing all criterion variables, with some caution given to estimations of MP and PP performed at lighter loads.

Uncertainty analysis of gross primary production partitioned from net ecosystem exchange measurements

NASA Astrophysics Data System (ADS)

Raj, Rahul; Hamm, Nicholas Alexander Samuel; van der Tol, Christiaan; Stein, Alfred

2016-03-01

Gross primary production (GPP) can be separated from flux tower measurements of net ecosystem exchange (NEE) of CO2. This is used increasingly to validate process-based simulators and remote-sensing-derived estimates of simulated GPP at various time steps. Proper validation includes the uncertainty associated with this separation. In this study, uncertainty assessment was done in a Bayesian framework. It was applied to data from the Speulderbos forest site, The Netherlands. We estimated the uncertainty in GPP at half-hourly time steps, using a non-rectangular hyperbola (NRH) model for its separation from the flux tower measurements. The NRH model provides a robust empirical relationship between radiation and GPP. It includes the degree of curvature of the light response curve, radiation and temperature. Parameters of the NRH model were fitted to the measured NEE data for every 10-day period during the growing season (April to October) in 2009. We defined the prior distribution of each NRH parameter and used Markov chain Monte Carlo (MCMC) simulation to estimate the uncertainty in the separated GPP from the posterior distribution at half-hourly time steps. This time series also allowed us to estimate the uncertainty at daily time steps. We compared the informative with the non-informative prior distributions of the NRH parameters and found that both choices produced similar posterior distributions of GPP. This will provide relevant and important information for the validation of process-based simulators in the future. Furthermore, the obtained posterior distributions of NEE and the NRH parameters are of interest for a range of applications.

Development and validation of an automated operational modal analysis algorithm for vibration-based monitoring and tensile load estimation

NASA Astrophysics Data System (ADS)

Rainieri, Carlo; Fabbrocino, Giovanni

2015-08-01

In the last few decades large research efforts have been devoted to the development of methods for automated detection of damage and degradation phenomena at an early stage. Modal-based damage detection techniques are well-established methods, whose effectiveness for Level 1 (existence) and Level 2 (location) damage detection is demonstrated by several studies. The indirect estimation of tensile loads in cables and tie-rods is another attractive application of vibration measurements. It provides interesting opportunities for cheap and fast quality checks in the construction phase, as well as for safety evaluations and structural maintenance over the structure lifespan. However, the lack of automated modal identification and tracking procedures has been for long a relevant drawback to the extensive application of the above-mentioned techniques in the engineering practice. An increasing number of field applications of modal-based structural health and performance assessment are appearing after the development of several automated output-only modal identification procedures in the last few years. Nevertheless, additional efforts are still needed to enhance the robustness of automated modal identification algorithms, control the computational efforts and improve the reliability of modal parameter estimates (in particular, damping). This paper deals with an original algorithm for automated output-only modal parameter estimation. Particular emphasis is given to the extensive validation of the algorithm based on simulated and real datasets in view of continuous monitoring applications. The results point out that the algorithm is fairly robust and demonstrate its ability to provide accurate and precise estimates of the modal parameters, including damping ratios. As a result, it has been used to develop systems for vibration-based estimation of tensile loads in cables and tie-rods. Promising results have been achieved for non-destructive testing as well as continuous monitoring purposes. They are documented in the last sections of the paper.

Computing travel time when the exact address is unknown: a comparison of point and polygon ZIP code approximation methods.

PubMed

Berke, Ethan M; Shi, Xun

2009-04-29

Travel time is an important metric of geographic access to health care. We compared strategies of estimating travel times when only subject ZIP code data were available. Using simulated data from New Hampshire and Arizona, we estimated travel times to nearest cancer centers by using: 1) geometric centroid of ZIP code polygons as origins, 2) population centroids as origin, 3) service area rings around each cancer center, assigning subjects to rings by assuming they are evenly distributed within their ZIP code, 4) service area rings around each center, assuming the subjects follow the population distribution within the ZIP code. We used travel times based on street addresses as true values to validate estimates. Population-based methods have smaller errors than geometry-based methods. Within categories (geometry or population), centroid and service area methods have similar errors. Errors are smaller in urban areas than in rural areas. Population-based methods are superior to the geometry-based methods, with the population centroid method appearing to be the best choice for estimating travel time. Estimates in rural areas are less reliable.

Detection of sea otters in boat-based surveys of Prince William Sound, Alaska. Marine mammal study 6-19. Exxon Valdez oil spill state/federal natural resource damage assessment final report

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

Udevitz, M.S.; Bodkin, J.L.; Costa, D.P.

1995-05-01

Boat-based surveys were used to monitor the Prince William Sound sea otter population before and after the Exxon Valdez oil spill. Population and loss estimates could be obtained from these surveys by direct expansion from the counts in the surveyed transects under the assumption that all otters in those transects were observed. The authors conducted a pilot study using ground-based observers in conjunction with the August 1990 survey of marine mammals and birds to investigate the validity of this assumption. The proportion of otters detected by boat crews was estimated by comparing boat and ground-based observations on 22 segments ofmore » shoreline transects. Overall, the authors estimated that only 70% of the otters in surveyed shoreline transects were detected by the boat crews. These results suggest that unadjusted expansions of boat survey transect counts will underestimate sea otter population size and that loss estimates based on comparisons of unadjusted population estimates will be biased.« less

Autonomous Landmark Calibration Method for Indoor Localization

PubMed Central

Kim, Jae-Hoon; Kim, Byoung-Seop

2017-01-01

Machine-generated data expansion is a global phenomenon in recent Internet services. The proliferation of mobile communication and smart devices has increased the utilization of machine-generated data significantly. One of the most promising applications of machine-generated data is the estimation of the location of smart devices. The motion sensors integrated into smart devices generate continuous data that can be used to estimate the location of pedestrians in an indoor environment. We focus on the estimation of the accurate location of smart devices by determining the landmarks appropriately for location error calibration. In the motion sensor-based location estimation, the proposed threshold control method determines valid landmarks in real time to avoid the accumulation of errors. A statistical method analyzes the acquired motion sensor data and proposes a valid landmark for every movement of the smart devices. Motion sensor data used in the testbed are collected from the actual measurements taken throughout a commercial building to demonstrate the practical usefulness of the proposed method. PMID:28837071

Validation of equations for pleural effusion volume estimation by ultrasonography.

PubMed

Hassan, Maged; Rizk, Rana; Essam, Hatem; Abouelnour, Ahmed

2017-12-01

To validate the accuracy of previously published equations that estimate pleural effusion volume using ultrasonography. Only equations using simple measurements were tested. Three measurements were taken at the posterior axillary line for each case with effusion: lateral height of effusion ( H ), distance between collapsed lung and chest wall ( C ) and distance between lung and diaphragm ( D ). Cases whose effusion was aspirated to dryness were included and drained volume was recorded. Intra-class correlation coefficient (ICC) was used to determine the predictive accuracy of five equations against the actual volume of aspirated effusion. 46 cases with effusion were included. The most accurate equation in predicting effusion volume was ( H  +  D ) × 70 (ICC 0.83). The simplest and yet accurate equation was H  × 100 (ICC 0.79). Pleural effusion height measured by ultrasonography gives a reasonable estimate of effusion volume. Incorporating distance between lung base and diaphragm into estimation improves accuracy from 79% with the first method to 83% with the latter.

A Bayesian Approach for Measurements of Stray Neutrons at Proton Therapy Facilities: Quantifying Neutron Dose Uncertainty.

PubMed

Dommert, M; Reginatto, M; Zboril, M; Fiedler, F; Helmbrecht, S; Enghardt, W; Lutz, B

2017-11-28

Bonner sphere measurements are typically analyzed using unfolding codes. It is well known that it is difficult to get reliable estimates of uncertainties for standard unfolding procedures. An alternative approach is to analyze the data using Bayesian parameter estimation. This method provides reliable estimates of the uncertainties of neutron spectra leading to rigorous estimates of uncertainties of the dose. We extend previous Bayesian approaches and apply the method to stray neutrons in proton therapy environments by introducing a new parameterized model which describes the main features of the expected neutron spectra. The parameterization is based on information that is available from measurements and detailed Monte Carlo simulations. The validity of this approach has been validated with results of an experiment using Bonner spheres carried out at the experimental hall of the OncoRay proton therapy facility in Dresden. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Conformal Prediction Based on K-Nearest Neighbors for Discrimination of Ginsengs by a Home-Made Electronic Nose

PubMed Central

Sun, Xiyang; Miao, Jiacheng; Wang, You; Luo, Zhiyuan; Li, Guang

2017-01-01

An estimate on the reliability of prediction in the applications of electronic nose is essential, which has not been paid enough attention. An algorithm framework called conformal prediction is introduced in this work for discriminating different kinds of ginsengs with a home-made electronic nose instrument. Nonconformity measure based on k-nearest neighbors (KNN) is implemented separately as underlying algorithm of conformal prediction. In offline mode, the conformal predictor achieves a classification rate of 84.44% based on 1NN and 80.63% based on 3NN, which is better than that of simple KNN. In addition, it provides an estimate of reliability for each prediction. In online mode, the validity of predictions is guaranteed, which means that the error rate of region predictions never exceeds the significance level set by a user. The potential of this framework for detecting borderline examples and outliers in the application of E-nose is also investigated. The result shows that conformal prediction is a promising framework for the application of electronic nose to make predictions with reliability and validity. PMID:28805721

Construction of measurement uncertainty profiles for quantitative analysis of genetically modified organisms based on interlaboratory validation data.

PubMed

Macarthur, Roy; Feinberg, Max; Bertheau, Yves

2010-01-01

A method is presented for estimating the size of uncertainty associated with the measurement of products derived from genetically modified organisms (GMOs). The method is based on the uncertainty profile, which is an extension, for the estimation of uncertainty, of a recent graphical statistical tool called an accuracy profile that was developed for the validation of quantitative analytical methods. The application of uncertainty profiles as an aid to decision making and assessment of fitness for purpose is also presented. Results of the measurement of the quantity of GMOs in flour by PCR-based methods collected through a number of interlaboratory studies followed the log-normal distribution. Uncertainty profiles built using the results generally give an expected range for measurement results of 50-200% of reference concentrations for materials that contain at least 1% GMO. This range is consistent with European Network of GM Laboratories and the European Union (EU) Community Reference Laboratory validation criteria and can be used as a fitness for purpose criterion for measurement methods. The effect on the enforcement of EU labeling regulations is that, in general, an individual analytical result needs to be < 0.45% to demonstrate compliance, and > 1.8% to demonstrate noncompliance with a labeling threshold of 0.9%.

Tumor response estimation in radar-based microwave breast cancer detection.

PubMed

Kurrant, Douglas J; Fear, Elise C; Westwick, David T

2008-12-01

Radar-based microwave imaging techniques have been proposed for early stage breast cancer detection. A considerable challenge for the successful implementation of these techniques is the reduction of clutter, or components of the signal originating from objects other than the tumor. In particular, the reduction of clutter from the late-time scattered fields is required in order to detect small (subcentimeter diameter) tumors. In this paper, a method to estimate the tumor response contained in the late-time scattered fields is presented. The method uses a parametric function to model the tumor response. A maximum a posteriori estimation approach is used to evaluate the optimal values for the estimates of the parameters. A pattern classification technique is then used to validate the estimation. The ability of the algorithm to estimate a tumor response is demonstrated by using both experimental and simulated data obtained with a tissue sensing adaptive radar system.

Validation of farm-scale methane emissions using nocturnal boundary layer budgets

NASA Astrophysics Data System (ADS)

Stieger, J.; Bamberger, I.; Buchmann, N.; Eugster, W.

2015-08-01

This study provides the first experimental validation of Swiss agricultural methane emission estimates at the farm scale. We measured CH4 concentrations at a Swiss farmstead during two intensive field campaigns in August 2011 and July 2012 to (1) quantify the source strength of livestock methane emissions using a tethered balloon system, and (2) to validate inventory emission estimates via nocturnal boundary layer (NBL) budgets. Field measurements were performed at a distance of 150 m from the nearest farm buildings with a tethered balloon system in combination with gradient measurements at eight heights on a 10 m tower to better resolve the near-surface concentrations. Vertical profiles of air temperature, relative humidity, CH4 concentration, wind speed and wind direction showed that the NBL was strongly influenced by local transport processes and by the valley wind system. Methane concentrations showed a pronounced time course, with highest concentrations in the second half of the night. NBL budget flux estimates were obtained via a time-space kriging approach. Main uncertainties of NBL budget flux estimates were associated with instationary atmospheric conditions and the estimate of the inversion height zi (top of volume integration). The mean NBL budget fluxes of 1.60 ± 0.31 μg CH4 m-2 s-1 (1.40 ± 0.50 and 1.66 ± 0.20 μg CH4 m-2 s-1 in 2011 and 2012, respectively) were in good agreement with local inventory estimates based on current livestock number and default emission factors, with 1.29 ± 0.47 and 1.74 ± 0.63 μg CH4 m-2 s-1 for 2011 and 2012, respectively. This indicates that emission factors used for the national inventory reports are adequate, and we conclude that the NBL budget approach is a useful tool to validate emission inventory estimates.

Validation of farm-scale methane emissions using nocturnal boundary layer budgets

NASA Astrophysics Data System (ADS)

Stieger, J.; Bamberger, I.; Buchmann, N.; Eugster, W.

2015-12-01

This study provides the first experimental validation of Swiss agricultural methane emission estimates at the farm scale. We measured CH4 concentrations at a Swiss farmstead during two intensive field campaigns in August 2011 and July 2012 to (1) quantify the source strength of livestock methane emissions using a tethered balloon system and (2) to validate inventory emission estimates via nocturnal boundary layer (NBL) budgets. Field measurements were performed at a distance of 150 m from the nearest farm buildings with a tethered balloon system in combination with gradient measurements at eight heights on a 10 m tower to better resolve the near-surface concentrations. Vertical profiles of air temperature, relative humidity, CH4 concentration, wind speed, and wind direction showed that the NBL was strongly influenced by local transport processes and by the valley wind system. Methane concentrations showed a pronounced time course, with highest concentrations in the second half of the night. NBL budget flux estimates were obtained via a time-space kriging approach. Main uncertainties of NBL budget flux estimates were associated with nonstationary atmospheric conditions and the estimate of the inversion height zi (top of volume integration). The mean NBL budget fluxes of 1.60 ± 0.31 μg CH4 m-2 s-1 (1.40 ± 0.50 and 1.66 ± 0.20 μg CH4 m-2 s-1 in 2011 and 2012 respectively) were in good agreement with local inventory estimates based on current livestock number and default emission factors, with 1.29 ± 0.47 and 1.74 ± 0.63 μg CH4 m-2 s-1 for 2011 and 2012 respectively. This indicates that emission factors used for the national inventory reports are adequate, and we conclude that the NBL budget approach is a useful tool to validate emission inventory estimates.

The Utility of Job Dimensions Based on Form B of the Position Analysis Questionnaire (PAQ) in a Job Component Validation Model. Report No. 5.

ERIC Educational Resources Information Center

Marquardt, Lloyd D.; McCormick, Ernest J.

The study involved the use of a structured job analysis instrument called the Position Analysis Questionnaire (PAQ) as the direct basis for the establishment of the job component validity of aptitude tests (that is, a procedure for estimating the aptitude requirements for jobs strictly on the basis of job analysis data). The sample of jobs used…

Development and validation of a food-based diet quality index for New Zealand adolescents

PubMed Central

2013-01-01

Background As there is no population-specific, simple food-based diet index suitable for examination of diet quality in New Zealand (NZ) adolescents, there is a need to develop such a tool. Therefore, this study aimed to develop an adolescent-specific diet quality index based on dietary information sourced from a Food Questionnaire (FQ) and examine its validity relative to a four-day estimated food record (4DFR) obtained from a group of adolescents aged 14 to 18 years. Methods A diet quality index for NZ adolescents (NZDQI-A) was developed based on ‘Adequacy’ and ‘Variety’ of five food groups reflecting the New Zealand Food and Nutrition Guidelines for Healthy Adolescents. The NZDQI-A was scored from zero to 100, with a higher score reflecting a better diet quality. Forty-one adolescents (16 males, 25 females, aged 14–18 years) each completed the FQ and a 4DFR. The test-retest reliability of the FQ-derived NZDQI-A scores over a two-week period and the relative validity of the scores compared to the 4DFR were estimated using Pearson’s correlations. Construct validity was examined by comparing NZDQI-A scores against nutrient intakes obtained from the 4DFR. Results The NZDQI-A derived from the FQ showed good reliability (r = 0.65) and reasonable agreement with 4DFR in ranking participants by scores (r = 0.39). More than half of the participants were classified into the same thirds of scores while 10% were misclassified into the opposite thirds by the two methods. Higher NZDQI-A scores were also associated with lower total fat and saturated fat intakes and higher iron intakes. Conclusions Higher NZDQI-A scores were associated with more desirable fat and iron intakes. The scores derived from either FQ or 4DFR were comparable and reproducible when repeated within two weeks. The NZDQI-A is relatively valid and reliable in ranking diet quality in adolescents at a group level even in a small sample size. Further studies are required to test the predictive validity of this food-based diet index in larger samples. PMID:23759064

Permeability Estimation of Rock Reservoir Based on PCA and Elman Neural Networks

NASA Astrophysics Data System (ADS)

Shi, Ying; Jian, Shaoyong

2018-03-01

an intelligent method which based on fuzzy neural networks with PCA algorithm, is proposed to estimate the permeability of rock reservoir. First, the dimensionality reduction process is utilized for these parameters by principal component analysis method. Further, the mapping relationship between rock slice characteristic parameters and permeability had been found through fuzzy neural networks. The estimation validity and reliability for this method were tested with practical data from Yan’an region in Ordos Basin. The result showed that the average relative errors of permeability estimation for this method is 6.25%, and this method had the better convergence speed and more accuracy than other. Therefore, by using the cheap rock slice related information, the permeability of rock reservoir can be estimated efficiently and accurately, and it is of high reliability, practicability and application prospect.

New robust statistical procedures for the polytomous logistic regression models.

PubMed

Castilla, Elena; Ghosh, Abhik; Martin, Nirian; Pardo, Leandro

2018-05-17

This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic regression model. Based on these estimators, a family of Wald-type test statistics for linear hypotheses is introduced. Robustness properties of both the proposed estimators and the test statistics are theoretically studied through the classical influence function analysis. Appropriate real life examples are presented to justify the requirement of suitable robust statistical procedures in place of the likelihood based inference for the polytomous logistic regression model. The validity of the theoretical results established in the article are further confirmed empirically through suitable simulation studies. Finally, an approach for the data-driven selection of the robustness tuning parameter is proposed with empirical justifications. © 2018, The International Biometric Society.

Using pedometers to estimate ambulatory physical activity in Vietnam.

PubMed

Thuy, Au Bich; Blizzard, Leigh; Schmidt, Michael; Magnussen, Costan; Hansen, Emily; Dwyer, Terence

2011-01-01

Pedometer measurement of physical activity (PA) has been shown to be reliable and valid in industrialized populations, but its applicability in economically developing Vietnam remains untested. This study assessed the feasibility, stability and validity of pedometer estimates of PA in Vietnam. 250 adults from a population-based survey were randomly selected to wear Yamax pedometers and record activities for 7 consecutive days. Stability and concurrent validity were assessed using intraclass correlation coefficients (ICC) and Spearman correlation coefficients. Overall, 97.6% of participants provided at least 1 day of usable recordings, and 76.2% wore pedometers for all 7 days. Only 5.2% of the sample participants were involved in work activities not measurable by pedometer. The number of steps increased with hours of wear. There was no significant difference between weekday and weekend in number of steps, and at least 3 days of recordings were required (ICC of the 3 days of recordings: men 0.96, women 0.97). Steps per hour were moderately correlated (men r = .42, women r = .26) with record estimates of total PA. It is feasible to use pedometers to estimate PA in Vietnam. The measure should involve at least 3 days of recording irrespective of day of the week. ©2011 Human Kinetics, Inc.

Prediction of resource volumes at untested locations using simple local prediction models

USGS Publications Warehouse

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

Development of an anaerobic threshold (HRLT, HRVT) estimation equation using the heart rate threshold (HRT) during the treadmill incremental exercise test

PubMed Central

Ham, Joo-ho; Park, Hun-Young; Kim, Youn-ho; Bae, Sang-kon; Ko, Byung-hoon

2017-01-01

[Purpose] The purpose of this study was to develop a regression model to estimate the heart rate at the lactate threshold (HRLT) and the heart rate at the ventilatory threshold (HRVT) using the heart rate threshold (HRT), and to test the validity of the regression model. [Methods] We performed a graded exercise test with a treadmill in 220 normal individuals (men: 112, women: 108) aged 20–59 years. HRT, HRLT, and HRVT were measured in all subjects. A regression model was developed to estimate HRLT and HRVT using HRT with 70% of the data (men: 79, women: 76) through randomization (7:3), with the Bernoulli trial. The validity of the regression model developed with the remaining 30% of the data (men: 33, women: 32) was also examined. [Results] Based on the regression coefficient, we found that the independent variable HRT was a significant variable in all regression models. The adjusted R2 of the developed regression models averaged about 70%, and the standard error of estimation of the validity test results was 11 bpm, which is similar to that of the developed model. [Conclusion] These results suggest that HRT is a useful parameter for predicting HRLT and HRVT. PMID:29036765

Development of an anaerobic threshold (HRLT, HRVT) estimation equation using the heart rate threshold (HRT) during the treadmill incremental exercise test.

PubMed

Ham, Joo-Ho; Park, Hun-Young; Kim, Youn-Ho; Bae, Sang-Kon; Ko, Byung-Hoon; Nam, Sang-Seok

2017-09-30

The purpose of this study was to develop a regression model to estimate the heart rate at the lactate threshold (HRLT) and the heart rate at the ventilatory threshold (HRVT) using the heart rate threshold (HRT), and to test the validity of the regression model. We performed a graded exercise test with a treadmill in 220 normal individuals (men: 112, women: 108) aged 20-59 years. HRT, HRLT, and HRVT were measured in all subjects. A regression model was developed to estimate HRLT and HRVT using HRT with 70% of the data (men: 79, women: 76) through randomization (7:3), with the Bernoulli trial. The validity of the regression model developed with the remaining 30% of the data (men: 33, women: 32) was also examined. Based on the regression coefficient, we found that the independent variable HRT was a significant variable in all regression models. The adjusted R2 of the developed regression models averaged about 70%, and the standard error of estimation of the validity test results was 11 bpm, which is similar to that of the developed model. These results suggest that HRT is a useful parameter for predicting HRLT and HRVT. ©2017 The Korean Society for Exercise Nutrition

Evaluation for relationship among source parameters of underground nuclear tests in Northern Korean Peninsula

NASA Astrophysics Data System (ADS)

Kim, G.; Che, I. Y.

2017-12-01

We evaluated relationship among source parameters of underground nuclear tests in northern Korean Peninsula using regional seismic data. Dense global and regional seismic networks are incorporated to measure locations and origin times precisely. Location analyses show that distance among the locations is tiny on a regional scale. The tiny location-differences validate a linear model assumption. We estimated source spectral ratios by excluding path effects based spectral ratios of the observed seismograms. We estimated empirical relationship among depth of burials and yields based on theoretical source models.

Validation techniques for fault emulation of SRAM-based FPGAs

DOE PAGES

Quinn, Heather; Wirthlin, Michael

2015-08-07

A variety of fault emulation systems have been created to study the effect of single-event effects (SEEs) in static random access memory (SRAM) based field-programmable gate arrays (FPGAs). These systems are useful for augmenting radiation-hardness assurance (RHA) methodologies for verifying the effectiveness for mitigation techniques; understanding error signatures and failure modes in FPGAs; and failure rate estimation. For radiation effects researchers, it is important that these systems properly emulate how SEEs manifest in FPGAs. If the fault emulation systems does not mimic the radiation environment, the system will generate erroneous data and incorrect predictions of behavior of the FPGA inmore » a radiation environment. Validation determines whether the emulated faults are reasonable analogs to the radiation-induced faults. In this study we present methods for validating fault emulation systems and provide several examples of validated FPGA fault emulation systems.« less

Validation of Nimbus-7 temperature-humidity infrared radiometer estimates of cloud type and amount

NASA Technical Reports Server (NTRS)

Stowe, L. L.

1982-01-01

Estimates of clear and low, middle and high cloud amount in fixed geographical regions approximately (160 km) squared are being made routinely from 11.5 micron radiance measurements of the Nimbus-7 Temperature-Humidity Infrared Radiometer (THIR). The purpose of validation is to determine the accuracy of the THIR cloud estimates. Validation requires that a comparison be made between the THIR estimates of cloudiness and the 'true' cloudiness. The validation results reported in this paper use human analysis of concurrent but independent satellite images with surface meteorological and radiosonde observations to approximate the 'true' cloudiness. Regression and error analyses are used to estimate the systematic and random errors of THIR derived clear amount.

The use of multiple imputation method for the validation of 24-h food recalls by part-time observation of dietary intake in school.

PubMed

Kupek, Emil; de Assis, Maria Alice A

2016-09-01

External validation of food recall over 24 h in schoolchildren is often restricted to eating events in schools and is based on direct observation as the reference method. The aim of this study was to estimate the dietary intake out of school, and consequently the bias in such research design based on only part-time validated food recall, using multiple imputation (MI) conditioned on the information on child age, sex, BMI, family income, parental education and the school attended. The previous-day, web-based questionnaire WebCAAFE, structured as six meals/snacks and thirty-two foods/beverage, was answered by a sample of 7-11-year-old Brazilian schoolchildren (n 602) from five public schools. Food/beverage intake recalled by children was compared with the records provided by trained observers during school meals. Sensitivity analysis was performed with artificial data emulating those recalled by children on WebCAAFE in order to evaluate the impact of both differential and non-differential bias. Estimated bias was within ±30 % interval for 84·4 % of the thirty-two foods/beverages evaluated in WebCAAFE, and half of the latter reached statistical significance (P<0·05). Rarely (<3 %) consumed dietary items were often under-reported (fish/seafood, vegetable soup, cheese bread, French fries), whereas some of those most frequently reported (meat, bread/biscuits, fruits) showed large overestimation. Compared with the analysis restricted to fully validated data, MI reduced differential bias in sensitivity analysis but the bias still remained large in most cases. MI provided a suitable statistical framework for part-time validation design of dietary intake over six daily eating events.

The composite complex span: French validation of a short working memory task.

PubMed

Gonthier, Corentin; Thomassin, Noémylle; Roulin, Jean-Luc

2016-03-01

Most studies in individual differences in the field of working memory research use complex span tasks to measure working memory capacity. Various complex span tasks based on different materials have been developed, and these tasks have proven both reliable and valid; several complex span tasks are often combined to provide a domain-general estimate of working memory capacity with even better psychometric properties. The present work sought to address two issues. Firstly, having participants perform several full-length complex span tasks in succession makes for a long and tedious procedure. Secondly, few complex span tasks have been translated and validated in French. We constructed a French working memory task labeled the Composite Complex Span (CCS). The CCS includes shortened versions of three classic complex span tasks: the reading span, symmetry span, and operation span. We assessed the psychometric properties of the CCS, including test-retest reliability and convergent validity, with Raven's Advanced Progressive Matrices and with an alpha span task; the CCS demonstrated satisfying qualities in a sample of 1,093 participants. This work provides evidence that shorter versions of classic complex span tasks can yield valid working memory estimates. The materials and normative data for the CCS are also included.

Estimating groundwater levels using system identification models in Nzhelele and Luvuvhu areas, Limpopo Province, South Africa

NASA Astrophysics Data System (ADS)

Makungo, Rachel; Odiyo, John O.

2017-08-01

This study was focused on testing the ability of a coupled linear and non-linear system identification model in estimating groundwater levels. System identification provides an alternative approach for estimating groundwater levels in areas that lack data required by physically-based models. It also overcomes the limitations of physically-based models due to approximations, assumptions and simplifications. Daily groundwater levels for 4 boreholes, rainfall and evaporation data covering the period 2005-2014 were used in the study. Seventy and thirty percent of the data were used to calibrate and validate the model, respectively. Correlation coefficient (R), coefficient of determination (R2), root mean square error (RMSE), percent bias (PBIAS), Nash Sutcliffe coefficient of efficiency (NSE) and graphical fits were used to evaluate the model performance. Values for R, R2, RMSE, PBIAS and NSE ranged from 0.8 to 0.99, 0.63 to 0.99, 0.01-2.06 m, -7.18 to 1.16 and 0.68 to 0.99, respectively. Comparisons of observed and simulated groundwater levels for calibration and validation runs showed close agreements. The model performance mostly varied from satisfactory, good, very good and excellent. Thus, the model is able to estimate groundwater levels. The calibrated models can reasonably capture description between input and output variables and can, thus be used to estimate long term groundwater levels.

Dutch population specific sex estimation formulae using the proximal femur.

PubMed

Colman, K L; Janssen, M C L; Stull, K E; van Rijn, R R; Oostra, R J; de Boer, H H; van der Merwe, A E

2018-05-01

Sex estimation techniques are frequently applied in forensic anthropological analyses of unidentified human skeletal remains. While morphological sex estimation methods are able to endure population differences, the classification accuracy of metric sex estimation methods are population-specific. No metric sex estimation method currently exists for the Dutch population. The purpose of this study is to create Dutch population specific sex estimation formulae by means of osteometric analyses of the proximal femur. Since the Netherlands lacks a representative contemporary skeletal reference population, 2D plane reconstructions, derived from clinical computed tomography (CT) data, were used as an alternative source for a representative reference sample. The first part of this study assesses the intra- and inter-observer error, or reliability, of twelve measurements of the proximal femur. The technical error of measurement (TEM) and relative TEM (%TEM) were calculated using 26 dry adult femora. In addition, the agreement, or accuracy, between the dry bone and CT-based measurements was determined by percent agreement. Only reliable and accurate measurements were retained for the logistic regression sex estimation formulae; a training set (n=86) was used to create the models while an independent testing set (n=28) was used to validate the models. Due to high levels of multicollinearity, only single variable models were created. Cross-validated classification accuracies ranged from 86% to 92%. The high cross-validated classification accuracies indicate that the developed formulae can contribute to the biological profile and specifically in sex estimation of unidentified human skeletal remains in the Netherlands. Furthermore, the results indicate that clinical CT data can be a valuable alternative source of data when representative skeletal collections are unavailable. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating Computer-Based Training Development Times

DTIC Science & Technology

1987-10-14

beginners , must be sure they interpret terms correctly. As a result of this informal validation, the authors suggest refinements in the tool which...Productivity tools available: automated design tools, text processor interfaces, flowcharting software, software interfaces a Multimedia interfaces e

Development and Validation of a Physiologically Based Pharmacokinetic Model of Chloral Hydrate and Its Main Metabolites

DTIC Science & Technology

1995-11-01

for a computer-aided simulation of body levels of chloral hydrate in a therapeutic situation and for the estimate of toxicokinetics of its active metabolites generated during the environmental pollution scenario.

Estimated glomerular filtration rate is an early biomarker of cardiac surgery-associated acute kidney injury.

PubMed

Candela-Toha, Ángel; Pardo, María Carmen; Pérez, Teresa; Muriel, Alfonso; Zamora, Javier

2018-04-20

and objective Acute kidney injury (AKI) diagnosis is still based on serum creatinine and diuresis. However, increases in creatinine are typically delayed 48h or longer after injury. Our aim was to determine the utility of routine postoperative renal function blood tests, to predict AKI one or 2days in advance in a cohort of cardiac surgery patients. Using a prospective database, we selected a sample of patients who had undergone major cardiac surgery between January 2002 and December 2013. The ability of the parameters to predict AKI was based on Acute Kidney Injury Network serum creatinine criteria. A cohort of 3,962 cases was divided into 2groups of similar size, one being exploratory and the other a validation sample. The exploratory group was used to show primary objectives and the validation group to confirm results. The ability to predict AKI of several kidney function parameters measured in routine postoperative blood tests, was measured with time-dependent ROC curves. The primary endpoint was time from measurement to AKI diagnosis. AKI developed in 610 (30.8%) and 623 (31.4%) patients in the exploratory and validation samples, respectively. Estimated glomerular filtration rate using the MDRD-4 equation showed the best AKI prediction capacity, with values for the AUC ROC curves between 0.700 and 0.946. We obtained different cut-off values for estimated glomerular filtration rate depending on the degree of AKI severity and on the time elapsed between surgery and parameter measurement. Results were confirmed in the validation sample. Postoperative estimated glomerular filtration rate using the MDRD-4 equation showed good ability to predict AKI following cardiac surgery one or 2days in advance. Copyright © 2018 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.

Validation by simulation of a clinical trial model using the standardized mean and variance criteria.

PubMed

Abbas, Ismail; Rovira, Joan; Casanovas, Josep

2006-12-01

To develop and validate a model of a clinical trial that evaluates the changes in cholesterol level as a surrogate marker for lipodystrophy in HIV subjects under alternative antiretroviral regimes, i.e., treatment with Protease Inhibitors vs. a combination of nevirapine and other antiretroviral drugs. Five simulation models were developed based on different assumptions, on treatment variability and pattern of cholesterol reduction over time. The last recorded cholesterol level, the difference from the baseline, the average difference from the baseline and level evolution, are the considered endpoints. Specific validation criteria based on a 10% minus or plus standardized distance in means and variances were used to compare the real and the simulated data. The validity criterion was met by all models for considered endpoints. However, only two models met the validity criterion when all endpoints were considered. The model based on the assumption that within-subjects variability of cholesterol levels changes over time is the one that minimizes the validity criterion, standardized distance equal to or less than 1% minus or plus. Simulation is a useful technique for calibration, estimation, and evaluation of models, which allows us to relax the often overly restrictive assumptions regarding parameters required by analytical approaches. The validity criterion can also be used to select the preferred model for design optimization, until additional data are obtained allowing an external validation of the model.

Validation of an administrative claims-based diagnostic code for pneumonia in a US-based commercially insured COPD population

PubMed Central

Kern, David M; Davis, Jill; Williams, Setareh A; Tunceli, Ozgur; Wu, Bingcao; Hollis, Sally; Strange, Charlie; Trudo, Frank

2015-01-01

Objective To estimate the accuracy of claims-based pneumonia diagnoses in COPD patients using clinical information in medical records as the reference standard. Methods Selecting from a repository containing members’ data from 14 regional United States health plans, this validation study identified pneumonia diagnoses within a group of patients initiating treatment for COPD between March 1, 2009 and March 31, 2012. Patients with ≥1 claim for pneumonia (International Classification of Diseases Version 9-CM code 480.xx–486.xx) were identified during the 12 months following treatment initiation. A subset of 800 patients was randomly selected to abstract medical record data (paper based and electronic) for a target sample of 400 patients, to estimate validity within 5% margin of error. Positive predictive value (PPV) was calculated for the claims diagnosis of pneumonia relative to the reference standard, defined as a documented diagnosis in the medical record. Results A total of 388 records were reviewed; 311 included a documented pneumonia diagnosis, indicating 80.2% (95% confidence interval [CI]: 75.8% to 84.0%) of claims-identified pneumonia diagnoses were validated by the medical charts. Claims-based diagnoses in inpatient or emergency departments (n=185) had greater PPV versus outpatient settings (n=203), 87.6% (95% CI: 81.9%–92.0%) versus 73.4% (95% CI: 66.8%–79.3%), respectively. Claims-diagnoses verified with paper-based charts had similar PPV as the overall study sample, 80.2% (95% CI: 71.1%–87.5%), and higher PPV than those linked to electronic medical records, 73.3% (95% CI: 65.5%–80.2%). Combined paper-based and electronic records had a higher PPV, 87.6% (95% CI: 80.9%–92.6%). Conclusion Administrative claims data indicating a diagnosis of pneumonia in COPD patients are supported by medical records. The accuracy of a medical record diagnosis of pneumonia remains unknown. With increased use of claims data in medical research, COPD researchers can study pneumonia with confidence that claims data are a valid tool when studying the safety of COPD therapies that could potentially lead to increased pneumonia susceptibility or severity. PMID:26229461

Validation of an administrative claims-based diagnostic code for pneumonia in a US-based commercially insured COPD population.

PubMed

Kern, David M; Davis, Jill; Williams, Setareh A; Tunceli, Ozgur; Wu, Bingcao; Hollis, Sally; Strange, Charlie; Trudo, Frank

2015-01-01

To estimate the accuracy of claims-based pneumonia diagnoses in COPD patients using clinical information in medical records as the reference standard. Selecting from a repository containing members' data from 14 regional United States health plans, this validation study identified pneumonia diagnoses within a group of patients initiating treatment for COPD between March 1, 2009 and March 31, 2012. Patients with ≥1 claim for pneumonia (International Classification of Diseases Version 9-CM code 480.xx-486.xx) were identified during the 12 months following treatment initiation. A subset of 800 patients was randomly selected to abstract medical record data (paper based and electronic) for a target sample of 400 patients, to estimate validity within 5% margin of error. Positive predictive value (PPV) was calculated for the claims diagnosis of pneumonia relative to the reference standard, defined as a documented diagnosis in the medical record. A total of 388 records were reviewed; 311 included a documented pneumonia diagnosis, indicating 80.2% (95% confidence interval [CI]: 75.8% to 84.0%) of claims-identified pneumonia diagnoses were validated by the medical charts. Claims-based diagnoses in inpatient or emergency departments (n=185) had greater PPV versus outpatient settings (n=203), 87.6% (95% CI: 81.9%-92.0%) versus 73.4% (95% CI: 66.8%-79.3%), respectively. Claims-diagnoses verified with paper-based charts had similar PPV as the overall study sample, 80.2% (95% CI: 71.1%-87.5%), and higher PPV than those linked to electronic medical records, 73.3% (95% CI: 65.5%-80.2%). Combined paper-based and electronic records had a higher PPV, 87.6% (95% CI: 80.9%-92.6%). Administrative claims data indicating a diagnosis of pneumonia in COPD patients are supported by medical records. The accuracy of a medical record diagnosis of pneumonia remains unknown. With increased use of claims data in medical research, COPD researchers can study pneumonia with confidence that claims data are a valid tool when studying the safety of COPD therapies that could potentially lead to increased pneumonia susceptibility or severity.

Development and application of Model of Resource Utilization, Costs, and Outcomes for Stroke (MORUCOS): an Australian economic model for stroke.

PubMed

Mihalopoulos, Catherine; Cadilhac, Dominique A; Moodie, Marjory L; Dewey, Helen M; Thrift, Amanda G; Donnan, Geoffrey A; Carter, Robert C

2005-01-01

To outline the development, structure, data assumptions, and application of an Australian economic model for stroke (Model of Resource Utilization, Costs, and Outcomes for Stroke [MORUCOS]). The model has a linked spreadsheet format with four modules to describe the disease burden and treatment pathways, estimate prevalence-based and incidence-based costs, and derive life expectancy and quality of life consequences. The model uses patient-level, community-based, stroke cohort data and macro-level simulations. An interventions module allows options for change to be consistently evaluated by modifying aspects of the other modules. To date, model validation has included sensitivity testing, face validity, and peer review. Further validation of technical and predictive accuracy is needed. The generic pathway model was assessed by comparison with a stroke subtypes (ischemic, hemorrhagic, or undetermined) approach and used to determine the relative cost-effectiveness of four interventions. The generic pathway model produced lower costs compared with a subtypes version (total average first-year costs/case AUD$ 15,117 versus AUD$ 17,786, respectively). Optimal evidence-based uptake of anticoagulation therapy for primary and secondary stroke prevention and intravenous thrombolytic therapy within 3 hours of stroke were more cost-effective than current practice (base year, 1997). MORUCOS is transparent and flexible in describing Australian stroke care and can effectively be used to systematically evaluate a range of different interventions. Adjusting results to account for stroke subtypes, as they influence cost estimates, could enhance the generic model.

Measuring reproductive health: review of community-based approaches to assessing morbidity.

PubMed Central

Sadana, R.

2000-01-01

This article begins by reviewing selected past approaches to estimating the prevalence of a range of morbidities through the use of household or community-based interview surveys in developed and developing countries. Subsequently, it reviews epidemiological studies that have used a range of methods to estimate the prevalence of reproductive morbidities. A detailed review of recent community or hospital based health interview validation studies that compare self-reported, clinical and laboratory measures is presented. Studies from Bangladesh, Bolivia, China, Egypt, India, Indonesia, Nigeria, Philippines and Turkey provide empirical evidence that self-reported morbidity and observed morbidity measure different phenomena and therefore different aspects of reproductive health and illness. Rather than estimating the prevalence of morbidity, interview-based surveys may provide useful information about the disability or burden associated with reproductive health and illness. PMID:10859858

Are Validity and Reliability "Relevant" in Qualitative Evaluation Research?

ERIC Educational Resources Information Center

Goodwin, Laura D.; Goodwin, William L.

1984-01-01

The views of prominant qualitative methodologists on the appropriateness of validity and reliability estimation for the measurement strategies employed in qualitative evaluations are summarized. A case is made for the relevance of validity and reliability estimation. Definitions of validity and reliability for qualitative measurement are presented…

Incremental inverse kinematics based vision servo for autonomous robotic capture of non-cooperative space debris

NASA Astrophysics Data System (ADS)

Dong, Gangqi; Zhu, Z. H.

2016-04-01

This paper proposed a new incremental inverse kinematics based vision servo approach for robotic manipulators to capture a non-cooperative target autonomously. The target's pose and motion are estimated by a vision system using integrated photogrammetry and EKF algorithm. Based on the estimated pose and motion of the target, the instantaneous desired position of the end-effector is predicted by inverse kinematics and the robotic manipulator is moved incrementally from its current configuration subject to the joint speed limits. This approach effectively eliminates the multiple solutions in the inverse kinematics and increases the robustness of the control algorithm. The proposed approach is validated by a hardware-in-the-loop simulation, where the pose and motion of the non-cooperative target is estimated by a real vision system. The simulation results demonstrate the effectiveness and robustness of the proposed estimation approach for the target and the incremental control strategy for the robotic manipulator.

Free kick instead of cross-validation in maximum-likelihood refinement of macromolecular crystal structures

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

Pražnikar, Jure; University of Primorska,; Turk, Dušan, E-mail: dusan.turk@ijs.si

2014-12-01

The maximum-likelihood free-kick target, which calculates model error estimates from the work set and a randomly displaced model, proved superior in the accuracy and consistency of refinement of crystal structures compared with the maximum-likelihood cross-validation target, which calculates error estimates from the test set and the unperturbed model. The refinement of a molecular model is a computational procedure by which the atomic model is fitted to the diffraction data. The commonly used target in the refinement of macromolecular structures is the maximum-likelihood (ML) function, which relies on the assessment of model errors. The current ML functions rely on cross-validation. Theymore » utilize phase-error estimates that are calculated from a small fraction of diffraction data, called the test set, that are not used to fit the model. An approach has been developed that uses the work set to calculate the phase-error estimates in the ML refinement from simulating the model errors via the random displacement of atomic coordinates. It is called ML free-kick refinement as it uses the ML formulation of the target function and is based on the idea of freeing the model from the model bias imposed by the chemical energy restraints used in refinement. This approach for the calculation of error estimates is superior to the cross-validation approach: it reduces the phase error and increases the accuracy of molecular models, is more robust, provides clearer maps and may use a smaller portion of data for the test set for the calculation of R{sub free} or may leave it out completely.« less

Modeling and simulation of soft sensor design for real-time speed estimation, measurement and control of induction motor.

PubMed

Etien, Erik

2013-05-01

This paper deals with the design of a speed soft sensor for induction motor. The sensor is based on the physical model of the motor. Because the validation step highlight the fact that the sensor cannot be validated for all the operating points, the model is modified in order to obtain a fully validated sensor in the whole speed range. An original feature of the proposed approach is that the modified model is derived from stability analysis using automatic control theory. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

SU-E-T-769: T-Test Based Prior Error Estimate and Stopping Criterion for Monte Carlo Dose Calculation in Proton Therapy

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

Hong, X; Gao, H; Schuemann, J

2015-06-15

Purpose: The Monte Carlo (MC) method is a gold standard for dose calculation in radiotherapy. However, it is not a priori clear how many particles need to be simulated to achieve a given dose accuracy. Prior error estimate and stopping criterion are not well established for MC. This work aims to fill this gap. Methods: Due to the statistical nature of MC, our approach is based on one-sample t-test. We design the prior error estimate method based on the t-test, and then use this t-test based error estimate for developing a simulation stopping criterion. The three major components are asmore » follows.First, the source particles are randomized in energy, space and angle, so that the dose deposition from a particle to the voxel is independent and identically distributed (i.i.d.).Second, a sample under consideration in the t-test is the mean value of dose deposition to the voxel by sufficiently large number of source particles. Then according to central limit theorem, the sample as the mean value of i.i.d. variables is normally distributed with the expectation equal to the true deposited dose.Third, the t-test is performed with the null hypothesis that the difference between sample expectation (the same as true deposited dose) and on-the-fly calculated mean sample dose from MC is larger than a given error threshold, in addition to which users have the freedom to specify confidence probability and region of interest in the t-test based stopping criterion. Results: The method is validated for proton dose calculation. The difference between the MC Result based on the t-test prior error estimate and the statistical Result by repeating numerous MC simulations is within 1%. Conclusion: The t-test based prior error estimate and stopping criterion are developed for MC and validated for proton dose calculation. Xiang Hong and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

Robust Foot Clearance Estimation Based on the Integration of Foot-Mounted IMU Acceleration Data

PubMed Central

Benoussaad, Mourad; Sijobert, Benoît; Mombaur, Katja; Azevedo Coste, Christine

2015-01-01

This paper introduces a method for the robust estimation of foot clearance during walking, using a single inertial measurement unit (IMU) placed on the subject’s foot. The proposed solution is based on double integration and drift cancellation of foot acceleration signals. The method is insensitive to misalignment of IMU axes with respect to foot axes. Details are provided regarding calibration and signal processing procedures. Experimental validation was performed on 10 healthy subjects under three walking conditions: normal, fast and with obstacles. Foot clearance estimation results were compared to measurements from an optical motion capture system. The mean error between them is significantly less than 15% under the various walking conditions. PMID:26703622

Conservative classical and quantum resolution limits for incoherent imaging

NASA Astrophysics Data System (ADS)

Tsang, Mankei

2018-06-01

I propose classical and quantum limits to the statistical resolution of two incoherent optical point sources from the perspective of minimax parameter estimation. Unlike earlier results based on the Cramér-Rao bound (CRB), the limits proposed here, based on the worst-case error criterion and a Bayesian version of the CRB, are valid for any biased or unbiased estimator and obey photon-number scalings that are consistent with the behaviours of actual estimators. These results prove that, from the minimax perspective, the spatial-mode demultiplexing measurement scheme recently proposed by Tsang, Nair, and Lu [Phys. Rev. X 2016, 6 031033.] remains superior to direct imaging for sufficiently high photon numbers.

Neural networks for tracking of unknown SISO discrete-time nonlinear dynamic systems.

PubMed

Aftab, Muhammad Saleheen; Shafiq, Muhammad

2015-11-01

This article presents a Lyapunov function based neural network tracking (LNT) strategy for single-input, single-output (SISO) discrete-time nonlinear dynamic systems. The proposed LNT architecture is composed of two feedforward neural networks operating as controller and estimator. A Lyapunov function based back propagation learning algorithm is used for online adjustment of the controller and estimator parameters. The controller and estimator error convergence and closed-loop system stability analysis is performed by Lyapunov stability theory. Moreover, two simulation examples and one real-time experiment are investigated as case studies. The achieved results successfully validate the controller performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling

NASA Astrophysics Data System (ADS)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-08-01

XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.

Position Estimation Using Image Derivative

NASA Technical Reports Server (NTRS)

Mortari, Daniele; deDilectis, Francesco; Zanetti, Renato

2015-01-01

This paper describes an image processing algorithm to process Moon and/or Earth images. The theory presented is based on the fact that Moon hard edge points are characterized by the highest values of the image derivative. Outliers are eliminated by two sequential filters. Moon center and radius are then estimated by nonlinear least-squares using circular sigmoid functions. The proposed image processing has been applied and validated using real and synthetic Moon images.

Comparison Between the Use of SAR and Optical Data for Wheat Yield Estimations Using Crop Model Assimilation

NASA Astrophysics Data System (ADS)

Silvestro, Paolo Cosmo; Yang, Hao; Jin, X. L.; Yang, Guijun; Casa, Raffaele; Pignatti, Stefano

2016-08-01

The ultimate aim of this work is to develop methods for the assimilation of the biophysical variables estimated by remote sensing in a suitable crop growth model. Two strategies were followed, one based on the use of Leaf Area Index (LAI) estimated by optical data, and the other based on the use of biomass estimated by SAR. The first one estimates LAI from the reflectance measured by the optical sensors on board of HJ1A, HJ1B and Landsat, using a method based on the training of artificial neural networks (ANN) with PROSAIL model simulations. The retrieved LAI is used to improve wheat yield estimation, using assimilation methods based on the Ensemble Kalman Filter, which assimilate the biophysical variables into growth crop model. The second strategy estimates biomass from SAR imagery. Polarimetric decomposition methods were used based on multi-temporal fully polarimetric Radarsat-2 data during the entire growing season. The estimated biomass was assimilating to FAO Aqua crop model for improving the winter wheat yield estimation, with the Particle Swarm Optimization (PSO) method. These procedures were used in a spatial application with data collected in the rural area of Yangling (Shaanxi Province) in 2014 and were validated for a number of wheat fields for which ground yield data had been recorded and according to statistical yield data for the area.

Performance assessment of different day-of-the-year-based models for estimating global solar radiation - Case study: Egypt

NASA Astrophysics Data System (ADS)

Hassan, Gasser E.; Youssef, M. Elsayed; Ali, Mohamed A.; Mohamed, Zahraa E.; Shehata, Ali I.

2016-11-01

Different models are introduced to predict the daily global solar radiation in different locations but there is no specific model based on the day of the year is proposed for many locations around the world. In this study, more than 20 years of measured data for daily global solar radiation on a horizontal surface are used to develop and validate seven models to estimate the daily global solar radiation by day of the year for ten cities around Egypt as a case study. Moreover, the generalization capability for the best models is examined all over the country. The regression analysis is employed to calculate the coefficients of different suggested models. The statistical indicators namely, RMSE, MABE, MAPE, r and R2 are calculated to evaluate the performance of the developed models. Based on the validation with the available data, the results show that the hybrid sine and cosine wave model and 4th order polynomial model have the best performance among other suggested models. Consequently, these two models coupled with suitable coefficients can be used for estimating the daily global solar radiation on a horizontal surface for each city, and also for all the locations around the studied region. It is believed that the established models in this work are applicable and significant for quick estimation for the average daily global solar radiation on a horizontal surface with higher accuracy. The values of global solar radiation generated by this approach can be utilized in the design and estimation of the performance of different solar applications.

Rainfall Product Evaluation for the TRMM Ground Validation Program

NASA Technical Reports Server (NTRS)

Amitai, E.; Wolff, D. B.; Robinson, M.; Silberstein, D. S.; Marks, D. A.; Kulie, M. S.; Fisher, B.; Einaudi, Franco (Technical Monitor)

2000-01-01

Evaluation of the Tropical Rainfall Measuring Mission (TRMM) satellite observations is conducted through a comprehensive Ground Validation (GV) Program. Standardized instantaneous and monthly rainfall products are routinely generated using quality-controlled ground based radar data from four primary GV sites. As part of the TRMM GV program, effort is being made to evaluate these GV products and to determine the uncertainties of the rainfall estimates. The evaluation effort is based on comparison to rain gauge data. The variance between the gauge measurement and the true averaged rain amount within the radar pixel is a limiting factor in the evaluation process. While monthly estimates are relatively simple to evaluate, the evaluation of the instantaneous products are much more of a challenge. Scattegrams of point comparisons between radar and rain gauges are extremely noisy for several reasons (e.g. sample volume discrepancies, timing and navigation mismatches, variability of Z(sub e)-R relationships), and therefore useless for evaluating the estimates. Several alternative methods, such as the analysis of the distribution of rain volume by rain rate as derived from gauge intensities and from reflectivities above the gauge network will be presented. Alternative procedures to increase the accuracy of the estimates and to reduce their uncertainties also will be discussed.

Estimating population trends with a linear model: Technical comments

USGS Publications Warehouse

Sauer, John R.; Link, William A.; Royle, J. Andrew

2004-01-01

Controversy has sometimes arisen over whether there is a need to accommodate the limitations of survey design in estimating population change from the count data collected in bird surveys. Analyses of surveys such as the North American Breeding Bird Survey (BBS) can be quite complex; it is natural to ask if the complexity is necessary, or whether the statisticians have run amok. Bart et al. (2003) propose a very simple analysis involving nothing more complicated than simple linear regression, and contrast their approach with model-based procedures. We review the assumptions implicit to their proposed method, and document that these assumptions are unlikely to be valid for surveys such as the BBS. One fundamental limitation of a purely design-based approach is the absence of controls for factors that influence detection of birds at survey sites. We show that failure to model observer effects in survey data leads to substantial bias in estimation of population trends from BBS data for the 20 species that Bart et al. (2003) used as the basis of their simulations. Finally, we note that the simulations presented in Bart et al. (2003) do not provide a useful evaluation of their proposed method, nor do they provide a valid comparison to the estimating- equations alternative they consider.

Development of the Galaxy Chronic Obstructive Pulmonary Disease (COPD) Model Using Data from ECLIPSE: Internal Validation of a Linked-Equations Cohort Model.

PubMed

Briggs, Andrew H; Baker, Timothy; Risebrough, Nancy A; Chambers, Mike; Gonzalez-McQuire, Sebastian; Ismaila, Afisi S; Exuzides, Alex; Colby, Chris; Tabberer, Maggie; Muellerova, Hana; Locantore, Nicholas; Rutten van Mölken, Maureen P M H; Lomas, David A

2017-05-01

The recent joint International Society for Pharmacoeconomics and Outcomes Research / Society for Medical Decision Making Modeling Good Research Practices Task Force emphasized the importance of conceptualizing and validating models. We report a new model of chronic obstructive pulmonary disease (COPD) (part of the Galaxy project) founded on a conceptual model, implemented using a novel linked-equation approach, and internally validated. An expert panel developed a conceptual model including causal relationships between disease attributes, progression, and final outcomes. Risk equations describing these relationships were estimated using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study, with costs estimated from the TOwards a Revolution in COPD Health (TORCH) study. Implementation as a linked-equation model enabled direct estimation of health service costs and quality-adjusted life years (QALYs) for COPD patients over their lifetimes. Internal validation compared 3 years of predicted cohort experience with ECLIPSE results. At 3 years, the Galaxy COPD model predictions of annual exacerbation rate and annual decline in forced expiratory volume in 1 second fell within the ECLIPSE data confidence limits, although 3-year overall survival was outside the observed confidence limits. Projections of the risk equations over time permitted extrapolation to patient lifetimes. Averaging the predicted cost/QALY outcomes for the different patients within the ECLIPSE cohort gives an estimated lifetime cost of £25,214 (undiscounted)/£20,318 (discounted) and lifetime QALYs of 6.45 (undiscounted/5.24 [discounted]) per ECLIPSE patient. A new form of model for COPD was conceptualized, implemented, and internally validated, based on a series of linked equations using epidemiological data (ECLIPSE) and cost data (TORCH). This Galaxy model predicts COPD outcomes from treatment effects on disease attributes such as lung function, exacerbations, symptoms, or exercise capacity; further external validation is required.

Subregional Nowcasts of Seasonal Influenza Using Search Trends.

PubMed

Kandula, Sasikiran; Hsu, Daniel; Shaman, Jeffrey

2017-11-06

Limiting the adverse effects of seasonal influenza outbreaks at state or city level requires close monitoring of localized outbreaks and reliable forecasts of their progression. Whereas forecasting models for influenza or influenza-like illness (ILI) are becoming increasingly available, their applicability to localized outbreaks is limited by the nonavailability of real-time observations of the current outbreak state at local scales. Surveillance data collected by various health departments are widely accepted as the reference standard for estimating the state of outbreaks, and in the absence of surveillance data, nowcast proxies built using Web-based activities such as search engine queries, tweets, and access of health-related webpages can be useful. Nowcast estimates of state and municipal ILI were previously published by Google Flu Trends (GFT); however, validations of these estimates were seldom reported. The aim of this study was to develop and validate models to nowcast ILI at subregional geographic scales. We built nowcast models based on autoregressive (autoregressive integrated moving average; ARIMA) and supervised regression methods (Random forests) at the US state level using regional weighted ILI and Web-based search activity derived from Google's Extended Trends application programming interface. We validated the performance of these methods using actual surveillance data for the 50 states across six seasons. We also built state-level nowcast models using state-level estimates of ILI and compared the accuracy of these estimates with the estimates of the regional models extrapolated to the state level and with the nowcast estimates published by GFT. Models built using regional ILI extrapolated to state level had a median correlation of 0.84 (interquartile range: 0.74-0.91) and a median root mean square error (RMSE) of 1.01 (IQR: 0.74-1.50), with noticeable variability across seasons and by state population size. Model forms that hypothesize the availability of timely state-level surveillance data show significantly lower errors of 0.83 (0.55-0.23). Compared with GFT, the latter model forms have lower errors but also lower correlation. These results suggest that the proposed methods may be an alternative to the discontinued GFT and that further improvements in the quality of subregional nowcasts may require increased access to more finely resolved surveillance data. ©Sasikiran Kandula, Daniel Hsu, Jeffrey Shaman. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 06.11.2017.

Validation and application of Acoustic Mapping Velocimetry

NASA Astrophysics Data System (ADS)

Baranya, Sandor; Muste, Marian

2016-04-01

The goal of this paper is to introduce a novel methodology to estimate bedload transport in rivers based on an improved bedform tracking procedure. The measurement technique combines components and processing protocols from two contemporary nonintrusive instruments: acoustic and image-based. The bedform mapping is conducted with acoustic surveys while the estimation of the velocity of the bedforms is obtained with processing techniques pertaining to image-based velocimetry. The technique is therefore called Acoustic Mapping Velocimetry (AMV). The implementation of this technique produces a whole-field velocity map associated with the multi-directional bedform movement. Based on the calculated two-dimensional bedform migration velocity field, the bedload transport estimation is done using the Exner equation. A proof-of-concept experiment was performed to validate the AMV based bedload estimation in a laboratory flume at IIHR-Hydroscience & Engineering (IIHR). The bedform migration was analysed at three different flow discharges. Repeated bed geometry mapping, using a multiple transducer array (MTA), provided acoustic maps, which were post-processed with a particle image velocimetry (PIV) method. Bedload transport rates were calculated along longitudinal sections using the streamwise components of the bedform velocity vectors and the measured bedform heights. The bulk transport rates were compared with the results from concurrent direct physical samplings and acceptable agreement was found. As a first field implementation of the AMV an attempt was made to estimate bedload transport for a section of the Ohio river in the United States, where bed geometry maps, resulted by repeated multibeam echo sounder (MBES) surveys, served as input data. Cross-sectional distributions of bedload transport rates from the AMV based method were compared with the ones obtained from another non-intrusive technique (due to the lack of direct samplings), ISSDOTv2, developed by the US Army Corps of Engineers. The good agreement between the results from the two different methods is encouraging and suggests further field tests in varying hydro-morphological situations.

The development of an estimation model for energy expenditure during water walking by acceleration and walking speed.

PubMed

Kaneda, Koichi; Ohgi, Yuji; Tanaka, Chiaki; Burkett, Brendan

2014-01-01

The aim of this study was to develop an estimation equation for energy expenditure during water walking based on the acceleration and walking speed. Cross-validation study. Fifty participants, males (n=29, age: 27-73) and females (n=21, age: 33-70) volunteered for this study. Based on their physical condition water walking was conducted at three self-selected walking speeds from a range of: 20, 25, 30, 35 and 40 m/min. Energy expenditure during each trial was calculated. During water walking, an accelerometer was attached to the occipital region and recorded three-dimensional accelerations at 100 Hz. A stopwatch was used for timing the participant's walking speed. The estimation model for energy expenditure included three components; (i) resting metabolic rate, (ii) internal energy expenditure for moving participants' body, and (iii) external energy expenditure due to water drag force. When comparing the measured and estimated energy expenditure with the acceleration data being the third component of the estimation model, high correlation coefficients were found in both male (r=0.73) and female (r=0.77) groups. When walking speeds were applied to the third component of the model, higher correlation coefficients were found (r=0.82 in male and r=0.88 in female). Good agreements of the developed estimation model were found in both methods, regardless of gender. This study developed a valid estimation model for energy expenditure during water walking by using head acceleration and walking speed. Copyright © 2013 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Verification of Satellite Rainfall Estimates from the Tropical Rainfall Measuring Mission over Ground Validation Sites

NASA Astrophysics Data System (ADS)

Fisher, B. L.; Wolff, D. B.; Silberstein, D. S.; Marks, D. M.; Pippitt, J. L.

2007-12-01

The Tropical Rainfall Measuring Mission's (TRMM) Ground Validation (GV) Program was originally established with the principal long-term goal of determining the random errors and systematic biases stemming from the application of the TRMM rainfall algorithms. The GV Program has been structured around two validation strategies: 1) determining the quantitative accuracy of the integrated monthly rainfall products at GV regional sites over large areas of about 500 km2 using integrated ground measurements and 2) evaluating the instantaneous satellite and GV rain rate statistics at spatio-temporal scales compatible with the satellite sensor resolution (Simpson et al. 1988, Thiele 1988). The GV Program has continued to evolve since the launch of the TRMM satellite on November 27, 1997. This presentation will discuss current GV methods of validating TRMM operational rain products in conjunction with ongoing research. The challenge facing TRMM GV has been how to best utilize rain information from the GV system to infer the random and systematic error characteristics of the satellite rain estimates. A fundamental problem of validating space-borne rain estimates is that the true mean areal rainfall is an ideal, scale-dependent parameter that cannot be directly measured. Empirical validation uses ground-based rain estimates to determine the error characteristics of the satellite-inferred rain estimates, but ground estimates also incur measurement errors and contribute to the error covariance. Furthermore, sampling errors, associated with the discrete, discontinuous temporal sampling by the rain sensors aboard the TRMM satellite, become statistically entangled in the monthly estimates. Sampling errors complicate the task of linking biases in the rain retrievals to the physics of the satellite algorithms. The TRMM Satellite Validation Office (TSVO) has made key progress towards effective satellite validation. For disentangling the sampling and retrieval errors, TSVO has developed and applied a methodology that statistically separates the two error sources. Using TRMM monthly estimates and high-resolution radar and gauge data, this method has been used to estimate sampling and retrieval error budgets over GV sites. More recently, a multi- year data set of instantaneous rain rates from the TRMM microwave imager (TMI), the precipitation radar (PR), and the combined algorithm was spatio-temporally matched and inter-compared to GV radar rain rates collected during satellite overpasses of select GV sites at the scale of the TMI footprint. The analysis provided a more direct probe of the satellite rain algorithms using ground data as an empirical reference. TSVO has also made significant advances in radar quality control through the development of the Relative Calibration Adjustment (RCA) technique. The RCA is currently being used to provide a long-term record of radar calibration for the radar at Kwajalein, a strategically important GV site in the tropical Pacific. The RCA technique has revealed previously undetected alterations in the radar sensitivity due to engineering changes (e.g., system modifications, antenna offsets, alterations of the receiver, or the data processor), making possible the correction of the radar rainfall measurements and ensuring the integrity of nearly a decade of TRMM GV observations and resources.

Derivation and Validation of Supraglacial Lake Volumes on the Greenland Ice Sheet from High-Resolution Satellite Imagery

NASA Technical Reports Server (NTRS)

Moussavi, Mahsa S.; Abdalati, Waleed; Pope, Allen; Scambos, Ted; Tedesco, Marco; MacFerrin, Michael; Grigsby, Shane

2016-01-01

Supraglacial meltwater lakes on the western Greenland Ice Sheet (GrIS) are critical components of its surface hydrology and surface mass balance, and they also affect its ice dynamics. Estimates of lake volume, however, are limited by the availability of in situ measurements of water depth,which in turn also limits the assessment of remotely sensed lake depths. Given the logistical difficulty of collecting physical bathymetric measurements, methods relying upon in situ data are generally restricted to small areas and thus their application to largescale studies is difficult to validate. Here, we produce and validate spaceborne estimates of supraglacial lake volumes across a relatively large area (1250 km(exp 2) of west Greenland's ablation region using data acquired by the WorldView-2 (WV-2) sensor, making use of both its stereo-imaging capability and its meter-scale resolution. We employ spectrally-derived depth retrieval models, which are either based on absolute reflectance (single-channel model) or a ratio of spectral reflectances in two bands (dual-channel model). These models are calibrated by usingWV-2multispectral imagery acquired early in the melt season and depth measurements from a high resolutionWV-2 DEM over the same lake basins when devoid of water. The calibrated models are then validated with different lakes in the area, for which we determined depths. Lake depth estimates based on measurements recorded in WV-2's blue (450-510 nm), green (510-580 nm), and red (630-690 nm) bands and dual-channel modes (blue/green, blue/red, and green/red band combinations) had near-zero bias, an average root-mean-squared deviation of 0.4 m (relative to post-drainage DEMs), and an average volumetric error of b1%. The approach outlined in this study - image-based calibration of depth-retrieval models - significantly improves spaceborne supraglacial bathymetry retrievals, which are completely independent from in situ measurements.

Runoff load estimation of particulate and dissolved nitrogen in Lake Inba watershed using continuous monitoring data on turbidity and electric conductivity.

PubMed

Kim, J; Nagano, Y; Furumai, H

2012-01-01

Easy-to-measure surrogate parameters for water quality indicators are needed for real time monitoring as well as for generating data for model calibration and validation. In this study, a novel linear regression model for estimating total nitrogen (TN) based on two surrogate parameters is proposed based on evaluation of pollutant loads flowing into a eutrophic lake. Based on their runoff characteristics during wet weather, electric conductivity (EC) and turbidity were selected as surrogates for particulate nitrogen (PN) and dissolved nitrogen (DN), respectively. Strong linear relationships were established between PN and turbidity and DN and EC, and both models subsequently combined for estimation of TN. This model was evaluated by comparison of estimated and observed TN runoff loads during rainfall events. This analysis showed that turbidity and EC are viable surrogates for PN and DN, respectively, and that the linear regression model for TN concentration was successful in estimating TN runoff loads during rainfall events and also under dry weather conditions.

Validation of Regression-Based Myogenic Correction Techniques for Scalp and Source-Localized EEG

PubMed Central

McMenamin, Brenton W.; Shackman, Alexander J.; Maxwell, Jeffrey S.; Greischar, Lawrence L.; Davidson, Richard J.

2008-01-01

EEG and EEG source-estimation are susceptible to electromyographic artifacts (EMG) generated by the cranial muscles. EMG can mask genuine effects or masquerade as a legitimate effect - even in low frequencies, such as alpha (8–13Hz). Although regression-based correction has been used previously, only cursory attempts at validation exist and the utility for source-localized data is unknown. To address this, EEG was recorded from 17 participants while neurogenic and myogenic activity were factorially varied. We assessed the sensitivity and specificity of four regression-based techniques: between-subjects, between-subjects using difference-scores, within-subjects condition-wise, and within-subject epoch-wise on the scalp and in data modeled using the LORETA algorithm. Although within-subject epoch-wise showed superior performance on the scalp, no technique succeeded in the source-space. Aside from validating the novel epoch-wise methods on the scalp, we highlight methods requiring further development. PMID:19298626

Validation of SMAP data using Cosmic-ray Neutron Probes during the SMAPVEX16-IA Campaign

NASA Astrophysics Data System (ADS)

Russell, M. V.

2016-12-01

Global trends in consumptive water-use indicate a growing and unsustainable reliance on water resources. Each year it is estimated that 60 percent of water used for agriculture is wasted through inadequate water conservation, losses in distribution, and inappropriate times and rates of irrigation. Satellite remote sensing offers a variety of water balance datasets (precipitation, evapotranspiration, soil moisture, groundwater storage) to increase the water use efficiency in agricultural systems. In this work, we aim to validate the Soil Moisture Active Passive (SMAP) soil moisture product using the ground based cosmic-ray neutron probe (CRNP) for estimating field scale soil moisture at intermediate spatial scales as part of SMAPVEX16-IA experiment. Typical SMAP calibration and validation has been done using a combination of direct gravimetric sampling and in-situ soil moisture point observations. Although these measurements provide accurate data, it is time consuming and labor intensive to collect data over a 36 by 36 km SMAP pixel. Through a joint effort with rovers provided by the US Army Corps of Engineers and University of Nebraska-Lincoln, we are able to cover the domain in 7 hours. Data from both rovers was combined in order to produce a 1, 3, 9 and 36 km resolution product on the day of 12 SMAP overpasses in May and August 2016. Here we will describe basic QAQC procedures for estimating soil moisture from the dual rover experiment. This will include discussion about calibration, validation, and accounting for conditions such as variable road type and growing vegetation. Lastly, we will compare the calibrated rover and SMAP products. If the products are highly correlated the ground based rovers offer a strategy for collecting finer resolution products that may be used in future downscaling efforts in support of high resolution Land Surface Modeling.

Validation of biomarkers of food intake-critical assessment of candidate biomarkers.

PubMed

Dragsted, L O; Gao, Q; Scalbert, A; Vergères, G; Kolehmainen, M; Manach, C; Brennan, L; Afman, L A; Wishart, D S; Andres Lacueva, C; Garcia-Aloy, M; Verhagen, H; Feskens, E J M; Praticò, G

2018-01-01

Biomarkers of food intake (BFIs) are a promising tool for limiting misclassification in nutrition research where more subjective dietary assessment instruments are used. They may also be used to assess compliance to dietary guidelines or to a dietary intervention. Biomarkers therefore hold promise for direct and objective measurement of food intake. However, the number of comprehensively validated biomarkers of food intake is limited to just a few. Many new candidate biomarkers emerge from metabolic profiling studies and from advances in food chemistry. Furthermore, candidate food intake biomarkers may also be identified based on extensive literature reviews such as described in the guidelines for Biomarker of Food Intake Reviews (BFIRev). To systematically and critically assess the validity of candidate biomarkers of food intake, it is necessary to outline and streamline an optimal and reproducible validation process. A consensus-based procedure was used to provide and evaluate a set of the most important criteria for systematic validation of BFIs. As a result, a validation procedure was developed including eight criteria, plausibility, dose-response, time-response, robustness, reliability, stability, analytical performance, and inter-laboratory reproducibility. The validation has a dual purpose: (1) to estimate the current level of validation of candidate biomarkers of food intake based on an objective and systematic approach and (2) to pinpoint which additional studies are needed to provide full validation of each candidate biomarker of food intake. This position paper on biomarker of food intake validation outlines the second step of the BFIRev procedure but may also be used as such for validation of new candidate biomarkers identified, e.g., in food metabolomic studies.

Spatial regression test for ensuring temperature data quality in southern Spain

NASA Astrophysics Data System (ADS)

Estévez, J.; Gavilán, P.; García-Marín, A. P.

2018-01-01

Quality assurance of meteorological data is crucial for ensuring the reliability of applications and models that use such data as input variables, especially in the field of environmental sciences. Spatial validation of meteorological data is based on the application of quality control procedures using data from neighbouring stations to assess the validity of data from a candidate station (the station of interest). These kinds of tests, which are referred to in the literature as spatial consistency tests, take data from neighbouring stations in order to estimate the corresponding measurement at the candidate station. These estimations can be made by weighting values according to the distance between the stations or to the coefficient of correlation, among other methods. The test applied in this study relies on statistical decision-making and uses a weighting based on the standard error of the estimate. This paper summarizes the results of the application of this test to maximum, minimum and mean temperature data from the Agroclimatic Information Network of Andalusia (southern Spain). This quality control procedure includes a decision based on a factor f, the fraction of potential outliers for each station across the region. Using GIS techniques, the geographic distribution of the errors detected has been also analysed. Finally, the performance of the test was assessed by evaluating its effectiveness in detecting known errors.

Validation and evaluation of model-based crosstalk compensation method in simultaneous /sup 99m/Tc stress and /sup 201/Tl rest myocardial perfusion SPECT

NASA Astrophysics Data System (ADS)

Song, X.; Frey, E. C.; Wang, W. T.; Du, Y.; Tsui, B. M. W.

2004-02-01

Simultaneous acquisition of /sup 99m/Tc stress and /sup 201/Tl rest myocardial perfusion SPECT has several potential advantages, but the image quality is degraded by crosstalk between the Tc and Tl data. We have previously developed a crosstalk model that includes estimates of the downscatter and Pb X-ray for use in crosstalk compensation. In this work, we validated the model by comparing the crosstalk from /sup 99m/Tc to the Tl window calculated using a combination of the SimSET-MCNP Monte Carlo simulation codes. We also evaluated the model-based crosstalk compensation method using both simulated data from the 3-D MCAT phantom and experimental data from a physical phantom with a myocardial defect. In these studies, the Tl distributions were reconstructed from crosstalk contaminated data without crosstalk compensation, with compensation using the model-based crosstalk estimate, and with compensation using the known true crosstalk, and were compared with the Tl distribution reconstructed from uncontaminated Tl data. Results show that the model gave good estimates of both the downscatter photons and Pb X-rays in the simultaneous dual-isotopes myocardial perfusion SPECT. The model-based compensation method provided image quality that was significantly improved as compared to no compensation and was very close to that from the separate acquisition.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

PubMed

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force.

Multisite evaluation of APEX for water quality: II. Regional parameterization

USDA-ARS?s Scientific Manuscript database

Phosphorus (P) index assessment requires independent estimates of long-term average annual P loss from multiple locations, management practices, soils, and landscape positions. Because currently available measured data are insufficient, calibrated and validated process-based models have been propos...

Sector-Based Detection for Hands-Free Speech Enhancement in Cars

NASA Astrophysics Data System (ADS)

Lathoud, Guillaume; Bourgeois, Julien; Freudenberger, Jürgen

2006-12-01

Adaptation control of beamforming interference cancellation techniques is investigated for in-car speech acquisition. Two efficient adaptation control methods are proposed that avoid target cancellation. The "implicit" method varies the step-size continuously, based on the filtered output signal. The "explicit" method decides in a binary manner whether to adapt or not, based on a novel estimate of target and interference energies. It estimates the average delay-sum power within a volume of space, for the same cost as the classical delay-sum. Experiments on real in-car data validate both methods, including a case with[InlineEquation not available: see fulltext.] km/h background road noise.

A physics based method for combining multiple anatomy models with application to medical simulation.

PubMed

Zhu, Yanong; Magee, Derek; Ratnalingam, Rishya; Kessel, David

2009-01-01

We present a physics based approach to the construction of anatomy models by combining components from different sources; different image modalities, protocols, and patients. Given an initial anatomy, a mass-spring model is generated which mimics the physical properties of the solid anatomy components. This helps maintain valid spatial relationships between the components, as well as the validity of their shapes. Combination can be either replacing/modifying an existing component, or inserting a new component. The external forces that deform the model components to fit the new shape are estimated from Gradient Vector Flow and Distance Transform maps. We demonstrate the applicability and validity of the described approach in the area of medical simulation, by showing the processes of non-rigid surface alignment, component replacement, and component insertion.

Retrieval of an available water-based soil moisture proxy from thermal infrared remote sensing. Part I: Methodology and validation

USDA-ARS?s Scientific Manuscript database

A retrieval of soil moisture is proposed using surface flux estimates from satellite-based thermal infrared (TIR) imagery and the Atmosphere-Land-Exchange-Inversion (ALEXI) model. The ability of ALEXI to provide valuable information about the partitioning of the surface energy budget, which can be l...

Error Estimation and Uncertainty Propagation in Computational Fluid Mechanics

NASA Technical Reports Server (NTRS)

Zhu, J. Z.; He, Guowei; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

Numerical simulation has now become an integral part of engineering design process. Critical design decisions are routinely made based on the simulation results and conclusions. Verification and validation of the reliability of the numerical simulation is therefore vitally important in the engineering design processes. We propose to develop theories and methodologies that can automatically provide quantitative information about the reliability of the numerical simulation by estimating numerical approximation error, computational model induced errors and the uncertainties contained in the mathematical models so that the reliability of the numerical simulation can be verified and validated. We also propose to develop and implement methodologies and techniques that can control the error and uncertainty during the numerical simulation so that the reliability of the numerical simulation can be improved.

Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging.

PubMed

Zhang, Shuanghui; Liu, Yongxiang; Li, Xiang; Bi, Guoan

2016-04-28

This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achieve performance improvement on sparse representation. The logarithmic Laplacian prior is used for ISAR imaging within the Bayesian framework to achieve better focused radar image. In the proposed method of ISAR imaging, the phase errors are jointly estimated based on the minimum entropy criterion to accomplish autofocusing. The maximum a posterior (MAP) estimation and the maximum likelihood estimation (MLE) are utilized to estimate the model parameters to avoid manually tuning process. Additionally, the fast Fourier Transform (FFT) and Hadamard product are used to minimize the required computational efficiency. Experimental results based on both simulated and measured data validate that the proposed algorithm outperforms the traditional sparse ISAR imaging algorithms in terms of resolution improvement and noise suppression.

Parametric Model Based On Imputations Techniques for Partly Interval Censored Data

NASA Astrophysics Data System (ADS)

Zyoud, Abdallah; Elfaki, F. A. M.; Hrairi, Meftah

2017-12-01

The term ‘survival analysis’ has been used in a broad sense to describe collection of statistical procedures for data analysis. In this case, outcome variable of interest is time until an event occurs where the time to failure of a specific experimental unit might be censored which can be right, left, interval, and Partly Interval Censored data (PIC). In this paper, analysis of this model was conducted based on parametric Cox model via PIC data. Moreover, several imputation techniques were used, which are: midpoint, left & right point, random, mean, and median. Maximum likelihood estimate was considered to obtain the estimated survival function. These estimations were then compared with the existing model, such as: Turnbull and Cox model based on clinical trial data (breast cancer data), for which it showed the validity of the proposed model. Result of data set indicated that the parametric of Cox model proved to be more superior in terms of estimation of survival functions, likelihood ratio tests, and their P-values. Moreover, based on imputation techniques; the midpoint, random, mean, and median showed better results with respect to the estimation of survival function.

Monte-Carlo-based phase retardation estimator for polarization sensitive optical coherence tomography

NASA Astrophysics Data System (ADS)

Duan, Lian; Makita, Shuichi; Yamanari, Masahiro; Lim, Yiheng; Yasuno, Yoshiaki

2011-08-01

A Monte-Carlo-based phase retardation estimator is developed to correct the systematic error in phase retardation measurement by polarization sensitive optical coherence tomography (PS-OCT). Recent research has revealed that the phase retardation measured by PS-OCT has a distribution that is neither symmetric nor centered at the true value. Hence, a standard mean estimator gives us erroneous estimations of phase retardation, and it degrades the performance of PS-OCT for quantitative assessment. In this paper, the noise property in phase retardation is investigated in detail by Monte-Carlo simulation and experiments. A distribution transform function is designed to eliminate the systematic error by using the result of the Monte-Carlo simulation. This distribution transformation is followed by a mean estimator. This process provides a significantly better estimation of phase retardation than a standard mean estimator. This method is validated both by numerical simulations and experiments. The application of this method to in vitro and in vivo biological samples is also demonstrated.

Strain Rate Tensor Estimation in Cine Cardiac MRI Based on Elastic Image Registration

NASA Astrophysics Data System (ADS)

Sánchez-Ferrero, Gonzalo Vegas; Vega, Antonio Tristán; Grande, Lucilio Cordero; de La Higuera, Pablo Casaseca; Fernández, Santiago Aja; Fernández, Marcos Martín; López, Carlos Alberola

In this work we propose an alternative method to estimate and visualize the Strain Rate Tensor (SRT) in Magnetic Resonance Images (MRI) when Phase Contrast MRI (PCMRI) and Tagged MRI (TMRI) are not available. This alternative is based on image processing techniques. Concretely, image registration algorithms are used to estimate the movement of the myocardium at each point. Additionally, a consistency checking method is presented to validate the accuracy of the estimates when no golden standard is available. Results prove that the consistency checking method provides an upper bound of the mean squared error of the estimate. Our experiments with real data show that the registration algorithm provides a useful deformation field to estimate the SRT fields. A classification between regional normal and dysfunctional contraction patterns, as compared with experts diagnosis, points out that the parameters extracted from the estimated SRT can represent these patterns. Additionally, a scheme for visualizing and analyzing the local behavior of the SRT field is presented.

A Particle Smoother with Sequential Importance Resampling for soil hydraulic parameter estimation: A lysimeter experiment

NASA Astrophysics Data System (ADS)

Montzka, Carsten; Hendricks Franssen, Harrie-Jan; Moradkhani, Hamid; Pütz, Thomas; Han, Xujun; Vereecken, Harry

2013-04-01

An adequate description of soil hydraulic properties is essential for a good performance of hydrological forecasts. So far, several studies showed that data assimilation could reduce the parameter uncertainty by considering soil moisture observations. However, these observations and also the model forcings were recorded with a specific measurement error. It seems a logical step to base state updating and parameter estimation on observations made at multiple time steps, in order to reduce the influence of outliers at single time steps given measurement errors and unknown model forcings. Such outliers could result in erroneous state estimation as well as inadequate parameters. This has been one of the reasons to use a smoothing technique as implemented for Bayesian data assimilation methods such as the Ensemble Kalman Filter (i.e. Ensemble Kalman Smoother). Recently, an ensemble-based smoother has been developed for state update with a SIR particle filter. However, this method has not been used for dual state-parameter estimation. In this contribution we present a Particle Smoother with sequentially smoothing of particle weights for state and parameter resampling within a time window as opposed to the single time step data assimilation used in filtering techniques. This can be seen as an intermediate variant between a parameter estimation technique using global optimization with estimation of single parameter sets valid for the whole period, and sequential Monte Carlo techniques with estimation of parameter sets evolving from one time step to another. The aims are i) to improve the forecast of evaporation and groundwater recharge by estimating hydraulic parameters, and ii) to reduce the impact of single erroneous model inputs/observations by a smoothing method. In order to validate the performance of the proposed method in a real world application, the experiment is conducted in a lysimeter environment.

Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.

PubMed

Engemann, Denis A; Gramfort, Alexandre

2015-03-01

Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The rationale for such models is that the signals can be modeled by a zero mean Gaussian distribution. While maximizing the Gaussian likelihood seems natural, it leads to a covariance estimate known as empirical covariance (EC). It turns out that the EC is a poor estimate of the true covariance when the number of samples is small. To address this issue the estimation needs to be regularized. The most common approach downweights off-diagonal coefficients, while more advanced regularization methods are based on shrinkage techniques or generative models with low rank assumptions: probabilistic PCA (PPCA) and factor analysis (FA). Using cross-validation all of these models can be tuned and compared based on Gaussian likelihood computed on unseen data. We investigated these models on simulations, one electroencephalography (EEG) dataset as well as magnetoencephalography (MEG) datasets from the most common MEG systems. First, our results demonstrate that different models can be the best, depending on the number of samples, heterogeneity of sensor types and noise properties. Second, we show that the models tuned by cross-validation are superior to models with hand-selected regularization. Hence, we propose an automated solution to the often overlooked problem of covariance estimation of M/EEG signals. The relevance of the procedure is demonstrated here for spatial whitening and source localization of MEG signals. Copyright © 2015 Elsevier Inc. All rights reserved.

Validation of High Wind Retrievals from the Cyclone Global Navigation Satellite System (CYGNSS) Mission

NASA Astrophysics Data System (ADS)

McKague, D. S.; Ruf, C. S.; Balasubramaniam, R.; Clarizia, M. P.

2017-12-01

The Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in December of 2016, provides all-weather observations of sea surface winds. Using GPS-based bistatic reflectometry, the CYGNSS satellites can estimate sea surface winds even through a hurricane eye wall. This, combined with the high temporal resolution of the CYGNSS constellation (median revisit time of 2.8 hours), yields unprecedented ability to estimate hurricane strength winds. While there are a number of other sources of sea surface wind estimates, such as buoys, dropsondes, passive and active microwave from aircraft and satellite, and models, the combination of all-weather, high accuracy, short revisit time, high spatial coverage, and continuous operation of the CYGNSS mission enables significant advances in the understanding, monitoring, and prediction of cyclones. Validating CYGNSS wind retrievals over the bulk of the global wind speed distribution, which peaks at around 7 meters per second, is relatively straight-forward, requiring spatial-temporal matching of observations with independent sources (such as those mentioned above). Validating CYGNSS wind retrievals for "high" winds (> 20 meters per second), though, is problematic. Such winds occur only in intense storms. While infrequent, making validation opportunities also infrequent and problematic due to their intense nature, such storms are important to study because of the high potential for damage and loss of life. This presentation will describe the efforts of the CYGNSS Calibration/Validation team to gather measurements of high sea surface winds for development and validation of the CYGNSS geophysical model function (GMF), which forms the basis of retrieving winds from CYGNSS observations. The bulk of these observations come from buoy measurements as well as aircraft ("hurricane hunter") measurements from passive microwave and dropsondes. These data are matched in space and time to CYGNSS observations for training of the CYGNSS GMF and an independent set is used for validation of the resulting high wind speed retrievals. In addition to describing the general validation process, results from matchups over the 2017 hurricane season will be presented.

Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data.

PubMed

Kloog, Itai; Sorek-Hamer, Meytar; Lyapustin, Alexei; Coull, Brent; Wang, Yujie; Just, Allan C; Schwartz, Joel; Broday, David M

2015-12-01

Estimates of exposure to PM 2.5 are often derived from geographic characteristics based on land-use regression or from a limited number of fixed ground monitors. Remote sensing advances have integrated these approaches with satellite-based measures of aerosol optical depth (AOD), which is spatially and temporally resolved, allowing greater coverage for PM 2.5 estimations. Israel is situated in a complex geo-climatic region with contrasting geographic and weather patterns, including both dark and bright surfaces within a relatively small area. Our goal was to examine the use of MODIS-based MAIAC data in Israel, and to explore the reliability of predicted PM 2.5 and PM 10 at a high spatiotemporal resolution. We applied a three stage process, including a daily calibration method based on a mixed effects model, to predict ground PM 2.5 and PM 10 over Israel. We later constructed daily predictions across Israel for 2003-2013 using spatial and temporal smoothing, to estimate AOD when satellite data were missing. Good model performance was achieved, with out-of-sample cross validation R 2 values of 0.79 and 0.72 for PM 10 and PM 2.5 , respectively. Model predictions had little bias, with cross-validated slopes (predicted vs. observed) of 0.99 for both the PM 2.5 and PM 10 models. To our knowledge, this is the first study that utilizes high resolution 1km MAIAC AOD retrievals for PM prediction while accounting for geo-climate complexities, such as experienced in Israel. This novel model allowed the reconstruction of long- and short-term spatially resolved exposure to PM 2.5 and PM 10 in Israel, which could be used in the future for epidemiological studies.

Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data

PubMed Central

Kloog, Itai; Sorek-Hamer, Meytar; Lyapustin, Alexei; Coull, Brent; Wang, Yujie; Just, Allan C.; Schwartz, Joel; Broday, David M.

2017-01-01

Estimates of exposure to PM2.5 are often derived from geographic characteristics based on land-use regression or from a limited number of fixed ground monitors. Remote sensing advances have integrated these approaches with satellite-based measures of aerosol optical depth (AOD), which is spatially and temporally resolved, allowing greater coverage for PM2.5 estimations. Israel is situated in a complex geo-climatic region with contrasting geographic and weather patterns, including both dark and bright surfaces within a relatively small area. Our goal was to examine the use of MODIS-based MAIAC data in Israel, and to explore the reliability of predicted PM2.5 and PM10 at a high spatiotemporal resolution. We applied a three stage process, including a daily calibration method based on a mixed effects model, to predict ground PM2.5 and PM10 over Israel. We later constructed daily predictions across Israel for 2003–2013 using spatial and temporal smoothing, to estimate AOD when satellite data were missing. Good model performance was achieved, with out-of-sample cross validation R2 values of 0.79 and 0.72 for PM10 and PM2.5, respectively. Model predictions had little bias, with cross-validated slopes (predicted vs. observed) of 0.99 for both the PM2.5 and PM10 models. To our knowledge, this is the first study that utilizes high resolution 1km MAIAC AOD retrievals for PM prediction while accounting for geo-climate complexities, such as experienced in Israel. This novel model allowed the reconstruction of long- and short-term spatially resolved exposure to PM2.5 and PM10 in Israel, which could be used in the future for epidemiological studies. PMID:28966551

Considerations Underlying the Use of Mixed Group Validation

ERIC Educational Resources Information Center

Jewsbury, Paul A.; Bowden, Stephen C.

2013-01-01

Mixed Group Validation (MGV) is an approach for estimating the diagnostic accuracy of tests. MGV is a promising alternative to the more commonly used Known Groups Validation (KGV) approach for estimating diagnostic accuracy. The advantage of MGV lies in the fact that the approach does not require a perfect external validity criterion or gold…

Adequacy of satellite derived rainfall data for stream flow modeling

USGS Publications Warehouse

Artan, G.; Gadain, Hussein; Smith, Jodie; Asante, Kwasi; Bandaragoda, C.J.; Verdin, J.P.

2007-01-01

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. ?? Springer Science+Business Media, Inc. 2007.

Using groundwater levels to estimate recharge

USGS Publications Warehouse

Healy, R.W.; Cook, P.G.

2002-01-01

Accurate estimation of groundwater recharge is extremely important for proper management of groundwater systems. Many different approaches exist for estimating recharge. This paper presents a review of methods that are based on groundwater-level data. The water-table fluctuation method may be the most widely used technique for estimating recharge; it requires knowledge of specific yield and changes in water levels over time. Advantages of this approach include its simplicity and an insensitivity to the mechanism by which water moves through the unsaturated zone. Uncertainty in estimates generated by this method relate to the limited accuracy with which specific yield can be determined and to the extent to which assumptions inherent in the method are valid. Other methods that use water levels (mostly based on the Darcy equation) are also described. The theory underlying the methods is explained. Examples from the literature are used to illustrate applications of the different methods.

The development and validity of the Salford Gait Tool: an observation-based clinical gait assessment tool.

PubMed

Toro, Brigitte; Nester, Christopher J; Farren, Pauline C

2007-03-01

To develop the construct, content, and criterion validity of the Salford Gait Tool (SF-GT) and to evaluate agreement between gait observations using the SF-GT and kinematic gait data. Tool development and comparative evaluation. University in the United Kingdom. For designing construct and content validity, convenience samples of 10 children with hemiplegic, diplegic, and quadriplegic cerebral palsy (CP) and 152 physical therapy students and 4 physical therapists were recruited. For developing criterion validity, kinematic gait data of 13 gait clusters containing 56 children with hemiplegic, diplegic, and quadriplegic CP and 11 neurologically intact children was used. For clinical evaluation, a convenience sample of 23 pediatric physical therapists participated. We developed a sagittal plane observational gait assessment tool through a series of design, test, and redesign iterations. The tool's grading system was calibrated using kinematic gait data of 13 gait clusters and was evaluated by comparing the agreement of gait observations using the SF-GT with kinematic gait data. Criterion standard kinematic gait data. There was 58% mean agreement based on grading categories and 80% mean agreement based on degree estimations evaluated with the least significant difference method. The new SF-GT has good concurrent criterion validity.

Validity and practicability of smartphone-based photographic food records for estimating energy and nutrient intake.

PubMed

Kong, Kaimeng; Zhang, Lulu; Huang, Lisu; Tao, Yexuan

2017-05-01

Image-assisted dietary assessment methods are frequently used to record individual eating habits. This study tested the validity of a smartphone-based photographic food recording approach by comparing the results obtained with those of a weighed food record. We also assessed the practicality of the method by using it to measure the energy and nutrient intake of college students. The experiment was implemented in two phases, each lasting 2 weeks. In the first phase, a labelled menu and a photograph database were constructed. The energy and nutrient content of 31 randomly selected dishes in three different portion sizes were then estimated by the photograph-based method and compared with a weighed food record. In the second phase, we combined the smartphone-based photographic method with the WeChat smartphone application and applied this to 120 randomly selected participants to record their energy and nutrient intake. The Pearson correlation coefficients for energy, protein, fat, and carbohydrate content between the weighed and the photographic food record were 0.997, 0.936, 0.996, and 0.999, respectively. Bland-Altman plots showed good agreement between the two methods. The estimated protein, fat, and carbohydrate intake by participants was in accordance with values in the Chinese Residents' Nutrition and Chronic Disease report (2015). Participants expressed satisfaction with the new approach and the compliance rate was 97.5%. The smartphone-based photographic dietary assessment method combined with the WeChat instant messaging application was effective and practical for use by young people.

SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

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

Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu

Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT,more » status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation.« less

Development and validation of a self-administered questionnaire to estimate the distance and mode of children's travel to school in urban India.

PubMed

Tetali, Shailaja; Edwards, Phil; Murthy, G V S; Roberts, I

2015-10-28

Although some 300 million Indian children travel to school every day, little is known about how they get there. This information is important for transport planners and public health authorities. This paper presents the development of a self-administered questionnaire and examines its reliability and validity in estimating distance and mode of travel to school in a low resource urban setting. We developed a questionnaire on children's travel to school. We assessed test re-test reliability by repeating the questionnaire one week later (n = 61). The questionnaire was improved and re-tested (n = 68). We examined the convergent validity of distance estimates by comparing estimates based on the nearest landmark to children's homes with a 'gold standard' based on one-to-one interviews with children using detailed maps (n = 50). Most questions showed fair to almost perfect agreement. Questions on usual mode of travel (κ 0.73- 0.84) and road injury (κ 0.61- 0.72) were found to be more reliable than those on parental permissions (κ 0.18- 0.30), perception of safety (κ 0.00- 0.54), and physical activity (κ -0.01- 0.07). The distance estimated by the nearest landmark method was not significantly different than the in-depth method for walking , 52 m [95 % CI -32 m to 135 m], 10 % of the mean difference, and for walking and cycling combined, 65 m [95 % CI -30 m to 159 m], 11 % of the mean difference. For children who used motorized transport (excluding private school bus), the nearest landmark method under-estimated distance by an average of 325 metres [95 % CI -664 m to 1314 m], 15 % of the mean difference. A self-administered questionnaire was found to provide reliable information on the usual mode of travel to school, and road injury, in a small sample of children in Hyderabad, India. The 'nearest landmark' method can be applied in similar low-resource settings, for a reasonably accurate estimate of the distance from a child's home to school.

Estimating effectiveness of HPV vaccination against HPV infection from post-vaccination data in the absence of baseline data.

PubMed

Vänskä, Simopekka; Söderlund-Strand, Anna; Uhnoo, Ingrid; Lehtinen, Matti; Dillner, Joakim

2018-04-28

HPV vaccination programs have been introduced in large parts of the world, but monitoring of effectiveness is not routinely performed. Many countries introduced vaccination programs without establishing the baseline of HPV prevalences. We developed and validated methods to estimate protective effectiveness (PE) of vaccination from the post-vaccination data alone using references, which are invariant under HPV vaccination. Type-specific HPV prevalence data for 15-39 year-old women were collected from the pre- and post-vaccination era in a region in southern Sweden. In a region in middle Sweden, where no baseline data had been collected, only post-vaccination data was collected. The age-specific baseline prevalence of vaccine HPV types (vtHPV, HPV 6, 11, 16, 18) were reconstructed as Beta distributions from post-vaccination data by applying the reference odds ratios between the target HPV type and non-vaccine-type HPV (nvtHPV) prevalences. Older non-vaccinated age cohorts and the southern Sweden region were used as the references. The methods for baseline reconstructions were validated by computing the Bhattacharyya coefficient (BC), a measure for divergence, between reconstructed and actual observed prevalences for vaccine HPV types in Southern Sweden, and in addition, for non-vaccine types in both regions. The PE estimates among 18-21 year-old women were validated by comparing the PE estimates that were based on the reconstructed baseline prevalences against the PE estimates based on the actual baseline prevalences. In Southern Sweden the PEs against vtHPV were 52.2% (95% CI: 44.9-58.5) using the reconstructed baseline and 49.6% (43.2-55.5) using the actual baseline, with high BC 82.7% between the reconstructed and actual baseline. In the middle Sweden region where baseline data was missing, the PE was estimated at 40.5% (31.6-48.5). Protective effectiveness of HPV vaccination can be estimated from post-vaccination data alone via reconstructing the baseline using non-vaccine HPV type data. Copyright © 2018 Elsevier Ltd. All rights reserved.

The composite dynamic method as evidence for age-specific waterfowl mortality

USGS Publications Warehouse

Burnham, Kenneth P.; Anderson, David R.

1979-01-01

For the past 25 years estimation of mortality rates for waterfowl has been based almost entirely on the composite dynamic life table. We examined the specific assumptions for this method and derived a valid goodness of fit test. We performed this test on 45 data sets representing a cross section of banded sampled for various waterfowl species, geographic areas, banding periods, and age/sex classes. We found that: (1) the composite dynamic method was rejected (P <0.001) in 37 of the 45 data sets (in fact, 29 were rejected at P <0.00001) and (2) recovery and harvest rates are year-specific (a critical violation of the necessary assumptions). We conclude that the restrictive assumptions required for the composite dynamic method to produce valid estimates of mortality rates are not met in waterfowl data. Also we demonstrate that even when the required assumptions are met, the method produces very biased estimates of age-specific mortality rates. We believe the composite dynamic method should not be used in the analysis of waterfowl banding data. Furthermore, the composite dynamic method does not provide valid evidence for age-specific mortality rates in waterfowl.

Validation of the work and health interview.

PubMed

Stewart, Walter F; Ricci, Judith A; Leotta, Carol; Chee, Elsbeth

2004-01-01

Instruments that measure the impact of illness on work do not usually provide a measure that can be directly translated into lost hours or costs. We describe the validation of the Work and Health Interview (WHI), a questionnaire that provides a measure of lost productive time (LPT) from work absence and reduced performance at work. A sample (n = 67) of inbound phone call agents was recruited for the study. Validity of the WHI was assessed over a 2-week period in reference to workplace data (i.e. absence time, time away from call station and electronic continuous performance) and repeated electronic diary data (n = 48) obtained approximately eight times a day to estimate time not working (i.e. a component of reduced performance). The mean (median) missed work time estimate for any reason was 11 (8.0) and 12.9 (8.0) hours in a 2-week period from the WHI and workplace data, respectively, with a Pearson's (Spearman's) correlation of 0.84 (0.76). The diary-based mean (median) estimate of time not working while at work was 3.9 (2.8) hours compared with the WHI estimate of 5.7 (3.2) hours with a Pearson's (Spearman's) correlation of 0.19 (0.33). The 2-week estimate of total productive time from the diary was 67.2 hours compared with 67.8 hours from the WHI, with a Pearson's (Spearman's) correlation of 0.50 (0.46). At a population level, the WHI provides an accurate estimate of missed time from work and total productive time when compared with workplace and diary estimates. At an individual level, the WHI measure of total missed time, but not reduced performance time, is moderately accurate.

Implementing the undergraduate mini-CEX: a tailored approach at Southampton University.

PubMed

Hill, Faith; Kendall, Kathleen; Galbraith, Kevin; Crossley, Jim

2009-04-01

The mini-clinical evaluation exercise (mini-CEX) is widely used in the UK to assess clinical competence, but there is little evidence regarding its implementation in the undergraduate setting. This study aimed to estimate the validity and reliability of the undergraduate mini-CEX and discuss the challenges involved in its implementation. A total of 3499 mini-CEX forms were completed. Validity was assessed by estimating associations between mini-CEX score and a number of external variables, examining the internal structure of the instrument, checking competency domain response rates and profiles against expectations, and by qualitative evaluation of stakeholder interviews. Reliability was evaluated by overall reliability coefficient (R), estimation of the standard error of measurement (SEM), and from stakeholders' perceptions. Variance component analysis examined the contribution of relevant factors to students' scores. Validity was threatened by various confounding variables, including: examiner status; case complexity; attachment specialty; patient gender, and case focus. Factor analysis suggested that competency domains reflect a single latent variable. Maximum reliability can be achieved by aggregating scores over 15 encounters (R = 0.73; 95% confidence interval [CI] +/- 0.28 based on a 6-point assessment scale). Examiner stringency contributed 29% of score variation and student attachment aptitude 13%. Stakeholder interviews revealed staff development needs but the majority perceived the mini-CEX as more reliable and valid than the previous long case. The mini-CEX has good overall utility for assessing aspects of the clinical encounter in an undergraduate setting. Strengths include fidelity, wide sampling, perceived validity, and formative observation and feedback. Reliability is limited by variable examiner stringency, and validity by confounding variables, but these should be viewed within the context of overall assessment strategies.

Time Domain Tool Validation Using ARES I-X Flight Data

NASA Technical Reports Server (NTRS)

Hough, Steven; Compton, James; Hannan, Mike; Brandon, Jay

2011-01-01

The ARES I-X vehicle was launched from NASA's Kennedy Space Center (KSC) on October 28, 2009 at approximately 11:30 EDT. ARES I-X was the first test flight for NASA s ARES I launch vehicle, and it was the first non-Shuttle launch vehicle designed and flown by NASA since Saturn. The ARES I-X had a 4-segment solid rocket booster (SRB) first stage and a dummy upper stage (US) to emulate the properties of the ARES I US. During ARES I-X pre-flight modeling and analysis, six (6) independent time domain simulation tools were developed and cross validated. Each tool represents an independent implementation of a common set of models and parameters in a different simulation framework and architecture. Post flight data and reconstructed models provide the means to validate a subset of the simulations against actual flight data and to assess the accuracy of pre-flight dispersion analysis. Post flight data consists of telemetered Operational Flight Instrumentation (OFI) data primarily focused on flight computer outputs and sensor measurements as well as Best Estimated Trajectory (BET) data that estimates vehicle state information from all available measurement sources. While pre-flight models were found to provide a reasonable prediction of the vehicle flight, reconstructed models were generated to better represent and simulate the ARES I-X flight. Post flight reconstructed models include: SRB propulsion model, thrust vector bias models, mass properties, base aerodynamics, and Meteorological Estimated Trajectory (wind and atmospheric data). The result of the effort is a set of independently developed, high fidelity, time-domain simulation tools that have been cross validated and validated against flight data. This paper presents the process and results of high fidelity aerospace modeling, simulation, analysis and tool validation in the time domain.

Validity and reliability of Optojump photoelectric cells for estimating vertical jump height.

PubMed

Glatthorn, Julia F; Gouge, Sylvain; Nussbaumer, Silvio; Stauffacher, Simone; Impellizzeri, Franco M; Maffiuletti, Nicola A

2011-02-01

Vertical jump is one of the most prevalent acts performed in several sport activities. It is therefore important to ensure that the measurements of vertical jump height made as a part of research or athlete support work have adequate validity and reliability. The aim of this study was to evaluate concurrent validity and reliability of the Optojump photocell system (Microgate, Bolzano, Italy) with force plate measurements for estimating vertical jump height. Twenty subjects were asked to perform maximal squat jumps and countermovement jumps, and flight time-derived jump heights obtained by the force plate were compared with those provided by Optojump, to examine its concurrent (criterion-related) validity (study 1). Twenty other subjects completed the same jump series on 2 different occasions (separated by 1 week), and jump heights of session 1 were compared with session 2, to investigate test-retest reliability of the Optojump system (study 2). Intraclass correlation coefficients (ICCs) for validity were very high (0.997-0.998), even if a systematic difference was consistently observed between force plate and Optojump (-1.06 cm; p < 0.001). Test-retest reliability of the Optojump system was excellent, with ICCs ranging from 0.982 to 0.989, low coefficients of variation (2.7%), and low random errors (±2.81 cm). The Optojump photocell system demonstrated strong concurrent validity and excellent test-retest reliability for the estimation of vertical jump height. We propose the following equation that allows force plate and Optojump results to be used interchangeably: force plate jump height (cm) = 1.02 × Optojump jump height + 0.29. In conclusion, the use of Optojump photoelectric cells is legitimate for field-based assessments of vertical jump height.

Validity of parent-reported weight and height of preschool children measured at home or estimated without home measurement: a validation study

PubMed Central

2011-01-01

Background Parental reports are often used in large-scale surveys to assess children's body mass index (BMI). Therefore, it is important to know to what extent these parental reports are valid and whether it makes a difference if the parents measured their children's weight and height at home or whether they simply estimated these values. The aim of this study is to compare the validity of parent-reported height, weight and BMI values of preschool children (3-7 y-old), when measured at home or estimated by parents without actual measurement. Methods The subjects were 297 Belgian preschool children (52.9% male). Participation rate was 73%. A questionnaire including questions about height and weight of the children was completed by the parents. Nurses measured height and weight following standardised procedures. International age- and sex-specific BMI cut-off values were employed to determine categories of weight status and obesity. Results On the group level, no important differences in accuracy of reported height, weight and BMI were identified between parent-measured or estimated values. However, for all 3 parameters, the correlations between parental reports and nurse measurements were higher in the group of children whose body dimensions were measured by the parents. Sensitivity for underweight and overweight/obesity were respectively 73% and 47% when parents measured their child's height and weight, and 55% and 47% when parents estimated values without measurement. Specificity for underweight and overweight/obesity were respectively 82% and 97% when parents measured the children, and 75% and 93% with parent estimations. Conclusions Diagnostic measures were more accurate when parents measured their child's weight and height at home than when those dimensions were based on parental judgements. When parent-reported data on an individual level is used, the accuracy could be improved by encouraging the parents to measure weight and height of their children at home. PMID:21736757

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

What automated age estimation of hand and wrist MRI data tells us about skeletal maturation in male adolescents.

PubMed

Urschler, Martin; Grassegger, Sabine; Štern, Darko

2015-01-01

Age estimation of individuals is important in human biology and has various medical and forensic applications. Recent interest in MR-based methods aims to investigate alternatives for established methods involving ionising radiation. Automatic, software-based methods additionally promise improved estimation objectivity. To investigate how informative automatically selected image features are regarding their ability to discriminate age, by exploring a recently proposed software-based age estimation method for MR images of the left hand and wrist. One hundred and two MR datasets of left hand images are used to evaluate age estimation performance, consisting of bone and epiphyseal gap volume localisation, computation of one age regression model per bone mapping image features to age and fusion of individual bone age predictions to a final age estimate. Quantitative results of the software-based method show an age estimation performance with a mean absolute difference of 0.85 years (SD = 0.58 years) to chronological age, as determined by a cross-validation experiment. Qualitatively, it is demonstrated how feature selection works and which image features of skeletal maturation are automatically chosen to model the non-linear regression function. Feasibility of automatic age estimation based on MRI data is shown and selected image features are found to be informative for describing anatomical changes during physical maturation in male adolescents.

Evaluating abundance estimate precision and the assumptions of a count-based index for small mammals

USGS Publications Warehouse

Wiewel, A.S.; Adams, A.A.Y.; Rodda, G.H.

2009-01-01

Conservation and management of small mammals requires reliable knowledge of population size. We investigated precision of markrecapture and removal abundance estimates generated from live-trapping and snap-trapping data collected at sites on Guam (n 7), Rota (n 4), Saipan (n 5), and Tinian (n 3), in the Mariana Islands. We also evaluated a common index, captures per unit effort (CPUE), as a predictor of abundance. In addition, we evaluated cost and time associated with implementing live-trapping and snap-trapping and compared species-specific capture rates of selected live- and snap-traps. For all species, markrecapture estimates were consistently more precise than removal estimates based on coefficients of variation and 95 confidence intervals. The predictive utility of CPUE was poor but improved with increasing sampling duration. Nonetheless, modeling of sampling data revealed that underlying assumptions critical to application of an index of abundance, such as constant capture probability across space, time, and individuals, were not met. Although snap-trapping was cheaper and faster than live-trapping, the time difference was negligible when site preparation time was considered. Rattus diardii spp. captures were greatest in Haguruma live-traps (Standard Trading Co., Honolulu, HI) and Victor snap-traps (Woodstream Corporation, Lititz, PA), whereas Suncus murinus and Mus musculus captures were greatest in Sherman live-traps (H. B. Sherman Traps, Inc., Tallahassee, FL) and Museum Special snap-traps (Woodstream Corporation). Although snap-trapping and CPUE may have utility after validation against more rigorous methods, validation should occur across the full range of study conditions. Resources required for this level of validation would likely be better allocated towards implementing rigorous and robust methods.

Evaluation of the 24-Hour Recall as a Reference Instrument for Calibrating Other Self-Report Instruments in Nutritional Cohort Studies: Evidence From the Validation Studies Pooling Project.

PubMed

Freedman, Laurence S; Commins, John M; Willett, Walter; Tinker, Lesley F; Spiegelman, Donna; Rhodes, Donna; Potischman, Nancy; Neuhouser, Marian L; Moshfegh, Alanna J; Kipnis, Victor; Baer, David J; Arab, Lenore; Prentice, Ross L; Subar, Amy F

2017-07-01

Calibrating dietary self-report instruments is recommended as a way to adjust for measurement error when estimating diet-disease associations. Because biomarkers available for calibration are limited, most investigators use self-reports (e.g., 24-hour recalls (24HRs)) as the reference instrument. We evaluated the performance of 24HRs as reference instruments for calibrating food frequency questionnaires (FFQs), using data from the Validation Studies Pooling Project, comprising 5 large validation studies using recovery biomarkers. Using 24HRs as reference instruments, we estimated attenuation factors, correlations with truth, and calibration equations for FFQ-reported intakes of energy and for protein, potassium, and sodium and their densities, and we compared them with values derived using biomarkers. Based on 24HRs, FFQ attenuation factors were substantially overestimated for energy and sodium intakes, less for protein and potassium, and minimally for nutrient densities. FFQ correlations with truth, based on 24HRs, were substantially overestimated for all dietary components. Calibration equations did not capture dependencies on body mass index. We also compared predicted bias in estimated relative risks adjusted using 24HRs as reference instruments with bias when making no adjustment. In disease models with energy and 1 or more nutrient intakes, predicted bias in estimated nutrient relative risks was reduced on average, but bias in the energy risk coefficient was unchanged. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Validation of NH3 satellite observations by ground-based FTIR measurements

NASA Astrophysics Data System (ADS)

Dammers, Enrico; Palm, Mathias; Van Damme, Martin; Shephard, Mark; Cady-Pereira, Karen; Capps, Shannon; Clarisse, Lieven; Coheur, Pierre; Erisman, Jan Willem

2016-04-01

Global emissions of reactive nitrogen have been increasing to an unprecedented level due to human activities and are estimated to be a factor four larger than pre-industrial levels. Concentration levels of NOx are declining, but ammonia (NH3) levels are increasing around the globe. While NH3 at its current concentrations poses significant threats to the environment and human health, relatively little is known about the total budget and global distribution. Surface observations are sparse and mainly available for north-western Europe, the United States and China and are limited by the high costs and poor temporal and spatial resolution. Since the lifetime of atmospheric NH3 is short, on the order of hours to a few days, due to efficient deposition and fast conversion to particulate matter, the existing surface measurements are not sufficient to estimate global concentrations. Advanced space-based IR-sounders such as the Tropospheric Emission Spectrometer (TES), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared Sounder (CrIS) enable global observations of atmospheric NH3 that help overcome some of the limitations of surface observations. However, the satellite NH3 retrievals are complex requiring extensive validation. Presently there have only been a few dedicated satellite NH3 validation campaigns performed with limited spatial, vertical or temporal coverage. Recently a retrieval methodology was developed for ground-based Fourier Transform Infrared Spectroscopy (FTIR) instruments to obtain vertical concentration profiles of NH3. Here we show the applicability of retrieved columns from nine globally distributed stations with a range of NH3 pollution levels to validate satellite NH3 products.

Uncertainty-based Estimation of the Secure Range for ISO New England Dynamic Interchange Adjustment

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

Etingov, Pavel V.; Makarov, Yuri V.; Wu, Di

2014-04-14

The paper proposes an approach to estimate the secure range for dynamic interchange adjustment, which assists system operators in scheduling the interchange with neighboring control areas. Uncertainties associated with various sources are incorporated. The proposed method is implemented in the dynamic interchange adjustment (DINA) tool developed by Pacific Northwest National Laboratory (PNNL) for ISO New England. Simulation results are used to validate the effectiveness of the proposed method.

Intrathoracic airway measurement: ex-vivo validation

NASA Astrophysics Data System (ADS)

Reinhardt, Joseph M.; Raab, Stephen A.; D'Souza, Neil D.; Hoffman, Eric A.

1997-05-01

High-resolution x-ray CT (HRCT) provides detailed images of the lungs and bronchial tree. HRCT-based imaging and quantitation of peripheral bronchial airway geometry provides a valuable tool for assessing regional airway physiology. Such measurements have been sued to address physiological questions related to the mechanics of airway collapse in sleep apnea, the measurement of airway response to broncho-constriction agents, and to evaluate and track the progression of disease affecting the airways, such as asthma and cystic fibrosis. Significant attention has been paid to the measurements of extra- and intra-thoracic airways in 2D sections from volumetric x-ray CT. A variety of manual and semi-automatic techniques have been proposed for airway geometry measurement, including the use of standardized display window and level settings for caliper measurements, methods based on manual or semi-automatic border tracing, and more objective, quantitative approaches such as the use of the 'half-max' criteria. A recently proposed measurements technique uses a model-based deconvolution to estimate the location of the inner and outer airway walls. Validation using a plexiglass phantom indicates that the model-based method is more accurate than the half-max approach for thin-walled structures. In vivo validation of these airway measurement techniques is difficult because of the problems in identifying a reliable measurement 'gold standard.' In this paper we report on ex vivo validation of the half-max and model-based methods using an excised pig lung. The lung is sliced into thin sections of tissue and scanned using an electron beam CT scanner. Airways of interest are measured from the CT images, and also measured with using a microscope and micrometer to obtain a measurement gold standard. The result show no significant difference between the model-based measurements and the gold standard; while the half-max estimates exhibited a measurement bias and were significantly different than the gold standard.

Collocation mismatch uncertainties in satellite aerosol retrieval validation

NASA Astrophysics Data System (ADS)

Virtanen, Timo H.; Kolmonen, Pekka; Sogacheva, Larisa; Rodríguez, Edith; Saponaro, Giulia; de Leeuw, Gerrit

2018-02-01

Satellite-based aerosol products are routinely validated against ground-based reference data, usually obtained from sun photometer networks such as AERONET (AEROsol RObotic NETwork). In a typical validation exercise a spatial sample of the instantaneous satellite data is compared against a temporal sample of the point-like ground-based data. The observations do not correspond to exactly the same column of the atmosphere at the same time, and the representativeness of the reference data depends on the spatiotemporal variability of the aerosol properties in the samples. The associated uncertainty is known as the collocation mismatch uncertainty (CMU). The validation results depend on the sampling parameters. While small samples involve less variability, they are more sensitive to the inevitable noise in the measurement data. In this paper we study systematically the effect of the sampling parameters in the validation of AATSR (Advanced Along-Track Scanning Radiometer) aerosol optical depth (AOD) product against AERONET data and the associated collocation mismatch uncertainty. To this end, we study the spatial AOD variability in the satellite data, compare it against the corresponding values obtained from densely located AERONET sites, and assess the possible reasons for observed differences. We find that the spatial AOD variability in the satellite data is approximately 2 times larger than in the ground-based data, and the spatial variability correlates only weakly with that of AERONET for short distances. We interpreted that only half of the variability in the satellite data is due to the natural variability in the AOD, and the rest is noise due to retrieval errors. However, for larger distances (˜ 0.5°) the correlation is improved as the noise is averaged out, and the day-to-day changes in regional AOD variability are well captured. Furthermore, we assess the usefulness of the spatial variability of the satellite AOD data as an estimate of CMU by comparing the retrieval errors to the total uncertainty estimates including the CMU in the validation. We find that accounting for CMU increases the fraction of consistent observations.

[An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

PubMed

Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

2009-10-01

Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

A new framework of statistical inferences based on the valid joint sampling distribution of the observed counts in an incomplete contingency table.

PubMed

Tian, Guo-Liang; Li, Hui-Qiong

2017-08-01

Some existing confidence interval methods and hypothesis testing methods in the analysis of a contingency table with incomplete observations in both margins entirely depend on an underlying assumption that the sampling distribution of the observed counts is a product of independent multinomial/binomial distributions for complete and incomplete counts. However, it can be shown that this independency assumption is incorrect and can result in unreliable conclusions because of the under-estimation of the uncertainty. Therefore, the first objective of this paper is to derive the valid joint sampling distribution of the observed counts in a contingency table with incomplete observations in both margins. The second objective is to provide a new framework for analyzing incomplete contingency tables based on the derived joint sampling distribution of the observed counts by developing a Fisher scoring algorithm to calculate maximum likelihood estimates of parameters of interest, the bootstrap confidence interval methods, and the bootstrap testing hypothesis methods. We compare the differences between the valid sampling distribution and the sampling distribution under the independency assumption. Simulation studies showed that average/expected confidence-interval widths of parameters based on the sampling distribution under the independency assumption are shorter than those based on the new sampling distribution, yielding unrealistic results. A real data set is analyzed to illustrate the application of the new sampling distribution for incomplete contingency tables and the analysis results again confirm the conclusions obtained from the simulation studies.

Large-scale estimates of gross primary production on the Qinghai-Tibet plateau based on remote sensing data

NASA Astrophysics Data System (ADS)

Ma, M., II; Yuan, W.; Dong, J.; Zhang, F.; Cai, W.; Li, H.

2017-12-01

Vegetation gross primary production (GPP) is an important variable for the carbon cycle on the Qinghai-Tibetan Plateau (QTP). Based on the measurements from twelve eddy covariance (EC) sites, we validated a light use efficiency model (i.e. EC-LUE) to evaluate the spatial-temporal patterns of GPP and the effect of environmental variables on QTP. The EC-LUE model explained 85.4% of the daily observed GPP variations through all of the twelve EC sites, and characterized very well the seasonal changes of GPP. Annual GPP over the entire QTP ranged from 575 to 703 Tg C, and showed a significantly increasing trend from 1982 to 2013. However, there were large spatial heterogeneities in long-term trends of GPP. Throughout the entire QTP, air temperature TA increase had a greater influence than solar radiation and PREC changes on productivity. Moreover, our results highlight the large uncertainties of previous GPP estimates due to insufficient parameterization and validations. When compared with GPP estimates of the EC-LUE model, most Coupled Model Intercomparison Project (CMIP5) GPP products overestimate the magnitude and increasing trends of regional GPP, which potentially impact the feedback of ecosystems to regional climate changes.

Validation of ERS-1 environmental data products

NASA Technical Reports Server (NTRS)

Goodberlet, Mark A.; Swift, Calvin T.; Wilkerson, John C.

1994-01-01

Evaluation of the launch-version algorithms used by the European Space Agency (ESA) to derive wind field and ocean wave estimates from measurements of sensors aboard the European Remote Sensing satellite, ERS-1, has been accomplished through comparison of the derived parameters with coincident measurements made by 24 open ocean buoys maintained by the National Oceanic and Atmospheric Administration). During the period from November 1, 1991 through February 28, 1992, data bases with 577 and 485 pairs of coincident sensor/buoy wind and wave measurements were collected for the Active Microwave Instrument (AMI) and Radar Altimeter (RA) respectively. Based on these data, algorithm retrieval accuracy is estimated to be plus or minus 4 m/s for AMI wind speed, plus or minus 3 m/s for RA wind speed and plus or minus 0.6 m for RA wave height. After removing 180 degree ambiguity errors, the AMI wind direction retrieval accuracy was estimated at plus or minus 28 degrees. All of the ERS-1 wind and wave retrievals are relatively unbiased. These results should be viewed as interim since improved algorithms are under development. As final versions are implemented, additional assessments should be conducted to complete the validation.

A revised surface resistance parameterisation for estimating latent heat flux from remotely sensed data

NASA Astrophysics Data System (ADS)

Song, Yi; Wang, Jiemin; Yang, Kun; Ma, Mingguo; Li, Xin; Zhang, Zhihui; Wang, Xufeng

2012-07-01

Estimating evapotranspiration (ET) is required for many environmental studies. Remote sensing provides the ability to spatially map latent heat flux. Many studies have developed approaches to derive spatially distributed surface energy fluxes from various satellite sensors with the help of field observations. In this study, remote-sensing-based λE mapping was conducted using a Landsat Thematic Mapper (TM) image and an Enhanced Thematic Mapper Plus (ETM+) image. The remotely sensed data and field observations employed in this study were obtained from Watershed Allied Telemetry Experimental Research (WATER). A biophysics-based surface resistance model was revised to account for water stress and temperature constraints. The precision of the results was validated using 'ground truth' data obtained by eddy covariance (EC) system. Scale effects play an important role, especially for parameter optimisation and validation of the latent heat flux (λE). After considering the footprint of EC, the λE derived from the remote sensing data was comparable to the EC measured value during the satellite's passage. The results showed that the revised surface resistance parameterisation scheme was useful for estimating the latent heat flux over cropland in arid regions.

Alternative methods to evaluate trial level surrogacy.

PubMed

Abrahantes, Josè Cortiñas; Shkedy, Ziv; Molenberghs, Geert

2008-01-01

The evaluation and validation of surrogate endpoints have been extensively studied in the last decade. Prentice [1] and Freedman, Graubard and Schatzkin [2] laid the foundations for the evaluation of surrogate endpoints in randomized clinical trials. Later, Buyse et al. [5] proposed a meta-analytic methodology, producing different methods for different settings, which was further studied by Alonso and Molenberghs [9], in their unifying approach based on information theory. In this article, we focus our attention on the trial-level surrogacy and propose alternative procedures to evaluate such surrogacy measure, which do not pre-specify the type of association. A promising correction based on cross-validation is investigated. As well as the construction of confidence intervals for this measure. In order to avoid making assumption about the type of relationship between the treatment effects and its distribution, a collection of alternative methods, based on regression trees, bagging, random forests, and support vector machines, combined with bootstrap-based confidence interval and, should one wish, in conjunction with a cross-validation based correction, will be proposed and applied. We apply the various strategies to data from three clinical studies: in opthalmology, in advanced colorectal cancer, and in schizophrenia. The results obtained for the three case studies are compared; they indicate that using random forest or bagging models produces larger estimated values for the surrogacy measure, which are in general stabler and the confidence interval narrower than linear regression and support vector regression. For the advanced colorectal cancer studies, we even found the trial-level surrogacy is considerably different from what has been reported. In general the alternative methods are more computationally demanding, and specially the calculation of the confidence intervals, require more computational time that the delta-method counterpart. First, more flexible modeling techniques can be used, allowing for other type of association. Second, when no cross-validation-based correction is applied, overly optimistic trial-level surrogacy estimates will be found, thus cross-validation is highly recommendable. Third, the use of the delta method to calculate confidence intervals is not recommendable since it makes assumptions valid only in very large samples. It may also produce range-violating limits. We therefore recommend alternatives: bootstrap methods in general. Also, the information-theoretic approach produces comparable results with the bagging and random forest approaches, when cross-validation correction is applied. It is also important to observe that, even for the case in which the linear model might be a good option too, bagging methods perform well too, and their confidence intervals were more narrow.

Uncertainty estimates of purity measurements based on current information: toward a "live validation" of purity methods.

PubMed

Apostol, Izydor; Kelner, Drew; Jiang, Xinzhao Grace; Huang, Gang; Wypych, Jette; Zhang, Xin; Gastwirt, Jessica; Chen, Kenneth; Fodor, Szilan; Hapuarachchi, Suminda; Meriage, Dave; Ye, Frank; Poppe, Leszek; Szpankowski, Wojciech

2012-12-01

To predict precision and other performance characteristics of chromatographic purity methods, which represent the most widely used form of analysis in the biopharmaceutical industry. We have conducted a comprehensive survey of purity methods, and show that all performance characteristics fall within narrow measurement ranges. This observation was used to develop a model called Uncertainty Based on Current Information (UBCI), which expresses these performance characteristics as a function of the signal and noise levels, hardware specifications, and software settings. We applied the UCBI model to assess the uncertainty of purity measurements, and compared the results to those from conventional qualification. We demonstrated that the UBCI model is suitable to dynamically assess method performance characteristics, based on information extracted from individual chromatograms. The model provides an opportunity for streamlining qualification and validation studies by implementing a "live validation" of test results utilizing UBCI as a concurrent assessment of measurement uncertainty. Therefore, UBCI can potentially mitigate the challenges associated with laborious conventional method validation and facilitates the introduction of more advanced analytical technologies during the method lifecycle.

Results and Validation of MODIS Aerosol Retrievals Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2001-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

Results and Validation of MODIS Aerosol Retrievals over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Ichoku, C.; Chu, D. A.; Mattoo, S.; Levy, R.; Martins, J. V.; Li, R.-R.; Einaudi, Franco (Technical Monitor)

2000-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

Remote sensing-based estimation of annual soil respiration at two contrasting forest sites

NASA Astrophysics Data System (ADS)

Huang, Ni; Gu, Lianhong; Black, T. Andrew; Wang, Li; Niu, Zheng

2015-11-01

Soil respiration (Rs), an important component of the global carbon cycle, can be estimated using remotely sensed data, but the accuracy of this technique has not been thoroughly investigated. In this study, we proposed a methodology for the remote estimation of annual Rs at two contrasting FLUXNET forest sites (a deciduous broadleaf forest and an evergreen needleleaf forest). A version of the Akaike's information criterion was used to select the best model from a range of models for annual Rs estimation based on the remotely sensed data products from the Moderate Resolution Imaging Spectroradiometer and root-zone soil moisture product derived from assimilation of the NASA Advanced Microwave Scanning Radiometer soil moisture products and a two-layer Palmer water balance model. We found that the Arrhenius-type function based on nighttime land surface temperature (LST-night) was the best model by comprehensively considering the model explanatory power and model complexity at the Missouri Ozark and BC-Campbell River 1949 Douglas-fir sites. In addition, a multicollinearity problem among LST-night, root-zone soil moisture, and plant photosynthesis factor was effectively avoided by selecting the LST-night-driven model. Cross validation showed that temporal variation in Rs was captured by the LST-night-driven model with a mean absolute error below 1 µmol CO2 m-2 s-1 at both forest sites. An obvious overestimation that occurred in 2005 and 2007 at the Missouri Ozark site reduced the evaluation accuracy of cross validation because of summer drought. However, no significant difference was found between the Arrhenius-type function driven by LST-night and the function considering LST-night and root-zone soil moisture. This finding indicated that the contribution of soil moisture to Rs was relatively small at our multiyear data set. To predict intersite Rs, maximum leaf area index (LAImax) was used as an upscaling factor to calibrate the site-specific reference respiration rates. Independent validation demonstrated that the model incorporating LST-night and LAImax efficiently predicted the spatial and temporal variabilities of Rs. Based on the Arrhenius-type function using LST-night as an input parameter, the rates of annual C release from Rs were 894-1027 g C m-2 yr-1 at the BC-Campbell River 1949 Douglas-fir site and 818-943 g C m-2 yr-1 at the Missouri Ozark site. The ratio between annual Rs estimates based on remotely sensed data and the total annual ecosystem respiration from eddy covariance measurements fell within the range reported in previous studies. Our results demonstrated that estimating annual Rs based on remote sensing data products was possible at deciduous and evergreen forest sites.

Validation of GOES-9 Satellite-Derived Cloud Properties over the Tropical Western Pacific Region

NASA Technical Reports Server (NTRS)

Khaiyer, Mandana M.; Nordeen, Michele L.; Doeling, David R.; Chakrapani, Venkatasan; Minnis, Patrick; Smith, William L., Jr.

2004-01-01

Real-time processing of hourly GOES-9 images in the ARM TWP region began operationally in October 2003 and is continuing. The ARM sites provide an excellent source for validating this new satellitederived cloud and radiation property dataset. Derived cloud amounts, heights, and broadband shortwave fluxes are compared with similar quantities derived from ground-based instrumentation. The results will provide guidance for estimating uncertainties in the GOES-9 products and to develop improvements in the retrieval methodologies and input.

Logistics: Implementation of Performance - Based Logistics for the Javelin Weapon System

DTIC Science & Technology

2005-03-07

the c.ontext of each lice within the Automated Cost 24 Batimating-hTasgraled Tools ( ACEIT ) mode], the Army’s standard cost model, containing the EA was...fully validated the EA, The Javelin E.A was valihdted through an extensive review of the EA cost documentation in (te ACEIT file in coordination with... ACEIT file of the system cost estimate- This documentation was conndered to be suflicienT by the CEAC Director once the EA was determinmd to be valid

Validating Savings Claims of Cold Climate Zero Energy Ready Homes

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

Williamson, J.; Puttagunta, S.

This report details the validation methods used to analyze consumption at each of these homes. It includes a detailed end-use examination of consumptions from the following categories: 1) Heating, 2) Cooling, 3) Lights, Appliances, and Miscellaneous Electric Loads (LAMELS) along with Domestic Hot Water Use, 4) Ventilation, and 5) PV generation. A utility bill disaggregation method, which allows a crude estimation of space conditioning loads based on outdoor air temperature, was also performed and the results compared to the actual measured data.

Estimating Shape and Micro-Motion Parameter of Rotationally Symmetric Space Objects from the Infrared Signature

PubMed Central

Wu, Yabei; Lu, Huanzhang; Zhao, Fei; Zhang, Zhiyong

2016-01-01

Shape serves as an important additional feature for space target classification, which is complementary to those made available. Since different shapes lead to different projection functions, the projection property can be regarded as one kind of shape feature. In this work, the problem of estimating the projection function from the infrared signature of the object is addressed. We show that the projection function of any rotationally symmetric object can be approximately represented as a linear combination of some base functions. Based on this fact, the signal model of the emissivity-area product sequence is constructed, which is a particular mathematical function of the linear coefficients and micro-motion parameters. Then, the least square estimator is proposed to estimate the projection function and micro-motion parameters jointly. Experiments validate the effectiveness of the proposed method. PMID:27763500

Identifying Seizure Onset Zone From the Causal Connectivity Inferred Using Directed Information

NASA Astrophysics Data System (ADS)

Malladi, Rakesh; Kalamangalam, Giridhar; Tandon, Nitin; Aazhang, Behnaam

2016-10-01

In this paper, we developed a model-based and a data-driven estimator for directed information (DI) to infer the causal connectivity graph between electrocorticographic (ECoG) signals recorded from brain and to identify the seizure onset zone (SOZ) in epileptic patients. Directed information, an information theoretic quantity, is a general metric to infer causal connectivity between time-series and is not restricted to a particular class of models unlike the popular metrics based on Granger causality or transfer entropy. The proposed estimators are shown to be almost surely convergent. Causal connectivity between ECoG electrodes in five epileptic patients is inferred using the proposed DI estimators, after validating their performance on simulated data. We then proposed a model-based and a data-driven SOZ identification algorithm to identify SOZ from the causal connectivity inferred using model-based and data-driven DI estimators respectively. The data-driven SOZ identification outperforms the model-based SOZ identification algorithm when benchmarked against visual analysis by neurologist, the current clinical gold standard. The causal connectivity analysis presented here is the first step towards developing novel non-surgical treatments for epilepsy.

Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities

PubMed Central

Helb, Danica A.; Tetteh, Kevin K. A.; Felgner, Philip L.; Skinner, Jeff; Hubbard, Alan; Arinaitwe, Emmanuel; Mayanja-Kizza, Harriet; Ssewanyana, Isaac; Kamya, Moses R.; Beeson, James G.; Tappero, Jordan; Smith, David L.; Crompton, Peter D.; Rosenthal, Philip J.; Dorsey, Grant; Drakeley, Christopher J.; Greenhouse, Bryan

2015-01-01

Tools to reliably measure Plasmodium falciparum (Pf) exposure in individuals and communities are needed to guide and evaluate malaria control interventions. Serologic assays can potentially produce precise exposure estimates at low cost; however, current approaches based on responses to a few characterized antigens are not designed to estimate exposure in individuals. Pf-specific antibody responses differ by antigen, suggesting that selection of antigens with defined kinetic profiles will improve estimates of Pf exposure. To identify novel serologic biomarkers of malaria exposure, we evaluated responses to 856 Pf antigens by protein microarray in 186 Ugandan children, for whom detailed Pf exposure data were available. Using data-adaptive statistical methods, we identified combinations of antibody responses that maximized information on an individual’s recent exposure. Responses to three novel Pf antigens accurately classified whether an individual had been infected within the last 30, 90, or 365 d (cross-validated area under the curve = 0.86–0.93), whereas responses to six antigens accurately estimated an individual’s malaria incidence in the prior year. Cross-validated incidence predictions for individuals in different communities provided accurate stratification of exposure between populations and suggest that precise estimates of community exposure can be obtained from sampling a small subset of that community. In addition, serologic incidence predictions from cross-sectional samples characterized heterogeneity within a community similarly to 1 y of continuous passive surveillance. Development of simple ELISA-based assays derived from the successful selection strategy outlined here offers the potential to generate rich epidemiologic surveillance data that will be widely accessible to malaria control programs. PMID:26216993

Evapotranspiration based on equilibrated relative humidity (ETRHEQ): Evaluation over the continental U.S.

NASA Astrophysics Data System (ADS)

Rigden, Angela J.; Salvucci, Guido D.

2015-04-01

A novel method of estimating evapotranspiration (ET), referred to as the ETRHEQ method, is further developed, validated, and applied across the U.S. from 1961 to 2010. The ETRHEQ method estimates the surface conductance to water vapor transport, which is the key rate-limiting parameter of typical ET models, by choosing the surface conductance that minimizes the vertical variance of the calculated relative humidity profile averaged over the day. The ETRHEQ method, which was previously tested at five AmeriFlux sites, is modified for use at common weather stations and further validated at 20 AmeriFlux sites that span a wide range of climates and limiting factors. Averaged across all sites, the daily latent heat flux RMSE is ˜26 W·m-2 (or 15%). The method is applied across the U.S. at 305 weather stations and spatially interpolated using ANUSPLIN software. Gridded annual mean ETRHEQ ET estimates are compared with four data sets, including water balance-derived ET, machine-learning ET estimates based on FLUXNET data, North American Land Data Assimilation System project phase 2 ET, and a benchmark product that integrates 14 global ET data sets, with RMSEs ranging from 8.7 to 12.5 cm·yr-1. The ETRHEQ method relies only on data measured at weather stations, an estimate of vegetation height derived from land cover maps, and an estimate of soil thermal inertia. These data requirements allow it to have greater spatial coverage than direct measurements, greater historical coverage than satellite methods, significantly less parameter specification than most land surface models, and no requirement for calibration.

Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities.

PubMed

Helb, Danica A; Tetteh, Kevin K A; Felgner, Philip L; Skinner, Jeff; Hubbard, Alan; Arinaitwe, Emmanuel; Mayanja-Kizza, Harriet; Ssewanyana, Isaac; Kamya, Moses R; Beeson, James G; Tappero, Jordan; Smith, David L; Crompton, Peter D; Rosenthal, Philip J; Dorsey, Grant; Drakeley, Christopher J; Greenhouse, Bryan

2015-08-11

Tools to reliably measure Plasmodium falciparum (Pf) exposure in individuals and communities are needed to guide and evaluate malaria control interventions. Serologic assays can potentially produce precise exposure estimates at low cost; however, current approaches based on responses to a few characterized antigens are not designed to estimate exposure in individuals. Pf-specific antibody responses differ by antigen, suggesting that selection of antigens with defined kinetic profiles will improve estimates of Pf exposure. To identify novel serologic biomarkers of malaria exposure, we evaluated responses to 856 Pf antigens by protein microarray in 186 Ugandan children, for whom detailed Pf exposure data were available. Using data-adaptive statistical methods, we identified combinations of antibody responses that maximized information on an individual's recent exposure. Responses to three novel Pf antigens accurately classified whether an individual had been infected within the last 30, 90, or 365 d (cross-validated area under the curve = 0.86-0.93), whereas responses to six antigens accurately estimated an individual's malaria incidence in the prior year. Cross-validated incidence predictions for individuals in different communities provided accurate stratification of exposure between populations and suggest that precise estimates of community exposure can be obtained from sampling a small subset of that community. In addition, serologic incidence predictions from cross-sectional samples characterized heterogeneity within a community similarly to 1 y of continuous passive surveillance. Development of simple ELISA-based assays derived from the successful selection strategy outlined here offers the potential to generate rich epidemiologic surveillance data that will be widely accessible to malaria control programs.

Validating the LASSO algorithm by unmixing spectral signatures in multicolor phantoms

NASA Astrophysics Data System (ADS)

Samarov, Daniel V.; Clarke, Matthew; Lee, Ji Yoon; Allen, David; Litorja, Maritoni; Hwang, Jeeseong

2012-03-01

As hyperspectral imaging (HSI) sees increased implementation into the biological and medical elds it becomes increasingly important that the algorithms being used to analyze the corresponding output be validated. While certainly important under any circumstance, as this technology begins to see a transition from benchtop to bedside ensuring that the measurements being given to medical professionals are accurate and reproducible is critical. In order to address these issues work has been done in generating a collection of datasets which could act as a test bed for algorithms validation. Using a microarray spot printer a collection of three food color dyes, acid red 1 (AR), brilliant blue R (BBR) and erioglaucine (EG) are mixed together at dierent concentrations in varying proportions at dierent locations on a microarray chip. With the concentration and mixture proportions known at each location, using HSI an algorithm should in principle, based on estimates of abundances, be able to determine the concentrations and proportions of each dye at each location on the chip. These types of data are particularly important in the context of medical measurements as the resulting estimated abundances will be used to make critical decisions which can have a serious impact on an individual's health. In this paper we present a novel algorithm for processing and analyzing HSI data based on the LASSO algorithm (similar to "basis pursuit"). The LASSO is a statistical method for simultaneously performing model estimation and variable selection. In the context of estimating abundances in an HSI scene these so called "sparse" representations provided by the LASSO are appropriate as not every pixel will be expected to contain every endmember. The algorithm we present takes the general framework of the LASSO algorithm a step further and incorporates the rich spatial information which is available in HSI to further improve the estimates of abundance. We show our algorithm's improvement over the standard LASSO using the dye mixture data as the test bed.

Validating alternative methodologies to estimate the regime of temporary rivers when flow data are unavailable.

PubMed

Gallart, F; Llorens, P; Latron, J; Cid, N; Rieradevall, M; Prat, N

2016-09-15

Hydrological data for assessing the regime of temporary rivers are often non-existent or scarce. The scarcity of flow data makes impossible to characterize the hydrological regime of temporary streams and, in consequence, to select the correct periods and methods to determine their ecological status. This is why the TREHS software is being developed, in the framework of the LIFE Trivers project. It will help managers to implement adequately the European Water Framework Directive in this kind of water body. TREHS, using the methodology described in Gallart et al. (2012), defines six transient 'aquatic states', based on hydrological conditions representing different mesohabitats, for a given reach at a particular moment. Because of its qualitative nature, this approach allows using alternative methodologies to assess the regime of temporary rivers when there are no observed flow data. These methods, based on interviews and high-resolution aerial photographs, were tested for estimating the aquatic regime of temporary rivers. All the gauging stations (13) belonging to the Catalan Internal Catchments (NE Spain) with recurrent zero-flow periods were selected to validate this methodology. On the one hand, non-structured interviews were conducted with inhabitants of villages near the gauging stations. On the other hand, the historical series of available orthophotographs were examined. Flow records measured at the gauging stations were used to validate the alternative methods. Flow permanence in the reaches was estimated reasonably by the interviews and adequately by aerial photographs, when compared with the values estimated using daily flows. The degree of seasonality was assessed only roughly by the interviews. The recurrence of disconnected pools was not detected by flow records but was estimated with some divergences by the two methods. The combination of the two alternative methods allows substituting or complementing flow records, to be updated in the future through monitoring by professionals and citizens. Copyright © 2016 Elsevier B.V. All rights reserved.

The burden of typhoid fever in low- and middle-income countries: A meta-regression approach.

PubMed

Antillón, Marina; Warren, Joshua L; Crawford, Forrest W; Weinberger, Daniel M; Kürüm, Esra; Pak, Gi Deok; Marks, Florian; Pitzer, Virginia E

2017-02-01

Upcoming vaccination efforts against typhoid fever require an assessment of the baseline burden of disease in countries at risk. There are no typhoid incidence data from most low- and middle-income countries (LMICs), so model-based estimates offer insights for decision-makers in the absence of readily available data. We developed a mixed-effects model fit to data from 32 population-based studies of typhoid incidence in 22 locations in 14 countries. We tested the contribution of economic and environmental indices for predicting typhoid incidence using a stochastic search variable selection algorithm. We performed out-of-sample validation to assess the predictive performance of the model. We estimated that 17.8 million cases of typhoid fever occur each year in LMICs (95% credible interval: 6.9-48.4 million). Central Africa was predicted to experience the highest incidence of typhoid, followed by select countries in Central, South, and Southeast Asia. Incidence typically peaked in the 2-4 year old age group. Models incorporating widely available economic and environmental indicators were found to describe incidence better than null models. Recent estimates of typhoid burden may under-estimate the number of cases and magnitude of uncertainty in typhoid incidence. Our analysis permits prediction of overall as well as age-specific incidence of typhoid fever in LMICs, and incorporates uncertainty around the model structure and estimates of the predictors. Future studies are needed to further validate and refine model predictions and better understand year-to-year variation in cases.

Curriculum-Based Measurement of Oral Reading: Multi-Study Evaluation of Schedule, Duration, and Dataset Quality on Progress Monitoring Outcomes

ERIC Educational Resources Information Center

Christ, Theodore J.; Zopluoglu, Cengiz; Monaghen, Barbara D.; Van Norman, Ethan R.

2013-01-01

Curriculum-Based Measurement of Oral Reading (CBM-R) is used to collect time series data, estimate the rate of student achievement, and evaluate program effectiveness. A series of 5 studies were carried out to evaluate the validity, reliability, precision, and diagnostic accuracy of progress monitoring across a variety of progress monitoring…

Curriculum-Based Measurement of Reading: An Evaluation of Frequentist and Bayesian Methods to Model Progress Monitoring Data

ERIC Educational Resources Information Center

Christ, Theodore J.; Desjardins, Christopher David

2018-01-01

Curriculum-Based Measurement of Oral Reading (CBM-R) is often used to monitor student progress and guide educational decisions. Ordinary least squares regression (OLSR) is the most widely used method to estimate the slope, or rate of improvement (ROI), even though published research demonstrates OLSR's lack of validity and reliability, and…

Cloud fraction and cloud base measurements from scanning Doppler lidar during WFIP-2

NASA Astrophysics Data System (ADS)

Bonin, T.; Long, C.; Lantz, K. O.; Choukulkar, A.; Pichugina, Y. L.; McCarty, B.; Banta, R. M.; Brewer, A.; Marquis, M.

2017-12-01

The second Wind Forecast Improvement Project (WFIP-2) consisted of an 18-month field deployment of a variety of instrumentation with the principle objective of validating and improving NWP forecasts for wind energy applications in complex terrain. As a part of the set of instrumentation, several scanning Doppler lidars were installed across the study domain to primarily measure profiles of the mean wind and turbulence at high-resolution within the planetary boundary layer. In addition to these measurements, Doppler lidar observations can be used to directly quantify the cloud fraction and cloud base, since clouds appear as a high backscatter return. These supplementary measurements of clouds can then be used to validate cloud cover and other properties in NWP output. Herein, statistics of the cloud fraction and cloud base height from the duration of WFIP-2 are presented. Additionally, these cloud fraction estimates from Doppler lidar are compared with similar measurements from a Total Sky Imager and Radiative Flux Analysis (RadFlux) retrievals at the Wasco site. During mostly cloudy to overcast conditions, estimates of the cloud radiating temperature from the RadFlux methodology are also compared with Doppler lidar measured cloud base height.

A method to estimate spatiotemporal air quality in an urban traffic corridor.

PubMed

Singh, Nongthombam Premananda; Gokhale, Sharad

2015-12-15

Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area. Copyright © 2015 Elsevier B.V. All rights reserved.

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications.

PubMed

Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

2016-09-14

Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments.

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications

PubMed Central

Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

2016-01-01

Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments. PMID:27649178

Cross-validation to select Bayesian hierarchical models in phylogenetics.

PubMed

Duchêne, Sebastián; Duchêne, David A; Di Giallonardo, Francesca; Eden, John-Sebastian; Geoghegan, Jemma L; Holt, Kathryn E; Ho, Simon Y W; Holmes, Edward C

2016-05-26

Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance. We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models. Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult.

Comparison of constitutive flow resistance equations based on the Manning and Chezy equations applied to natural rivers

USGS Publications Warehouse

Bjerklie, David M.; Dingman, S. Lawrence; Bolster, Carl H.

2005-01-01

A set of conceptually derived in‐bank river discharge–estimating equations (models), based on the Manning and Chezy equations, are calibrated and validated using a database of 1037 discharge measurements in 103 rivers in the United States and New Zealand. The models are compared to a multiple regression model derived from the same data. The comparison demonstrates that in natural rivers, using an exponent on the slope variable of 0.33 rather than the traditional value of 0.5 reduces the variance associated with estimating flow resistance. Mean model uncertainty, assuming a constant value for the conductance coefficient, is less than 5% for a large number of estimates, and 67% of the estimates would be accurate within 50%. The models have potential application where site‐specific flow resistance information is not available and can be the basis for (1) a general approach to estimating discharge from remotely sensed hydraulic data, (2) comparison to slope‐area discharge estimates, and (3) large‐scale river modeling.

ARM Climate Modeling Best Estimate Lamont, OK Statistical Summary (ARMBE-CLDRAD SGPC1)

DOE Data Explorer

McCoy, Renata; Xie, Shaocheng

2010-01-26

Calculate monthly mean diurnal cycle based on the hourly CMBE data with qcflag >=-1 (>30% valid data within the averaged hour). For 2-D clouds, only data over the period when both MMCR and MPL were working are used.

Inferring pregnancy episodes and outcomes within a network of observational databases

PubMed Central

Ryan, Patrick; Fife, Daniel; Gifkins, Dina; Knoll, Chris; Friedman, Andrew

2018-01-01

Administrative claims and electronic health records are valuable resources for evaluating pharmaceutical effects during pregnancy. However, direct measures of gestational age are generally not available. Establishing a reliable approach to infer the duration and outcome of a pregnancy could improve pharmacovigilance activities. We developed and applied an algorithm to define pregnancy episodes in four observational databases: three US-based claims databases: Truven MarketScan® Commercial Claims and Encounters (CCAE), Truven MarketScan® Multi-state Medicaid (MDCD), and the Optum ClinFormatics® (Optum) database and one non-US database, the United Kingdom (UK) based Clinical Practice Research Datalink (CPRD). Pregnancy outcomes were classified as live births, stillbirths, abortions and ectopic pregnancies. Start dates were estimated using a derived hierarchy of available pregnancy markers, including records such as last menstrual period and nuchal ultrasound dates. Validation included clinical adjudication of 700 electronic Optum and CPRD pregnancy episode profiles to assess the operating characteristics of the algorithm, and a comparison of the algorithm’s Optum pregnancy start estimates to starts based on dates of assisted conception procedures. Distributions of pregnancy outcome types were similar across all four data sources and pregnancy episode lengths found were as expected for all outcomes, excepting term lengths in episodes that used amenorrhea and urine pregnancy tests for start estimation. Validation survey results found highest agreement between reviewer chosen and algorithm operating characteristics for questions assessing pregnancy status and accuracy of outcome category with 99–100% agreement for Optum and CPRD. Outcome date agreement within seven days in either direction ranged from 95–100%, while start date agreement within seven days in either direction ranged from 90–97%. In Optum validation sensitivity analysis, a total of 73% of algorithm estimated starts for live births were in agreement with fertility procedure estimated starts within two weeks in either direction; ectopic pregnancy 77%, stillbirth 47%, and abortion 36%. An algorithm to infer live birth and ectopic pregnancy episodes and outcomes can be applied to multiple observational databases with acceptable accuracy for further epidemiologic research. Less accuracy was found for start date estimations in stillbirth and abortion outcomes in our sensitivity analysis, which may be expected given the nature of the outcomes. PMID:29389968

An improved swarm optimization for parameter estimation and biological model selection.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

Assessment of the global monthly mean surface insolation estimated from satellite measurements using global energy balance archive data

NASA Technical Reports Server (NTRS)

Li, Zhanqing; Whitlock, Charles H.; Charlock, Thomas P.

1995-01-01

Global sets of surface radiation budget (SRB) have been obtained from satellite programs. These satellite-based estimates need validation with ground-truth observations. This study validates the estimates of monthly mean surface insolation contained in two satellite-based SRB datasets with the surface measurements made at worldwide radiation stations from the Global Energy Balance Archive (GEBA). One dataset was developed from the Earth Radiation Budget Experiment (ERBE) using the algorithm of Li et al. (ERBE/SRB), and the other from the International Satellite Cloud Climatology Project (ISCCP) using the algorithm of Pinker and Laszlo and that of Staylor (GEWEX/SRB). Since the ERBE/SRB data contain the surface net solar radiation only, the values of surface insolation were derived by making use of the surface albedo data contained GEWEX/SRB product. The resulting surface insolation has a bias error near zero and a root-mean-square error (RMSE) between 8 and 28 W/sq m. The RMSE is mainly associated with poor representation of surface observations within a grid cell. When the number of surface observations are sufficient, the random error is estimated to be about 5 W/sq m with present satellite-based estimates. In addition to demonstrating the strength of the retrieving method, the small random error demonstrates how well the ERBE derives from the monthly mean fluxes at the top of the atmosphere (TOA). A larger scatter is found for the comparison of transmissivity than for that of insolation. Month to month comparison of insolation reveals a weak seasonal trend in bias error with an amplitude of about 3 W/sq m. As for the insolation data from the GEWEX/SRB, larger bias errors of 5-10 W/sq m are evident with stronger seasonal trends and almost identical RMSEs.

Modeling the uncertainty of estimating forest carbon stocks in China

NASA Astrophysics Data System (ADS)

Yue, T. X.; Wang, Y. F.; Du, Z. P.; Zhao, M. W.; Zhang, L. L.; Zhao, N.; Lu, M.; Larocque, G. R.; Wilson, J. P.

2015-12-01

Earth surface systems are controlled by a combination of global and local factors, which cannot be understood without accounting for both the local and global components. The system dynamics cannot be recovered from the global or local controls alone. Ground forest inventory is able to accurately estimate forest carbon stocks at sample plots, but these sample plots are too sparse to support the spatial simulation of carbon stocks with required accuracy. Satellite observation is an important source of global information for the simulation of carbon stocks. Satellite remote-sensing can supply spatially continuous information about the surface of forest carbon stocks, which is impossible from ground-based investigations, but their description has considerable uncertainty. In this paper, we validated the Lund-Potsdam-Jena dynamic global vegetation model (LPJ), the Kriging method for spatial interpolation of ground sample plots and a satellite-observation-based approach as well as an approach for fusing the ground sample plots with satellite observations and an assimilation method for incorporating the ground sample plots into LPJ. The validation results indicated that both the data fusion and data assimilation approaches reduced the uncertainty of estimating carbon stocks. The data fusion had the lowest uncertainty by using an existing method for high accuracy surface modeling to fuse the ground sample plots with the satellite observations (HASM-SOA). The estimates produced with HASM-SOA were 26.1 and 28.4 % more accurate than the satellite-based approach and spatial interpolation of the sample plots, respectively. Forest carbon stocks of 7.08 Pg were estimated for China during the period from 2004 to 2008, an increase of 2.24 Pg from 1984 to 2008, using the preferred HASM-SOA method.

Collective odor source estimation and search in time-variant airflow environments using mobile robots.

PubMed

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Zeng, Ming

2011-01-01

This paper addresses the collective odor source localization (OSL) problem in a time-varying airflow environment using mobile robots. A novel OSL methodology which combines odor-source probability estimation and multiple robots' search is proposed. The estimation phase consists of two steps: firstly, the separate probability-distribution map of odor source is estimated via Bayesian rules and fuzzy inference based on a single robot's detection events; secondly, the separate maps estimated by different robots at different times are fused into a combined map by way of distance based superposition. The multi-robot search behaviors are coordinated via a particle swarm optimization algorithm, where the estimated odor-source probability distribution is used to express the fitness functions. In the process of OSL, the estimation phase provides the prior knowledge for the searching while the searching verifies the estimation results, and both phases are implemented iteratively. The results of simulations for large-scale advection-diffusion plume environments and experiments using real robots in an indoor airflow environment validate the feasibility and robustness of the proposed OSL method.

Collective Odor Source Estimation and Search in Time-Variant Airflow Environments Using Mobile Robots

PubMed Central

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Zeng, Ming

2011-01-01

This paper addresses the collective odor source localization (OSL) problem in a time-varying airflow environment using mobile robots. A novel OSL methodology which combines odor-source probability estimation and multiple robots’ search is proposed. The estimation phase consists of two steps: firstly, the separate probability-distribution map of odor source is estimated via Bayesian rules and fuzzy inference based on a single robot’s detection events; secondly, the separate maps estimated by different robots at different times are fused into a combined map by way of distance based superposition. The multi-robot search behaviors are coordinated via a particle swarm optimization algorithm, where the estimated odor-source probability distribution is used to express the fitness functions. In the process of OSL, the estimation phase provides the prior knowledge for the searching while the searching verifies the estimation results, and both phases are implemented iteratively. The results of simulations for large-scale advection–diffusion plume environments and experiments using real robots in an indoor airflow environment validate the feasibility and robustness of the proposed OSL method. PMID:22346650

Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review.

PubMed

Frankenfield, David; Roth-Yousey, Lori; Compher, Charlene

2005-05-01

An assessment of energy needs is a necessary component in the development and evaluation of a nutrition care plan. The metabolic rate can be measured or estimated by equations, but estimation is by far the more common method. However, predictive equations might generate errors large enough to impact outcome. Therefore, a systematic review of the literature was undertaken to document the accuracy of predictive equations preliminary to deciding on the imperative to measure metabolic rate. As part of a larger project to determine the role of indirect calorimetry in clinical practice, an evidence team identified published articles that examined the validity of various predictive equations for resting metabolic rate (RMR) in nonobese and obese people and also in individuals of various ethnic and age groups. Articles were accepted based on defined criteria and abstracted using evidence analysis tools developed by the American Dietetic Association. Because these equations are applied by dietetics practitioners to individuals, a key inclusion criterion was research reports of individual data. The evidence was systematically evaluated, and a conclusion statement and grade were developed. Four prediction equations were identified as the most commonly used in clinical practice (Harris-Benedict, Mifflin-St Jeor, Owen, and World Health Organization/Food and Agriculture Organization/United Nations University [WHO/FAO/UNU]). Of these equations, the Mifflin-St Jeor equation was the most reliable, predicting RMR within 10% of measured in more nonobese and obese individuals than any other equation, and it also had the narrowest error range. No validation work concentrating on individual errors was found for the WHO/FAO/UNU equation. Older adults and US-residing ethnic minorities were underrepresented both in the development of predictive equations and in validation studies. The Mifflin-St Jeor equation is more likely than the other equations tested to estimate RMR to within 10% of that measured, but noteworthy errors and limitations exist when it is applied to individuals and possibly when it is generalized to certain age and ethnic groups. RMR estimation errors would be eliminated by valid measurement of RMR with indirect calorimetry, using an evidence-based protocol to minimize measurement error. The Expert Panel advises clinical judgment regarding when to accept estimated RMR using predictive equations in any given individual. Indirect calorimetry may be an important tool when, in the judgment of the clinician, the predictive methods fail an individual in a clinically relevant way. For members of groups that are greatly underrepresented by existing validation studies of predictive equations, a high level of suspicion regarding the accuracy of the equations is warranted.

Validation of SMAP Root Zone Soil Moisture Estimates with Improved Cosmic-Ray Neutron Probe Observations

NASA Astrophysics Data System (ADS)

Babaeian, E.; Tuller, M.; Sadeghi, M.; Franz, T.; Jones, S. B.

2017-12-01

Soil Moisture Active Passive (SMAP) soil moisture products are commonly validated based on point-scale reference measurements, despite the exorbitant spatial scale disparity. The difference between the measurement depth of point-scale sensors and the penetration depth of SMAP further complicates evaluation efforts. Cosmic-ray neutron probes (CRNP) with an approximately 500-m radius footprint provide an appealing alternative for SMAP validation. This study is focused on the validation of SMAP level-4 root zone soil moisture products with 9-km spatial resolution based on CRNP observations at twenty U.S. reference sites with climatic conditions ranging from semiarid to humid. The CRNP measurements are often biased by additional hydrogen sources such as surface water, atmospheric vapor, or mineral lattice water, which sometimes yield unrealistic moisture values in excess of the soil water storage capacity. These effects were removed during CRNP data analysis. Comparison of SMAP data with corrected CRNP observations revealed a very high correlation for most of the investigated sites, which opens new avenues for validation of current and future satellite soil moisture products.

Validity and Feasibility of a Digital Diet Estimation Method for Use with Preschool Children: A Pilot Study

ERIC Educational Resources Information Center

Nicklas, Theresa A.; O'Neil, Carol E.; Stuff, Janice; Goodell, Lora Suzanne; Liu, Yan; Martin, Corby K.

2012-01-01

Objective: The goal of the study was to assess the validity and feasibility of a digital diet estimation method for use with preschool children in "Head Start." Methods: Preschool children and their caregivers participated in validation (n = 22) and feasibility (n = 24) pilot studies. Validity was determined in the metabolic research unit using…

Generation and Validation of Spatial Distribution of Hourly Wind Speed Time-Series using Machine Learning

NASA Astrophysics Data System (ADS)

Veronesi, F.; Grassi, S.

2016-09-01

Wind resource assessment is a key aspect of wind farm planning since it allows to estimate the long term electricity production. Moreover, wind speed time-series at high resolution are helpful to estimate the temporal changes of the electricity generation and indispensable to design stand-alone systems, which are affected by the mismatch of supply and demand. In this work, we present a new generalized statistical methodology to generate the spatial distribution of wind speed time-series, using Switzerland as a case study. This research is based upon a machine learning model and demonstrates that statistical wind resource assessment can successfully be used for estimating wind speed time-series. In fact, this method is able to obtain reliable wind speed estimates and propagate all the sources of uncertainty (from the measurements to the mapping process) in an efficient way, i.e. minimizing computational time and load. This allows not only an accurate estimation, but the creation of precise confidence intervals to map the stochasticity of the wind resource for a particular site. The validation shows that machine learning can minimize the bias of the wind speed hourly estimates. Moreover, for each mapped location this method delivers not only the mean wind speed, but also its confidence interval, which are crucial data for planners.

Sensor Fusion to Estimate the Depth and Width of the Weld Bead in Real Time in GMAW Processes

PubMed Central

Sampaio, Renato Coral; Vargas, José A. R.

2018-01-01

The arc welding process is widely used in industry but its automatic control is limited by the difficulty in measuring the weld bead geometry and closing the control loop on the arc, which has adverse environmental conditions. To address this problem, this work proposes a system to capture the welding variables and send stimuli to the Gas Metal Arc Welding (GMAW) conventional process with a constant voltage power source, which allows weld bead geometry estimation with an open-loop control. Dynamic models of depth and width estimators of the weld bead are implemented based on the fusion of thermographic data, welding current and welding voltage in a multilayer perceptron neural network. The estimators were trained and validated off-line with data from a novel algorithm developed to extract the features of the infrared image, a laser profilometer was implemented to measure the bead dimensions and an image processing algorithm that measures depth by making a longitudinal cut in the weld bead. These estimators are optimized for embedded devices and real-time processing and were implemented on a Field-Programmable Gate Array (FPGA) device. Experiments to collect data, train and validate the estimators are presented and discussed. The results show that the proposed method is useful in industrial and research environments. PMID:29570698

Sensor Fusion to Estimate the Depth and Width of the Weld Bead in Real Time in GMAW Processes.

PubMed

Bestard, Guillermo Alvarez; Sampaio, Renato Coral; Vargas, José A R; Alfaro, Sadek C Absi

2018-03-23

The arc welding process is widely used in industry but its automatic control is limited by the difficulty in measuring the weld bead geometry and closing the control loop on the arc, which has adverse environmental conditions. To address this problem, this work proposes a system to capture the welding variables and send stimuli to the Gas Metal Arc Welding (GMAW) conventional process with a constant voltage power source, which allows weld bead geometry estimation with an open-loop control. Dynamic models of depth and width estimators of the weld bead are implemented based on the fusion of thermographic data, welding current and welding voltage in a multilayer perceptron neural network. The estimators were trained and validated off-line with data from a novel algorithm developed to extract the features of the infrared image, a laser profilometer was implemented to measure the bead dimensions and an image processing algorithm that measures depth by making a longitudinal cut in the weld bead. These estimators are optimized for embedded devices and real-time processing and were implemented on a Field-Programmable Gate Array (FPGA) device. Experiments to collect data, train and validate the estimators are presented and discussed. The results show that the proposed method is useful in industrial and research environments.

Cost Validation Using PRICE H

NASA Technical Reports Server (NTRS)

Jack, John; Kwan, Eric; Wood, Milana

2011-01-01

PRICE H was introduced into the JPL cost estimation tool set circa 2003. It became more available at JPL when IPAO funded the NASA-wide site license for all NASA centers. PRICE H was mainly used as one of the cost tools to validate proposal grassroots cost estimates. Program offices at JPL view PRICE H as an additional crosscheck to Team X (JPL Concurrent Engineering Design Center) estimates. PRICE H became widely accepted ca, 2007 at JPL when the program offices moved away from grassroots cost estimation for Step 1 proposals. PRICE H is now one of the key cost tools used for cost validation, cost trades, and independent cost estimates.

A generalized groundwater fluctuation model based on precipitation for estimating water table levels of deep unconfined aquifers

NASA Astrophysics Data System (ADS)

Jeong, Jina; Park, Eungyu; Shik Han, Weon; Kim, Kue-Young; Suk, Heejun; Beom Jo, Si

2018-07-01

A generalized water table fluctuation model based on precipitation was developed using a statistical conceptualization of unsaturated infiltration fluxes. A gamma distribution function was adopted as a transfer function due to its versatility in representing recharge rates with temporally dispersed infiltration fluxes, and a Laplace transformation was used to obtain an analytical solution. To prove the general applicability of the model, convergences with previous water table fluctuation models were shown as special cases. For validation, a few hypothetical cases were developed, where the applicability of the model to a wide range of unsaturated zone conditions was confirmed. For further validation, the model was applied to water table level estimations of three monitoring wells with considerably thick unsaturated zones on Jeju Island. The results show that the developed model represented the pattern of hydrographs from the two monitoring wells fairly well. The lag times from precipitation to recharge estimated from the developed system transfer function were found to agree with those from a conventional cross-correlation analysis. The developed model has the potential to be adopted for the hydraulic characterization of both saturated and unsaturated zones by being calibrated to actual data when extraneous and exogenous causes of water table fluctuation are limited. In addition, as it provides reference estimates, the model can be adopted as a tool for surveilling groundwater resources under hydraulically stressed conditions.

Ray Tracing for Dispersive Tsunamis and Source Amplitude Estimation Based on Green's Law: Application to the 2015 Volcanic Tsunami Earthquake Near Torishima, South of Japan

NASA Astrophysics Data System (ADS)

Sandanbata, Osamu; Watada, Shingo; Satake, Kenji; Fukao, Yoshio; Sugioka, Hiroko; Ito, Aki; Shiobara, Hajime

2018-04-01

Ray tracing, which has been widely used for seismic waves, was also applied to tsunamis to examine the bathymetry effects during propagation, but it was limited to linear shallow-water waves. Green's law, which is based on the conservation of energy flux, has been used to estimate tsunami amplitude on ray paths. In this study, we first propose a new ray tracing method extended to dispersive tsunamis. By using an iterative algorithm to map two-dimensional tsunami velocity fields at different frequencies, ray paths at each frequency can be traced. We then show that Green's law is valid only outside the source region and that extension of Green's law is needed for source amplitude estimation. As an application example, we analyzed tsunami waves generated by an earthquake that occurred at a submarine volcano, Smith Caldera, near Torishima, Japan, in 2015. The ray-tracing results reveal that the ray paths are very dependent on its frequency, particularly at deep oceans. The validity of our frequency-dependent ray tracing is confirmed by the comparison of arrival angles and travel times with those of observed tsunami waveforms at an array of ocean bottom pressure gauges. The tsunami amplitude at the source is nearly twice or more of that just outside the source estimated from the array tsunami data by Green's law.

Copula based prediction models: an application to an aortic regurgitation study

PubMed Central

Kumar, Pranesh; Shoukri, Mohamed M

2007-01-01

Background: An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an appropriate methodology. As an alternative, a copula based methodology for prediction modeling and an algorithm to simulate data are proposed. Methods: The method consists of introducing copulas as an alternative to the correlation coefficient commonly used as a measure of dependence. An algorithm based on the marginal distributions of random variables is applied to construct the Archimedean copulas. Monte Carlo simulations are carried out to replicate datasets, estimate prediction model parameters and validate them using Lin's concordance measure. Results: We have carried out a correlation-based regression analysis on data from 20 patients aged 17–82 years on pre-operative and post-operative ejection fractions after surgery and estimated the prediction model: Post-operative ejection fraction = - 0.0658 + 0.8403 (Pre-operative ejection fraction); p = 0.0008; 95% confidence interval of the slope coefficient (0.3998, 1.2808). From the exploratory data analysis, it is noted that both the pre-operative and post-operative ejection fractions measurements have slight departures from symmetry and are skewed to the left. It is also noted that the measurements tend to be widely spread and have shorter tails compared to normal distribution. Therefore predictions made from the correlation-based model corresponding to the pre-operative ejection fraction measurements in the lower range may not be accurate. Further it is found that the best approximated marginal distributions of pre-operative and post-operative ejection fractions (using q-q plots) are gamma distributions. The copula based prediction model is estimated as: Post -operative ejection fraction = - 0.0933 + 0.8907 × (Pre-operative ejection fraction); p = 0.00008 ; 95% confidence interval for slope coefficient (0.4810, 1.3003). For both models differences in the predicted post-operative ejection fractions in the lower range of pre-operative ejection measurements are considerably different and prediction errors due to copula model are smaller. To validate the copula methodology we have re-sampled with replacement fifty independent bootstrap samples and have estimated concordance statistics 0.7722 (p = 0.0224) for the copula model and 0.7237 (p = 0.0604) for the correlation model. The predicted and observed measurements are concordant for both models. The estimates of accuracy components are 0.9233 and 0.8654 for copula and correlation models respectively. Conclusion: Copula-based prediction modeling is demonstrated to be an appropriate alternative to the conventional correlation-based prediction modeling since the correlation-based prediction models are not appropriate to model the dependence in populations with asymmetrical tails. Proposed copula-based prediction model has been validated using the independent bootstrap samples. PMID:17573974

Development and validation of an electronic frailty index using routine primary care electronic health record data

PubMed Central

Clegg, Andrew; Bates, Chris; Young, John; Ryan, Ronan; Nichols, Linda; Ann Teale, Elizabeth; Mohammed, Mohammed A.; Parry, John; Marshall, Tom

2016-01-01

Background: frailty is an especially problematic expression of population ageing. International guidelines recommend routine identification of frailty to provide evidence-based treatment, but currently available tools require additional resource. Objectives: to develop and validate an electronic frailty index (eFI) using routinely available primary care electronic health record data. Study design and setting: retrospective cohort study. Development and internal validation cohorts were established using a randomly split sample of the ResearchOne primary care database. External validation cohort established using THIN database. Participants: patients aged 65–95, registered with a ResearchOne or THIN practice on 14 October 2008. Predictors: we constructed the eFI using the cumulative deficit frailty model as our theoretical framework. The eFI score is calculated by the presence or absence of individual deficits as a proportion of the total possible. Categories of fit, mild, moderate and severe frailty were defined using population quartiles. Outcomes: outcomes were 1-, 3- and 5-year mortality, hospitalisation and nursing home admission. Statistical analysis: hazard ratios (HRs) were estimated using bivariate and multivariate Cox regression analyses. Discrimination was assessed using receiver operating characteristic (ROC) curves. Calibration was assessed using pseudo-R2 estimates. Results: we include data from a total of 931,541 patients. The eFI incorporates 36 deficits constructed using 2,171 CTV3 codes. One-year adjusted HR for mortality was 1.92 (95% CI 1.81–2.04) for mild frailty, 3.10 (95% CI 2.91–3.31) for moderate frailty and 4.52 (95% CI 4.16–4.91) for severe frailty. Corresponding estimates for hospitalisation were 1.93 (95% CI 1.86–2.01), 3.04 (95% CI 2.90–3.19) and 4.73 (95% CI 4.43–5.06) and for nursing home admission were 1.89 (95% CI 1.63–2.15), 3.19 (95% CI 2.73–3.73) and 4.76 (95% CI 3.92–5.77), with good to moderate discrimination but low calibration estimates. Conclusions: the eFI uses routine data to identify older people with mild, moderate and severe frailty, with robust predictive validity for outcomes of mortality, hospitalisation and nursing home admission. Routine implementation of the eFI could enable delivery of evidence-based interventions to improve outcomes for this vulnerable group. PMID:26944937

Quantifying annual internal effective 137Cesium dose utilizing direct body-burden measurement and ecological dose modeling.

PubMed

Jelin, Benjamin A; Sun, Wenjie; Kravets, Alexandra; Naboka, Maryna; Stepanova, Eugenia I; Vdovenko, Vitaliy Y; Karmaus, Wilfried J; Lichosherstov, Alex; Svendsen, Erik R

2016-11-01

The Chernobyl Nuclear Power Plant (CNPP) accident represents one of the most significant civilian releases of 137 Cesium ( 137 Cs, radiocesium) in human history. In the Chernobyl-affected region, radiocesium is considered to be the greatest on-going environmental hazard to human health by radiobiologists and public health scientists. The goal of this study was to characterize dosimetric patterns and predictive factors for whole-body count (WBC)-derived radiocesium internal dose estimations in a CNPP-affected children's cohort, and cross-validate these estimations with a soil-based ecological dose estimation model. WBC data were used to estimate the internal effective dose using the International Commission on Radiological Protection (ICRP) 67 dose conversion coefficient for 137 Cs and MONDAL Version 3.01 software. Geometric mean dose estimates from each model were compared utilizing paired t-tests and intra-class correlation coefficients. Additionally, we developed predictive models for WBC-derived dose estimation in order to determine the appropriateness of EMARC to estimate dose for this population. The two WBC-derived dose predictive models identified 137 Cs soil concentration (P<0.0001) as the strongest predictor of annual internal effective dose from radiocesium validating the use of the soil-based EMARC model. The geometric mean internal effective dose estimate of the EMARC model (0.183 mSv/y) was the highest followed by the ICRP 67 dose estimates (0.165 mSv/y) and the MONDAL model estimates (0.149 mSv/y). All three models yielded significantly different geometric mean dose (P<0.05) estimates for this cohort when stratified by sex, age at time of exam and season of exam, except for the mean MONDAL and EMARC estimates for 15- and 16-year olds and mean ICRP and MONDAL estimates for children examined in Winter. Further prospective and retrospective radio-epidemiological studies utilizing refined WBC measurements and ecological model dose estimations, in conjunction with findings from animal toxicological studies, should help elucidate possible deterministic radiogenic health effects associated with chronic low-dose internal exposure to 137 Cs.

Estimating GFR using Serum Cystatin C Alone and in Combination with Serum Creatinine: A Pooled Analysis of 3418 Individuals with CKD

PubMed Central

Stevens, Lesley A; Coresh, Josef; Schmid, Christopher H; Feldman, Harold I.; Froissart, Marc; Kusek, John; Rossert, Jerome; Van Lente, Frederick; Bruce, Robert D.; Zhang, Yaping (Lucy); Greene, Tom; Levey, Andrew S

2008-01-01

Background Serum cystatin C (Scys) has been proposed as a potential replacement for serum creatinine (Scr) in glomerular filtration rate (GFR) estimation. We report development and evaluation of GFR estimating equations using Scys alone and Scys, Scr or both with demographic variables. Study Design Test of diagnostic accuracy. Setting and Participants Participants screened for three chronic kidney disease (CKD) studies in the US (n=2980) and a clinical population in Paris, France (n=438) Reference Test Measured GFR (mGFR). Index Test Estimated GFR using the four new equations based on Scys alone, Scys, Scr or both with age, sex and race. New equations were developed using regression with log GFR as the outcome in 2/3 data from US studies. Internal validation was performed in remaining 1/3 of data from US CKD studies; external validation was performed in the Paris study. Measurements GFR was measured using urinary clearance of 125I-iothalamate in the US studies and chromium-ethylenediaminetetraacetate (51Cr-EDTA) in the Paris study. Scys was measured by Dade Behring assay, standardized Scr. Results Mean mGFR, Scr and Scys were 48 (5th–95th percentile 15–95) ml/min/1.73m2 2.1 mg/dL and 1.8 mg/L respectively. For the new equations, the coefficients for age, sex and race were significant in the equation with Scys but 2 to 4 fold smaller than in the equation with Scr. Measures of performance among new equations were consistent across development, internal and external validation datasets. Percent of eGFR within 30% of mGFR for equations based on Scys alone, Scys, Scr or both with age, sex and race were 81, 83, 85, and 89%, respectively. The equation using Scys alone yields estimates with small biases in age, sex and race subgroups, which are improved in equations including these variables. Limitations Study population composed mainly of patients with CKD. Conclusions Scys alone provides GFR estimates that are nearly as accurate as Scr adjusted for age, sex and race thus providing an alternative GFR estimate that is not linked to muscle mass. An equation including Scys in combination with Scr, age, sex and race provide most accurate estimates. PMID:18295055

Estimating Prevalence of Overweight or Obese Children and Adolescents in Small Geographic Areas Using Publicly Available Data

PubMed Central

Davila-Payan, Carlo; DeGuzman, Michael; Johnson, Kevin; Serban, Nicoleta

2015-01-01

Introduction Interventions for pediatric obesity can be geographically targeted if high-risk populations can be identified. We developed an approach to estimate the percentage of overweight or obese children aged 2 to 17 years in small geographic areas using publicly available data. We piloted our approach for Georgia. Methods We created a logistic regression model to estimate the individual probability of high body mass index (BMI), given data on the characteristics of the survey participants. We combined the regression model with a simulation to sample subpopulations and obtain prevalence estimates. The models used information from the 2001–2010 National Health and Nutrition Examination Survey, the 2010 Census, and the 2010 American Community Survey. We validated our results by comparing 1) estimates for adults in Georgia produced by using our approach with estimates from the Centers for Disease Control and Prevention (CDC) and 2) estimates for children in Arkansas produced by using our approach with school examination data. We generated prevalence estimates for census tracts in Georgia and prioritized areas for interventions. Results In DeKalb County, the mean prevalence among census tracts varied from 27% to 40%. For adults, the median difference between our estimates and CDC estimates was 1.3 percentage points; for Arkansas children, the median difference between our estimates and examination-based estimates data was 1.7 percentage points. Conclusion Prevalence estimates for census tracts can be different from estimates for the county, so small-area estimates are crucial for designing effective interventions. Our approach validates well against external data, and it can be a relevant aid for planning local interventions for children. PMID:25764138

Criterion-Related Validity of Sit-and-Reach Tests for Estimating Hamstring and Lumbar Extensibility: a Meta-Analysis

PubMed Central

Mayorga-Vega, Daniel; Merino-Marban, Rafael; Viciana, Jesús

2014-01-01

The main purpose of the present meta-analysis was to examine the scientific literature on the criterion-related validity of sit-and-reach tests for estimating hamstring and lumbar extensibility. For this purpose relevant studies were searched from seven electronic databases dated up through December 2012. Primary outcomes of criterion-related validity were Pearson´s zero-order correlation coefficients (r) between sit-and-reach tests and hamstrings and/or lumbar extensibility criterion measures. Then, from the included studies, the Hunter- Schmidt´s psychometric meta-analysis approach was conducted to estimate population criterion- related validity of sit-and-reach tests. Firstly, the corrected correlation mean (rp), unaffected by statistical artefacts (i.e., sampling error and measurement error), was calculated separately for each sit-and-reach test. Subsequently, the three potential moderator variables (sex of participants, age of participants, and level of hamstring extensibility) were examined by a partially hierarchical analysis. Of the 34 studies included in the present meta-analysis, 99 correlations values across eight sit-and-reach tests and 51 across seven sit-and-reach tests were retrieved for hamstring and lumbar extensibility, respectively. The overall results showed that all sit-and-reach tests had a moderate mean criterion-related validity for estimating hamstring extensibility (rp = 0.46-0.67), but they had a low mean for estimating lumbar extensibility (rp = 0. 16-0.35). Generally, females, adults and participants with high levels of hamstring extensibility tended to have greater mean values of criterion-related validity for estimating hamstring extensibility. When the use of angular tests is limited such as in a school setting or in large scale studies, scientists and practitioners could use the sit-and-reach tests as a useful alternative for hamstring extensibility estimation, but not for estimating lumbar extensibility. Key Points Overall sit-and-reach tests have a moderate mean criterion-related validity for estimating hamstring extensibility, but they have a low mean validity for estimating lumbar extensibility. Among all the sit-and-reach test protocols, the Classic sit-and-reach test seems to be the best option to estimate hamstring extensibility. End scores (e.g., the Classic sit-and-reach test) are a better indicator of hamstring extensibility than the modifications that incorporate fingers-to-box distance (e.g., the Modified sit-and-reach test). When angular tests such as straight leg raise or knee extension tests cannot be used, sit-and-reach tests seem to be a useful field test alternative to estimate hamstring extensibility, but not to estimate lumbar extensibility. PMID:24570599

Population-based absolute risk estimation with survey data

PubMed Central

Kovalchik, Stephanie A.; Pfeiffer, Ruth M.

2013-01-01

Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level. PMID:23686614

Wideband Direction of Arrival Estimation in the Presence of Unknown Mutual Coupling

PubMed Central

Li, Weixing; Zhang, Yue; Lin, Jianzhi; Guo, Rui; Chen, Zengping

2017-01-01

This paper investigates a subarray based algorithm for direction of arrival (DOA) estimation of wideband uniform linear array (ULA), under the presence of frequency-dependent mutual coupling effects. Based on the Toeplitz structure of mutual coupling matrices, the whole array is divided into the middle subarray and the auxiliary subarray. Then two-sided correlation transformation is applied to the correlation matrix of the middle subarray instead of the whole array. In this way, the mutual coupling effects can be eliminated. Finally, the multiple signal classification (MUSIC) method is utilized to derive the DOAs. For the condition when the blind angles exist, we refine DOA estimation by using a simple approach based on the frequency-dependent mutual coupling matrixes (MCMs). The proposed method can achieve high estimation accuracy without any calibration sources. It has a low computational complexity because iterative processing is not required. Simulation results validate the effectiveness and feasibility of the proposed algorithm. PMID:28178177

A Simulation Environment for Benchmarking Sensor Fusion-Based Pose Estimators.

PubMed

Ligorio, Gabriele; Sabatini, Angelo Maria

2015-12-19

In-depth analysis and performance evaluation of sensor fusion-based estimators may be critical when performed using real-world sensor data. For this reason, simulation is widely recognized as one of the most powerful tools for algorithm benchmarking. In this paper, we present a simulation framework suitable for assessing the performance of sensor fusion-based pose estimators. The systems used for implementing the framework were magnetic/inertial measurement units (MIMUs) and a camera, although the addition of further sensing modalities is straightforward. Typical nuisance factors were also included for each sensor. The proposed simulation environment was validated using real-life sensor data employed for motion tracking. The higher mismatch between real and simulated sensors was about 5% of the measured quantity (for the camera simulation), whereas a lower correlation was found for an axis of the gyroscope (0.90). In addition, a real benchmarking example of an extended Kalman filter for pose estimation from MIMU and camera data is presented.

Using RAQMS Chemical Transport Model, Aircraft In-situ and Satellite Data to Verify Ground-based Biomass Burning Emissions from the Extreme Fire Event in Boreal Alaska 2004

NASA Astrophysics Data System (ADS)

Soja, A. J.; Pierce, R. B.; Al-Saadi, J. A.; Alvarado, E.; Sandberg, D. V.; Ottmar, R. D.; Kittaka, C.; McMillian, W. W.; Sachse, G. W.; Warner, J. X.; Szykman, J. J.

2006-12-01

Current climate change scenarios are predicted to result in increased biomass burning, particularly in boreal regions. Biomass burning events feedback to the climate system by altering albedo (affecting the energy balance) and by direct and indirect fire emissions. Additionally, fire emissions influence air quality and human health downwind of burning. Biomass burning emission estimates are difficult to quantify in near-real-time and accurate estimates are useful for large-scale chemical transport models, which could be used to warn the public of potential health risks and for climate modeling. In this talk, we describe a methodology to quantify emissions, validate those emission estimates, transport the emissions and verify the resultant CO plume 100's of kilometers from the fire events using aircraft in-situ and satellite data. First, we developed carbon consumption estimates that are specifically designed for near-real-time use in conjunction with satellite-derived fire data for regional- to global-chemical transport models. Large-scale carbon consumption estimates are derived for 10 ecozones across North America and each zone contains 3 classes of severity. The estimates range is from a low severity 3.11 t C ha-1 estimate from the Western Taiga Shield to a high severity 59.83 t C ha-1 estimate from the Boreal Cordillera. These estimates are validated using extensive supplementary ground-based Alaskan data. Then, the RAQMS chemical transport model ingests these data and transports CO from the Alaskan 2004 fires across North America, where results are compared with in-situ flight CO data measured during INTEX-A and satellite-based CO data (AIRS and MOPITT). Ground-based CO is 6 to 14 times greater than the typically modeled fire climatology. RAQMS often overestimates CO in the biomass plumes in comparison to satellite- derived CO data and we suspect this may be due to the satellite instruments low sensitivity to planetary boundary layer CO, which is prevalent in the near field plumes, and also the assumption of high-severity fires throughout the burning season. RAQMS underestimates biomass CO in comparison to in-situ CO data (146 out of 148 ascents and descents), and we suspect this may be due to RAQMS difficulty in defining narrow fire plumes due to the 1.4° x 1.4° resolution.

A new validation technique for estimations of body segment inertia tensors: Principal axes of inertia do matter.

PubMed

Rossi, Marcel M; Alderson, Jacqueline; El-Sallam, Amar; Dowling, James; Reinbolt, Jeffrey; Donnelly, Cyril J

2016-12-08

The aims of this study were to: (i) establish a new criterion method to validate inertia tensor estimates by setting the experimental angular velocity data of an airborne objects as ground truth against simulations run with the estimated tensors, and (ii) test the sensitivity of the simulations to changes in the inertia tensor components. A rigid steel cylinder was covered with reflective kinematic markers and projected through a calibrated motion capture volume. Simulations of the airborne motion were run with two models, using inertia tensor estimated with geometric formula or the compound pendulum technique. The deviation angles between experimental (ground truth) and simulated angular velocity vectors and the root mean squared deviation angle were computed for every simulation. Monte Carlo analyses were performed to assess the sensitivity of simulations to changes in magnitude of principal moments of inertia within ±10% and to changes in orientation of principal axes of inertia within ±10° (of the geometric-based inertia tensor). Root mean squared deviation angles ranged between 2.9° and 4.3° for the inertia tensor estimated geometrically, and between 11.7° and 15.2° for the compound pendulum values. Errors up to 10% in magnitude of principal moments of inertia yielded root mean squared deviation angles ranging between 3.2° and 6.6°, and between 5.5° and 7.9° when lumped with errors of 10° in principal axes of inertia orientation. The proposed technique can effectively validate inertia tensors from novel estimation methods of body segment inertial parameter. Principal axes of inertia orientation should not be neglected when modelling human/animal mechanics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

PubMed

Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

2017-08-01

Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

Leaching of biocides from building facades: Upscaling of a local two-region leaching model to the city scale

NASA Astrophysics Data System (ADS)

Coutu, S.; Rota, C.; Rossi, L.; Barry, D. A.

2011-12-01

Facades are protected by paints that contain biocides as protection against degradation. These biocides are leached by rainfall (albeit at low concentrations). At the city scale, however, the surface area of building facades is significant, and leached biocides are a potential environmental risk to receiving waters. A city-scale biocide-leaching model was developed based on two main steps. In the first step, laboratory experiments on a single facade were used to calibrate and validate a 1D, two-region phenomenological model of biocide leaching. The same data set was analyzed independently by another research group who found empirically that biocide leachate breakthrough curves were well represented by a sum of two exponentials. Interestingly, the two-region model was found analytically to reproduce this functional form as a special case. The second step in the method is site-specific, and involves upscaling the validated single facade model to a particular city. In this step, (i) GIS-based estimates of facade heights and areas are deduced using the city's cadastral data, (ii) facade flow is estimated using local meteorological data (rainfall, wind direction) and (iii) paint application rates are modeled as a stochastic process based on manufacturers' recommendations. The methodology was applied to Lausanne, Switzerland, a city of about 200,000 inhabitants. Approximately 30% of the annually applied mass of biocides was estimated to be released to the environment.

Malaria Eradication and Educational Attainment: Evidence from Paraguay and Sri Lanka†

PubMed Central

Lucas, Adrienne M.

2013-01-01

Mid-twentieth century malaria eradication campaigns largely eliminated malaria from Paraguay and Sri Lanka. Using these interventions as quasi-experiments, I estimate malaria’s effect on lifetime female educational attainment through the combination of pre-existing geographic variation in malarial intensity and cohort exposure based on the timing of the national anti-malaria campaigns. The estimates from Sri Lanka and Paraguay are similar and indicate that malaria eradication increased years of educational attainment and literacy. The similarity of the estimates across the countries reinforces our confidence in the validity of the identification strategy. PMID:23946866

Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs)

NASA Astrophysics Data System (ADS)

Roushangar, Kiyoumars; Mehrabani, Fatemeh Vojoudi; Shiri, Jalal

2014-06-01

This study presents Artificial Intelligence (AI)-based modeling of total bed material load through developing the accuracy level of the predictions of traditional models. Gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS)-based models were developed and validated for estimations. Sediment data from Qotur River (Northwestern Iran) were used for developing and validation of the applied techniques. In order to assess the applied techniques in relation to traditional models, stream power-based and shear stress-based physical models were also applied in the studied case. The obtained results reveal that developed AI-based models using minimum number of dominant factors, give more accurate results than the other applied models. Nonetheless, it was revealed that k-fold test is a practical but high-cost technique for complete scanning of applied data and avoiding the over-fitting.

Concurrent validation of the Actigraph gt3x+, Polar Active accelerometer, Omron HJ-720 and Yamax Digiwalker SW-701 pedometer step counts in lab-based and free-living settings.

PubMed

Lee, Joey A; Williams, Skip M; Brown, Dale D; Laurson, Kelly R

2015-01-01

Activity monitors are frequently used to assess activity in many settings. But as technology advances, so do the mechanisms used to estimate activity causing a continuous need to validate newly developed monitors. The purpose of this study was to examine the step count validity of the Yamax Digiwalker SW-701 pedometer (YX), Omron HJ-720 T pedometer (OP), Polar Active accelerometer (PAC) and Actigraph gt3x+ accelerometer (AG) under controlled and free-living conditions. Participants completed five stages of treadmill walking (n = 43) and a subset of these completed a 3-day free-living wear period (n = 37). Manually counted (MC) steps provided a criterion measure for treadmill walking, whereas the comparative measure during free-living was the YX. During treadmill walking, the OP was the most accurate monitor across all speeds (±1.1% of MC steps), while the PAC underestimated steps by 6.7-16.0% per stage. During free-living, the OP and AG counted 97.5% and 98.5% of YX steps, respectively. The PAC overestimated steps by 44.0%, or 5,265 steps per day. The Omron pedometer seems to provide the most reliable and valid estimate of steps taken, as it was the best performer under lab-based conditions and provided comparable results to the YX in free-living. Future studies should consider these monitors in additional populations and settings.

From mess to mass: a methodology for calculating storm event pollutant loads with their uncertainties, from continuous raw data time series.

PubMed

Métadier, M; Bertrand-Krajewski, J-L

2011-01-01

With the increasing implementation of continuous monitoring of both discharge and water quality in sewer systems, large data bases are now available. In order to manage large amounts of data and calculate various variables and indicators of interest it is necessary to apply automated methods for data processing. This paper deals with the processing of short time step turbidity time series to estimate TSS (Total Suspended Solids) and COD (Chemical Oxygen Demand) event loads in sewer systems during storm events and their associated uncertainties. The following steps are described: (i) sensor calibration, (ii) estimation of data uncertainties, (iii) correction of raw data, (iv) data pre-validation tests, (v) final validation, and (vi) calculation of TSS and COD event loads and estimation of their uncertainties. These steps have been implemented in an integrated software tool. Examples of results are given for a set of 33 storm events monitored in a stormwater separate sewer system.