An Empirical Model for Estimating the Probability of Electrical Short Circuits from Tin Whiskers. Part 2

NASA Technical Reports Server (NTRS)

Courey, Karim; Wright, Clara; Asfour, Shihab; Onar, Arzu; Bayliss, Jon; Ludwig, Larry

2009-01-01

In this experiment, an empirical model to quantify the probability of occurrence of an electrical short circuit from tin whiskers as a function of voltage was developed. This empirical model can be used to improve existing risk simulation models. FIB and TEM images of a tin whisker confirm the rare polycrystalline structure on one of the three whiskers studied. FIB cross-section of the card guides verified that the tin finish was bright tin.

Development of an Empirical Model for Optimization of Machining Parameters to Minimize Power Consumption

NASA Astrophysics Data System (ADS)

Kant Garg, Girish; Garg, Suman; Sangwan, K. S.

2018-04-01

The manufacturing sector consumes huge energy demand and the machine tools used in this sector have very less energy efficiency. Selection of the optimum machining parameters for machine tools is significant for energy saving and for reduction of environmental emission. In this work an empirical model is developed to minimize the power consumption using response surface methodology. The experiments are performed on a lathe machine tool during the turning of AISI 6061 Aluminum with coated tungsten inserts. The relationship between the power consumption and machining parameters is adequately modeled. This model is used for formulation of minimum power consumption criterion as a function of optimal machining parameters using desirability function approach. The influence of machining parameters on the energy consumption has been found using the analysis of variance. The validation of the developed empirical model is proved using the confirmation experiments. The results indicate that the developed model is effective and has potential to be adopted by the industry for minimum power consumption of machine tools.

Assessment of Prevalence of Persons with Down Syndrome: A Theory-Based Demographic Model

ERIC Educational Resources Information Center

de Graaf, Gert; Vis, Jeroen C.; Haveman, Meindert; van Hove, Geert; de Graaf, Erik A. B.; Tijssen, Jan G. P.; Mulder, Barbara J. M.

2011-01-01

Background: The Netherlands are lacking reliable empirical data in relation to the development of birth and population prevalence of Down syndrome. For the UK and Ireland there are more historical empirical data available. A theory-based model is developed for predicting Down syndrome prevalence in the Netherlands from the 1950s onwards. It is…

Disorders without borders: current and future directions in the meta-structure of mental disorders.

PubMed

Carragher, Natacha; Krueger, Robert F; Eaton, Nicholas R; Slade, Tim

2015-03-01

Classification is the cornerstone of clinical diagnostic practice and research. However, the extant psychiatric classification systems are not well supported by research evidence. In particular, extensive comorbidity among putatively distinct disorders flags an urgent need for fundamental changes in how we conceptualize psychopathology. Over the past decade, research has coalesced on an empirically based model that suggests many common mental disorders are structured according to two correlated latent dimensions: internalizing and externalizing. We review and discuss the development of a dimensional-spectrum model which organizes mental disorders in an empirically based manner. We also touch upon changes in the DSM-5 and put forward recommendations for future research endeavors. Our review highlights substantial empirical support for the empirically based internalizing-externalizing model of psychopathology, which provides a parsimonious means of addressing comorbidity. As future research goals, we suggest that the field would benefit from: expanding the meta-structure of psychopathology to include additional disorders, development of empirically based thresholds, inclusion of a developmental perspective, and intertwining genomic and neuroscience dimensions with the empirical structure of psychopathology.

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

Measurements and empirical model of the acoustic properties of reticulated vitreous carbon.

PubMed

Muehleisena, Ralph T; Beamer, C Walter; Tinianov, Brandon D

2005-02-01

Reticulated vitreous carbon (RVC) is a highly porous, rigid, open cell carbon foam structure with a high melting point, good chemical inertness, and low bulk thermal conductivity. For the proper design of acoustic devices such as acoustic absorbers and thermoacoustic stacks and regenerators utilizing RVC, the acoustic properties of RVC must be known. From knowledge of the complex characteristic impedance and wave number most other acoustic properties can be computed. In this investigation, the four-microphone transfer matrix measurement method is used to measure the complex characteristic impedance and wave number for 60 to 300 pore-per-inch RVC foams with flow resistivities from 1759 to 10,782 Pa s m(-2) in the frequency range of 330 Hz-2 kHz. The data are found to be poorly predicted by the fibrous material empirical model developed by Delany and Bazley, the open cell plastic foam empirical model developed by Qunli, or the Johnson-Allard microstructural model. A new empirical power law model is developed and is shown to provide good predictions of the acoustic properties over the frequency range of measurement. Uncertainty estimates for the constants of the model are also computed.

Measurements and empirical model of the acoustic properties of reticulated vitreous carbon

NASA Astrophysics Data System (ADS)

Muehleisen, Ralph T.; Beamer, C. Walter; Tinianov, Brandon D.

2005-02-01

Reticulated vitreous carbon (RVC) is a highly porous, rigid, open cell carbon foam structure with a high melting point, good chemical inertness, and low bulk thermal conductivity. For the proper design of acoustic devices such as acoustic absorbers and thermoacoustic stacks and regenerators utilizing RVC, the acoustic properties of RVC must be known. From knowledge of the complex characteristic impedance and wave number most other acoustic properties can be computed. In this investigation, the four-microphone transfer matrix measurement method is used to measure the complex characteristic impedance and wave number for 60 to 300 pore-per-inch RVC foams with flow resistivities from 1759 to 10 782 Pa s m-2 in the frequency range of 330 Hz-2 kHz. The data are found to be poorly predicted by the fibrous material empirical model developed by Delany and Bazley, the open cell plastic foam empirical model developed by Qunli, or the Johnson-Allard microstructural model. A new empirical power law model is developed and is shown to provide good predictions of the acoustic properties over the frequency range of measurement. Uncertainty estimates for the constants of the model are also computed. .

An empirical approach to estimate near-infra-red photon propagation and optically induced drug release in brain tissues

NASA Astrophysics Data System (ADS)

Prabhu Verleker, Akshay; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M.

2015-03-01

The purpose of this study is to develop an alternate empirical approach to estimate near-infra-red (NIR) photon propagation and quantify optically induced drug release in brain metastasis, without relying on computationally expensive Monte Carlo techniques (gold standard). Targeted drug delivery with optically induced drug release is a noninvasive means to treat cancers and metastasis. This study is part of a larger project to treat brain metastasis by delivering lapatinib-drug-nanocomplexes and activating NIR-induced drug release. The empirical model was developed using a weighted approach to estimate photon scattering in tissues and calibrated using a GPU based 3D Monte Carlo. The empirical model was developed and tested against Monte Carlo in optical brain phantoms for pencil beams (width 1mm) and broad beams (width 10mm). The empirical algorithm was tested against the Monte Carlo for different albedos along with diffusion equation and in simulated brain phantoms resembling white-matter (μs'=8.25mm-1, μa=0.005mm-1) and gray-matter (μs'=2.45mm-1, μa=0.035mm-1) at wavelength 800nm. The goodness of fit between the two models was determined using coefficient of determination (R-squared analysis). Preliminary results show the Empirical algorithm matches Monte Carlo simulated fluence over a wide range of albedo (0.7 to 0.99), while the diffusion equation fails for lower albedo. The photon fluence generated by empirical code matched the Monte Carlo in homogeneous phantoms (R2=0.99). While GPU based Monte Carlo achieved 300X acceleration compared to earlier CPU based models, the empirical code is 700X faster than the Monte Carlo for a typical super-Gaussian laser beam.

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

PubMed Central

Gray, Veronica; Whittaker, Mark

2015-01-01

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

A quantitative dynamic systems model of health-related quality of life among older adults

PubMed Central

Roppolo, Mattia; Kunnen, E Saskia; van Geert, Paul L; Mulasso, Anna; Rabaglietti, Emanuela

2015-01-01

Health-related quality of life (HRQOL) is a person-centered concept. The analysis of HRQOL is highly relevant in the aged population, which is generally suffering from health decline. Starting from a conceptual dynamic systems model that describes the development of HRQOL in individuals over time, this study aims to develop and test a quantitative dynamic systems model, in order to reveal the possible dynamic trends of HRQOL among older adults. The model is tested in different ways: first, with a calibration procedure to test whether the model produces theoretically plausible results, and second, with a preliminary validation procedure using empirical data of 194 older adults. This first validation tested the prediction that given a particular starting point (first empirical data point), the model will generate dynamic trajectories that lead to the observed endpoint (second empirical data point). The analyses reveal that the quantitative model produces theoretically plausible trajectories, thus providing support for the calibration procedure. Furthermore, the analyses of validation show a good fit between empirical and simulated data. In fact, no differences were found in the comparison between empirical and simulated final data for the same subgroup of participants, whereas the comparison between different subgroups of people resulted in significant differences. These data provide an initial basis of evidence for the dynamic nature of HRQOL during the aging process. Therefore, these data may give new theoretical and applied insights into the study of HRQOL and its development with time in the aging population. PMID:26604722

A simple empirical model for the clarification-thickening process in wastewater treatment plants.

PubMed

Zhang, Y K; Wang, H C; Qi, L; Liu, G H; He, Z J; Fan, H T

2015-01-01

In wastewater treatment plants (WWTPs), activated sludge is thickened in secondary settling tanks and recycled into the biological reactor to maintain enough biomass for wastewater treatment. Accurately estimating the activated sludge concentration in the lower portion of the secondary clarifiers is of great importance for evaluating and controlling the sludge recycled ratio, ensuring smooth and efficient operation of the WWTP. By dividing the overall activated sludge-thickening curve into a hindered zone and a compression zone, an empirical model describing activated sludge thickening in the compression zone was obtained by empirical regression. This empirical model was developed through experiments conducted using sludge from five WWTPs, and validated by the measured data from a sixth WWTP, which fit the model well (R² = 0.98, p < 0.001). The model requires application of only one parameter, the sludge volume index (SVI), which is readily incorporated into routine analysis. By combining this model with the conservation of mass equation, an empirical model for compression settling was also developed. Finally, the effects of denitrification and addition of a polymer were also analysed because of their effect on sludge thickening, which can be useful for WWTP operation, e.g., improving wastewater treatment or the proper use of the polymer.

Machine learning strategies for systems with invariance properties

NASA Astrophysics Data System (ADS)

Ling, Julia; Jones, Reese; Templeton, Jeremy

2016-08-01

In many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds Averaged Navier Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high performance computing has led to a growing availability of high fidelity simulation data. These data open up the possibility of using machine learning algorithms, such as random forests or neural networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these empirical models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first method, a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance at significantly reduced computational training costs.

Development of a hybrid modeling approach for predicting intensively managed Douglas-fir growth at multiple scales.

Treesearch

A. Weiskittel; D. Maguire; R. Monserud

2007-01-01

Hybrid models offer the opportunity to improve future growth projections by combining advantages of both empirical and process-based modeling approaches. Hybrid models have been constructed in several regions and their performance relative to a purely empirical approach has varied. A hybrid model was constructed for intensively managed Douglas-fir plantations in the...

Modeling of Principal Flank Wear: An Empirical Approach Combining the Effect of Tool, Environment and Workpiece Hardness

NASA Astrophysics Data System (ADS)

Mia, Mozammel; Al Bashir, Mahmood; Dhar, Nikhil Ranjan

2016-10-01

Hard turning is increasingly employed in machining, lately, to replace time-consuming conventional turning followed by grinding process. An excessive amount of tool wear in hard turning is one of the main hurdles to be overcome. Many researchers have developed tool wear model, but most of them developed it for a particular work-tool-environment combination. No aggregate model is developed that can be used to predict the amount of principal flank wear for specific machining time. An empirical model of principal flank wear (VB) has been developed for the different hardness of workpiece (HRC40, HRC48 and HRC56) while turning by coated carbide insert with different configurations (SNMM and SNMG) under both dry and high pressure coolant conditions. Unlike other developed model, this model includes the use of dummy variables along with the base empirical equation to entail the effect of any changes in the input conditions on the response. The base empirical equation for principal flank wear is formulated adopting the Exponential Associate Function using the experimental results. The coefficient of dummy variable reflects the shifting of the response from one set of machining condition to another set of machining condition which is determined by simple linear regression. The independent cutting parameters (speed, rate, depth of cut) are kept constant while formulating and analyzing this model. The developed model is validated with different sets of machining responses in turning hardened medium carbon steel by coated carbide inserts. For any particular set, the model can be used to predict the amount of principal flank wear for specific machining time. Since the predicted results exhibit good resemblance with experimental data and the average percentage error is <10 %, this model can be used to predict the principal flank wear for stated conditions.

Empirical modeling of Single-Event Upset (SEU) in NMOS depletion-mode-load static RAM (SRAM) chips

NASA Technical Reports Server (NTRS)

Zoutendyk, J. A.; Smith, L. S.; Soli, G. A.; Smith, S. L.; Atwood, G. E.

1986-01-01

A detailed experimental investigation of single-event upset (SEU) in static RAM (SRAM) chips fabricated using a family of high-performance NMOS (HMOS) depletion-mode-load process technologies, has been done. Empirical SEU models have been developed with the aid of heavy-ion data obtained with a three-stage tandem van de Graaff accelerator. The results of this work demonstrate a method by which SEU may be empirically modeled in NMOS integrated circuits.

An empirical model for optimal highway durability in cold regions.

DOT National Transportation Integrated Search

2016-03-10

We develop an empirical tool to estimate optimal highway durability in cold regions. To test the model, we assemble a data set : containing all highway construction and maintenance projects in Arizona and Washington State from 1990 to 2014. The data ...

Development, Testing, and Validation of a Model-Based Tool to Predict Operator Responses in Unexpected Workload Transitions

NASA Technical Reports Server (NTRS)

Sebok, Angelia; Wickens, Christopher; Sargent, Robert

2015-01-01

One human factors challenge is predicting operator performance in novel situations. Approaches such as drawing on relevant previous experience, and developing computational models to predict operator performance in complex situations, offer potential methods to address this challenge. A few concerns with modeling operator performance are that models need to realistic, and they need to be tested empirically and validated. In addition, many existing human performance modeling tools are complex and require that an analyst gain significant experience to be able to develop models for meaningful data collection. This paper describes an effort to address these challenges by developing an easy to use model-based tool, using models that were developed from a review of existing human performance literature and targeted experimental studies, and performing an empirical validation of key model predictions.

Satellite-based empirical models linking river plume dynamics with hypoxic area andvolume

EPA Science Inventory

Satellite-based empirical models explaining hypoxic area and volume variation were developed for the seasonally hypoxic (O2 < 2 mg L−1) northern Gulf of Mexico adjacent to the Mississippi River. Annual variations in midsummer hypoxic area and ...

Econometrics of exhaustible resource supply: a theory and an application

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

Epple, D.

1983-01-01

This report takes a major step toward developing a fruitful approach to empirical analysis of resource supply. It is the first empirical application of resource theory that has successfully integrated the effects of depletion of nonrenewable resources with the effects of uncertainty about future costs and prices on supply behavior. Thus, the model is a major improvement over traditional engineering-optimization models that assume complete certainty, and over traditional econometrics models that are only implicitly related to the theory of resource supply. The model is used to test hypotheses about interdependence of oil and natural gas discoveries, depletion, ultimate recovery, andmore » the role of price expectations. This paper demonstrates the feasibility of using exhaustible resource theory in the development of empirically testable models. 19 refs., 1 fig., 5 tabs.« less

Robust categorization of microfacet BRDF models to enable flexible application-specific BRDF adaptation

NASA Astrophysics Data System (ADS)

Butler, Samuel D.; Marciniak, Michael A.

2014-09-01

Since the development of the Torrance-Sparrow bidirectional re ectance distribution function (BRDF) model in 1967, several BRDF models have been created. Previous attempts to categorize BRDF models have relied upon somewhat vague descriptors, such as empirical, semi-empirical, and experimental. Our approach is to instead categorize BRDF models based on functional form: microfacet normal distribution, geometric attenua- tion, directional-volumetric and Fresnel terms, and cross section conversion factor. Several popular microfacet models are compared to a standardized notation for a microfacet BRDF model. A library of microfacet model components is developed, allowing for creation of unique microfacet models driven by experimentally measured BRDFs.

Predicting plot soil loss by empirical and process-oriented approaches: A review

USDA-ARS?s Scientific Manuscript database

Soil erosion directly affects the quality of the soil, its agricultural productivity and its biological diversity. Many mathematical models have been developed to estimate plot soil erosion at different temporal scales. At present, empirical soil loss equations and process-oriented models are consid...

GPP in Loblolly Pine: A Monthly Comparison of Empirical and Process Models

Treesearch

Christopher Gough; John Seiler; Kurt Johnsen; David Arthur Sampson

2002-01-01

Monthly and yearly gross primary productivity (GPP) estimates derived from an empirical and two process based models (3PG and BIOMASS) were compared. Spatial and temporal variation in foliar gas photosynthesis was examined and used to develop GPP prediction models for fertilized nine-year-old loblolly pine (Pinus taeda) stands located in the North...

Development of Mathematical Literacy: Results of an Empirical Study

ERIC Educational Resources Information Center

Kaiser, Gabriele; Willander, Torben

2005-01-01

In the paper the results of an empirical study, which has evaluated the development of mathematical literacy in an innovative teaching programme, are presented. The theoretical approach of mathematical literacy relies strongly on applications and modelling and the study follows the approach of R. Bybee, who develops a theoretical concept of…

Empirical and semi-analytical models for predicting peak outflows caused by embankment dam failures

NASA Astrophysics Data System (ADS)

Wang, Bo; Chen, Yunliang; Wu, Chao; Peng, Yong; Song, Jiajun; Liu, Wenjun; Liu, Xin

2018-07-01

Prediction of peak discharge of floods has attracted great attention for researchers and engineers. In present study, nine typical nonlinear mathematical models are established based on database of 40 historical dam failures. The first eight models that were developed with a series of regression analyses are purely empirical, while the last one is a semi-analytical approach that was derived from an analytical solution of dam-break floods in a trapezoidal channel. Water depth above breach invert (Hw), volume of water stored above breach invert (Vw), embankment length (El), and average embankment width (Ew) are used as independent variables to develop empirical formulas of estimating the peak outflow from breached embankment dams. It is indicated from the multiple regression analysis that a function using the former two variables (i.e., Hw and Vw) produce considerably more accurate results than that using latter two variables (i.e., El and Ew). It is shown that the semi-analytical approach works best in terms of both prediction accuracy and uncertainty, and the established empirical models produce considerably reasonable results except the model only using El. Moreover, present models have been compared with other models available in literature for estimating peak discharge.

From Positive Youth Development to Youth's Engagement: The Dream Teens

ERIC Educational Resources Information Center

Gaspar de Matos, Margarida; Simões, Celeste

2016-01-01

In addition to the empirical validation of "health and happiness" determinants, theoretical models suggesting where to ground actions are necessary. In the beginning of the twentieth century, intervention models focused on evaluation and empirical validation were only concerned about overt behaviours (verbal and non-verbal) and covert…

Combining DSMC Simulations and ROSINA/COPS Data of Comet 67P/Churyumov-Gerasimenko to Develop a Realistic Empirical Coma Model and to Determine Accurate Production Rates

NASA Astrophysics Data System (ADS)

Hansen, K. C.; Fougere, N.; Bieler, A. M.; Altwegg, K.; Combi, M. R.; Gombosi, T. I.; Huang, Z.; Rubin, M.; Tenishev, V.; Toth, G.; Tzou, C. Y.

2015-12-01

We have previously published results from the AMPS DSMC (Adaptive Mesh Particle Simulator Direct Simulation Monte Carlo) model and its characterization of the neutral coma of comet 67P/Churyumov-Gerasimenko through detailed comparison with data collected by the ROSINA/COPS (Rosetta Orbiter Spectrometer for Ion and Neutral Analysis/COmet Pressure Sensor) instrument aboard the Rosetta spacecraft [Bieler, 2015]. Results from these DSMC models have been used to create an empirical model of the near comet coma (<200 km) of comet 67P. The empirical model characterizes the neutral coma in a comet centered, sun fixed reference frame as a function of heliocentric distance, radial distance from the comet, local time and declination. The model is a significant improvement over more simple empirical models, such as the Haser model. While the DSMC results are a more accurate representation of the coma at any given time, the advantage of a mean state, empirical model is the ease and speed of use. One use of such an empirical model is in the calculation of a total cometary coma production rate from the ROSINA/COPS data. The COPS data are in situ measurements of gas density and velocity along the ROSETTA spacecraft track. Converting the measured neutral density into a production rate requires knowledge of the neutral gas distribution in the coma. Our empirical model provides this information and therefore allows us to correct for the spacecraft location to calculate a production rate as a function of heliocentric distance. We will present the full empirical model as well as the calculated neutral production rate for the period of August 2014 - August 2015 (perihelion).

Sorption and reemission of formaldehyde by gypsum wallboard. Report for June 1990-August 1992

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

Chang, J.C.S.

1993-01-01

The paper gives results of an analysis of the sorption and desorption of formaldehyde by unpainted wallboard, using a mass transfer model based on the Langmuir sorption isotherm. The sorption and desorption rate constants are determined by short-term experimental data. Long-term sorption and desorption curves are developed by the mass transfer model without any adjustable parameters. Compared with other empirically developed models, the mass transfer model has more extensive applicability and provides an elucidation of the sorption and desorption mechanism that empirical models cannot. The mass transfer model is also more feasible and accurate than empirical models for applications suchmore » as scale-up and exposure assessment. For a typical indoor environment, the model predicts that gypsum wallboard is a much stronger sink for formaldehyde than for other indoor air pollutants such as tetrachloroethylene and ethylbenzene. The strong sink effects are reflected by the high equilibrium capacity and slow decay of the desorption curve.« less

Theoretical models of parental HIV disclosure: a critical review.

PubMed

Qiao, Shan; Li, Xiaoming; Stanton, Bonita

2013-01-01

This study critically examined three major theoretical models related to parental HIV disclosure (i.e., the Four-Phase Model [FPM], the Disclosure Decision Making Model [DDMM], and the Disclosure Process Model [DPM]), and the existing studies that could provide empirical support to these models or their components. For each model, we briefly reviewed its theoretical background, described its components and/or mechanisms, and discussed its strengths and limitations. The existing empirical studies supported most theoretical components in these models. However, hypotheses related to the mechanisms proposed in the models have not yet tested due to a lack of empirical evidence. This study also synthesized alternative theoretical perspectives and new issues in disclosure research and clinical practice that may challenge the existing models. The current study underscores the importance of including components related to social and cultural contexts in theoretical frameworks, and calls for more adequately designed empirical studies in order to test and refine existing theories and to develop new ones.

An empirical/theoretical model with dimensionless numbers to predict the performance of electrodialysis systems on the basis of operating conditions.

PubMed

Karimi, Leila; Ghassemi, Abbas

2016-07-01

Among the different technologies developed for desalination, the electrodialysis/electrodialysis reversal (ED/EDR) process is one of the most promising for treating brackish water with low salinity when there is high risk of scaling. Multiple researchers have investigated ED/EDR to optimize the process, determine the effects of operating parameters, and develop theoretical/empirical models. Previously published empirical/theoretical models have evaluated the effect of the hydraulic conditions of the ED/EDR on the limiting current density using dimensionless numbers. The reason for previous studies' emphasis on limiting current density is twofold: 1) to maximize ion removal, most ED/EDR systems are operated close to limiting current conditions if there is not a scaling potential in the concentrate chamber due to a high concentration of less-soluble salts; and 2) for modeling the ED/EDR system with dimensionless numbers, it is more accurate and convenient to use limiting current density, where the boundary layer's characteristics are known at constant electrical conditions. To improve knowledge of ED/EDR systems, ED/EDR models should be also developed for the Ohmic region, where operation reduces energy consumption, facilitates targeted ion removal, and prolongs membrane life compared to limiting current conditions. In this paper, theoretical/empirical models were developed for ED/EDR performance in a wide range of operating conditions. The presented ion removal and selectivity models were developed for the removal of monovalent ions and divalent ions utilizing the dominant dimensionless numbers obtained from laboratory scale electrodialysis experiments. At any system scale, these models can predict ED/EDR performance in terms of monovalent and divalent ion removal. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparing Multidimensional and Continuum Models of Vocabulary Acquisition: An Empirical Examination of the Vocabulary Knowledge Scale

ERIC Educational Resources Information Center

Stewart, Jeffrey; Batty, Aaron Olaf; Bovee, Nicholas

2012-01-01

Second language vocabulary acquisition has been modeled both as multidimensional in nature and as a continuum wherein the learner's knowledge of a word develops along a cline from recognition through production. In order to empirically examine and compare these models, the authors assess the degree to which the Vocabulary Knowledge Scale (VKS;…

The Waterfall Model in Large-Scale Development

NASA Astrophysics Data System (ADS)

Petersen, Kai; Wohlin, Claes; Baca, Dejan

Waterfall development is still a widely used way of working in software development companies. Many problems have been reported related to the model. Commonly accepted problems are for example to cope with change and that defects all too often are detected too late in the software development process. However, many of the problems mentioned in literature are based on beliefs and experiences, and not on empirical evidence. To address this research gap, we compare the problems in literature with the results of a case study at Ericsson AB in Sweden, investigating issues in the waterfall model. The case study aims at validating or contradicting the beliefs of what the problems are in waterfall development through empirical research.

The Storm Time Ring Current Dynamics and Response to CMEs and CIRs Using Van Allen Probes Observations and CIMI Simulations

NASA Astrophysics Data System (ADS)

Bingham, S.; Mouikis, C.; Kistler, L. M.; Fok, M. C. H.; Glocer, A.; Farrugia, C. J.; Gkioulidou, M.; Spence, H. E.

2016-12-01

The ring current responds differently to the different solar and interplanetary storm drivers such as coronal mass injections, (CMEs), and co-rotating interaction regions (CIRs). Delineating the differences in the ring current development between these two drivers will aid our understanding of the ring current dynamics. Using Van Allen Probes observations, we develop an empirical ring current model of the ring current pressure, the pressure anisotropy and the current density development during the storm phases for both types of storm drivers and for all MLTs inside L 6. In addition, we identify the populations (energy and species) responsible. We find that during the storm main phase and the early recovery phase the plasma sheet particles (10-80 keV) convecting from the nightside contribute the most on the ring current pressure and current density. However, during these phases, the main difference between CMEs and CIRs is in the O+ contribution. This empirical model is compared to the results of CIMI simulations of CMEs and CIRs where the model input is comprised of the superposed epoch solar wind conditions of the storms that comprise the empirical model, while different inner magnetosphere boundary conditions will be tested in order to match the empirical model results. Comparing the model and simulation results will fill our understanding of the ring current dynamics as part of the highly coupled inner magnetosphere system.

Time-varying volatility in Malaysian stock exchange: An empirical study using multiple-volatility-shift fractionally integrated model

NASA Astrophysics Data System (ADS)

Cheong, Chin Wen

2008-02-01

This article investigated the influences of structural breaks on the fractionally integrated time-varying volatility model in the Malaysian stock markets which included the Kuala Lumpur composite index and four major sectoral indices. A fractionally integrated time-varying volatility model combined with sudden changes is developed to study the possibility of structural change in the empirical data sets. Our empirical results showed substantial reduction in fractional differencing parameters after the inclusion of structural change during the Asian financial and currency crises. Moreover, the fractionally integrated model with sudden change in volatility performed better in the estimation and specification evaluations.

Are Model Transferability And Complexity Antithetical? Insights From Validation of a Variable-Complexity Empirical Snow Model in Space and Time

NASA Astrophysics Data System (ADS)

Lute, A. C.; Luce, Charles H.

2017-11-01

The related challenges of predictions in ungauged basins and predictions in ungauged climates point to the need to develop environmental models that are transferable across both space and time. Hydrologic modeling has historically focused on modelling one or only a few basins using highly parameterized conceptual or physically based models. However, model parameters and structures have been shown to change significantly when calibrated to new basins or time periods, suggesting that model complexity and model transferability may be antithetical. Empirical space-for-time models provide a framework within which to assess model transferability and any tradeoff with model complexity. Using 497 SNOTEL sites in the western U.S., we develop space-for-time models of April 1 SWE and Snow Residence Time based on mean winter temperature and cumulative winter precipitation. The transferability of the models to new conditions (in both space and time) is assessed using non-random cross-validation tests with consideration of the influence of model complexity on transferability. As others have noted, the algorithmic empirical models transfer best when minimal extrapolation in input variables is required. Temporal split-sample validations use pseudoreplicated samples, resulting in the selection of overly complex models, which has implications for the design of hydrologic model validation tests. Finally, we show that low to moderate complexity models transfer most successfully to new conditions in space and time, providing empirical confirmation of the parsimony principal.

Path integral for equities: Dynamic correlation and empirical analysis

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.; Cao, Yang; Lau, Ada; Tang, Pan

2012-02-01

This paper develops a model to describe the unequal time correlation between rate of returns of different stocks. A non-trivial fourth order derivative Lagrangian is defined to provide an unequal time propagator, which can be fitted to the market data. A calibration algorithm is designed to find the empirical parameters for this model and different de-noising methods are used to capture the signals concealed in the rate of return. The detailed results of this Gaussian model show that the different stocks can have strong correlation and the empirical unequal time correlator can be described by the model's propagator. This preliminary study provides a novel model for the correlator of different instruments at different times.

Development of An Empirical Water Quality Model for Stormwater Based on Watershed Land Use in Puget Sound

DTIC Science & Technology

2007-03-29

Development of An Empirical Water Quality Model for Stormwater Based on Watershed Land Use in Puget Sound Valerie I. Cullinan, Christopher W. May...Systems Center, Bremerton, WA) Introduction The Sinclair and Dyes Inlet watershed is located on the west side of Puget Sound in Kitsap County...Washington, U.S.A. (Figure 1). The Puget Sound Naval Shipyard (PSNS), U.S Environmental Protection Agency (USEPA), the Washington State Department of

SPECTRAL data-based estimation of soil heat flux

USGS Publications Warehouse

Singh, Ramesh K.; Irmak, A.; Walter-Shea, Elizabeth; Verma, S.B.; Suyker, A.E.

2011-01-01

Numerous existing spectral-based soil heat flux (G) models have shown wide variation in performance for maize and soybean cropping systems in Nebraska, indicating the need for localized calibration and model development. The objectives of this article are to develop a semi-empirical model to estimate G from a normalized difference vegetation index (NDVI) and net radiation (Rn) for maize (Zea mays L.) and soybean (Glycine max L.) fields in the Great Plains, and present the suitability of the developed model to estimate G under similar and different soil and management conditions. Soil heat fluxes measured in both irrigated and rainfed fields in eastern and south-central Nebraska were used for model development and validation. An exponential model that uses NDVI and Rn was found to be the best to estimate G based on r2 values. The effect of geographic location, crop, and water management practices were used to develop semi-empirical models under four case studies. Each case study has the same exponential model structure but a different set of coefficients and exponents to represent the crop, soil, and management practices. Results showed that the semi-empirical models can be used effectively for G estimation for nearby fields with similar soil properties for independent years, regardless of differences in crop type, crop rotation, and irrigation practices, provided that the crop residue from the previous year is more than 4000 kg ha-1. The coefficients calibrated from particular fields can be used at nearby fields in order to capture temporal variation in G. However, there is a need for further investigation of the models to account for the interaction effects of crop rotation and irrigation. Validation at an independent site having different soil and crop management practices showed the limitation of the semi-empirical model in estimating G under different soil and environment conditions.

A Unified Model of Knowledge Sharing Behaviours: Theoretical Development and Empirical Test

ERIC Educational Resources Information Center

Chennamaneni, Anitha; Teng, James T. C.; Raja, M. K.

2012-01-01

Research and practice on knowledge management (KM) have shown that information technology alone cannot guarantee that employees will volunteer and share knowledge. While previous studies have linked motivational factors to knowledge sharing (KS), we took a further step to thoroughly examine this theoretically and empirically. We developed a…

A methodology for reduced order modeling and calibration of the upper atmosphere

NASA Astrophysics Data System (ADS)

Mehta, Piyush M.; Linares, Richard

2017-10-01

Atmospheric drag is the largest source of uncertainty in accurately predicting the orbit of satellites in low Earth orbit (LEO). Accurately predicting drag for objects that traverse LEO is critical to space situational awareness. Atmospheric models used for orbital drag calculations can be characterized either as empirical or physics-based (first principles based). Empirical models are fast to evaluate but offer limited real-time predictive/forecasting ability, while physics based models offer greater predictive/forecasting ability but require dedicated parallel computational resources. Also, calibration with accurate data is required for either type of models. This paper presents a new methodology based on proper orthogonal decomposition toward development of a quasi-physical, predictive, reduced order model that combines the speed of empirical and the predictive/forecasting capabilities of physics-based models. The methodology is developed to reduce the high dimensionality of physics-based models while maintaining its capabilities. We develop the methodology using the Naval Research Lab's Mass Spectrometer Incoherent Scatter model and show that the diurnal and seasonal variations can be captured using a small number of modes and parameters. We also present calibration of the reduced order model using the CHAMP and GRACE accelerometer-derived densities. Results show that the method performs well for modeling and calibration of the upper atmosphere.

Theoretical and Empirical Descriptions of Thermospheric Density

NASA Astrophysics Data System (ADS)

Solomon, S. C.; Qian, L.

2004-12-01

The longest-term and most accurate overall description the density of the upper thermosphere is provided by analysis of change in the ephemeris of Earth-orbiting satellites. Empirical models of the thermosphere developed in part from these measurements can do a reasonable job of describing thermospheric properties on a climatological basis, but the promise of first-principles global general circulation models of the coupled thermosphere/ionosphere system is that a true high-resolution, predictive capability may ultimately be developed for thermospheric density. However, several issues are encountered when attempting to tune such models so that they accurately represent absolute densities as a function of altitude, and their changes on solar-rotational and solar-cycle time scales. Among these are the crucial ones of getting the heating rates (from both solar and auroral sources) right, getting the cooling rates right, and establishing the appropriate boundary conditions. However, there are several ancillary issues as well, such as the problem of registering a pressure-coordinate model onto an altitude scale, and dealing with possible departures from hydrostatic equilibrium in empirical models. Thus, tuning a theoretical model to match empirical climatology may be difficult, even in the absence of high temporal or spatial variation of the energy sources. We will discuss some of the challenges involved, and show comparisons of simulations using the NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM) to empirical model estimates of neutral thermosphere density and temperature. We will also show some recent simulations using measured solar irradiance from the TIMED/SEE instrument as input to the TIE-GCM.

Machine learning strategies for systems with invariance properties

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

Ling, Julia; Jones, Reese E.; Templeton, Jeremy Alan

Here, in many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds-Averaged Navier-Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high-performance computing has led to a growing availability of high-fidelity simulation data, which open up the possibility of using machine learning algorithms, such as random forests or neuralmore » networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first , a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance with significantly reduced computational training costs.« less

Machine learning strategies for systems with invariance properties

DOE PAGES

Ling, Julia; Jones, Reese E.; Templeton, Jeremy Alan

2016-05-06

Here, in many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds-Averaged Navier-Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high-performance computing has led to a growing availability of high-fidelity simulation data, which open up the possibility of using machine learning algorithms, such as random forests or neuralmore » networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first , a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance with significantly reduced computational training costs.« less

Empirical downscaling of daily minimum air temperature at very fine resolutions in complex terrain

Treesearch

Zachary A. Holden; John T. Abatzoglou; Charles H. Luce; L. Scott Baggett

2011-01-01

Available air temperature models do not adequately account for the influence of terrain on nocturnal air temperatures. An empirical model for night time air temperatures was developed using a network of one hundred and forty inexpensive temperature sensors deployed across the Bitterroot National Forest, Montana. A principle component analysis (PCA) on minimum...

Empirical Modeling of Information Communication Technology Usage Behaviour among Business Education Teachers in Tertiary Colleges of a Developing Country

ERIC Educational Resources Information Center

Isiyaku, Dauda Dansarki; Ayub, Ahmad Fauzi Mohd; Abdulkadir, Suhaida

2015-01-01

This study has empirically tested the fitness of a structural model in explaining the influence of two exogenous variables (perceived enjoyment and attitude towards ICTs) on two endogenous variables (behavioural intention and teachers' Information Communication Technology (ICT) usage behavior), based on the proposition of Technology Acceptance…

Comparison of modelled and empirical atmospheric propagation data

NASA Technical Reports Server (NTRS)

Schott, J. R.; Biegel, J. D.

1983-01-01

The radiometric integrity of TM thermal infrared channel data was evaluated and monitored to develop improved radiometric preprocessing calibration techniques for removal of atmospheric effects. Modelled atmospheric transmittance and path radiance were compared with empirical values derived from aircraft underflight data. Aircraft thermal infrared imagery and calibration data were available on two dates as were corresponding atmospheric radiosonde data. The radiosonde data were used as input to the LOWTRAN 5A code which was modified to output atmospheric path radiance in addition to transmittance. The aircraft data were calibrated and used to generate analogous measurements. These data indicate that there is a tendancy for the LOWTRAN model to underestimate atmospheric path radiance and transmittance as compared to empirical data. A plot of transmittance versus altitude for both LOWTRAN and empirical data is presented.

Developing Inventory Projection Models Using Empirical Net Forest Growth and Growing-Stock Density Relationships Across U.S. Regions and Species Group

Treesearch

Prakash Nepal; Peter J. Ince; Kenneth E. Skog; Sun J. Chang

2012-01-01

This paper describes a set of empirical net forest growth models based on forest growing-stock density relationships for three U.S. regions (North, South, and West) and two species groups (softwoods and hardwoods) at the regional aggregate level. The growth models accurately predict historical U.S. timber inventory trends when we incorporate historical timber harvests...

Entrepreneurial propensity in health care: models and propositions for empirical research.

PubMed

Asoh, Derek A; Rivers, Patrick A; McCleary, Karl J; Sarvela, Paul

2005-01-01

We maintain that entrepreneurial propensity is a focal construct in entrepreneurial research. We synthesize the literature to develop models depicting the antecedents and consequents of entrepreneurial propensity in a network of other constructs and variables of interest in the health care industry. We advance propositions for empirical investigation and validation of competing research models associated with entrepreneurial propensity. We conclude with a discussion of directions of future research.

Modeling the Role of Priming in Executive Control: Cognitive and Neural Constraints

DTIC Science & Technology

2012-01-24

theoretical and empirical advances in our understanding of cognitive control. We discovered new phenomena and developed theories to account for them. We...developed theories of cognitive control and visual attention that integrated mathematical psychology with cognitive science and with neuroscience. We...significant theoretical and empirical advances in our understanding of cognitive control. We discovered new phenomena and developed theories to account

Empirical support for global integrated assessment modeling: Productivity trends and technological change in developing countries' agriculture and electric power sectors

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

Sathaye, Jayant A.

2000-04-01

Integrated assessment (IA) modeling of climate policy is increasingly global in nature, with models incorporating regional disaggregation. The existing empirical basis for IA modeling, however, largely arises from research on industrialized economies. Given the growing importance of developing countries in determining long-term global energy and carbon emissions trends, filling this gap with improved statistical information on developing countries' energy and carbon-emissions characteristics is an important priority for enhancing IA modeling. Earlier research at LBNL on this topic has focused on assembling and analyzing statistical data on productivity trends and technological change in the energy-intensive manufacturing sectors of five developing countries,more » India, Brazil, Mexico, Indonesia, and South Korea. The proposed work will extend this analysis to the agriculture and electric power sectors in India, South Korea, and two other developing countries. They will also examine the impact of alternative model specifications on estimates of productivity growth and technological change for each of the three sectors, and estimate the contribution of various capital inputs--imported vs. indigenous, rigid vs. malleable-- in contributing to productivity growth and technological change. The project has already produced a data resource on the manufacturing sector which is being shared with IA modelers. This will be extended to the agriculture and electric power sectors, which would also be made accessible to IA modeling groups seeking to enhance the empirical descriptions of developing country characteristics. The project will entail basic statistical and econometric analysis of productivity and energy trends in these developing country sectors, with parameter estimates also made available to modeling groups. The parameter estimates will be developed using alternative model specifications that could be directly utilized by the existing IAMs for the manufacturing, agriculture, and electric power sectors.« less

Diagnosing Model Errors in Simulations of Solar Radiation on Inclined Surfaces: Preprint

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

Xie, Yu; Sengupta, Manajit

2016-06-01

Transposition models have been widely used in the solar energy industry to simulate solar radiation on inclined PV panels. Following numerous studies comparing the performance of transposition models, this paper aims to understand the quantitative uncertainty in the state-of-the-art transposition models and the sources leading to the uncertainty. Our results suggest that an isotropic transposition model developed by Badescu substantially underestimates diffuse plane-of-array (POA) irradiances when diffuse radiation is perfectly isotropic. In the empirical transposition models, the selection of empirical coefficients and land surface albedo can both result in uncertainty in the output. This study can be used as amore » guide for future development of physics-based transposition models.« less

A Bayesian estimation of a stochastic predator-prey model of economic fluctuations

NASA Astrophysics Data System (ADS)

Dibeh, Ghassan; Luchinsky, Dmitry G.; Luchinskaya, Daria D.; Smelyanskiy, Vadim N.

2007-06-01

In this paper, we develop a Bayesian framework for the empirical estimation of the parameters of one of the best known nonlinear models of the business cycle: The Marx-inspired model of a growth cycle introduced by R. M. Goodwin. The model predicts a series of closed cycles representing the dynamics of labor's share and the employment rate in the capitalist economy. The Bayesian framework is used to empirically estimate a modified Goodwin model. The original model is extended in two ways. First, we allow for exogenous periodic variations of the otherwise steady growth rates of the labor force and productivity per worker. Second, we allow for stochastic variations of those parameters. The resultant modified Goodwin model is a stochastic predator-prey model with periodic forcing. The model is then estimated using a newly developed Bayesian estimation method on data sets representing growth cycles in France and Italy during the years 1960-2005. Results show that inference of the parameters of the stochastic Goodwin model can be achieved. The comparison of the dynamics of the Goodwin model with the inferred values of parameters demonstrates quantitative agreement with the growth cycle empirical data.

Lexical Processing and Organization in Bilingual First Language Acquisition: Guiding Future Research

PubMed Central

DeAnda, Stephanie; Poulin-Dubois, Diane; Zesiger, Pascal; Friend, Margaret

2016-01-01

A rich body of work in adult bilinguals documents an interconnected lexical network across languages, such that early word retrieval is language independent. This literature has yielded a number of influential models of bilingual semantic memory. However, extant models provide limited predictions about the emergence of lexical organization in bilingual first language acquisition (BFLA). Empirical evidence from monolingual infants suggests that lexical networks emerge early in development as children integrate phonological and semantic information. These findings tell us little about the interaction between two languages in the early bilingual memory. To date, an understanding of when and how languages interact in early bilingual development is lacking. In this literature review, we present research documenting lexical-semantic development across monolingual and bilingual infants. This is followed by a discussion of current models of bilingual language representation and organization and their ability to account for the available empirical evidence. Together, these theoretical and empirical accounts inform and highlight unexplored areas of research and guide future work on early bilingual memory. PMID:26866430

Verification and implementation of set-up empirical models in pile design : research project capsule.

DOT National Transportation Integrated Search

2016-08-01

The primary objectives of this research include: performing static and dynamic load tests on : newly instrumented test piles to better understand the set-up mechanism for individual soil : layers, verifying or recalibrating previously developed empir...

Modified empirical Solar Radiation Pressure model for IRNSS constellation

NASA Astrophysics Data System (ADS)

Rajaiah, K.; Manamohan, K.; Nirmala, S.; Ratnakara, S. C.

2017-11-01

Navigation with Indian Constellation (NAVIC) also known as Indian Regional Navigation Satellite System (IRNSS) is India's regional navigation system designed to provide position accuracy better than 20 m over India and the region extending to 1500 km around India. The reduced dynamic precise orbit estimation is utilized to determine the orbit broadcast parameters for IRNSS constellation. The estimation is mainly affected by the parameterization of dynamic models especially Solar Radiation Pressure (SRP) model which is a non-gravitational force depending on shape and attitude dynamics of the spacecraft. An empirical nine parameter solar radiation pressure model is developed for IRNSS constellation, using two-way range measurements from IRNSS C-band ranging system. The paper addresses the development of modified SRP empirical model for IRNSS (IRNSS SRP Empirical Model, ISEM). The performance of the ISEM was assessed based on overlap consistency, long term prediction, Satellite Laser Ranging (SLR) residuals and compared with ECOM9, ECOM5 and new-ECOM9 models developed by Center for Orbit Determination in Europe (CODE). For IRNSS Geostationary Earth Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites, ISEM has shown promising results with overlap RMS error better than 5.3 m and 3.5 m respectively. Long term orbit prediction using numerical integration has improved with error better than 80%, 26% and 7.8% in comparison to ECOM9, ECOM5 and new-ECOM9 respectively. Further, SLR based orbit determination with ISEM shows 70%, 47% and 39% improvement over 10 days orbit prediction in comparison to ECOM9, ECOM5 and new-ECOM9 respectively and also highlights the importance of wide baseline tracking network.

Traditional Arabic & Islamic medicine: validation and empirical assessment of a conceptual model in Qatar.

PubMed

AlRawi, Sara N; Khidir, Amal; Elnashar, Maha S; Abdelrahim, Huda A; Killawi, Amal K; Hammoud, Maya M; Fetters, Michael D

2017-03-14

Evidence indicates traditional medicine is no longer only used for the healthcare of the poor, its prevalence is also increasing in countries where allopathic medicine is predominant in the healthcare system. While these healing practices have been utilized for thousands of years in the Arabian Gulf, only recently has a theoretical model been developed illustrating the linkages and components of such practices articulated as Traditional Arabic & Islamic Medicine (TAIM). Despite previous theoretical work presenting development of the TAIM model, empirical support has been lacking. The objective of this research is to provide empirical support for the TAIM model and illustrate real world applicability. Using an ethnographic approach, we recruited 84 individuals (43 women and 41 men) who were speakers of one of four common languages in Qatar; Arabic, English, Hindi, and Urdu, Through in-depth interviews, we sought confirming and disconfirming evidence of the model components, namely, health practices, beliefs and philosophy to treat, diagnose, and prevent illnesses and/or maintain well-being, as well as patterns of communication about their TAIM practices with their allopathic providers. Based on our analysis, we find empirical support for all elements of the TAIM model. Participants in this research, visitors to major healthcare centers, mentioned using all elements of the TAIM model: herbal medicines, spiritual therapies, dietary practices, mind-body methods, and manual techniques, applied singularly or in combination. Participants had varying levels of comfort sharing information about TAIM practices with allopathic practitioners. These findings confirm an empirical basis for the elements of the TAIM model. Three elements, namely, spiritual healing, herbal medicine, and dietary practices, were most commonly found. Future research should examine the prevalence of TAIM element use, how it differs among various populations, and its impact on health.

Comparison of the Various Methodologies Used in Studying Runoff and Sediment Load in the Yellow River Basin

NASA Astrophysics Data System (ADS)

Xu, M., III; Liu, X.

2017-12-01

In the past 60 years, both the runoff and sediment load in the Yellow River Basin showed significant decreasing trends owing to the influences of human activities and climate change. Quantifying the impact of each factor (e.g. precipitation, sediment trapping dams, pasture, terrace, etc.) on the runoff and sediment load is among the key issues to guide the implement of water and soil conservation measures, and to predict the variation trends in the future. Hundreds of methods have been developed for studying the runoff and sediment load in the Yellow River Basin. Generally, these methods can be classified into empirical methods and physical-based models. The empirical methods, including hydrological method, soil and water conservation method, etc., are widely used in the Yellow River management engineering. These methods generally apply the statistical analyses like the regression analysis to build the empirical relationships between the main characteristic variables in a river basin. The elasticity method extensively used in the hydrological research can be classified into empirical method as it is mathematically deduced to be equivalent with the hydrological method. Physical-based models mainly include conceptual models and distributed models. The conceptual models are usually lumped models (e.g. SYMHD model, etc.) and can be regarded as transition of empirical models and distributed models. Seen from the publications that less studies have been conducted applying distributed models than empirical models as the simulation results of runoff and sediment load based on distributed models (e.g. the Digital Yellow Integrated Model, the Geomorphology-Based Hydrological Model, etc.) were usually not so satisfied owing to the intensive human activities in the Yellow River Basin. Therefore, this study primarily summarizes the empirical models applied in the Yellow River Basin and theoretically analyzes the main causes for the significantly different results using different empirical researching methods. Besides, we put forward an assessment frame for the researching methods of the runoff and sediment load variations in the Yellow River Basin from the point of view of inputting data, model structure and result output. And the assessment frame was then applied in the Huangfuchuan River.

PATENTS AND RESEARCH INVESTMENTS: ASSESSING THE EMPIRICAL EVIDENCE.

PubMed

Budish, Eric; Roin, Benjamin N; Williams, Heidi L

2016-05-01

A well-developed theoretical literature - dating back at least to Nordhaus (1969) - has analyzed optimal patent policy design. We re-present the core trade-off of the Nordhaus model and highlight an empirical question which emerges from the Nordhaus framework as a key input into optimal patent policy design: namely, what is the elasticity of R&D investment with respect to the patent term? We then review the - surprisingly small - body of empirical evidence that has been developed on this question over the nearly half century since the publication of Nordhaus's book.

The Impact of Social Desirability on Organizational Behavior Research Results: An Empirical Investigation of Alternative Models,

DTIC Science & Technology

1982-02-01

TANAAD S t(AB A , THE IMPACT OF SOCIAL DESIRABILITY ON ORGANIZATIONAL BEHAVIOR RESEARCH RESULTS: AN EMPIRICAL INVESTIGATION OF ALTERNATIVE MODELS Daniel C...Investigation of Alternative Models 4- PERFORMING G. RE.PORTNUMBER 7. AU ?wnOPe) a. CONTRACf OR GR1ANT NUBAe Daniel C. Ganster, Harry W. Hennessey, and Fred...Fred Luthans University of Nebraska-Lincoln ABSTRACT Three conceptual and statistical models are developed for the effects of social desirability (SD

Modeling thermal sensation in a Mediterranean climate—a comparison of linear and ordinal models

NASA Astrophysics Data System (ADS)

Pantavou, Katerina; Lykoudis, Spyridon

2014-08-01

A simple thermo-physiological model of outdoor thermal sensation adjusted with psychological factors is developed aiming to predict thermal sensation in Mediterranean climates. Microclimatic measurements simultaneously with interviews on personal and psychological conditions were carried out in a square, a street canyon and a coastal location of the greater urban area of Athens, Greece. Multiple linear and ordinal regression were applied in order to estimate thermal sensation making allowance for all the recorded parameters or specific, empirically selected, subsets producing so-called extensive and empirical models, respectively. Meteorological, thermo-physiological and overall models - considering psychological factors as well - were developed. Predictions were improved when personal and psychological factors were taken into account as compared to meteorological models. The model based on ordinal regression reproduced extreme values of thermal sensation vote more adequately than the linear regression one, while the empirical model produced satisfactory results in relation to the extensive model. The effects of adaptation and expectation on thermal sensation vote were introduced in the models by means of the exposure time, season and preference related to air temperature and irradiation. The assessment of thermal sensation could be a useful criterion in decision making regarding public health, outdoor spaces planning and tourism.

Developing an Empirical Model for Jet-Surface Interaction Noise

NASA Technical Reports Server (NTRS)

Brown, Clifford A.

2014-01-01

The process of developing an empirical model for jet-surface interaction noise is described and the resulting model evaluated. Jet-surface interaction noise is generated when the high-speed engine exhaust from modern tightly integrated or conventional high-bypass ratio engine aircraft strikes or flows over the airframe surfaces. An empirical model based on an existing experimental database is developed for use in preliminary design system level studies where computation speed and range of configurations is valued over absolute accuracy to select the most promising (or eliminate the worst) possible designs. The model developed assumes that the jet-surface interaction noise spectra can be separated from the jet mixing noise and described as a parabolic function with three coefficients: peak amplitude, spectral width, and peak frequency. These coefficients are fit to functions of surface length and distance from the jet lipline to form a characteristic spectra which is then adjusted for changes in jet velocity and/or observer angle using scaling laws from published theoretical and experimental work. The resulting model is then evaluated for its ability to reproduce the characteristic spectra and then for reproducing spectra measured at other jet velocities and observer angles; successes and limitations are discussed considering the complexity of the jet-surface interaction noise versus the desire for a model that is simple to implement and quick to execute.

Developing an Empirical Model for Jet-Surface Interaction Noise

NASA Technical Reports Server (NTRS)

Brown, Clif

2014-01-01

The process of developing an empirical model for jet-surface interaction noise is described and the resulting model evaluated. Jet-surface interaction noise is generated when the high-speed engine exhaust from modern tightly integrated or conventional high-bypass ratio engine aircraft strikes or flows over the airframe surfaces. An empirical model based on an existing experimental database is developed for use in preliminary design system level studies where computation speed and range of configurations is valued over absolute accuracy to select the most promising (or eliminate the worst) possible designs. The model developed assumes that the jet-surface interaction noise spectra can be separated from the jet mixing noise and described as a parabolic function with three coefficients: peak amplitude, spectral width, and peak frequency. These coefficients are t to functions of surface length and distance from the jet lipline to form a characteristic spectra which is then adjusted for changes in jet velocity and/or observer angle using scaling laws from published theoretical and experimental work. The resulting model is then evaluated for its ability to reproduce the characteristic spectra and then for reproducing spectra measured at other jet velocities and observer angles; successes and limitations are discussed considering the complexity of the jet-surface interaction noise versus the desire for a model that is simple to implement and quick to execute.

Lead Slowing-Down Spectrometry Time Spectral Analysis for Spent Fuel Assay: FY11 Status Report

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

Kulisek, Jonathan A.; Anderson, Kevin K.; Bowyer, Sonya M.

2011-09-30

Developing a method for the accurate, direct, and independent assay of the fissile isotopes in bulk materials (such as used fuel) from next-generation domestic nuclear fuel cycles is a goal of the Office of Nuclear Energy, Fuel Cycle R&D, Material Protection and Control Technology (MPACT) Campaign. To meet this goal, MPACT supports a multi-institutional collaboration, of which PNNL is a part, to study the feasibility of Lead Slowing Down Spectroscopy (LSDS). This technique is an active nondestructive assay method that has the potential to provide independent, direct measurement of Pu and U isotopic masses in used fuel with an uncertaintymore » considerably lower than the approximately 10% typical of today's confirmatory assay methods. This document is a progress report for FY2011 PNNL analysis and algorithm development. Progress made by PNNL in FY2011 continues to indicate the promise of LSDS analysis and algorithms applied to used fuel. PNNL developed an empirical model based on calibration of the LSDS to responses generated from well-characterized used fuel. The empirical model, which accounts for self-shielding effects using empirical basis vectors calculated from the singular value decomposition (SVD) of a matrix containing the true self-shielding functions of the used fuel assembly models. The potential for the direct and independent assay of the sum of the masses of 239Pu and 241Pu to within approximately 3% over a wide used fuel parameter space was demonstrated. Also, in FY2011, PNNL continued to develop an analytical model. Such efforts included the addition of six more non-fissile absorbers in the analytical shielding function and the non-uniformity of the neutron flux across the LSDS assay chamber. A hybrid analytical-empirical approach was developed to determine the mass of total Pu (sum of the masses of 239Pu, 240Pu, and 241Pu), which is an important quantity in safeguards. Results using this hybrid method were of approximately the same accuracy as the pure empirical approach. In addition, total Pu with much better accuracy with the hybrid approach than the pure analytical approach. In FY2012, PNNL will continue efforts to optimize its empirical model and minimize its reliance on calibration data. In addition, PNNL will continue to develop an analytical model, considering effects such as neutron-scattering in the fuel and cladding, as well as neutrons streaming through gaps between fuel pins in the fuel assembly.« less

Empirical Storm-Time Correction to the International Reference Ionosphere Model E-Region Electron and Ion Density Parameterizations Using Observations from TIMED/SABER

NASA Technical Reports Server (NTRS)

Mertens, Christoper J.; Winick, Jeremy R.; Russell, James M., III; Mlynczak, Martin G.; Evans, David S.; Bilitza, Dieter; Xu, Xiaojing

2007-01-01

The response of the ionospheric E-region to solar-geomagnetic storms can be characterized using observations of infrared 4.3 micrometers emission. In particular, we utilize nighttime TIMED/SABER measurements of broadband 4.3 micrometers limb emission and derive a new data product, the NO+(v) volume emission rate, which is our primary observation-based quantity for developing an empirical storm-time correction the IRI E-region electron density. In this paper we describe our E-region proxy and outline our strategy for developing the empirical storm model. In our initial studies, we analyzed a six day storm period during the Halloween 2003 event. The results of this analysis are promising and suggest that the ap-index is a viable candidate to use as a magnetic driver for our model.

Empirical phylogenies and species abundance distributions are consistent with preequilibrium dynamics of neutral community models with gene flow.

PubMed

Bonnet-Lebrun, Anne-Sophie; Manica, Andrea; Eriksson, Anders; Rodrigues, Ana S L

2017-05-01

Community characteristics reflect past ecological and evolutionary dynamics. Here, we investigate whether it is possible to obtain realistically shaped modeled communities-that is with phylogenetic trees and species abundance distributions shaped similarly to typical empirical bird and mammal communities-from neutral community models. To test the effect of gene flow, we contrasted two spatially explicit individual-based neutral models: one with protracted speciation, delayed by gene flow, and one with point mutation speciation, unaffected by gene flow. The former produced more realistic communities (shape of phylogenetic tree and species-abundance distribution), consistent with gene flow being a key process in macro-evolutionary dynamics. Earlier models struggled to capture the empirically observed branching tempo in phylogenetic trees, as measured by the gamma statistic. We show that the low gamma values typical of empirical trees can be obtained in models with protracted speciation, in preequilibrium communities developing from an initially abundant and widespread species. This was even more so in communities sampled incompletely, particularly if the unknown species are the youngest. Overall, our results demonstrate that the characteristics of empirical communities that we have studied can, to a large extent, be explained through a purely neutral model under preequilibrium conditions. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Foundations for computer simulation of a low pressure oil flooded single screw air compressor

NASA Astrophysics Data System (ADS)

Bein, T. W.

1981-12-01

The necessary logic to construct a computer model to predict the performance of an oil flooded, single screw air compressor is developed. The geometric variables and relationships used to describe the general single screw mechanism are developed. The governing equations to describe the processes are developed from their primary relationships. The assumptions used in the development are also defined and justified. The computer model predicts the internal pressure, temperature, and flowrates through the leakage paths throughout the compression cycle of the single screw compressor. The model uses empirical external values as the basis for the internal predictions. The computer values are compared to the empirical values, and conclusions are drawn based on the results. Recommendations are made for future efforts to improve the computer model and to verify some of the conclusions that are drawn.

Empirical modeling of environment-enhanced fatigue crack propagation in structural alloys for component life prediction

NASA Technical Reports Server (NTRS)

Richey, Edward, III

1995-01-01

This research aims to develop the methods and understanding needed to incorporate time and loading variable dependent environmental effects on fatigue crack propagation (FCP) into computerized fatigue life prediction codes such as NASA FLAGRO (NASGRO). In particular, the effect of loading frequency on FCP rates in alpha + beta titanium alloys exposed to an aqueous chloride solution is investigated. The approach couples empirical modeling of environmental FCP with corrosion fatigue experiments. Three different computer models have been developed and incorporated in the DOS executable program. UVAFAS. A multiple power law model is available, and can fit a set of fatigue data to a multiple power law equation. A model has also been developed which implements the Wei and Landes linear superposition model, as well as an interpolative model which can be utilized to interpolate trends in fatigue behavior based on changes in loading characteristics (stress ratio, frequency, and hold times).

Developing Rational-Empirical Views of Intelligent Adaptive Behavior

DTIC Science & Technology

2004-08-01

biological frame to the information processing model and outline our understanding of intentions and beliefs that co-exist with rational and...notion that the evolution of cognition has produced memory/ knowledge systems that specialize in the processing of particular types of information ...1 PERMIS 2004 Developing Rational-Empirical Views of Intelligent Adaptive Behavior Gary Berg-Cross, Knowledge Strategies Potomac, Maryland

Health care competition, strategic mission, and patient satisfaction: research model and propositions.

PubMed

Rivers, Patrick A; Glover, Saundra H

2008-01-01

In all industries, competition among businesses has long been encouraged as a mechanism to increase value for patients. In other words, competition ensures the provision of better products and services to satisfy the needs of customers This paper aims to develop a model that can be used to empirically investigate a number of complex issues and relationships associated with competition in the health care industry. A literature review was conducted. A total of 50 items of literature related to the subject were reviewed. Various perspectives of competition, the nature of service quality, health system costs, and patient satisfaction in health care are examined. A model of the relationship among these variables is developed. The model depicts patient satisfaction as an outcome measure directly dependent on competition. Quality of care and health care systems costs, while also directly dependent on the strategic mission and goals, are considered as determinants of customer satisfaction as well. The model is discussed in the light of propositions for empirical research. Empirical studies based on the model proposed in this paper should help identify areas with significant impact on patient satisfaction while maintaining high quality of service at lower costs in a competitive environment. The authors develop a research model which included propositions to examine the complex issues of competition in the health care industry.

Longitudinal Studies of Spelling Development.

ERIC Educational Resources Information Center

Ellis, Nick

Noting that proposed models of literacy development suggest that reading and writing mutually influence and grow from each other, this paper summarizes aspects of stage theories of literacy development and an integrative model, and considers how the model fared in empirical longitudinal tests. The paper begins with a summary of the modal aspects…

Rollover risk prediction of heavy vehicles by reliability index and empirical modelling

NASA Astrophysics Data System (ADS)

Sellami, Yamine; Imine, Hocine; Boubezoul, Abderrahmane; Cadiou, Jean-Charles

2018-03-01

This paper focuses on a combination of a reliability-based approach and an empirical modelling approach for rollover risk assessment of heavy vehicles. A reliability-based warning system is developed to alert the driver to a potential rollover before entering into a bend. The idea behind the proposed methodology is to estimate the rollover risk by the probability that the vehicle load transfer ratio (LTR) exceeds a critical threshold. Accordingly, a so-called reliability index may be used as a measure to assess the vehicle safe functioning. In the reliability method, computing the maximum of LTR requires to predict the vehicle dynamics over the bend which can be in some cases an intractable problem or time-consuming. With the aim of improving the reliability computation time, an empirical model is developed to substitute the vehicle dynamics and rollover models. This is done by using the SVM (Support Vector Machines) algorithm. The preliminary obtained results demonstrate the effectiveness of the proposed approach.

Using an empirical and rule-based modeling approach to map cause of disturbance in U.S

Treesearch

Todd A. Schroeder; Gretchen G. Moisen; Karen Schleeweis; Chris Toney; Warren B. Cohen; Zhiqiang Yang; Elizabeth A. Freeman

2015-01-01

Recently completing over a decade of research, the NASA/NACP funded North American Forest Dynamics (NAFD) project has led to several important advancements in the way U.S. forest disturbance dynamics are mapped at regional and continental scales. One major contribution has been the development of an empirical and rule-based modeling approach which addresses two of the...

The storm time ring current dynamics and response to CMEs and CIRs using Van Allen Probes observations and CIMI simulations

NASA Astrophysics Data System (ADS)

Mouikis, Christopher; Bingham, Samuel; Kistler, Lynn; Spence, Harlan; Gkioulidou, Matina

2017-04-01

The ring current responds differently to the different solar and interplanetary storm drivers such as coronal mass injections, (CME's), and co-rotating interaction regions (CIR's). Using Van Allen Probes observations, we develop an empirical ring current model of the ring current pressure, the pressure anisotropy and the current density development during the storm phases for both types of storm drivers and for all MLTs inside L 6. Delineating the differences in the ring current development between these two drivers will aid our understanding of the ring current dynamics. We find that during the storm main phase most of the ring current pressure in the pre-midnight inner magnetosphere is contributed by particles on open drift paths that cause the development of a strong partial ring current that causes most of the main phase Dst drop. These particles can reach as deep as L 2 and their pressure compares to the local magnetic field pressure as deep as L 3. During the recovery phase, if these particles are not lost at the magnetopause, will become trapped and will contribute to the symmetric ring current. However, the largest difference between the CME and CIR ring current responses during the storm main and early recovery phases is caused by how the 15 - 60 keV O+ responds to these drivers. This empirical model is compared to the results of CIMI simulations of a CMEs and a CIRs where the model input is comprised of the superposed epoch solar wind conditions of the storms that comprise the empirical model. Different inner magnetosphere boundary conditions are tested in order to match the empirical model results. Comparing the model and simulation results improves our understanding of the ring current dynamics as part of the highly coupled inner magnetosphere system. In addition, within the framework of this empirical model, the prediction of the EMIC wave generation linear theory is tested using the observed plasma parameters and comparing with the observations of EMIC waves.

Combining Empirical and Stochastic Models for Extreme Floods Estimation

NASA Astrophysics Data System (ADS)

Zemzami, M.; Benaabidate, L.

2013-12-01

Hydrological models can be defined as physical, mathematical or empirical. The latter class uses mathematical equations independent of the physical processes involved in the hydrological system. The linear regression and Gradex (Gradient of Extreme values) are classic examples of empirical models. However, conventional empirical models are still used as a tool for hydrological analysis by probabilistic approaches. In many regions in the world, watersheds are not gauged. This is true even in developed countries where the gauging network has continued to decline as a result of the lack of human and financial resources. Indeed, the obvious lack of data in these watersheds makes it impossible to apply some basic empirical models for daily forecast. So we had to find a combination of rainfall-runoff models in which it would be possible to create our own data and use them to estimate the flow. The estimated design floods would be a good choice to illustrate the difficulties facing the hydrologist for the construction of a standard empirical model in basins where hydrological information is rare. The construction of the climate-hydrological model, which is based on frequency analysis, was established to estimate the design flood in the Anseghmir catchments, Morocco. The choice of using this complex model returns to its ability to be applied in watersheds where hydrological information is not sufficient. It was found that this method is a powerful tool for estimating the design flood of the watershed and also other hydrological elements (runoff, volumes of water...).The hydrographic characteristics and climatic parameters were used to estimate the runoff, water volumes and design flood for different return periods.

An Empirical Bayes Approach to Spatial Analysis

NASA Technical Reports Server (NTRS)

Morris, C. N.; Kostal, H.

1983-01-01

Multi-channel LANDSAT data are collected in several passes over agricultural areas during the growing season. How empirical Bayes modeling can be used to develop crop identification and discrimination techniques that account for spatial correlation in such data is considered. The approach models the unobservable parameters and the data separately, hoping to take advantage of the fact that the bulk of spatial correlation lies in the parameter process. The problem is then framed in terms of estimating posterior probabilities of crop types for each spatial area. Some empirical Bayes spatial estimation methods are used to estimate the logits of these probabilities.

Empirical factors and structure transference: Returning to the London account

NASA Astrophysics Data System (ADS)

Bueno, Otávio; French, Steven; Ladyman, James

2012-05-01

We offer a framework to represent the roles of empirical and theoretical factors in theory construction, and examine a case study to illustrate how the framework can be used to illuminate central features of scientific reasoning. The case study provides an extension of French and Ladyman's (1997) analysis of Fritz and Heinz London's model of superconductivity to accommodate the role of the analogy between superconductivity and diamagnetic phenomena in the development of the model between 1935 and 1937. We focus on this case since it allows us to separate the roles of empirical and theoretical factors, and so provides an example of the utility of the approach that we have adopted. We conclude the paper by drawing on the particular framework here developed to address a range of concerns.

Using Landsat to provide potato production estimates to Columbia Basin farmers and processors

NASA Technical Reports Server (NTRS)

1990-01-01

A summary of project activities relative to the estimation of potato yields in the Columbia Basin is given. Oregon State University is using a two-pronged approach to yield estimation, one using simulation models and the other using purely empirical models. The simulation modeling approach has used satellite observations to determine key dates in the development of the crop for each field identified as potatoes. In particular, these include planting dates, emergence dates, and harvest dates. These critical dates are fed into simulation models of crop growth and development to derive yield forecasts. Two empirical modeling approaches are illustrated. One relates tuber yield to estimates of cumulative intercepted solar radiation; the other relates tuber yield to the integral under the GVI curve.

Modeling and Simulation of Upset-Inducing Disturbances for Digital Systems in an Electromagnetic Reverberation Chamber

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2014-01-01

This report describes a modeling and simulation approach for disturbance patterns representative of the environment experienced by a digital system in an electromagnetic reverberation chamber. The disturbance is modeled by a multi-variate statistical distribution based on empirical observations. Extended versions of the Rejection Samping and Inverse Transform Sampling techniques are developed to generate multi-variate random samples of the disturbance. The results show that Inverse Transform Sampling returns samples with higher fidelity relative to the empirical distribution. This work is part of an ongoing effort to develop a resilience assessment methodology for complex safety-critical distributed systems.

Decision-support models for empiric antibiotic selection in Gram-negative bloodstream infections.

PubMed

MacFadden, D R; Coburn, B; Shah, N; Robicsek, A; Savage, R; Elligsen, M; Daneman, N

2018-04-25

Early empiric antibiotic therapy in patients can improve clinical outcomes in Gram-negative bacteraemia. However, the widespread prevalence of antibiotic-resistant pathogens compromises our ability to provide adequate therapy while minimizing use of broad antibiotics. We sought to determine whether readily available electronic medical record data could be used to develop predictive models for decision support in Gram-negative bacteraemia. We performed a multi-centre cohort study, in Canada and the USA, of hospitalized patients with Gram-negative bloodstream infection from April 2010 to March 2015. We analysed multivariable models for prediction of antibiotic susceptibility at two empiric windows: Gram-stain-guided and pathogen-guided treatment. Decision-support models for empiric antibiotic selection were developed based on three clinical decision thresholds of acceptable adequate coverage (80%, 90% and 95%). A total of 1832 patients with Gram-negative bacteraemia were evaluated. Multivariable models showed good discrimination across countries and at both Gram-stain-guided (12 models, areas under the curve (AUCs) 0.68-0.89, optimism-corrected AUCs 0.63-0.85) and pathogen-guided (12 models, AUCs 0.75-0.98, optimism-corrected AUCs 0.64-0.95) windows. Compared to antibiogram-guided therapy, decision-support models of antibiotic selection incorporating individual patient characteristics and prior culture results have the potential to increase use of narrower-spectrum antibiotics (in up to 78% of patients) while reducing inadequate therapy. Multivariable models using readily available epidemiologic factors can be used to predict antimicrobial susceptibility in infecting pathogens with reasonable discriminatory ability. Implementation of sequential predictive models for real-time individualized empiric antibiotic decision-making has the potential to both optimize adequate coverage for patients while minimizing overuse of broad-spectrum antibiotics, and therefore requires further prospective evaluation. Readily available epidemiologic risk factors can be used to predict susceptibility of Gram-negative organisms among patients with bacteraemia, using automated decision-making models. Copyright © 2018 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

A Conceptual Model of Career Development to Enhance Academic Motivation

ERIC Educational Resources Information Center

Collins, Nancy Creighton

2010-01-01

The purpose of this study was to develop, refine, and validate a conceptual model of career development to enhance the academic motivation of community college students. To achieve this end, a straw model was built from the theoretical and empirical research literature. The model was then refined and validated through three rounds of a Delphi…

Development of a rotor wake-vortex model, volume 1

NASA Technical Reports Server (NTRS)

Majjigi, R. K.; Gliebe, P. R.

1984-01-01

Certain empirical rotor wake and turbulence relationships were developed using existing low speed rotor wave data. A tip vortex model was developed by replacing the annulus wall with a row of image vortices. An axisymmetric turbulence spectrum model, developed in the context of rotor inflow turbulence, was adapted to predicting the turbulence spectrum of the stator gust upwash.

Carbon deposition model for oxygen-hydrocarbon combustion. Task 6: Data analysis and formulation of an empirical model

NASA Technical Reports Server (NTRS)

Makel, Darby B.; Rosenberg, Sanders D.

1990-01-01

The formation and deposition of carbon (soot) was studied in the Carbon Deposition Model for Oxygen-Hydrocarbon Combustion Program. An empirical, 1-D model for predicting soot formation and deposition in LO2/hydrocarbon gas generators/preburners was derived. The experimental data required to anchor the model were identified and a test program to obtain the data was defined. In support of the model development, cold flow mixing experiments using a high injection density injector were performed. The purpose of this investigation was to advance the state-of-the-art in LO2/hydrocarbon gas generator design by developing a reliable engineering model of gas generator operation. The model was formulated to account for the influences of fluid dynamics, chemical kinetics, and gas generator hardware design on soot formation and deposition.

The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms

NASA Technical Reports Server (NTRS)

Brewin, Robert J.W.; Sathyendranath, Shubha; Muller, Dagmar; Brockmann, Carsten; Deschamps, Pierre-Yves; Devred, Emmanuel; Doerffer, Roland; Fomferra, Norman; Franz, Bryan; Grant, Mike;

Generalized Constitutive-Based Theoretical and Empirical Models for Hot Working Behavior of Functionally Graded Steels

NASA Astrophysics Data System (ADS)

Vanini, Seyed Ali Sadough; Abolghasemzadeh, Mohammad; Assadi, Abbas

2013-07-01

Functionally graded steels with graded ferritic and austenitic regions including bainite and martensite intermediate layers produced by electroslag remelting have attracted much attention in recent years. In this article, an empirical model based on the Zener-Hollomon (Z-H) constitutive equation with generalized material constants is presented to investigate the effects of temperature and strain rate on the hot working behavior of functionally graded steels. Next, a theoretical model, generalized by strain compensation, is developed for the flow stress estimation of functionally graded steels under hot compression based on the phase mixture rule and boundary layer characteristics. The model is used for different strains and grading configurations. Specifically, the results for αβγMγ steels from empirical and theoretical models showed excellent agreement with those of experiments of other references within acceptable error.

Numerical methods for assessing water quality in lakes and reservoirs

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

Mahamah, D.S.

1984-01-01

Water quality models are used as tools for predicting both short-term and long-term trends in water quality. They are generally classified into two groups based on the degree of empiricism. The two groups consists of the purely empirical types known as black-box models and the theoretical types called ecosystem models. This dissertation deals with both types of water quality models. The first part deals with empirical phosphorus models. The theory behind this class of models is discussed, leading to the development of an empirical phosphorus model using data from 79 western US lakes. A new approach to trophic state classificationmore » is introduced. The data used for the model was obtained from the Environmental Protection Agency National Eutrophication Study (EPA-NES) of western US lakes. The second portion of the dissertation discusses the development of an ecosystem model for culturally eutrophic Liberty Lake situated in eastern Washington State. The model is capable of simulating chlorophyll-a, phosphorus, and nitrogen levels in the lake on a weekly basis. For computing sediment release rates of phosphorus and nitrogen, equations based on laboratory bench-top studies using sediment samples from Liberty Lake are used. The model is used to simulate certain hypothetical nutrient control techniques such as phosphorus flushing, precipitation, and diversion.« less

Attachment-based family therapy for depressed and suicidal adolescents: theory, clinical model and empirical support.

PubMed

Ewing, E Stephanie Krauthamer; Diamond, Guy; Levy, Suzanne

2015-01-01

Attachment-Based Family Therapy (ABFT) is a manualized family-based intervention designed for working with depressed adolescents, including those at risk for suicide, and their families. It is an empirically informed and supported treatment. ABFT has its theoretical underpinnings in attachment theory and clinical roots in structural family therapy and emotion focused therapies. ABFT relies on a transactional model that aims to transform the quality of adolescent-parent attachment, as a means of providing the adolescent with a more secure relationship that can support them during challenging times generally, and the crises related to suicidal thinking and behavior, specifically. This article reviews: (1) the theoretical foundations of ABFT (attachment theory, models of emotional development); (2) the ABFT clinical model, including training and supervision factors; and (3) empirical support.

Towards a New Paradigm of Moral Personhood

ERIC Educational Resources Information Center

Frimer, Jeremy A.; Walker, Lawrence J.

2008-01-01

Moral psychology is between paradigms. Kohlberg's model of moral rationality has proved inadequate in explaining action; yet its augmentation--moral personality--awaits empirical embodiment. This article addresses some critical issues in developing a comprehensive empirical paradigm of moral personhood. Is a first-person or a third-person…

Measuring Service Quality in Higher Education: Development of a Hierarchical Model (HESQUAL)

ERIC Educational Resources Information Center

Teeroovengadum, Viraiyan; Kamalanabhan, T. J.; Seebaluck, Ashley Keshwar

2016-01-01

Purpose: This paper aims to develop and empirically test a hierarchical model for measuring service quality in higher education. Design/methodology/approach: The first phase of the study consisted of qualitative research methods and a comprehensive literature review, which allowed the development of a conceptual model comprising 53 service quality…

An empirical model for polarized and cross-polarized scattering from a vegetation layer

NASA Technical Reports Server (NTRS)

Liu, H. L.; Fung, A. K.

1988-01-01

An empirical model for scattering from a vegetation layer above an irregular ground surface is developed in terms of the first-order solution for like-polarized scattering and the second-order solution for cross-polarized scattering. The effects of multiple scattering within the layer and at the surface-volume boundary are compensated by using a correction factor based on the matrix doubling method. The major feature of this model is that all parameters in the model are physical parameters of the vegetation medium. There are no regression parameters. Comparisons of this empirical model with theoretical matrix-doubling method and radar measurements indicate good agreements in polarization, angular trends, and k sub a up to 4, where k is the wave number and a is the disk radius. The computational time is shortened by a factor of 8, relative to the theoretical model calculation.

Generic domain models in software engineering

NASA Technical Reports Server (NTRS)

Maiden, Neil

1992-01-01

This paper outlines three research directions related to domain-specific software development: (1) reuse of generic models for domain-specific software development; (2) empirical evidence to determine these generic models, namely elicitation of mental knowledge schema possessed by expert software developers; and (3) exploitation of generic domain models to assist modelling of specific applications. It focuses on knowledge acquisition for domain-specific software development, with emphasis on tool support for the most important phases of software development.

An integrated conceptual framework for evaluating and improving 'understanding' in informed consent.

PubMed

Bossert, Sabine; Strech, Daniel

2017-10-17

The development of understandable informed consent (IC) documents has proven to be one of the most important challenges in research with humans as well as in healthcare settings. Therefore, evaluating and improving understanding has been of increasing interest for empirical research on IC. However, several conceptual and practical challenges for the development of understandable IC documents remain unresolved. In this paper, we will outline and systematize some of these challenges. On the basis of our own experiences in empirical user testing of IC documents as well as the relevant literature on understanding in IC, we propose an integrated conceptual model for the development of understandable IC documents. The proposed conceptual model integrates different methods for the participatory improvement of written information, including IC, as well as quantitative methods for measuring understanding in IC. In most IC processes, understandable written information is an important prerequisite for valid IC. To improve the quality of IC documents, a conceptual model for participatory procedures of testing, revising, and retesting can be applied. However, the model presented in this paper needs further theoretical and empirical elaboration and clarification of several conceptual and practical challenges.

Empirical analysis of storm-time energetic electron enhancements

NASA Astrophysics Data System (ADS)

O'Brien, Thomas Paul, III

This Ph.D. thesis documents a program for studying the appearance of energetic electrons in the Earth's outer radiation belts that is associated with many geomagnetic storms. The dynamic evolution of the electron radiation belts is an outstanding empirical problem in both theoretical space physics and its applied sibling, space weather. The project emphasizes the development of empirical tools and their use in testing several theoretical models of the energization of the electron belts. First, I develop the Statistical Asynchronous Regression technique to provide proxy electron fluxes throughout the parts of the radiation belts explored by geosynchronous and GPS spacecraft. Next, I show that a theoretical adiabatic model can relate the local time asymmetry of the proxy geosynchronous fluxes to the asymmetry of the geomagnetic field. Then, I perform a superposed epoch analysis on the proxy fluxes at local noon to identify magnetospheric and interplanetary precursors of relativistic electron enhancements. Finally, I use statistical and neural network phase space analyses to determine the hourly evolution of flux at a virtual stationary monitor. The dynamic equation quantitatively identifies the importance of different drivers of the electron belts. This project provides empirical constraints on theoretical models of electron acceleration.

Lexical processing and organization in bilingual first language acquisition: Guiding future research.

PubMed

DeAnda, Stephanie; Poulin-Dubois, Diane; Zesiger, Pascal; Friend, Margaret

2016-06-01

A rich body of work in adult bilinguals documents an interconnected lexical network across languages, such that early word retrieval is language independent. This literature has yielded a number of influential models of bilingual semantic memory. However, extant models provide limited predictions about the emergence of lexical organization in bilingual first language acquisition (BFLA). Empirical evidence from monolingual infants suggests that lexical networks emerge early in development as children integrate phonological and semantic information. These findings tell us little about the interaction between 2 languages in early bilingual memory. To date, an understanding of when and how languages interact in early bilingual development is lacking. In this literature review, we present research documenting lexical-semantic development across monolingual and bilingual infants. This is followed by a discussion of current models of bilingual language representation and organization and their ability to account for the available empirical evidence. Together, these theoretical and empirical accounts inform and highlight unexplored areas of research and guide future work on early bilingual memory. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Role of Statistical Random-Effects Linear Models in Personalized Medicine.

PubMed

Diaz, Francisco J; Yeh, Hung-Wen; de Leon, Jose

2012-03-01

Some empirical studies and recent developments in pharmacokinetic theory suggest that statistical random-effects linear models are valuable tools that allow describing simultaneously patient populations as a whole and patients as individuals. This remarkable characteristic indicates that these models may be useful in the development of personalized medicine, which aims at finding treatment regimes that are appropriate for particular patients, not just appropriate for the average patient. In fact, published developments show that random-effects linear models may provide a solid theoretical framework for drug dosage individualization in chronic diseases. In particular, individualized dosages computed with these models by means of an empirical Bayesian approach may produce better results than dosages computed with some methods routinely used in therapeutic drug monitoring. This is further supported by published empirical and theoretical findings that show that random effects linear models may provide accurate representations of phase III and IV steady-state pharmacokinetic data, and may be useful for dosage computations. These models have applications in the design of clinical algorithms for drug dosage individualization in chronic diseases; in the computation of dose correction factors; computation of the minimum number of blood samples from a patient that are necessary for calculating an optimal individualized drug dosage in therapeutic drug monitoring; measure of the clinical importance of clinical, demographic, environmental or genetic covariates; study of drug-drug interactions in clinical settings; the implementation of computational tools for web-site-based evidence farming; design of pharmacogenomic studies; and in the development of a pharmacological theory of dosage individualization.

Biomass viability: An experimental study and the development of an empirical mathematical model for submerged membrane bioreactor.

PubMed

Zuthi, M F R; Ngo, H H; Guo, W S; Nghiem, L D; Hai, F I; Xia, S Q; Zhang, Z Q; Li, J X

2015-08-01

This study investigates the influence of key biomass parameters on specific oxygen uptake rate (SOUR) in a sponge submerged membrane bioreactor (SSMBR) to develop mathematical models of biomass viability. Extra-cellular polymeric substances (EPS) were considered as a lumped parameter of bound EPS (bEPS) and soluble microbial products (SMP). Statistical analyses of experimental results indicate that the bEPS, SMP, mixed liquor suspended solids and volatile suspended solids (MLSS and MLVSS) have functional relationships with SOUR and their relative influence on SOUR was in the order of EPS>bEPS>SMP>MLVSS/MLSS. Based on correlations among biomass parameters and SOUR, two independent empirical models of biomass viability were developed. The models were validated using results of the SSMBR. However, further validation of the models for different operating conditions is suggested. Copyright © 2015 Elsevier Ltd. All rights reserved.

Empirical modeling of dynamic behaviors of pneumatic artificial muscle actuators.

PubMed

Wickramatunge, Kanchana Crishan; Leephakpreeda, Thananchai

2013-11-01

Pneumatic Artificial Muscle (PAM) actuators yield muscle-like mechanical actuation with high force to weight ratio, soft and flexible structure, and adaptable compliance for rehabilitation and prosthetic appliances to the disabled as well as humanoid robots or machines. The present study is to develop empirical models of the PAM actuators, that is, a PAM coupled with pneumatic control valves, in order to describe their dynamic behaviors for practical control design and usage. Empirical modeling is an efficient approach to computer-based modeling with observations of real behaviors. Different characteristics of dynamic behaviors of each PAM actuator are due not only to the structures of the PAM actuators themselves, but also to the variations of their material properties in manufacturing processes. To overcome the difficulties, the proposed empirical models are experimentally derived from real physical behaviors of the PAM actuators, which are being implemented. In case studies, the simulated results with good agreement to experimental results, show that the proposed methodology can be applied to describe the dynamic behaviors of the real PAM actuators. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Hindcasting of Equatorial Spread F Using Seasonal Empirical Models

NASA Astrophysics Data System (ADS)

Aswathy, R. P.; Manju, G.

2018-02-01

The role of gravity waves in modulating equatorial spread F (ESF) day-to-day variability is investigated using ionosonde data at Trivandrum (geographic coordinates, 8.5°N, 77°E; mean geomagnetic latitude -0.3°N) a magnetic equatorial location. A novel empirical model that incorporates the combined effects of electrodynamics and gravity waves in modulating ESF occurrence during autumnal equinox season was presented by Aswathy and Manju (2017). In the present study, the height variations of the requisite gravity wave seed perturbations for ESF are examined for the vernal equinoxes, summer solstices, and winter solstices of different years. Subsequently, the empirical model, incorporating the electrodynamical effects and the gravity wave modulation, valid for each of the seasons is developed. Accordingly, for each season, the threshold curve may be demarcated provided the solar flux index (F10.7) is known. The empirical models are validated using the data for high, moderate, and low solar activity years corresponding to each season. In the next stage, this model is to be fine tuned to facilitate the prediction of ESF well before its onset.

Using DFT methodology for more reliable predictive models: Design of inhibitors of Golgi α-Mannosidase II.

PubMed

Bobovská, Adela; Tvaroška, Igor; Kóňa, Juraj

2016-05-01

Human Golgi α-mannosidase II (GMII), a zinc ion co-factor dependent glycoside hydrolase (E.C.3.2.1.114), is a pharmaceutical target for the design of inhibitors with anti-cancer activity. The discovery of an effective inhibitor is complicated by the fact that all known potent inhibitors of GMII are involved in unwanted co-inhibition with lysosomal α-mannosidase (LMan, E.C.3.2.1.24), a relative to GMII. Routine empirical QSAR models for both GMII and LMan did not work with a required accuracy. Therefore, we have developed a fast computational protocol to build predictive models combining interaction energy descriptors from an empirical docking scoring function (Glide-Schrödinger), Linear Interaction Energy (LIE) method, and quantum mechanical density functional theory (QM-DFT) calculations. The QSAR models were built and validated with a library of structurally diverse GMII and LMan inhibitors and non-active compounds. A critical role of QM-DFT descriptors for the more accurate prediction abilities of the models is demonstrated. The predictive ability of the models was significantly improved when going from the empirical docking scoring function to mixed empirical-QM-DFT QSAR models (Q(2)=0.78-0.86 when cross-validation procedures were carried out; and R(2)=0.81-0.83 for a testing set). The average error for the predicted ΔGbind decreased to 0.8-1.1kcalmol(-1). Also, 76-80% of non-active compounds were successfully filtered out from GMII and LMan inhibitors. The QSAR models with the fragmented QM-DFT descriptors may find a useful application in structure-based drug design where pure empirical and force field methods reached their limits and where quantum mechanics effects are critical for ligand-receptor interactions. The optimized models will apply in lead optimization processes for GMII drug developments. Copyright © 2016 Elsevier Inc. All rights reserved.

PROJECT SUMMARY: DEVELOPMENT OF THE VIRTUAL BEACH MODEL, PHASE I: AN EMPIRICAL MODEL

EPA Science Inventory

Mathematical models based on water-quality and other environmental surrogates may help to provide water quality assessment within a few hours and potentially provide one to three day forecasts, providing beach managers and public-health officials a tool for developing beach-speci...

Development of an empirically based dynamic biomechanical strength model

NASA Technical Reports Server (NTRS)

Pandya, A.; Maida, J.; Aldridge, A.; Hasson, S.; Woolford, B.

1992-01-01

The focus here is on the development of a dynamic strength model for humans. Our model is based on empirical data. The shoulder, elbow, and wrist joints are characterized in terms of maximum isolated torque, position, and velocity in all rotational planes. This information is reduced by a least squares regression technique into a table of single variable second degree polynomial equations determining the torque as a function of position and velocity. The isolated joint torque equations are then used to compute forces resulting from a composite motion, which in this case is a ratchet wrench push and pull operation. What is presented here is a comparison of the computed or predicted results of the model with the actual measured values for the composite motion.

Competence and Drug Use: Theoretical Frameworks, Empirical Evidence and Measurement.

ERIC Educational Resources Information Center

Lindenberg, Cathy Strachan; Solorzano, Rosa; Kelley, Maureen; Darrow, Vicki; Gendrop, Sylvia C.; Strickland, Ora

1998-01-01

Discusses the Social Stress Model of Substance Abuse. Summarizes theoretical and conceptual formulations for the construct of competence, reviews empirical evidence for the association of competence with drug use, and describes the preliminary development of a multiscale instrument designed to assess drug-protective competence among low-income…

Preparing Current and Future Practitioners to Integrate Research in Real Practice Settings

ERIC Educational Resources Information Center

Thyer, Bruce A.

2015-01-01

Past efforts aimed at promoting a better integration between research and practice are reviewed. These include the empirical clinical practice movement (ECP), originating within social work; the empirically supported treatment (EST) initiative of clinical psychology; and the evidence-based practice (EBP) model developed within medicine. The…

Health care competition, strategic mission, and patient satisfaction: research model and propositions

PubMed Central

Rivers, Patrick A.; Glover, Saundra H.

2010-01-01

Purpose In all industries, competition among businesses has long been encouraged as a mechanism to increase value for patients. In other words, competition ensures the provision of better products and services to satisfy the needs of customers This paper aims to develop a model that can be used to empirically investigate a number of complex issues and relationships associated with competition in the health care industry. Design/methodology/approach A literature review was conducted. A total of 50 items of literature related to the subject were reviewed.. Various perspectives of competition, the nature of service quality, health system costs, and patient satisfaction in health care are examined Findings A model of the relationship among these variables is developed. The model depicts patient satisfaction as an outcome measure directly dependent on competition. Quality of care and health care systems costs, while also directly dependent on the strategic mission and goals, are considered as determinants of customer satisfaction as well. The model is discussed in the light of propositions for empirical research. Practical implications Empirical studies based on the model proposed in this paper should help identify areas with significant impact on patient satisfaction while maintaining high quality of service at lower costs in a competitive environment. Originality/value The authors develop a research model which included propositions to examine the complex issues of competition in the health care industry. PMID:19579575

The efficacy of using inventory data to develop optimal diameter increment models

Treesearch

Don C. Bragg

2002-01-01

Most optimal tree diameter growth models have arisen through either the conceptualization of physiological processes or the adaptation of empirical increment models. However, surprisingly little effort has been invested in the melding of these approaches even though it is possible to develop theoretically sound, computationally efficient optimal tree growth models...

Review of Thawing Time Prediction Models Depending
on Process Conditions and Product Characteristics

PubMed Central

Kluza, Franciszek; Spiess, Walter E. L.; Kozłowicz, Katarzyna

2016-01-01

Summary Determining thawing times of frozen foods is a challenging problem as the thermophysical properties of the product change during thawing. A number of calculation models and solutions have been developed. The proposed solutions range from relatively simple analytical equations based on a number of assumptions to a group of empirical approaches that sometimes require complex calculations. In this paper analytical, empirical and graphical models are presented and critically reviewed. The conditions of solution, limitations and possible applications of the models are discussed. The graphical and semi--graphical models are derived from numerical methods. Using the numerical methods is not always possible as running calculations takes time, whereas the specialized software and equipment are not always cheap. For these reasons, the application of analytical-empirical models is more useful for engineering. It is demonstrated that there is no simple, accurate and feasible analytical method for thawing time prediction. Consequently, simplified methods are needed for thawing time estimation of agricultural and food products. The review reveals the need for further improvement of the existing solutions or development of new ones that will enable accurate determination of thawing time within a wide range of practical conditions of heat transfer during processing. PMID:27904387

Integrated urban systems model with multiple transportation supply agents.

DOT National Transportation Integrated Search

2012-10-01

This project demonstrates the feasibility of developing quantitative models that can forecast future networks under : current and alternative transportation planning processes. The current transportation planning process is modeled : based on empiric...

Forecasting stochastic neural network based on financial empirical mode decomposition.

PubMed

Wang, Jie; Wang, Jun

2017-06-01

In an attempt to improve the forecasting accuracy of stock price fluctuations, a new one-step-ahead model is developed in this paper which combines empirical mode decomposition (EMD) with stochastic time strength neural network (STNN). The EMD is a processing technique introduced to extract all the oscillatory modes embedded in a series, and the STNN model is established for considering the weight of occurrence time of the historical data. The linear regression performs the predictive availability of the proposed model, and the effectiveness of EMD-STNN is revealed clearly through comparing the predicted results with the traditional models. Moreover, a new evaluated method (q-order multiscale complexity invariant distance) is applied to measure the predicted results of real stock index series, and the empirical results show that the proposed model indeed displays a good performance in forecasting stock market fluctuations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Design of exchange-correlation functionals through the correlation factor approach

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

Pavlíková Přecechtělová, Jana, E-mail: j.precechtelova@gmail.com, E-mail: Matthias.Ernzerhof@UMontreal.ca; Institut für Chemie, Theoretische Chemie / Quantenchemie, Sekr. C7, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin; Bahmann, Hilke

The correlation factor model is developed in which the spherically averaged exchange-correlation hole of Kohn-Sham theory is factorized into an exchange hole model and a correlation factor. The exchange hole model reproduces the exact exchange energy per particle. The correlation factor is constructed in such a manner that the exchange-correlation energy correctly reduces to exact exchange in the high density and rapidly varying limits. Four different correlation factor models are presented which satisfy varying sets of physical constraints. Three models are free from empirical adjustments to experimental data, while one correlation factor model draws on one empirical parameter. The correlationmore » factor models are derived in detail and the resulting exchange-correlation holes are analyzed. Furthermore, the exchange-correlation energies obtained from the correlation factor models are employed to calculate total energies, atomization energies, and barrier heights. It is shown that accurate, non-empirical functionals can be constructed building on exact exchange. Avenues for further improvements are outlined as well.« less

Quality evaluation of health information system's architectures developed using the HIS-DF methodology.

PubMed

López, Diego M; Blobel, Bernd; Gonzalez, Carolina

2010-01-01

Requirement analysis, design, implementation, evaluation, use, and maintenance of semantically interoperable Health Information Systems (HIS) have to be based on eHealth standards. HIS-DF is a comprehensive approach for HIS architectural development based on standard information models and vocabulary. The empirical validity of HIS-DF has not been demonstrated so far. Through an empirical experiment, the paper demonstrates that using HIS-DF and HL7 information models, semantic quality of HIS architecture can be improved, compared to architectures developed using traditional RUP process. Semantic quality of the architecture has been measured in terms of model's completeness and validity metrics. The experimental results demonstrated an increased completeness of 14.38% and an increased validity of 16.63% when using the HIS-DF and HL7 information models in a sample HIS development project. Quality assurance of the system architecture in earlier stages of HIS development presumes an increased quality of final HIS systems, which supposes an indirect impact on patient care.

Empirical relationships between soil moisture, albedo, and the planetary boundary layer height: a two-layer bucket model approach

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Z. M.; Papuga, S. A.

2013-12-01

In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used data from the Santa Rita Creosote Ameriflux site and Tucson Airport atmospheric sounding to generate empirical relationships between soil moisture, albedo and PBLh. We developed empirical relationships and show that at least 50% of the variation in PBLh can be explained by soil moisture and albedo. Then, we used a stochastically driven two-layer bucket model of soil moisture dynamics and our empirical relationships to model PBLh. We explored soil moisture dynamics under three different mean annual precipitation regimes: current, increase, and decrease, to evaluate at the influence on soil moisture on land surface-atmospheric processes. While our precipitation regimes are simple, they represent future precipitation regimes that can influence the two soil layers in our conceptual framework. For instance, an increase in annual precipitation, could impact on deep soil moisture and atmospheric processes if precipitation events remain intense. We observed that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface - atmosphere applications are of great value.

History of research on modelling gypsy moth population ecology

Treesearch

J. J. Colbert

1991-01-01

History of research to develop models of gypsy moth population dynamics and some related studies are described. Empirical regression-based models are reviewed, and then the more comprehensive process models are discussed. Current model- related research efforts are introduced.

Empirical fitness landscapes and the predictability of evolution.

PubMed

de Visser, J Arjan G M; Krug, Joachim

2014-07-01

The genotype-fitness map (that is, the fitness landscape) is a key determinant of evolution, yet it has mostly been used as a superficial metaphor because we know little about its structure. This is now changing, as real fitness landscapes are being analysed by constructing genotypes with all possible combinations of small sets of mutations observed in phylogenies or in evolution experiments. In turn, these first glimpses of empirical fitness landscapes inspire theoretical analyses of the predictability of evolution. Here, we review these recent empirical and theoretical developments, identify methodological issues and organizing principles, and discuss possibilities to develop more realistic fitness landscape models.

Two modeling strategies for empirical Bayes estimation

PubMed Central

Efron, Bradley

2014-01-01

Empirical Bayes methods use the data from parallel experiments, for instance observations Xk ~ 𝒩 (Θk, 1) for k = 1, 2, …, N, to estimate the conditional distributions Θk|Xk. There are two main estimation strategies: modeling on the θ space, called “g-modeling” here, and modeling on the×space, called “f-modeling.” The two approaches are de- scribed and compared. A series of computational formulas are developed to assess their frequentist accuracy. Several examples, both contrived and genuine, show the strengths and limitations of the two strategies. PMID:25324592

A Model of Therapist Competencies for the Empirically Supported Interpersonal Psychotherapy for Adolescent Depression

ERIC Educational Resources Information Center

Sburlati, Elizabeth S.; Lyneham, Heidi J.; Mufson, Laura H.; Schniering, Carolyn A.

2012-01-01

In order to treat adolescent depression, a number of empirically supported treatments (ESTs) have been developed from both the cognitive behavioral therapy (CBT) and interpersonal psychotherapy (IPT-A) frameworks. Research has shown that in order for these treatments to be implemented in routine clinical practice (RCP), effective therapist…

An Empirical Examination of Individual and System Characteristics on Enhancing E-Learning Acceptance

ERIC Educational Resources Information Center

Lee, Yi-Hsuan; Hsiao, Chan; Purnomo, Sutrisno Hadi

2014-01-01

Due to the continued prevalence of e-learning underutilization in Indonesia's higher education context, this study empirically examines individual and system characteristics believed to influence students' acceptance of e-learning systems. The proposed research model is developed to examine the influence of five characteristics of the Technology…

Mechanistic-Empirical Pavement Design Guide Flexible Pavement Performance Prediction Models Volume III Field Guide - Calibration and User's Guide for the Mechanistic-Empirical Pavement Design Guide

DOT National Transportation Integrated Search

2007-08-01

The objective of this research study was to develop performance characteristics or variables (e.g., ride quality, rutting, : fatigue cracking, transverse cracking) of flexible pavements in Montana, and to use these characteristics in the : implementa...

An Empirical Model of Culture of Assessment in Student Affairs

ERIC Educational Resources Information Center

Fuller, Matther B.; Lane, Forrest C.

2017-01-01

Student affairs, like all arms of academe, has taken up the mantle of assessing college student learning and development in their unique programs and experiences. Yet, cultures of assessment in student affairs organizations are rarely examined empirically. This study provides results from an exploratory factor analysis of data gathered using the…

Understanding and Modeling Freight Stakeholder Behavior

DOT National Transportation Integrated Search

2012-04-01

This project developed a conceptual model of private-sector freight stakeholder decisions and interactions for : forecasting freight demands in response to key policy variables. Using East Central Wisconsin as a study area, empirical : models were de...

Empirical and model study on Travel-entering China

NASA Astrophysics Data System (ADS)

Han, Xue-Fang; Chen, Qi-Juan; Chang, Hui; He, Da-Ren

2006-03-01

We have done an empirical investigation on the travel-entering China from abroad to 31 regions of Chinese Mainland in recent ten years, including the development of the traveler's number, the traveler's number distribution for the traveler's home regions, the traveler's number distribution for the traveler's destination regions in Chinese mainland, and so on. We also suggest a dynamic model for simulating the competition between the 31 regions in the traveling market by considering two main influence factors, the attracting factor of the travel destinations and the distance between the destination and the home regions of the travelers. The simulation results show a good agreement with the empirical data. We expect the model could suggest some advice and thoughts to the travel-entering management departments in China and may be also for other countries.

Learning practice: a new model of health visitor intervention to drive outcomes.

PubMed

Ebeid, Ann

2012-03-01

Although there is a body of literature related to how hospital nurses develop skill, judgement or expertise there is little empirical work that focuses on understanding and developing health visiting expertise. The aims of this paper are: to identify a typology of health visitor skills, knowledge and cognition in use and the nature of health visitor expertise; to present an expert model of practice as a practice learning tool; to locate this model in context of my 2007 empirical research. This explored the problems of families and children in need and how they were supported by health visitors. This new practice model is timely in view of the need to train more health visitors, educators and practice facilitators as set out in the Health Visitor Implementation Plan.

Simulating the Risk of Liver Fluke Infection using a Mechanistic Hydro-epidemiological Model

NASA Astrophysics Data System (ADS)

Beltrame, Ludovica; Dunne, Toby; Rose, Hannah; Walker, Josephine; Morgan, Eric; Vickerman, Peter; Wagener, Thorsten

2016-04-01

Liver Fluke (Fasciola hepatica) is a common parasite found in livestock and responsible for considerable economic losses throughout the world. Risk of infection is strongly influenced by climatic and hydrological conditions, which characterise the host environment for parasite development and transmission. Despite on-going control efforts, increases in fluke outbreaks have been reported in recent years in the UK, and have been often attributed to climate change. Currently used fluke risk models are based on empirical relationships derived between historical climate and incidence data. However, hydro-climate conditions are becoming increasingly non-stationary due to climate change and direct anthropogenic impacts such as land use change, making empirical models unsuitable for simulating future risk. In this study we introduce a mechanistic hydro-epidemiological model for Liver Fluke, which explicitly simulates habitat suitability for disease development in space and time, representing the parasite life cycle in connection with key environmental conditions. The model is used to assess patterns of Liver Fluke risk for two catchments in the UK under current and potential future climate conditions. Comparisons are made with a widely used empirical model employing different datasets, including data from regional veterinary laboratories. Results suggest that mechanistic models can achieve adequate predictive ability and support adaptive fluke control strategies under climate change scenarios.

Contributions of Dynamic Systems Theory to Cognitive Development

PubMed Central

Spencer, John P.; Austin, Andrew; Schutte, Anne R.

2015-01-01

This paper examines the contributions of dynamic systems theory to the field of cognitive development, focusing on modeling using dynamic neural fields. A brief overview highlights the contributions of dynamic systems theory and the central concepts of dynamic field theory (DFT). We then probe empirical predictions and findings generated by DFT around two examples—the DFT of infant perseverative reaching that explains the Piagetian A-not-B error, and the DFT of spatial memory that explain changes in spatial cognition in early development. A systematic review of the literature around these examples reveals that computational modeling is having an impact on empirical research in cognitive development; however, this impact does not extend to neural and clinical research. Moreover, there is a tendency for researchers to interpret models narrowly, anchoring them to specific tasks. We conclude on an optimistic note, encouraging both theoreticians and experimentalists to work toward a more theory-driven future. PMID:26052181

The 2 × 2 Standpoints Model of Achievement Goals

PubMed Central

Korn, Rachel M.; Elliot, Andrew J.

2016-01-01

In the present research, we proposed and tested a 2 × 2 standpoints model of achievement goals grounded in the development-demonstration and approach-avoidance distinctions. Three empirical studies are presented. Study 1 provided evidence supporting the structure and psychometric properties of a newly developed measure of the goals of the 2 × 2 standpoints model. Study 2 documented the predictive utility of these goal constructs for intrinsic motivation: development-approach and development-avoidance goals were positive predictors, and demonstration-avoidance goals were a negative predictor of intrinsic motivation. Study 3 documented the predictive utility of these goal constructs for performance attainment: Demonstration-approach goals were a positive predictor and demonstration-avoidance goals were a negative predictor of exam performance. The conceptual and empirical contributions of the present research were discussed within the broader context of existing achievement goal theory and research. PMID:27242641

Role of Statistical Random-Effects Linear Models in Personalized Medicine

PubMed Central

Diaz, Francisco J; Yeh, Hung-Wen; de Leon, Jose

2012-01-01

Some empirical studies and recent developments in pharmacokinetic theory suggest that statistical random-effects linear models are valuable tools that allow describing simultaneously patient populations as a whole and patients as individuals. This remarkable characteristic indicates that these models may be useful in the development of personalized medicine, which aims at finding treatment regimes that are appropriate for particular patients, not just appropriate for the average patient. In fact, published developments show that random-effects linear models may provide a solid theoretical framework for drug dosage individualization in chronic diseases. In particular, individualized dosages computed with these models by means of an empirical Bayesian approach may produce better results than dosages computed with some methods routinely used in therapeutic drug monitoring. This is further supported by published empirical and theoretical findings that show that random effects linear models may provide accurate representations of phase III and IV steady-state pharmacokinetic data, and may be useful for dosage computations. These models have applications in the design of clinical algorithms for drug dosage individualization in chronic diseases; in the computation of dose correction factors; computation of the minimum number of blood samples from a patient that are necessary for calculating an optimal individualized drug dosage in therapeutic drug monitoring; measure of the clinical importance of clinical, demographic, environmental or genetic covariates; study of drug-drug interactions in clinical settings; the implementation of computational tools for web-site-based evidence farming; design of pharmacogenomic studies; and in the development of a pharmacological theory of dosage individualization. PMID:23467392

CloudSat-Constrained Cloud Ice Water Path and Cloud Top Height Retrievals from MHS 157 and 183.3 GHz Radiances

NASA Technical Reports Server (NTRS)

Gong, J.; Wu, D. L.

2014-01-01

Ice water path (IWP) and cloud top height (ht) are two of the key variables in determining cloud radiative and thermodynamical properties in climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3+/-3 and 190.3 GHz radiances of the Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining the empirical forward models between collocated and coincident measurements of CloudSat IWP and MHS cloud-induced radiance depression (Tcir) at these channels. The empirical forward model is represented by a lookup table (LUT) of Tcir-IWP relationships as a function of ht and the frequency channel.With ht simultaneously retrieved, the IWP is found to be more accurate. The useful range of the MHS IWP retrieval is between 0.5 and 10 kg/sq m, and agrees well with CloudSat in terms of the normalized probability density function (PDF). Compared to the empirical model, current operational radiative transfer models (RTMs) still have significant uncertainties in characterizing the observed Tcir-IWP relationships. Therefore, the empirical LUT method developed here remains an effective approach to retrieving ice cloud properties from the MHS-like microwave channels.

The dual process model of coping with bereavement: a decade on.

PubMed

Stroebe, Margaret; Schut, Henk

2010-01-01

The Dual Process Model of Coping with Bereavement (DPM; Stroebe & Schut, 1999) is described in this article. The rationale is given as to why this model was deemed necessary and how it was designed to overcome limitations of earlier models of adaptive coping with loss. Although building on earlier theoretical formulations, it contrasts with other models along a number of dimensions which are outlined. In addition to describing the basic parameters of the DPM, theoretical and empirical developments that have taken place since the original publication of the model are summarized. Guidelines for future research are given focusing on principles that should be followed to put the model to stringent empirical test.

Determination of errors in derived magnetic field directions in geosynchronous orbit: results from a statistical approach

NASA Astrophysics Data System (ADS)

Chen, Yue; Cunningham, Gregory; Henderson, Michael

2016-09-01

This study aims to statistically estimate the errors in local magnetic field directions that are derived from electron directional distributions measured by Los Alamos National Laboratory geosynchronous (LANL GEO) satellites. First, by comparing derived and measured magnetic field directions along the GEO orbit to those calculated from three selected empirical global magnetic field models (including a static Olson and Pfitzer 1977 quiet magnetic field model, a simple dynamic Tsyganenko 1989 model, and a sophisticated dynamic Tsyganenko 2001 storm model), it is shown that the errors in both derived and modeled directions are at least comparable. Second, using a newly developed proxy method as well as comparing results from empirical models, we are able to provide for the first time circumstantial evidence showing that derived magnetic field directions should statistically match the real magnetic directions better, with averaged errors < ˜ 2°, than those from the three empirical models with averaged errors > ˜ 5°. In addition, our results suggest that the errors in derived magnetic field directions do not depend much on magnetospheric activity, in contrast to the empirical field models. Finally, as applications of the above conclusions, we show examples of electron pitch angle distributions observed by LANL GEO and also take the derived magnetic field directions as the real ones so as to test the performance of empirical field models along the GEO orbits, with results suggesting dependence on solar cycles as well as satellite locations. This study demonstrates the validity and value of the method that infers local magnetic field directions from particle spin-resolved distributions.

Modelling land use change with generalized linear models--a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana.

PubMed

Aspinall, Richard

2004-08-01

This paper develops an approach to modelling land use change that links model selection and multi-model inference with empirical models and GIS. Land use change is frequently studied, and understanding gained, through a process of modelling that is an empirical analysis of documented changes in land cover or land use patterns. The approach here is based on analysis and comparison of multiple models of land use patterns using model selection and multi-model inference. The approach is illustrated with a case study of rural housing as it has developed for part of Gallatin County, Montana, USA. A GIS contains the location of rural housing on a yearly basis from 1860 to 2000. The database also documents a variety of environmental and socio-economic conditions. A general model of settlement development describes the evolution of drivers of land use change and their impacts in the region. This model is used to develop a series of different models reflecting drivers of change at different periods in the history of the study area. These period specific models represent a series of multiple working hypotheses describing (a) the effects of spatial variables as a representation of social, economic and environmental drivers of land use change, and (b) temporal changes in the effects of the spatial variables as the drivers of change evolve over time. Logistic regression is used to calibrate and interpret these models and the models are then compared and evaluated with model selection techniques. Results show that different models are 'best' for the different periods. The different models for different periods demonstrate that models are not invariant over time which presents challenges for validation and testing of empirical models. The research demonstrates (i) model selection as a mechanism for rating among many plausible models that describe land cover or land use patterns, (ii) inference from a set of models rather than from a single model, (iii) that models can be developed based on hypothesised relationships based on consideration of underlying and proximate causes of change, and (iv) that models are not invariant over time.

Developing an Adequately Specified Model of State Level Student Achievement with Multilevel Data.

ERIC Educational Resources Information Center

Bernstein, Lawrence

Limitations of using linear, unilevel regression procedures in modeling student achievement are discussed. This study is a part of a broader study that is developing an empirically-based predictive model of variables associated with academic achievement from a multilevel perspective and examining the differences by which parameters are estimated…

Role Modelling in Manager Development: Learning that Which Cannot Be Taught

ERIC Educational Resources Information Center

Warhurst, Russell

2011-01-01

Purpose: This is an empirical article which aims to examine the extent and nature of management role modelling and the learning achieved from role modelling. The article argues that the spread of taught management development and formal mentoring programmes has resulted in the neglect of practice-knowledge and facets of managerial character…

Development of an Empirically Based Learning Performances Framework for Third-Grade Students' Model-Based Explanations about Plant Processes

ERIC Educational Resources Information Center

Zangori, Laura; Forbes, Cory T.

2016-01-01

To develop scientific literacy, elementary students should engage in knowledge building of core concepts through scientific practice (Duschl, Schweingruber, & Schouse, 2007). A core scientific practice is engagement in scientific modeling to build conceptual understanding about discipline-specific concepts. Yet scientific modeling remains…

A Theoretical Model of Children's Storytelling Using Physically-Oriented Technologies (SPOT)

ERIC Educational Resources Information Center

Guha, Mona Leigh; Druin, Allison; Montemayor, Jaime; Chipman, Gene; Farber, Allison

2007-01-01

This paper develops a model of children's storytelling using Physically-Oriented Technology (SPOT). The SPOT model draws upon literature regarding current physical storytelling technologies and was developed using a grounded theory approach to qualitative research. This empirical work focused on the experiences of 18 children, ages 5-6, who worked…

An empirical propellant response function for combustion stability predictions

NASA Technical Reports Server (NTRS)

Hessler, R. O.

1980-01-01

An empirical response function model was developed for ammonium perchlorate propellants to supplant T-burner testing at the preliminary design stage. The model was developed by fitting a limited T-burner data base, in terms of oxidizer size and concentration, to an analytical two parameter response function expression. Multiple peaks are predicted, but the primary effect is of a single peak for most formulations, with notable bulges for the various AP size fractions. The model was extended to velocity coupling with the assumption that dynamic response was controlled primarily by the solid phase described by the two parameter model. The magnitude of velocity coupling was then scaled using an erosive burning law. Routine use of the model for stability predictions on a number of propulsion units indicates that the model tends to overpredict propellant response. It is concluded that the model represents a generally conservative prediction tool, suited especially for the preliminary design stage when T-burner data may not be readily available. The model work included development of a rigorous summation technique for pseudopropellant properties and of a concept for modeling ordered packing of particulates.

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

Simpson, L.; Britt, J.; Birkmire, R.

ITN Energy Systems, Inc., and Global Solar Energy, Inc., assisted by NREL's PV Manufacturing R&D program, have continued to advance CIGS production technology by developing trajectory-oriented predictive/control models, fault-tolerance control, control platform development, in-situ sensors, and process improvements. Modeling activities included developing physics-based and empirical models for CIGS and sputter-deposition processing, implementing model-based control, and applying predictive models to the construction of new evaporation sources and for control. Model-based control is enabled by implementing reduced or empirical models into a control platform. Reliability improvement activities include implementing preventive maintenance schedules; detecting failed sensors/equipment and reconfiguring to tinue processing; and systematicmore » development of fault prevention and reconfiguration strategies for the full range of CIGS PV production deposition processes. In-situ sensor development activities have resulted in improved control and indicated the potential for enhanced process status monitoring and control of the deposition processes. Substantial process improvements have been made, including significant improvement in CIGS uniformity, thickness control, efficiency, yield, and throughput. In large measure, these gains have been driven by process optimization, which in turn have been enabled by control and reliability improvements due to this PV Manufacturing R&D program.« less

Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

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

Brown, C. W.; Hood, Raleigh R.; Long, Wen

The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat modelsmore » of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanistic–empirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.« less

The Impact of Professional Development: A Theoretical Model for Empirical Research, Evaluation, Planning and Conducting Training and Development Programmes

ERIC Educational Resources Information Center

Huber, Stephan Gerhard

2011-01-01

This paper considers several trends in professional development programmes found internationally. The use of multiple learning approaches and of different modes and types of learning in PD is described. Various theories and models of evaluation are discussed in the light of common professional development activities. Several recommendations are…

EIA models and capacity building in Viet Nam: an analysis of development aid programs

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

Doberstein, Brent

2004-04-01

There has been a decided lack of empirical research examining development aid agencies as 'agents of change' in environmental impact assessment (EIA) systems in developing countries, particularly research examining the model of environmental planning practice promoted by aid agencies as part of capacity building. This paper briefly traces a conceptual framework of EIA, then introduces the concept of 'EIA capacity building'. Using Viet Nam as a case study, the paper then outlines the empirical results of the research, focusing on the extent to which aid agency capacity-building programs promoted a Technical vs. Planning Model of EIA and on the coherencemore » of capacity-building efforts across all aid programs. A discussion follows, where research results are interpreted within the Vietnamese context, and implications of research results are identified for three main groups of actors. The paper concludes by calling for development aid agencies to reconceptualise EIA capacity building as an opportunity to transform developing countries' development planning processes.« less

Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

NASA Astrophysics Data System (ADS)

Moura, Antonio Divino; Hastenrath, Stefan

2004-07-01

Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

Smsynth: AN Imagery Synthesis System for Soil Moisture Retrieval

NASA Astrophysics Data System (ADS)

Cao, Y.; Xu, L.; Peng, J.

2018-04-01

Soil moisture (SM) is a important variable in various research areas, such as weather and climate forecasting, agriculture, drought and flood monitoring and prediction, and human health. An ongoing challenge in estimating SM via synthetic aperture radar (SAR) is the development of the retrieval SM methods, especially the empirical models needs as training samples a lot of measurements of SM and soil roughness parameters which are very difficult to acquire. As such, it is difficult to develop empirical models using realistic SAR imagery and it is necessary to develop methods to synthesis SAR imagery. To tackle this issue, a SAR imagery synthesis system based on the SM named SMSynth is presented, which can simulate radar signals that are realistic as far as possible to the real SAR imagery. In SMSynth, SAR backscatter coefficients for each soil type are simulated via the Oh model under the Bayesian framework, where the spatial correlation is modeled by the Markov random field (MRF) model. The backscattering coefficients simulated based on the designed soil parameters and sensor parameters are added into the Bayesian framework through the data likelihood where the soil parameters and sensor parameters are set as realistic as possible to the circumstances on the ground and in the validity range of the Oh model. In this way, a complete and coherent Bayesian probabilistic framework is established. Experimental results show that SMSynth is capable of generating realistic SAR images that suit the needs of a large amount of training samples of empirical models.

Gravity wave control on ESF day-to-day variability: An empirical approach

NASA Astrophysics Data System (ADS)

Aswathy, R. P.; Manju, G.

2017-06-01

The gravity wave control on the daily variation in nighttime ionization irregularity occurrence is studied using ionosonde data for the period 2002-2007 at magnetic equatorial location Trivandrum. Recent studies during low solar activity period have revealed that the seed perturbations should have the threshold amplitude required to trigger equatorial spread F (ESF), at a particular altitude and that this threshold amplitude undergoes seasonal and solar cycle changes. In the present study, the altitude variation of the threshold seed perturbations is examined for autumnal equinox of different years. Thereafter, a unique empirical model, incorporating the electrodynamical effects and the gravity wave modulation, is developed. Using the model the threshold curve for autumnal equinox season of any year may be delineated if the solar flux index (F10.7) is known. The empirical model is validated using the data for high, moderate, and low solar epochs in 2001, 2004, and 1995, respectively. This model has the potential to be developed further, to forecast ESF incidence, if the base height of ionosphere is in the altitude region where electrodynamics controls the occurrence of ESF. ESF irregularities are harmful for communication and navigation systems, and therefore, research is ongoing globally to predict them. In this context, this study is crucial for evolving a methodology to predict communication as well as navigation outages.