empirically based models: Topics by Science.gov

Sample records for empirically based models

Bridging process-based and empirical approaches to modeling tree growth

Treesearch

Harry T. Valentine; Annikki Makela; Annikki Makela

2005-01-01

The gulf between process-based and empirical approaches to modeling tree growth may be bridged, in part, by the use of a common model. To this end, we have formulated a process-based model of tree growth that can be fitted and applied in an empirical mode. The growth model is grounded in pipe model theory and an optimal control model of crown development. Together, the...
EMPIRE and pyenda: Two ensemble-based data assimilation systems written in Fortran and Python

NASA Astrophysics Data System (ADS)

Geppert, Gernot; Browne, Phil; van Leeuwen, Peter Jan; Merker, Claire

2017-04-01

We present and compare the features of two ensemble-based data assimilation frameworks, EMPIRE and pyenda. Both frameworks allow to couple models to the assimilation codes using the Message Passing Interface (MPI), leading to extremely efficient and fast coupling between models and the data-assimilation codes. The Fortran-based system EMPIRE (Employing Message Passing Interface for Researching Ensembles) is optimized for parallel, high-performance computing. It currently includes a suite of data assimilation algorithms including variants of the ensemble Kalman and several the particle filters. EMPIRE is targeted at models of all kinds of complexity and has been coupled to several geoscience models, eg. the Lorenz-63 model, a barotropic vorticity model, the general circulation model HadCM3, the ocean model NEMO, and the land-surface model JULES. The Python-based system pyenda (Python Ensemble Data Assimilation) allows Fortran- and Python-based models to be used for data assimilation. Models can be coupled either using MPI or by using a Python interface. Using Python allows quick prototyping and pyenda is aimed at small to medium scale models. pyenda currently includes variants of the ensemble Kalman filter and has been coupled to the Lorenz-63 model, an advection-based precipitation nowcasting scheme, and the dynamic global vegetation model JSBACH.
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.
Tracking Expected Improvements of Decadal Prediction in Climate Services

NASA Astrophysics Data System (ADS)

Suckling, E.; Thompson, E.; Smith, L. A.

2013-12-01

Physics-based simulation models are ultimately expected to provide the best available (decision-relevant) probabilistic climate predictions, as they can capture the dynamics of the Earth System across a range of situations, situations for which observations for the construction of empirical models are scant if not nonexistent. This fact in itself provides neither evidence that predictions from today's Earth Systems Models will outperform today's empirical models, nor a guide to the space and time scales on which today's model predictions are adequate for a given purpose. Empirical (data-based) models are employed to make probability forecasts on decadal timescales. The skill of these forecasts is contrasted with that of state-of-the-art climate models, and the challenges faced by each approach are discussed. The focus is on providing decision-relevant probability forecasts for decision support. An empirical model, known as Dynamic Climatology is shown to be competitive with CMIP5 climate models on decadal scale probability forecasts. Contrasting the skill of simulation models not only with each other but also with empirical models can reveal the space and time scales on which a generation of simulation models exploits their physical basis effectively. It can also quantify their ability to add information in the formation of operational forecasts. Difficulties (i) of information contamination (ii) of the interpretation of probabilistic skill and (iii) of artificial skill complicate each modelling approach, and are discussed. "Physics free" empirical models provide fixed, quantitative benchmarks for the evaluation of ever more complex climate models, that is not available from (inter)comparisons restricted to only complex models. At present, empirical models can also provide a background term for blending in the formation of probability forecasts from ensembles of simulation models. In weather forecasting this role is filled by the climatological distribution, and can significantly enhance the value of longer lead-time weather forecasts to those who use them. It is suggested that the direct comparison of simulation models with empirical models become a regular component of large model forecast intercomparison and evaluation. This would clarify the extent to which a given generation of state-of-the-art simulation models provide information beyond that available from simpler empirical models. It would also clarify current limitations in using simulation forecasting for decision support. No model-based probability forecast is complete without a quantitative estimate if its own irrelevance; this estimate is likely to increase as a function of lead time. A lack of decision-relevant quantitative skill would not bring the science-based foundation of anthropogenic warming into doubt. Similar levels of skill with empirical models does suggest a clear quantification of limits, as a function of lead time, for spatial and temporal scales on which decisions based on such model output are expected to prove maladaptive. Failing to clearly state such weaknesses of a given generation of simulation models, while clearly stating their strength and their foundation, risks the credibility of science in support of policy in the long term.
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.
Agent-Based Models in Empirical Social Research

ERIC Educational Resources Information Center

Bruch, Elizabeth; Atwell, Jon

2015-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first…
How "Does" the Comforting Process Work? An Empirical Test of an Appraisal-Based Model of Comforting

ERIC Educational Resources Information Center

Jones, Susanne M.; Wirtz, John G.

2006-01-01

Burleson and Goldsmith's (1998) comforting model suggests an appraisal-based mechanism through which comforting messages can bring about a positive change in emotional states. This study is a first empirical test of three causal linkages implied by the appraisal-based comforting model. Participants (N=258) talked about an upsetting event with a…
An empirical and model study on automobile market in Taiwan

NASA Astrophysics Data System (ADS)

Tang, Ji-Ying; Qiu, Rong; Zhou, Yueping; He, Da-Ren

2006-03-01

We have done an empirical investigation on automobile market in Taiwan including the development of the possession rate of the companies in the market from 1979 to 2003, the development of the largest possession rate, and so on. A dynamic model for describing the competition between the companies is suggested based on the empirical study. In the model each company is given a long-term competition factor (such as technology, capital and scale) and a short-term competition factor (such as management, service and advertisement). Then the companies play games in order to obtain more possession rate in the market under certain rules. Numerical simulation based on the model display a competition developing process, which qualitatively and quantitatively agree with our empirical investigation results.
Performance-Based Service Quality Model: An Empirical Study on Japanese Universities

ERIC Educational Resources Information Center

Sultan, Parves; Wong, Ho

2010-01-01

Purpose: This paper aims to develop and empirically test the performance-based higher education service quality model. Design/methodology/approach: The study develops 67-item instrument for measuring performance-based service quality with a particular focus on the higher education sector. Scale reliability is confirmed using the Cronbach's alpha.…
Transition mixing study empirical model report

NASA Technical Reports Server (NTRS)

Srinivasan, R.; White, C.

1988-01-01

The empirical model developed in the NASA Dilution Jet Mixing Program has been extended to include the curvature effects of transition liners. This extension is based on the results of a 3-D numerical model generated under this contract. The empirical model results agree well with the numerical model results for all tests cases evaluated. The empirical model shows faster mixing rates compared to the numerical model. Both models show drift of jets toward the inner wall of a turning duct. The structure of the jets from the inner wall does not exhibit the familiar kidney-shaped structures observed for the outer wall jets or for jets injected in rectangular ducts.
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 ...
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.
Bias-dependent hybrid PKI empirical-neural model of microwave FETs

NASA Astrophysics Data System (ADS)

Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

2011-10-01

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.
AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH*

PubMed Central

Bruch, Elizabeth; Atwell, Jon

2014-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research. PMID:25983351
Achilles tendons from decorin- and biglycan-null mouse models have inferior mechanical and structural properties predicted by an image-based empirical damage model

PubMed Central

Gordon, J.A.; Freedman, B.R.; Zuskov, A.; Iozzo, R.V.; Birk, D.E.; Soslowsky, L.J.

2015-01-01

Achilles tendons are a common source of pain and injury, and their pathology may originate from aberrant structure function relationships. Small leucine rich proteoglycans (SLRPs) influence mechanical and structural properties in a tendon-specific manner. However, their roles in the Achilles tendon have not been defined. The objective of this study was to evaluate the mechanical and structural differences observed in mouse Achilles tendons lacking class I SLRPs; either decorin or biglycan. In addition, empirical modeling techniques based on mechanical and image-based measures were employed. Achilles tendons from decorin-null (Dcn−/−) and biglycan-null (Bgn−/−) C57BL/6 female mice (N=102) were used. Each tendon underwent a dynamic mechanical testing protocol including simultaneous polarized light image capture to evaluate both structural and mechanical properties of each Achilles tendon. An empirical damage model was adapted for application to genetic variation and for use with image based structural properties to predict tendon dynamic mechanical properties. We found that Achilles tendons lacking decorin and biglycan had inferior mechanical and structural properties that were age dependent; and that simple empirical models, based on previously described damage models, were predictive of Achilles tendon dynamic modulus in both decorin- and biglycan-null mice. PMID:25888014
Achilles tendons from decorin- and biglycan-null mouse models have inferior mechanical and structural properties predicted by an image-based empirical damage model.

PubMed

Gordon, J A; Freedman, B R; Zuskov, A; Iozzo, R V; Birk, D E; Soslowsky, L J

2015-07-16

Achilles tendons are a common source of pain and injury, and their pathology may originate from aberrant structure function relationships. Small leucine rich proteoglycans (SLRPs) influence mechanical and structural properties in a tendon-specific manner. However, their roles in the Achilles tendon have not been defined. The objective of this study was to evaluate the mechanical and structural differences observed in mouse Achilles tendons lacking class I SLRPs; either decorin or biglycan. In addition, empirical modeling techniques based on mechanical and image-based measures were employed. Achilles tendons from decorin-null (Dcn(-/-)) and biglycan-null (Bgn(-/-)) C57BL/6 female mice (N=102) were used. Each tendon underwent a dynamic mechanical testing protocol including simultaneous polarized light image capture to evaluate both structural and mechanical properties of each Achilles tendon. An empirical damage model was adapted for application to genetic variation and for use with image based structural properties to predict tendon dynamic mechanical properties. We found that Achilles tendons lacking decorin and biglycan had inferior mechanical and structural properties that were age dependent; and that simple empirical models, based on previously described damage models, were predictive of Achilles tendon dynamic modulus in both decorin- and biglycan-null mice. Copyright © 2015 Elsevier Ltd. All rights reserved.
An empirical model of H2O, CO2 and CO coma distributions and production rates for comet 67P/Churyumov-Gerasimenko based on ROSINA/DFMS measurements and AMPS-DSMC simulations

NASA Astrophysics Data System (ADS)

Hansen, Kenneth C.; Altwegg, Kathrin; Bieler, Andre; Berthelier, Jean-Jacques; Calmonte, Ursina; Combi, Michael R.; De Keyser, Johan; Fiethe, Björn; Fougere, Nicolas; Fuselier, Stephen; Gombosi, T. I.; Hässig, Myrtha; Huang, Zhenguang; Le Roy, Léna; Rubin, Martin; Tenishev, Valeriy; Toth, Gabor; Tzou, Chia-Yu; ROSINA Team

2016-10-01

We have previously used results from the AMPS DSMC (Adaptive Mesh Particle Simulator Direct Simulation Monte Carlo) model to create an empirical model of the near comet water (H2O) coma of comet 67P/Churyumov-Gerasimenko. In this work we create additional empirical models for the coma distributions of CO2 and CO. The AMPS simulations are based on ROSINA DFMS (Rosetta Orbiter Spectrometer for Ion and Neutral Analysis, Double Focusing Mass Spectrometer) data taken over the entire timespan of the Rosetta mission. The empirical model is created using AMPS DSMC results which are extracted from simulations at a range of radial distances, rotation phases and heliocentric distances. The simulation results are then averaged over a comet rotation and fitted to an empirical model distribution. Model coefficients are then fitted to piecewise-linear functions of heliocentric distance. The final product is an empirical model of the coma distribution which is a function of heliocentric distance, radial distance, and sun-fixed longitude and latitude angles. The model clearly mimics the behavior of water shifting production from North to South across the inbound equinox while the CO2 production is always in the South.The empirical model can be used to de-trend the spacecraft motion from the ROSINA COPS and DFMS data. The ROSINA instrument measures the neutral coma density at a single point and the measured value is influenced by the location of the spacecraft relative to the comet and the comet-sun line. Using the empirical coma model we can correct for the position of the spacecraft and compute a total production rate based on single point measurements. In this presentation we will present the coma production rates as a function of heliocentric distance for the entire Rosetta mission.This work was supported by contracts JPL#1266313 and JPL#1266314 from the US Rosetta Project and NASA grant NNX14AG84G from the Planetary Atmospheres Program.
Linking agent-based models and stochastic models of financial markets

PubMed Central

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H. Eugene

2012-01-01

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that “fat” tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting. PMID:22586086
Linking agent-based models and stochastic models of financial markets.

PubMed

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.
Empirical agreement in model validation.

PubMed

Jebeile, Julie; Barberousse, Anouk

2016-04-01

Empirical agreement is often used as an important criterion when assessing the validity of scientific models. However, it is by no means a sufficient criterion as a model can be so adjusted as to fit available data even though it is based on hypotheses whose plausibility is known to be questionable. Our aim in this paper is to investigate into the uses of empirical agreement within the process of model validation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Untangling the Evidence: Introducing an Empirical Model for Evidence-Based Library and Information Practice

ERIC Educational Resources Information Center

Gillespie, Ann

2014-01-01

Introduction: This research is the first to investigate the experiences of teacher-librarians as evidence-based practice. An empirically derived model is presented in this paper. Method: This qualitative study utilised the expanded critical incident approach, and investigated the real-life experiences of fifteen Australian teacher-librarians,…
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.
Reacting Chemistry Based Burn Model for Explosive Hydrocodes

NASA Astrophysics Data System (ADS)

Schwaab, Matthew; Greendyke, Robert; Steward, Bryan

2017-06-01

Currently, in hydrocodes designed to simulate explosive material undergoing shock-induced ignition, the state of the art is to use one of numerous reaction burn rate models. These burn models are designed to estimate the bulk chemical reaction rate. Unfortunately, these models are largely based on empirical data and must be recalibrated for every new material being simulated. We propose that the use of an equilibrium Arrhenius rate reacting chemistry model in place of these empirically derived burn models will improve the accuracy for these computational codes. Such models have been successfully used in codes simulating the flow physics around hypersonic vehicles. A reacting chemistry model of this form was developed for the cyclic nitramine RDX by the Naval Research Laboratory (NRL). Initial implementation of this chemistry based burn model has been conducted on the Air Force Research Laboratory's MPEXS multi-phase continuum hydrocode. In its present form, the burn rate is based on the destruction rate of RDX from NRL's chemistry model. Early results using the chemistry based burn model show promise in capturing deflagration to detonation features more accurately in continuum hydrocodes than previously achieved using empirically derived burn models.
Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

2016-08-01

In the present research, three artificial intelligence methods including Gene Expression Programming (GEP), Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as, 48 empirical equations (10, 12 and 26 equations were temperature-based, sunshine-based and meteorological parameters-based, respectively) were used to estimate daily solar radiation in Kerman, Iran in the period of 1992-2009. To develop the GEP, ANN and ANFIS models, depending on the used empirical equations, various combinations of minimum air temperature, maximum air temperature, mean air temperature, extraterrestrial radiation, actual sunshine duration, maximum possible sunshine duration, sunshine duration ratio, relative humidity and precipitation were considered as inputs in the mentioned intelligent methods. To compare the accuracy of empirical equations and intelligent models, root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE) and determination coefficient (R2) indices were used. The results showed that in general, sunshine-based and meteorological parameters-based scenarios in ANN and ANFIS models presented high accuracy than mentioned empirical equations. Moreover, the most accurate method in the studied region was ANN11 scenario with five inputs. The values of RMSE, MAE, MARE and R2 indices for the mentioned model were 1.850 MJ m-2 day-1, 1.184 MJ m-2 day-1, 9.58% and 0.935, respectively.
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.
Base drag prediction on missile configurations

NASA Technical Reports Server (NTRS)

Moore, F. G.; Hymer, T.; Wilcox, F.

1993-01-01

New wind tunnel data have been taken, and a new empirical model has been developed for predicting base drag on missile configurations. The new wind tunnel data were taken at NASA-Langley in the Unitary Wind Tunnel at Mach numbers from 2.0 to 4.5, angles of attack to 16 deg, fin control deflections up to 20 deg, fin thickness/chord of 0.05 to 0.15, and fin locations from 'flush with the base' to two chord-lengths upstream of the base. The empirical model uses these data along with previous wind tunnel data, estimating base drag as a function of all these variables as well as boat-tail and power-on/power-off effects. The new model yields improved accuracy, compared to wind tunnel data. The new model also is more robust due to inclusion of additional variables. On the other hand, additional wind tunnel data are needed to validate or modify the current empirical model in areas where data are not available.
Predicting the Magnetic Properties of ICMEs: A Pragmatic View

NASA Astrophysics Data System (ADS)

Riley, P.; Linker, J.; Ben-Nun, M.; Torok, T.; Ulrich, R. K.; Russell, C. T.; Lai, H.; de Koning, C. A.; Pizzo, V. J.; Liu, Y.; Hoeksema, J. T.

2017-12-01

The southward component of the interplanetary magnetic field plays a crucial role in being able to successfully predict space weather phenomena. Yet, thus far, it has proven extremely difficult to forecast with any degree of accuracy. In this presentation, we describe an empirically-based modeling framework for estimating Bz values during the passage of interplanetary coronal mass ejections (ICMEs). The model includes: (1) an empirically-based estimate of the magnetic properties of the flux rope in the low corona (including helicity and field strength); (2) an empirically-based estimate of the dynamic properties of the flux rope in the high corona (including direction, speed, and mass); and (3) a physics-based estimate of the evolution of the flux rope during its passage to 1 AU driven by the output from (1) and (2). We compare model output with observations for a selection of events to estimate the accuracy of this approach. Importantly, we pay specific attention to the uncertainties introduced by the components within the framework, separating intrinsic limitations from those that can be improved upon, either by better observations or more sophisticated modeling. Our analysis suggests that current observations/modeling are insufficient for this empirically-based framework to provide reliable and actionable prediction of the magnetic properties of ICMEs. We suggest several paths that may lead to better forecasts.
Prediction of the Dynamic Yield Strength of Metals Using Two Structural-Temporal Parameters

NASA Astrophysics Data System (ADS)

Selyutina, N. S.; Petrov, Yu. V.

2018-02-01

The behavior of the yield strength of steel and a number of aluminum alloys is investigated in a wide range of strain rates, based on the incubation time criterion of yield and the empirical models of Johnson-Cook and Cowper-Symonds. In this paper, expressions for the parameters of the empirical models are derived through the characteristics of the incubation time criterion; a satisfactory agreement of these data and experimental results is obtained. The parameters of the empirical models can depend on some strain rate. The independence of the characteristics of the incubation time criterion of yield from the loading history and their connection with the structural and temporal features of the plastic deformation process give advantage of the approach based on the concept of incubation time with respect to empirical models and an effective and convenient equation for determining the yield strength in a wider range of strain rates.
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…
Attachment-Based Family Therapy: A Review of the Empirical Support.

PubMed

Diamond, Guy; Russon, Jody; Levy, Suzanne

2016-09-01

Attachment-based family therapy (ABFT) is an empirically supported treatment designed to capitalize on the innate, biological desire for meaningful and secure relationships. The therapy is grounded in attachment theory and provides an interpersonal, process-oriented, trauma-focused approach to treating adolescent depression, suicidality, and trauma. Although a process-oriented therapy, ABFT offers a clear structure and road map to help therapists quickly address attachment ruptures that lie at the core of family conflict. Several clinical trials and process studies have demonstrated empirical support for the model and its proposed mechanism of change. This article provides an overview of the clinical model and the existing empirical support for ABFT. © 2016 Family Process Institute.
The Role of Empirical Evidence in Modeling Speech Segmentation

ERIC Educational Resources Information Center

Phillips, Lawrence

2015-01-01

Choosing specific implementational details is one of the most important aspects of creating and evaluating a model. In order to properly model cognitive processes, choices for these details must be made based on empirical research. Unfortunately, modelers are often forced to make decisions in the absence of relevant data. My work investigates the…
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.
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.
Empirical Allometric Models to Estimate Total Needle Biomass For Loblolly Pine

Treesearch

Hector M. de los Santos-Posadas; Bruce E. Borders

2002-01-01

Empirical geometric models based on the cone surface formula were adapted and used to estimate total dry needle biomass (TNB) and live branch basal area (LBBA). The results suggest that the empirical geometric equations produced good fit and stable parameters while estimating TNB and LBBA. The data used include trees form a spacing study of 12 years old and a set of...
An empirically-based model for the lift coefficients of twisted airfoils with leading-edge tubercles

NASA Astrophysics Data System (ADS)

Ni, Zao; Su, Tsung-chow; Dhanak, Manhar

2018-04-01

Experimental data for untwisted airfoils are utilized to propose a model for predicting the lift coefficients of twisted airfoils with leading-edge tubercles. The effectiveness of the empirical model is verified through comparison with results of a corresponding computational fluid-dynamic (CFD) study. The CFD study is carried out for both twisted and untwisted airfoils with tubercles, the latter shown to compare well with available experimental data. Lift coefficients of twisted airfoils predicted from the proposed empirically-based model match well with the corresponding coefficients determined using the verified CFD study. Flow details obtained from the latter provide better insight into the underlying mechanism and behavior at stall of twisted airfoils with leading edge tubercles.
A Perspective on Computational Human Performance Models as Design Tools

NASA Technical Reports Server (NTRS)

Jones, Patricia M.

2010-01-01

The design of interactive systems, including levels of automation, displays, and controls, is usually based on design guidelines and iterative empirical prototyping. A complementary approach is to use computational human performance models to evaluate designs. An integrated strategy of model-based and empirical test and evaluation activities is particularly attractive as a methodology for verification and validation of human-rated systems for commercial space. This talk will review several computational human performance modeling approaches and their applicability to design of display and control requirements.
Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578
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 noisy resonant system response

NASA Astrophysics Data System (ADS)

Weber, Patrick Thomas; Walrath, David Edwin

2017-02-01

In this paper, a theory-based model replicating empirical acoustic resonant signals is presented and studied to understand sources of noise present in acoustic signals. Statistical properties of empirical signals are quantified and a noise amplitude parameter, which models frequency and amplitude-based noise, is created, defined, and presented. This theory-driven model isolates each phenomenon and allows for parameters to be independently studied. Using seven independent degrees of freedom, this model will accurately reproduce qualitative and quantitative properties measured from laboratory data. Results are presented and demonstrate success in replicating qualitative and quantitative properties of experimental data.
Learning-Testing Process in Classroom: An Empirical Simulation Model

ERIC Educational Resources Information Center

Buda, Rodolphe

2009-01-01

This paper presents an empirical micro-simulation model of the teaching and the testing process in the classroom (Programs and sample data are available--the actual names of pupils have been hidden). It is a non-econometric micro-simulation model describing informational behaviors of the pupils, based on the observation of the pupils'…

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...
Incorporating video modeling into a school-based intervention for students with autism spectrum disorders.

PubMed

Wilson, Kaitlyn P

2013-01-01

Video modeling is an intervention strategy that has been shown to be effective in improving the social and communication skills of students with autism spectrum disorders, or ASDs. The purpose of this tutorial is to outline empirically supported, step-by-step instructions for the use of video modeling by school-based speech-language pathologists (SLPs) serving students with ASDs. This tutorial draws from the many reviews and meta-analyses of the video modeling literature that have been conducted over the past decade, presenting empirically supported considerations for school-based SLPs who are planning to incorporate video modeling into their service delivery for students with ASD. The 5 overarching procedural phases presented in this tutorial are (a) preparation, (b) recording of the video model, (c) implementation of the video modeling intervention, (d) monitoring of the student's response to the intervention, and (e) planning of the next steps. Video modeling is not only a promising intervention strategy for students with ASD, but it is also a practical and efficient tool that is well-suited to the school setting. This tutorial will facilitate school-based SLPs' incorporation of this empirically supported intervention into their existing strategies for intervention for students with ASD.
An empirically based model for knowledge management in health care organizations.

PubMed

Sibbald, Shannon L; Wathen, C Nadine; Kothari, Anita

2016-01-01

Knowledge management (KM) encompasses strategies, processes, and practices that allow an organization to capture, share, store, access, and use knowledge. Ideal KM combines different sources of knowledge to support innovation and improve performance. Despite the importance of KM in health care organizations (HCOs), there has been very little empirical research to describe KM in this context. This study explores KM in HCOs, focusing on the status of current intraorganizational KM. The intention is to provide insight for future studies and model development for effective KM implementation in HCOs. A qualitative methods approach was used to create an empirically based model of KM in HCOs. Methods included (a) qualitative interviews (n = 24) with senior leadership to identify types of knowledge important in these roles plus current information-seeking behaviors/needs and (b) in-depth case study with leaders in new executive positions (n = 2). The data were collected from 10 HCOs. Our empirically based model for KM was assessed for face and content validity. The findings highlight the paucity of formal KM in our sample HCOs. Organizational culture, leadership, and resources are instrumental in supporting KM processes. An executive's knowledge needs are extensive, but knowledge assets are often limited or difficult to acquire as much of the available information is not in a usable format. We propose an empirically based model for KM to highlight the importance of context (internal and external), and knowledge seeking, synthesis, sharing, and organization. Participants who reviewed the model supported its basic components and processes, and potential for incorporating KM into organizational processes. Our results articulate ways to improve KM, increase organizational learning, and support evidence-informed decision-making. This research has implications for how to better integrate evidence and knowledge into organizations while considering context and the role of organizational processes.
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...
A spatial model of land use change for western Oregon and western Washington.

Treesearch

Jeffrey D. Kline; Ralph J. Alig

2001-01-01

We developed an empirical model describing the probability that forests and farmland in western Oregon and western Washington were developed for residential, commercial, or industrial uses during a 30-year period, as a function of spatial socioeconomic variables, ownership, and geographic and physical land characteristics. The empirical model is based on a conceptual...
Evaluation of Regression Models of Balance Calibration Data Using an Empirical Criterion

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert; Volden, Thomas R.

2012-01-01

An empirical criterion for assessing the significance of individual terms of regression models of wind tunnel strain gage balance outputs is evaluated. The criterion is based on the percent contribution of a regression model term. It considers a term to be significant if its percent contribution exceeds the empirical threshold of 0.05%. The criterion has the advantage that it can easily be computed using the regression coefficients of the gage outputs and the load capacities of the balance. First, a definition of the empirical criterion is provided. Then, it is compared with an alternate statistical criterion that is widely used in regression analysis. Finally, calibration data sets from a variety of balances are used to illustrate the connection between the empirical and the statistical criterion. A review of these results indicated that the empirical criterion seems to be suitable for a crude assessment of the significance of a regression model term as the boundary between a significant and an insignificant term cannot be defined very well. Therefore, regression model term reduction should only be performed by using the more universally applicable statistical criterion.
Modeling the erythemal surface diffuse irradiance fraction for Badajoz, Spain

NASA Astrophysics Data System (ADS)

Sanchez, Guadalupe; Serrano, Antonio; Cancillo, María Luisa

2017-10-01

Despite its important role on the human health and numerous biological processes, the diffuse component of the erythemal ultraviolet irradiance (UVER) is scarcely measured at standard radiometric stations and therefore needs to be estimated. This study proposes and compares 10 empirical models to estimate the UVER diffuse fraction. These models are inspired from mathematical expressions originally used to estimate total diffuse fraction, but, in this study, they are applied to the UVER case and tested against experimental measurements. In addition to adapting to the UVER range the various independent variables involved in these models, the total ozone column has been added in order to account for its strong impact on the attenuation of ultraviolet radiation. The proposed models are fitted to experimental measurements and validated against an independent subset. The best-performing model (RAU3) is based on a model proposed by Ruiz-Arias et al. (2010) and shows values of r2 equal to 0.91 and relative root-mean-square error (rRMSE) equal to 6.1 %. The performance achieved by this entirely empirical model is better than those obtained by previous semi-empirical approaches and therefore needs no additional information from other physically based models. This study expands on previous research to the ultraviolet range and provides reliable empirical models to accurately estimate the UVER diffuse fraction.
Modelling public support for wildland fire policy

Treesearch

J.D. Absher; J.J. Vaske

2007-01-01

Theoretically grounded explanations of wildland fire policy can be improved by empirically documenting the causal influences of support for (or opposition to) management alternatives. This chapter proposes a model based on the specificity principle (i.e. correspondence between measured variables to empirically examine four common wildland fire policies in relation to...
An optimum organizational structure for a large earth-orbiting multidisciplinary space base. Ph.D. Thesis - Fla. State Univ., 1973

NASA Technical Reports Server (NTRS)

Ragusa, J. M.

1975-01-01

An optimum hypothetical organizational structure was studied for a large earth-orbiting, multidisciplinary research and applications space base manned by a crew of technologists. Because such a facility does not presently exist, in situ empirical testing was not possible. Study activity was, therefore, concerned with the identification of a desired organizational structural model rather than with the empirical testing of the model. The essential finding of this research was that a four-level project type total matrix model will optimize the efficiency and effectiveness of space base technologists.
Cascading Walks Model for Human Mobility Patterns

PubMed Central

Han, Xiao-Pu; Wang, Xiang-Wen; Yan, Xiao-Yong; Wang, Bing-Hong

2015-01-01

Background Uncovering the mechanism behind the scaling laws and series of anomalies in human trajectories is of fundamental significance in understanding many spatio-temporal phenomena. Recently, several models, e.g. the explorations-returns model (Song et al., 2010) and the radiation model for intercity travels (Simini et al., 2012), have been proposed to study the origin of these anomalies and the prediction of human movements. However, an agent-based model that could reproduce most of empirical observations without priori is still lacking. Methodology/Principal Findings In this paper, considering the empirical findings on the correlations of move-lengths and staying time in human trips, we propose a simple model which is mainly based on the cascading processes to capture the human mobility patterns. In this model, each long-range movement activates series of shorter movements that are organized by the law of localized explorations and preferential returns in prescribed region. Conclusions/Significance Based on the numerical simulations and analytical studies, we show more than five statistical characters that are well consistent with the empirical observations, including several types of scaling anomalies and the ultraslow diffusion properties, implying the cascading processes associated with the localized exploration and preferential returns are indeed a key in the understanding of human mobility activities. Moreover, the model shows both of the diverse individual mobility and aggregated scaling displacements, bridging the micro and macro patterns in human mobility. In summary, our model successfully explains most of empirical findings and provides deeper understandings on the emergence of human mobility patterns. PMID:25860140
Cascading walks model for human mobility patterns.

PubMed

Han, Xiao-Pu; Wang, Xiang-Wen; Yan, Xiao-Yong; Wang, Bing-Hong

2015-01-01

Uncovering the mechanism behind the scaling laws and series of anomalies in human trajectories is of fundamental significance in understanding many spatio-temporal phenomena. Recently, several models, e.g. the explorations-returns model (Song et al., 2010) and the radiation model for intercity travels (Simini et al., 2012), have been proposed to study the origin of these anomalies and the prediction of human movements. However, an agent-based model that could reproduce most of empirical observations without priori is still lacking. In this paper, considering the empirical findings on the correlations of move-lengths and staying time in human trips, we propose a simple model which is mainly based on the cascading processes to capture the human mobility patterns. In this model, each long-range movement activates series of shorter movements that are organized by the law of localized explorations and preferential returns in prescribed region. Based on the numerical simulations and analytical studies, we show more than five statistical characters that are well consistent with the empirical observations, including several types of scaling anomalies and the ultraslow diffusion properties, implying the cascading processes associated with the localized exploration and preferential returns are indeed a key in the understanding of human mobility activities. Moreover, the model shows both of the diverse individual mobility and aggregated scaling displacements, bridging the micro and macro patterns in human mobility. In summary, our model successfully explains most of empirical findings and provides deeper understandings on the emergence of human mobility patterns.
Semi-empirical long-term cycle life model coupled with an electrolyte depletion function for large-format graphite/LiFePO4 lithium-ion batteries

NASA Astrophysics Data System (ADS)

Park, Joonam; Appiah, Williams Agyei; Byun, Seoungwoo; Jin, Dahee; Ryou, Myung-Hyun; Lee, Yong Min

2017-10-01

To overcome the limitation of simple empirical cycle life models based on only equivalent circuits, we attempt to couple a conventional empirical capacity loss model with Newman's porous composite electrode model, which contains both electrochemical reaction kinetics and material/charge balances. In addition, an electrolyte depletion function is newly introduced to simulate a sudden capacity drop at the end of cycling, which is frequently observed in real lithium-ion batteries (LIBs). When simulated electrochemical properties are compared with experimental data obtained with 20 Ah-level graphite/LiFePO4 LIB cells, our semi-empirical model is sufficiently accurate to predict a voltage profile having a low standard deviation of 0.0035 V, even at 5C. Additionally, our model can provide broad cycle life color maps under different c-rate and depth-of-discharge operating conditions. Thus, this semi-empirical model with an electrolyte depletion function will be a promising platform to predict long-term cycle lives of large-format LIB cells under various operating conditions.
Empirical Testing of a Theoretical Extension of the Technology Acceptance Model: An Exploratory Study of Educational Wikis

ERIC Educational Resources Information Center

Liu, Xun

2010-01-01

This study extended the technology acceptance model and empirically tested the new model with wikis, a new type of educational technology. Based on social cognitive theory and the theory of planned behavior, three new variables, wiki self-efficacy, online posting anxiety, and perceived behavioral control, were added to the original technology…
Computer Model of the Empirical Knowledge of Physics Formation: Coordination with Testing Results

ERIC Educational Resources Information Center

Mayer, Robert V.

2016-01-01

The use of method of imitational modeling to study forming the empirical knowledge in pupil's consciousness is discussed. The offered model is based on division of the physical facts into three categories: 1) the facts established in everyday life; 2) the facts, which the pupil can experimentally establish at a physics lesson; 3) the facts which…
Retrieving hydrological connectivity from empirical causality in karst systems

NASA Astrophysics Data System (ADS)

Delforge, Damien; Vanclooster, Marnik; Van Camp, Michel; Poulain, Amaël; Watlet, Arnaud; Hallet, Vincent; Kaufmann, Olivier; Francis, Olivier

2017-04-01

Because of their complexity, karst systems exhibit nonlinear dynamics. Moreover, if one attempts to model a karst, the hidden behavior complicates the choice of the most suitable model. Therefore, both intense investigation methods and nonlinear data analysis are needed to reveal the underlying hydrological connectivity as a prior for a consistent physically based modelling approach. Convergent Cross Mapping (CCM), a recent method, promises to identify causal relationships between time series belonging to the same dynamical systems. The method is based on phase space reconstruction and is suitable for nonlinear dynamics. As an empirical causation detection method, it could be used to highlight the hidden complexity of a karst system by revealing its inner hydrological and dynamical connectivity. Hence, if one can link causal relationships to physical processes, the method should show great potential to support physically based model structure selection. We present the results of numerical experiments using karst model blocks combined in different structures to generate time series from actual rainfall series. CCM is applied between the time series to investigate if the empirical causation detection is consistent with the hydrological connectivity suggested by the karst model.
Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

PubMed

Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.
Modelling Hen Harrier Dynamics to Inform Human-Wildlife Conflict Resolution: A Spatially-Realistic, Individual-Based Approach

PubMed Central

Heinonen, Johannes P. M.; Palmer, Stephen C. F.; Redpath, Steve M.; Travis, Justin M. J.

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions. PMID:25405860
Improved prediction of tacrolimus concentrations early after kidney transplantation using theory-based pharmacokinetic modelling.

PubMed

Størset, Elisabet; Holford, Nick; Hennig, Stefanie; Bergmann, Troels K; Bergan, Stein; Bremer, Sara; Åsberg, Anders; Midtvedt, Karsten; Staatz, Christine E

2014-09-01

The aim was to develop a theory-based population pharmacokinetic model of tacrolimus in adult kidney transplant recipients and to externally evaluate this model and two previous empirical models. Data were obtained from 242 patients with 3100 tacrolimus whole blood concentrations. External evaluation was performed by examining model predictive performance using Bayesian forecasting. Pharmacokinetic disposition parameters were estimated based on tacrolimus plasma concentrations, predicted from whole blood concentrations, haematocrit and literature values for tacrolimus binding to red blood cells. Disposition parameters were allometrically scaled to fat free mass. Tacrolimus whole blood clearance/bioavailability standardized to haematocrit of 45% and fat free mass of 60 kg was estimated to be 16.1 l h−1 [95% CI 12.6, 18.0 l h−1]. Tacrolimus clearance was 30% higher (95% CI 13, 46%) and bioavailability 18% lower (95% CI 2, 29%) in CYP3A5 expressers compared with non-expressers. An Emax model described decreasing tacrolimus bioavailability with increasing prednisolone dose. The theory-based model was superior to the empirical models during external evaluation displaying a median prediction error of −1.2% (95% CI −3.0, 0.1%). Based on simulation, Bayesian forecasting led to 65% (95% CI 62, 68%) of patients achieving a tacrolimus average steady-state concentration within a suggested acceptable range. A theory-based population pharmacokinetic model was superior to two empirical models for prediction of tacrolimus concentrations and seemed suitable for Bayesian prediction of tacrolimus doses early after kidney transplantation.
Simulation studies of chemical erosion on carbon based materials at elevated temperatures

NASA Astrophysics Data System (ADS)

Kenmotsu, T.; Kawamura, T.; Li, Zhijie; Ono, T.; Yamamura, Y.

1999-06-01

We simulated the fluence dependence of methane reaction yield in carbon with hydrogen bombardment using the ACAT-DIFFUSE code. The ACAT-DIFFUSE code is a simulation code based on a Monte Carlo method with a binary collision approximation and on solving diffusion equations. The chemical reaction model in carbon was studied by Roth or other researchers. Roth's model is suitable for the steady state methane reaction. But this model cannot estimate the fluence dependence of the methane reaction. Then, we derived an empirical formula based on Roth's model for methane reaction. In this empirical formula, we assumed the reaction region where chemical sputtering due to methane formation takes place. The reaction region corresponds to the peak range of incident hydrogen distribution in the target material. We adopted this empirical formula to the ACAT-DIFFUSE code. The simulation results indicate the similar fluence dependence compared with the experiment result. But, the fluence to achieve the steady state are different between experiment and simulation results.
The importance of education, understanding, and empirical research in social work: the nuts and bolts of the business.

PubMed

Long, Kimberly; Wodarski, John S

2010-05-01

Over the past three decades, existing literature has demanded, and continues to demand, accountability in the delivery of social services through empirically based research and implementation of established norms: this is, and of itself, the true basis of social work. It is through these norms and empirically established models and theories of treatment that a social worker can really do what he/she wants to do: help the client. This article will describe the nuts and bolts of social work; i.e. those theories, models, and the established norms of practice. It is the desire of the author's that all social workers be educated in the nuts and bolts (basics) and that education will be based on empirical evidence that supports behavioral change through intervention and modification.

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.
Combination of a Stresor-Response Model with a Conditional Probability Anaylsis Approach to Develop Candidate Criteria from Empirical Data

EPA Science Inventory

We show that a conditional probability analysis that utilizes a stressor-response model based on a logistic regression provides a useful approach for developing candidate water quality criterai from empirical data. The critical step in this approach is transforming the response ...
Variable Density Multilayer Insulation for Cryogenic Storage

NASA Technical Reports Server (NTRS)

Hedayat, A.; Brown, T. M.; Hastings, L. J.; Martin, J.

2000-01-01

Two analytical models for a foam/Variable Density Multi-Layer Insulation (VD-MLI) system performance are discussed. Both models are one-dimensional and contain three heat transfer mechanisms, namely conduction through the spacer material, radiation between the shields, and conduction through the gas. One model is based on the methodology developed by McIntosh while the other model is based on the Lockheed semi-empirical approach. All models input variables are based on the Multi-purpose Hydrogen Test Bed (MHTB) geometry and available values for material properties and empirical solid conduction coefficient. Heat flux predictions are in good agreement with the MHTB data, The heat flux predictions are presented for the foam/MLI combinations with 30, 45, 60, and 75 MLI layers
Validating Computational Human Behavior Models: Consistency and Accuracy Issues

DTIC Science & Technology

2004-06-01

includes a discussion of SME demographics, content, and organization of the datasets . This research generalizes data from two pilot studies and two base...meet requirements for validating the varied and complex behavioral models. Through a series of empirical studies , this research identifies subject...meet requirements for validating the varied and complex behavioral models. Through a series of empirical studies , this research identifies subject
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
Does Gene Tree Discordance Explain the Mismatch between Macroevolutionary Models and Empirical Patterns of Tree Shape and Branching Times?

PubMed Central

Stadler, Tanja; Degnan, James H.; Rosenberg, Noah A.

2016-01-01

Classic null models for speciation and extinction give rise to phylogenies that differ in distribution from empirical phylogenies. In particular, empirical phylogenies are less balanced and have branching times closer to the root compared to phylogenies predicted by common null models. This difference might be due to null models of the speciation and extinction process being too simplistic, or due to the empirical datasets not being representative of random phylogenies. A third possibility arises because phylogenetic reconstruction methods often infer gene trees rather than species trees, producing an incongruity between models that predict species tree patterns and empirical analyses that consider gene trees. We investigate the extent to which the difference between gene trees and species trees under a combined birth–death and multispecies coalescent model can explain the difference in empirical trees and birth–death species trees. We simulate gene trees embedded in simulated species trees and investigate their difference with respect to tree balance and branching times. We observe that the gene trees are less balanced and typically have branching times closer to the root than the species trees. Empirical trees from TreeBase are also less balanced than our simulated species trees, and model gene trees can explain an imbalance increase of up to 8% compared to species trees. However, we see a much larger imbalance increase in empirical trees, about 100%, meaning that additional features must also be causing imbalance in empirical trees. This simulation study highlights the necessity of revisiting the assumptions made in phylogenetic analyses, as these assumptions, such as equating the gene tree with the species tree, might lead to a biased conclusion. PMID:26968785
High-Throughput Physiologically Based Toxicokinetic Models for ToxCast Chemicals

EPA Science Inventory

Physiologically based toxicokinetic (PBTK) models aid in predicting exposure doses needed to create tissue concentrations equivalent to those identified as bioactive by ToxCast. We have implemented four empirical and physiologically-based toxicokinetic (TK) models within a new R ...
Component-based model to predict aerodynamic noise from high-speed train pantographs

NASA Astrophysics Data System (ADS)

Latorre Iglesias, E.; Thompson, D. J.; Smith, M. G.

2017-04-01

At typical speeds of modern high-speed trains the aerodynamic noise produced by the airflow over the pantograph is a significant source of noise. Although numerical models can be used to predict this they are still very computationally intensive. A semi-empirical component-based prediction model is proposed to predict the aerodynamic noise from train pantographs. The pantograph is approximated as an assembly of cylinders and bars with particular cross-sections. An empirical database is used to obtain the coefficients of the model to account for various factors: incident flow speed, diameter, cross-sectional shape, yaw angle, rounded edges, length-to-width ratio, incoming turbulence and directivity. The overall noise from the pantograph is obtained as the incoherent sum of the predicted noise from the different pantograph struts. The model is validated using available wind tunnel noise measurements of two full-size pantographs. The results show the potential of the semi-empirical model to be used as a rapid tool to predict aerodynamic noise from train pantographs.
Power-Laws and Scaling in Finance: Empirical Evidence and Simple Models

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe

We discuss several models that may explain the origin of power-law distributions and power-law correlations in financial time series. From an empirical point of view, the exponents describing the tails of the price increments distribution and the decay of the volatility correlations are rather robust and suggest universality. However, many of the models that appear naturally (for example, to account for the distribution of wealth) contain some multiplicative noise, which generically leads to non universal exponents. Recent progress in the empirical study of the volatility suggests that the volatility results from some sort of multiplicative cascade. A convincing `microscopic' (i.e. trader based) model that explains this observation is however not yet available. We discuss a rather generic mechanism for long-ranged volatility correlations based on the idea that agents constantly switch between active and inactive strategies depending on their relative performance.
Organizational Learning, Strategic Flexibility and Business Model Innovation: An Empirical Research Based on Logistics Enterprises

NASA Astrophysics Data System (ADS)

Bao, Yaodong; Cheng, Lin; Zhang, Jian

Using the data of 237 Jiangsu logistics firms, this paper empirically studies the relationship among organizational learning capability, business model innovation, strategic flexibility. The results show as follows; organizational learning capability has positive impacts on business model innovation performance; strategic flexibility plays mediating roles on the relationship between organizational learning capability and business model innovation; interaction among strategic flexibility, explorative learning and exploitative learning play significant roles in radical business model innovation and incremental business model innovation.
A watershed scale spatially-distributed model for streambank erosion rate driven by channel curvature

NASA Astrophysics Data System (ADS)

McMillan, Mitchell; Hu, Zhiyong

2017-10-01

Streambank erosion is a major source of fluvial sediment, but few large-scale, spatially distributed models exist to quantify streambank erosion rates. We introduce a spatially distributed model for streambank erosion applicable to sinuous, single-thread channels. We argue that such a model can adequately characterize streambank erosion rates, measured at the outsides of bends over a 2-year time period, throughout a large region. The model is based on the widely-used excess-velocity equation and comprised three components: a physics-based hydrodynamic model, a large-scale 1-dimensional model of average monthly discharge, and an empirical bank erodibility parameterization. The hydrodynamic submodel requires inputs of channel centerline, slope, width, depth, friction factor, and a scour factor A; the large-scale watershed submodel utilizes watershed-averaged monthly outputs of the Noah-2.8 land surface model; bank erodibility is based on tree cover and bank height as proxies for root density. The model was calibrated with erosion rates measured in sand-bed streams throughout the northern Gulf of Mexico coastal plain. The calibrated model outperforms a purely empirical model, as well as a model based only on excess velocity, illustrating the utility of combining a physics-based hydrodynamic model with an empirical bank erodibility relationship. The model could be improved by incorporating spatial variability in channel roughness and the hydrodynamic scour factor, which are here assumed constant. A reach-scale application of the model is illustrated on ∼1 km of a medium-sized, mixed forest-pasture stream, where the model identifies streambank erosion hotspots on forested and non-forested bends.
An empirical model of water quality for use in rapid management strategy evaluation in Southeast Queensland, Australia.

PubMed

de la Mare, William; Ellis, Nick; Pascual, Ricardo; Tickell, Sharon

2012-04-01

Simulation models have been widely adopted in fisheries for management strategy evaluation (MSE). However, in catchment management of water quality, MSE is hampered by the complexity of both decision space and the hydrological process models. Empirical models based on monitoring data provide a feasible alternative to process models; they run much faster and, by conditioning on data, they can simulate realistic responses to management actions. Using 10 years of water quality indicators from Queensland, Australia, we built an empirical model suitable for rapid MSE that reproduces the water quality variables' mean and covariance structure, adjusts the expected indicators through local management effects, and propagates effects downstream by capturing inter-site regression relationships. Empirical models enable managers to search the space of possible strategies using rapid assessment. They provide not only realistic responses in water quality indicators but also variability in those indicators, allowing managers to assess strategies in an uncertain world. Copyright © 2012 Elsevier Ltd. All rights reserved.
Pre- and Post-equinox ROSINA production rates calculated using a realistic empirical coma model derived from AMPS-DSMC simulations of comet 67P/Churyumov-Gerasimenko

NASA Astrophysics Data System (ADS)

Hansen, Kenneth; Altwegg, Kathrin; Berthelier, Jean-Jacques; Bieler, Andre; Calmonte, Ursina; Combi, Michael; De Keyser, Johan; Fiethe, Björn; Fougere, Nicolas; Fuselier, Stephen; Gombosi, Tamas; Hässig, Myrtha; Huang, Zhenguang; Le Roy, Lena; Rubin, Martin; Tenishev, Valeriy; Toth, Gabor; Tzou, Chia-Yu

2016-04-01

We have previously used results from the AMPS DSMC (Adaptive Mesh Particle Simulator Direct Simulation Monte Carlo) model to create an empirical model of the near comet coma (<400 km) of comet 67P for the pre-equinox orbit of comet 67P/Churyumov-Gerasimenko. In this work we extend the empirical model to the post-equinox, post-perihelion time period. In addition, we extend the coma model to significantly further from the comet (~100,000-1,000,000 km). 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. Furthermore, we have generalized the model beyond application to 67P by replacing the heliocentric distance parameterizations and mapping them to production rates. Using this method, the model become significantly more general and can be applied to any comet. The model is a significant improvement over simpler empirical models, such as the Haser model. For 67P, the DSMC results are, of course, a more accurate representation of the coma at any given time, but the advantage of a mean state, empirical model is the ease and speed of use. One application of the empirical model is to de-trend the spacecraft motion from the ROSINA COPS and DFMS data (Rosetta Orbiter Spectrometer for Ion and Neutral Analysis, Comet Pressure Sensor, Double Focusing Mass Spectrometer). The ROSINA instrument measures the neutral coma density at a single point and the measured value is influenced by the location of the spacecraft relative to the comet and the comet-sun line. Using the empirical coma model we can correct for the position of the spacecraft and compute a total production rate based on the single point measurement. In this presentation we will present the coma production rate as a function of heliocentric distance both pre- and post-equinox and perihelion.
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…
An Empirical Study on Washback Effects of the Internet-Based College English Test Band 4 in China

ERIC Educational Resources Information Center

Wang, Chao; Yan, Jiaolan; Liu, Bao

2014-01-01

Based on Bailey's washback model, in respect of participants, process and products, the present empirical study was conducted to find the actual washback effects of the internet-based College English Test Band 4 (IB CET-4). The methods adopted are questionnaires, class observation, interview and the analysis of both the CET-4 teaching and testing…
Statistical validation and an empirical model of hydrogen production enhancement found by utilizing passive flow disturbance in the steam-reformation process

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

Erickson, Paul A.; Liao, Chang-hsien

2007-11-15

A passive flow disturbance has been proven to enhance the conversion of fuel in a methanol-steam reformer. This study presents a statistical validation of the experiment based on a standard 2{sup k} factorial experiment design and the resulting empirical model of the enhanced hydrogen producing process. A factorial experiment design was used to statistically analyze the effects and interactions of various input factors in the experiment. Three input factors, including the number of flow disturbers, catalyst size, and reactant flow rate were investigated for their effects on the fuel conversion in the steam-reformation process. Based on the experimental results, anmore » empirical model was developed and further evaluated with an uncertainty analysis and interior point data. (author)« less
Ultrasonic nondestructive evaluation, microstructure, and mechanical property interrelations

NASA Technical Reports Server (NTRS)

Vary, A.

1984-01-01

Ultrasonic techniques for mechanical property characterizations are reviewed and conceptual models are advanced for explaining and interpreting the empirically based results. At present, the technology is generally empirically based and is emerging from the research laboratory. Advancement of the technology will require establishment of theoretical foundations for the experimentally observed interrelations among ultrasonic measurements, mechanical properties, and microstructure. Conceptual models are applied to ultrasonic assessment of fracture toughness to illustrate an approach for predicting correlations found among ultrasonic measurements, microstructure, and mechanical properties.
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...
Quantitative model of the growth of floodplains by vertical accretion

USGS Publications Warehouse

Moody, J.A.; Troutman, B.M.

2000-01-01

A simple one-dimensional model is developed to quantitatively predict the change in elevation, over a period of decades, for vertically accreting floodplains. This unsteady model approximates the monotonic growth of a floodplain as an incremental but constant increase of net sediment deposition per flood for those floods of a partial duration series that exceed a threshold discharge corresponding to the elevation of the floodplain. Sediment deposition from each flood increases the elevation of the floodplain and consequently the magnitude of the threshold discharge resulting in a decrease in the number of floods and growth rate of the floodplain. Floodplain growth curves predicted by this model are compared to empirical growth curves based on dendrochronology and to direct field measurements at five floodplain sites. The model was used to predict the value of net sediment deposition per flood which best fits (in a least squares sense) the empirical and field measurements; these values fall within the range of independent estimates of the net sediment deposition per flood based on empirical equations. These empirical equations permit the application of the model to estimate of floodplain growth for other floodplains throughout the world which do not have detailed data of sediment deposition during individual floods. Copyright (C) 2000 John Wiley and Sons, Ltd.
Extended Empirical Roadside Shadowing model from ACTS mobile measurements

NASA Technical Reports Server (NTRS)

Goldhirsh, Julius; Vogel, Wolfhard

1995-01-01

Employing multiple data bases derived from land-mobile satellite measurements using the Advanced Communications Technology Satellite (ACTS) at 20 GHz, MARECS B-2 at 1.5 GHz, and helicopter measurements at 870 MHz and 1.5 GHz, the Empirical Road Side Shadowing Model (ERS) has been extended. The new model (Extended Empirical Roadside Shadowing Model, EERS) may now be employed at frequencies from UHF to 20 GHz, at elevation angles from 7 to 60 deg and at percentages from 1 to 80 percent (0 dB fade). The EERS distributions are validated against measured ones and fade deviations associated with the model are assessed. A model is also presented for estimating the effects of foliage (or non-foliage) on 20 GHz distributions, given distributions from deciduous trees devoid of leaves (or in full foliage).

Best Practices in Physics-Based Fault Rupture Models for Seismic Hazard Assessment of Nuclear Installations

NASA Astrophysics Data System (ADS)

Dalguer, Luis A.; Fukushima, Yoshimitsu; Irikura, Kojiro; Wu, Changjiang

2017-09-01

Inspired by the first workshop on Best Practices in Physics-Based Fault Rupture Models for Seismic Hazard Assessment of Nuclear Installations (BestPSHANI) conducted by the International Atomic Energy Agency (IAEA) on 18-20 November, 2015 in Vienna (http://www-pub.iaea.org/iaeameetings/50896/BestPSHANI), this PAGEOPH topical volume collects several extended articles from this workshop as well as several new contributions. A total of 17 papers have been selected on topics ranging from the seismological aspects of earthquake cycle simulations for source-scaling evaluation, seismic source characterization, source inversion and ground motion modeling (based on finite fault rupture using dynamic, kinematic, stochastic and empirical Green's functions approaches) to the engineering application of simulated ground motion for the analysis of seismic response of structures. These contributions include applications to real earthquakes and description of current practice to assess seismic hazard in terms of nuclear safety in low seismicity areas, as well as proposals for physics-based hazard assessment for critical structures near large earthquakes. Collectively, the papers of this volume highlight the usefulness of physics-based models to evaluate and understand the physical causes of observed and empirical data, as well as to predict ground motion beyond the range of recorded data. Relevant importance is given on the validation and verification of the models by comparing synthetic results with observed data and empirical models.
The Structure of Psychopathology: Toward an Expanded Quantitative Empirical Model

PubMed Central

Wright, Aidan G.C.; Krueger, Robert F.; Hobbs, Megan J.; Markon, Kristian E.; Eaton, Nicholas R.; Slade, Tim

2013-01-01

There has been substantial recent interest in the development of a quantitative, empirically based model of psychopathology. However, the majority of pertinent research has focused on analyses of diagnoses, as described in current official nosologies. This is a significant limitation because existing diagnostic categories are often heterogeneous. In the current research, we aimed to redress this limitation of the existing literature, and to directly compare the fit of categorical, continuous, and hybrid (i.e., combined categorical and continuous) models of syndromes derived from indicators more fine-grained than diagnoses. We analyzed data from a large representative epidemiologic sample (the 2007 Australian National Survey of Mental Health and Wellbeing; N = 8,841). Continuous models provided the best fit for each syndrome we observed (Distress, Obsessive Compulsivity, Fear, Alcohol Problems, Drug Problems, and Psychotic Experiences). In addition, the best fitting higher-order model of these syndromes grouped them into three broad spectra: Internalizing, Externalizing, and Psychotic Experiences. We discuss these results in terms of future efforts to refine emerging empirically based, dimensional-spectrum model of psychopathology, and to use the model to frame psychopathology research more broadly. PMID:23067258
Evaluating the generalizability of GEP models for estimating reference evapotranspiration in distant humid and arid locations

NASA Astrophysics Data System (ADS)

Kiafar, Hamed; Babazadeh, Hosssien; Marti, Pau; Kisi, Ozgur; Landeras, Gorka; Karimi, Sepideh; Shiri, Jalal

2017-10-01

Evapotranspiration estimation is of crucial importance in arid and hyper-arid regions, which suffer from water shortage, increasing dryness and heat. A modeling study is reported here to cross-station assessment between hyper-arid and humid conditions. The derived equations estimate ET0 values based on temperature-, radiation-, and mass transfer-based configurations. Using data from two meteorological stations in a hyper-arid region of Iran and two meteorological stations in a humid region of Spain, different local and cross-station approaches are applied for developing and validating the derived equations. The comparison of the gene expression programming (GEP)-based-derived equations with corresponding empirical-semi empirical ET0 estimation equations reveals the superiority of new formulas in comparison with the corresponding empirical equations. Therefore, the derived models can be successfully applied in these hyper-arid and humid regions as well as similar climatic contexts especially in data-lack situations. The results also show that when relying on proper input configurations, cross-station might be a promising alternative for locally trained models for the stations with data scarcity.
An optimum organizational structure for a large earth-orbiting multidisciplinary Space Base

NASA Technical Reports Server (NTRS)

Ragusa, J. M.

1973-01-01

The purpose of this exploratory study was to identify an optimum hypothetical organizational structure for a large earth-orbiting multidisciplinary research and applications (R&A) Space Base manned by a mixed crew of technologists. Since such a facility does not presently exist, in situ empirical testing was not possible. Study activity was, therefore, concerned with the identification of a desired organizational structural model rather than the empirical testing of it. The essential finding of this research was that a four-level project type 'total matrix' model will optimize the efficiency and effectiveness of Space Base technologists.
Two models for evaluating landslide hazards

USGS Publications Warehouse

Davis, J.C.; Chung, C.-J.; Ohlmacher, G.C.

2006-01-01

Two alternative procedures for estimating landslide hazards were evaluated using data on topographic digital elevation models (DEMs) and bedrock lithologies in an area adjacent to the Missouri River in Atchison County, Kansas, USA. The two procedures are based on the likelihood ratio model but utilize different assumptions. The empirical likelihood ratio model is based on non-parametric empirical univariate frequency distribution functions under an assumption of conditional independence while the multivariate logistic discriminant model assumes that likelihood ratios can be expressed in terms of logistic functions. The relative hazards of occurrence of landslides were estimated by an empirical likelihood ratio model and by multivariate logistic discriminant analysis. Predictor variables consisted of grids containing topographic elevations, slope angles, and slope aspects calculated from a 30-m DEM. An integer grid of coded bedrock lithologies taken from digitized geologic maps was also used as a predictor variable. Both statistical models yield relative estimates in the form of the proportion of total map area predicted to already contain or to be the site of future landslides. The stabilities of estimates were checked by cross-validation of results from random subsamples, using each of the two procedures. Cell-by-cell comparisons of hazard maps made by the two models show that the two sets of estimates are virtually identical. This suggests that the empirical likelihood ratio and the logistic discriminant analysis models are robust with respect to the conditional independent assumption and the logistic function assumption, respectively, and that either model can be used successfully to evaluate landslide hazards. ?? 2006.
VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data

PubMed Central

Daunizeau, Jean; Adam, Vincent; Rigoux, Lionel

2014-01-01

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

PubMed

Schumann, Anja; John, Ulrich; Ulbricht, Sabina; Rüge, Jeannette; Bischof, Gallus; Meyer, Christian

2008-11-01

This study examines tailored feedback letters of a smoking cessation intervention that is conceptually based on the transtheoretical model, from a content-based perspective. Data of 2 population-based intervention studies, both randomized controlled trials, with total N=1044 were used. The procedure of the intervention, the tailoring principle for the feedback letters, and the content of the intervention materials are described in detail. Theoretical and empirical frequencies of unique feedback letters are presented. The intervention system was able to generate a total of 1040 unique letters with normative feedback only, and almost half a million unique letters with normative and ipsative feedback. Almost every single smoker in contemplation, preparation, action, and maintenance had an empirically unique combination of tailoring variables and received a unique letter. In contrast, many smokers in precontemplation shared a combination of tailoring variables and received identical letters. The transtheoretical model provides an enormous theoretical and empirical variability of tailoring. However, tailoring for a major subgroup of smokers, i.e. those who do not intend to quit, needs improvement. Conceptual ideas for additional tailoring variables are discussed.
Fuel Performance Experiments and Modeling: Fission Gas Bubble Nucleation and Growth in Alloy Nuclear Fuels

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

McDeavitt, Sean; Shao, Lin; Tsvetkov, Pavel

2014-04-07

Advanced fast reactor systems being developed under the DOE's Advanced Fuel Cycle Initiative are designed to destroy TRU isotopes generated in existing and future nuclear energy systems. Over the past 40 years, multiple experiments and demonstrations have been completed using U-Zr, U-Pu-Zr, U-Mo and other metal alloys. As a result, multiple empirical and semi-empirical relationships have been established to develop empirical performance modeling codes. Many mechanistic questions about fission as mobility, bubble coalescience, and gas release have been answered through industrial experience, research, and empirical understanding. The advent of modern computational materials science, however, opens new doors of development suchmore » that physics-based multi-scale models may be developed to enable a new generation of predictive fuel performance codes that are not limited by empiricism.« less
Construction of Optimally Reduced Empirical Model by Spatially Distributed Climate Data

NASA Astrophysics Data System (ADS)

Gavrilov, A.; Mukhin, D.; Loskutov, E.; Feigin, A.

2016-12-01

We present an approach to empirical reconstruction of the evolution operator in stochastic form by space-distributed time series. The main problem in empirical modeling consists in choosing appropriate phase variables which can efficiently reduce the dimension of the model at minimal loss of information about system's dynamics which consequently leads to more robust model and better quality of the reconstruction. For this purpose we incorporate in the model two key steps. The first step is standard preliminary reduction of observed time series dimension by decomposition via certain empirical basis (e. g. empirical orthogonal function basis or its nonlinear or spatio-temporal generalizations). The second step is construction of an evolution operator by principal components (PCs) - the time series obtained by the decomposition. In this step we introduce a new way of reducing the dimension of the embedding in which the evolution operator is constructed. It is based on choosing proper combinations of delayed PCs to take into account the most significant spatio-temporal couplings. The evolution operator is sought as nonlinear random mapping parameterized using artificial neural networks (ANN). Bayesian approach is used to learn the model and to find optimal hyperparameters: the number of PCs, the dimension of the embedding, the degree of the nonlinearity of ANN. The results of application of the method to climate data (sea surface temperature, sea level pressure) and their comparing with the same method based on non-reduced embedding are presented. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS).
Modified retrieval algorithm for three types of precipitation distribution using x-band synthetic aperture radar

NASA Astrophysics Data System (ADS)

Xie, Yanan; Zhou, Mingliang; Pan, Dengke

2017-10-01

The forward-scattering model is introduced to describe the response of normalized radar cross section (NRCS) of precipitation with synthetic aperture radar (SAR). Since the distribution of near-surface rainfall is related to the rate of near-surface rainfall and horizontal distribution factor, a retrieval algorithm called modified regression empirical and model-oriented statistical (M-M) based on the volterra integration theory is proposed. Compared with the model-oriented statistical and volterra integration (MOSVI) algorithm, the biggest difference is that the M-M algorithm is based on the modified regression empirical algorithm rather than the linear regression formula to retrieve the value of near-surface rainfall rate. Half of the empirical parameters are reduced in the weighted integral work and a smaller average relative error is received while the rainfall rate is less than 100 mm/h. Therefore, the algorithm proposed in this paper can obtain high-precision rainfall information.
Complex dynamics and empirical evidence (Invited Paper)

NASA Astrophysics Data System (ADS)

Delli Gatti, Domenico; Gaffeo, Edoardo; Giulioni, Gianfranco; Gallegati, Mauro; Kirman, Alan; Palestrini, Antonio; Russo, Alberto

2005-05-01

Standard macroeconomics, based on a reductionist approach centered on the representative agent, is badly equipped to explain the empirical evidence where heterogeneity and industrial dynamics are the rule. In this paper we show that a simple agent-based model of heterogeneous financially fragile agents is able to replicate a large number of scaling type stylized facts with a remarkable degree of statistical precision.
Comparing an annual and daily time-step model for predicting field-scale phosphorus loss

USDA-ARS?s Scientific Manuscript database

Numerous models exist for describing phosphorus (P) losses from agricultural fields. The complexity of these models varies considerably ranging from simple empirically-based annual time-step models to more complex process-based daily time step models. While better accuracy is often assumed with more...
Monthly hydroclimatology of the continental United States

NASA Astrophysics Data System (ADS)

Petersen, Thomas; Devineni, Naresh; Sankarasubramanian, A.

2018-04-01

Physical/semi-empirical models that do not require any calibration are of paramount need for estimating hydrological fluxes for ungauged sites. We develop semi-empirical models for estimating the mean and variance of the monthly streamflow based on Taylor Series approximation of a lumped physically based water balance model. The proposed models require mean and variance of monthly precipitation and potential evapotranspiration, co-variability of precipitation and potential evapotranspiration and regionally calibrated catchment retention sensitivity, atmospheric moisture uptake sensitivity, groundwater-partitioning factor, and the maximum soil moisture holding capacity parameters. Estimates of mean and variance of monthly streamflow using the semi-empirical equations are compared with the observed estimates for 1373 catchments in the continental United States. Analyses show that the proposed models explain the spatial variability in monthly moments for basins in lower elevations. A regionalization of parameters for each water resources region show good agreement between observed moments and model estimated moments during January, February, March and April for mean and all months except May and June for variance. Thus, the proposed relationships could be employed for understanding and estimating the monthly hydroclimatology of ungauged basins using regional parameters.
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.
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.
Soil Erosion as a stochastic process

NASA Astrophysics Data System (ADS)

Casper, Markus C.

2015-04-01

The main tools to provide estimations concerning risk and amount of erosion are different types of soil erosion models: on the one hand, there are empirically based model concepts on the other hand there are more physically based or process based models. However, both types of models have substantial weak points. All empirical model concepts are only capable of providing rough estimates over larger temporal and spatial scales, they do not account for many driving factors that are in the scope of scenario related analysis. In addition, the physically based models contain important empirical parts and hence, the demand for universality and transferability is not given. As a common feature, we find, that all models rely on parameters and input variables, which are to certain, extend spatially and temporally averaged. A central question is whether the apparent heterogeneity of soil properties or the random nature of driving forces needs to be better considered in our modelling concepts. Traditionally, researchers have attempted to remove spatial and temporal variability through homogenization. However, homogenization has been achieved through physical manipulation of the system, or by statistical averaging procedures. The price for obtaining this homogenized (average) model concepts of soils and soil related processes has often been a failure to recognize the profound importance of heterogeneity in many of the properties and processes that we study. Especially soil infiltrability and the resistance (also called "critical shear stress" or "critical stream power") are the most important empirical factors of physically based erosion models. The erosion resistance is theoretically a substrate specific parameter, but in reality, the threshold where soil erosion begins is determined experimentally. The soil infiltrability is often calculated with empirical relationships (e.g. based on grain size distribution). Consequently, to better fit reality, this value needs to be corrected experimentally. To overcome this disadvantage of our actual models, soil erosion models are needed that are able to use stochastic directly variables and parameter distributions. There are only some minor approaches in this direction. The most advanced is the model "STOSEM" proposed by Sidorchuk in 2005. In this model, only a small part of the soil erosion processes is described, the aggregate detachment and the aggregate transport by flowing water. The concept is highly simplified, for example, many parameters are temporally invariant. Nevertheless, the main problem is that our existing measurements and experiments are not geared to provide stochastic parameters (e.g. as probability density functions); in the best case they deliver a statistical validation of the mean values. Again, we get effective parameters, spatially and temporally averaged. There is an urgent need for laboratory and field experiments on overland flow structure, raindrop effects and erosion rate, which deliver information on spatial and temporal structure of soil and surface properties and processes.
Implications of alternative field-sampling designs on Landsat-based mapping of stand age and carbon stocks in Oregon forests

Treesearch

Maureen V. Duane; Warren B. Cohen; John L. Campbell; Tara Hudiburg; David P. Turner; Dale Weyermann

2010-01-01

Empirical models relating forest attributes to remotely sensed metrics are widespread in the literature and underpin many of our efforts to map forest structure across complex landscapes. In this study we compared empirical models relating Landsat reflectance to forest age across Oregon using two alternate sets of ground data: one from a large (n ~ 1500) systematic...
An Empirical Agent-Based Model to Simulate the Adoption of Water Reuse Using the Social Amplification of Risk Framework.

PubMed

Kandiah, Venu; Binder, Andrew R; Berglund, Emily Z

2017-10-01

Water reuse can serve as a sustainable alternative water source for urban areas. However, the successful implementation of large-scale water reuse projects depends on community acceptance. Because of the negative perceptions that are traditionally associated with reclaimed water, water reuse is often not considered in the development of urban water management plans. This study develops a simulation model for understanding community opinion dynamics surrounding the issue of water reuse, and how individual perceptions evolve within that context, which can help in the planning and decision-making process. Based on the social amplification of risk framework, our agent-based model simulates consumer perceptions, discussion patterns, and their adoption or rejection of water reuse. The model is based on the "risk publics" model, an empirical approach that uses the concept of belief clusters to explain the adoption of new technology. Each household is represented as an agent, and parameters that define their behavior and attributes are defined from survey data. Community-level parameters-including social groups, relationships, and communication variables, also from survey data-are encoded to simulate the social processes that influence community opinion. The model demonstrates its capabilities to simulate opinion dynamics and consumer adoption of water reuse. In addition, based on empirical data, the model is applied to investigate water reuse behavior in different regions of the United States. Importantly, our results reveal that public opinion dynamics emerge differently based on membership in opinion clusters, frequency of discussion, and the structure of social networks. © 2017 Society for Risk Analysis.
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.
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.

Oseltamivir Treatment for Children with Influenza-Like Illness in China: A Cost-Effectiveness Analysis.

PubMed

Shen, Kunling; Xiong, Tengbin; Tan, Seng Chuen; Wu, Jiuhong

2016-01-01

Influenza is a common viral respiratory infection that causes epidemics and pandemics in the human population. Oseltamivir is a neuraminidase inhibitor-a new class of antiviral therapy for influenza. Although its efficacy and safety have been established, there is uncertainty regarding whether influenza-like illness (ILI) in children is best managed by oseltamivir at the onset of illness, and its cost-effectiveness in children has not been studied in China. To evaluate the cost-effectiveness of post rapid influenza diagnostic test (RIDT) treatment with oseltamivir and empiric treatment with oseltamivir comparing with no antiviral therapy against influenza for children with ILI. We developed a decision-analytic model based on previously published evidence to simulate and evaluate 1-year potential clinical and economic outcomes associated with three managing strategies for children presenting with symptoms of influenza. Model inputs were derived from literature and expert opinion of clinical practice and research in China. Outcome measures included costs and quality-adjusted life year (QALY). All the interventions were compared with incremental cost-effectiveness ratios (ICER). In base case analysis, empiric treatment with oseltamivir consistently produced the greatest gains in QALY. When compared with no antiviral therapy, the empiric treatment with oseltamivir strategy is very cost effective with an ICER of RMB 4,438. When compared with the post RIDT treatment with oseltamivir, the empiric treatment with oseltamivir strategy is dominant. Probabilistic sensitivity analysis projected that there is a 100% probability that empiric oseltamivir treatment would be considered as a very cost-effective strategy compared to the no antiviral therapy, according to the WHO recommendations for cost-effectiveness thresholds. The same was concluded with 99% probability for empiric oseltamivir treatment being a very cost-effective strategy compared to the post RIDT treatment with oseltamivir. In the Chinese setting of current health system, our modelling based simulation analysis suggests that empiric treatment with oseltamivir to be a cost-saving and very cost-effective strategy in managing children with ILI.
Inductive reasoning.

PubMed

Hayes, Brett K; Heit, Evan; Swendsen, Haruka

2010-03-01

Inductive reasoning entails using existing knowledge or observations to make predictions about novel cases. We review recent findings in research on category-based induction as well as theoretical models of these results, including similarity-based models, connectionist networks, an account based on relevance theory, Bayesian models, and other mathematical models. A number of touchstone empirical phenomena that involve taxonomic similarity are described. We also examine phenomena involving more complex background knowledge about premises and conclusions of inductive arguments and the properties referenced. Earlier models are shown to give a good account of similarity-based phenomena but not knowledge-based phenomena. Recent models that aim to account for both similarity-based and knowledge-based phenomena are reviewed and evaluated. Among the most important new directions in induction research are a focus on induction with uncertain premise categories, the modeling of the relationship between inductive and deductive reasoning, and examination of the neural substrates of induction. A common theme in both the well-established and emerging lines of induction research is the need to develop well-articulated and empirically testable formal models of induction. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.
Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

PubMed

Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A

2015-04-21

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.
Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise

PubMed Central

Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.

2015-01-01

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351
Empirical flow parameters - a tool for hydraulic model validity assessment : [summary].

DOT National Transportation Integrated Search

2013-10-01

Hydraulic modeling assembles models based on generalizations of parameter values from textbooks, professional literature, computer program documentation, and engineering experience. Actual measurements adjacent to the model location are seldom availa...
Spectral Classes for FAA's Integrated Noise Model Version 6.0.

DOT National Transportation Integrated Search

1999-12-07

The starting point in any empirical model such as the Federal Aviation Administrations (FAA) : Integrated Noise Model (INM) is a reference data base. In Version 5.2 and in previous versions : the reference data base consisted solely of a set of no...
An HIV Epidemic Model Based on Viral Load Dynamics: Value in Assessing Empirical Trends in HIV Virulence and Community Viral Load

PubMed Central

Herbeck, Joshua T.; Mittler, John E.; Gottlieb, Geoffrey S.; Mullins, James I.

2014-01-01

Trends in HIV virulence have been monitored since the start of the AIDS pandemic, as studying HIV virulence informs our understanding of HIV epidemiology and pathogenesis. Here, we model changes in HIV virulence as a strictly evolutionary process, using set point viral load (SPVL) as a proxy, to make inferences about empirical SPVL trends from longitudinal HIV cohorts. We develop an agent-based epidemic model based on HIV viral load dynamics. The model contains functions for viral load and transmission, SPVL and disease progression, viral load trajectories in multiple stages of infection, and the heritability of SPVL across transmissions. We find that HIV virulence evolves to an intermediate level that balances infectiousness with longer infected lifespans, resulting in an optimal SPVL∼4.75 log10 viral RNA copies/mL. Adaptive viral evolution may explain observed HIV virulence trends: our model produces SPVL trends with magnitudes that are broadly similar to empirical trends. With regard to variation among studies in empirical SPVL trends, results from our model suggest that variation may be explained by the specific epidemic context, e.g. the mean SPVL of the founding lineage or the age of the epidemic; or improvements in HIV screening and diagnosis that results in sampling biases. We also use our model to examine trends in community viral load, a population-level measure of HIV viral load that is thought to reflect a population's overall transmission potential. We find that community viral load evolves in association with SPVL, in the absence of prevention programs such as antiretroviral therapy, and that the mean community viral load is not necessarily a strong predictor of HIV incidence. PMID:24945322
A prototype of the procedure of strong ground motion prediction for intraslab earthquake based on characterized source model

NASA Astrophysics Data System (ADS)

Iwata, T.; Asano, K.; Sekiguchi, H.

2011-12-01

We propose a prototype of the procedure to construct source models for strong motion prediction during intraslab earthquakes based on the characterized source model (Irikura and Miyake, 2011). The key is the characterized source model which is based on the empirical scaling relationships for intraslab earthquakes and involve the correspondence between the SMGA (strong motion generation area, Miyake et al., 2003) and the asperity (large slip area). Iwata and Asano (2011) obtained the empirical relationships of the rupture area (S) and the total asperity area (Sa) to the seismic moment (Mo) as follows, with assuming power of 2/3 dependency of S and Sa on M0, S (km**2) = 6.57×10**(-11)×Mo**(2/3) (Nm) (1) Sa (km**2) = 1.04 ×10**(-11)×Mo**(2/3) (Nm) (2). Iwata and Asano (2011) also pointed out that the position and the size of SMGA approximately corresponds to the asperity area for several intraslab events. Based on the empirical relationships, we gave a procedure for constructing source models of intraslab earthquakes for strong motion prediction. [1] Give the seismic moment, Mo. [2] Obtain the total rupture area and the total asperity area according to the empirical scaling relationships between S, Sa, and Mo given by Iwata and Asano (2011). [3] Square rupture area and asperities are assumed. [4] The source mechanism is assumed to be the same as that of small events in the source region. [5] Plural scenarios including variety of the number of asperities and rupture starting points are prepared. We apply this procedure by simulating strong ground motions for several observed events for confirming the methodology.
Validating an operational physical method to compute surface radiation from geostationary satellites

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

Sengupta, Manajit; Dhere, Neelkanth G.; Wohlgemuth, John H.

We developed models to compute global horizontal irradiance (GHI) and direct normal irradiance (DNI) over the last three decades. These models can be classified as empirical or physical based on the approach. Empirical models relate ground-based observations with satellite measurements and use these relations to compute surface radiation. Physical models consider the physics behind the radiation received at the satellite and create retrievals to estimate surface radiation. Furthermore, while empirical methods have been traditionally used for computing surface radiation for the solar energy industry, the advent of faster computing has made operational physical models viable. The Global Solar Insolation Projectmore » (GSIP) is a physical model that computes DNI and GHI using the visible and infrared channel measurements from a weather satellite. GSIP uses a two-stage scheme that first retrieves cloud properties and uses those properties in a radiative transfer model to calculate GHI and DNI. Developed for polar orbiting satellites, GSIP has been adapted to NOAA's Geostationary Operation Environmental Satellite series and can run operationally at high spatial resolutions. Our method holds the possibility of creating high quality datasets of GHI and DNI for use by the solar energy industry. We present an outline of the methodology and results from running the model as well as a validation study using ground-based instruments.« 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.
Point- and line-based transformation models for high resolution satellite image rectification

NASA Astrophysics Data System (ADS)

Abd Elrahman, Ahmed Mohamed Shaker

Rigorous mathematical models with the aid of satellite ephemeris data can present the relationship between the satellite image space and the object space. With government funded satellites, access to calibration and ephemeris data has allowed the development and use of these models. However, for commercial high-resolution satellites, which have been recently launched, these data are withheld from users, and therefore alternative empirical models should be used. In general, the existing empirical models are based on the use of control points and involve linking points in the image space and the corresponding points in the object space. But the lack of control points in some remote areas and the questionable accuracy of the identified discrete conjugate points provide a catalyst for the development of algorithms based on features other than control points. This research, concerned with image rectification and 3D geo-positioning determination using High-Resolution Satellite Imagery (HRSI), has two major objectives. First, the effects of satellite sensor characteristics, number of ground control points (GCPs), and terrain elevation variations on the performance of several point based empirical models are studied. Second, a new mathematical model, using only linear features as control features, or linear features with a minimum number of GCPs, is developed. To meet the first objective, several experiments for different satellites such as Ikonos, QuickBird, and IRS-1D have been conducted using different point based empirical models. Various data sets covering different terrain types are presented and results from representative sets of the experiments are shown and analyzed. The results demonstrate the effectiveness and the superiority of these models under certain conditions. From the results obtained, several alternatives to circumvent the effects of the satellite sensor characteristics, the number of GCPs, and the terrain elevation variations are introduced. To meet the second objective, a new model named the Line Based Transformation Model (LBTM) is developed for HRSI rectification. The model has the flexibility to either solely use linear features or use linear features and a number of control points to define the image transformation parameters. Unlike point features, which must be explicitly defined, linear features have the advantage that they can be implicitly defined by any segment along the line. (Abstract shortened by UMI.)
Understanding the effects of different HIV transmission models in individual-based microsimulation of HIV epidemic dynamics in people who inject drugs

PubMed Central

MONTEIRO, J.F.G.; ESCUDERO, D.J.; WEINREB, C.; FLANIGAN, T.; GALEA, S.; FRIEDMAN, S.R.; MARSHALL, B.D.L.

2017-01-01

SUMMARY We investigated how different models of HIV transmission, and assumptions regarding the distribution of unprotected sex and syringe-sharing events (‘risk acts’), affect quantitative understanding of HIV transmission process in people who inject drugs (PWID). The individual-based model simulated HIV transmission in a dynamic sexual and injecting network representing New York City. We constructed four HIV transmission models: model 1, constant probabilities; model 2, random number of sexual and parenteral acts; model 3, viral load individual assigned; and model 4, two groups of partnerships (low and high risk). Overall, models with less heterogeneity were more sensitive to changes in numbers risk acts, producing HIV incidence up to four times higher than that empirically observed. Although all models overestimated HIV incidence, micro-simulations with greater heterogeneity in the HIV transmission modelling process produced more robust results and better reproduced empirical epidemic dynamics. PMID:26753627
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
Evaluation of theoretical and empirical water vapor sorption isotherm models for soils

NASA Astrophysics Data System (ADS)

Arthur, Emmanuel; Tuller, Markus; Moldrup, Per; de Jonge, Lis W.

2016-01-01

The mathematical characterization of water vapor sorption isotherms of soils is crucial for modeling processes such as volatilization of pesticides and diffusive and convective water vapor transport. Although numerous physically based and empirical models were previously proposed to describe sorption isotherms of building materials, food, and other industrial products, knowledge about the applicability of these functions for soils is noticeably lacking. We present an evaluation of nine models for characterizing adsorption/desorption isotherms for a water activity range from 0.03 to 0.93 based on measured data of 207 soils with widely varying textures, organic carbon contents, and clay mineralogy. In addition, the potential applicability of the models for prediction of sorption isotherms from known clay content was investigated. While in general, all investigated models described measured adsorption and desorption isotherms reasonably well, distinct differences were observed between physical and empirical models and due to the different degrees of freedom of the model equations. There were also considerable differences in model performance for adsorption and desorption data. While regression analysis relating model parameters and clay content and subsequent model application for prediction of measured isotherms showed promise for the majority of investigated soils, for soils with distinct kaolinitic and smectitic clay mineralogy predicted isotherms did not closely match the measurements.
Empirical intrinsic geometry for nonlinear modeling and time series filtering.

PubMed

Talmon, Ronen; Coifman, Ronald R

2013-07-30

In this paper, we present a method for time series analysis based on empirical intrinsic geometry (EIG). EIG enables one to reveal the low-dimensional parametric manifold as well as to infer the underlying dynamics of high-dimensional time series. By incorporating concepts of information geometry, this method extends existing geometric analysis tools to support stochastic settings and parametrizes the geometry of empirical distributions. However, the statistical models are not required as priors; hence, EIG may be applied to a wide range of real signals without existing definitive models. We show that the inferred model is noise-resilient and invariant under different observation and instrumental modalities. In addition, we show that it can be extended efficiently to newly acquired measurements in a sequential manner. These two advantages enable us to revisit the Bayesian approach and incorporate empirical dynamics and intrinsic geometry into a nonlinear filtering framework. We show applications to nonlinear and non-Gaussian tracking problems as well as to acoustic signal localization.
An Empirical Bayes Approach to Item Banking. Project Psychometric Aspects of Item Banking No. 6. Research Report 86-6.

ERIC Educational Resources Information Center

van der Linden, Wim J.; Eggen, Theo J. H. M.

A procedure for the sequential optimization of the calibration of an item bank is given. The procedure is based on an empirical Bayes approach to a reformulation of the Rasch model as a model for paired comparisons between the difficulties of test items in which ties are allowed to occur. First, it is indicated how a paired-comparisons design…
Ehrenfest model with large jumps in finance

NASA Astrophysics Data System (ADS)

Takahashi, Hisanao

2004-02-01

Changes (returns) in stock index prices and exchange rates for currencies are argued, based on empirical data, to obey a stable distribution with characteristic exponent α<2 for short sampling intervals and a Gaussian distribution for long sampling intervals. In order to explain this phenomenon, an Ehrenfest model with large jumps (ELJ) is introduced to explain the empirical density function of price changes for both short and long sampling intervals.
Integrating WEPP into the WEPS infrastructure

USDA-ARS?s Scientific Manuscript database

The Wind Erosion Prediction System (WEPS) and the Water Erosion Prediction Project (WEPP) share a common modeling philosophy, that of moving away from primarily empirically based models based on indices or "average conditions", and toward a more process based approach which can be evaluated using ac...
An all-atom structure-based potential for proteins: bridging minimal models with all-atom empirical forcefields.

PubMed

Whitford, Paul C; Noel, Jeffrey K; Gosavi, Shachi; Schug, Alexander; Sanbonmatsu, Kevin Y; Onuchic, José N

2009-05-01

Protein dynamics take place on many time and length scales. Coarse-grained structure-based (Go) models utilize the funneled energy landscape theory of protein folding to provide an understanding of both long time and long length scale dynamics. All-atom empirical forcefields with explicit solvent can elucidate our understanding of short time dynamics with high energetic and structural resolution. Thus, structure-based models with atomic details included can be used to bridge our understanding between these two approaches. We report on the robustness of folding mechanisms in one such all-atom model. Results for the B domain of Protein A, the SH3 domain of C-Src Kinase, and Chymotrypsin Inhibitor 2 are reported. The interplay between side chain packing and backbone folding is explored. We also compare this model to a C(alpha) structure-based model and an all-atom empirical forcefield. Key findings include: (1) backbone collapse is accompanied by partial side chain packing in a cooperative transition and residual side chain packing occurs gradually with decreasing temperature, (2) folding mechanisms are robust to variations of the energetic parameters, (3) protein folding free-energy barriers can be manipulated through parametric modifications, (4) the global folding mechanisms in a C(alpha) model and the all-atom model agree, although differences can be attributed to energetic heterogeneity in the all-atom model, and (5) proline residues have significant effects on folding mechanisms, independent of isomerization effects. Because this structure-based model has atomic resolution, this work lays the foundation for future studies to probe the contributions of specific energetic factors on protein folding and function.
An All-atom Structure-Based Potential for Proteins: Bridging Minimal Models with All-atom Empirical Forcefields

PubMed Central

Whitford, Paul C.; Noel, Jeffrey K.; Gosavi, Shachi; Schug, Alexander; Sanbonmatsu, Kevin Y.; Onuchic, José N.

2012-01-01

Protein dynamics take place on many time and length scales. Coarse-grained structure-based (Gō) models utilize the funneled energy landscape theory of protein folding to provide an understanding of both long time and long length scale dynamics. All-atom empirical forcefields with explicit solvent can elucidate our understanding of short time dynamics with high energetic and structural resolution. Thus, structure-based models with atomic details included can be used to bridge our understanding between these two approaches. We report on the robustness of folding mechanisms in one such all-atom model. Results for the B domain of Protein A, the SH3 domain of C-Src Kinase and Chymotrypsin Inhibitor 2 are reported. The interplay between side chain packing and backbone folding is explored. We also compare this model to a Cα structure-based model and an all-atom empirical forcefield. Key findings include 1) backbone collapse is accompanied by partial side chain packing in a cooperative transition and residual side chain packing occurs gradually with decreasing temperature 2) folding mechanisms are robust to variations of the energetic parameters 3) protein folding free energy barriers can be manipulated through parametric modifications 4) the global folding mechanisms in a Cα model and the all-atom model agree, although differences can be attributed to energetic heterogeneity in the all-atom model 5) proline residues have significant effects on folding mechanisms, independent of isomerization effects. Since this structure-based model has atomic resolution, this work lays the foundation for future studies to probe the contributions of specific energetic factors on protein folding and function. PMID:18837035

Improved model predictive control of resistive wall modes by error field estimator in EXTRAP T2R

NASA Astrophysics Data System (ADS)

Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

2016-12-01

Many implementations of a model-based approach for toroidal plasma have shown better control performance compared to the conventional type of feedback controller. One prerequisite of model-based control is the availability of a control oriented model. This model can be obtained empirically through a systematic procedure called system identification. Such a model is used in this work to design a model predictive controller to stabilize multiple resistive wall modes in EXTRAP T2R reversed-field pinch. Model predictive control is an advanced control method that can optimize the future behaviour of a system. Furthermore, this paper will discuss an additional use of the empirical model which is to estimate the error field in EXTRAP T2R. Two potential methods are discussed that can estimate the error field. The error field estimator is then combined with the model predictive control and yields better radial magnetic field suppression.
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.
A new parameterization of an empirical model for wind/ocean scatterometry

NASA Technical Reports Server (NTRS)

Woiceshyn, P. M.; Wurtele, M. G.; Boggs, D. H.; Mcgoldrick, L. F.; Peteherych, S.

1984-01-01

The power law form of the SEASAT A Scatterometer System (SASS) empirical backscatter-to-wind model function does not uniformly meet the instrument performance over the range 4 to 24 /ms. Analysis indicates that the horizontal polarization (H-Pol) and vertical polarization (V-Pol) components of the benchmark SASS1 model function yield self-consistent results only for a small mid-range of speeds at larger incidence angles, and for a somewhat larger range of speeds at smaller incidence angles. Comparison of SASS1 to in situ data over the Gulf of Alaska region further underscores the shortcomings of the power law form. Finally, a physically based empirical SASS model is proposed which corrects some of the deficiencies of power law models like SASS1. The new model allows the mutual determination of sea surface wind stress and wind speed in a consistent manner from SASS backscatter measurements.
Empirical validation of an agent-based model of wood markets in Switzerland

PubMed Central

Hilty, Lorenz M.; Lemm, Renato; Thees, Oliver

2018-01-01

We present an agent-based model of wood markets and show our efforts to validate this model using empirical data from different sources, including interviews, workshops, experiments, and official statistics. Own surveys closed gaps where data was not available. Our approach to model validation used a variety of techniques, including the replication of historical production amounts, prices, and survey results, as well as a historical case study of a large sawmill entering the market and becoming insolvent only a few years later. Validating the model using this case provided additional insights, showing how the model can be used to simulate scenarios of resource availability and resource allocation. We conclude that the outcome of the rigorous validation qualifies the model to simulate scenarios concerning resource availability and allocation in our study region. PMID:29351300
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.
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.
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…
Educational Inequality and Income Inequality: An Empirical Study on China

ERIC Educational Resources Information Center

Yang, Jun; Huang, Xiao; Li, Xiaoyu

2009-01-01

Based on the endogenous growth theory, this paper uses the Gini coefficient to measure educational inequality and studies the empirical relationship between educational inequality and income inequality through a simultaneous equation model. The results show that: (1) Income inequality leads to educational inequality while the reduction of…
Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets

NASA Astrophysics Data System (ADS)

Gontis, V.; Kononovicius, A.

2017-10-01

We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3 / 2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.
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.
Competency-Based Curriculum Development: A Pragmatic Approach

ERIC Educational Resources Information Center

Broski, David; And Others

1977-01-01

Examines the concept of competency-based education, describes an experience-based model for its development, and discusses some empirically derived rules-of-thumb for its application in allied health. (HD)
Default contagion risks in Russian interbank market

NASA Astrophysics Data System (ADS)

Leonidov, A. V.; Rumyantsev, E. L.

2016-06-01

Systemic risks of default contagion in the Russian interbank market are investigated. The analysis is based on considering the bow-tie structure of the weighted oriented graph describing the structure of the interbank loans. A probabilistic model of interbank contagion explicitly taking into account the empirical bow-tie structure reflecting functionality of the corresponding nodes (borrowers, lenders, borrowers and lenders simultaneously), degree distributions and disassortativity of the interbank network under consideration based on empirical data is developed. The characteristics of contagion-related systemic risk calculated with this model are shown to be in agreement with those of explicit stress tests.
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.
A Simulation Study of Threats to Validity in Quasi-Experimental Designs: Interrelationship between Design, Measurement, and Analysis.

PubMed

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

2016-01-01

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

PubMed Central

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

2016-01-01

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

PubMed

Hoy, Damian G; Rao, Chalapati; Hoa, Nguyen Phuong; Suhardi, S; Lwin, Aye Moe Moe

2013-10-01

Stroke is a leading cause of death in Asia; however, many estimates of stroke mortality are based on epidemiological models rather than empirical data. Since 2005, initiatives have been undertaken in a number of Asian countries to strengthen and analyse vital registration data. This has increased the availability of empirical data on stroke mortality. The aim of this paper is to present estimates of stroke mortality for Indonesia, Myanmar, Viet Nam, Thailand, and Malaysia, which have been derived using these empirical data. Age-specific stroke mortality rates were calculated in each of the five countries, and adjusted for data completeness or misclassification where feasible. All data were age-standardized and the resulting rates were compared with World Health Organization estimates, which are largely based on epidemiological models. Using empirical data, stroke ranked as the leading cause of death in all countries except Malaysia, where it ranked as the second leading cause. Age-standardized rates for males ranged from 94 per 100,000 in Thailand, to over 300 per 100,000 in Indonesia. In all countries, rates were higher for males than for females, and those compiled from empirical data were generally higher than modelled estimates published by World Health Organization. This study highlights the extent of stroke mortality in selected Asian countries, and provides important baseline information to investigate the aetiology of stroke in Asia and design appropriate public health strategies to address the rapidly growing burden from stroke. © 2012 The Authors. International Journal of Stroke © 2012 World Stroke Organization.
Probabilistic representation in syllogistic reasoning: A theory to integrate mental models and heuristics.

PubMed

Hattori, Masasi

2016-12-01

This paper presents a new theory of syllogistic reasoning. The proposed model assumes there are probabilistic representations of given signature situations. Instead of conducting an exhaustive search, the model constructs an individual-based "logical" mental representation that expresses the most probable state of affairs, and derives a necessary conclusion that is not inconsistent with the model using heuristics based on informativeness. The model is a unification of previous influential models. Its descriptive validity has been evaluated against existing empirical data and two new experiments, and by qualitative analyses based on previous empirical findings, all of which supported the theory. The model's behavior is also consistent with findings in other areas, including working memory capacity. The results indicate that people assume the probabilities of all target events mentioned in a syllogism to be almost equal, which suggests links between syllogistic reasoning and other areas of cognition. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.
Route-choice modeling using GPS-based travel surveys.

DOT National Transportation Integrated Search

2013-06-01

The advent of GPS-based travel surveys offers an opportunity to develop empirically-rich route-choice models. However, the GPS traces must first be mapped to the roadway network, map-matching, to identify the network-links actually traversed. For thi...
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...
A physical-based gas-surface interaction model for rarefied gas flow simulation

NASA Astrophysics Data System (ADS)

Liang, Tengfei; Li, Qi; Ye, Wenjing

2018-01-01

Empirical gas-surface interaction models, such as the Maxwell model and the Cercignani-Lampis model, are widely used as the boundary condition in rarefied gas flow simulations. The accuracy of these models in the prediction of macroscopic behavior of rarefied gas flows is less satisfactory in some cases especially the highly non-equilibrium ones. Molecular dynamics simulation can accurately resolve the gas-surface interaction process at atomic scale, and hence can predict accurate macroscopic behavior. They are however too computationally expensive to be applied in real problems. In this work, a statistical physical-based gas-surface interaction model, which complies with the basic relations of boundary condition, is developed based on the framework of the washboard model. In virtue of its physical basis, this new model is capable of capturing some important relations/trends for which the classic empirical models fail to model correctly. As such, the new model is much more accurate than the classic models, and in the meantime is more efficient than MD simulations. Therefore, it can serve as a more accurate and efficient boundary condition for rarefied gas flow simulations.

A Critical Plane-energy Model for Multiaxial Fatigue Life Prediction of Homogeneous and Heterogeneous Materials

NASA Astrophysics Data System (ADS)

Wei, Haoyang

A new critical plane-energy model is proposed in this thesis for multiaxial fatigue life prediction of homogeneous and heterogeneous materials. Brief review of existing methods, especially on the critical plane-based and energy-based methods, are given first. Special focus is on one critical plane approach which has been shown to work for both brittle and ductile metals. The key idea is to automatically change the critical plane orientation with respect to different materials and stress states. One potential drawback of the developed model is that it needs an empirical calibration parameter for non-proportional multiaxial loadings since only the strain terms are used and the out-of-phase hardening cannot be considered. The energy-based model using the critical plane concept is proposed with help of the Mroz-Garud hardening rule to explicitly include the effect of non-proportional hardening under fatigue cyclic loadings. Thus, the empirical calibration for non-proportional loading is not needed since the out-of-phase hardening is naturally included in the stress calculation. The model predictions are compared with experimental data from open literature and it is shown the proposed model can work for both proportional and non-proportional loadings without the empirical calibration. Next, the model is extended for the fatigue analysis of heterogeneous materials integrating with finite element method. Fatigue crack initiation of representative volume of heterogeneous materials is analyzed using the developed critical plane-energy model and special focus is on the microstructure effect on the multiaxial fatigue life predictions. Several conclusions and future work is drawn based on the proposed study.
Predicting Exposure to Consumer-Products Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence and Empirically -Based Scheduling Models

EPA Science Inventory

Information on human behavior and consumer product use is important for characterizing exposures to chemicals in consumer products and in indoor environments. Traditionally, exposure-assessors have relied on time-use surveys to obtain information on exposure-related behavior. In ...
Recent solar extreme ultraviolet irradiance observations and modeling: A review

NASA Technical Reports Server (NTRS)

Tobiska, W. Kent

1993-01-01

For more than 90 years, solar extreme ultraviolet (EUV) irradiance modeling has progressed from empirical blackbody radiation formulations, through fudge factors, to typically measured irradiances and reference spectra was well as time-dependent empirical models representing continua and line emissions. A summary of recent EUV measurements by five rockets and three satellites during the 1980s is presented along with the major modeling efforts. The most significant reference spectra are reviewed and threee independently derived empirical models are described. These include Hinteregger's 1981 SERF1, Nusinov's 1984 two-component, and Tobiska's 1990/1991/SERF2/EUV91 flux models. They each provide daily full-disk broad spectrum flux values from 2 to 105 nm at 1 AU. All the models depend to one degree or another on the long time series of the Atmosphere Explorer E (AE-E) EUV database. Each model uses ground- and/or space-based proxies to create emissions from solar atmospheric regions. Future challenges in EUV modeling are summarized including the basic requirements of models, the task of incorporating new observations and theory into the models, the task of comparing models with solar-terrestrial data sets, and long-term goals and modeling objectives. By the late 1990s, empirical models will potentially be improved through the use of proposed solar EUV irradiance measurements and images at selected wavelengths that will greatly enhance modeling and predictive capabilities.
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.
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
Empirical conversion of the vertical profile of reflectivity from Ku-band to S-band frequency

NASA Astrophysics Data System (ADS)

Cao, Qing; Hong, Yang; Qi, Youcun; Wen, Yixin; Zhang, Jian; Gourley, Jonathan J.; Liao, Liang

2013-02-01

ABSTRACT This paper presents an empirical method for converting reflectivity from Ku-band (13.8 GHz) to S-band (2.8 GHz) for several hydrometeor species, which facilitates the incorporation of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements into quantitative precipitation estimation (QPE) products from the U.S. Next-Generation Radar (NEXRAD). The development of empirical dual-frequency relations is based on theoretical simulations, which have assumed appropriate scattering and microphysical models for liquid and solid hydrometeors (raindrops, snow, and ice/hail). Particle phase, shape, orientation, and density (especially for snow particles) have been considered in applying the T-matrix method to compute the scattering amplitudes. Gamma particle size distribution (PSD) is utilized to model the microphysical properties in the ice region, melting layer, and raining region of precipitating clouds. The variability of PSD parameters is considered to study the characteristics of dual-frequency reflectivity, especially the variations in radar dual-frequency ratio (DFR). The empirical relations between DFR and Ku-band reflectivity have been derived for particles in different regions within the vertical structure of precipitating clouds. The reflectivity conversion using the proposed empirical relations has been tested using real data collected by TRMM-PR and a prototype polarimetric WSR-88D (Weather Surveillance Radar 88 Doppler) radar, KOUN. The processing and analysis of collocated data demonstrate the validity of the proposed empirical relations and substantiate their practical significance for reflectivity conversion, which is essential to the TRMM-based vertical profile of reflectivity correction approach in improving NEXRAD-based QPE.
Dynamics of bloggers’ communities: Bipartite networks from empirical data and agent-based modeling

NASA Astrophysics Data System (ADS)

Mitrović, Marija; Tadić, Bosiljka

2012-11-01

We present an analysis of the empirical data and the agent-based modeling of the emotional behavior of users on the Web portals where the user interaction is mediated by posted comments, like Blogs and Diggs. We consider the dataset of discussion-driven popular Diggs, in which all comments are screened by machine-learning emotion detection in the text, to determine positive and negative valence (attractiveness and aversiveness) of each comment. By mapping the data onto a suitable bipartite network, we perform an analysis of the network topology and the related time-series of the emotional comments. The agent-based model is then introduced to simulate the dynamics and to capture the emergence of the emotional behaviors and communities. The agents are linked to posts on a bipartite network, whose structure evolves through their actions on the posts. The emotional states (arousal and valence) of each agent fluctuate in time, subject to the current contents of the posts to which the agent is exposed. By an agent’s action on a post its current emotions are transferred to the post. The model rules and the key parameters are inferred from the considered empirical data to ensure their realistic values and mutual consistency. The model assumes that the emotional arousal over posts drives the agent’s action. The simulations are preformed for the case of constant flux of agents and the results are analyzed in full analogy with the empirical data. The main conclusions are that the emotion-driven dynamics leads to long-range temporal correlations and emergent networks with community structure, that are comparable with the ones in the empirical system of popular posts. In view of pure emotion-driven agents actions, this type of comparisons provide a quantitative measure for the role of emotions in the dynamics on real blogs. Furthermore, the model reveals the underlying mechanisms which relate the post popularity with the emotion dynamics and the prevalence of negative emotions (critique). We also demonstrate how the community structure is tuned by varying a relevant parameter in the model. All data used in these works are fully anonymized.
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.
Poisson-process generalization for the trading waiting-time distribution in a double-auction mechanism

NASA Astrophysics Data System (ADS)

Cincotti, Silvano; Ponta, Linda; Raberto, Marco; Scalas, Enrico

2005-05-01

In this paper, empirical analyses and computational experiments are presented on high-frequency data for a double-auction (book) market. Main objective of the paper is to generalize the order waiting time process in order to properly model such empirical evidences. The empirical study is performed on the best bid and best ask data of 7 U.S. financial markets, for 30-stock time series. In particular, statistical properties of trading waiting times have been analyzed and quality of fits is evaluated by suitable statistical tests, i.e., comparing empirical distributions with theoretical models. Starting from the statistical studies on real data, attention has been focused on the reproducibility of such results in an artificial market. The computational experiments have been performed within the Genoa Artificial Stock Market. In the market model, heterogeneous agents trade one risky asset in exchange for cash. Agents have zero intelligence and issue random limit or market orders depending on their budget constraints. The price is cleared by means of a limit order book. The order generation is modelled with a renewal process. Based on empirical trading estimation, the distribution of waiting times between two consecutive orders is modelled by a mixture of exponential processes. Results show that the empirical waiting-time distribution can be considered as a generalization of a Poisson process. Moreover, the renewal process can approximate real data and implementation on the artificial stocks market can reproduce the trading activity in a realistic way.
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.
Composite Pseudoclassical Models of Quarks

NASA Astrophysics Data System (ADS)

Musin, Yu. R.

2018-05-01

Composite models of quarks are proposed, analogous to composite models of leptons. A model-based explanation of the appearance of generations of fundamental particles in the Standard Model is given. New empirical formulas are proposed for the quark masses, modifying Barut's well-known formula.
Improving Global Models of Remotely Sensed Ocean Chlorophyll Content Using Partial Least Squares and Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Gholizadeh, H.; Robeson, S. M.

2015-12-01

Empirical models have been widely used to estimate global chlorophyll content from remotely sensed data. Here, we focus on the standard NASA empirical models that use blue-green band ratios. These band ratio ocean color (OC) algorithms are in the form of fourth-order polynomials and the parameters of these polynomials (i.e. coefficients) are estimated from the NASA bio-Optical Marine Algorithm Data set (NOMAD). Most of the points in this data set have been sampled from tropical and temperate regions. However, polynomial coefficients obtained from this data set are used to estimate chlorophyll content in all ocean regions with different properties such as sea-surface temperature, salinity, and downwelling/upwelling patterns. Further, the polynomial terms in these models are highly correlated. In sum, the limitations of these empirical models are as follows: 1) the independent variables within the empirical models, in their current form, are correlated (multicollinear), and 2) current algorithms are global approaches and are based on the spatial stationarity assumption, so they are independent of location. Multicollinearity problem is resolved by using partial least squares (PLS). PLS, which transforms the data into a set of independent components, can be considered as a combined form of principal component regression (PCR) and multiple regression. Geographically weighted regression (GWR) is also used to investigate the validity of spatial stationarity assumption. GWR solves a regression model over each sample point by using the observations within its neighbourhood. PLS results show that the empirical method underestimates chlorophyll content in high latitudes, including the Southern Ocean region, when compared to PLS (see Figure 1). Cluster analysis of GWR coefficients also shows that the spatial stationarity assumption in empirical models is not likely a valid assumption.
Recent progress in empirical modeling of ion composition in the topside ionosphere

NASA Astrophysics Data System (ADS)

Truhlik, Vladimir; Triskova, Ludmila; Bilitza, Dieter; Kotov, Dmytro; Bogomaz, Oleksandr; Domnin, Igor

2016-07-01

The last deep and prolonged solar minimum revealed shortcomings of existing empirical models, especially of parameter models that depend strongly on solar activity, such as the IRI (International Reference Ionosphere) ion composition model, and that are based on data sets from previous solar cycles. We have improved the TTS-03 ion composition model (Triskova et al., 2003) which is included in IRI since version 2007. The new model called AEIKion-13 employs an improved description of the dependence of ion composition on solar activity. We have also developed new global models of the upper transition height based on large data sets of vertical electron density profiles from ISIS, Alouette and COSMIC. The upper transition height is used as an anchor point for adjustment of the AEIKion-13 ion composition model. Additionally, we show also progress on improvements of the altitudinal dependence of the ion composition in the AEIKion-13 model. Results of the improved model are compared with data from other types of measurements including data from the Atmosphere Explorer C and E and C/NOFS satellites, and the Kharkiv and Arecibo incoherent scatter radars. Possible real time updating of the model by the upper transition height from the real time COSMIC vertical profiles is discussed. Triskova, L.,Truhlik,V., Smilauer, J.,2003. An empirical model of ion composition in the outer ionosphere. Adv. Space Res. 31(3), 653-663.
Evaluation of an activated carbon packed bed for the adsorption of phenols from petroleum refinery wastewater.

PubMed

El-Naas, Muftah H; Alhaija, Manal A; Al-Zuhair, Sulaiman

2017-03-01

The performance of an adsorption column packed with granular activated carbon was evaluated for the removal of phenols from refinery wastewater. The effects of phenol feed concentration (80-182 mg/l), feed flow rate (5-20 ml/min), and activated carbon packing mass (5-15 g) on the breakthrough characteristics of the adsorption system were determined. The continuous adsorption process was simulated using batch data and the parameters for a new empirical model were determined. Different dynamic models such as Adams-Bohart, Wolborsko, Thomas, and Yoon-Nelson models were also fitted to the experimental data for the sake of comparison. The empirical, Yoon-Nelson and Thomas models showed a high degree of fitting at different operation conditions, with the empirical model giving the best fit based on the Akaike information criterion (AIC). At an initial phenol concentration of 175 mg/l, packing mass of 10 g, a flow rate of 10 ml/min and a temperature of 25 °C, the SSE of the new empirical and Thomas models were identical (248.35) and very close to that of the Yoon-Nelson model (259.49). The values were significantly lower than that of the Adams-Bohart model, which was determined to be 19,358.48. The superiority of the new empirical model and the Thomas model was also confirmed from the values of the R 2 and AIC, which were 0.99 and 38.3, respectively, compared to 0.92 and 86.2 for Adams-Bohart model.
GPS-Derived Precipitable Water Compared with the Air Force Weather Agency’s MM5 Model Output

DTIC Science & Technology

2002-03-26

and less then 100 sensors are available throughout Europe . While the receiver density is currently comparable to the upper-air sounding network...profiles from 38 upper air sites throughout Europe . Based on these empirical formulae and simplifications, Bevis (1992) has determined that the error...Alaska using Bevis’ (1992) empirical correlation based on 8718 radiosonde calculations over 2 years. Other studies have been conducted in Europe and
Improving reliability of aggregation, numerical simulation and analysis of complex systems by empirical data

NASA Astrophysics Data System (ADS)

Dobronets, Boris S.; Popova, Olga A.

2018-05-01

The paper considers a new approach of regression modeling that uses aggregated data presented in the form of density functions. Approaches to Improving the reliability of aggregation of empirical data are considered: improving accuracy and estimating errors. We discuss the procedures of data aggregation as a preprocessing stage for subsequent to regression modeling. An important feature of study is demonstration of the way how represent the aggregated data. It is proposed to use piecewise polynomial models, including spline aggregate functions. We show that the proposed approach to data aggregation can be interpreted as the frequency distribution. To study its properties density function concept is used. Various types of mathematical models of data aggregation are discussed. For the construction of regression models, it is proposed to use data representation procedures based on piecewise polynomial models. New approaches to modeling functional dependencies based on spline aggregations are proposed.
Experimental Evaluation of Equivalent-Fluid Models for Melamine Foam

NASA Technical Reports Server (NTRS)

Allen, Albert R.; Schiller, Noah H.

2016-01-01

Melamine foam is a soft porous material commonly used in noise control applications. Many models exist to represent porous materials at various levels of fidelity. This work focuses on rigid frame equivalent fluid models, which represent the foam as a fluid with a complex speed of sound and density. There are several empirical models available to determine these frequency dependent parameters based on an estimate of the material flow resistivity. Alternatively, these properties can be experimentally educed using an impedance tube setup. Since vibroacoustic models are generally sensitive to these properties, this paper assesses the accuracy of several empirical models relative to impedance tube measurements collected with melamine foam samples. Diffuse field sound absorption measurements collected using large test articles in a laboratory are also compared with absorption predictions determined using model-based and measured foam properties. Melamine foam slabs of various thicknesses are considered.
Student Interactions in Online Discussion Forum: Empirical Research from "Media Richness Theory" Perspective

ERIC Educational Resources Information Center

Balaji, M. S.; Chakrabarti, Diganta

2010-01-01

The present study contributes to the understanding of the effectiveness of online discussion forum in student learning. A conceptual model based on "theory of online learning" and "media richness theory" was proposed and empirically tested. We extend the current understanding of media richness theory to suggest that use of…
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.
Language acquisition is model-based rather than model-free.

PubMed

Wang, Felix Hao; Mintz, Toben H

2016-01-01

Christiansen & Chater (C&C) propose that learning language is learning to process language. However, we believe that the general-purpose prediction mechanism they propose is insufficient to account for many phenomena in language acquisition. We argue from theoretical considerations and empirical evidence that many acquisition tasks are model-based, and that different acquisition tasks require different, specialized models.

Intrinsic Motivation and Engagement as "Active Ingredients" in Garden-Based Education: Examining Models and Measures Derived from Self-Determination Theory

ERIC Educational Resources Information Center

Skinner, Ellen A.; Chi, Una

2012-01-01

Building on self-determination theory, this study presents a model of intrinsic motivation and engagement as "active ingredients" in garden-based education. The model was used to create reliable and valid measures of key constructs, and to guide the empirical exploration of motivational processes in garden-based learning. Teacher- and…
Space evolution model and empirical analysis of an urban public transport network

NASA Astrophysics Data System (ADS)

Sui, Yi; Shao, Feng-jing; Sun, Ren-cheng; Li, Shu-jing

2012-07-01

This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.
Nonlinear Model Reduction in Power Systems by Balancing of Empirical Controllability and Observability Covariances

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

Qi, Junjian; Wang, Jianhui; Liu, Hui

Abstract: In this paper, nonlinear model reduction for power systems is performed by the balancing of empirical controllability and observability covariances that are calculated around the operating region. Unlike existing model reduction methods, the external system does not need to be linearized but is directly dealt with as a nonlinear system. A transformation is found to balance the controllability and observability covariances in order to determine which states have the greatest contribution to the input-output behavior. The original system model is then reduced by Galerkin projection based on this transformation. The proposed method is tested and validated on a systemmore » comprised of a 16-machine 68-bus system and an IEEE 50-machine 145-bus system. The results show that by using the proposed model reduction the calculation efficiency can be greatly improved; at the same time, the obtained state trajectories are close to those for directly simulating the whole system or partitioning the system while not performing reduction. Compared with the balanced truncation method based on a linearized model, the proposed nonlinear model reduction method can guarantee higher accuracy and similar calculation efficiency. It is shown that the proposed method is not sensitive to the choice of the matrices for calculating the empirical covariances.« less
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…
Probabilistic empirical prediction of seasonal climate: evaluation and potential applications

NASA Astrophysics Data System (ADS)

Dieppois, B.; Eden, J.; van Oldenborgh, G. J.

2017-12-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a new evaluation of an established empirical system used to predict seasonal climate across the globe. Forecasts for surface air temperature, precipitation and sea level pressure are produced by the KNMI Probabilistic Empirical Prediction (K-PREP) system every month and disseminated via the KNMI Climate Explorer (climexp.knmi.nl). K-PREP is based on multiple linear regression and built on physical principles to the fullest extent with predictive information taken from the global CO2-equivalent concentration, large-scale modes of variability in the climate system and regional-scale information. K-PREP seasonal forecasts for the period 1981-2016 will be compared with corresponding dynamically generated forecasts produced by operational forecast systems. While there are many regions of the world where empirical forecast skill is extremely limited, several areas are identified where K-PREP offers comparable skill to dynamical systems. We discuss two key points in the future development and application of the K-PREP system: (a) the potential for K-PREP to provide a more useful basis for reference forecasts than those based on persistence or climatology, and (b) the added value of including K-PREP forecast information in multi-model forecast products, at least for known regions of good skill. We also discuss the potential development of stakeholder-driven applications of the K-PREP system, including empirical forecasts for circumboreal fire activity.
Overview of physical models of liquid entrainment in annular gas-liquid flow

NASA Astrophysics Data System (ADS)

Cherdantsev, Andrey V.

2018-03-01

A number of recent papers devoted to development of physically-based models for prediction of liquid entrainment in annular regime of two-phase flow are analyzed. In these models shearing-off the crests of disturbance waves by the gas drag force is supposed to be the physical mechanism of entrainment phenomenon. The models are based on a number of assumptions on wavy structure, including inception of disturbance waves due to Kelvin-Helmholtz instability, linear velocity profile inside liquid film and high degree of three-dimensionality of disturbance waves. Validity of the assumptions is analyzed by comparison to modern experimental observations. It was shown that nearly every assumption is in strong qualitative and quantitative disagreement with experiments, which leads to massive discrepancies between the modeled and real properties of the disturbance waves. As a result, such models over-predict the entrained fraction by several orders of magnitude. The discrepancy is usually reduced using various kinds of empirical corrections. This, combined with empiricism already included in the models, turns the models into another kind of empirical correlations rather than physically-based models.
Estimating Casualties for Large Earthquakes Worldwide Using an Empirical Approach

USGS Publications Warehouse

Jaiswal, Kishor; Wald, David J.; Hearne, Mike

2009-01-01

We developed an empirical country- and region-specific earthquake vulnerability model to be used as a candidate for post-earthquake fatality estimation by the U.S. Geological Survey's Prompt Assessment of Global Earthquakes for Response (PAGER) system. The earthquake fatality rate is based on past fatal earthquakes (earthquakes causing one or more deaths) in individual countries where at least four fatal earthquakes occurred during the catalog period (since 1973). Because only a few dozen countries have experienced four or more fatal earthquakes since 1973, we propose a new global regionalization scheme based on idealization of countries that are expected to have similar susceptibility to future earthquake losses given the existing building stock, its vulnerability, and other socioeconomic characteristics. The fatality estimates obtained using an empirical country- or region-specific model will be used along with other selected engineering risk-based loss models for generation of automated earthquake alerts. These alerts could potentially benefit the rapid-earthquake-response agencies and governments for better response to reduce earthquake fatalities. Fatality estimates are also useful to stimulate earthquake preparedness planning and disaster mitigation. The proposed model has several advantages as compared with other candidate methods, and the country- or region-specific fatality rates can be readily updated when new data become available.
Empirically based device modeling of bulk heterojunction organic photovoltaics

NASA Astrophysics Data System (ADS)

Pierre, Adrien; Lu, Shaofeng; Howard, Ian A.; Facchetti, Antonio; Arias, Ana Claudia

2013-10-01

An empirically based, open source, optoelectronic model is constructed to accurately simulate organic photovoltaic (OPV) devices. Bulk heterojunction OPV devices based on a new low band gap dithienothiophene- diketopyrrolopyrrole donor polymer (P(TBT-DPP)) are blended with PC70BM and processed under various conditions, with efficiencies up to 4.7%. The mobilities of electrons and holes, bimolecular recombination coefficients, exciton quenching efficiencies in donor and acceptor domains and optical constants of these devices are measured and input into the simulator to yield photocurrent with less than 7% error. The results from this model not only show carrier activity in the active layer but also elucidate new routes of device optimization by varying donor-acceptor composition as a function of position. Sets of high and low performance devices are investigated and compared side-by-side.
A Motivational Theory of Life-Span Development

PubMed Central

Heckhausen, Jutta; Wrosch, Carsten; Schulz, Richard

2010-01-01

This article had four goals. First, the authors identified a set of general challenges and questions that a life-span theory of development should address. Second, they presented a comprehensive account of their Motivational Theory of Life-Span Development. They integrated the model of optimization in primary and secondary control and the action-phase model of developmental regulation with their original life-span theory of control to present a comprehensive theory of development. Third, they reviewed the relevant empirical literature testing key propositions of the Motivational Theory of Life-Span Development. Finally, because the conceptual reach of their theory goes far beyond the current empirical base, they pointed out areas that deserve further and more focused empirical inquiry. PMID:20063963
Generalized Bootstrap Method for Assessment of Uncertainty in Semivariogram Inference

USGS Publications Warehouse

Olea, R.A.; Pardo-Iguzquiza, E.

2011-01-01

The semivariogram and its related function, the covariance, play a central role in classical geostatistics for modeling the average continuity of spatially correlated attributes. Whereas all methods are formulated in terms of the true semivariogram, in practice what can be used are estimated semivariograms and models based on samples. A generalized form of the bootstrap method to properly model spatially correlated data is used to advance knowledge about the reliability of empirical semivariograms and semivariogram models based on a single sample. Among several methods available to generate spatially correlated resamples, we selected a method based on the LU decomposition and used several examples to illustrate the approach. The first one is a synthetic, isotropic, exhaustive sample following a normal distribution, the second example is also a synthetic but following a non-Gaussian random field, and a third empirical sample consists of actual raingauge measurements. Results show wider confidence intervals than those found previously by others with inadequate application of the bootstrap. Also, even for the Gaussian example, distributions for estimated semivariogram values and model parameters are positively skewed. In this sense, bootstrap percentile confidence intervals, which are not centered around the empirical semivariogram and do not require distributional assumptions for its construction, provide an achieved coverage similar to the nominal coverage. The latter cannot be achieved by symmetrical confidence intervals based on the standard error, regardless if the standard error is estimated from a parametric equation or from bootstrap. ?? 2010 International Association for Mathematical Geosciences.
A test-based strategy is more cost effective than empiric dose escalation for patients with Crohn's disease who lose responsiveness to infliximab.

PubMed

Velayos, Fernando S; Kahn, James G; Sandborn, William J; Feagan, Brian G

2013-06-01

Patients with Crohn's disease who become unresponsive to therapy with tumor necrosis factor antagonists are managed initially with either empiric dose escalation or testing-based strategies. The comparative cost effectiveness of these 2 strategies is unknown. We investigated whether a testing-based strategy is more cost effective than an empiric dose-escalation strategy. A decision analytic model that simulated 2 cohorts of patients with Crohn's disease compared outcomes for the 2 strategies over a 1-year time period. The incremental cost-effectiveness ratio of the empiric strategy was expressed as cost per quality-adjusted life-year (QALY) gained, compared with the testing-based strategy. We performed 1-way, probabilistic, and prespecified secondary analyses. The testing strategy yielded similar QALYs compared with the empiric strategy (0.801 vs 0.800, respectively) but was less expensive ($31,870 vs $37,266, respectively). In sensitivity analyses, the incremental cost-effectiveness ratio of the empiric strategy ranged from $500,000 to more than $5 million per QALY gained. Similar rates of remission (63% vs 66%) and response (28% vs 26%) were achieved through differential use of available interventions. The testing-based strategy resulted in a higher percentage of surgeries (48% vs 34%) and lower percentage use of high-dose biological therapy (41% vs 54%). A testing-based strategy is a cost-effective alternative to the current strategy of empiric dose escalation for managing patients with Crohn's disease who have lost responsiveness to infliximab. The basis for this difference is lower cost at similar outcomes. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, A.; Sengupta, M.; Wilcox, S.

Models to compute Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) have been in development over the last 3 decades. These models can be classified as empirical or physical, based on the approach. Empirical models relate ground based observations with satellite measurements and use these relations to compute surface radiation. Physical models consider the radiation received from the earth at the satellite and create retrievals to estimate surface radiation. While empirical methods have been traditionally used for computing surface radiation for the solar energy industry the advent of faster computing has made operational physical models viable. The Global Solarmore » Insolation Project (GSIP) is an operational physical model from NOAA that computes GHI using the visible and infrared channel measurements from the GOES satellites. GSIP uses a two-stage scheme that first retrieves cloud properties and uses those properties in a radiative transfer model to calculate surface radiation. NREL, University of Wisconsin and NOAA have recently collaborated to adapt GSIP to create a 4 km GHI and DNI product every 30 minutes. This paper presents an outline of the methodology and a comprehensive validation using high quality ground based solar data from the National Oceanic and Atmospheric Administration (NOAA) Surface Radiation (SURFRAD) (http://www.srrb.noaa.gov/surfrad/sitepage.html) and Integrated Surface Insolation Study (ISIS) http://www.srrb.noaa.gov/isis/isissites.html), the Solar Radiation Research Laboratory (SRRL) at National Renewable Energy Laboratory (NREL), and Sun Spot One (SS1) stations.« less
Empirical Requirements Analysis for Mars Surface Operations Using the Flashline Mars Arctic Research Station

NASA Technical Reports Server (NTRS)

Clancey, William J.; Lee, Pascal; Sierhuis, Maarten; Norvig, Peter (Technical Monitor)

2001-01-01

Living and working on Mars will require model-based computer systems for maintaining and controlling complex life support, communication, transportation, and power systems. This technology must work properly on the first three-year mission, augmenting human autonomy, without adding-yet more complexity to be diagnosed and repaired. One design method is to work with scientists in analog (mars-like) setting to understand how they prefer to work, what constrains will be imposed by the Mars environment, and how to ameliorate difficulties. We describe how we are using empirical requirements analysis to prototype model-based tools at a research station in the High Canadian Arctic.
Quantitative evaluation of simulated functional brain networks in graph theoretical analysis.

PubMed

Lee, Won Hee; Bullmore, Ed; Frangou, Sophia

2017-02-01

There is increasing interest in the potential of whole-brain computational models to provide mechanistic insights into resting-state brain networks. It is therefore important to determine the degree to which computational models reproduce the topological features of empirical functional brain networks. We used empirical connectivity data derived from diffusion spectrum and resting-state functional magnetic resonance imaging data from healthy individuals. Empirical and simulated functional networks, constrained by structural connectivity, were defined based on 66 brain anatomical regions (nodes). Simulated functional data were generated using the Kuramoto model in which each anatomical region acts as a phase oscillator. Network topology was studied using graph theory in the empirical and simulated data. The difference (relative error) between graph theory measures derived from empirical and simulated data was then estimated. We found that simulated data can be used with confidence to model graph measures of global network organization at different dynamic states and highlight the sensitive dependence of the solutions obtained in simulated data on the specified connection densities. This study provides a method for the quantitative evaluation and external validation of graph theory metrics derived from simulated data that can be used to inform future study designs. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Predictive vs. Empiric Assessment of Schistosomiasis: Implications for Treatment Projections in Ghana

PubMed Central

Kabore, Achille; Biritwum, Nana-Kwadwo; Downs, Philip W.; Soares Magalhaes, Ricardo J.; Zhang, Yaobi; Ottesen, Eric A.

2013-01-01

Background Mapping the distribution of schistosomiasis is essential to determine where control programs should operate, but because it is impractical to assess infection prevalence in every potentially endemic community, model-based geostatistics (MBG) is increasingly being used to predict prevalence and determine intervention strategies. Methodology/Principal Findings To assess the accuracy of MBG predictions for Schistosoma haematobium infection in Ghana, school surveys were evaluated at 79 sites to yield empiric prevalence values that could be compared with values derived from recently published MBG predictions. Based on these findings schools were categorized according to WHO guidelines so that practical implications of any differences could be determined. Using the mean predicted values alone, 21 of the 25 empirically determined ‘high-risk’ schools requiring yearly praziquantel would have been undertreated and almost 20% of the remaining schools would have been treated despite empirically-determined absence of infection – translating into 28% of the children in the 79 schools being undertreated and 12% receiving treatment in the absence of any demonstrated need. Conclusions/Significance Using the current predictive map for Ghana as a spatial decision support tool by aggregating prevalence estimates to the district level was clearly not adequate for guiding the national program, but the alternative of assessing each school in potentially endemic areas of Ghana or elsewhere is not at all feasible; modelling must be a tool complementary to empiric assessments. Thus for practical usefulness, predictive risk mapping should not be thought of as a one-time exercise but must, as in the current study, be an iterative process that incorporates empiric testing and model refining to create updated versions that meet the needs of disease control operational managers. PMID:23505584
Predicting the particle size distribution of eroded sediment using artificial neural networks.

PubMed

Lagos-Avid, María Paz; Bonilla, Carlos A

2017-03-01

Water erosion causes soil degradation and nonpoint pollution. Pollutants are primarily transported on the surfaces of fine soil and sediment particles. Several soil loss models and empirical equations have been developed for the size distribution estimation of the sediment leaving the field, including the physically-based models and empirical equations. Usually, physically-based models require a large amount of data, sometimes exceeding the amount of available data in the modeled area. Conversely, empirical equations do not always predict the sediment composition associated with individual events and may require data that are not always available. Therefore, the objective of this study was to develop a model to predict the particle size distribution (PSD) of eroded soil. A total of 41 erosion events from 21 soils were used. These data were compiled from previous studies. Correlation and multiple regression analyses were used to identify the main variables controlling sediment PSD. These variables were the particle size distribution in the soil matrix, the antecedent soil moisture condition, soil erodibility, and hillslope geometry. With these variables, an artificial neural network was calibrated using data from 29 events (r 2 =0.98, 0.97, and 0.86; for sand, silt, and clay in the sediment, respectively) and then validated and tested on 12 events (r 2 =0.74, 0.85, and 0.75; for sand, silt, and clay in the sediment, respectively). The artificial neural network was compared with three empirical models. The network presented better performance in predicting sediment PSD and differentiating rain-runoff events in the same soil. In addition to the quality of the particle distribution estimates, this model requires a small number of easily obtained variables, providing a convenient routine for predicting PSD in eroded sediment in other pollutant transport models. Copyright © 2017 Elsevier B.V. All rights reserved.
Derivation of an Explicit Form of the Percolation-Based Effective-Medium Approximation for Thermal Conductivity of Partially Saturated Soils

NASA Astrophysics Data System (ADS)

Sadeghi, Morteza; Ghanbarian, Behzad; Horton, Robert

2018-02-01

Thermal conductivity is an essential component in multiphysics models and coupled simulation of heat transfer, fluid flow, and solute transport in porous media. In the literature, various empirical, semiempirical, and physical models were developed for thermal conductivity and its estimation in partially saturated soils. Recently, Ghanbarian and Daigle (GD) proposed a theoretical model, using the percolation-based effective-medium approximation, whose parameters are physically meaningful. The original GD model implicitly formulates thermal conductivity λ as a function of volumetric water content θ. For the sake of computational efficiency in numerical calculations, in this study, we derive an explicit λ(θ) form of the GD model. We also demonstrate that some well-known empirical models, e.g., Chung-Horton, widely applied in the HYDRUS model, as well as mixing models are special cases of the GD model under specific circumstances. Comparison with experiments indicates that the GD model can accurately estimate soil thermal conductivity.
Species delimitation using Bayes factors: simulations and application to the Sceloporus scalaris species group (Squamata: Phrynosomatidae).

PubMed

Grummer, Jared A; Bryson, Robert W; Reeder, Tod W

2014-03-01

Current molecular methods of species delimitation are limited by the types of species delimitation models and scenarios that can be tested. Bayes factors allow for more flexibility in testing non-nested species delimitation models and hypotheses of individual assignment to alternative lineages. Here, we examined the efficacy of Bayes factors in delimiting species through simulations and empirical data from the Sceloporus scalaris species group. Marginal-likelihood scores of competing species delimitation models, from which Bayes factor values were compared, were estimated with four different methods: harmonic mean estimation (HME), smoothed harmonic mean estimation (sHME), path-sampling/thermodynamic integration (PS), and stepping-stone (SS) analysis. We also performed model selection using a posterior simulation-based analog of the Akaike information criterion through Markov chain Monte Carlo analysis (AICM). Bayes factor species delimitation results from the empirical data were then compared with results from the reversible-jump MCMC (rjMCMC) coalescent-based species delimitation method Bayesian Phylogenetics and Phylogeography (BP&P). Simulation results show that HME and sHME perform poorly compared with PS and SS marginal-likelihood estimators when identifying the true species delimitation model. Furthermore, Bayes factor delimitation (BFD) of species showed improved performance when species limits are tested by reassigning individuals between species, as opposed to either lumping or splitting lineages. In the empirical data, BFD through PS and SS analyses, as well as the rjMCMC method, each provide support for the recognition of all scalaris group taxa as independent evolutionary lineages. Bayes factor species delimitation and BP&P also support the recognition of three previously undescribed lineages. In both simulated and empirical data sets, harmonic and smoothed harmonic mean marginal-likelihood estimators provided much higher marginal-likelihood estimates than PS and SS estimators. The AICM displayed poor repeatability in both simulated and empirical data sets, and produced inconsistent model rankings across replicate runs with the empirical data. Our results suggest that species delimitation through the use of Bayes factors with marginal-likelihood estimates via PS or SS analyses provide a useful and complementary alternative to existing species delimitation methods.
When Does Model-Based Control Pay Off?

PubMed

Kool, Wouter; Cushman, Fiery A; Gershman, Samuel J

2016-08-01

Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to "model-free" and "model-based" strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand.
Modeling Infrared Signal Reflections to Characterize Indoor Multipath Propagation

PubMed Central

De-La-Llana-Calvo, Álvaro; Lázaro-Galilea, José Luis; Gardel-Vicente, Alfredo; Rodríguez-Navarro, David; Bravo-Muñoz, Ignacio; Tsirigotis, Georgios; Iglesias-Miguel, Juan

2017-01-01

In this paper, we propose a model to characterize Infrared (IR) signal reflections on any kind of surface material, together with a simplified procedure to compute the model parameters. The model works within the framework of Local Positioning Systems (LPS) based on IR signals (IR-LPS) to evaluate the behavior of transmitted signal Multipaths (MP), which are the main cause of error in IR-LPS, and makes several contributions to mitigation methods. Current methods are based on physics, optics, geometry and empirical methods, but these do not meet our requirements because of the need to apply several different restrictions and employ complex tools. We propose a simplified model based on only two reflection components, together with a method for determining the model parameters based on 12 empirical measurements that are easily performed in the real environment where the IR-LPS is being applied. Our experimental results show that the model provides a comprehensive solution to the real behavior of IR MP, yielding small errors when comparing real and modeled data (the mean error ranges from 1% to 4% depending on the environment surface materials). Other state-of-the-art methods yielded mean errors ranging from 15% to 40% in test measurements. PMID:28406436

An Empirical Model for the Use of Biglan's Disciplinary Categories. AIR Forum 1979 Paper.

ERIC Educational Resources Information Center

Muffo, John A.; Langston, Ira W., IV

The Biglan method of grouping academic disciplines for comparative purposes is discussed as well as an empirically-based system for making internal comparisons among different academic units. The clusters of disciplines developed by Biglan (pure and applied, soft and hard, life and nonlife) are useful guides in working with data involving…
Synthesis of asymmetric movement trajectories in timed rhythmic behaviour by means of frequency modulation.

PubMed

Waadeland, Carl Haakon

2017-01-01

Results from different empirical investigations on gestural aspects of timed rhythmic movements indicate that the production of asymmetric movement trajectories is a feature that seems to be a common characteristic of various performances of repetitive rhythmic patterns. The behavioural or neural origin of these asymmetrical trajectories is, however, not identified. In the present study we outline a theoretical model that is capable of producing syntheses of asymmetric movement trajectories documented in empirical investigations by Balasubramaniam et al. (2004). Characteristic qualities of the extension/flexion profiles in the observed asymmetric trajectories are reproduced, and we conduct an experiment similar to Balasubramaniam et al. (2004) to show that the empirically documented movement trajectories and our modelled approximations share the same spectral components. The model is based on an application of frequency modulated movements, and a theoretical interpretation offered by the model is to view paced rhythmic movements as a result of an unpaced movement being "stretched" and "compressed", caused by the presence of a metronome. We discuss our model construction within the framework of event-based and emergent timing, and argue that a change between these timing modes might be reflected by the strength of the modulation in our model. Copyright © 2016 Elsevier B.V. All rights reserved.
A Formal Approach to Empirical Dynamic Model Optimization and Validation

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

PubMed Central

2012-01-01

Background In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression. Methods We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final P values between methods. Results We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases. Conclusions We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase P values in meta-regression of multiple covariates for relatively small amount of trials. PMID:22587815
Hydraulic-based empirical model for sediment and soil organic carbon loss on steep slopes for extreme rainstorms on the Chinese loess Plateau

NASA Astrophysics Data System (ADS)

Liu, L.; Li, Z. W.; Nie, X. D.; He, J. J.; Huang, B.; Chang, X. F.; Liu, C.; Xiao, H. B.; Wang, D. Y.

2017-11-01

Building a hydraulic-based empirical model for sediment and soil organic carbon (SOC) loss is significant because of the complex erosion process that includes gravitational erosion, ephemeral gully, and gully erosion for loess soils. To address this issue, a simulation of rainfall experiments was conducted in a 1 m × 5 m box on slope gradients of 15°, 20°, and 25° for four typical loess soils with different textures, namely, Ansai, Changwu, Suide, and Yangling. The simulated rainfall of 120 mm h-1 lasted for 45 min. Among the five hydraulic factors (i.e., flow velocity, runoff depth, shear stress, stream power, and unit stream power), flow velocity and stream power showed close relationships with SOC concentration, especially the average flow velocity at 2 m from the outlet where the runoff attained the maximum sediment load. Flow velocity controlled SOC enrichment by affecting the suspension-saltation transport associated with the clay and silt contents in sediments. In consideration of runoff rate, average flow velocity at 2 m location from the outlet, and slope steepness as input variables, a hydraulic-based sediment and SOC loss model was built on the basis of the relationships of hydraulic factors to sediment and SOC loss. Nonlinear regression models were built to calculate the parameters of the model. The difference between the effective and dispersed median diameter (δD50) or the SOC content of the original soil served as the independent variable. The hydraulic-based sediment and SOC loss model exhibited good performance for the Suide and Changwu soils, that is, these soils contained lower amounts of aggregates than those of Ansai and Yangling soils. The hydraulic-based empirical model for sediment and SOC loss can serve as an important reference for physical-based sediment models and can bring new insights into SOC loss prediction when serious erosion occurs on steep slopes.
Mechanism-based modeling of solute strengthening: application to thermal creep in Zr alloy

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

Tome, Carlos; Wen, Wei; Capolungo, Laurent

2017-08-01

This report focuses on the development of a physics-based thermal creep model aiming to predict the behavior of Zr alloy under reactor accident condition. The current models used for this kind of simulations are mostly empirical in nature, based generally on fits to the experimental steady-state creep rates under different temperature and stress conditions, which has the following limitations. First, reactor accident conditions, such as RIA and LOCA, usually take place in short times and involve only the primary, not the steady-state creep behavior stage. Moreover, the empirical models cannot cover the conditions from normal operation to accident environments. Formore » example, Kombaiah and Murty [1,2] recently reported a transition between the low (n~4) and high (n~9) power law creep regimes in Zr alloys depending on the applied stress. Capturing such a behavior requires an accurate description of the mechanisms involved in the process. Therefore, a mechanism-based model that accounts for the evolution with time of microstructure is more appropriate and reliable for this kind of simulation.« less
The fractional volatility model: An agent-based interpretation

NASA Astrophysics Data System (ADS)

Vilela Mendes, R.

2008-06-01

Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.
Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

Eight different variable selection techniques for model-based and non-model-based clustering are evaluated across a wide range of cluster structures. It is shown that several methods have difficulties when non-informative variables (i.e., random noise) are included in the model. Furthermore, the distribution of the random noise greatly impacts the…
Development of a new model for short period ocean tidal variations of Earth rotation

NASA Astrophysics Data System (ADS)

Schuh, Harald

2015-08-01

Within project SPOT (Short Period Ocean Tidal variations in Earth rotation) we develop a new high frequency Earth rotation model based on empirical ocean tide models. The main purpose of the SPOT model is its application to space geodetic observations such as GNSS and VLBI.We consider an empirical ocean tide model, which does not require hydrodynamic ocean modeling to determine ocean tidal angular momentum. We use here the EOT11a model of Savcenko & Bosch (2012), which is extended for some additional minor tides (e.g. M1, J1, T2). As empirical tidal models do not provide ocean tidal currents, which are re- quired for the computation of oceanic relative angular momentum, we implement an approach first published by Ray (2001) to estimate ocean tidal current veloci- ties for all tides considered in the extended EOT11a model. The approach itself is tested by application to tidal heights from hydrodynamic ocean tide models, which also provide tidal current velocities. Based on the tidal heights and the associated current velocities the oceanic tidal angular momentum (OTAM) is calculated.For the computation of the related short period variation of Earth rotation, we have re-examined the Euler-Liouville equation for an elastic Earth model with a liquid core. The focus here is on the consistent calculation of the elastic Love num- bers and associated Earth model parameters, which are considered in the Euler- Liouville equation for diurnal and sub-diurnal periods in the frequency domain.
Application of a compressible flow solver and barotropic cavitation model for the evaluation of the suction head in a low specific speed centrifugal pump impeller channel

NASA Astrophysics Data System (ADS)

Limbach, P.; Müller, T.; Skoda, R.

2015-12-01

Commonly, for the simulation of cavitation in centrifugal pumps incompressible flow solvers with VOF kind cavitation models are applied. Since the source/sink terms of the void fraction transport equation are based on simplified bubble dynamics, empirical parameters may need to be adjusted to the particular pump operating point. In the present study a barotropic cavitation model, which is based solely on thermodynamic fluid properties and does not include any empirical parameters, is applied on a single flow channel of a pump impeller in combination with a time-explicit viscous compressible flow solver. The suction head curves (head drop) are compared to the results of an incompressible implicit standard industrial CFD tool and are predicted qualitatively correct by the barotropic model.
Global model of zenith tropospheric delay proposed based on EOF analysis

NASA Astrophysics Data System (ADS)

Sun, Langlang; Chen, Peng; Wei, Erhu; Li, Qinzheng

2017-07-01

Tropospheric delay is one of the main error budgets in Global Navigation Satellite System (GNSS) measurements. Many empirical correction models have been developed to compensate this delay, and models which do not require meteorological parameters have received the most attention. This study established a global troposphere zenith total delay (ZTD) model, called Global Empirical Orthogonal Function Troposphere (GEOFT), based on the empirical orthogonal function (EOF, also known as geographically weighted PCAs) analysis method and the Global Geodetic Observing System (GGOS) Atmosphere data from 2012 to 2015. The results showed that ZTD variation could be well represented by the characteristics of the EOF base function Ek and associated coefficients Pk. Here, E1 mainly signifies the equatorial anomaly; E2 represents north-south asymmetry, and E3 and E4 reflects regional variation. Moreover, P1 mainly reflects annual and semiannual variation components; P2 and P3 mainly contains annual variation components, and P4 displays semiannual variation components. We validated the proposed GEOFT model using tropospheric delay data of GGOS ZTD grid data and the tropospheric product of the International GNSS Service (IGS) over the year 2016. The results showed that GEOFT model has high accuracy with bias and RMS of -0.3 and 3.9 cm, respectively, with respect to the GGOS ZTD data, and of -0.8 and 4.1 cm, respectively, with respect to the global IGS tropospheric product. The accuracy of GEOFT demonstrating that the use of the EOF analysis method to characterize ZTD variation is reasonable.
When Does Model-Based Control Pay Off?

PubMed Central

2016-01-01

Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to “model-free” and “model-based” strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand. PMID:27564094
Development of a lifetime prediction model for lithium-ion batteries based on extended accelerated aging test data

NASA Astrophysics Data System (ADS)

Ecker, Madeleine; Gerschler, Jochen B.; Vogel, Jan; Käbitz, Stefan; Hust, Friedrich; Dechent, Philipp; Sauer, Dirk Uwe

2012-10-01

Battery lifetime prognosis is a key requirement for successful market introduction of electric and hybrid vehicles. This work aims at the development of a lifetime prediction approach based on an aging model for lithium-ion batteries. A multivariable analysis of a detailed series of accelerated lifetime experiments representing typical operating conditions in hybrid electric vehicle is presented. The impact of temperature and state of charge on impedance rise and capacity loss is quantified. The investigations are based on a high-power NMC/graphite lithium-ion battery with good cycle lifetime. The resulting mathematical functions are physically motivated by the occurring aging effects and are used for the parameterization of a semi-empirical aging model. An impedance-based electric-thermal model is coupled to the aging model to simulate the dynamic interaction between aging of the battery and the thermal as well as electric behavior. Based on these models different drive cycles and management strategies can be analyzed with regard to their impact on lifetime. It is an important tool for vehicle designers and for the implementation of business models. A key contribution of the paper is the parameterization of the aging model by experimental data, while aging simulation in the literature usually lacks a robust empirical foundation.
A Novel Approach for Blast-Induced Flyrock Prediction Based on Imperialist Competitive Algorithm and Artificial Neural Network

PubMed Central

Marto, Aminaton; Jahed Armaghani, Danial; Tonnizam Mohamad, Edy; Makhtar, Ahmad Mahir

2014-01-01

Flyrock is one of the major disturbances induced by blasting which may cause severe damage to nearby structures. This phenomenon has to be precisely predicted and subsequently controlled through the changing in the blast design to minimize potential risk of blasting. The scope of this study is to predict flyrock induced by blasting through a novel approach based on the combination of imperialist competitive algorithm (ICA) and artificial neural network (ANN). For this purpose, the parameters of 113 blasting operations were accurately recorded and flyrock distances were measured for each operation. By applying the sensitivity analysis, maximum charge per delay and powder factor were determined as the most influential parameters on flyrock. In the light of this analysis, two new empirical predictors were developed to predict flyrock distance. For a comparison purpose, a predeveloped backpropagation (BP) ANN was developed and the results were compared with those of the proposed ICA-ANN model and empirical predictors. The results clearly showed the superiority of the proposed ICA-ANN model in comparison with the proposed BP-ANN model and empirical approaches. PMID:25147856
A novel approach for blast-induced flyrock prediction based on imperialist competitive algorithm and artificial neural network.

PubMed

Marto, Aminaton; Hajihassani, Mohsen; Armaghani, Danial Jahed; Mohamad, Edy Tonnizam; Makhtar, Ahmad Mahir

2014-01-01

Flyrock is one of the major disturbances induced by blasting which may cause severe damage to nearby structures. This phenomenon has to be precisely predicted and subsequently controlled through the changing in the blast design to minimize potential risk of blasting. The scope of this study is to predict flyrock induced by blasting through a novel approach based on the combination of imperialist competitive algorithm (ICA) and artificial neural network (ANN). For this purpose, the parameters of 113 blasting operations were accurately recorded and flyrock distances were measured for each operation. By applying the sensitivity analysis, maximum charge per delay and powder factor were determined as the most influential parameters on flyrock. In the light of this analysis, two new empirical predictors were developed to predict flyrock distance. For a comparison purpose, a predeveloped backpropagation (BP) ANN was developed and the results were compared with those of the proposed ICA-ANN model and empirical predictors. The results clearly showed the superiority of the proposed ICA-ANN model in comparison with the proposed BP-ANN model and empirical approaches.
[Crop geometry identification based on inversion of semiempirical BRDF models].

PubMed

Huang, Wen-jiang; Wang, Jin-di; Mu, Xi-han; Wang, Ji-hua; Liu, Liang-yun; Liu, Qiang; Niu, Zheng

2007-10-01

Investigations have been made on identification of erective and horizontal varieties by bidirectional canopy reflected spectrum and semi-empirical bidirectional reflectance distribution function (BRDF) models. The qualitative effect of leaf area index (LAI) and average leaf angle (ALA) on crop canopy reflected spectrum was studied. The structure parameter sensitive index (SPEI) based on the weight for the volumetric kernel (fvol), the weight for the geometric kernel (fgeo), and the weight for constant corresponding to isotropic reflectance (fiso), was defined in the present study for crop geometry identification. However, the weights associated with the kernels of semi-empirical BRDF model do not have a direct relationship with measurable biophysical parameters. Therefore, efforts have focused on trying to find the relation between these semi-empirical BRDF kernel weights and various vegetation structures. SPEI was proved to be more sensitive to identify crop geometry structures than structural scattering index (SSI) and normalized difference f-index (NDFI), SPEI could be used to distinguish erective and horizontal geometry varieties. So, it is feasible to identify horizontal and erective varieties of wheat by bidirectional canopy reflected spectrum.
Evaluation of Multispectral Based Radiative Transfer Model Inversion to Estimate Leaf Area Index in Wheat

USDA-ARS?s Scientific Manuscript database

Leaf area index (LAI) is a critical variable for predicting the growth and productivity of crops. Remote sensing estimates of LAI have relied upon empirical relationships between spectral vegetation indices and ground measurements that are costly to obtain. Radiative transfer model inversion based o...
Small field detector correction factors kQclin,Qmsr (fclin,fmsr) for silicon-diode and diamond detectors with circular 6 MV fields derived using both empirical and numerical methods.

PubMed

O'Brien, D J; León-Vintró, L; McClean, B

2016-01-01

The use of radiotherapy fields smaller than 3 cm in diameter has resulted in the need for accurate detector correction factors for small field dosimetry. However, published factors do not always agree and errors introduced by biased reference detectors, inaccurate Monte Carlo models, or experimental errors can be difficult to distinguish. The aim of this study was to provide a robust set of detector-correction factors for a range of detectors using numerical, empirical, and semiempirical techniques under the same conditions and to examine the consistency of these factors between techniques. Empirical detector correction factors were derived based on small field output factor measurements for circular field sizes from 3.1 to 0.3 cm in diameter performed with a 6 MV beam. A PTW 60019 microDiamond detector was used as the reference dosimeter. Numerical detector correction factors for the same fields were derived based on calculations from a geant4 Monte Carlo model of the detectors and the Linac treatment head. Semiempirical detector correction factors were derived from the empirical output factors and the numerical dose-to-water calculations. The PTW 60019 microDiamond was found to over-respond at small field sizes resulting in a bias in the empirical detector correction factors. The over-response was similar in magnitude to that of the unshielded diode. Good agreement was generally found between semiempirical and numerical detector correction factors except for the PTW 60016 Diode P, where the numerical values showed a greater over-response than the semiempirical values by a factor of 3.7% for a 1.1 cm diameter field and higher for smaller fields. Detector correction factors based solely on empirical measurement or numerical calculation are subject to potential bias. A semiempirical approach, combining both empirical and numerical data, provided the most reliable results.
An empirical model of the topside plasma density around 600 km based on ROCSAT-1 and Hinotori observations

NASA Astrophysics Data System (ADS)

Huang, He; Chen, Yiding; Liu, Libo; Le, Huijun; Wan, Weixing

2015-05-01

It is an urgent task to improve the ability of ionospheric empirical models to more precisely reproduce the plasma density variations in the topside ionosphere. Based on the Republic of China Satellite 1 (ROCSAT-1) observations, we developed a new empirical model of topside plasma density around 600 km under relatively quiet geomagnetic conditions. The model reproduces the ROCSAT-1 plasma density observations with a root-mean-square-error of 0.125 in units of lg(Ni(cm-3)) and reasonably describes the temporal and spatial variations of plasma density at altitudes in the range from 550 to 660 km. The model results are also in good agreement with observations from Hinotori, Coupled Ion-Neutral Dynamics Investigations/Communications/Navigation Outage Forecasting System satellites and the incoherent scatter radar at Arecibo. Further, we combined ROCSAT-1 and Hinotori data to improve the ROCSAT-1 model and built a new model (R&H model) after the consistency between the two data sets had been confirmed with the original ROCSAT-1 model. In particular, we studied the solar activity dependence of topside plasma density at a fixed altitude by R&H model and find that its feature slightly differs from the case when the orbit altitude evolution is ignored. In addition, the R&H model shows the merging of the two crests of equatorial ionization anomaly above the F2 peak, while the IRI_Nq topside option always produces two separate crests in this range of altitudes.
Box-wing model approach for solar radiation pressure modelling in a multi-GNSS scenario

NASA Astrophysics Data System (ADS)

Tobias, Guillermo; Jesús García, Adrián

2016-04-01

The solar radiation pressure force is the largest orbital perturbation after the gravitational effects and the major error source affecting GNSS satellites. A wide range of approaches have been developed over the years for the modelling of this non gravitational effect as part of the orbit determination process. These approaches are commonly divided into empirical, semi-analytical and analytical, where their main difference relies on the amount of knowledge of a-priori physical information about the properties of the satellites (materials and geometry) and their attitude. It has been shown in the past that the pre-launch analytical models fail to achieve the desired accuracy mainly due to difficulties in the extrapolation of the in-orbit optical and thermic properties, the perturbations in the nominal attitude law and the aging of the satellite's surfaces, whereas empirical models' accuracies strongly depend on the amount of tracking data used for deriving the models, and whose performances are reduced as the area to mass ratio of the GNSS satellites increases, as it happens for the upcoming constellations such as BeiDou and Galileo. This paper proposes to use basic box-wing model for Galileo complemented with empirical parameters, based on the limited available information about the Galileo satellite's geometry. The satellite is modelled as a box, representing the satellite bus, and a wing representing the solar panel. The performance of the model will be assessed for GPS, GLONASS and Galileo constellations. The results of the proposed approach have been analyzed over a one year period. In order to assess the results two different SRP models have been used. Firstly, the proposed box-wing model and secondly, the new CODE empirical model, ECOM2. The orbit performances of both models are assessed using Satellite Laser Ranging (SLR) measurements, together with the evaluation of the orbit prediction accuracy. This comparison shows the advantages and disadvantages of taking the physical interactions between satellite and solar radiation into account in an empirical model with respect to a pure empirical model.

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
Diagnosing Model Errors in Simulation of Solar Radiation on Inclined Surfaces

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

Xie, Yu; Sengupta, Manajit

2016-11-21

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 show significant differences between two highly used isotropic transposition models with one substantially underestimating the 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 canmore » be used as a guide for future development of physics-based transposition models.« less
Student Background, School Climate, School Disorder, and Student Achievement: An Empirical Study of New York City's Middle Schools

ERIC Educational Resources Information Center

Chen, Greg; Weikart, Lynne A.

2008-01-01

This study develops and tests a school disorder and student achievement model based upon the school climate framework. The model was fitted to 212 New York City middle schools using the Structural Equations Modeling Analysis method. The analysis shows that the model fits the data well based upon test statistics and goodness of fit indices. The…
Tsunami probability in the Caribbean Region

USGS Publications Warehouse

Parsons, T.; Geist, E.L.

2008-01-01

We calculated tsunami runup probability (in excess of 0.5 m) at coastal sites throughout the Caribbean region. We applied a Poissonian probability model because of the variety of uncorrelated tsunami sources in the region. Coastlines were discretized into 20 km by 20 km cells, and the mean tsunami runup rate was determined for each cell. The remarkable ???500-year empirical record compiled by O'Loughlin and Lander (2003) was used to calculate an empirical tsunami probability map, the first of three constructed for this study. However, it is unclear whether the 500-year record is complete, so we conducted a seismic moment-balance exercise using a finite-element model of the Caribbean-North American plate boundaries and the earthquake catalog, and found that moment could be balanced if the seismic coupling coefficient is c = 0.32. Modeled moment release was therefore used to generate synthetic earthquake sequences to calculate 50 tsunami runup scenarios for 500-year periods. We made a second probability map from numerically-calculated runup rates in each cell. Differences between the first two probability maps based on empirical and numerical-modeled rates suggest that each captured different aspects of tsunami generation; the empirical model may be deficient in primary plate-boundary events, whereas numerical model rates lack backarc fault and landslide sources. We thus prepared a third probability map using Bayesian likelihood functions derived from the empirical and numerical rate models and their attendant uncertainty to weight a range of rates at each 20 km by 20 km coastal cell. Our best-estimate map gives a range of 30-year runup probability from 0 - 30% regionally. ?? irkhaueser 2008.
pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

PubMed

Zhang, J; Feng, J-Y; Ni, Y-L; Wen, Y-J; Niu, Y; Tamba, C L; Yue, C; Song, Q; Zhang, Y-M

2017-06-01

Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.
Predictive Modeling of Risk Associated with Temperature Extremes over Continental US

NASA Astrophysics Data System (ADS)

Kravtsov, S.; Roebber, P.; Brazauskas, V.

2016-12-01

We build an extremely statistically accurate, essentially bias-free empirical emulator of atmospheric surface temperature and apply it for meteorological risk assessment over the domain of continental US. The resulting prediction scheme achieves an order-of-magnitude or larger gain of numerical efficiency compared with the schemes based on high-resolution dynamical atmospheric models, leading to unprecedented accuracy of the estimated risk distributions. The empirical model construction methodology is based on our earlier work, but is further modified to account for the influence of large-scale, global climate change on regional US weather and climate. The resulting estimates of the time-dependent, spatially extended probability of temperature extremes over the simulation period can be used as a risk management tool by insurance companies and regulatory governmental agencies.
Study of the cross-market effects of Brexit based on the improved symbolic transfer entropy GARCH model—An empirical analysis of stock–bond correlations

PubMed Central

Chen, Xiurong; Zhao, Rubo

2017-01-01

In this paper, we study the cross-market effects of Brexit on the stock and bond markets of nine major countries in the world. By incorporating information theory, we introduce the time-varying impact weights based on symbolic transfer entropy to improve the traditional GARCH model. The empirical results show that under the influence of Brexit, flight-to-quality not only commonly occurs between the stocks and bonds of each country but also simultaneously occurs among different countries. We also find that the accuracy of the time-varying symbolic transfer entropy GARCH model proposed in this paper has been improved compared to the traditional GARCH model, which indicates that it has a certain practical application value. PMID:28817712
Around the macrolide - Impact of 3D structure of macrocycles on lipophilicity and cellular accumulation.

PubMed

Koštrun, Sanja; Munic Kos, Vesna; Matanović Škugor, Maja; Palej Jakopović, Ivana; Malnar, Ivica; Dragojević, Snježana; Ralić, Jovica; Alihodžić, Sulejman

2017-06-16

The aim of this study was to investigate lipophilicity and cellular accumulation of rationally designed azithromycin and clarithromycin derivatives at the molecular level. The effect of substitution site and substituent properties on a global physico-chemical profile and cellular accumulation of investigated compounds was studied using calculated structural parameters as well as experimentally determined lipophilicity. In silico models based on the 3D structure of molecules were generated to investigate conformational effect on studied properties and to enable prediction of lipophilicity and cellular accumulation for this class of molecules based on non-empirical parameters. The applicability of developed models was explored on a validation and test sets and compared with previously developed empirical models. Copyright © 2017 Elsevier Masson SAS. All rights reserved.
Best Practice Models of Effective Vocational Rehabilitation Service Delivery in the Public Rehabilitation Program: A Review and Synthesis of the Empirical Literature

ERIC Educational Resources Information Center

Fleming, Allison R.; Del Valle, Roy; Kim, Muwoong; Leahy, Michael J.

2013-01-01

Rehabilitation counselors and practitioners are under increased pressure to adopt and pursue evidenced-based practices, and the rehabilitation counseling literature has been criticized for a lack of empirical work providing support for individual-level interventions. The purpose of this literature review was to examine the last 25 years of…
Towards Validation of an Adaptive Flight Control Simulation Using Statistical Emulation

NASA Technical Reports Server (NTRS)

He, Yuning; Lee, Herbert K. H.; Davies, Misty D.

2012-01-01

Traditional validation of flight control systems is based primarily upon empirical testing. Empirical testing is sufficient for simple systems in which a.) the behavior is approximately linear and b.) humans are in-the-loop and responsible for off-nominal flight regimes. A different possible concept of operation is to use adaptive flight control systems with online learning neural networks (OLNNs) in combination with a human pilot for off-nominal flight behavior (such as when a plane has been damaged). Validating these systems is difficult because the controller is changing during the flight in a nonlinear way, and because the pilot and the control system have the potential to co-adapt in adverse ways traditional empirical methods are unlikely to provide any guarantees in this case. Additionally, the time it takes to find unsafe regions within the flight envelope using empirical testing means that the time between adaptive controller design iterations is large. This paper describes a new concept for validating adaptive control systems using methods based on Bayesian statistics. This validation framework allows the analyst to build nonlinear models with modal behavior, and to have an uncertainty estimate for the difference between the behaviors of the model and system under test.
Understanding hind limb lameness signs in horses using simple rigid body mechanics.

PubMed

Starke, S D; May, S A; Pfau, T

2015-09-18

Hind limb lameness detection in horses relies on the identification of movement asymmetry which can be based on multiple pelvic landmarks. This study explains the poorly understood relationship between hind limb lameness pointers, related to the tubera coxae and sacrum, based on experimental data in context of a simple rigid body model. Vertical displacement of tubera coxae and sacrum was quantified experimentally in 107 horses with varying lameness degrees. A geometrical rigid-body model of pelvis movement during lameness was created in Matlab. Several asymmetry measures were calculated and contrasted. Results showed that model predictions for tubera coxae asymmetry during lameness matched experimental observations closely. Asymmetry for sacrum and comparative tubera coxae movement showed a strong association both empirically (R(2)≥ 0.92) and theoretically. We did not find empirical or theoretical evidence for a systematic, pronounced adaptation in the pelvic rotation pattern with increasing lameness. The model showed that the overall range of movement between tubera coxae does not allow the appreciation of asymmetry changes beyond mild lameness. When evaluating movement relative to the stride cycle we did find empirical evidence for asymmetry being slightly more visible when comparing tubera coxae amplitudes rather than sacrum amplitudes, although variation exists for mild lameness. In conclusion, the rigidity of the equine pelvis results in tightly linked movement trajectories of different pelvic landmarks. The model allows the explanation of empirical observations in the context of the underlying mechanics, helping the identification of potentially limited assessment choices when evaluating gait. Copyright © 2015 Elsevier Ltd. All rights reserved.
Do quantitative decadal forecasts from GCMs provide decision relevant skill?

NASA Astrophysics Data System (ADS)

Suckling, E. B.; Smith, L. A.

2012-04-01

It is widely held that only physics-based simulation models can capture the dynamics required to provide decision-relevant probabilistic climate predictions. This fact in itself provides no evidence that predictions from today's GCMs are fit for purpose. Empirical (data-based) models are employed to make probability forecasts on decadal timescales, where it is argued that these 'physics free' forecasts provide a quantitative 'zero skill' target for the evaluation of forecasts based on more complicated models. It is demonstrated that these zero skill models are competitive with GCMs on decadal scales for probability forecasts evaluated over the last 50 years. Complications of statistical interpretation due to the 'hindcast' nature of this experiment, and the likely relevance of arguments that the lack of hindcast skill is irrelevant as the signal will soon 'come out of the noise' are discussed. A lack of decision relevant quantiative skill does not bring the science-based insights of anthropogenic warming into doubt, but it does call for a clear quantification of limits, as a function of lead time, for spatial and temporal scales on which decisions based on such model output are expected to prove maladaptive. Failing to do so may risk the credibility of science in support of policy in the long term. The performance amongst a collection of simulation models is evaluated, having transformed ensembles of point forecasts into probability distributions through the kernel dressing procedure [1], according to a selection of proper skill scores [2] and contrasted with purely data-based empirical models. Data-based models are unlikely to yield realistic forecasts for future climate change if the Earth system moves away from the conditions observed in the past, upon which the models are constructed; in this sense the empirical model defines zero skill. When should a decision relevant simulation model be expected to significantly outperform such empirical models? Probability forecasts up to ten years ahead (decadal forecasts) are considered, both on global and regional spatial scales for surface air temperature. Such decadal forecasts are not only important in terms of providing information on the impacts of near-term climate change, but also from the perspective of climate model validation, as hindcast experiments and a sufficient database of historical observations allow standard forecast verification methods to be used. Simulation models from the ENSEMBLES hindcast experiment [3] are evaluated and contrasted with static forecasts of the observed climatology, persistence forecasts and against simple statistical models, called dynamic climatology (DC). It is argued that DC is a more apropriate benchmark in the case of a non-stationary climate. It is found that the ENSEMBLES models do not demonstrate a significant increase in skill relative to the empirical models even at global scales over any lead time up to a decade ahead. It is suggested that the contsruction and co-evaluation with the data-based models become a regular component of the reporting of large simulation model forecasts. The methodology presented may easily be adapted to other forecasting experiments and is expected to influence the design of future experiments. The inclusion of comparisons with dynamic climatology and other data-based approaches provide important information to both scientists and decision makers on which aspects of state-of-the-art simulation forecasts are likely to be fit for purpose. [1] J. Bröcker and L. A. Smith. From ensemble forecasts to predictive distributions, Tellus A, 60(4), 663-678 (2007). [2] J. Bröcker and L. A. Smith. Scoring probabilistic forecasts: The importance of being proper, Weather and Forecasting, 22, 382-388 (2006). [3] F. J. Doblas-Reyes, A. Weisheimer, T. N. Palmer, J. M. Murphy and D. Smith. Forecast quality asessment of the ENSEMBLES seasonal-to-decadal stream 2 hindcasts, ECMWF Technical Memorandum, 621 (2010).
High-resolution empirical geomagnetic field model TS07D: Investigating run-on-request and forecasting modes of operation

NASA Astrophysics Data System (ADS)

Stephens, G. K.; Sitnov, M. I.; Ukhorskiy, A. Y.; Vandegriff, J. D.; Tsyganenko, N. A.

2010-12-01

The dramatic increase of the geomagnetic field data volume available due to many recent missions, including GOES, Polar, Geotail, Cluster, and THEMIS, required at some point the appropriate qualitative transition in the empirical modeling tools. Classical empirical models, such as T96 and T02, used few custom-tailored modules to represent major magnetospheric current systems and simple data binning or loading-unloading inputs for their fitting with data and the subsequent applications. They have been replaced by more systematic expansions of the equatorial and field-aligned current contributions as well as by the advanced data-mining algorithms searching for events with the global activity parameters, such as the Sym-H index, similar to those at the time of interest, as is done in the model TS07D (Tsyganenko and Sitnov, 2007; Sitnov et al., 2008). The necessity to mine and fit data dynamically, with the individual subset of the database being used to reproduce the geomagnetic field pattern at every new moment in time, requires the corresponding transition in the use of the new empirical geomagnetic field models. It becomes more similar to runs-on-request offered by the Community Coordinated Modeling Center for many first principles MHD and kinetic codes. To provide this mode of operation for the TS07D model a new web-based modeling tool has been created and tested at the JHU/APL (http://geomag_field.jhuapl.edu/model/), and we discuss the first results of its performance testing and validation, including in-sample and out-of-sample modeling of a number of CME- and CIR-driven magnetic storms. We also report on the first tests of the forecasting version of the TS07D model, where the magnetospheric part of the macro-parameters involved in the data-binning process (Sym-H index and its trend parameter) are replaced by their solar wind-based analogs obtained using the Burton-McPherron-Russell approach.
Suitability of Synthetic Driving Profiles from Traffic Micro-Simulation for Real-World Energy Analysis: Preprint

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

Hou, Yunfei; Wood, Eric; Burton, Evan

A shift towards increased levels of driving automation is generally expected to result in improved safety and traffic congestion outcomes. However, little empirical data exists to estimate the impact that automated driving could have on energy consumption and greenhouse gas emissions. In the absence of empirical data on differences between drive cycles from present day vehicles (primarily operated by humans) and future vehicles (partially or fully operated by computers) one approach is to model both situations over identical traffic conditions. Such an exercise requires traffic micro-simulation to not only accurately model vehicle operation under high levels of automation, but alsomore » (and potentially more challenging) vehicle operation under present day human drivers. This work seeks to quantify the ability of a commercial traffic micro-simulation program to accurately model real-world drive cycles in vehicles operated primarily by humans in terms of driving speed, acceleration, and simulated fuel economy. Synthetic profiles from models of freeway and arterial facilities near Atlanta, Georgia, are compared to empirical data collected from real-world drivers on the same facilities. Empirical and synthetic drive cycles are then simulated in a powertrain efficiency model to enable comparison on the basis of fuel economy. Synthetic profiles from traffic micro-simulation were found to exhibit low levels of transient behavior relative to the empirical data. Even with these differences, the synthetic and empirical data in this study agree well in terms of driving speed and simulated fuel economy. The differences in transient behavior between simulated and empirical data suggest that larger stochastic contributions in traffic micro-simulation (relative to those present in the traffic micro-simulation tool used in this study) are required to fully capture the arbitrary elements of human driving. Interestingly, the lack of stochastic contributions from models of human drivers in this study did not result in a significant discrepancy between fuel economy simulations based on synthetic and empirical data; a finding with implications on the potential energy efficiency gains of automated vehicle technology.« less
a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images

NASA Astrophysics Data System (ADS)

Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei

2018-04-01

Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.
Process-based soil erodibility estimation for empirical water erosion models

USDA-ARS?s Scientific Manuscript database

A variety of modeling technologies exist for water erosion prediction each with specific parameters. It is of interest to scrutinize parameters of a particular model from the point of their compatibility with dataset of other models. In this research, functional relationships between soil erodibilit...
Energy risk in the arbitrage pricing model: an empirical and theoretical study

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

Bremer, M.A.

1986-01-01

This dissertation empirically explores the Arbitrage Pricing Theory in the context of energy risk for securities over the 1960s, 1970s, and early 1980s. Starting from a general multifactor pricing model, the paper develops a two factor model based on a market-like factor and an energy factor. This model is then tested on portfolios of securities grouped according to industrial classification using several econometric techniques designed to overcome some of the more serious estimation problems common to these models. The paper concludes that energy risk is priced in the 1970s and possibly even in the 1960s. Energy risk is found tomore » be priced in the sense that investors who hold assets subjected to energy risk are paid for this risk. The classic version of the Capital Asset Pricing Model which posits the market as the single priced factor is rejected in favor of the Arbitrage Pricing Theory or multi-beta versions of the Capital Asset Pricing Model. The study introduces some original econometric methodology to carry out empirical tests.« less
Evaluation of chiller modeling approaches and their usability for fault detection

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

Sreedharan, Priya

Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Several factors must be considered in model evaluation, including accuracy, training data requirements, calibration effort, generality, and computational requirements. All modeling approaches fall somewhere between pure first-principles models, and empirical models. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression air conditioning units, which are commonly known as chillers. Three different models were studied: two are based on first-principles and the third is empirical in nature. The first-principles models are themore » Gordon and Ng Universal Chiller model (2nd generation), and a modified version of the ASHRAE Primary Toolkit model, which are both based on first principles. The DOE-2 chiller model as implemented in CoolTools{trademark} was selected for the empirical category. The models were compared in terms of their ability to reproduce the observed performance of an older chiller operating in a commercial building, and a newer chiller in a laboratory. The DOE-2 and Gordon-Ng models were calibrated by linear regression, while a direct-search method was used to calibrate the Toolkit model. The ''CoolTools'' package contains a library of calibrated DOE-2 curves for a variety of different chillers, and was used to calibrate the building chiller to the DOE-2 model. All three models displayed similar levels of accuracy. Of the first principles models, the Gordon-Ng model has the advantage of being linear in the parameters, which allows more robust parameter estimation methods to be used and facilitates estimation of the uncertainty in the parameter values. The ASHRAE Toolkit Model may have advantages when refrigerant temperature measurements are also available. The DOE-2 model can be expected to have advantages when very limited data are available to calibrate the model, as long as one of the previously identified models in the CoolTools library matches the performance of the chiller in question.« less
Incorporating Video Modeling into a School-Based Intervention for Students with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Wilson, Kaitlyn P.

2013-01-01

Purpose: Video modeling is an intervention strategy that has been shown to be effective in improving the social and communication skills of students with autism spectrum disorders, or ASDs. The purpose of this tutorial is to outline empirically supported, step-by-step instructions for the use of video modeling by school-based speech-language…
Climate data induced uncertainty in model based estimations of terrestrial primary productivity

NASA Astrophysics Data System (ADS)

Wu, Z.; Ahlström, A.; Smith, B.; Ardö, J.; Eklundh, L.; Fensholt, R.; Lehsten, V.

2016-12-01

Models used to project global vegetation and carbon cycle differ in their estimates of historical fluxes and pools. These differences arise not only from differences between models but also from differences in the environmental and climatic data that forces the models. Here we investigate the role of uncertainties in historical climate data, encapsulated by a set of six historical climate datasets. We focus on terrestrial gross primary productivity (GPP) and analyze the results from a dynamic process-based vegetation model (LPJ-GUESS) forced by six different climate datasets and two empirical datasets of GPP (derived from flux towers and remote sensing). We find that the climate induced uncertainty, defined as the difference among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 33 Pg C yr-1 globally (19% of mean GPP). The uncertainty is partitioned into the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (the data range) and the sensitivity of the modeled GPP to the driver (the ecosystem sensitivity). The analysis is performed globally and stratified into five land cover classes. We find that the dynamic vegetation model overestimates GPP, compared to empirically based GPP data over most areas, except for the tropical region. Both the simulations and empirical estimates agree that the tropical region is a disproportionate source of uncertainty in GPP estimation. This is mainly caused by uncertainties in shortwave radiation forcing, of which climate data range contributes slightly higher uncertainty than ecosystem sensitivity to shortwave radiation. We also find that precipitation dominated the climate induced uncertainty over nearly half of terrestrial vegetated surfaces, which is mainly due to large ecosystem sensitivity to precipitation. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than ecosystem sensitivity. Our study highlights the need to better constrain tropical climate and demonstrate that uncertainty caused by climatic forcing data must be considered when comparing and evaluating model results and empirical datasets.

Modelling of project cash flow on construction projects in Malang city

NASA Astrophysics Data System (ADS)

Djatmiko, Bambang

2017-09-01

Contractors usually prepare a project cash flow (PCF) on construction projects. The flow of cash in and cash out within a construction project may vary depending on the owner, contract documents, and construction service providers who have their own authority. Other factors affecting the PCF are down payment, termyn, progress schedule, material schedule, equipment schedule, manpower schedules, and wages of workers and subcontractors. This study aims to describe the cash inflow and cash outflow based on the empirical data obtained from contractors, develop a PCF model based on Halpen & Woodhead's PCF model, and investigate whether or not there is a significant difference between the Halpen & Woodhead's PCF model and the empirical PCF model. Based on the researcher's observation, the PCF management has never been implemented by the contractors in Malang in serving their clients (owners). The research setting is in Malang City because physical development in all field and there are many new construction service providers. The findings in this current study are summarised as follows: 1) Cash in included current assets (20%), owner's down payment (20%), termyin I (5%-25%), termyin II (20%), termyin III (25%), termyin IV (25%) and retention (5%). Cash out included direct cost (65%), indirect cost (20%), and profit + informal cost(15%), 2)the construction work involving the empirical PCF model in this study was started with the funds obtained from DP or current assets and 3) The two models bear several similarities in the upward trends of direct cost, indirect cost, Pro Ic, progress billing, and S-curve. The difference between the two models is the occurrence of overdraft in the Halpen and Woodhead's PCF model only.
Empirical Study on Total Factor Productive Energy Efficiency in Beijing-Tianjin-Hebei Region-Analysis based on Malmquist Index and Window Model

NASA Astrophysics Data System (ADS)

Xu, Qiang; Ding, Shuai; An, Jingwen

2017-12-01

This paper studies the energy efficiency of Beijing-Tianjin-Hebei region and to finds out the trend of energy efficiency in order to improve the economic development quality of Beijing-Tianjin-Hebei region. Based on Malmquist index and window analysis model, this paper estimates the total factor energy efficiency in Beijing-Tianjin-Hebei region empirically by using panel data in this region from 1991 to 2014, and provides the corresponding political recommendations. The empirical result shows that, the total factor energy efficiency in Beijing-Tianjin-Hebei region increased from 1991 to 2014, mainly relies on advances in energy technology or innovation, and obvious regional differences in energy efficiency to exist. Throughout the window period of 24 years, the regional differences of energy efficiency in Beijing-Tianjin-Hebei region shrank. There has been significant convergent trend in energy efficiency after 2000, mainly depends on the diffusion and spillover of energy technologies.
Detection and localization of change points in temporal networks with the aid of stochastic block models

NASA Astrophysics Data System (ADS)

De Ridder, Simon; Vandermarliere, Benjamin; Ryckebusch, Jan

2016-11-01

A framework based on generalized hierarchical random graphs (GHRGs) for the detection of change points in the structure of temporal networks has recently been developed by Peel and Clauset (2015 Proc. 29th AAAI Conf. on Artificial Intelligence). We build on this methodology and extend it to also include the versatile stochastic block models (SBMs) as a parametric family for reconstructing the empirical networks. We use five different techniques for change point detection on prototypical temporal networks, including empirical and synthetic ones. We find that none of the considered methods can consistently outperform the others when it comes to detecting and locating the expected change points in empirical temporal networks. With respect to the precision and the recall of the results of the change points, we find that the method based on a degree-corrected SBM has better recall properties than other dedicated methods, especially for sparse networks and smaller sliding time window widths.
Design and experimentation of an empirical multistructure framework for accurate, sharp and reliable hydrological ensembles

NASA Astrophysics Data System (ADS)

Seiller, G.; Anctil, F.; Roy, R.

2017-09-01

This paper outlines the design and experimentation of an Empirical Multistructure Framework (EMF) for lumped conceptual hydrological modeling. This concept is inspired from modular frameworks, empirical model development, and multimodel applications, and encompasses the overproduce and select paradigm. The EMF concept aims to reduce subjectivity in conceptual hydrological modeling practice and includes model selection in the optimisation steps, reducing initial assumptions on the prior perception of the dominant rainfall-runoff transformation processes. EMF generates thousands of new modeling options from, for now, twelve parent models that share their functional components and parameters. Optimisation resorts to ensemble calibration, ranking and selection of individual child time series based on optimal bias and reliability trade-offs, as well as accuracy and sharpness improvement of the ensemble. Results on 37 snow-dominated Canadian catchments and 20 climatically-diversified American catchments reveal the excellent potential of the EMF in generating new individual model alternatives, with high respective performance values, that may be pooled efficiently into ensembles of seven to sixty constitutive members, with low bias and high accuracy, sharpness, and reliability. A group of 1446 new models is highlighted to offer good potential on other catchments or applications, based on their individual and collective interests. An analysis of the preferred functional components reveals the importance of the production and total flow elements. Overall, results from this research confirm the added value of ensemble and flexible approaches for hydrological applications, especially in uncertain contexts, and open up new modeling possibilities.
Empirical Investigation of Critical Transitions in Paleoclimate

NASA Astrophysics Data System (ADS)

Loskutov, E. M.; Mukhin, D.; Gavrilov, A.; Feigin, A.

2016-12-01

In this work we apply a new empirical method for the analysis of complex spatially distributed systems to the analysis of paleoclimate data. The method consists of two general parts: (i) revealing the optimal phase-space variables and (ii) construction the empirical prognostic model by observed time series. The method of phase space variables construction based on the data decomposition into nonlinear dynamical modes which was successfully applied to global SST field and allowed clearly separate time scales and reveal climate shift in the observed data interval [1]. The second part, the Bayesian approach to optimal evolution operator reconstruction by time series is based on representation of evolution operator in the form of nonlinear stochastic function represented by artificial neural networks [2,3]. In this work we are focused on the investigation of critical transitions - the abrupt changes in climate dynamics - in match longer time scale process. It is well known that there were number of critical transitions on different time scales in the past. In this work, we demonstrate the first results of applying our empirical methods to analysis of paleoclimate variability. In particular, we discuss the possibility of detecting, identifying and prediction such critical transitions by means of nonlinear empirical modeling using the paleoclimate record time series. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep155102. Ya. I. Molkov, D. N. Mukhin, E. M. Loskutov, A.M. Feigin, (2012) : Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.3. Mukhin, D., Kondrashov, D., Loskutov, E., Gavrilov, A., Feigin, A., & Ghil, M. (2015). Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models. Journal of Climate, 28(5), 1962-1976. http://doi.org/10.1175/JCLI-D-14-00240.1
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.
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.
The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

ERIC Educational Resources Information Center

Hali, Nur Ihsan

2017-01-01

This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by…
Toward a Predictive Model of Arctic Coastal Retreat in a Warming Climate, Beaufort Sea, Alaska

DTIC Science & Technology

2011-09-30

level by waves and surge and tide. Melt rate is governed by an empirically based iceberg melting algorithm that includes explicitly the roles of wave...Thermal erosion of a permafrost coastline: Improving process-based models using time-lapse photography, Arctic Alpine Antarctic Research 43(3): 474
Movement behavior explains genetic differentiation in American black bears

Treesearch

Samuel A Cushman; Jesse S. Lewis

2010-01-01

Individual-based landscape genetic analyses provide empirically based models of gene flow. It would be valuable to verify the predictions of these models using independent data of a different type. Analyses using different data sources that produce consistent results provide strong support for the generality of the findings. Mating and dispersal movements are the...
Defining Strategic and Excellence Bases for the Development of Portuguese Higher Education

ERIC Educational Resources Information Center

Rosa, Maria Joao; Saraiva, Pedro M.; Diz, Henrique

2005-01-01

A self-assessment model was developed for the Portuguese higher education institutions (HEIs) which was based on an empirical study aiming at better understanding their strategic and quality management and innovation practices and tools and on the study of several quality assessment models developed both for HEIs and business organisations. From…
Integrating the Demonstration Orientation and Standards-Based Models of Achievement Goal Theory

ERIC Educational Resources Information Center

Wynne, Heather Marie

2014-01-01

Achievement goal theory and thus, the empirical measures stemming from the research, are currently divided on two conceptual approaches, namely the reason versus aims-based models of achievement goals. The factor structure and predictive utility of goal constructs from the Patterns of Adaptive Learning Strategies (PALS) and the latest two versions…
Modeling dynamic beta-gamma polymorphic transition in Tin

NASA Astrophysics Data System (ADS)

Chauvin, Camille; Montheillet, Frank; Petit, Jacques; CEA Gramat Collaboration; EMSE Collaboration

2015-06-01

Solid-solid phase transitions in metals have been studied by shock waves techniques for many decades. Recent experiments have investigated the transition during isentropic compression experiments and shock-wave compression and have highlighted the strong influence of the loading rate on the transition. Complementary data obtained with velocity and temperature measurements around the polymorphic transition beta-gamma of Tin on gas gun experiments have displayed the importance of the kinetics of the transition. But, even though this phenomenon is known, modeling the kinetic remains complex and based on empirical formulations. A multiphase EOS is available in our 1D Lagrangian code Unidim. We propose to present the influence of various kinetic laws (either empirical or involving nucleation and growth mechanisms) and their parameters (Gibbs free energy, temperature, pressure) on the transformation rate. We compare experimental and calculated velocities and temperature profiles and we underline the effects of the empirical parameters of these models.
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.
Fuel consumption modeling in support of ATM environmental decision-making

DOT National Transportation Integrated Search

2009-07-01

The FAA has recently updated the airport terminal : area fuel consumption methods used in its environmental models. : These methods are based on fitting manufacturers fuel : consumption data to empirical equations. The new fuel : consumption metho...
Modeling Demic and Cultural Diffusion: An Introduction.

PubMed

Fort, Joaquim; Crema, Enrico R; Madella, Marco

2015-07-01

Identifying the processes by which human cultures spread across different populations is one of the most topical objectives shared among different fields of study. Seminal works have analyzed a variety of data and attempted to determine whether empirically observed patterns are the result of demic and/or cultural diffusion. This special issue collects articles exploring several themes (from modes of cultural transmission to drivers of dispersal mechanisms) and contexts (from the Neolithic in Europe to the spread of computer programming languages), which offer new insights that will augment the theoretical and empirical basis for the study of demic and cultural diffusion. In this introduction we outline the state of art in the modeling of these processes, briefly discuss the pros and cons of two of the most commonly used frameworks (equation-based models and agent-based models), and summarize the significance of each article in this special issue.
Urban tree growth modeling

Treesearch

E. Gregory McPherson; Paula J. Peper

2012-01-01

This paper describes three long-term tree growth studies conducted to evaluate tree performance because repeated measurements of the same trees produce critical data for growth model calibration and validation. Several empirical and process-based approaches to modeling tree growth are reviewed. Modeling is more advanced in the fields of forestry and...
Consumer psychology: categorization, inferences, affect, and persuasion.

PubMed

Loken, Barbara

2006-01-01

This chapter reviews research on consumer psychology with emphasis on the topics of categorization, inferences, affect, and persuasion. The chapter reviews theory-based empirical research during the period 1994-2004. Research on categorization includes empirical research on brand categories, goals as organizing frameworks and motivational bases for judgments, and self-based processing. Research on inferences includes numerous types of inferences that are cognitively and/or experienced based. Research on affect includes the effects of mood on processing and cognitive and noncognitive bases for attitudes and intentions. Research on persuasion focuses heavily on the moderating role of elaboration and dual-process models, and includes research on attitude strength responses, advertising responses, and negative versus positive evaluative dimensions.
V and V Efforts of Auroral Precipitation Models: Preliminary Results

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Kuznetsova, Masha; Rastaetter, Lutz; Hesse, Michael

2011-01-01

Auroral precipitation models have been valuable both in terms of space weather applications and space science research. Yet very limited testing has been performed regarding model performance. A variety of auroral models are available, including empirical models that are parameterized by geomagnetic indices or upstream solar wind conditions, now casting models that are based on satellite observations, or those derived from physics-based, coupled global models. In this presentation, we will show our preliminary results regarding V&V efforts of some of the models.
Mental workload prediction based on attentional resource allocation and information processing.

PubMed

Xiao, Xu; Wanyan, Xiaoru; Zhuang, Damin

2015-01-01

Mental workload is an important component in complex human-machine systems. The limited applicability of empirical workload measures produces the need for workload modeling and prediction methods. In the present study, a mental workload prediction model is built on the basis of attentional resource allocation and information processing to ensure pilots' accuracy and speed in understanding large amounts of flight information on the cockpit display interface. Validation with an empirical study of an abnormal attitude recovery task showed that this model's prediction of mental workload highly correlated with experimental results. This mental workload prediction model provides a new tool for optimizing human factors interface design and reducing human errors.

Relative performance of empirical and physical models in assessing the seasonal and annual glacier surface mass balance of Saint-Sorlin Glacier (French Alps)

NASA Astrophysics Data System (ADS)

Réveillet, Marion; Six, Delphine; Vincent, Christian; Rabatel, Antoine; Dumont, Marie; Lafaysse, Matthieu; Morin, Samuel; Vionnet, Vincent; Litt, Maxime

2018-04-01

This study focuses on simulations of the seasonal and annual surface mass balance (SMB) of Saint-Sorlin Glacier (French Alps) for the period 1996-2015 using the detailed SURFEX/ISBA-Crocus snowpack model. The model is forced by SAFRAN meteorological reanalysis data, adjusted with automatic weather station (AWS) measurements to ensure that simulations of all the energy balance components, in particular turbulent fluxes, are accurately represented with respect to the measured energy balance. Results indicate good model performance for the simulation of summer SMB when using meteorological forcing adjusted with in situ measurements. Model performance however strongly decreases without in situ meteorological measurements. The sensitivity of the model to meteorological forcing indicates a strong sensitivity to wind speed, higher than the sensitivity to ice albedo. Compared to an empirical approach, the model exhibited better performance for simulations of snow and firn melting in the accumulation area and similar performance in the ablation area when forced with meteorological data adjusted with nearby AWS measurements. When such measurements were not available close to the glacier, the empirical model performed better. Our results suggest that simulations of the evolution of future mass balance using an energy balance model require very accurate meteorological data. Given the uncertainties in the temporal evolution of the relevant meteorological variables and glacier surface properties in the future, empirical approaches based on temperature and precipitation could be more appropriate for simulations of glaciers in the future.
Usage Intention Framework Model: A Fuzzy Logic Interpretation of the Classical Utaut Model

ERIC Educational Resources Information Center

Sandaire, Johnny

2009-01-01

A fuzzy conjoint analysis (FCA: Turksen, 1992) model for enhancing management decision in the technology adoption domain was implemented as an extension to the UTAUT model (Venkatesh, Morris, Davis, & Davis, 2003). Additionally, a UTAUT-based Usage Intention Framework Model (UIFM) introduced a closed-loop feedback system. The empirical evidence…
An investigation of the mentalization-based model of borderline pathology in adolescents.

PubMed

Quek, Jeremy; Bennett, Clair; Melvin, Glenn A; Saeedi, Naysun; Gordon, Michael S; Newman, Louise K

2018-07-01

According to mentalization-based theory, transgenerational transmission of mentalization from caregiver to offspring is implicated in the pathogenesis of borderline personality disorder (BPD). Recent research has demonstrated an association between hypermentalizing (excessive, inaccurate mental state reasoning) and BPD, indicating the particular relevance of this form of mentalizing dysfunction to the transgenerational mentalization-based model. As yet, no study has empirically assessed a transgenerational mentalization-based model of BPD. The current study sought firstly to test the mentalization-based model, and additionally, to determine the form of mentalizing dysfunction in caregivers (e.g., hypo- or hypermentalizing) most relevant to a hypermentalizing model of BPD. Participants were a mixed sample of adolescents with BPD and a sample of non-clinical adolescents, and their respective primary caregivers (n = 102; 51 dyads). Using an ecologically valid measure of mentalization, mediational analyses were conducted to examine the relationships between caregiver mentalizing, adolescent mentalizing, and adolescent borderline features. Findings demonstrated that adolescent mentalization mediated the effect of caregiver mentalization on adolescent borderline personality pathology. Furthermore, results indicated that hypomentalizing in caregivers was related to adolescent borderline personality pathology via an effect on adolescent hypermentalizing. Results provide empirical support for the mentalization-based model of BPD, and suggest the indirect influence of caregiver mentalization on adolescent borderline psychopathology. Results further indicate the relevance of caregiver hypomentalizing to a hypermentalizing model of BPD. Copyright © 2018 Elsevier Inc. All rights reserved.
Empirically Based Leadership: Integrating the Science of Psychology in Building a Better Leadership Model

DTIC Science & Technology

2013-02-01

outcomes related to leader performance. Another significant area of interest within the empirical literature is emotional intelligence (EI), which...officers’ overall emotional intelligence and effectiveness as a leader. More specifically, when analyzing the subscales, the researchers detected...commonly asso- ciated qualities like mental abilities or emotional intelligence .17 Similar results have been obtained in other studies with a variety
Estimating habitat carrying capacity for migrating and wintering waterfowl: Considerations, pitfalls and improvements

USGS Publications Warehouse

Williams, Christopher; Dugger, Bruce D.; Brasher, Michael G.; Coluccy, John M.; Cramer, Dane M.; Eadie, John M.; Gray, Matthew J.; Hagy, Heath M.; Livolsi, Mark; McWilliams, Scott R.; Petrie, Matthew; Soulliere, Gregory J.; Tirpak, John M.; Webb, Elisabeth B.

2014-01-01

Population-based habitat conservation planning for migrating and wintering waterfowl in North America is carried out by habitat Joint Venture (JV) initiatives and is based on the premise that food can limit demography (i.e. food limitation hypothesis). Consequently, planners use bioenergetic models to estimate food (energy) availability and population-level energy demands at appropriate spatial and temporal scales, and translate these values into regional habitat objectives. While simple in principle, there are both empirical and theoretical challenges associated with calculating energy supply and demand including: 1) estimating food availability, 2) estimating the energy content of specific foods, 3) extrapolating site-specific estimates of food availability to landscapes for focal species, 4) applicability of estimates from a single species to other species, 5) estimating resting metabolic rate, 6) estimating cost of daily behaviours, and 7) estimating costs of thermoregulation or tissue synthesis. Most models being used are daily ration models (DRMs) whose set of simplifying assumptions are well established and whose use is widely accepted and feasible given the empirical data available to populate such models. However, DRMs do not link habitat objectives to metrics of ultimate ecological importance such as individual body condition or survival, and largely only consider food-producing habitats. Agent-based models (ABMs) provide a possible alternative for creating more biologically realistic models under some conditions; however, ABMs require different types of empirical inputs, many of which have yet to be estimated for key North American waterfowl. Decisions about how JVs can best proceed with habitat conservation would benefit from the use of sensitivity analyses that could identify the empirical and theoretical uncertainties that have the greatest influence on efforts to estimate habitat carrying capacity. Development of ABMs at restricted, yet biologically relevant spatial scales, followed by comparisons of their outputs to those generated from more simplistic, deterministic models can provide a means of assessing degrees of dissimilarity in how alternative models describe desired landscape conditions for migrating and wintering waterfowl.
Performance Analysis of Transposition Models Simulating Solar Radiation on Inclined Surfaces

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

Xie, Yu; Sengupta, Manajit

2016-06-02

Transposition models have been widely used in the solar energy industry to simulate solar radiation on inclined photovoltaic panels. Following numerous studies comparing the performance of transposition models, this work aims to understand the quantitative uncertainty in state-of-the-art transposition models and the sources leading to the uncertainty. Our results show significant differences between two highly used isotropic transposition models, with one substantially underestimating the diffuse plane-of-array irradiances when diffuse radiation is perfectly isotropic. In the empirical transposition models, the selection of the empirical coefficients and land surface albedo can both result in uncertainty in the output. This study can bemore » used as a guide for the future development of physics-based transposition models and evaluations of system performance.« less
A comparison of three radiation models for the calculation of nozzle arcs

NASA Astrophysics Data System (ADS)

Dixon, C. M.; Yan, J. D.; Fang, M. T. C.

2004-12-01

Three radiation models, the semi-empirical model based on net emission coefficients (Zhang et al 1987 J. Phys. D: Appl. Phys. 20 386-79), the five-band P1 model (Eby et al 1998 J. Phys. D: Appl. Phys. 31 1578-88), and the method of partial characteristics (Aubrecht and Lowke 1994 J. Phys. D: Appl.Phys. 27 2066-73, Sevast'yanenko 1979 J. Eng. Phys. 36 138-48), are used to calculate the radiation transfer in an SF6 nozzle arc. The temperature distributions computed by the three models are compared with the measurements of Leseberg and Pietsch (1981 Proc. 4th Int. Symp. on Switching Arc Phenomena (Lodz, Poland) pp 236-40) and Leseberg (1982 PhD Thesis RWTH Aachen, Germany). It has been found that all three models give similar distributions of radiation loss per unit time and volume. For arcs burning in axially dominated flow, such as arcs in nozzle flow, the semi-empirical model and the P1 model give accurate predictions when compared with experimental results. The prediction by the method of partial characteristics is poorest. The computational cost is the lowest for the semi-empirical model.
Systematics of capture and fusion dynamics in heavy-ion collisions

NASA Astrophysics Data System (ADS)

Wang, Bing; Wen, Kai; Zhao, Wei-Juan; Zhao, En-Guang; Zhou, Shan-Gui

2017-03-01

We perform a systematic study of capture excitation functions by using an empirical coupled-channel (ECC) model. In this model, a barrier distribution is used to take effectively into account the effects of couplings between the relative motion and intrinsic degrees of freedom. The shape of the barrier distribution is of an asymmetric Gaussian form. The effect of neutron transfer channels is also included in the barrier distribution. Based on the interaction potential between the projectile and the target, empirical formulas are proposed to determine the parameters of the barrier distribution. Theoretical estimates for barrier distributions and calculated capture cross sections together with experimental cross sections of 220 reaction systems with 182 ⩽ZPZT ⩽ 1640 are tabulated. The results show that the ECC model together with the empirical formulas for parameters of the barrier distribution work quite well in the energy region around the Coulomb barrier. This ECC model can provide prediction of capture cross sections for the synthesis of superheavy nuclei as well as valuable information on capture and fusion dynamics.
Benchmarking test of empirical root water uptake models

NASA Astrophysics Data System (ADS)

dos Santos, Marcos Alex; de Jong van Lier, Quirijn; van Dam, Jos C.; Freire Bezerra, Andre Herman

2017-01-01

Detailed physical models describing root water uptake (RWU) are an important tool for the prediction of RWU and crop transpiration, but the hydraulic parameters involved are hardly ever available, making them less attractive for many studies. Empirical models are more readily used because of their simplicity and the associated lower data requirements. The purpose of this study is to evaluate the capability of some empirical models to mimic the RWU distribution under varying environmental conditions predicted from numerical simulations with a detailed physical model. A review of some empirical models used as sub-models in ecohydrological models is presented, and alternative empirical RWU models are proposed. All these empirical models are analogous to the standard Feddes model, but differ in how RWU is partitioned over depth or how the transpiration reduction function is defined. The parameters of the empirical models are determined by inverse modelling of simulated depth-dependent RWU. The performance of the empirical models and their optimized empirical parameters depends on the scenario. The standard empirical Feddes model only performs well in scenarios with low root length density R, i.e. for scenarios with low RWU compensation. For medium and high R, the Feddes RWU model cannot mimic properly the root uptake dynamics as predicted by the physical model. The Jarvis RWU model in combination with the Feddes reduction function (JMf) only provides good predictions for low and medium R scenarios. For high R, it cannot mimic the uptake patterns predicted by the physical model. Incorporating a newly proposed reduction function into the Jarvis model improved RWU predictions. Regarding the ability of the models to predict plant transpiration, all models accounting for compensation show good performance. The Akaike information criterion (AIC) indicates that the Jarvis (2010) model (JMII), with no empirical parameters to be estimated, is the best model. The proposed models are better in predicting RWU patterns similar to the physical model. The statistical indices point to them as the best alternatives for mimicking RWU predictions of the physical model.
Dementia and well-being: A conceptual framework based on Tom Kitwood's model of needs.

PubMed

Kaufmann, Elke G; Engel, Sabine A

2016-07-01

The topic of well-being is becoming increasingly significant as a key outcome measure in dementia care. Previous work on personhood of individuals with dementia suggests that their subjective well-being can be described in terms of comfort, inclusion, identity, occupation and attachment The study aimed to examine Tom Kitwood's model of psychological needs and well-being in dementia based on the self-report of individuals with moderate or severe dementia and to differentiate and elaborate this model in the light of the empirical qualitative data. Nineteen inhabitants of a special long-term care unit were interviewed using a semi-structured interview. Data were analysed using content analysis. Thirty components within Kitwood's model have been identified. A conceptual framework of subjective well-being in dementia was developed based on a theoretical background. The study was able to find indications that Kitwood's model has empirical relevance. Nevertheless, it requires to be extended by the domain agency. Furthermore, the study suggests that individuals with dementia are important informants of their subjective well-being. © The Author(s) 2014.
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.
An Empirical Model of the Variation of the Solar Lyman-α Spectral Irradiance

NASA Astrophysics Data System (ADS)

Kretzschmar, Matthieu; Snow, Martin; Curdt, Werner

2018-03-01

We propose a simple model that computes the spectral profile of the solar irradiance in the hydrogen Lyman alpha line, H Ly-α (121.567 nm), from 1947 to present. Such a model is relevant for the study of many astronomical environments, from planetary atmospheres to interplanetary medium. This empirical model is based on the SOlar Heliospheric Observatory/Solar Ultraviolet Measurement of Emitted Radiation observations of the Ly-α irradiance over solar cycle 23 and the Ly-α disk-integrated irradiance composite. The model reproduces the temporal variability of the spectral profile and matches the independent SOlar Radiation and Climate Experiment/SOLar-STellar Irradiance Comparison Experiment spectral observations from 2003 to 2007 with an accuracy better than 10%.
Variance-based selection may explain general mating patterns in social insects.

PubMed

Rueppell, Olav; Johnson, Nels; Rychtár, Jan

2008-06-23

Female mating frequency is one of the key parameters of social insect evolution. Several hypotheses have been suggested to explain multiple mating and considerable empirical research has led to conflicting results. Building on several earlier analyses, we present a simple general model that links the number of queen matings to variance in colony performance and this variance to average colony fitness. The model predicts selection for multiple mating if the average colony succeeds in a focal task, and selection for single mating if the average colony fails, irrespective of the proximate mechanism that links genetic diversity to colony fitness. Empirical support comes from interspecific comparisons, e.g. between the bee genera Apis and Bombus, and from data on several ant species, but more comprehensive empirical tests are needed.
Modeling the risk of water pollution by pesticides from imbalanced data.

PubMed

Trajanov, Aneta; Kuzmanovski, Vladimir; Real, Benoit; Perreau, Jonathan Marks; Džeroski, Sašo; Debeljak, Marko

2018-04-30

The pollution of ground and surface waters with pesticides is a serious ecological issue that requires adequate treatment. Most of the existing water pollution models are mechanistic mathematical models. While they have made a significant contribution to understanding the transfer processes, they face the problem of validation because of their complexity, the user subjectivity in their parameterization, and the lack of empirical data for validation. In addition, the data describing water pollution with pesticides are, in most cases, very imbalanced. This is due to strict regulations for pesticide applications, which lead to only a few pollution events. In this study, we propose the use of data mining to build models for assessing the risk of water pollution by pesticides in field-drained outflow water. Unlike the mechanistic models, the models generated by data mining are based on easily obtainable empirical data, while the parameterization of the models is not influenced by the subjectivity of ecological modelers. We used empirical data from field trials at the La Jaillière experimental site in France and applied the random forests algorithm to build predictive models that predict "risky" and "not-risky" pesticide application events. To address the problems of the imbalanced classes in the data, cost-sensitive learning and different measures of predictive performance were used. Despite the high imbalance between risky and not-risky application events, we managed to build predictive models that make reliable predictions. The proposed modeling approach can be easily applied to other ecological modeling problems where we encounter empirical data with highly imbalanced classes.
New robust statistical procedures for the polytomous logistic regression models.

PubMed

Castilla, Elena; Ghosh, Abhik; Martin, Nirian; Pardo, Leandro

2018-05-17

This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic regression model. Based on these estimators, a family of Wald-type test statistics for linear hypotheses is introduced. Robustness properties of both the proposed estimators and the test statistics are theoretically studied through the classical influence function analysis. Appropriate real life examples are presented to justify the requirement of suitable robust statistical procedures in place of the likelihood based inference for the polytomous logistic regression model. The validity of the theoretical results established in the article are further confirmed empirically through suitable simulation studies. Finally, an approach for the data-driven selection of the robustness tuning parameter is proposed with empirical justifications. © 2018, The International Biometric Society.
On the need and use of models to explore the role of economic confidence:a survey.

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

Sprigg, James A.; Paez, Paul J.; Hand, Michael S.

2005-04-01

Empirical studies suggest that consumption is more sensitive to current income than suggested under the permanent income hypothesis, which raises questions regarding expectations for future income, risk aversion, and the role of economic confidence measures. This report surveys a body of fundamental economic literature as well as burgeoning computational modeling methods to support efforts to better anticipate cascading economic responses to terrorist threats and attacks. This is a three part survey to support the incorporation of models of economic confidence into agent-based microeconomic simulations. We first review broad underlying economic principles related to this topic. We then review the economicmore » principle of confidence and related empirical studies. Finally, we provide a brief survey of efforts and publications related to agent-based economic simulation.« less
Merger of three modeling approaches to assess potential effects of climate change on trees in the eastern United States

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew P. Peters

2010-01-01

Climate change will likely cause impacts that are species specific and significant; modeling is critical to better understand potential changes in suitable habitat. We use empirical, abundance-based habitat models utilizing decision tree-based ensemble methods to explore potential changes of 134 tree species habitats in the eastern United States (http://www.nrs.fs.fed....
An Empirical and Qualitative Study of the Strategic Planning Process of a Higher Education Institution

ERIC Educational Resources Information Center

Aleong, Chandra

2007-01-01

This paper discusses whether there are differences in performance based on differences in strategy. First, an attempt was made to determine whether the institution had a strategy, and if so, did it follow a particular model. Major models of strategy are the industry analysis approach, the resource based view or the RBV model and the more recent,…
A model of therapist competencies for the empirically supported interpersonal psychotherapy for adolescent depression.

PubMed

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

2012-06-01

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 training must be generated and provided. However, before such training can be developed, a good understanding of the therapist competencies needed to implement these ESTs is required. Sburlati et al. (Clin Child Fam Psychol Rev 14:89-109, 2011) developed a model of therapist competencies for implementing CBT using the well-established Delphi technique. Given that IPT-A differs considerably to CBT, the current study aims to develop a model of therapist competencies for the implementation of IPT-A using a similar procedure as that applied in Sburlati et al. (Clin Child Fam Psychol Rev 14:89-109, 2011). This method involved: (1) identifying and reviewing an empirically supported IPT-A approach, (2) extracting therapist competencies required for the implementation of IPT-A, (3) consulting with a panel of IPT-A experts to generate an overall model of therapist competencies, and (4) validating the overall model with the IPT-A manual author. The resultant model offers an empirically derived set of competencies necessary for effectively treating adolescent depression using IPT-A and has wide implications for the development of therapist training, competence assessment measures, and evidence-based practice guidelines. This model, therefore, provides an empirical framework for the development of dissemination and implementation programs aimed at ensuring that adolescents with depression receive effective care in RCP settings. Key similarities and differences between CBT and IPT-A, and the therapist competencies required for implementing these treatments, are also highlighted throughout this article.
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...

Estimating wildfire behavior and effects

Treesearch

Frank A. Albini

1976-01-01

This paper presents a brief survey of the research literature on wildfire behavior and effects and assembles formulae and graphical computation aids based on selected theoretical and empirical models. The uses of mathematical fire behavior models are discussed, and the general capabilities and limitations of currently available models are outlined.
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
The ecological module of BOATS-1.0: a bioenergetically-constrained model of marine upper trophic levels suitable for studies of fisheries and ocean biogeochemistry

NASA Astrophysics Data System (ADS)

Carozza, D. A.; Bianchi, D.; Galbraith, E. D.

2015-12-01

Environmental change and the exploitation of marine resources have had profound impacts on marine communities, with potential implications for ocean biogeochemistry and food security. In order to study such global-scale problems, it is helpful to have computationally efficient numerical models that predict the first-order features of fish biomass production as a function of the environment, based on empirical and mechanistic understandings of marine ecosystems. Here we describe the ecological module of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model, which takes an Earth-system approach to modeling fish biomass at the global scale. The ecological model is designed to be used on an Earth System model grid, and determines size spectra of fish biomass by explicitly resolving life history as a function of local temperature and net primary production. Biomass production is limited by the availability of photosynthetic energy to upper trophic levels, following empirical trophic efficiency scalings, and by well-established empirical temperature-dependent growth rates. Natural mortality is calculated using an empirical size-based relationship, while reproduction and recruitment depend on both the food availability to larvae from net primary production and the production of eggs by mature adult fish. We describe predicted biomass spectra and compare them to observations, and conduct a sensitivity study to determine how the change as a function of net primary production and temperature. The model relies on a limited number of parameters compared to similar modeling efforts, while retaining realistic representations of biological and ecological processes, and is computationally efficient, allowing extensive parameter-space analyses even when implemented globally. As such, it enables the exploration of the linkages between ocean biogeochemistry, climate, and upper trophic levels at the global scale, as well as a representation of fish biomass for idealized studies of fisheries.
The ecological module of BOATS-1.0: a bioenergetically constrained model of marine upper trophic levels suitable for studies of fisheries and ocean biogeochemistry

NASA Astrophysics Data System (ADS)

Carozza, David Anthony; Bianchi, Daniele; Galbraith, Eric Douglas

2016-04-01

Environmental change and the exploitation of marine resources have had profound impacts on marine communities, with potential implications for ocean biogeochemistry and food security. In order to study such global-scale problems, it is helpful to have computationally efficient numerical models that predict the first-order features of fish biomass production as a function of the environment, based on empirical and mechanistic understandings of marine ecosystems. Here we describe the ecological module of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model, which takes an Earth-system approach to modelling fish biomass at the global scale. The ecological model is designed to be used on an Earth-system model grid, and determines size spectra of fish biomass by explicitly resolving life history as a function of local temperature and net primary production. Biomass production is limited by the availability of photosynthetic energy to upper trophic levels, following empirical trophic efficiency scalings, and by well-established empirical temperature-dependent growth rates. Natural mortality is calculated using an empirical size-based relationship, while reproduction and recruitment depend on both the food availability to larvae from net primary production and the production of eggs by mature adult fish. We describe predicted biomass spectra and compare them to observations, and conduct a sensitivity study to determine how they change as a function of net primary production and temperature. The model relies on a limited number of parameters compared to similar modelling efforts, while retaining reasonably realistic representations of biological and ecological processes, and is computationally efficient, allowing extensive parameter-space analyses even when implemented globally. As such, it enables the exploration of the linkages between ocean biogeochemistry, climate, and upper trophic levels at the global scale, as well as a representation of fish biomass for idealized studies of fisheries.
A Conceptual Application of Attachment Theory and Research to the Social Work Student-Field Instructor Supervisory Relationship

ERIC Educational Resources Information Center

Bennett, Susanne; Saks, Loretta Vitale

2006-01-01

This article conceptualizes an attachment-based model of the student-field instructor relationship, based on empirical research concerning internal working models of attachment, which continue into adulthood and serve as templates for life-long relating. Supportive relationships within a noncritical context are salient for effective supervision;…
Pathways to Children's Academic Performance and Prosocial Behaviour: Roles of Physical Health Status, Environmental, Family, and Child Factors

ERIC Educational Resources Information Center

King, Gillian; McDougall, Janette; DeWit, David; Hong, Sungjin; Miller, Linda; Offord, David; Meyer, Katherine; LaPorta, John

2005-01-01

The objective of this article is to examine the pathways by which children's physical health status, environmental, family, and child factors affect children's academic performance and prosocial behaviour, using a theoretically-based and empirically-based model of competence development. The model proposes that 3 types of relational processes,…
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.
Lithium-ion battery models: a comparative study and a model-based powerline communication

NASA Astrophysics Data System (ADS)

Saidani, Fida; Hutter, Franz X.; Scurtu, Rares-George; Braunwarth, Wolfgang; Burghartz, Joachim N.

2017-09-01

In this work, various Lithium-ion (Li-ion) battery models are evaluated according to their accuracy, complexity and physical interpretability. An initial classification into physical, empirical and abstract models is introduced. Also known as white, black and grey boxes, respectively, the nature and characteristics of these model types are compared. Since the Li-ion battery cell is a thermo-electro-chemical system, the models are either in the thermal or in the electrochemical state-space. Physical models attempt to capture key features of the physical process inside the cell. Empirical models describe the system with empirical parameters offering poor analytical, whereas abstract models provide an alternative representation. In addition, a model selection guideline is proposed based on applications and design requirements. A complex model with a detailed analytical insight is of use for battery designers but impractical for real-time applications and in situ diagnosis. In automotive applications, an abstract model reproducing the battery behavior in an equivalent but more practical form, mainly as an equivalent circuit diagram, is recommended for the purpose of battery management. As a general rule, a trade-off should be reached between the high fidelity and the computational feasibility. Especially if the model is embedded in a real-time monitoring unit such as a microprocessor or a FPGA, the calculation time and memory requirements rise dramatically with a higher number of parameters. Moreover, examples of equivalent circuit models of Lithium-ion batteries are covered. Equivalent circuit topologies are introduced and compared according to the previously introduced criteria. An experimental sequence to model a 20 Ah cell is presented and the results are used for the purposes of powerline communication.
How much detail is needed in modeling a transcranial magnetic stimulation figure-8 coil: Measurements and brain simulations

PubMed Central

Mandija, Stefano; Sommer, Iris E. C.; van den Berg, Cornelis A. T.; Neggers, Sebastiaan F. W.

2017-01-01

Background Despite TMS wide adoption, its spatial and temporal patterns of neuronal effects are not well understood. Although progress has been made in predicting induced currents in the brain using realistic finite element models (FEM), there is little consensus on how a magnetic field of a typical TMS coil should be modeled. Empirical validation of such models is limited and subject to several limitations. Methods We evaluate and empirically validate models of a figure-of-eight TMS coil that are commonly used in published modeling studies, of increasing complexity: simple circular coil model; coil with in-plane spiral winding turns; and finally one with stacked spiral winding turns. We will assess the electric fields induced by all 3 coil models in the motor cortex using a computer FEM model. Biot-Savart models of discretized wires were used to approximate the 3 coil models of increasing complexity. We use a tailored MR based phase mapping technique to get a full 3D validation of the incident magnetic field induced in a cylindrical phantom by our TMS coil. FEM based simulations on a meshed 3D brain model consisting of five tissues types were performed, using two orthogonal coil orientations. Results Substantial differences in the induced currents are observed, both theoretically and empirically, between highly idealized coils and coils with correctly modeled spiral winding turns. Thickness of the coil winding turns affect minimally the induced electric field, and it does not influence the predicted activation. Conclusion TMS coil models used in FEM simulations should include in-plane coil geometry in order to make reliable predictions of the incident field. Modeling the in-plane coil geometry is important to correctly simulate the induced electric field and to correctly make reliable predictions of neuronal activation PMID:28640923
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.
Is Dysfunctional Use of the Mobile Phone a Behavioural Addiction? Confronting Symptom-Based Versus Process-Based Approaches.

PubMed

Billieux, Joël; Philippot, Pierre; Schmid, Cécile; Maurage, Pierre; De Mol, Jan; Van der Linden, Martial

2015-01-01

Dysfunctional use of the mobile phone has often been conceptualized as a 'behavioural addiction' that shares most features with drug addictions. In the current article, we challenge the clinical utility of the addiction model as applied to mobile phone overuse. We describe the case of a woman who overuses her mobile phone from two distinct approaches: (1) a symptom-based categorical approach inspired from the addiction model of dysfunctional mobile phone use and (2) a process-based approach resulting from an idiosyncratic clinical case conceptualization. In the case depicted here, the addiction model was shown to lead to standardized and non-relevant treatment, whereas the clinical case conceptualization allowed identification of specific psychological processes that can be targeted with specific, empirically based psychological interventions. This finding highlights that conceptualizing excessive behaviours (e.g., gambling and sex) within the addiction model can be a simplification of an individual's psychological functioning, offering only limited clinical relevance. The addiction model, applied to excessive behaviours (e.g., gambling, sex and Internet-related activities) may lead to non-relevant standardized treatments. Clinical case conceptualization allowed identification of specific psychological processes that can be targeted with specific empirically based psychological interventions. The biomedical model might lead to the simplification of an individual's psychological functioning with limited clinical relevance. Copyright © 2014 John Wiley & Sons, Ltd.
Teachers' Temporary Support and Worked-Out Examples as Elements of Scaffolding in Mathematical Modeling

ERIC Educational Resources Information Center

Tropper, Natalie; Leiss, Dominik; Hänze, Martin

2015-01-01

Empirical findings show that students have manifold difficulties when dealing with mathematical modeling problems. Accordingly, approaches for supporting students in modeling-based learning environments have to be investigated. In the research presented here, we adopted a scaffolding perspective on teaching modeling with the aim of both providing…
Developing the next generation of forest ecosystem models

Treesearch

Christopher R. Schwalm; Alan R. Ek

2002-01-01

Forest ecology and management are model-rich areas for research. Models are often cast as either empirical or mechanistic. With evolving climate change, hybrid models gain new relevance because of their ability to integrate existing mechanistic knowledge with empiricism based on causal thinking. The utility of hybrid platforms results in the combination of...
Analytical and Empirical Modeling of Wear and Forces of CBN Tool in Hard Turning - A Review

NASA Astrophysics Data System (ADS)

Patel, Vallabh Dahyabhai; Gandhi, Anishkumar Hasmukhlal

2017-08-01

Machining of steel material having hardness above 45 HRC (Hardness-Rockwell C) is referred as a hard turning. There are numerous models which should be scrutinized and implemented to gain optimum performance of hard turning. Various models in hard turning by cubic boron nitride tool have been reviewed, in attempt to utilize appropriate empirical and analytical models. Validation of steady state flank and crater wear model, Usui's wear model, forces due to oblique cutting theory, extended Lee and Shaffer's force model, chip formation and progressive flank wear have been depicted in this review paper. Effort has been made to understand the relationship between tool wear and tool force based on the different cutting conditions and tool geometries so that appropriate model can be used according to user requirement in hard turning.
Modeling the Flow Behavior, Recrystallization, and Crystallographic Texture in Hot-Deformed Fe-30 Wt Pct Ni Austenite

NASA Astrophysics Data System (ADS)

Abbod, M. F.; Sellars, C. M.; Cizek, P.; Linkens, D. A.; Mahfouf, M.

2007-10-01

The present work describes a hybrid modeling approach developed for predicting the flow behavior, recrystallization characteristics, and crystallographic texture evolution in a Fe-30 wt pct Ni austenitic model alloy subjected to hot plane strain compression. A series of compression tests were performed at temperatures between 850 °C and 1050 °C and strain rates between 0.1 and 10 s-1. The evolution of grain structure, crystallographic texture, and dislocation substructure was characterized in detail for a deformation temperature of 950 °C and strain rates of 0.1 and 10 s-1, using electron backscatter diffraction and transmission electron microscopy. The hybrid modeling method utilizes a combination of empirical, physically-based, and neuro-fuzzy models. The flow stress is described as a function of the applied variables of strain rate and temperature using an empirical model. The recrystallization behavior is predicted from the measured microstructural state variables of internal dislocation density, subgrain size, and misorientation between subgrains using a physically-based model. The texture evolution is modeled using artificial neural networks.
Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

PubMed Central

Zhu, Qing; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614
Empirical Estimation of Local Dielectric Constants: Toward Atomistic Design of Collagen Mimetic Peptides

PubMed Central

Pike, Douglas H.; Nanda, Vikas

2017-01-01

One of the key challenges in modeling protein energetics is the treatment of solvent interactions. This is particularly important in the case of peptides, where much of the molecule is highly exposed to solvent due to its small size. In this study, we develop an empirical method for estimating the local dielectric constant based on an additive model of atomic polarizabilities. Calculated values match reported apparent dielectric constants for a series of Staphylococcus aureus nuclease mutants. Calculated constants are used to determine screening effects on Coulombic interactions and to determine solvation contributions based on a modified Generalized Born model. These terms are incorporated into the protein modeling platform protCAD, and benchmarked on a data set of collagen mimetic peptides for which experimentally determined stabilities are available. Computing local dielectric constants using atomistic protein models and the assumption of additive atomic polarizabilities is a rapid and potentially useful method for improving electrostatics and solvation calculations that can be applied in the computational design of peptides. PMID:25784456
Advanced solar irradiances applied to satellite and ionospheric operational systems

NASA Astrophysics Data System (ADS)

Tobiska, W. Kent; Schunk, Robert; Eccles, Vince; Bouwer, Dave

Satellite and ionospheric operational systems require solar irradiances in a variety of time scales and spectral formats. We describe the development of a system using operational grade solar irradiances that are applied to empirical thermospheric density models and physics-based ionospheric models used by operational systems that require a space weather characterization. The SOLAR2000 (S2K) and SOLARFLARE (SFLR) models developed by Space Environment Technologies (SET) provide solar irradiances from the soft X-rays (XUV) through the Far Ultraviolet (FUV) spectrum. The irradiances are provided as integrated indices for the JB2006 empirical atmosphere density models and as line/band spectral irradiances for the physics-based Ionosphere Forecast Model (IFM) developed by the Space Environment Corporation (SEC). We describe the integration of these irradiances in historical, current epoch, and forecast modes through the Communication Alert and Prediction System (CAPS). CAPS provides real-time and forecast HF radio availability for global and regional users and global total electron content (TEC) conditions.
The Massive Star Content of Circumnuclear Star Clusters in M83

NASA Astrophysics Data System (ADS)

Wofford, A.; Chandar, R.; Leitherer, C.

2011-06-01

The circumnuclear starburst of M83 (NGC 5236), the nearest such example (4.6 Mpc), constitutes an ideal site for studying the massive star IMF at high metallicity (12+log[O/H]=9.1±0.2, Bresolin & Kennicutt 2002). We analyzed archival HST/STIS FUV imaging and spectroscopy of 13 circumnuclear star clusters in M83. We compared the observed spectra with two types of single stellar population (SSP) models; semi-empirical models, which are based on an empirical library of Galactic O and B stars observed with IUE (Robert et al. 1993), and theoretical models, which are based on a new theoretical UV library of hot massive stars described in Leitherer et al. (2010) and computed with WM-Basic (Pauldrach et al. 2001). The models were generated with Starburst99 (Leitherer & Chen 2009). We derived the reddenings, the ages, and the masses of the clusters from model fits to the FUV spectroscopy, as well as from optical HST/WFC3 photometry.
Day-ahead crude oil price forecasting using a novel morphological component analysis based model.

PubMed

Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

The Gaussian copula model for the joint deficit index for droughts

NASA Astrophysics Data System (ADS)

Van de Vyver, H.; Van den Bergh, J.

2018-06-01

The characterization of droughts and their impacts is very dependent on the time scale that is involved. In order to obtain an overall drought assessment, the cumulative effects of water deficits over different times need to be examined together. For example, the recently developed joint deficit index (JDI) is based on multivariate probabilities of precipitation over various time scales from 1- to 12-months, and was constructed from empirical copulas. In this paper, we examine the Gaussian copula model for the JDI. We model the covariance across the temporal scales with a two-parameter function that is commonly used in the specific context of spatial statistics or geostatistics. The validity of the covariance models is demonstrated with long-term precipitation series. Bootstrap experiments indicate that the Gaussian copula model has advantages over the empirical copula method in the context of drought severity assessment: (i) it is able to quantify droughts outside the range of the empirical copula, (ii) provides adequate drought quantification, and (iii) provides a better understanding of the uncertainty in the estimation.
An improved empirical dynamic control system model of global mean sea level rise and surface temperature change

NASA Astrophysics Data System (ADS)

Wu, Qing; Luu, Quang-Hung; Tkalich, Pavel; Chen, Ge

2018-04-01

Having great impacts on human lives, global warming and associated sea level rise are believed to be strongly linked to anthropogenic causes. Statistical approach offers a simple and yet conceptually verifiable combination of remotely connected climate variables and indices, including sea level and surface temperature. We propose an improved statistical reconstruction model based on the empirical dynamic control system by taking into account the climate variability and deriving parameters from Monte Carlo cross-validation random experiments. For the historic data from 1880 to 2001, we yielded higher correlation results compared to those from other dynamic empirical models. The averaged root mean square errors are reduced in both reconstructed fields, namely, the global mean surface temperature (by 24-37%) and the global mean sea level (by 5-25%). Our model is also more robust as it notably diminished the unstable problem associated with varying initial values. Such results suggest that the model not only enhances significantly the global mean reconstructions of temperature and sea level but also may have a potential to improve future projections.
Regional Models for Sediment Toxicity Assessment

EPA Science Inventory

This paper investigates the use of empirical models to predict the toxicity of sediment samples within a region to laboratory test organisms based on sediment chemistry. In earlier work, we used a large nationwide database of matching sediment chemistry and marine amphipod sedim...
The relative effectiveness of empirical and physical models for simulating the dense undercurrent of pyroclastic flows under different emplacement conditions

USGS Publications Warehouse

Ogburn, Sarah E.; Calder, Eliza S

2017-01-01

High concentration pyroclastic density currents (PDCs) are hot avalanches of volcanic rock and gas and are among the most destructive volcanic hazards due to their speed and mobility. Mitigating the risk associated with these flows depends upon accurate forecasting of possible impacted areas, often using empirical or physical models. TITAN2D, VolcFlow, LAHARZ, and ΔH/L or energy cone models each employ different rheologies or empirical relationships and therefore differ in appropriateness of application for different types of mass flows and topographic environments. This work seeks to test different statistically- and physically-based models against a range of PDCs of different volumes, emplaced under different conditions, over different topography in order to test the relative effectiveness, operational aspects, and ultimately, the utility of each model for use in hazard assessments. The purpose of this work is not to rank models, but rather to understand the extent to which the different modeling approaches can replicate reality in certain conditions, and to explore the dynamics of PDCs themselves. In this work, these models are used to recreate the inundation areas of the dense-basal undercurrent of all 13 mapped, land-confined, Soufrière Hills Volcano dome-collapse PDCs emplaced from 1996 to 2010 to test the relative effectiveness of different computational models. Best-fit model results and their input parameters are compared with results using observation- and deposit-derived input parameters. Additional comparison is made between best-fit model results and those using empirically-derived input parameters from the FlowDat global database, which represent “forward” modeling simulations as would be completed for hazard assessment purposes. Results indicate that TITAN2D is able to reproduce inundated areas well using flux sources, although velocities are often unrealistically high. VolcFlow is also able to replicate flow runout well, but does not capture the lateral spreading in distal regions of larger-volume flows. Both models are better at reproducing the inundated area of single-pulse, valley-confined, smaller-volume flows than sustained, highly unsteady, larger-volume flows, which are often partially unchannelized. The simple rheological models of TITAN2D and VolcFlow are not able to recreate all features of these more complex flows. LAHARZ is fast to run and can give a rough approximation of inundation, but may not be appropriate for all PDCs and the designation of starting locations is difficult. The ΔH/L cone model is also very quick to run and gives reasonable approximations of runout distance, but does not inherently model flow channelization or directionality and thus unrealistically covers all interfluves. Empirically-based models like LAHARZ and ΔH/L cones can be quick, first-approximations of flow runout, provided a database of similar flows, e.g., FlowDat, is available to properly calculate coefficients or ΔH/L. For hazard assessment purposes, geophysical models like TITAN2D and VolcFlow can be useful for producing both scenario-based or probabilistic hazard maps, but must be run many times with varying input parameters. LAHARZ and ΔH/L cones can be used to produce simple modeling-based hazard maps when run with a variety of input volumes, but do not explicitly consider the probability of occurrence of different volumes. For forward modeling purposes, the ability to derive potential input parameters from global or local databases is crucial, though important input parameters for VolcFlow cannot be empirically estimated. Not only does this work provide a useful comparison of the operational aspects and behavior of various models for hazard assessment, but it also enriches conceptual understanding of the dynamics of the PDCs themselves.
Inter-firm Networks, Organizational Learning and Knowledge Updating: An Empirical Study

NASA Astrophysics Data System (ADS)

Zhang, Su-rong; Wang, Wen-ping

In the era of knowledge-based economy which information technology develops rapidly, the rate of knowledge updating has become a critical factor for enterprises to gaining competitive advantage .We build an interactional theoretical model among inter-firm networks, organizational learning and knowledge updating thereby and demonstrate it with empirical study at last. The result shows that inter-firm networks and organizational learning is the source of knowledge updating.
Internet-based system for simulation-based medical planning for cardiovascular disease.

PubMed

Steele, Brooke N; Draney, Mary T; Ku, Joy P; Taylor, Charles A

2003-06-01

Current practice in vascular surgery utilizes only diagnostic and empirical data to plan treatments, which does not enable quantitative a priori prediction of the outcomes of interventions. We have previously described simulation-based medical planning methods to model blood flow in arteries and plan medical treatments based on physiologic models. An important consideration for the design of these patient-specific modeling systems is the accessibility to physicians with modest computational resources. We describe a simulation-based medical planning environment developed for the World Wide Web (WWW) using the Virtual Reality Modeling Language (VRML) and the Java programming language.
Using change-point models to estimate empirical critical loads for nitrogen in mountain ecosystems.

PubMed

Roth, Tobias; Kohli, Lukas; Rihm, Beat; Meier, Reto; Achermann, Beat

2017-01-01

To protect ecosystems and their services, the critical load concept has been implemented under the framework of the Convention on Long-range Transboundary Air Pollution (UNECE) to develop effects-oriented air pollution abatement strategies. Critical loads are thresholds below which damaging effects on sensitive habitats do not occur according to current knowledge. Here we use change-point models applied in a Bayesian context to overcome some of the difficulties when estimating empirical critical loads for nitrogen (N) from empirical data. We tested the method using simulated data with varying sample sizes, varying effects of confounding variables, and with varying negative effects of N deposition on species richness. The method was applied to the national-scale plant species richness data from mountain hay meadows and (sub)alpine scrubs sites in Switzerland. Seven confounding factors (elevation, inclination, precipitation, calcareous content, aspect as well as indicator values for humidity and light) were selected based on earlier studies examining numerous environmental factors to explain Swiss vascular plant diversity. The estimated critical load confirmed the existing empirical critical load of 5-15 kg N ha -1 yr -1 for (sub)alpine scrubs, while for mountain hay meadows the estimated critical load was at the lower end of the current empirical critical load range. Based on these results, we suggest to narrow down the critical load range for mountain hay meadows to 10-15 kg N ha -1 yr -1 . Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Determination of a Limited Scope Network's Lightning Detection Efficiency

NASA Technical Reports Server (NTRS)

Rompala, John T.; Blakeslee, R.

2008-01-01

This paper outlines a modeling technique to map lightning detection efficiency variations over a region surveyed by a sparse array of ground based detectors. A reliable flash peak current distribution (PCD) for the region serves as the technique's base. This distribution is recast as an event probability distribution function. The technique then uses the PCD together with information regarding: site signal detection thresholds, type of solution algorithm used, and range attenuation; to formulate the probability that a flash at a specified location will yield a solution. Applying this technique to the full region produces detection efficiency contour maps specific to the parameters employed. These contours facilitate a comparative analysis of each parameter's effect on the network's detection efficiency. In an alternate application, this modeling technique gives an estimate of the number, strength, and distribution of events going undetected. This approach leads to a variety of event density contour maps. This application is also illustrated. The technique's base PCD can be empirical or analytical. A process for formulating an empirical PCD specific to the region and network being studied is presented. A new method for producing an analytical representation of the empirical PCD is also introduced.
Improved theory of time domain reflectometry with variable coaxial cable length for electrical conductivity measurements

USDA-ARS?s Scientific Manuscript database

Although empirical models have been developed previously, a mechanistic model is needed for estimating electrical conductivity (EC) using time domain reflectometry (TDR) with variable lengths of coaxial cable. The goals of this study are to: (1) derive a mechanistic model based on multisection tra...
Drugs and Crime: An Empirically Based, Interdisciplinary Model

ERIC Educational Resources Information Center

Quinn, James F.; Sneed, Zach

2008-01-01

This article synthesizes neuroscience findings with long-standing criminological models and data into a comprehensive explanation of the relationship between drug use and crime. The innate factors that make some people vulnerable to drug use are conceptually similar to those that predict criminality, supporting a spurious reciprocal model of the…
A Quantitative Cost Effectiveness Model for Web-Supported Academic Instruction

ERIC Educational Resources Information Center

Cohen, Anat; Nachmias, Rafi

2006-01-01

This paper describes a quantitative cost effectiveness model for Web-supported academic instruction. The model was designed for Web-supported instruction (rather than distance learning only) characterizing most of the traditional higher education institutions. It is based on empirical data (Web logs) of students' and instructors' usage…
An alternative method for centrifugal compressor loading factor modelling

NASA Astrophysics Data System (ADS)

Galerkin, Y.; Drozdov, A.; Rekstin, A.; Soldatova, K.

2017-08-01

The loading factor at design point is calculated by one or other empirical formula in classical design methods. Performance modelling as a whole is out of consideration. Test data of compressor stages demonstrates that loading factor versus flow coefficient at the impeller exit has a linear character independent of compressibility. Known Universal Modelling Method exploits this fact. Two points define the function - loading factor at design point and at zero flow rate. The proper formulae include empirical coefficients. A good modelling result is possible if the choice of coefficients is based on experience and close analogs. Earlier Y. Galerkin and K. Soldatova had proposed to define loading factor performance by the angle of its inclination to the ordinate axis and by the loading factor at zero flow rate. Simple and definite equations with four geometry parameters were proposed for loading factor performance calculated for inviscid flow. The authors of this publication have studied the test performance of thirteen stages of different types. The equations are proposed with universal empirical coefficients. The calculation error lies in the range of plus to minus 1,5%. The alternative model of a loading factor performance modelling is included in new versions of the Universal Modelling Method.
Plant water potential improves prediction of empirical stomatal models.

PubMed

Anderegg, William R L; Wolf, Adam; Arango-Velez, Adriana; Choat, Brendan; Chmura, Daniel J; Jansen, Steven; Kolb, Thomas; Li, Shan; Meinzer, Frederick; Pita, Pilar; Resco de Dios, Víctor; Sperry, John S; Wolfe, Brett T; Pacala, Stephen

2017-01-01

Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.
Hybrid BEM/empirical approach for scattering of correlated sources in rocket noise prediction

NASA Astrophysics Data System (ADS)

Barbarino, Mattia; Adamo, Francesco P.; Bianco, Davide; Bartoccini, Daniele

2017-09-01

Empirical models such as the Eldred standard model are commonly used for rocket noise prediction. Such models directly provide a definition of the Sound Pressure Level through the quadratic pressure term by uncorrelated sources. In this paper, an improvement of the Eldred Standard model has been formulated. This new formulation contains an explicit expression for the acoustic pressure of each noise source, in terms of amplitude and phase, in order to investigate the sources correlation effects and to propagate them through a wave equation. In particular, the correlation effects between adjacent and not-adjacent sources have been modeled and analyzed. The noise prediction obtained with the revised Eldred-based model has then been used for formulating an empirical/BEM (Boundary Element Method) hybrid approach that allows an evaluation of the scattering effects. In the framework of the European Space Agency funded program VECEP (VEga Consolidation and Evolution Programme), these models have been applied for the prediction of the aeroacoustics loads of the VEGA (Vettore Europeo di Generazione Avanzata - Advanced Generation European Carrier Rocket) launch vehicle at lift-off and the results have been compared with experimental data.
Integrating Empirical-Modeling Approaches to Improve Understanding of Terrestrial Ecology Processes

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

McCarthy, Heather; Luo, Yiqi; Wullschleger, Stan D

Recent decades have seen tremendous increases in the quantity of empirical ecological data collected by individual investigators, as well as through research networks such as FLUXNET (Baldocchi et al., 2001). At the same time, advances in computer technology have facilitated the development and implementation of large and complex land surface and ecological process models. Separately, each of these information streams provides useful, but imperfect information about ecosystems. To develop the best scientific understanding of ecological processes, and most accurately predict how ecosystems may cope with global change, integration of empirical and modeling approaches is necessary. However, true integration - inmore » which models inform empirical research, which in turn informs models (Fig. 1) - is not yet common in ecological research (Luo et al., 2011). The goal of this workshop, sponsored by the Department of Energy, Office of Science, Biological and Environmental Research (BER) program, was to bring together members of the empirical and modeling communities to exchange ideas and discuss scientific practices for increasing empirical - model integration, and to explore infrastructure and/or virtual network needs for institutionalizing empirical - model integration (Yiqi Luo, University of Oklahoma, Norman, OK, USA). The workshop included presentations and small group discussions that covered topics ranging from model-assisted experimental design to data driven modeling (e.g. benchmarking and data assimilation) to infrastructure needs for empirical - model integration. Ultimately, three central questions emerged. How can models be used to inform experiments and observations? How can experimental and observational results be used to inform models? What are effective strategies to promote empirical - model integration?« less
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.
Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model

PubMed Central

2011-01-01

Background Simulation models of influenza spread play an important role for pandemic preparedness. However, as the world has not faced a severe pandemic for decades, except the rather mild H1N1 one in 2009, pandemic influenza models are inherently hypothetical and validation is, thus, difficult. We aim at reconstructing a recent seasonal influenza epidemic that occurred in Switzerland and deem this to be a promising validation strategy for models of influenza spread. Methods We present a spatially explicit, individual-based simulation model of influenza spread. The simulation model bases upon (i) simulated human travel data, (ii) data on human contact patterns and (iii) empirical knowledge on the epidemiology of influenza. For model validation we compare the simulation outcomes with empirical knowledge regarding (i) the shape of the epidemic curve, overall infection rate and reproduction number, (ii) age-dependent infection rates and time of infection, (iii) spatial patterns. Results The simulation model is capable of reproducing the shape of the 2003/2004 H3N2 epidemic curve of Switzerland and generates an overall infection rate (14.9 percent) and reproduction numbers (between 1.2 and 1.3), which are realistic for seasonal influenza epidemics. Age and spatial patterns observed in empirical data are also reflected by the model: Highest infection rates are in children between 5 and 14 and the disease spreads along the main transport axes from west to east. Conclusions We show that finding evidence for the validity of simulation models of influenza spread by challenging them with seasonal influenza outbreak data is possible and promising. Simulation models for pandemic spread gain more credibility if they are able to reproduce seasonal influenza outbreaks. For more robust modelling of seasonal influenza, serological data complementing sentinel information would be beneficial. PMID:21554680
Modeling Healthcare Processes Using Commitments: An Empirical Evaluation.

PubMed

Telang, Pankaj R; Kalia, Anup K; Singh, Munindar P

2015-01-01

The two primary objectives of this paper are: (a) to demonstrate how Comma, a business modeling methodology based on commitments, can be applied in healthcare process modeling, and (b) to evaluate the effectiveness of such an approach in producing healthcare process models. We apply the Comma approach on a breast cancer diagnosis process adapted from an HHS committee report, and presents the results of an empirical study that compares Comma with a traditional approach based on the HL7 Messaging Standard (Traditional-HL7). Our empirical study involved 47 subjects, and two phases. In the first phase, we partitioned the subjects into two approximately equal groups. We gave each group the same requirements based on a process scenario for breast cancer diagnosis. Members of one group first applied Traditional-HL7 and then Comma whereas members of the second group first applied Comma and then Traditional-HL7-each on the above-mentioned requirements. Thus, each subject produced two models, each model being a set of UML Sequence Diagrams. In the second phase, we repartitioned the subjects into two groups with approximately equal distributions from both original groups. We developed exemplar Traditional-HL7 and Comma models; we gave one repartitioned group our Traditional-HL7 model and the other repartitioned group our Comma model. We provided the same changed set of requirements to all subjects and asked them to modify the provided exemplar model to satisfy the new requirements. We assessed solutions produced by subjects in both phases with respect to measures of flexibility, time, difficulty, objective quality, and subjective quality. Our study found that Comma is superior to Traditional-HL7 in flexibility and objective quality as validated via Student's t-test to the 10% level of significance. Comma is a promising new approach for modeling healthcare processes. Further gains could be made through improved tooling and enhanced training of modeling personnel.
Modeling Healthcare Processes Using Commitments: An Empirical Evaluation

PubMed Central

2015-01-01

The two primary objectives of this paper are: (a) to demonstrate how Comma, a business modeling methodology based on commitments, can be applied in healthcare process modeling, and (b) to evaluate the effectiveness of such an approach in producing healthcare process models. We apply the Comma approach on a breast cancer diagnosis process adapted from an HHS committee report, and presents the results of an empirical study that compares Comma with a traditional approach based on the HL7 Messaging Standard (Traditional-HL7). Our empirical study involved 47 subjects, and two phases. In the first phase, we partitioned the subjects into two approximately equal groups. We gave each group the same requirements based on a process scenario for breast cancer diagnosis. Members of one group first applied Traditional-HL7 and then Comma whereas members of the second group first applied Comma and then Traditional-HL7—each on the above-mentioned requirements. Thus, each subject produced two models, each model being a set of UML Sequence Diagrams. In the second phase, we repartitioned the subjects into two groups with approximately equal distributions from both original groups. We developed exemplar Traditional-HL7 and Comma models; we gave one repartitioned group our Traditional-HL7 model and the other repartitioned group our Comma model. We provided the same changed set of requirements to all subjects and asked them to modify the provided exemplar model to satisfy the new requirements. We assessed solutions produced by subjects in both phases with respect to measures of flexibility, time, difficulty, objective quality, and subjective quality. Our study found that Comma is superior to Traditional-HL7 in flexibility and objective quality as validated via Student’s t-test to the 10% level of significance. Comma is a promising new approach for modeling healthcare processes. Further gains could be made through improved tooling and enhanced training of modeling personnel. PMID:26539985
Quasi-dynamic earthquake fault systems with rheological heterogeneity

NASA Astrophysics Data System (ADS)

Brietzke, G. B.; Hainzl, S.; Zoeller, G.; Holschneider, M.

2009-12-01

Seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates, such models cannot allow for physical statements of the described seismicity. In contrary such empirical stochastic models, physics based earthquake fault systems models allow for a physical reasoning and interpretation of the produced seismicity and system dynamics. Recently different fault system earthquake simulators based on frictional stick-slip behavior have been used to study effects of stress heterogeneity, rheological heterogeneity, or geometrical complexity on earthquake occurrence, spatial and temporal clustering of earthquakes, and system dynamics. Here we present a comparison of characteristics of synthetic earthquake catalogs produced by two different formulations of quasi-dynamic fault system earthquake simulators. Both models are based on discretized frictional faults embedded in an elastic half-space. While one (1) is governed by rate- and state-dependent friction with allowing three evolutionary stages of independent fault patches, the other (2) is governed by instantaneous frictional weakening with scheduled (and therefore causal) stress transfer. We analyze spatial and temporal clustering of events and characteristics of system dynamics by means of physical parameters of the two approaches.

Anticipating surprise: Using agent-based alternative futures simulation modeling to identify and map surprising fires in the Willamette Valley, Oregon USA

Treesearch

David Hulse; Allan Branscomb; Chris Enright; Bart Johnson; Cody Evers; John Bolte; Alan Ager

2016-01-01

This article offers a literature-supported conception and empirically grounded analysis of surprise by exploring the capacity of scenario-driven, agent-based simulation models to better anticipate it. Building on literature-derived definitions and typologies of surprise, and using results from a modeled 81,000 ha study area in a wildland-urban interface of western...
Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models.

PubMed

Hristov, A N; Kebreab, E; Niu, M; Oh, J; Bannink, A; Bayat, A R; Boland, T B; Brito, A F; Casper, D P; Crompton, L A; Dijkstra, J; Eugène, M; Garnsworthy, P C; Haque, N; Hellwing, A L F; Huhtanen, P; Kreuzer, M; Kuhla, B; Lund, P; Madsen, J; Martin, C; Moate, P J; Muetzel, S; Muñoz, C; Peiren, N; Powell, J M; Reynolds, C K; Schwarm, A; Shingfield, K J; Storlien, T M; Weisbjerg, M R; Yáñez-Ruiz, D R; Yu, Z

2018-04-18

Ruminant production systems are important contributors to anthropogenic methane (CH 4 ) emissions, but there are large uncertainties in national and global livestock CH 4 inventories. Sources of uncertainty in enteric CH 4 emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH 4 emission factors. There is also significant uncertainty associated with enteric CH 4 measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF 6 ) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH 4 emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH 4 emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH 4 prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH 4 emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH 4 prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH 4 emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
An empirical model of the phytoplankton chlorophyll : carbon ratio-the conversion factor between productivity and growth rate

USGS Publications Warehouse

Cloern, James E.; Grenz, Christian; Vidergar-Lucas, Lisa

1995-01-01

We present an empirical model that describes the ratio of phytoplankton chlorophyll a to carbon, Chl: C, as a function of temperature, daily irradiance, and nutrient-limited growth rate. Our model is based on 219 published measurements of algal cultures exposed to light-limited or nutrient-limited growth conditions. We illustrate an approach for using this estimator of Chl: C to calculate phytoplankton population growth rate from measured primary productivity. This adaptive Chl: C model gives rise to interactive light-nutrient effects in which growth efficiency increases with nutrient availability under low-light conditions. One implication of this interaction is the enhancement of phytoplankton growth efficiency, in addition to enhancement of biomass yield, as a response to eutrophication.
From sparse to dense and from assortative to disassortative in online social networks

PubMed Central

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-01-01

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks. PMID:24798703
From sparse to dense and from assortative to disassortative in online social networks.

PubMed

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-05-06

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks.
Accounting for energy and protein reserve changes in predicting diet-allowable milk production in cattle.

PubMed

Tedeschi, L O; Seo, S; Fox, D G; Ruiz, R

2006-12-01

Current ration formulation systems used to formulate diets on farms and to evaluate experimental data estimate metabolizable energy (ME)-allowable and metabolizable protein (MP)-allowable milk production from the intake above animal requirements for maintenance, pregnancy, and growth. The changes in body reserves, measured via the body condition score (BCS), are not accounted for in predicting ME and MP balances. This paper presents 2 empirical models developed to adjust predicted diet-allowable milk production based on changes in BCS. Empirical reserves model 1 was based on the reserves model described by the 2001 National Research Council (NRC) Nutrient Requirements of Dairy Cattle, whereas empirical reserves model 2 was developed based on published data of body weight and composition changes in lactating dairy cows. A database containing 134 individually fed lactating dairy cows from 3 trials was used to evaluate these adjustments in milk prediction based on predicted first-limiting ME or MP by the 2001 Dairy NRC and Cornell Net Carbohydrate and Protein System models. The analysis of first-limiting ME or MP milk production without adjustments for BCS changes indicated that the predictions of both models were consistent (r(2) of the regression between observed and model-predicted values of 0.90 and 0.85), had mean biases different from zero (12.3 and 5.34%), and had moderate but different roots of mean square errors of prediction (5.42 and 4.77 kg/d) for the 2001 NRC model and the Cornell Net Carbohydrate and Protein System model, respectively. The adjustment of first-limiting ME- or MP-allowable milk to BCS changes improved the precision and accuracy of both models. We further investigated 2 methods of adjustment; the first method used only the first and last BCS values, whereas the second method used the mean of weekly BCS values to adjust ME- and MP-allowable milk production. The adjustment to BCS changes based on first and last BCS values was more accurate than the adjustment to BCS based on the mean of all BCS values, suggesting that adjusting milk production for mean weekly variations in BCS added more variability to model-predicted milk production. We concluded that both models adequately predicted the first-limiting ME- or MP-allowable milk after adjusting for changes in BCS.
Are more complex physiological models of forest ecosystems better choices for plot and regional predictions?

Treesearch

Wenchi Jin; Hong S. He; Frank R. Thompson

2016-01-01

Process-based forest ecosystem models vary from simple physiological, complex physiological, to hybrid empirical-physiological models. Previous studies indicate that complex models provide the best prediction at plot scale with a temporal extent of less than 10 years, however, it is largely untested as to whether complex models outperform the other two types of models...
Using Empirical Models for Communication Prediction of Spacecraft

NASA Technical Reports Server (NTRS)

Quasny, Todd

2015-01-01

A viable communication path to a spacecraft is vital for its successful operation. For human spaceflight, a reliable and predictable communication link between the spacecraft and the ground is essential not only for the safety of the vehicle and the success of the mission, but for the safety of the humans on board as well. However, analytical models of these communication links are challenged by unique characteristics of space and the vehicle itself. For example, effects of radio frequency during high energy solar events while traveling through a solar array of a spacecraft can be difficult to model, and thus to predict. This presentation covers the use of empirical methods of communication link predictions, using the International Space Station (ISS) and its associated historical data as the verification platform and test bed. These empirical methods can then be incorporated into communication prediction and automation tools for the ISS in order to better understand the quality of the communication path given a myriad of variables, including solar array positions, line of site to satellites, position of the sun, and other dynamic structures on the outside of the ISS. The image on the left below show the current analytical model of one of the communication systems on the ISS. The image on the right shows a rudimentary empirical model of the same system based on historical archived data from the ISS.
Sensitivity Analysis and Accuracy of a CFD-TFM Approach to Bubbling Bed Using Pressure Drop Fluctuations

PubMed Central

Tricomi, Leonardo; Melchiori, Tommaso; Chiaramonti, David; Boulet, Micaël; Lavoie, Jean Michel

2017-01-01

Based upon the two fluid model (TFM) theory, a CFD model was implemented to investigate a cold multiphase-fluidized bubbling bed reactor. The key variable used to characterize the fluid dynamic of the experimental system, and compare it to model predictions, was the time-pressure drop induced by the bubble motion across the bed. This time signal was then processed to obtain the power spectral density (PSD) distribution of pressure fluctuations. As an important aspect of this work, the effect of the sampling time scale on the empirical power spectral density (PSD) was investigated. A time scale of 40 s was found to be a good compromise ensuring both simulation performance and numerical validation consistency. The CFD model was first numerically verified by mesh refinement process, after what it was used to investigate the sensitivity with regards to minimum fluidization velocity (as a calibration point for drag law), restitution coefficient, and solid pressure term while assessing his accuracy in matching the empirical PSD. The 2D model provided a fair match with the empirical time-averaged pressure drop, the relating fluctuations amplitude, and the signal’s energy computed as integral of the PSD. A 3D version of the TFM was also used and it improved the match with the empirical PSD in the very first part of the frequency spectrum. PMID:28695119
Sensitivity Analysis and Accuracy of a CFD-TFM Approach to Bubbling Bed Using Pressure Drop Fluctuations.

PubMed

Tricomi, Leonardo; Melchiori, Tommaso; Chiaramonti, David; Boulet, Micaël; Lavoie, Jean Michel

2017-01-01

Based upon the two fluid model (TFM) theory, a CFD model was implemented to investigate a cold multiphase-fluidized bubbling bed reactor. The key variable used to characterize the fluid dynamic of the experimental system, and compare it to model predictions, was the time-pressure drop induced by the bubble motion across the bed. This time signal was then processed to obtain the power spectral density (PSD) distribution of pressure fluctuations. As an important aspect of this work, the effect of the sampling time scale on the empirical power spectral density (PSD) was investigated. A time scale of 40 s was found to be a good compromise ensuring both simulation performance and numerical validation consistency. The CFD model was first numerically verified by mesh refinement process, after what it was used to investigate the sensitivity with regards to minimum fluidization velocity (as a calibration point for drag law), restitution coefficient, and solid pressure term while assessing his accuracy in matching the empirical PSD. The 2D model provided a fair match with the empirical time-averaged pressure drop, the relating fluctuations amplitude, and the signal's energy computed as integral of the PSD. A 3D version of the TFM was also used and it improved the match with the empirical PSD in the very first part of the frequency spectrum.
On the complex relationship between energy expenditure and longevity: Reconciling the contradictory empirical results with a simple theoretical model.

PubMed

Hou, Chen; Amunugama, Kaushalya

2015-07-01

The relationship between energy expenditure and longevity has been a central theme in aging studies. Empirical studies have yielded controversial results, which cannot be reconciled by existing theories. In this paper, we present a simple theoretical model based on first principles of energy conservation and allometric scaling laws. The model takes into considerations the energy tradeoffs between life history traits and the efficiency of the energy utilization, and offers quantitative and qualitative explanations for a set of seemingly contradictory empirical results. We show that oxidative metabolism can affect cellular damage and longevity in different ways in animals with different life histories and under different experimental conditions. Qualitative data and the linearity between energy expenditure, cellular damage, and lifespan assumed in previous studies are not sufficient to understand the complexity of the relationships. Our model provides a theoretical framework for quantitative analyses and predictions. The model is supported by a variety of empirical studies, including studies on the cellular damage profile during ontogeny; the intra- and inter-specific correlations between body mass, metabolic rate, and lifespan; and the effects on lifespan of (1) diet restriction and genetic modification of growth hormone, (2) the cold and exercise stresses, and (3) manipulations of antioxidant. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Fire activity and severity in the western US vary along proxy gradients representing fuel amount and fuel moisture.

PubMed

Parks, Sean A; Parisien, Marc-André; Miller, Carol; Dobrowski, Solomon Z

2014-01-01

Numerous theoretical and empirical studies have shown that wildfire activity (e.g., area burned) at regional to global scales may be limited at the extremes of environmental gradients such as productivity or moisture. Fire activity, however, represents only one component of the fire regime, and no studies to date have characterized fire severity along such gradients. Given the importance of fire severity in dictating ecological response to fire, this is a considerable knowledge gap. For the western US, we quantify relationships between climate and the fire regime by empirically describing both fire activity and severity along two climatic water balance gradients, actual evapotranspiration (AET) and water deficit (WD), that can be considered proxies for fuel amount and fuel moisture, respectively. We also concurrently summarize fire activity and severity among ecoregions, providing an empirically based description of the geographic distribution of fire regimes. Our results show that fire activity in the western US increases with fuel amount (represented by AET) but has a unimodal (i.e., humped) relationship with fuel moisture (represented by WD); fire severity increases with fuel amount and fuel moisture. The explicit links between fire regime components and physical environmental gradients suggest that multivariable statistical models can be generated to produce an empirically based fire regime map for the western US. Such models will potentially enable researchers to anticipate climate-mediated changes in fire recurrence and its impacts based on gridded spatial data representing future climate scenarios.
Fire Activity and Severity in the Western US Vary along Proxy Gradients Representing Fuel Amount and Fuel Moisture

PubMed Central

Parks, Sean A.; Parisien, Marc-André; Miller, Carol; Dobrowski, Solomon Z.

2014-01-01

Numerous theoretical and empirical studies have shown that wildfire activity (e.g., area burned) at regional to global scales may be limited at the extremes of environmental gradients such as productivity or moisture. Fire activity, however, represents only one component of the fire regime, and no studies to date have characterized fire severity along such gradients. Given the importance of fire severity in dictating ecological response to fire, this is a considerable knowledge gap. For the western US, we quantify relationships between climate and the fire regime by empirically describing both fire activity and severity along two climatic water balance gradients, actual evapotranspiration (AET) and water deficit (WD), that can be considered proxies for fuel amount and fuel moisture, respectively. We also concurrently summarize fire activity and severity among ecoregions, providing an empirically based description of the geographic distribution of fire regimes. Our results show that fire activity in the western US increases with fuel amount (represented by AET) but has a unimodal (i.e., humped) relationship with fuel moisture (represented by WD); fire severity increases with fuel amount and fuel moisture. The explicit links between fire regime components and physical environmental gradients suggest that multivariable statistical models can be generated to produce an empirically based fire regime map for the western US. Such models will potentially enable researchers to anticipate climate-mediated changes in fire recurrence and its impacts based on gridded spatial data representing future climate scenarios. PMID:24941290
Data envelopment analysis in service quality evaluation: an empirical study

NASA Astrophysics Data System (ADS)

Najafi, Seyedvahid; Saati, Saber; Tavana, Madjid

2015-09-01

Service quality is often conceptualized as the comparison between service expectations and the actual performance perceptions. It enhances customer satisfaction, decreases customer defection, and promotes customer loyalty. Substantial literature has examined the concept of service quality, its dimensions, and measurement methods. We introduce the perceived service quality index (PSQI) as a single measure for evaluating the multiple-item service quality construct based on the SERVQUAL model. A slack-based measure (SBM) of efficiency with constant inputs is used to calculate the PSQI. In addition, a non-linear programming model based on the SBM is proposed to delineate an improvement guideline and improve service quality. An empirical study is conducted to assess the applicability of the method proposed in this study. A large number of studies have used DEA as a benchmarking tool to measure service quality. These models do not propose a coherent performance evaluation construct and consequently fail to deliver improvement guidelines for improving service quality. The DEA models proposed in this study are designed to evaluate and improve service quality within a comprehensive framework and without any dependency on external data.
Response: Reading between the lines of cancer screening trials: using modeling to understand the evidence.

PubMed

Etzioni, Ruth; Gulati, Roman

2013-04-01

In our article about limitations of basing screening policy on screening trials, we offered several examples of ways in which modeling, using data from large screening trials and population trends, provided insights that differed somewhat from those based only on empirical trial results. In this editorial, we take a step back and consider the general question of whether randomized screening trials provide the strongest evidence for clinical guidelines concerning population screening programs. We argue that randomized trials provide a process that is designed to protect against certain biases but that this process does not guarantee that inferences based on empirical results from screening trials will be unbiased. Appropriate quantitative methods are key to obtaining unbiased inferences from screening trials. We highlight several studies in the statistical literature demonstrating that conventional survival analyses of screening trials can be misleading and list a number of key questions concerning screening harms and benefits that cannot be answered without modeling. Although we acknowledge the centrality of screening trials in the policy process, we maintain that modeling constitutes a powerful tool for screening trial interpretation and screening policy development.
An Empirical Model of the Variations of the Solar Lyman-Alpha Spectral Irradiance

NASA Astrophysics Data System (ADS)

Kretzschmar, M.; Snow, M. A.; Curdt, W.

2017-12-01

We propose a simple model that computes the spectral profile of the solar irradiance in the Hydrogen Lyman alpha line, H Ly-α (121.567nm), from 1947 to present. Such a model is relevant for the study of many astronomical environments, from planetary atmospheres to interplanetary medium, and can be used to improve the analysis of data from mission like MAVEN or GOES-16. This empirical model is based on the SOHO/SUMER observations of the Ly-α irradiance over solar cycle 23, which we analyze in details, and relies on the Ly-α integrated irradiance composite. The model reproduces the temporal variability of the spectral profile and matches the independent SORCE/SOSLTICE spectral observations from 2003 to 2007 with an accuracy better than 10%.
Uncertainty quantification in Eulerian-Lagrangian models for particle-laden flows

NASA Astrophysics Data System (ADS)

Fountoulakis, Vasileios; Jacobs, Gustaaf; Udaykumar, Hs

2017-11-01

A common approach to ameliorate the computational burden in simulations of particle-laden flows is to use a point-particle based Eulerian-Lagrangian model, which traces individual particles in their Lagrangian frame and models particles as mathematical points. The particle motion is determined by Stokes drag law, which is empirically corrected for Reynolds number, Mach number and other parameters. The empirical corrections are subject to uncertainty. Treating them as random variables renders the coupled system of PDEs and ODEs stochastic. An approach to quantify the propagation of this parametric uncertainty to the particle solution variables is proposed. The approach is based on averaging of the governing equations and allows for estimation of the first moments of the quantities of interest. We demonstrate the feasibility of our proposed methodology of uncertainty quantification of particle-laden flows on one-dimensional linear and nonlinear Eulerian-Lagrangian systems. This research is supported by AFOSR under Grant FA9550-16-1-0008.
How to Enhance Interdisciplinary Competence--Interdisciplinary Problem-Based Learning versus Interdisciplinary Project-Based Learning

ERIC Educational Resources Information Center

Brassler, Mirjam; Dettmers, Jan

2017-01-01

Interdisciplinary competence is important in academia for both employability and sustainable development. However, to date, there are no specific interdisciplinary education models and, naturally, no empirical studies to assess them. Since problem-based learning (PBL) and project-based learning (PjBL) are learning approaches that emphasize…
A Mathematical Model of a Simple Amplifier Using a Ferroelectric Transistor

NASA Technical Reports Server (NTRS)

Sayyah, Rana; Hunt, Mitchell; MacLeod, Todd C.; Ho, Fat D.

2009-01-01

This paper presents a mathematical model characterizing the behavior of a simple amplifier using a FeFET. The model is based on empirical data and incorporates several variables that affect the output, including frequency, load resistance, and gate-to-source voltage. Since the amplifier is the basis of many circuit configurations, a mathematical model that describes the behavior of a FeFET-based amplifier will help in the integration of FeFETs into many other circuits.
Toward Creating Synergy Among Policy, Procedures, and Implementation of Evidence-Based Models in Child Welfare Systems: Two Case Examples.

PubMed

Chamberlain, Patricia

2017-03-01

Over the past four to five decades, multiple randomized controlled trials have verified that preventive interventions targeting key parenting skills can have far-reaching effects on improving a diverse array of child outcomes. Further, these studies have shown that parenting skills can be taught, and they are malleable. Given these advances, prevention scientists are in a position to make solid empirically based recommendations to public child service systems on using parent-mediated interventions to optimize positive outcomes for the children and families that they serve. Child welfare systems serve some of this country's most vulnerable children and families, yet they have been slow (compared to juvenile justice and mental health systems) to adopt empirically based interventions. This paper describes two child-welfare-initiated, policy-based case studies that have sought to scale-up research-based parenting skills into the routine services that caseworkers deliver to the families that they serve. In both case studies, the child welfare system leaders worked with evaluators and model developers to tailor policy, administrative, and fiscal system practices to institutionalize and sustain evidence-based practices into usual foster care services. Descriptions of the implementations, intervention models, and preliminary results are described.

Proposed Core Competencies and Empirical Validation Procedure in Competency Modeling: Confirmation and Classification.

PubMed

Baczyńska, Anna K; Rowiński, Tomasz; Cybis, Natalia

2016-01-01

Competency models provide insight into key skills which are common to many positions in an organization. Moreover, there is a range of competencies that is used by many companies. Researchers have developed core competency terminology to underline their cross-organizational value. The article presents a theoretical model of core competencies consisting of two main higher-order competencies called performance and entrepreneurship. Each of them consists of three elements: the performance competency includes cooperation, organization of work and goal orientation, while entrepreneurship includes innovativeness, calculated risk-taking and pro-activeness. However, there is lack of empirical validation of competency concepts in organizations and this would seem crucial for obtaining reliable results from organizational research. We propose a two-step empirical validation procedure: (1) confirmation factor analysis, and (2) classification of employees. The sample consisted of 636 respondents (M = 44.5; SD = 15.1). Participants were administered a questionnaire developed for the study purpose. The reliability, measured by Cronbach's alpha, ranged from 0.60 to 0.83 for six scales. Next, we tested the model using a confirmatory factor analysis. The two separate, single models of performance and entrepreneurial orientations fit quite well to the data, while a complex model based on the two single concepts needs further research. In the classification of employees based on the two higher order competencies we obtained four main groups of employees. Their profiles relate to those found in the literature, including so-called niche finders and top performers. Some proposal for organizations is discussed.
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.
Effects of Network Structure, Competition and Memory Time on Social Spreading Phenomena

NASA Astrophysics Data System (ADS)

Gleeson, James P.; O'Sullivan, Kevin P.; Baños, Raquel A.; Moreno, Yamir

2016-04-01

Online social media has greatly affected the way in which we communicate with each other. However, little is known about what fundamental mechanisms drive dynamical information flow in online social systems. Here, we introduce a generative model for online sharing behavior that is analytically tractable and that can reproduce several characteristics of empirical micro-blogging data on hashtag usage, such as (time-dependent) heavy-tailed distributions of meme popularity. The presented framework constitutes a null model for social spreading phenomena that, in contrast to purely empirical studies or simulation-based models, clearly distinguishes the roles of two distinct factors affecting meme popularity: the memory time of users and the connectivity structure of the social network.
A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

NASA Astrophysics Data System (ADS)

Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

2016-06-01

To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.
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.
Essays on pricing electricity and electricity derivatives in deregulated markets

NASA Astrophysics Data System (ADS)

Popova, Julia

2008-10-01

This dissertation is composed of four essays on the behavior of wholesale electricity prices and their derivatives. The first essay provides an empirical model that takes into account the spatial features of a transmission network on the electricity market. The spatial structure of the transmission grid plays a key role in determining electricity prices, but it has not been incorporated into previous empirical models. The econometric model in this essay incorporates a simple representation of the transmission system into a spatial panel data model of electricity prices, and also accounts for the effect of dynamic transmission system constraints on electricity market integration. Empirical results using PJM data confirm the existence of spatial patterns in electricity prices and show that spatial correlation diminishes as transmission lines become more congested. The second essay develops and empirically tests a model of the influence of natural gas storage inventories on the electricity forward premium. I link a model of the effect of gas storage constraints on the higher moments of the distribution of electricity prices to a model of the effect of those moments on the forward premium. Empirical results using PJM data support the model's predictions that gas storage inventories sharply reduce the electricity forward premium when demand for electricity is high and space-heating demand for gas is low. The third essay examines the efficiency of PJM electricity markets. A market is efficient if prices reflect all relevant information, so that prices follow a random walk. The hypothesis of random walk is examined using empirical tests, including the Portmanteau, Augmented Dickey-Fuller, KPSS, and multiple variance ratio tests. The results are mixed though evidence of some level of market efficiency is found. The last essay investigates the possibility that previous researchers have drawn spurious conclusions based on classical unit root tests incorrectly applied to wholesale electricity prices. It is well known that electricity prices exhibit both cyclicity and high volatility which varies through time. Results indicate that heterogeneity in unconditional variance---which is not detected by classical unit root tests---may contribute to the appearance of non-stationarity.
Do Professors Have Customer-Based Brand Equity?

ERIC Educational Resources Information Center

Jillapalli, Ravi K.; Jillapalli, Regina

2014-01-01

This research endeavors to understand whether certain professors have customer-based brand equity (CBBE) in the minds of students. Consequently, the purpose of this study is to conceptualize, develop, and empirically test a model of customer-based professor brand equity. Survey data gathered from 465 undergraduate business students were used to…
Intervention Fidelity in Family-Based Prevention Counseling for Adolescent Problem Behaviors

ERIC Educational Resources Information Center

Hogue, Aaron; Liddle, Howard A.; Singer, Alisa; Leckrone, Jodi

2005-01-01

This study examined fidelity in multidimensional family prevention (MDFP), a family-based prevention counseling model for adolescents at high risk for substance abuse and related behavior problems, in comparison to two empirically based treatments for adolescent drug abuse: multidimensional family therapy (MDFT) and cognitive-behavioral therapy…
Transference of Responsibility Model Goals to the School Environment: Exploring the Impact of a Coaching Club Program

ERIC Educational Resources Information Center

Walsh, David S.; Ozaeta, Jimmy; Wright, Paul M.

2010-01-01

Background: The Teaching Personal and Social Responsibility Model (TPSR) has been used throughout the USA and in several other countries to integrate systematically life skill development within physical activity-based programs. While TPSR is widely used in practice and has a growing empirical base, few studies have examined the degree of…
Validation of a new plasmapause model derived from CHAMP field-aligned current signatures

NASA Astrophysics Data System (ADS)

Heilig, Balázs; Darrouzet, Fabien; Vellante, Massimo; Lichtenberger, János; Lühr, Hermann

2014-05-01

Recently a new model for the plasmapause location in the equatorial plane was introduced based on magnetic field observations made by the CHAMP satellite in the topside ionosphere (Heilig and Lühr, 2013). Related signals are medium-scale field-aligned currents (MSFAC) (some 10km scale size). An empirical model for the MSFAC boundary was developed as a function of Kp and MLT. The MSFAC model then was compared to in situ plasmapause observations of IMAGE RPI. By considering this systematic displacement resulting from this comparison and by taking into account the diurnal variation and Kp-dependence of the residuals an empirical model of the plasmapause location that is based on MSFAC measurements from CHAMP was constructed. As a first step toward validation of the new plasmapause model we used in-situ (Van Allen Probes/EMFISIS, Cluster/WHISPER) and ground based (EMMA) plasma density observations. Preliminary results show a good agreement in general between the model and observations. Some observed differences stem from the different definitions of the plasmapause. A more detailed validation of the method can take place as soon as SWARM and VAP data become available. Heilig, B., and H. Lühr (2013) New plasmapause model derived from CHAMP field-aligned current signatures, Ann. Geophys., 31, 529-539, doi:10.5194/angeo-31-529-2013
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
Economic analysis of empiric versus diagnostic-driven strategies for immunocompromised patients with suspected fungal infections in the People's Republic of China.

PubMed

Mao, Ningying; Lesher, Beth; Liu, Qifa; Qin, Lei; Chen, Yixi; Gao, Xin; Earnshaw, Stephanie R; McDade, Cheryl L; Charbonneau, Claudie

2016-01-01

Invasive fungal infections (IFIs) require rapid diagnosis and treatment. A decision-analytic model was used to estimate total costs and survival associated with a diagnostic-driven (DD) or an empiric treatment approach in neutropenic patients with hematological malignancies receiving chemotherapy or autologous/allogeneic stem cell transplants in Shanghai, Beijing, Chengdu, and Guangzhou, the People's Republic of China. Treatment initiation for the empiric approach occurred after clinical suspicion of an IFI; treatment initiation for the DD approach occurred after clinical suspicion and a positive IFI diagnostic test result. Model inputs were obtained from the literature; treatment patterns and resource use were based on clinical opinion. Total costs were lower for the DD versus the empiric approach in Shanghai (¥3,232 vs ¥4,331), Beijing (¥3,894 vs ¥4,864), Chengdu, (¥4,632 vs ¥5,795), and Guangzhou (¥8,489 vs ¥9,795). Antifungal administration was lower using the DD (5.7%) than empiric (9.8%) approach, with similar survival rates. Results from one-way and probabilistic sensitivity analyses were most sensitive to changes in diagnostic test sensitivity and IFI incidence; the DD approach dominated the empiric approach in 88% of scenarios. These results suggest that a DD compared to an empiric treatment approach in the People's Republic of China may be cost saving, with similar overall survival in immunocompromised patients with suspected IFIs.
Comparative Analysis of VaR Estimation of Double Long-Memory GARCH Models: Empirical Analysis of China's Stock Market

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Guo, Jianping; Xu, Lin

GARCH models are widely used to model the volatility of financial assets and measure VaR. Based on the characteristics of long-memory and lepkurtosis and fat tail of stock market return series, we compared the ability of double long-memory GARCH models with skewed student-t-distribution to compute VaR, through the empirical analysis of Shanghai Composite Index (SHCI) and Shenzhen Component Index (SZCI). The results show that the ARFIMA-HYGARCH model performance better than others, and at less than or equal to 2.5 percent of the level of VaR, double long-memory GARCH models have stronger ability to evaluate in-sample VaRs in long position than in short position while there is a diametrically opposite conclusion for ability of out-of-sample VaR forecast.
A semi-empirical model for the complete orientation dependence of the growth rate for vapor phase epitaxy - Chloride VPE of GaAs

NASA Technical Reports Server (NTRS)

Seidel-Salinas, L. K.; Jones, S. H.; Duva, J. M.

1992-01-01

A semi-empirical model has been developed to determine the complete crystallographic orientation dependence of the growth rate for vapor phase epitaxy (VPE). Previous researchers have been able to determine this dependence for a limited range of orientations; however, our model yields relative growth rate information for any orientation. This model for diamond and zincblende structure materials is based on experimental growth rate data, gas phase diffusion, and surface reactions. Data for GaAs chloride VPE is used to illustrate the model. The resulting growth rate polar diagrams are used in conjunction with Wulff constructions to simulate epitaxial layer shapes as grown on patterned substrates. In general, this model can be applied to a variety of materials and vapor phase epitaxy systems.
DOUBLE SHELL TANK (DST) HYDROXIDE DEPLETION MODEL FOR CARBON DIOXIDE ABSORPTION

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

OGDEN DM; KIRCH NW

2007-10-31

This document generates a supernatant hydroxide ion depletion model based on mechanistic principles. The carbon dioxide absorption mechanistic model is developed in this report. The report also benchmarks the model against historical tank supernatant hydroxide data and vapor space carbon dioxide data. A comparison of the newly generated mechanistic model with previously applied empirical hydroxide depletion equations is also performed.
Knowledge-Based Information Retrieval.

ERIC Educational Resources Information Center

Ford, Nigel

1991-01-01

Discussion of information retrieval focuses on theoretical and empirical advances in knowledge-based information retrieval. Topics discussed include the use of natural language for queries; the use of expert systems; intelligent tutoring systems; user modeling; the need for evaluation of system effectiveness; and examples of systems, including…
The Small World of Psychopathology

PubMed Central

Borsboom, Denny; Cramer, Angélique O. J.; Schmittmann, Verena D.; Epskamp, Sacha; Waldorp, Lourens J.

2011-01-01

Background Mental disorders are highly comorbid: people having one disorder are likely to have another as well. We explain empirical comorbidity patterns based on a network model of psychiatric symptoms, derived from an analysis of symptom overlap in the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). Principal Findings We show that a) half of the symptoms in the DSM-IV network are connected, b) the architecture of these connections conforms to a small world structure, featuring a high degree of clustering but a short average path length, and c) distances between disorders in this structure predict empirical comorbidity rates. Network simulations of Major Depressive Episode and Generalized Anxiety Disorder show that the model faithfully reproduces empirical population statistics for these disorders. Conclusions In the network model, mental disorders are inherently complex. This explains the limited successes of genetic, neuroscientific, and etiological approaches to unravel their causes. We outline a psychosystems approach to investigate the structure and dynamics of mental disorders. PMID:22114671
Empirical prediction of peak pressure levels in anthropogenic impulsive noise. Part I: Airgun arrays signals.

PubMed

Galindo-Romero, Marta; Lippert, Tristan; Gavrilov, Alexander

2015-12-01

This paper presents an empirical linear equation to predict peak pressure level of anthropogenic impulsive signals based on its correlation with the sound exposure level. The regression coefficients are shown to be weakly dependent on the environmental characteristics but governed by the source type and parameters. The equation can be applied to values of the sound exposure level predicted with a numerical model, which provides a significant improvement in the prediction of the peak pressure level. Part I presents the analysis for airgun arrays signals, and Part II considers the application of the empirical equation to offshore impact piling noise.
Analog modeling of Worm-Like Chain molecules using macroscopic beads-on-a-string.

PubMed

Tricard, Simon; Feinstein, Efraim; Shepherd, Robert F; Reches, Meital; Snyder, Phillip W; Bandarage, Dileni C; Prentiss, Mara; Whitesides, George M

2012-07-07

This paper describes an empirical model of polymer dynamics, based on the agitation of millimeter-sized polymeric beads. Although the interactions between the particles in the macroscopic model and those between the monomers of molecular-scale polymers are fundamentally different, both systems follow the Worm-Like Chain theory.
An improved Ångström-type model for estimating solar radiation over the Tibetan Plateau

USDA-ARS?s Scientific Manuscript database

Sunshine- and temperature-based empirical models are widely used for solar radiation estimation over the world, but the coefficients of the models are mostly site-dependent. The coefficients are expected to vary more under complex terrain conditions than under flat terrains. To test this hypothesis,...

W17_geonuc “Application of the Spectral Element Method to improvement of Ground-based Nuclear Explosion Monitoring”

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

Larmat, Carene; Rougier, Esteban; Lei, Zhou

This project is in support of the Source Physics Experiment SPE (Snelson et al. 2013), which aims to develop new seismic source models of explosions. One priority of this program is first principle numerical modeling to validate and extend current empirical models.
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…
LSTM, GRU, Highway and a Bit of Attention: An Empirical Overview for Language Modeling in Speech Recognition

DTIC Science & Technology

2016-09-12

on learning word triggers with an attention mechanism. 5.1. Model descriptions 5.1.1. Attention layer A minimalistic attention mechanism can be...word trigger model based on a minimalistic attention mechanism: it already showed some interesting qualitative re- sults, while the performance was not
Understanding human dynamics in microblog posting activities

NASA Astrophysics Data System (ADS)

Jiang, Zhihong; Zhang, Yubao; Wang, Hui; Li, Pei

2013-02-01

Human activity patterns are an important issue in behavior dynamics research. Empirical evidence indicates that human activity patterns can be characterized by a heavy-tailed inter-event time distribution. However, most researchers give an understanding by only modeling the power-law feature of the inter-event time distribution, and those overlooked non-power-law features are likely to be nontrivial. In this work, we propose a behavior dynamics model, called the finite memory model, in which humans adaptively change their activity rates based on a finite memory of recent activities, which is driven by inherent individual interest. Theoretical analysis shows a finite memory model can properly explain various heavy-tailed inter-event time distributions, including a regular power law and some non-power-law deviations. To validate the model, we carry out an empirical study based on microblogging activity from thousands of microbloggers in the Celebrity Hall of the Sina microblog. The results show further that the model is reasonably effective. We conclude that finite memory is an effective dynamics element to describe the heavy-tailed human activity pattern.
Exponential model for option prices: Application to the Brazilian market

NASA Astrophysics Data System (ADS)

Ramos, Antônio M. T.; Carvalho, J. A.; Vasconcelos, G. L.

2016-03-01

In this paper we report an empirical analysis of the Ibovespa index of the São Paulo Stock Exchange and its respective option contracts. We compare the empirical data on the Ibovespa options with two option pricing models, namely the standard Black-Scholes model and an empirical model that assumes that the returns are exponentially distributed. It is found that at times near the option expiration date the exponential model performs better than the Black-Scholes model, in the sense that it fits the empirical data better than does the latter model.
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.
An Initial Non-Equilibrium Porous-Media Model for CFD Simulation of Stirling Regenerators

NASA Technical Reports Server (NTRS)

Tew, Roy; Simon, Terry; Gedeon, David; Ibrahim, Mounir; Rong, Wei

2006-01-01

The objective of this paper is to define empirical parameters (or closwre models) for an initial thermai non-equilibrium porous-media model for use in Computational Fluid Dynamics (CFD) codes for simulation of Stirling regenerators. The two CFD codes currently being used at Glenn Research Center (GRC) for Stirling engine modeling are Fluent and CFD-ACE. The porous-media models available in each of these codes are equilibrium models, which assmne that the solid matrix and the fluid are in thermal equilibrium at each spatial location within the porous medium. This is believed to be a poor assumption for the oscillating-flow environment within Stirling regenerators; Stirling 1-D regenerator models, used in Stirling design, we non-equilibrium regenerator models and suggest regenerator matrix and gas average temperatures can differ by several degrees at a given axial location end time during the cycle. A NASA regenerator research grant has been providing experimental and computational results to support definition of various empirical coefficients needed in defining a noa-equilibrium, macroscopic, porous-media model (i.e., to define "closure" relations). The grant effort is being led by Cleveland State University, with subcontractor assistance from the University of Minnesota, Gedeon Associates, and Sunpower, Inc. Friction-factor and heat-transfer correlations based on data taken with the NASAlSunpower oscillating-flow test rig also provide experimentally based correlations that are useful in defining parameters for the porous-media model; these correlations are documented in Gedeon Associates' Sage Stirling-Code Manuals. These sources of experimentally based information were used to define the following terms and parameters needed in the non-equilibrium porous-media model: hydrodynamic dispersion, permeability, inertial coefficient, fluid effective thermal conductivity (including themal dispersion and estimate of tortuosity effects}, and fluid-solid heat transfer coefficient. Solid effective thermal conductivity (including the effect of tortuosity) was also estimated. Determination of the porous-media model parameters was based on planned use in a CFD model of Infinia's Stirling Technology Demonstration Convertor (TDC), which uses a random-fiber regenerator matrix. The non-equilibrium porous-media model presented is considered to be an initial, or "draft," model for possible incorporation in commercial CFD codes, with the expectation that the empirical parameters will likely need to be updated once resulting Stirling CFD model regenerator and engine results have been analyzed. The emphasis of the paper is on use of available data to define empirical parameters (and closure models) needed in a thermal non-equilibrium porous-media model for Stirling regenerator simulation. Such a model has not yet been implemented by the authors or their associates. However, it is anticipated that a thermal non-equilibrium model such as that presented here, when iacorporated in the CFD codes, will improve our ability to accurately model Stirling regenerators with CFD relative to current thermal-equilibrium porous-media models.
Fatigue crack propagation behavior of stainless steel welds

NASA Astrophysics Data System (ADS)

Kusko, Chad S.

The fatigue crack propagation behavior of austenitic and duplex stainless steel base and weld metals has been investigated using various fatigue crack growth test procedures, ferrite measurement techniques, light optical microscopy, stereomicroscopy, scanning electron microscopy, and optical profilometry. The compliance offset method has been incorporated to measure crack closure during testing in order to determine a stress ratio at which such closure is overcome. Based on this method, an empirically determined stress ratio of 0.60 has been shown to be very successful in overcoming crack closure for all da/dN for gas metal arc and laser welds. This empirically-determined stress ratio of 0.60 has been applied to testing of stainless steel base metal and weld metal to understand the influence of microstructure. Regarding the base metal investigation, for 316L and AL6XN base metals, grain size and grain plus twin size have been shown to influence resulting crack growth behavior. The cyclic plastic zone size model has been applied to accurately model crack growth behavior for austenitic stainless steels when the average grain plus twin size is considered. Additionally, the effect of the tortuous crack paths observed for the larger grain size base metals can be explained by a literature model for crack deflection. Constant Delta K testing has been used to characterize the crack growth behavior across various regions of the gas metal arc and laser welds at the empirically determined stress ratio of 0.60. Despite an extensive range of stainless steel weld metal FN and delta-ferrite morphologies, neither delta-ferrite morphology significantly influence the room temperature crack growth behavior. However, variations in weld metal da/dN can be explained by local surface roughness resulting from large columnar grains and tortuous crack paths in the weld metal.
Empirical correlations of the performance of vapor-anode PX-series AMTEC cells

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

Huang, L.; Merrill, J.M.; Mayberry, C.

Power systems based on AMTEC technology will be used for future NASA missions, including a Pluto-Express (PX) or Europa mission planned for approximately year 2004. AMTEC technology may also be used as an alternative to photovoltaic based power systems for future Air Force missions. An extensive development program of Alkali-Metal Thermal-to-Electric Conversion (AMTEC) technology has been underway at the Vehicle Technologies Branch of the Air Force Research Laboratory (AFRL) in Albuquerque, New Mexico since 1992. Under this program, numerical modeling and experimental investigations of the performance of the various multi-BASE tube, vapor-anode AMTEC cells have been and are being performed.more » Vacuum testing of AMTEC cells at AFRL determines the effects of changing the hot and cold end temperatures, T{sub hot} and T{sub cold}, and applied external load, R{sub ext}, on the cell electric power output, current-voltage characteristics, and conversion efficiency. Test results have traditionally been used to provide feedback to cell designers, and to validate numerical models. The current work utilizes the test data to develop empirical correlations for cell output performance under various working conditions. Because the empirical correlations are developed directly from the experimental data, uncertainties arising from material properties that must be used in numerical modeling can be avoided. Empirical correlations of recent vapor-anode PX-series AMTEC cells have been developed. Based on AMTEC theory and the experimental data, the cell output power (as well as voltage and current) was correlated as a function of three parameters (T{sub hot}, T{sub cold}, and R{sub ext}) for a given cell. Correlations were developed for different cells (PX-3C, PX-3A, PX-G3, and PX-5A), and were in good agreement with experimental data for these cells. Use of these correlations can greatly reduce the testing required to determine electrical performance of a given type of AMTEC cell over a wide range of operating conditions.« less
Photoresist and stochastic modeling

NASA Astrophysics Data System (ADS)

Hansen, Steven G.

2018-01-01

Analysis of physical modeling results can provide unique insights into extreme ultraviolet stochastic variation, which augment, and sometimes refute, conclusions based on physical intuition and even wafer experiments. Simulations verify the primacy of "imaging critical" counting statistics (photons, electrons, and net acids) and the image/blur-dependent dose sensitivity in describing the local edge or critical dimension variation. But the failure of simple counting when resist thickness is varied highlights a limitation of this exact analytical approach, so a calibratable empirical model offers useful simplicity and convenience. Results presented here show that a wide range of physical simulation results can be well matched by an empirical two-parameter model based on blurred image log-slope (ILS) for lines/spaces and normalized ILS for holes. These results are largely consistent with a wide range of published experimental results; however, there is some disagreement with the recently published dataset of De Bisschop. The present analysis suggests that the origin of this model failure is an unexpected blurred ILS:dose-sensitivity relationship failure in that resist process. It is shown that a photoresist mechanism based on high photodecomposable quencher loading and high quencher diffusivity can give rise to pitch-dependent blur, which may explain the discrepancy.
The logical primitives of thought: Empirical foundations for compositional cognitive models.

PubMed

Piantadosi, Steven T; Tenenbaum, Joshua B; Goodman, Noah D

2016-07-01

The notion of a compositional language of thought (LOT) has been central in computational accounts of cognition from earliest attempts (Boole, 1854; Fodor, 1975) to the present day (Feldman, 2000; Penn, Holyoak, & Povinelli, 2008; Fodor, 2008; Kemp, 2012; Goodman, Tenenbaum, & Gerstenberg, 2015). Recent modeling work shows how statistical inferences over compositionally structured hypothesis spaces might explain learning and development across a variety of domains. However, the primitive components of such representations are typically assumed a priori by modelers and theoreticians rather than determined empirically. We show how different sets of LOT primitives, embedded in a psychologically realistic approximate Bayesian inference framework, systematically predict distinct learning curves in rule-based concept learning experiments. We use this feature of LOT models to design a set of large-scale concept learning experiments that can determine the most likely primitives for psychological concepts involving Boolean connectives and quantification. Subjects' inferences are most consistent with a rich (nonminimal) set of Boolean operations, including first-order, but not second-order, quantification. Our results more generally show how specific LOT theories can be distinguished empirically. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Increasing the relevance of GCM simulations for Climate Services

NASA Astrophysics Data System (ADS)

Smith, L. A.; Suckling, E.

2012-12-01

The design and interpretation of model simulations for climate services differ significantly from experimental design for the advancement of the fundamental research on predictability that underpins it. Climate services consider the sources of best information available today; this calls for a frank evaluation of model skill in the face of statistical benchmarks defined by empirical models. The fact that Physical simulation models are thought to provide the only reliable method for extrapolating into conditions not previously observed has no bearing on whether or not today's simulation models outperform empirical models. Evidence on the length scales on which today's simulation models fail to outperform empirical benchmarks is presented; it is illustrated that this occurs even on global scales in decadal prediction. At all timescales considered thus far (as of July 2012), predictions based on simulation models are improved by blending with the output of statistical models. Blending is shown to be more interesting in the climate context than it is in the weather context, where blending with a history-based climatology is straightforward. As GCMs improve and as the Earth's climate moves further from that of the last century, the skill from simulation models and their relevance to climate services is expected to increase. Examples from both seasonal and decadal forecasting will be used to discuss a third approach that may increase the role of current GCMs more quickly. Specifically, aspects of the experimental design in previous hind cast experiments are shown to hinder the use of GCM simulations for climate services. Alternative designs are proposed. The value in revisiting Thompson's classic approach to improving weather forecasting in the fifties in the context of climate services is discussed.
Use of Decision Models in the Development of Evidence-Based Clinical Preventive Services Recommendations: Methods of the U.S. Preventive Services Task Force.

PubMed

Owens, Douglas K; Whitlock, Evelyn P; Henderson, Jillian; Pignone, Michael P; Krist, Alex H; Bibbins-Domingo, Kirsten; Curry, Susan J; Davidson, Karina W; Ebell, Mark; Gillman, Matthew W; Grossman, David C; Kemper, Alex R; Kurth, Ann E; Maciosek, Michael; Siu, Albert L; LeFevre, Michael L

2016-10-04

The U.S. Preventive Services Task Force (USPSTF) develops evidence-based recommendations about preventive care based on comprehensive systematic reviews of the best available evidence. Decision models provide a complementary, quantitative approach to support the USPSTF as it deliberates about the evidence and develops recommendations for clinical and policy use. This article describes the rationale for using modeling, an approach to selecting topics for modeling, and how modeling may inform recommendations about clinical preventive services. Decision modeling is useful when clinical questions remain about how to target an empirically established clinical preventive service at the individual or program level or when complex determinations of magnitude of net benefit, overall or among important subpopulations, are required. Before deciding whether to use decision modeling, the USPSTF assesses whether the benefits and harms of the preventive service have been established empirically, assesses whether there are key issues about applicability or implementation that modeling could address, and then defines the decision problem and key questions to address through modeling. Decision analyses conducted for the USPSTF are expected to follow best practices for modeling. For chosen topics, the USPSTF assesses the strengths and limitations of the systematically reviewed evidence and the modeling analyses and integrates the results of each to make preventive service recommendations.
Empirical models of demand for out-patient physician services and their relevance to the assessment of patient payment policies: a critical review of the literature.

PubMed

Skriabikova, Olga; Pavlova, Milena; Groot, Wim

2010-06-01

This paper reviews the existing empirical micro-level models of demand for out-patient physician services where the size of patient payment is included either directly as an independent variable (when a flat-rate co-payment fee) or indirectly as a level of deductibles and/or co-insurance defined by the insurance coverage. The paper also discusses the relevance of these models for the assessment of patient payment policies. For this purpose, a systematic literature review is carried out. In total, 46 relevant publications were identified. These publications are classified into categories based on their general approach to demand modeling, specifications of data collection, data analysis, and main empirical findings. The analysis indicates a rising research interest in the empirical micro-level models of demand for out-patient physician services that incorporate the size of patient payment. Overall, the size of patient payments, consumer socio-economic and demographic features, and quality of services provided emerge as important determinants of demand for out-patient physician services. However, there is a great variety in the modeling approaches and inconsistencies in the findings regarding the impact of price on demand for out-patient physician services. Hitherto, the empirical research fails to offer policy-makers a clear strategy on how to develop a country-specific model of demand for out-patient physician services suitable for the assessment of patient payment policies in their countries. In particular, theoretically important factors, such as provider behavior, consumer attitudes, experience and culture, and informal patient payments, are not considered. Although we recognize that it is difficult to measure these factors and to incorporate them in the demand models, it is apparent that there is a gap in research for the construction of effective patient payment schemes.
Empirical Models of Demand for Out-Patient Physician Services and Their Relevance to the Assessment of Patient Payment Policies: A Critical Review of the Literature

PubMed Central

Skriabikova, Olga; Pavlova, Milena; Groot, Wim

2010-01-01

This paper reviews the existing empirical micro-level models of demand for out-patient physician services where the size of patient payment is included either directly as an independent variable (when a flat-rate co-payment fee) or indirectly as a level of deductibles and/or co-insurance defined by the insurance coverage. The paper also discusses the relevance of these models for the assessment of patient payment policies. For this purpose, a systematic literature review is carried out. In total, 46 relevant publications were identified. These publications are classified into categories based on their general approach to demand modeling, specifications of data collection, data analysis, and main empirical findings. The analysis indicates a rising research interest in the empirical micro-level models of demand for out-patient physician services that incorporate the size of patient payment. Overall, the size of patient payments, consumer socio-economic and demographic features, and quality of services provided emerge as important determinants of demand for out-patient physician services. However, there is a great variety in the modeling approaches and inconsistencies in the findings regarding the impact of price on demand for out-patient physician services. Hitherto, the empirical research fails to offer policy-makers a clear strategy on how to develop a country-specific model of demand for out-patient physician services suitable for the assessment of patient payment policies in their countries. In particular, theoretically important factors, such as provider behavior, consumer attitudes, experience and culture, and informal patient payments, are not considered. Although we recognize that it is difficult to measure these factors and to incorporate them in the demand models, it is apparent that there is a gap in research for the construction of effective patient payment schemes. PMID:20644697
Geospace environment modeling 2008--2009 challenge: Dst index

USGS Publications Warehouse

Rastätter, L.; Kuznetsova, M.M.; Glocer, A.; Welling, D.; Meng, X.; Raeder, J.; Wittberger, M.; Jordanova, V.K.; Yu, Y.; Zaharia, S.; Weigel, R.S.; Sazykin, S.; Boynton, R.; Wei, H.; Eccles, V.; Horton, W.; Mays, M.L.; Gannon, J.

2013-01-01

This paper reports the metrics-based results of the Dst index part of the 2008–2009 GEM Metrics Challenge. The 2008–2009 GEM Metrics Challenge asked modelers to submit results for four geomagnetic storm events and five different types of observations that can be modeled by statistical, climatological or physics-based models of the magnetosphere-ionosphere system. We present the results of 30 model settings that were run at the Community Coordinated Modeling Center and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations, we use comparisons of 1 hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of 1 minute model data with the 1 minute Dst index calculated by the United States Geological Survey. The latter index can be used to calculate spectral variability of model outputs in comparison to the index. We find that model rankings vary widely by skill score used. None of the models consistently perform best for all events. We find that empirical models perform well in general. Magnetohydrodynamics-based models of the global magnetosphere with inner magnetosphere physics (ring current model) included and stand-alone ring current models with properly defined boundary conditions perform well and are able to match or surpass results from empirical models. Unlike in similar studies, the statistical models used in this study found their challenge in the weakest events rather than the strongest events.
Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

NASA Astrophysics Data System (ADS)

Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

2012-04-01

In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological dynamic and processes, i. e. sample heterogeneity. For a same streamflow range corresponds different processes such as rising limbs or recession, where uncertainties are different. The dynamical approach improves reliability, skills and sharpness of forecasts and globally reduces confidence intervals width. When compared in details, the dynamical approach allows a noticeable reduction of confidence intervals during recessions where uncertainty is relatively lower and a slight increase of confidence intervals during rising limbs or snowmelt where uncertainty is greater. The dynamic approach, validated by forecaster's experience that considered the empirical approach not discriminative enough, improved forecaster's confidence and communication of uncertainties. Montanari, A. and Brath, A., (2004). A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resources Research, 40, W01106, doi:10.1029/2003WR002540. Schaefli, B., Balin Talamba, D. and Musy, A., (2007). Quantifying hydrological modeling errors through a mixture of normal distributions. Journal of Hydrology, 332, 303-315.
Development of sustainable precision farming systems for swine: estimating real-time individual amino acid requirements in growing-finishing pigs.

PubMed

Hauschild, L; Lovatto, P A; Pomar, J; Pomar, C

2012-07-01

The objective of this study was to develop and evaluate a mathematical model used to estimate the daily amino acid requirements of individual growing-finishing pigs. The model includes empirical and mechanistic model components. The empirical component estimates daily feed intake (DFI), BW, and daily gain (DG) based on individual pig information collected in real time. Based on DFI, BW, and DG estimates, the mechanistic component uses classic factorial equations to estimate the optimal concentration of amino acids that must be offered to each pig to meet its requirements. The model was evaluated with data from a study that investigated the effect of feeding pigs with a 3-phase or daily multiphase system. The DFI and BW values measured in this study were compared with those estimated by the empirical component of the model. The coherence of the values estimated by the mechanistic component was evaluated by analyzing if it followed a normal pattern of requirements. Lastly, the proposed model was evaluated by comparing its estimates with those generated by the existing growth model (InraPorc). The precision of the proposed model and InraPorc in estimating DFI and BW was evaluated through the mean absolute error. The empirical component results indicated that the DFI and BW trajectories of individual pigs fed ad libitum could be predicted 1 d (DFI) or 7 d (BW) ahead with the average mean absolute error of 12.45 and 1.85%, respectively. The average mean absolute error obtained with the InraPorc for the average individual of the population was 14.72% for DFI and 5.38% for BW. Major differences were observed when estimates from InraPorc were compared with individual observations. The proposed model, however, was effective in tracking the change in DFI and BW for each individual pig. The mechanistic model component estimated the optimal standardized ileal digestible Lys to NE ratio with reasonable between animal (average CV = 7%) and overtime (average CV = 14%) variation. Thus, the amino acid requirements estimated by model are animal- and time-dependent and follow, in real time, the individual DFI and BW growth patterns. The proposed model can follow the average feed intake and feed weight trajectory of each individual pig in real time with good accuracy. Based on these trajectories and using classical factorial equations, the model makes it possible to estimate dynamically the AA requirements of each animal, taking into account the intake and growth changes of the animal.
Testing a theory of aircraft noise annoyance: a structural equation analysis.

PubMed

Kroesen, Maarten; Molin, Eric J E; van Wee, Bert

2008-06-01

Previous research has stressed the relevance of nonacoustical factors in the perception of aircraft noise. However, it is largely empirically driven and lacks a sound theoretical basis. In this paper, a theoretical model which explains noise annoyance based on the psychological stress theory is empirically tested. The model is estimated by applying structural equation modeling based on data from residents living in the vicinity of Amsterdam Airport Schiphol in The Netherlands. The model provides a good model fit and indicates that concern about the negative health effects of noise and pollution, perceived disturbance, and perceived control and coping capacity are the most important variables that explain noise annoyance. Furthermore, the model provides evidence for the existence of two reciprocal relationships between (1) perceived disturbance and noise annoyance and (2) perceived control and coping capacity and noise annoyance. Lastly, the model yielded two unexpected results. Firstly, the variables noise sensitivity and fear related to the noise source were unable to explain additional variance in the endogenous variables of the model and were therefore excluded from the model. And secondly, the size of the total effect of noise exposure on noise annoyance was relatively small. The paper concludes with some recommended directions for further research.
On the use of Empirical Data to Downscale Non-scientific Scepticism About Results From Complex Physical Based Models

NASA Astrophysics Data System (ADS)

Germer, S.; Bens, O.; Hüttl, R. F.

2008-12-01

The scepticism of non-scientific local stakeholders about results from complex physical based models is a major problem concerning the development and implementation of local climate change adaptation measures. This scepticism originates from the high complexity of such models. Local stakeholders perceive complex models as black-box models, as it is impossible to gasp all underlying assumptions and mathematically formulated processes at a glance. The use of physical based models is, however, indispensible to study complex underlying processes and to predict future environmental changes. The increase of climate change adaptation efforts following the release of the latest IPCC report indicates that the communication of facts about what has already changed is an appropriate tool to trigger climate change adaptation. Therefore we suggest increasing the practice of empirical data analysis in addition to modelling efforts. The analysis of time series can generate results that are easier to comprehend for non-scientific stakeholders. Temporal trends and seasonal patterns of selected hydrological parameters (precipitation, evapotranspiration, groundwater levels and river discharge) can be identified and the dependence of trends and seasonal patters to land use, topography and soil type can be highlighted. A discussion about lag times between the hydrological parameters can increase the awareness of local stakeholders for delayed environment responses.

Integrating statistical and process-based models to produce probabilistic landslide hazard at regional scale

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.

2017-12-01

We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.
Toward a Model-Based Approach to the Clinical Assessment of Personality Psychopathology

PubMed Central

Eaton, Nicholas R.; Krueger, Robert F.; Docherty, Anna R.; Sponheim, Scott R.

2015-01-01

Recent years have witnessed tremendous growth in the scope and sophistication of statistical methods available to explore the latent structure of psychopathology, involving continuous, discrete, and hybrid latent variables. The availability of such methods has fostered optimism that they can facilitate movement from classification primarily crafted through expert consensus to classification derived from empirically-based models of psychopathological variation. The explication of diagnostic constructs with empirically supported structures can then facilitate the development of assessment tools that appropriately characterize these constructs. Our goal in this paper is to illustrate how new statistical methods can inform conceptualization of personality psychopathology and therefore its assessment. We use magical thinking as example, because both theory and earlier empirical work suggested the possibility of discrete aspects to the latent structure of personality psychopathology, particularly forms of psychopathology involving distortions of reality testing, yet other data suggest that personality psychopathology is generally continuous in nature. We directly compared the fit of a variety of latent variable models to magical thinking data from a sample enriched with clinically significant variation in psychotic symptomatology for explanatory purposes. Findings generally suggested a continuous latent variable model best represented magical thinking, but results varied somewhat depending on different indices of model fit. We discuss the implications of the findings for classification and applied personality assessment. We also highlight some limitations of this type of approach that are illustrated by these data, including the importance of substantive interpretation, in addition to use of model fit indices, when evaluating competing structural models. PMID:24007309
The effects of time-varying observation errors on semi-empirical sea-level projections

DOE PAGES

Ruckert, Kelsey L.; Guan, Yawen; Bakker, Alexander M. R.; ...

2016-11-30

Sea-level rise is a key driver of projected flooding risks. The design of strategies to manage these risks often hinges on projections that inform decision-makers about the surrounding uncertainties. Producing semi-empirical sea-level projections is difficult, for example, due to the complexity of the error structure of the observations, such as time-varying (heteroskedastic) observation errors and autocorrelation of the data-model residuals. This raises the question of how neglecting the error structure impacts hindcasts and projections. Here, we quantify this effect on sea-level projections and parameter distributions by using a simple semi-empirical sea-level model. Specifically, we compare three model-fitting methods: a frequentistmore » bootstrap as well as a Bayesian inversion with and without considering heteroskedastic residuals. All methods produce comparable hindcasts, but the parametric distributions and projections differ considerably based on methodological choices. In conclusion, our results show that the differences based on the methodological choices are enhanced in the upper tail projections. For example, the Bayesian inversion accounting for heteroskedasticity increases the sea-level anomaly with a 1% probability of being equaled or exceeded in the year 2050 by about 34% and about 40% in the year 2100 compared to a frequentist bootstrap. These results indicate that neglecting known properties of the observation errors and the data-model residuals can lead to low-biased sea-level projections.« less
The effects of time-varying observation errors on semi-empirical sea-level projections

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

Ruckert, Kelsey L.; Guan, Yawen; Bakker, Alexander M. R.

Sea-level rise is a key driver of projected flooding risks. The design of strategies to manage these risks often hinges on projections that inform decision-makers about the surrounding uncertainties. Producing semi-empirical sea-level projections is difficult, for example, due to the complexity of the error structure of the observations, such as time-varying (heteroskedastic) observation errors and autocorrelation of the data-model residuals. This raises the question of how neglecting the error structure impacts hindcasts and projections. Here, we quantify this effect on sea-level projections and parameter distributions by using a simple semi-empirical sea-level model. Specifically, we compare three model-fitting methods: a frequentistmore » bootstrap as well as a Bayesian inversion with and without considering heteroskedastic residuals. All methods produce comparable hindcasts, but the parametric distributions and projections differ considerably based on methodological choices. In conclusion, our results show that the differences based on the methodological choices are enhanced in the upper tail projections. For example, the Bayesian inversion accounting for heteroskedasticity increases the sea-level anomaly with a 1% probability of being equaled or exceeded in the year 2050 by about 34% and about 40% in the year 2100 compared to a frequentist bootstrap. These results indicate that neglecting known properties of the observation errors and the data-model residuals can lead to low-biased sea-level projections.« less
Modeling a Common-Source Amplifier Using a Ferroelectric Transistor

NASA Technical Reports Server (NTRS)

Sayyah, Rana; Hunt, Mitchell; MacLeond, Todd C.; Ho, Fat D.

2010-01-01

This paper presents a mathematical model characterizing the behavior of a common-source amplifier using a FeFET. The model is based on empirical data and incorporates several variables that affect the output, including frequency, load resistance, and gate-to-source voltage. Since the common-source amplifier is the most widely used amplifier in MOS technology, understanding and modeling the behavior of the FeFET-based common-source amplifier will help in the integration of FeFETs into many circuits.
Hurricane Sandy Economic Impacts Assessment: A Computable General Equilibrium Approach and Validation

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

Boero, Riccardo; Edwards, Brian Keith

Economists use computable general equilibrium (CGE) models to assess how economies react and self-organize after changes in policies, technology, and other exogenous shocks. CGE models are equation-based, empirically calibrated, and inspired by Neoclassical economic theory. The focus of this work was to validate the National Infrastructure Simulation and Analysis Center (NISAC) CGE model and apply it to the problem of assessing the economic impacts of severe events. We used the 2012 Hurricane Sandy event as our validation case. In particular, this work first introduces the model and then describes the validation approach and the empirical data available for studying themore » event of focus. Shocks to the model are then formalized and applied. Finally, model results and limitations are presented and discussed, pointing out both the model degree of accuracy and the assessed total damage caused by Hurricane Sandy.« less
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).
Optimal Sequential Rules for Computer-Based Instruction.

ERIC Educational Resources Information Center

Vos, Hans J.

1998-01-01

Formulates sequential rules for adapting the appropriate amount of instruction to learning needs in the context of computer-based instruction. Topics include Bayesian decision theory, threshold and linear-utility structure, psychometric model, optimal sequential number of test questions, and an empirical example of sequential instructional…
A global empirical system for probabilistic seasonal climate prediction

NASA Astrophysics Data System (ADS)

Eden, J. M.; van Oldenborgh, G. J.; Hawkins, E.; Suckling, E. B.

2015-12-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.
An empirical system for probabilistic seasonal climate prediction

NASA Astrophysics Data System (ADS)

Eden, Jonathan; van Oldenborgh, Geert Jan; Hawkins, Ed; Suckling, Emma

2016-04-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.
Modelling nanoscale objects in order to conduct an empirical research into their properties as part of an engineering system designed

NASA Astrophysics Data System (ADS)

Makarov, M.; Shchanikov, S.; Trantina, N.

2017-01-01

We have conducted a research into the major, in terms of their future application, properties of nanoscale objects, based on modelling these objects as free-standing physical elements beyond the structure of an engineering system designed for their integration as well as a part of a system that operates under the influence of the external environment. For the empirical research suggested within the scope of this work, we have chosen a nanoscale electronic element intended to be used while designing information processing systems with the parallel architecture - a memristor. The target function of the research was to provide the maximum fault-tolerance index of a memristor-based system when affected by all possible impacts of the internal destabilizing factors and external environment. The research results have enabled us to receive and classify all the factors predetermining the fault-tolerance index of the hardware implementation of a computing system based on the nanoscale electronic element base.
Volatility in financial markets: stochastic models and empirical results

NASA Astrophysics Data System (ADS)

Miccichè, Salvatore; Bonanno, Giovanni; Lillo, Fabrizio; Mantegna, Rosario N.

2002-11-01

We investigate the historical volatility of the 100 most capitalized stocks traded in US equity markets. An empirical probability density function (pdf) of volatility is obtained and compared with the theoretical predictions of a lognormal model and of the Hull and White model. The lognormal model well describes the pdf in the region of low values of volatility whereas the Hull and White model better approximates the empirical pdf for large values of volatility. Both models fail in describing the empirical pdf over a moderately large volatility range.
Complex systems approach to scientific publication and peer-review system: development of an agent-based model calibrated with empirical journal data.

PubMed

Kovanis, Michail; Porcher, Raphaël; Ravaud, Philippe; Trinquart, Ludovic

Scientific peer-review and publication systems incur a huge burden in terms of costs and time. Innovative alternatives have been proposed to improve the systems, but assessing their impact in experimental studies is not feasible at a systemic level. We developed an agent-based model by adopting a unified view of peer review and publication systems and calibrating it with empirical journal data in the biomedical and life sciences. We modeled researchers, research manuscripts and scientific journals as agents. Researchers were characterized by their scientific level and resources, manuscripts by their scientific value, and journals by their reputation and acceptance or rejection thresholds. These state variables were used in submodels for various processes such as production of articles, submissions to target journals, in-house and external peer review, and resubmissions. We collected data for a sample of biomedical and life sciences journals regarding acceptance rates, resubmission patterns and total number of published articles. We adjusted submodel parameters so that the agent-based model outputs fit these empirical data. We simulated 105 journals, 25,000 researchers and 410,000 manuscripts over 10 years. A mean of 33,600 articles were published per year; 19 % of submitted manuscripts remained unpublished. The mean acceptance rate was 21 % after external peer review and rejection rate 32 % after in-house review; 15 % publications resulted from the first submission, 47 % the second submission and 20 % the third submission. All decisions in the model were mainly driven by the scientific value, whereas journal targeting and persistence in resubmission defined whether a manuscript would be published or abandoned after one or many rejections. This agent-based model may help in better understanding the determinants of the scientific publication and peer-review systems. It may also help in assessing and identifying the most promising alternative systems of peer review.
Sticky knowledge: A possible model for investigating implementation in healthcare contexts

PubMed Central

Elwyn, Glyn; Taubert, Mark; Kowalczuk, Jenny

2007-01-01

Background In health care, a well recognized gap exists between what we know should be done based on accumulated evidence and what we actually do in practice. A body of empirical literature shows organizations, like individuals, are difficult to change. In the business literature, knowledge management and transfer has become an established area of theory and practice, whilst in healthcare it is only starting to establish a firm footing. Knowledge has become a business resource, and knowledge management theorists and practitioners have examined how knowledge moves in organisations, how it is shared, and how the return on knowledge capital can be maximised to create competitive advantage. New models are being considered, and we wanted to explore the applicability of one of these conceptual models to the implementation of evidence-based practice in healthcare systems. Methods The application of a conceptual model called sticky knowledge, based on an integration of communication theory and knowledge transfer milestones, into a scenario of attempting knowledge transfer in primary care. Results We describe Szulanski's model, the empirical work he conducted, and illustrate its potential applicability with a hypothetical healthcare example based on improving palliative care services. We follow a doctor through two different posts and analyse aspects of knowledge transfer in different primary care settings. The factors included in the sticky knowledge model include: causal ambiguity, unproven knowledge, motivation of source, credibility of source, recipient motivation, recipient absorptive capacity, recipient retentive capacity, barren organisational context, and arduous relationship between source and recipient. We found that we could apply all these factors to the difficulty of implementing new knowledge into practice in primary care settings. Discussion Szulanski argues that knowledge factors play a greater role in the success or failure of a knowledge transfer than has been suspected, and we consider that this conjecture requires further empirical work in healthcare settings. PMID:18096040
Evidence-Based Administration for Decision Making in the Framework of Knowledge Strategic Management

ERIC Educational Resources Information Center

Del Junco, Julio Garcia; Zaballa, Rafael De Reyna; de Perea, Juan Garcia Alvarez

2010-01-01

Purpose: This paper seeks to present a model based on evidence-based administration (EBA), which aims to facilitate the creation, transformation and diffusion of knowledge in learning organizations. Design/methodology/approach: A theoretical framework is proposed based on EBA and the case method. Accordingly, an empirical study was carried out in…
Evaluation and parameterization of ATCOR3 topographic correction method for forest cover mapping in mountain areas

NASA Astrophysics Data System (ADS)

Balthazar, Vincent; Vanacker, Veerle; Lambin, Eric F.

2012-08-01

A topographic correction of optical remote sensing data is necessary to improve the quality of quantitative forest cover change analyses in mountainous terrain. The implementation of semi-empirical correction methods requires the calibration of model parameters that are empirically defined. This study develops a method to improve the performance of topographic corrections for forest cover change detection in mountainous terrain through an iterative tuning method of model parameters based on a systematic evaluation of the performance of the correction. The latter was based on: (i) the general matching of reflectances between sunlit and shaded slopes and (ii) the occurrence of abnormal reflectance values, qualified as statistical outliers, in very low illuminated areas. The method was tested on Landsat ETM+ data for rough (Ecuadorian Andes) and very rough mountainous terrain (Bhutan Himalayas). Compared to a reference level (no topographic correction), the ATCOR3 semi-empirical correction method resulted in a considerable reduction of dissimilarities between reflectance values of forested sites in different topographic orientations. Our results indicate that optimal parameter combinations are depending on the site, sun elevation and azimuth and spectral conditions. We demonstrate that the results of relatively simple topographic correction methods can be greatly improved through a feedback loop between parameter tuning and evaluation of the performance of the correction model.
Recent Advances in Model-Assisted Probability of Detection

NASA Technical Reports Server (NTRS)

Thompson, R. Bruce; Brasche, Lisa J.; Lindgren, Eric; Swindell, Paul; Winfree, William P.

2009-01-01

The increased role played by probability of detection (POD) in structural integrity programs, combined with the significant time and cost associated with the purely empirical determination of POD, provides motivation for alternate means to estimate this important metric of NDE techniques. One approach to make the process of POD estimation more efficient is to complement limited empirical experiments with information from physics-based models of the inspection process or controlled laboratory experiments. The Model-Assisted Probability of Detection (MAPOD) Working Group was formed by the Air Force Research Laboratory, the FAA Technical Center, and NASA to explore these possibilities. Since the 2004 inception of the MAPOD Working Group, 11 meetings have been held in conjunction with major NDE conferences. This paper will review the accomplishments of this group, which includes over 90 members from around the world. Included will be a discussion of strategies developed to combine physics-based and empirical understanding, draft protocols that have been developed to guide application of the strategies, and demonstrations that have been or are being carried out in a number of countries. The talk will conclude with a discussion of future directions, which will include documentation of benefits via case studies, development of formal protocols for engineering practice, as well as a number of specific technical issues.
Population consequences of aggregative movement

Treesearch

Peter Turchin

1989-01-01

Gregarious behaviour is an important factor influencing survival and reproduction of animals, as well as population interactions. In this paper I develop a model of movement with attraction or repulsion between conspecifics. To facilitate its use in empirical studies, the model is based on experimentally measurable features of individual behaviour.
Consumer involvement in seafood as family meals in Norway: an application of the expectancy-value approach.

PubMed

Olsen, S O

2001-04-01

A theoretical model of involvement in consumption of food products was tested in a representative survey of Norwegian households for the particular case of consuming seafood as a common family meal. The empirical study is based on using structural equation approach to test construct validity of measures and the empirical fit of the theoretical model. Attitudes, negative feelings, social norms and moral obligation were proved to be important, reliable and different constructs and explained 63% of the variation in seafood involvement. Negative feelings and moral obligation was the most important antecedents of involvement. Both our proposed model and modified model with seafood involvement as a mediator fit well with the data and proved our expectations in a promising way. Copyright 2001 Academic Press.
Assessing the accuracy of improved force-matched water models derived from Ab initio molecular dynamics simulations.

PubMed

Köster, Andreas; Spura, Thomas; Rutkai, Gábor; Kessler, Jan; Wiebeler, Hendrik; Vrabec, Jadran; Kühne, Thomas D

2016-07-15

The accuracy of water models derived from ab initio molecular dynamics simulations by means on an improved force-matching scheme is assessed for various thermodynamic, transport, and structural properties. It is found that although the resulting force-matched water models are typically less accurate than fully empirical force fields in predicting thermodynamic properties, they are nevertheless much more accurate than generally appreciated in reproducing the structure of liquid water and in fact superseding most of the commonly used empirical water models. This development demonstrates the feasibility to routinely parametrize computationally efficient yet predictive potential energy functions based on accurate ab initio molecular dynamics simulations for a large variety of different systems. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Regionally Adaptable Ground Motion Prediction Equation (GMPE) from Empirical Models of Fourier and Duration of Ground Motion

NASA Astrophysics Data System (ADS)

Bora, Sanjay; Scherbaum, Frank; Kuehn, Nicolas; Stafford, Peter; Edwards, Benjamin

2016-04-01

The current practice of deriving empirical ground motion prediction equations (GMPEs) involves using ground motions recorded at multiple sites. However, in applications like site-specific (e.g., critical facility) hazard ground motions obtained from the GMPEs are need to be adjusted/corrected to a particular site/site-condition under investigation. This study presents a complete framework for developing a response spectral GMPE, within which the issue of adjustment of ground motions is addressed in a manner consistent with the linear system framework. The present approach is a two-step process in which the first step consists of deriving two separate empirical models, one for Fourier amplitude spectra (FAS) and the other for a random vibration theory (RVT) optimized duration (Drvto) of ground motion. In the second step the two models are combined within the RVT framework to obtain full response spectral amplitudes. Additionally, the framework also involves a stochastic model based extrapolation of individual Fourier spectra to extend the useable frequency limit of the empirically derived FAS model. The stochastic model parameters were determined by inverting the Fourier spectral data using an approach similar to the one as described in Edwards and Faeh (2013). Comparison of median predicted response spectra from present approach with those from other regional GMPEs indicates that the present approach can also be used as a stand-alone model. The dataset used for the presented analysis is a subset of the recently compiled database RESORCE-2012 across Europe, the Middle East and the Mediterranean region.
Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state: Pumas as a case study

Treesearch

Katherine A. Zeller; Kevin McGarigal; Paul Beier; Samuel A. Cushman; T. Winston Vickers; Walter M. Boyce

2014-01-01

Estimating landscape resistance to animal movement is the foundation for connectivity modeling, and resource selection functions based on point data are commonly used to empirically estimate resistance. In this study, we used GPS data points acquired at 5-min intervals from radiocollared pumas in southern California to model context-dependent point selection...
Effectiveness of an Asynchronous Online Module on University Students' Understanding of the Bohr Model of the Hydrogen Atom

ERIC Educational Resources Information Center

Farina, William J., Jr.; Bodzin, Alec M.

2018-01-01

Web-based learning is a growing field in education, yet empirical research into the design of high quality Web-based university science instruction is scarce. A one-week asynchronous online module on the Bohr Model of the atom was developed and implemented guided by the knowledge integration framework. The unit design aligned with three identified…
Effects of streamflow diversion on a fish population: combining empirical data and individual-based models in a site-specific evaluation

Treesearch

Bret C. Harvey; Jason L. White; Rodney J. Nakamoto; Steven F. Railsback

2014-01-01

Resource managers commonly face the need to evaluate the ecological consequences of specific water diversions of small streams. We addressed this need by conducting 4 years of biophysical monitoring of stream reaches above and below a diversion and applying two individual-based models of salmonid fish that simulated different levels of behavioral complexity. The...
Emirates Mars Ultraviolet Spectrometer's (EMUS) Prediction of Oxygen OI 135.6 nm and CO 4PG Emissions in the Martian Atmosphere

NASA Astrophysics Data System (ADS)

Almatroushi, H. R.; Lootah, F. H.; Deighan, J.; Fillingim, M. O.; Jain, S.; Bougher, S. W.; England, S.; Schneider, N. M.

2017-12-01

This research focuses on developing empirical and theoretical models for OI 135.6 nm and CO 4PG band system FUV dayglow emissions in the Martian thermosphere as predicted to be seen from the Emirates Mars Ultraviolet Spectrometer (EMUS), one of the three scientific instruments aboard the Emirates Mars Mission (EMM) to be launched in 2020. These models will aid in simulating accurate disk radiances which will be utilized as an input to an EMUS instrument simulator. The developed zonally averaged empirical models are based on FUV data from the IUVS instrument onboard the MAVEN mission, while the theoretical models are based on a basic Chapman profile. The models calculate the brightness (B) of those emissions taking into consideration observation geometry parameters such as emission angle (EA), solar zenith angle (SZA) and planet distance from the sun (Ds). Specifically, the empirical models takes a general form of Bn=A*cos(SZA)n/cos(EA)m , where Bn is the normalized brightness value of an emission feature, and A, n, and m are positive constant values. The model form shows that the brightness has a positive correlation with EA and a negative correlation with SZA. A comparison of both models are explained in this research while examining full Mars and half Mars disk images generated using geometry code specially developed for the EMUS instrument. Sensitivity analyses have also been conducted for the theoretical modeling to observe the contributions of electron impact on atomic oxygen and CO2 to the brightness of OI 135.6nm, in addition to the effect of electron temperature on the CO2± dissociative recombination contribution to the CO 4PG band system.
Semi-empirical master curve concept describing the rate capability of lithium insertion electrodes

NASA Astrophysics Data System (ADS)

Heubner, C.; Seeba, J.; Liebmann, T.; Nickol, A.; Börner, S.; Fritsch, M.; Nikolowski, K.; Wolter, M.; Schneider, M.; Michaelis, A.

2018-03-01

A simple semi-empirical master curve concept, describing the rate capability of porous insertion electrodes for lithium-ion batteries, is proposed. The model is based on the evaluation of the time constants of lithium diffusion in the liquid electrolyte and the solid active material. This theoretical approach is successfully verified by comprehensive experimental investigations of the rate capability of a large number of porous insertion electrodes with various active materials and design parameters. It turns out, that the rate capability of all investigated electrodes follows a simple master curve governed by the time constant of the rate limiting process. We demonstrate that the master curve concept can be used to determine optimum design criteria meeting specific requirements in terms of maximum gravimetric capacity for a desired rate capability. The model further reveals practical limits of the electrode design, attesting the empirically well-known and inevitable tradeoff between energy and power density.
Semi-Empirical Prediction of Aircraft Low-Speed Aerodynamic Characteristics

NASA Technical Reports Server (NTRS)

Olson, Erik D.

2015-01-01

This paper lays out a comprehensive methodology for computing a low-speed, high-lift polar, without requiring additional details about the aircraft design beyond what is typically available at the conceptual design stage. Introducing low-order, physics-based aerodynamic analyses allows the methodology to be more applicable to unconventional aircraft concepts than traditional, fully-empirical methods. The methodology uses empirical relationships for flap lift effectiveness, chord extension, drag-coefficient increment and maximum lift coefficient of various types of flap systems as a function of flap deflection, and combines these increments with the characteristics of the unflapped airfoils. Once the aerodynamic characteristics of the flapped sections are known, a vortex-lattice analysis calculates the three-dimensional lift, drag and moment coefficients of the whole aircraft configuration. This paper details the results of two validation cases: a supercritical airfoil model with several types of flaps; and a 12-foot, full-span aircraft model with slats and double-slotted flaps.
Advances in the Application of Decision Theory to Test-Based Decision Making.

ERIC Educational Resources Information Center

van der Linden, Wim J.

This paper reviews recent research in the Netherlands on the application of decision theory to test-based decision making about personnel selection and student placement. The review is based on an earlier model proposed for the classification of decision problems, and emphasizes an empirical Bayesian framework. Classification decisions with…
Mechanisms of Power within a Community-Based Food Security Planning Process

ERIC Educational Resources Information Center

McCullum, Christine; Pelletier, David; Barr, Donald; Wilkins, Jennifer; Habicht, Jean-Pierre

2004-01-01

A community food security movement has begun to address problems of hunger and food insecurity by utilizing a community-based approach. Although various models have been implemented, little empirical research has assessed how power operates within community-based food security initiatives. The purpose of this research was to determine how power…
Empirically Supported Family-Based Treatments for Conduct Disorder and Delinquency in Adolescents

ERIC Educational Resources Information Center

Henggeler, Scott W.; Sheidow, Ashli J.

2012-01-01

Several family-based treatments of conduct disorder and delinquency in adolescents have emerged as evidence-based and, in recent years, have been transported to more than 800 community practice settings. These models include multisystemic therapy, functional family therapy, multidimensional treatment foster care, and, to a lesser extent, brief…
The Philosophy, Theoretical Bases, and Implementation of the AHAAH Model for Evaluation of Hazard from Exposure to Intense Sounds

DTIC Science & Technology

2018-04-01

empirical, external energy-damage correlation methods for evaluating hearing damage risk associated with impulsive noise exposure. AHAAH applies the...is validated against the measured results of human exposures to impulsive sounds, and unlike wholly empirical correlation approaches, AHAAH’s...a measured level (LAEQ8 of 85 dB). The approach in MIL-STD-1474E is very different. Previous standards tried to find a correlation between some
Investigating the empirical support for therapeutic targets proposed by the temporal experience of pleasure model in schizophrenia: A systematic review.

PubMed

Edwards, Clementine J; Cella, Matteo; Tarrier, Nicholas; Wykes, Til

2015-10-01

Anhedonia and amotivation are substantial predictors of poor functional outcomes in people with schizophrenia and often present a formidable barrier to returning to work or building relationships. The Temporal Experience of Pleasure Model proposes constructs which should be considered therapeutic targets for these symptoms in schizophrenia e.g. anticipatory pleasure, memory, executive functions, motivation and behaviours related to the activity. Recent reviews have highlighted the need for a clear evidence base to drive the development of targeted interventions. To review systematically the empirical evidence for each TEP model component and propose evidence-based therapeutic targets for anhedonia and amotivation in schizophrenia. Following PRISMA guidelines, PubMed and PsycInfo were searched using the terms "schizophrenia" and "anhedonia". Studies were included if they measured anhedonia and participants had a diagnosis of schizophrenia. The methodology, measures and main findings from each study were extracted and critically summarised for each TEP model construct. 80 independent studies were reviewed and executive functions, emotional memory and the translation of motivation into actions are highlighted as key deficits with a strong evidence base in people with schizophrenia. However, there are many relationships that are unclear because the empirical work is limited by over-general tasks and measures. Promising methods for research which have more ecological validity include experience sampling and behavioural tasks assessing motivation. Specific adaptations to Cognitive Remediation Therapy, Cognitive Behavioural Therapy and the utilisation of mobile technology to enhance representations and emotional memory are recommended for future development. Copyright © 2015. Published by Elsevier B.V.
Verification of GCM-generated regional seasonal precipitation for current climate and of statistical downscaling estimates under changing climate conditions

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

Busuioc, A.; Storch, H. von; Schnur, R.

Empirical downscaling procedures relate large-scale atmospheric features with local features such as station rainfall in order to facilitate local scenarios of climate change. The purpose of the present paper is twofold: first, a downscaling technique is used as a diagnostic tool to verify the performance of climate models on the regional scale; second, a technique is proposed for verifying the validity of empirical downscaling procedures in climate change applications. The case considered is regional seasonal precipitation in Romania. The downscaling model is a regression based on canonical correlation analysis between observed station precipitation and European-scale sea level pressure (SLP). Themore » climate models considered here are the T21 and T42 versions of the Hamburg ECHAM3 atmospheric GCM run in time-slice mode. The climate change scenario refers to the expected time of doubled carbon dioxide concentrations around the year 2050. Generally, applications of statistical downscaling to climate change scenarios have been based on the assumption that the empirical link between the large-scale and regional parameters remains valid under a changed climate. In this study, a rationale is proposed for this assumption by showing the consistency of the 2 x CO{sub 2} GCM scenarios in winter, derived directly from the gridpoint data, with the regional scenarios obtained through empirical downscaling. Since the skill of the GCMs in regional terms is already established, it is concluded that the downscaling technique is adequate for describing climatically changing regional and local conditions, at least for precipitation in Romania during winter.« less
An improved empirical model of electron and ion fluxes at geosynchronous orbit based on upstream solar wind conditions

DOE PAGES

Denton, M. H.; Henderson, M. G.; Jordanova, V. K.; ...

2016-07-01

In this study, a new empirical model of the electron fluxes and ion fluxes at geosynchronous orbit (GEO) is introduced, based on observations by Los Alamos National Laboratory (LANL) satellites. The model provides flux predictions in the energy range ~1 eV to ~40 keV, as a function of local time, energy, and the strength of the solar wind electric field (the negative product of the solar wind speed and the z component of the magnetic field). Given appropriate upstream solar wind measurements, the model provides a forecast of the fluxes at GEO with a ~1 h lead time. Model predictionsmore » are tested against in-sample observations from LANL satellites and also against out-of-sample observations from the Compact Environmental Anomaly Sensor II detector on the AMC-12 satellite. The model does not reproduce all structure seen in the observations. However, for the intervals studied here (quiet and storm times) the normalized root-mean-square deviation < ~0.3. It is intended that the model will improve forecasting of the spacecraft environment at GEO and also provide improved boundary/input conditions for physical models of the magnetosphere.« less
Enhancing the Impact of Family Justice Centers via Motivational Interviewing: An Integrated Review.

PubMed

Simmons, Catherine A; Howell, Kathryn H; Duke, Michael R; Beck, J Gayle

2016-12-01

The Family Justice Center (FJC) model is an approach to assisting survivors of intimate partner violence (IPV) that focuses on integration of services under one roof and co-location of staff members from a range of multidisciplinary agencies. Even though the FJC model is touted as a best practice strategy to help IPV survivors, empirical support for the effectiveness of this approach is scarce. The current article consolidates this small yet promising body of empirically based literature in a clinically focused review. Findings point to the importance of integrating additional resources into the FJC model to engage IPV survivors who have ambivalent feelings about whether to accept help, leave the abusive relationship, and/or participate in criminal justice processes to hold the offender accountable. One such resource, motivational interviewing (MI), holds promise in aiding IPV survivors with these decisions, but empirical investigation into how MI can be incorporated into the FJC model has yet to be published. This article, therefore, also integrates the body of literature supporting the FJC model with the body of literature supporting MI with IPV survivors. Implications for practice, policy, and research are incorporated throughout this review. © The Author(s) 2015.
Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

NASA Astrophysics Data System (ADS)

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.
Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

PubMed

Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

2017-01-04

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.
Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

PubMed Central

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O’Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike. PMID:28051123
Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting

NASA Astrophysics Data System (ADS)

Zhang, Ningning; Lin, Aijing; Shang, Pengjian

2017-07-01

In this paper, we propose a new two-stage methodology that combines the ensemble empirical mode decomposition (EEMD) with multidimensional k-nearest neighbor model (MKNN) in order to forecast the closing price and high price of the stocks simultaneously. The modified algorithm of k-nearest neighbors (KNN) has an increasingly wide application in the prediction of all fields. Empirical mode decomposition (EMD) decomposes a nonlinear and non-stationary signal into a series of intrinsic mode functions (IMFs), however, it cannot reveal characteristic information of the signal with much accuracy as a result of mode mixing. So ensemble empirical mode decomposition (EEMD), an improved method of EMD, is presented to resolve the weaknesses of EMD by adding white noise to the original data. With EEMD, the components with true physical meaning can be extracted from the time series. Utilizing the advantage of EEMD and MKNN, the new proposed ensemble empirical mode decomposition combined with multidimensional k-nearest neighbor model (EEMD-MKNN) has high predictive precision for short-term forecasting. Moreover, we extend this methodology to the case of two-dimensions to forecast the closing price and high price of the four stocks (NAS, S&P500, DJI and STI stock indices) at the same time. The results indicate that the proposed EEMD-MKNN model has a higher forecast precision than EMD-KNN, KNN method and ARIMA.
Worrying trends in econophysics

NASA Astrophysics Data System (ADS)

Gallegati, Mauro; Keen, Steve; Lux, Thomas; Ormerod, Paul

2006-10-01

Econophysics has already made a number of important empirical contributions to our understanding of the social and economic world. These fall mainly into the areas of finance and industrial economics, where in each case there is a large amount of reasonably well-defined data. More recently, Econophysics has also begun to tackle other areas of economics where data is much more sparse and much less reliable. In addition, econophysicists have attempted to apply the theoretical approach of statistical physics to try to understand empirical findings. Our concerns are fourfold. First, a lack of awareness of work that has been done within economics itself. Second, resistance to more rigorous and robust statistical methodology. Third, the belief that universal empirical regularities can be found in many areas of economic activity. Fourth, the theoretical models which are being used to explain empirical phenomena. The latter point is of particular concern. Essentially, the models are based upon models of statistical physics in which energy is conserved in exchange processes. There are examples in economics where the principle of conservation may be a reasonable approximation to reality, such as primitive hunter-gatherer societies. But in the industrialised capitalist economies, income is most definitely not conserved. The process of production and not exchange is responsible for this. Models which focus purely on exchange and not on production cannot by definition offer a realistic description of the generation of income in the capitalist, industrialised economies.

Statistical microeconomics and commodity prices: theory and empirical results.

PubMed

Baaquie, Belal E

2016-01-13

A review is made of the statistical generalization of microeconomics by Baaquie (Baaquie 2013 Phys. A 392, 4400-4416. (doi:10.1016/j.physa.2013.05.008)), where the market price of every traded commodity, at each instant of time, is considered to be an independent random variable. The dynamics of commodity market prices is given by the unequal time correlation function and is modelled by the Feynman path integral based on an action functional. The correlation functions of the model are defined using the path integral. The existence of the action functional for commodity prices that was postulated to exist in Baaquie (Baaquie 2013 Phys. A 392, 4400-4416. (doi:10.1016/j.physa.2013.05.008)) has been empirically ascertained in Baaquie et al. (Baaquie et al. 2015 Phys. A 428, 19-37. (doi:10.1016/j.physa.2015.02.030)). The model's action functionals for different commodities has been empirically determined and calibrated using the unequal time correlation functions of the market commodity prices using a perturbation expansion (Baaquie et al. 2015 Phys. A 428, 19-37. (doi:10.1016/j.physa.2015.02.030)). Nine commodities drawn from the energy, metal and grain sectors are empirically studied and their auto-correlation for up to 300 days is described by the model to an accuracy of R(2)>0.90-using only six parameters. © 2015 The Author(s).
Elastohydrodynamic film thickness model for heavily loaded contacts

NASA Technical Reports Server (NTRS)

Loewenthal, S. H.; Parker, R. J.; Zaretsky, E. V.

1973-01-01

An empirical elastohydrodynamic (EHD) film thickness formula for predicting the minimum film thickness occurring within heavily loaded contacts (maximum Hertz stresses above 150,000 psi) was developed. The formula was based upon X-ray film thickness measurements made with synthetic paraffinic, fluorocarbon, Type II ester and polyphenyl ether fluids covering a wide range of test conditions. Comparisons were made between predictions from an isothermal EHD theory and the test data. The deduced relationship was found to adequately reflect the high-load dependence exhibited by the measured data. The effects of contact geometry, material and lubricant properties on the form of the empirical model are also discussed.
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.
A New Global Empirical Model of the Electron Temperature with the Inclusion of the Solar Activity Variations for IRI

NASA Technical Reports Server (NTRS)

Truhlik, V.; Triskova, L.

2012-01-01

A data-base of electron temperature (T(sub e)) comprising of most of the available LEO satellite measurements in the altitude range from 350 to 2000 km has been used for the development of a new global empirical model of T(sub e) for the International Reference Ionosphere (IRI). For the first time this will include variations with solar activity. Variations at five fixed altitude ranges centered at 350, 550, 850, 1400, and 2000 km and three seasons (summer, winter, and equinox) were represented by a system of associated Legendre polynomials (up to the 8th order) in terms of magnetic local time and the earlier introduced in vdip latitude. The solar activity variations of T(sub e) are represented by a correction term of the T(sub e) global pattern and it has been derived from the empirical latitudinal profiles of T(sub e) for day and night (Truhlik et al., 2009a). Comparisons of the new T(sub e) model with data and with the IRI 2007 Te model show that the new model agrees well with the data generally within standard deviation limits and that the model performs better than the current IRI T(sub e) model.
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.
Predicting overload-affected fatigue crack growth in steels

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

Skorupa, M.; Skorupa, A.; Ladecki, B.

1996-12-01

The ability of semi-empirical crack closure models to predict the effect of overloads on fatigue crack growth in low-alloy steels has been investigated. With this purpose, the CORPUS model developed for aircraft metals and spectra has been checked first through comparisons between the simulated and observed results for a low-alloy steel. The CORPUS predictions of crack growth under several types of simple load histories containing overloads appeared generally unconservative which prompted the authors to formulate a new model, more suitable for steels. With the latter approach, the assumed evolution of the crack opening stress during the delayed retardation stage hasmore » been based on experimental results reported for various steels. For all the load sequences considered, the predictions from the proposed model appeared to be by far more accurate than those from CORPUS. Based on the analysis results, the capability of semi-empirical prediction concepts to cover experimentally observed trends that have been reported for sequences with overloads is discussed. Finally, possibilities of improving the model performance are considered.« less
Application of natural analog studies to exploration for ore deposits

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

Gustafson, D.L.

1995-09-01

Natural analogs are viewed as similarities in nature and are routinely utilized by exploration geologists in their search for economic mineral deposits. Ore deposit modeling is undertaken by geologists to direct their exploration activities toward favorable geologic environments and, therefore, successful programs. Two types of modeling are presented: (i) empirical model development based on the study of known ore deposit characteristics, and (ii) concept model development based on theoretical considerations and field observations that suggest a new deposit type, not known to exist in nature, may exist and justifies an exploration program. Key elements that are important in empirical modelmore » development are described, and examples of successful applications of these natural analogs to exploration are presented. A classical example of successful concept model development, the discovery of the McLaughlin gold mine in California, is presented. The utilization of natural analogs is an important facet of mineral exploration. Natural analogs guide explorationists in their search for new discoveries, increase the probability of success, and may decrease overall exploration expenditure.« less
Polarimetry noise in fiber-based optical coherence tomography instrumentation

PubMed Central

Zhang, Ellen Ziyi; Vakoc, Benjamin J.

2011-01-01

High noise levels in fiber-based polarization-sensitive optical coherence tomography (PS-OCT) have broadly limited its clinical utility. In this study we investigate contribution of polarization mode dispersion (PMD) to the polarimetry noise. We develop numerical models of the PS-OCT system including PMD and validate these models with empirical data. Using these models, we provide a framework for predicting noise levels, for processing signals to reduce noise, and for designing an optimized system. PMID:21935044
Mesoscale Particle-Based Model of Electrophoresis

DOE PAGES

Giera, Brian; Zepeda-Ruiz, Luis A.; Pascall, Andrew J.; ...

2015-07-31

Here, we develop and evaluate a semi-empirical particle-based model of electrophoresis using extensive mesoscale simulations. We parameterize the model using only measurable quantities from a broad set of colloidal suspensions with properties that span the experimentally relevant regime. With sufficient sampling, simulated diffusivities and electrophoretic velocities match predictions of the ubiquitous Stokes-Einstein and Henry equations, respectively. This agreement holds for non-polar and aqueous solvents or ionic liquid colloidal suspensions under a wide range of applied electric fields.
Mesoscale Particle-Based Model of Electrophoresis

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

Giera, Brian; Zepeda-Ruiz, Luis A.; Pascall, Andrew J.

Here, we develop and evaluate a semi-empirical particle-based model of electrophoresis using extensive mesoscale simulations. We parameterize the model using only measurable quantities from a broad set of colloidal suspensions with properties that span the experimentally relevant regime. With sufficient sampling, simulated diffusivities and electrophoretic velocities match predictions of the ubiquitous Stokes-Einstein and Henry equations, respectively. This agreement holds for non-polar and aqueous solvents or ionic liquid colloidal suspensions under a wide range of applied electric fields.
Characteristics Of Ferroelectric Logic Gates Using a Spice-Based Model

NASA Technical Reports Server (NTRS)

MacLeod, Todd C.; Phillips, Thomas A.; Ho, Fat D.

2005-01-01

A SPICE-based model of an n-channel ferroelectric field effect transistor has been developed based on both theoretical and empirical data. This model was used to generate the I-V characteristic of several logic gates. The use of ferroelectric field effect transistors in memory circuits is being developed by several organizations. The use of FFETs in other circuits, both analog and digital needs to be better understood. The ability of FFETs to have different characteristics depending on the initial polarization can be used to create logic gates. These gates can have properties not available to standard CMOS logic gates, such as memory, reconfigurability and memory. This paper investigates basic properties of FFET logic gates. It models FFET inverter, NAND gate and multi-input NAND gate. The I-V characteristics of the gates are presented as well as transfer characteristics and timing. The model used is a SPICE-based model developed from empirical data from actual Ferroelectric transistors. It simulates all major characteristics of the ferroelectric transistor, including polarization, hysteresis and decay. Contrasts are made of the differences between FFET logic gates and CMOS logic gates. FFET parameters are varied to show the effect on the overall gate. A recodigurable gate is investigated which is not possible with CMOS circuits. The paper concludes that FFETs can be used in logic gates and have several advantages over standard CMOS gates.
New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.
The Teaching-Research Gestalt: The Development of a Discipline-Based Scale

ERIC Educational Resources Information Center

Duff, Angus; Marriott, Neil

2017-01-01

This paper reports the development and empirical testing of a model of the factors that influence the teaching-research nexus. No prior work has attempted to create a measurement model of the nexus. The conceptual model is derived from 19 propositions grouped into four sets of factors relating to: rewards, researchers, curriculum, and students.…
Predicting User Acceptance of Collaborative Technologies: An Extension of the Technology Acceptance Model for E-Learning

ERIC Educational Resources Information Center

Cheung, Ronnie; Vogel, Doug

2013-01-01

Collaborative technologies support group work in project-based environments. In this study, we enhance the technology acceptance model to explain the factors that influence the acceptance of Google Applications for collaborative learning. The enhanced model was empirically evaluated using survey data collected from 136 students enrolled in a…
Understanding Female Sport Attrition in a Stereotypical Male Sport within the Framework of Eccles's Expectancy-Value Model

ERIC Educational Resources Information Center

Guillet, Emma; Sarrazin, Philippe; Fontayne, Paul; Brustad, Robert J.

2006-01-01

An empirical research study based upon the expectancy-value model of Eccles and colleagues (1983) investigated the effect of gender-role orientations on psychological dimensions of female athletes' sport participation and the likelihood of their continued participation in a stereotypical masculine activity. The model (Eccles et al., 1983) posits…
CALCINATION AND SINTERING MODELS FOR APPLICATION TO HIGH-TEMPERATURE, SHORT-TIME SULFATION OF CALCIUM-BASED SORBENTS

EPA Science Inventory

To simulate the staged availability of transient high surface area CaO observed in high-temperature flow-reactor data, the rate of calcination of CaCO3 or Ca(OH)2 is described by an empirical modification of the shrinking-core model. The physical model depicts particle decomposi...
Ignition behavior of live California chaparral leaves

Treesearch

J.D. Engstrom; J.K Butler; S.G. Smith; L.L. Baxter; T.H. Fletcher; D.R. Weise

2004-01-01

Current forest fire models are largely empirical correlations based on data from beds of dead vegetation Improvement in model capabilities is sought by developing models of the combustion of live fuels. A facility was developed to determine the combustion behavior of small samples of live fuels, consisting of a flat-flame burner on a moveable platform Qualitative and...
Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization

PubMed Central

Cavagnaro, Daniel R.; Pitt, Mark A.; Gonzalez, Richard; Myung, Jay I.

2014-01-01

Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments to investigate the extent to which different parametric forms of the probability weighting function can be discriminated using adaptive design optimization, a computer-based methodology that identifies and exploits model differences for the purpose of model discrimination. The simulation experiments show that the correct (data-generating) form can be conclusively discriminated from its competitors. The results of an empirical experiment reveal heterogeneity between participants in terms of the functional form, with two models (Prelec-2, Linear in Log Odds) emerging as the most common best-fitting models. The findings shed light on assumptions underlying these models. PMID:24453406
An Empirical Human Controller Model for Preview Tracking Tasks.

PubMed

van der El, Kasper; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus Rene M; Mulder, Max

2016-11-01

Real-life tracking tasks often show preview information to the human controller about the future track to follow. The effect of preview on manual control behavior is still relatively unknown. This paper proposes a generic operator model for preview tracking, empirically derived from experimental measurements. Conditions included pursuit tracking, i.e., without preview information, and tracking with 1 s of preview. Controlled element dynamics varied between gain, single integrator, and double integrator. The model is derived in the frequency domain, after application of a black-box system identification method based on Fourier coefficients. Parameter estimates are obtained to assess the validity of the model in both the time domain and frequency domain. Measured behavior in all evaluated conditions can be captured with the commonly used quasi-linear operator model for compensatory tracking, extended with two viewpoints of the previewed target. The derived model provides new insights into how human operators use preview information in tracking tasks.
Regional TEC model under quiet geomagnetic conditions and low-to-moderate solar activity based on CODE GIMs

NASA Astrophysics Data System (ADS)

Feng, Jiandi; Jiang, Weiping; Wang, Zhengtao; Zhao, Zhenzhen; Nie, Linjuan

2017-08-01

Global empirical total electron content (TEC) models based on TEC maps effectively describe the average behavior of the ionosphere. However, the accuracy of these global models for a certain region may not be ideal. Due to the number and distribution of the International GNSS Service (IGS) stations, the accuracy of TEC maps is geographically different. The modeling database derived from the global TEC maps with different accuracy is likely one of the main reasons that limits the accuracy of the new models. Moreover, many anomalies in the ionosphere are geographic or geomagnetic dependent, and as such the accuracy of global models can deteriorate if these anomalies are not fully incorporated into the modeling approach. For regional models built in small areas, these influences on modeling are immensely weakened. Thus, the regional TEC models may better reflect the temporal and spatial variations of TEC. In our previous work (Feng et al., 2016), a regional TEC model TECM-NEC is proposed for northeast China. However, this model is only directed against the typical region of Mid-latitude Summer Nighttime Anomaly (MSNA) occurrence, which is meaningless in other regions without MSNA. Following the technique of TECM-NEC model, this study proposes another regional empirical TEC model for other regions in mid-latitudes. Taking a small area BeiJing-TianJin-Tangshan (JJT) region (37.5°-42.5° N, 115°-120° E) in China as an example, a regional empirical TEC model (TECM-JJT) is proposed using the TEC grid data from January 1, 1999 to June 30, 2015 provided by the Center for Orbit Determination in Europe (CODE) under quiet geomagnetic conditions. The TECM-JJT model fits the input CODE TEC data with a bias of 0.11TECU and a root mean square error of 3.26TECU. Result shows that the regional model TECM-JJT is consistent with CODE TEC data and GPS-TEC data.

Modeling Addictive Consumption as an Infectious Disease*

PubMed Central

Alamar, Benjamin; Glantz, Stanton A.

2011-01-01

The dominant model of addictive consumption in economics is the theory of rational addiction. The addict in this model chooses how much they are going to consume based upon their level of addiction (past consumption), the current benefits and all future costs. Several empirical studies of cigarette sales and price data have found a correlation between future prices and consumption and current consumption. These studies have argued that the correlation validates the rational addiction model and invalidates any model in which future consumption is not considered. An alternative to the rational addiction model is one in which addiction spreads through a population as if it were an infectious disease, as supported by the large body of empirical research of addictive behaviors. In this model an individual's probability of becoming addicted to a substance is linked to the behavior of their parents, friends and society. In the infectious disease model current consumption is based only on the level of addiction and current costs. Price and consumption data from a simulation of the infectious disease model showed a qualitative match to the results of the rational addiction model. The infectious disease model can explain all of the theoretical results of the rational addiction model with the addition of explaining initial consumption of the addictive good. PMID:21339848
Factorial Based Response Surface Modeling with Confidence Intervals for Optimizing Thermal Optical Transmission Analysis of Atmospheric Black Carbon

EPA Science Inventory

We demonstrate how thermal-optical transmission analysis (TOT) for refractory light-absorbing carbon in atmospheric particulate matter was optimized with empirical response surface modeling. TOT employs pyrolysis to distinguish the mass of black carbon (BC) from organic carbon (...
Model development and applications at the USDA-ARS National Soil Erosion Research Laboratory

USDA-ARS?s Scientific Manuscript database

The United States Department of Agriculture (USDA) has a long history of development of soil erosion prediction technology, initially with empirical equations like the Universal Soil Loss Equation (USLE), and more recently with process-based models such as the Water Erosion Prediction Project (WEPP)...
Empirically-based modeling and mapping to consider the co-occurrence of ecological receptors and stressors

EPA Science Inventory

Part of the ecological risk assessment process involves examining the potential for environmental stressors and ecological receptors to co-occur across a landscape. In this study, we introduce a Bayesian joint modeling framework for use in evaluating and mapping the co-occurrence...
Modelling Diffusion of a Personalized Learning Framework

ERIC Educational Resources Information Center

Karmeshu; Raman, Raghu; Nedungadi, Prema

2012-01-01

A new modelling approach for diffusion of personalized learning as an educational process innovation in social group comprising adopter-teachers is proposed. An empirical analysis regarding the perception of 261 adopter-teachers from 18 schools in India about a particular personalized learning framework has been made. Based on this analysis,…
Establishing an Explanatory Model for Mathematics Identity

ERIC Educational Resources Information Center

Cribbs, Jennifer D.; Hazari, Zahra; Sonnert, Gerhard; Sadler, Philip M.

2015-01-01

This article empirically tests a previously developed theoretical framework for mathematics identity based on students' beliefs. The study employs data from more than 9,000 college calculus students across the United States to build a robust structural equation model. While it is generally thought that students' beliefs about their own competence…
Combination of a Stressor-Response Model with a Conditional Probability Analysis Approach for Developing Candidate Criteria from MBSS

EPA Science Inventory

I show that a conditional probability analysis using a stressor-response model based on a logistic regression provides a useful approach for developing candidate water quality criteria from empirical data, such as the Maryland Biological Streams Survey (MBSS) data.
A temperature-precipitation-based model of thiry-year mean snowpack accumulation and melt in Oregon, USA

EPA Science Inventory

High-resolution, spatially extensive climate grids can be useful in regional hydrologic applications. However, in regions where precipitation is dominated by snow, snowmelt models are often used to account for timing and magnitude of water delivery. We developed an empirical, non...
Distributed Leadership as Work Redesign: Retrofitting the Job Characteristics Model

ERIC Educational Resources Information Center

Mayrowetz, David; Murphy, Joseph; Louis, Karen Seashore; Smylie, Mark A.

2007-01-01

In this article, we revive work redesign theory, specifically Hackman and Oldham's Job Characteristics Model (JCM), to examine distributed leadership initiatives. Based on our early observations of six schools engaged in distributed leadership reform and a broad review of literature, including empirical tests of work redesign theory, we retrofit…
Reflective equilibrium and empirical data: third person moral experiences in empirical medical ethics.

PubMed

De Vries, Martine; Van Leeuwen, Evert

2010-11-01

In ethics, the use of empirical data has become more and more popular, leading to a distinct form of applied ethics, namely empirical ethics. This 'empirical turn' is especially visible in bioethics. There are various ways of combining empirical research and ethical reflection. In this paper we discuss the use of empirical data in a special form of Reflective Equilibrium (RE), namely the Network Model with Third Person Moral Experiences. In this model, the empirical data consist of the moral experiences of people in a practice. Although inclusion of these moral experiences in this specific model of RE can be well defended, their use in the application of the model still raises important questions. What precisely are moral experiences? How to determine relevance of experiences, in other words: should there be a selection of the moral experiences that are eventually used in the RE? How much weight should the empirical data have in the RE? And the key question: can the use of RE by empirical ethicists really produce answers to practical moral questions? In this paper we start to answer the above questions by giving examples taken from our research project on understanding the norm of informed consent in the field of pediatric oncology. We especially emphasize that incorporation of empirical data in a network model can reduce the risk of self-justification and bias and can increase the credibility of the RE reached. © 2009 Blackwell Publishing Ltd.
Firm performance model in small and medium enterprises (SMEs) based on learning orientation and innovation

NASA Astrophysics Data System (ADS)

Lestari, E. R.; Ardianti, F. L.; Rachmawati, L.

2018-03-01

This study investigated the relationship between learning orientation, innovation, and firm performance. A conceptual model and hypothesis were empirically examined using structural equation modelling. The study involved a questionnaire-based survey of owners of small and medium enterprises (SMEs) operating in Batu City, Indonesia. The results showed that both variables of learning orientation and innovation effect positively on firm performance. Additionally, learning orientation has positive effect innovation. This study has implication for SMEs aiming at increasing their firm performance based on learning orientation and innovation capability.
Proposed Core Competencies and Empirical Validation Procedure in Competency Modeling: Confirmation and Classification

PubMed Central

Baczyńska, Anna K.; Rowiński, Tomasz; Cybis, Natalia

2016-01-01

Competency models provide insight into key skills which are common to many positions in an organization. Moreover, there is a range of competencies that is used by many companies. Researchers have developed core competency terminology to underline their cross-organizational value. The article presents a theoretical model of core competencies consisting of two main higher-order competencies called performance and entrepreneurship. Each of them consists of three elements: the performance competency includes cooperation, organization of work and goal orientation, while entrepreneurship includes innovativeness, calculated risk-taking and pro-activeness. However, there is lack of empirical validation of competency concepts in organizations and this would seem crucial for obtaining reliable results from organizational research. We propose a two-step empirical validation procedure: (1) confirmation factor analysis, and (2) classification of employees. The sample consisted of 636 respondents (M = 44.5; SD = 15.1). Participants were administered a questionnaire developed for the study purpose. The reliability, measured by Cronbach’s alpha, ranged from 0.60 to 0.83 for six scales. Next, we tested the model using a confirmatory factor analysis. The two separate, single models of performance and entrepreneurial orientations fit quite well to the data, while a complex model based on the two single concepts needs further research. In the classification of employees based on the two higher order competencies we obtained four main groups of employees. Their profiles relate to those found in the literature, including so-called niche finders and top performers. Some proposal for organizations is discussed. PMID:27014111
Modeling of Kerena Emergency Condenser

NASA Astrophysics Data System (ADS)

Bryk, Rafał; Schmidt, Holger; Mull, Thomas; Wagner, Thomas; Ganzmann, Ingo; Herbst, Oliver

2017-12-01

KERENA is an innovative boiling water reactor concept equipped with several passive safety systems. For the experimental verification of performance of the systems and for codes validation, the Integral Test Stand Karlstein (INKA) was built in Karlstein, Germany. The emergency condenser (EC) system transfers heat from the reactor pressure vessel (RPV) to the core flooding pool in case of water level decrease in the RPV. EC is composed of a large number of slightly inclined tubes. During accident conditions, steam enters into the tubes and condenses due to the contact of the tubes with cold water at the secondary side. The condensed water flows then back to the RPV due to gravity. In this paper two approaches for modeling of condensation in slightly inclined tubes are compared and verified against experiments. The first approach is based on the flow regime map. Depending on the regime, heat transfer coefficient is calculated according to specific semi-empirical correlation. The second approach uses a general, fully-empirical correlation. The models are developed with utilization of the object-oriented Modelica language and the open-source OpenModelica environment. The results are compared with data obtained during a large scale integral test, simulating loss of coolant accident performed at Integral Test Stand Karlstein (INKA). The comparison shows a good agreement.Due to the modularity of models, both of them may be used in the future in systems incorporating condensation in horizontal or slightly inclined tubes. Depending on his preferences, the modeller may choose one-equation based approach or more sophisticated model composed of several exchangeable semi-empirical correlations.
Development of Response Spectral Ground Motion Prediction Equations from Empirical Models for Fourier Spectra and Duration of Ground Motion

NASA Astrophysics Data System (ADS)

Bora, S. S.; Scherbaum, F.; Kuehn, N. M.; Stafford, P.; Edwards, B.

2014-12-01

In a probabilistic seismic hazard assessment (PSHA) framework, it still remains a challenge to adjust ground motion prediction equations (GMPEs) for application in different seismological environments. In this context, this study presents a complete framework for the development of a response spectral GMPE easily adjustable to different seismological conditions; and which does not suffer from the technical problems associated with the adjustment in response spectral domain. Essentially, the approach consists of an empirical FAS (Fourier Amplitude Spectrum) model and a duration model for ground motion which are combined within the random vibration theory (RVT) framework to obtain the full response spectral ordinates. Additionally, FAS corresponding to individual acceleration records are extrapolated beyond the frequency range defined by the data using the stochastic FAS model, obtained by inversion as described in Edwards & Faeh, (2013). To that end, an empirical model for a duration, which is tuned to optimize the fit between RVT based and observed response spectral ordinate, at each oscillator frequency is derived. Although, the main motive of the presented approach was to address the adjustability issues of response spectral GMPEs; comparison, of median predicted response spectra with the other regional models indicate that presented approach can also be used as a stand-alone model. Besides that, a significantly lower aleatory variability (σ<0.5 in log units) in comparison to other regional models, at shorter periods brands it to a potentially viable alternative to the classical regression (on response spectral ordinates) based GMPEs for seismic hazard studies in the near future. The dataset used for the presented analysis is a subset of the recently compiled database RESORCE-2012 across Europe, Middle East and the Mediterranean region.
Analytical Modeling of Pressure Wall Hole Size and Maximum Tip-to-Tip Crack Length for Perforating Normal and Oblique Orbital Debris Impacts

NASA Technical Reports Server (NTRS)

Schonberg, William P.; Mohamed, Essam

1997-01-01

This report presents the results of a study whose objective was to develop first-principles-based models of hole size and maximum tip-to-tip crack length for a spacecraft module pressure wall that has been perforated in an orbital debris particle impact. The hole size and crack length models are developed by sequentially characterizing the phenomena comprising the orbital debris impact event, including the initial impact, the creation and motion of a debris cloud within the dual-wall system, the impact of the debris cloud on the pressure wall, the deformation of the pressure wall due to debris cloud impact loading prior to crack formation, pressure wall crack initiation, propagation, and arrest, and finally pressure wall deformation following crack initiation and growth. The model development has been accomplished through the application of elementary shock physics and thermodynamic theory, as well as the principles of mass, momentum, and energy conservation. The predictions of the model developed herein are compared against the predictions of empirically-based equations for hole diameters and maximum tip-to-tip crack length for three International Space Station wall configurations. The ISS wall systems considered are the baseline U.S. Lab Cylinder, the enhanced U.S. Lab Cylinder, and the U.S. Lab Endcone. The empirical predictor equations were derived from experimentally obtained hole diameters and crack length data. The original model predictions did not compare favorably with the experimental data, especially for cases in which pressure wall petalling did not occur. Several modifications were made to the original model to bring its predictions closer in line with the experimental results. Following the adjustment of several empirical constants, the predictions of the modified analytical model were in much closer agreement with the experimental results.
Measurement invariance study of the training satisfaction questionnaire (TSQ).

PubMed

Sanduvete-Chaves, Susana; Holgado-Tello, F Pablo; Chacón-Moscoso, Salvador; Barbero-García, M Isabel

2013-01-01

This article presents an empirical measurement invariance study in the substantive area of satisfaction evaluation in training programs. Specifically, it (I) provides an empirical solution to the lack of explicit measurement models of satisfaction scales, offering a way of analyzing and operationalizing the substantive theoretical dimensions; (II) outlines and discusses the analytical consequences of considering the effects of categorizing supposedly continuous variables, which are not usually taken into account; (III) presents empirical results from a measurement invariance study based on 5,272 participants' responses to a training satisfaction questionnaire in three different organizations and in two different training methods, taking into account the factor structure of the measured construct and the ordinal nature of the recorded data; and (IV) describes the substantive implications in the area of training satisfaction evaluation, such as the usefulness of the training satisfaction questionnaire to measure satisfaction in different organizations and different training methods. It also discusses further research based on these findings.
Empirical Bayes estimation of proportions with application to cowbird parasitism rates

USGS Publications Warehouse

Link, W.A.; Hahn, D.C.

1996-01-01

Bayesian models provide a structure for studying collections of parameters such as are considered in the investigation of communities, ecosystems, and landscapes. This structure allows for improved estimation of individual parameters, by considering them in the context of a group of related parameters. Individual estimates are differentially adjusted toward an overall mean, with the magnitude of their adjustment based on their precision. Consequently, Bayesian estimation allows for a more credible identification of extreme values in a collection of estimates. Bayesian models regard individual parameters as values sampled from a specified probability distribution, called a prior. The requirement that the prior be known is often regarded as an unattractive feature of Bayesian analysis and may be the reason why Bayesian analyses are not frequently applied in ecological studies. Empirical Bayes methods provide an alternative approach that incorporates the structural advantages of Bayesian models while requiring a less stringent specification of prior knowledge. Rather than requiring that the prior distribution be known, empirical Bayes methods require only that it be in a certain family of distributions, indexed by hyperparameters that can be estimated from the available data. This structure is of interest per se, in addition to its value in allowing for improved estimation of individual parameters; for example, hypotheses regarding the existence of distinct subgroups in a collection of parameters can be considered under the empirical Bayes framework by allowing the hyperparameters to vary among subgroups. Though empirical Bayes methods have been applied in a variety of contexts, they have received little attention in the ecological literature. We describe the empirical Bayes approach in application to estimation of proportions, using data obtained in a community-wide study of cowbird parasitism rates for illustration. Since observed proportions based on small sample sizes are heavily adjusted toward the mean, extreme values among empirical Bayes estimates identify those species for which there is the greatest evidence of extreme parasitism rates. Applying a subgroup analysis to our data on cowbird parasitism rates, we conclude that parasitism rates for Neotropical Migrants as a group are no greater than those of Resident/Short-distance Migrant species in this forest community. Our data and analyses demonstrate that the parasitism rates for certain Neotropical Migrant species are remarkably low (Wood Thrush and Rose-breasted Grosbeak) while those for others are remarkably high (Ovenbird and Red-eyed Vireo).
Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human-Automation Interaction.

PubMed

Sebok, Angelia; Wickens, Christopher D

2017-03-01

The objectives were to (a) implement theoretical perspectives regarding human-automation interaction (HAI) into model-based tools to assist designers in developing systems that support effective performance and (b) conduct validations to assess the ability of the models to predict operator performance. Two key concepts in HAI, the lumberjack analogy and black swan events, have been studied extensively. The lumberjack analogy describes the effects of imperfect automation on operator performance. In routine operations, an increased degree of automation supports performance, but in failure conditions, increased automation results in more significantly impaired performance. Black swans are the rare and unexpected failures of imperfect automation. The lumberjack analogy and black swan concepts have been implemented into three model-based tools that predict operator performance in different systems. These tools include a flight management system, a remotely controlled robotic arm, and an environmental process control system. Each modeling effort included a corresponding validation. In one validation, the software tool was used to compare three flight management system designs, which were ranked in the same order as predicted by subject matter experts. The second validation compared model-predicted operator complacency with empirical performance in the same conditions. The third validation compared model-predicted and empirically determined time to detect and repair faults in four automation conditions. The three model-based tools offer useful ways to predict operator performance in complex systems. The three tools offer ways to predict the effects of different automation designs on operator performance.
Use of empirical likelihood to calibrate auxiliary information in partly linear monotone regression models.

PubMed

Chen, Baojiang; Qin, Jing

2014-05-10

In statistical analysis, a regression model is needed if one is interested in finding the relationship between a response variable and covariates. When the response depends on the covariate, then it may also depend on the function of this covariate. If one has no knowledge of this functional form but expect for monotonic increasing or decreasing, then the isotonic regression model is preferable. Estimation of parameters for isotonic regression models is based on the pool-adjacent-violators algorithm (PAVA), where the monotonicity constraints are built in. With missing data, people often employ the augmented estimating method to improve estimation efficiency by incorporating auxiliary information through a working regression model. However, under the framework of the isotonic regression model, the PAVA does not work as the monotonicity constraints are violated. In this paper, we develop an empirical likelihood-based method for isotonic regression model to incorporate the auxiliary information. Because the monotonicity constraints still hold, the PAVA can be used for parameter estimation. Simulation studies demonstrate that the proposed method can yield more efficient estimates, and in some situations, the efficiency improvement is substantial. We apply this method to a dementia study. Copyright © 2013 John Wiley & Sons, Ltd.
Empirical membrane lifetime model for heavy duty fuel cell systems

NASA Astrophysics Data System (ADS)

Macauley, Natalia; Watson, Mark; Lauritzen, Michael; Knights, Shanna; Wang, G. Gary; Kjeang, Erik

2016-12-01

Heavy duty fuel cells used in transportation system applications such as transit buses expose the fuel cell membranes to conditions that can lead to lifetime-limiting membrane failure via combined chemical and mechanical degradation. Highly durable membranes and reliable predictive models are therefore needed in order to achieve the ultimate heavy duty fuel cell lifetime target of 25,000 h. In the present work, an empirical membrane lifetime model was developed based on laboratory data from a suite of accelerated membrane durability tests. The model considers the effects of cell voltage, temperature, oxygen concentration, humidity cycling, humidity level, and platinum in the membrane using inverse power law and exponential relationships within the framework of a general log-linear Weibull life-stress statistical distribution. The obtained model is capable of extrapolating the membrane lifetime from accelerated test conditions to use level conditions during field operation. Based on typical conditions for the Whistler, British Columbia fuel cell transit bus fleet, the model predicts a stack lifetime of 17,500 h and a membrane leak initiation time of 9200 h. Validation performed with the aid of a field operated stack confirmed the initial goal of the model to predict membrane lifetime within 20% of the actual operating time.

Measurement and Estimation of Riverbed Scour in a Mountain River

NASA Astrophysics Data System (ADS)

Song, L. A.; Chan, H. C.; Chen, B. A.

2016-12-01

Mountains are steep with rapid flows in Taiwan. After installing a structure in a mountain river, scour usually occurs around the structure because of the high energy gradient. Excessive scouring has been reported as one of the main causes of failure of river structures. The scouring disaster related to the flood can be reduced if the riverbed variation can be properly evaluated based on the flow conditions. This study measures the riverbed scour by using an improved "float-out device". Scouring and hydrodynamic data were simultaneously collected in the Mei River, Nantou County located in central Taiwan. The semi-empirical models proposed by previous researchers were used to estimate the scour depths based on the measured flow characteristics. The differences between the measured and estimated scour depths were discussed. Attempts were then made to improve the estimating results by developing a semi-empirical model to predict the riverbed scour based on the local field data. It is expected to setup a warning system of river structure safety by using the flow conditions. Keywords: scour, model, float-out device
Going Global: A Model for Evaluating Empirically Supported Family-Based Interventions in New Contexts.

PubMed

Sundell, Knut; Ferrer-Wreder, Laura; Fraser, Mark W

2014-06-01

The spread of evidence-based practice throughout the world has resulted in the wide adoption of empirically supported interventions (ESIs) and a growing number of controlled trials of imported and culturally adapted ESIs. This article is informed by outcome research on family-based interventions including programs listed in the American Blueprints Model and Promising Programs. Evidence from these controlled trials is mixed and, because it is comprised of both successful and unsuccessful replications of ESIs, it provides clues for the translation of promising programs in the future. At least four explanations appear plausible for the mixed results in replication trials. One has to do with methodological differences across trials. A second deals with ambiguities in the cultural adaptation process. A third explanation is that ESIs in failed replications have not been adequately implemented. A fourth source of variation derives from unanticipated contextual influences that might affect the effects of ESIs when transported to other cultures and countries. This article describes a model that allows for the differential examination of adaptations of interventions in new cultural contexts. © The Author(s) 2012.
Analysis and experimental kinematics of a skid-steering wheeled robot based on a laser scanner sensor.

PubMed

Wang, Tianmiao; Wu, Yao; Liang, Jianhong; Han, Chenhao; Chen, Jiao; Zhao, Qiteng

2015-04-24

Skid-steering mobile robots are widely used because of their simple mechanism and robustness. However, due to the complex wheel-ground interactions and the kinematic constraints, it is a challenge to understand the kinematics and dynamics of such a robotic platform. In this paper, we develop an analysis and experimental kinematic scheme for a skid-steering wheeled vehicle based-on a laser scanner sensor. The kinematics model is established based on the boundedness of the instantaneous centers of rotation (ICR) of treads on the 2D motion plane. The kinematic parameters (the ICR coefficient , the path curvature variable and robot speed ), including the effect of vehicle dynamics, are introduced to describe the kinematics model. Then, an exact but costly dynamic model is used and the simulation of this model's stationary response for the vehicle shows a qualitative relationship for the specified parameters and . Moreover, the parameters of the kinematic model are determined based-on a laser scanner localization experimental analysis method with a skid-steering robotic platform, Pioneer P3-AT. The relationship between the ICR coefficient and two physical factors is studied, i.e., the radius of the path curvature and the robot speed . An empirical function-based relationship between the ICR coefficient of the robot and the path parameters is derived. To validate the obtained results, it is empirically demonstrated that the proposed kinematics model significantly improves the dead-reckoning performance of this skid-steering robot.
Elastohydrodynamic film thickness formula based on X-ray measurements with a synthetic paraffinic oil

NASA Technical Reports Server (NTRS)

Loewenthal, S. H.; Parker, R. J.; Zaretsky, E. V.

1973-01-01

An empirical elastohydrodynamic film thickness formula for heavily loaded contacts based upon X-ray film thickness measurements made with a synthetic paraffinic oil is presented. The deduced relation was found to adequately reflect the high load dependence exhibited by the measured minimum film thickness data at high Hertizian contact stresses, that is, above 1.04 x 10 to the ninth N/sq m (150,000 psi). Comparisons were made with the numerical results from a theoretical isothermal film thickness formula. The effects of changes in contact geometry, material, and lubricant properties on the form of the empirical model are also discussed.
An Initial Non-Equilibrium Porous-Media Model for CFD Simulation of Stirling Regenerators

NASA Technical Reports Server (NTRS)

Tew, Roy C.; Simon, Terry; Gedeon, David; Ibrahim, Mounir; Rong, Wei

2006-01-01

The objective of this paper is to define empirical parameters for an initial thermal non-equilibrium porous-media model for use in Computational Fluid Dynamics (CFD) codes for simulation of Stirling regenerators. The two codes currently used at Glenn Research Center for Stirling modeling are Fluent and CFD-ACE. The codes porous-media models are equilibrium models, which assume solid matrix and fluid are in thermal equilibrium. This is believed to be a poor assumption for Stirling regenerators; Stirling 1-D regenerator models, used in Stirling design, use non-equilibrium regenerator models and suggest regenerator matrix and gas average temperatures can differ by several degrees at a given axial location and time during the cycle. Experimentally based information was used to define: hydrodynamic dispersion, permeability, inertial coefficient, fluid effective thermal conductivity, and fluid-solid heat transfer coefficient. Solid effective thermal conductivity was also estimated. Determination of model parameters was based on planned use in a CFD model of Infinia's Stirling Technology Demonstration Converter (TDC), which uses a random-fiber regenerator matrix. Emphasis is on use of available data to define empirical parameters needed in a thermal non-equilibrium porous media model for Stirling regenerator simulation. Such a model has not yet been implemented by the authors or their associates.
A Model of Compound Heterozygous, Loss-of-Function Alleles Is Broadly Consistent with Observations from Complex-Disease GWAS Datasets

PubMed Central

Sanjak, Jaleal S.; Long, Anthony D.; Thornton, Kevin R.

2017-01-01

The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation. PMID:28103232
Viscoelastic shear properties of human vocal fold mucosa: theoretical characterization based on constitutive modeling.

PubMed

Chan, R W; Titze, I R

2000-01-01

The viscoelastic shear properties of human vocal fold mucosa (cover) were previously measured as a function of frequency [Chan and Titze, J. Acoust. Soc. Am. 106, 2008-2021 (1999)], but data were obtained only in a frequency range of 0.01-15 Hz, an order of magnitude below typical frequencies of vocal fold oscillation (on the order of 100 Hz). This study represents an attempt to extrapolate the data to higher frequencies based on two viscoelastic theories, (1) a quasilinear viscoelastic theory widely used for the constitutive modeling of the viscoelastic properties of biological tissues [Fung, Biomechanics (Springer-Verlag, New York, 1993), pp. 277-292], and (2) a molecular (statistical network) theory commonly used for the rheological modeling of polymeric materials [Zhu et al., J. Biomech. 24, 1007-1018 (1991)]. Analytical expressions of elastic and viscous shear moduli, dynamic viscosity, and damping ratio based on the two theories with specific model parameters were applied to curve-fit the empirical data. Results showed that the theoretical predictions matched the empirical data reasonably well, allowing for parametric descriptions of the data and their extrapolations to frequencies of phonation.
Emergence of a coherent and cohesive swarm based on mutual anticipation

PubMed Central

Murakami, Hisashi; Niizato, Takayuki; Gunji, Yukio-Pegio

2017-01-01

Collective behavior emerging out of self-organization is one of the most striking properties of an animal group. Typically, it is hypothesized that each individual in an animal group tends to align its direction of motion with those of its neighbors. Most previous models for collective behavior assume an explicit alignment rule, by which an agent matches its velocity with that of neighbors in a certain neighborhood, to reproduce a collective order pattern by simple interactions. Recent empirical studies, however, suggest that there is no evidence for explicit matching of velocity, and that collective polarization arises from interactions other than those that follow the explicit alignment rule. We here propose a new lattice-based computational model that does not incorporate the explicit alignment rule but is based instead on mutual anticipation and asynchronous updating. Moreover, we show that this model can realize densely collective motion with high polarity. Furthermore, we focus on the behavior of a pair of individuals, and find that the turning response is drastically changed depending on the distance between two individuals rather than the relative heading, and is consistent with the empirical observations. Therefore, the present results suggest that our approach provides an alternative model for collective behavior. PMID:28406173
Development of Specialization Scales for the MSPI: A Comparison of Empirical and Inductive Strategies

ERIC Educational Resources Information Center

Porfeli, Erik J.; Richard, George V.; Savickas, Mark L.

2010-01-01

An empirical measurement model for interest inventory construction uses internal criteria whereas an inductive measurement model uses external criteria. The empirical and inductive measurement models are compared and contrasted and then two models are assessed through tests of the effectiveness and economy of scales for the Medical Specialty…
Quantum chemical calculations for polymers and organic compounds

NASA Technical Reports Server (NTRS)

Lopez, J.; Yang, C.

1982-01-01

The relativistic effects of the orbiting electrons on a model compound were calculated. The computational method used was based on 'Modified Neglect of Differential Overlap' (MNDO). The compound tetracyanoplatinate was used since empirical measurement and calculations along "classical" lines had yielded many known properties. The purpose was to show that for large molecules relativity effects could not be ignored and that these effects could be calculated and yield data in closer agreement to empirical measurements. Both the energy band structure and molecular orbitals are depicted.
High Velocity Jet Noise Source Location and Reduction. Task 3 - Experimental Investigation of Suppression Principles. Volume I. Suppressor Concepts Optimization

DTIC Science & Technology

1978-12-01

multinational corporation in the 1960’s placed extreme emphasis on the need for effective and efficient noise suppression devices. Phase I of work...through model and engine testing applicable to an afterburning turbojet engine. Suppressor designs were based primarily on empirical methods. Phase II...using "ray" acoustics. This method is in contrast to the purely empirical method which consists of the curve -fitting of normalized data. In order to
Evaluating 1-, 2- and 3- Parameter Logistic Models Using Model-Based and Empirically-Based Simulations under Homogeneous and Heterogeneous Set Conditions

ERIC Educational Resources Information Center

Rizavi, Saba; Way, Walter D.; Lu, Ying; Pitoniak, Mary; Steffen, Manfred

2004-01-01

The purpose of this study was to use realistically simulated data to evaluate various CAT designs for use with the verbal reasoning measure of the Medical College Admissions Test (MCAT). Factors such as item pool depth, content constraints, and item formats often cause repeated adaptive administrations of an item at ability levels that are not…
An empirical model to forecast solar wind velocity through statistical modeling

NASA Astrophysics Data System (ADS)

Gao, Y.; Ridley, A. J.

2013-12-01

The accurate prediction of the solar wind velocity has been a major challenge in the space weather community. Previous studies proposed many empirical and semi-empirical models to forecast the solar wind velocity based on either the historical observations, e.g. the persistence model, or the instantaneous observations of the sun, e.g. the Wang-Sheeley-Arge model. In this study, we use the one-minute WIND data from January 1995 to August 2012 to investigate and compare the performances of 4 models often used in literature, here referred to as the null model, the persistence model, the one-solar-rotation-ago model, and the Wang-Sheeley-Arge model. It is found that, measured by root mean square error, the persistence model gives the most accurate predictions within two days. Beyond two days, the Wang-Sheeley-Arge model serves as the best model, though it only slightly outperforms the null model and the one-solar-rotation-ago model. Finally, we apply the least-square regression to linearly combine the null model, the persistence model, and the one-solar-rotation-ago model to propose a 'general persistence model'. By comparing its performance against the 4 aforementioned models, it is found that the accuracy of the general persistence model outperforms the other 4 models within five days. Due to its great simplicity and superb performance, we believe that the general persistence model can serve as a benchmark in the forecast of solar wind velocity and has the potential to be modified to arrive at better models.
Foundation for Problem-Based Gaming

ERIC Educational Resources Information Center

Kiili, Kristian

2007-01-01

Educational games may offer a viable strategy for developing students' problem-solving skills. However, the state of art of educational game research does not provide an account for that. Thus, the aim of this research is to develop an empirically allocated model about problem-based gaming that can be utilised to design pedagogically meaningful…
Strength of single-pole utility structures

Treesearch

Ronald W. Wolfe

2006-01-01

This section presents three basic methods for deriving and documenting Rn as an LTL value along with the coefficient of variation (COVR) for single-pole structures. These include the following: 1. An empirical analysis based primarily on tests of full-sized poles. 2. A theoretical analysis of mechanics-based models used in...
Improving the performance of the mass transfer-based reference evapotranspiration estimation approaches through a coupled wavelet-random forest methodology

NASA Astrophysics Data System (ADS)

Shiri, Jalal

2018-06-01

Among different reference evapotranspiration (ETo) modeling approaches, mass transfer-based methods have been less studied. These approaches utilize temperature and wind speed records. On the other hand, the empirical equations proposed in this context generally produce weak simulations, except when a local calibration is used for improving their performance. This might be a crucial drawback for those equations in case of local data scarcity for calibration procedure. So, application of heuristic methods can be considered as a substitute for improving the performance accuracy of the mass transfer-based approaches. However, given that the wind speed records have usually higher variation magnitudes than the other meteorological parameters, application of a wavelet transform for coupling with heuristic models would be necessary. In the present paper, a coupled wavelet-random forest (WRF) methodology was proposed for the first time to improve the performance accuracy of the mass transfer-based ETo estimation approaches using cross-validation data management scenarios in both local and cross-station scales. The obtained results revealed that the new coupled WRF model (with the minimum scatter index values of 0.150 and 0.192 for local and external applications, respectively) improved the performance accuracy of the single RF models as well as the empirical equations to great extent.
Testing an empirically derived mental health training model featuring small groups, distributed practice and patient discussion.

PubMed

Murrihy, Rachael C; Byrne, Mitchell K; Gonsalvez, Craig J

2009-02-01

Internationally, family doctors seeking to enhance their skills in evidence-based mental health treatment are attending brief training workshops, despite clear evidence in the literature that short-term, massed formats are not likely to improve skills in this complex area. Reviews of the educational literature suggest that an optimal model of training would incorporate distributed practice techniques; repeated practice over a lengthy time period, small-group interactive learning, mentoring relationships, skills-based training and an ongoing discussion of actual patients. This study investigates the potential role of group-based training incorporating multiple aspects of good pedagogy for training doctors in basic competencies in brief cognitive behaviour therapy (BCBT). Six groups of family doctors (n = 32) completed eight 2-hour sessions of BCBT group training over a 6-month period. A baseline control design was utilised with pre- and post-training measures of doctors' BCBT skills, knowledge and engagement in BCBT treatment. Family doctors' knowledge, skills in and actual use of BCBT with patients improved significantly over the course of training compared with the control period. This research demonstrates preliminary support for the efficacy of an empirically derived group training model for family doctors. Brief CBT group-based training could prove to be an effective and viable model for future doctor training.
Understanding Cirrus Ice Crystal Number Variability for Different Heterogeneous Ice Nucleation Spectra

NASA Technical Reports Server (NTRS)

Sullivan, Sylvia C.; Betancourt, Ricardo Morales; Barahona, Donifan; Nenes, Athanasios

2016-01-01

Along with minimizing parameter uncertainty, understanding the cause of temporal and spatial variability of the nucleated ice crystal number, Ni, is key to improving the representation of cirrus clouds in climate models. To this end, sensitivities of Ni to input variables like aerosol number and diameter provide valuable information about nucleation regime and efficiency for a given model formulation. Here we use the adjoint model of the adjoint of a cirrus formation parameterization (Barahona and Nenes, 2009b) to understand Ni variability for various ice-nucleating particle (INP) spectra. Inputs are generated with the Community Atmosphere Model version 5, and simulations are done with a theoretically derived spectrum, an empirical lab-based spectrum and two field-based empirical spectra that differ in the nucleation threshold for black carbon particles and in the active site density for dust. The magnitude and sign of Ni sensitivity to insoluble aerosol number can be directly linked to nucleation regime and efficiency of various INP. The lab-based spectrum calculates much higher INP efficiencies than field-based ones, which reveals a disparity in aerosol surface properties. Ni sensitivity to temperature tends to be low, due to the compensating effects of temperature on INP spectrum parameters; this low temperature sensitivity regime has been experimentally reported before but never deconstructed as done here.
What is heartburn worth? A cost-utility analysis of management strategies.

PubMed

Heudebert, G R; Centor, R M; Klapow, J C; Marks, R; Johnson, L; Wilcox, C M

2000-03-01

To determine the best treatment strategy for the management of patients presenting with symptoms consistent with uncomplicated heartburn. We performed a cost-utility analysis of 4 alternatives: empirical proton pump inhibitor, empirical histamine2-receptor antagonist, and diagnostic strategies consisting of either esophagogastroduodenoscopy (EGD) or an upper gastrointestinal series before treatment. The time horizon of the model was 1 year. The base case analysis assumed a cohort of otherwise healthy 45-year-old individuals in a primary care practice. Empirical treatment with a proton pump inhibitor was projected to provide the greatest quality-adjusted survival for the cohort. Empirical treatment with a histamine2 receptor antagonist was projected to be the least costly of the alternatives. The marginal cost-effectiveness of using a proton pump inhibitor over a histamine2-receptor antagonist was approximately $10,400 per quality-adjusted life year (QALY) gained in the base case analysis and was less than $50,000 per QALY as long as the utility for heartburn was less than 0.95. Both diagnostic strategies were dominated by proton pump inhibitor alternative. Empirical treatment seems to be the optimal initial management strategy for patients with heartburn, but the choice between a proton pump inhibitor or histamine2-receptor antagonist depends on the impact of heartburn on quality of life.
What Is Heartburn Worth?

PubMed Central

Heudebert, Gustavo R; Centor, Robert M; Klapow, Joshua C; Marks, Robert; Johnson, Lawrence; Wilcox, C Mel

2000-01-01

OBJECTIVE T o determine the best treatment strategy for the management of patients presenting with symptoms consistent with uncomplicated heartburn. METHODS We performed a cost-utility analysis of 4 alternatives: empirical proton pump inhibitor, empirical histamine2-receptor antagonist, and diagnostic strategies consisting of either esophagogastroduodenoscopy (EGD) or an upper gastrointestinal series before treatment. The time horizon of the model was 1 year. The base case analysis assumed a cohort of otherwise healthy 45-year-old individuals in a primary care practice. MAIN RESULTS Empirical treatment with a proton pump inhibitor was projected to provide the greatest quality-adjusted survival for the cohort. Empirical treatment with a histamine2receptor antagonist was projected to be the least costly of the alternatives. The marginal cost-effectiveness of using a proton pump inhibitor over a histamine2-receptor antagonist was approximately $10,400 per quality-adjusted life year (QALY) gained in the base case analysis and was less than $50,000 per QALY as long as the utility for heartburn was less than 0.95. Both diagnostic strategies were dominated by proton pump inhibitor alternative. CONCLUSIONS Empirical treatment seems to be the optimal initial management strategy for patients with heartburn, but the choice between a proton pump inhibitor or histamine2-receptor antagonist depends on the impact of heartburn on quality of life. PMID:10718898

Consumer trust in food safety--a multidisciplinary approach and empirical evidence from Taiwan.

PubMed

Chen, Mei-Fang

2008-12-01

Food scandals that happened in recent years have increased consumers' risk perceptions of foods and decreased their trust in food safety. A better understanding of the consumer trust in food safety can improve the effectiveness of public policy and allow the development of the best practice in risk communication. This study proposes a research framework from a psychometric approach to investigate the relationships between the consumer's trust in food safety and the antecedents of risk perceptions of foods based on a reflexive modernization perspective and a cultural theory perspective in the hope of benefiting the future empirical study. The empirical results from a structural equation modeling analysis of Taiwan as a case in point reveal that this research framework based on a multidisciplinary perspective can be a valuable tool for a growing understanding of consumer trust in food safety. The antecedents in the psychometric research framework comprised reflexive modernization factors and cultural theory factors have all been supported in this study except the consumer's perception of pessimism toward food. Moreover, the empirical results of repeated measures analysis of variance give more detailed information to grasp empirical implications and to provide some suggestions to the actors and institutions involved in the food supply chain in Taiwan.
Topography and geology site effects from the intensity prediction model (ShakeMap) for Austria

NASA Astrophysics Data System (ADS)

del Puy Papí Isaba, María; Jia, Yan; Weginger, Stefan

2017-04-01

The seismicity in Austria can be categorized as moderated. Despite the fact that the hazard seems to be rather low, earthquakes can cause great damage and losses, specially in densely populated and industrialized areas. It is well known, that equations which predict intensity as a function of magnitude and distance, among other parameters, are useful tool for hazard and risk assessment. Therefore, this study aims to determine an empirical model of the ground shaking intensities (ShakeMap) of a series of earthquakes occurred in Austria between 1000 and 2014. Furthermore, the obtained empirical model will lead to further interpretation of both, contemporary and historical earthquakes. A total of 285 events, which epicenters were located in Austria, and a sum of 22.739 reported macreoseismic data points from Austria and adjoining countries, were used. These events are enclosed in the period 1000-2014 and characterized by having a local magnitude greater than 3. In the first state of the model development, the data was careful selected, e.g. solely intensities equal or greater than III were used. In a second state the data was adjusted to the selected empirical model. Finally, geology and topography corrections were obtained by means of the model residuals in order to derive intensity-based site amplification effects.
Optimization of a middle atmosphere diagnostic scheme

NASA Astrophysics Data System (ADS)

Akmaev, Rashid A.

1997-06-01

A new assimilative diagnostic scheme based on the use of a spectral model was recently tested on the CIRA-86 empirical model. It reproduced the observed climatology with an annual global rms temperature deviation of 3.2 K in the 15-110 km layer. The most important new component of the scheme is that the zonal forcing necessary to maintain the observed climatology is diagnosed from empirical data and subsequently substituted into the simulation model at the prognostic stage of the calculation in an annual cycle mode. The simulation results are then quantitatively compared with the empirical model, and the above mentioned rms temperature deviation provides an objective measure of the `distance' between the two climatologies. This quantitative criterion makes it possible to apply standard optimization procedures to the whole diagnostic scheme and/or the model itself. The estimates of the zonal drag have been improved in this study by introducing a nudging (Newtonian-cooling) term into the thermodynamic equation at the diagnostic stage. A proper optimal adjustment of the strength of this term makes it possible to further reduce the rms temperature deviation of simulations down to approximately 2.7 K. These results suggest that direct optimization can successfully be applied to atmospheric model parameter identification problems of moderate dimensionality.
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).
Model for estimating enteric methane emissions from United States dairy and feedlot cattle.

PubMed

Kebreab, E; Johnson, K A; Archibeque, S L; Pape, D; Wirth, T

2008-10-01

Methane production from enteric fermentation in cattle is one of the major sources of anthropogenic greenhouse gas emission in the United States and worldwide. National estimates of methane emissions rely on mathematical models such as the one recommended by the Intergovernmental Panel for Climate Change (IPCC). Models used for prediction of methane emissions from cattle range from empirical to mechanistic with varying input requirements. Two empirical and 2 mechanistic models (COWPOLL and MOLLY) were evaluated for their prediction ability using individual cattle measurements. Model selection was based on mean square prediction error (MSPE), concordance correlation coefficient, and residuals vs. predicted values analyses. In dairy cattle, COWPOLL had the lowest root MSPE and greatest accuracy and precision of predicting methane emissions (correlation coefficient estimate = 0.75). The model simulated differences in diet more accurately than the other models, and the residuals vs. predicted value analysis showed no mean bias (P = 0.71). In feedlot cattle, MOLLY had the lowest root MSPE with almost all errors from random sources (correlation coefficient estimate = 0.69). The IPCC model also had good agreement with observed values, and no significant mean (P = 0.74) or linear bias (P = 0.11) was detected when residuals were plotted against predicted values. A fixed methane conversion factor (Ym) might be an easier alternative to diet-dependent variable Ym. Based on the results, the 2 mechanistic models were used to simulate methane emissions from representative US diets and were compared with the IPCC model. The average Ym in dairy cows was 5.63% of GE (range 3.78 to 7.43%) compared with 6.5% +/- 1% recommended by IPCC. In feedlot cattle, the average Ym was 3.88% (range 3.36 to 4.56%) compared with 3% +/- 1% recommended by IPCC. Based on our simulations, using IPCC values can result in an overestimate of about 12.5% and underestimate of emissions by about 9.8% for dairy and feedlot cattle, respectively. In addition to providing improved estimates of emissions based on diets, mechanistic models can be used to assess mitigation options such as changing source of carbohydrate or addition of fat to decrease methane, which is not possible with empirical models. We recommend national inventories use diet-specific Ym values predicted by mechanistic models to estimate methane emissions from cattle.
The Influence of Curriculum, Instruction, Technology, and Social Interactions on Two Fifth-Grade Students' Epistemologies in Modeling throughout a Model-Based Curriculum Unit

ERIC Educational Resources Information Center

Baek, Hamin; Schwarz, Christina V.

2015-01-01

In the past decade, reform efforts in science education have increasingly attended to engaging students in scientific practices such as scientific modeling. Engaging students in scientific modeling can help them develop their epistemologies by allowing them to attend to the roles of mechanism and empirical evidence when constructing and revising…
Lessons learned while integrating habitat, dispersal, disturbance, and life-history traits into species habitat models under climate change

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew P. Peters

2011-01-01

We present an approach to modeling potential climate-driven changes in habitat for tree and bird species in the eastern United States. First, we took an empirical-statistical modeling approach, using randomForest, with species abundance data from national inventories combined with soil, climate, and landscape variables, to build abundance-based habitat models for 134...
Identification of AR(I)MA processes for modelling temporal correlations of GPS observations

NASA Astrophysics Data System (ADS)

Luo, X.; Mayer, M.; Heck, B.

2009-04-01

In many geodetic applications observations of the Global Positioning System (GPS) are routinely processed by means of the least-squares method. However, this algorithm delivers reliable estimates of unknown parameters und realistic accuracy measures only if both the functional and stochastic models are appropriately defined within GPS data processing. One deficiency of the stochastic model used in many GPS software products consists in neglecting temporal correlations of GPS observations. In practice the knowledge of the temporal stochastic behaviour of GPS observations can be improved by analysing time series of residuals resulting from the least-squares evaluation. This paper presents an approach based on the theory of autoregressive (integrated) moving average (AR(I)MA) processes to model temporal correlations of GPS observations using time series of observation residuals. A practicable integration of AR(I)MA models in GPS data processing requires the determination of the order parameters of AR(I)MA processes at first. In case of GPS, the identification of AR(I)MA processes could be affected by various factors impacting GPS positioning results, e.g. baseline length, multipath effects, observation weighting, or weather variations. The influences of these factors on AR(I)MA identification are empirically analysed based on a large amount of representative residual time series resulting from differential GPS post-processing using 1-Hz observation data collected within the permanent SAPOS® (Satellite Positioning Service of the German State Survey) network. Both short and long time series are modelled by means of AR(I)MA processes. The final order parameters are determined based on the whole residual database; the corresponding empirical distribution functions illustrate that multipath and weather variations seem to affect the identification of AR(I)MA processes much more significantly than baseline length and observation weighting. Additionally, the modelling results of temporal correlations using high-order AR(I)MA processes are compared with those by means of first order autoregressive (AR(1)) processes and empirically estimated autocorrelation functions.
Experimental validation of new empirical models of the thermal properties of food products for safe shipping

NASA Astrophysics Data System (ADS)

Hamid, Hanan H.; Mitchell, Mark; Jahangiri, Amirreza; Thiel, David V.

2018-04-01

Temperature controlled food transport is essential for human safety and to minimise food waste. The thermal properties of food are important for determining the heat transfer during the transient stages of transportation (door opening during loading and unloading processes). For example, the temperature of most dairy products must be confined to a very narrow range (3-7 °C). If a predefined critical temperature is exceeded, the food is defined as spoiled and unfit for human consumption. An improved empirical model for the thermal conductivity and specific heat capacity of a wide range of food products was derived based on the food composition (moisture, fat, protein, carbohydrate and ash). The models that developed using linear regression analysis were compared with the published measured parameters in addition to previously published theoretical and empirical models. It was found that the maximum variation in the predicated thermal properties leads to less than 0.3 °C temperature change. The correlation coefficient for these models was 0.96. The t-Stat test ( P-value >0.99) demonstrated that the model results are an improvement on previous works. The transient heat transfer based on the food composition and the temperature boundary conditions was found for a Camembert cheese (short cylindrical shape) using a multiple dimension finite difference method code. The result was verified using the heat transfer today (HTT) educational software which is based on finite volume method. The core temperature rises from the initial temperature (2.7 °C) to the maximum safe temperature in ambient air (20.24 °C) was predicted to within about 35.4 ± 0.5 min. The simulation results agree very well ( +0.2 °C) with the measured temperature data. This improved model impacts on temperature estimation during loading and unloading the trucks and provides a clear direction for temperature control in all refrigerated transport applications.
An Empirical Study of Instructor Adoption of Web-Based Learning Systems

ERIC Educational Resources Information Center

Wang, Wei-Tsong; Wang, Chun-Chieh

2009-01-01

For years, web-based learning systems have been widely employed in both educational and non-educational institutions. Although web-based learning systems are emerging as a useful tool for facilitating teaching and learning activities, the number of users is not increasing as fast as expected. This study develops an integrated model of instructor…
An Empirical Model-based MOE for Friction Reduction by Slot-Ejected Polymer Solutions in an Aqueous Environment

DTIC Science & Technology

2007-12-21

of hydrodynamics and the physical characteristics of the polymers. The physics models include both analytical models and numerical simulations ...the experimental observations. The numerical simulations also succeed in replicating some experimental measurements. However, there is still no...become quite significant. 4.5 Documentation The complete model is coded in MatLab . In the model, all units are cgs, so distances are in
Modeling and prediction of ionospheric scintillation

NASA Technical Reports Server (NTRS)

Fremouw, E. J.

1974-01-01

Scintillation modeling performed thus far is based on the theory of diffraction by a weakly modulating phase screen developed by Briggs and Parkin (1963). Shortcomings of the existing empirical model for the scintillation index are discussed together with questions of channel modeling, giving attention to the needs of the communication engineers. It is pointed out that much improved scintillation index models may be available in a matter of a year or so.
ITS logical architecture : volume 3, data dictionary.

DOT National Transportation Integrated Search

1981-01-01

The objective of the research effort was to develop an empirically and experiencially based model pedestrian safety program which cities can use as guidelines for pedestrian safety program planning, implementation, and evaluation. The basis of these ...
Empirical likelihood method for non-ignorable missing data problems.

PubMed

Guan, Zhong; Qin, Jing

2017-01-01

Missing response problem is ubiquitous in survey sampling, medical, social science and epidemiology studies. It is well known that non-ignorable missing is the most difficult missing data problem where the missing of a response depends on its own value. In statistical literature, unlike the ignorable missing data problem, not many papers on non-ignorable missing data are available except for the full parametric model based approach. In this paper we study a semiparametric model for non-ignorable missing data in which the missing probability is known up to some parameters, but the underlying distributions are not specified. By employing Owen (1988)'s empirical likelihood method we can obtain the constrained maximum empirical likelihood estimators of the parameters in the missing probability and the mean response which are shown to be asymptotically normal. Moreover the likelihood ratio statistic can be used to test whether the missing of the responses is non-ignorable or completely at random. The theoretical results are confirmed by a simulation study. As an illustration, the analysis of a real AIDS trial data shows that the missing of CD4 counts around two years are non-ignorable and the sample mean based on observed data only is biased.
Price Formation Based on Particle-Cluster Aggregation

NASA Astrophysics Data System (ADS)

Wang, Shijun; Zhang, Changshui

In the present work, we propose a microscopic model of financial markets based on particle-cluster aggregation on a two-dimensional small-world information network in order to simulate the dynamics of the stock markets. "Stylized facts" of the financial market time series, such as fat-tail distribution of returns, volatility clustering and multifractality, are observed in the model. The results of the model agree with empirical data taken from historical records of the daily closures of the NYSE composite index.
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.
The response of the SSM/I to the marine environment. Part 2: A parameterization of the effect of the sea surface slope distribution on emission and reflection

NASA Technical Reports Server (NTRS)

Petty, Grant W.; Katsaros, Kristina B.

1994-01-01

Based on a geometric optics model and the assumption of an isotropic Gaussian surface slope distribution, the component of ocean surface microwave emissivity variation due to large-scale surface roughness is parameterized for the frequencies and approximate viewing angle of the Special Sensor Microwave/Imager. Independent geophysical variables in the parameterization are the effective (microwave frequency dependent) slope variance and the sea surface temperature. Using the same physical model, the change in the effective zenith angle of reflected sky radiation arising from large-scale roughness is also parameterized. Independent geophysical variables in this parameterization are the effective slope variance and the atmospheric optical depth at the frequency in question. Both of the above model-based parameterizations are intended for use in conjunction with empirical parameterizations relating effective slope variance and foam coverage to near-surface wind speed. These empirical parameterizations are the subject of a separate paper.
Estimating and Identifying Unspecified Correlation Structure for Longitudinal Data

PubMed Central

Hu, Jianhua; Wang, Peng; Qu, Annie

2014-01-01

Identifying correlation structure is important to achieving estimation efficiency in analyzing longitudinal data, and is also crucial for drawing valid statistical inference for large size clustered data. In this paper, we propose a nonparametric method to estimate the correlation structure, which is applicable for discrete longitudinal data. We utilize eigenvector-based basis matrices to approximate the inverse of the empirical correlation matrix and determine the number of basis matrices via model selection. A penalized objective function based on the difference between the empirical and model approximation of the correlation matrices is adopted to select an informative structure for the correlation matrix. The eigenvector representation of the correlation estimation is capable of reducing the risk of model misspecification, and also provides useful information on the specific within-cluster correlation pattern of the data. We show that the proposed method possesses the oracle property and selects the true correlation structure consistently. The proposed method is illustrated through simulations and two data examples on air pollution and sonar signal studies. PMID:26361433
Channel characterization and empirical model for ergodic capacity of free-space optical communication link

NASA Astrophysics Data System (ADS)

Alimi, Isiaka; Shahpari, Ali; Ribeiro, Vítor; Sousa, Artur; Monteiro, Paulo; Teixeira, António

2017-05-01

In this paper, we present experimental results on channel characterization of single input single output (SISO) free-space optical (FSO) communication link that is based on channel measurements. The histograms of the FSO channel samples and the log-normal distribution fittings are presented along with the measured scintillation index. Furthermore, we extend our studies to diversity schemes and propose a closed-form expression for determining ergodic channel capacity of multiple input multiple output (MIMO) FSO communication systems over atmospheric turbulence fading channels. The proposed empirical model is based on SISO FSO channel characterization. Also, the scintillation effects on the system performance are analyzed and results for different turbulence conditions are presented. Moreover, we observed that the histograms of the FSO channel samples that we collected from a 1548.51 nm link have good fits with log-normal distributions and the proposed model for MIMO FSO channel capacity is in conformity with the simulation results in terms of normalized mean-square error (NMSE).
Treatment of Adolescent Substance Use Disorders and Co-Occurring Internalizing Disorders: A Critical Review and Proposed Model.

PubMed

Hulvershorn, Leslie A; Quinn, Patrick D; Scott, Eric L

2015-01-01

The past several decades have seen dramatic growth in empirically supported treatments for adolescent substance use disorders (SUDs), yet even the most well-established approaches struggle to produce large or long-lasting improvements. These difficulties may stem, in part, from the high rates of comorbidity between SUDs and other psychiatric disorders. We critically reviewed the treatment outcome literature for adolescents with co-occurring SUDs and internalizing disorders. Our review identified components of existing treatments that might be included in an integrated, evidence-based approach to the treatment of SUDs and internalizing disorders. An effective program may involve careful assessment, inclusion of parents or guardians, and tailoring of interventions via a modular strategy. The existing literature guides the development of a conceptual evidence-based, modular treatment model targeting adolescents with co-occurring internalizing and SUDs. With empirical study, such a model may better address treatment outcomes for both disorder types in adolescents.

Direct Extraction of Tumor Response Based on Ensemble Empirical Mode Decomposition for Image Reconstruction of Early Breast Cancer Detection by UWB.

PubMed

Li, Qinwei; Xiao, Xia; Wang, Liang; Song, Hang; Kono, Hayato; Liu, Peifang; Lu, Hong; Kikkawa, Takamaro

2015-10-01

A direct extraction method of tumor response based on ensemble empirical mode decomposition (EEMD) is proposed for early breast cancer detection by ultra-wide band (UWB) microwave imaging. With this approach, the image reconstruction for the tumor detection can be realized with only extracted signals from as-detected waveforms. The calibration process executed in the previous research for obtaining reference waveforms which stand for signals detected from the tumor-free model is not required. The correctness of the method is testified by successfully detecting a 4 mm tumor located inside the glandular region in one breast model and by the model located at the interface between the gland and the fat, respectively. The reliability of the method is checked by distinguishing a tumor buried in the glandular tissue whose dielectric constant is 35. The feasibility of the method is confirmed by showing the correct tumor information in both simulation results and experimental results for the realistic 3-D printed breast phantom.
Treatment of Adolescent Substance Use Disorders and Co-Occurring Internalizing Disorders: A Critical Review and Proposed Model

PubMed Central

Hulvershorn, Leslie A.; Quinn, Patrick D.; Scott, Eric L.

2016-01-01

Background The past several decades have seen dramatic growth in empirically supported treatments for adolescent substance use disorders (SUDs), yet even the most well-established approaches struggle to produce large or long-lasting improvements. These difficulties may stem, in part, from the high rates of comorbidity between SUDs and other psychiatric disorders. Method We critically reviewed the treatment outcome literature for adolescents with co-occurring SUDs and internalizing disorders. Results Our review identified components of existing treatments that might be included in an integrated, evidence-based approach to the treatment of SUDs and internalizing disorders. An effective program may involve careful assessment, inclusion of parents or guardians, and tailoring of interventions via a modular strategy. Conclusions The existing literature guides the development of a conceptual evidence-based, modular treatment model targeting adolescents with co-occurring internalizing and SUDs. With empirical study, such a model may better address treatment outcomes for both disorder types in adolescents. PMID:25973718
A novel hybrid ensemble learning paradigm for tourism forecasting

NASA Astrophysics Data System (ADS)

Shabri, Ani

2015-02-01

In this paper, a hybrid forecasting model based on Empirical Mode Decomposition (EMD) and Group Method of Data Handling (GMDH) is proposed to forecast tourism demand. This methodology first decomposes the original visitor arrival series into several Intrinsic Model Function (IMFs) components and one residual component by EMD technique. Then, IMFs components and the residual components is forecasted respectively using GMDH model whose input variables are selected by using Partial Autocorrelation Function (PACF). The final forecasted result for tourism series is produced by aggregating all the forecasted results. For evaluating the performance of the proposed EMD-GMDH methodologies, the monthly data of tourist arrivals from Singapore to Malaysia are used as an illustrative example. Empirical results show that the proposed EMD-GMDH model outperforms the EMD-ARIMA as well as the GMDH and ARIMA (Autoregressive Integrated Moving Average) models without time series decomposition.
The consentaneous model of the financial markets exhibiting spurious nature of long-range memory

NASA Astrophysics Data System (ADS)

Gontis, V.; Kononovicius, A.

2018-09-01

It is widely accepted that there is strong persistence in the volatility of financial time series. The origin of the observed persistence, or long-range memory, is still an open problem as the observed phenomenon could be a spurious effect. Earlier we have proposed the consentaneous model of the financial markets based on the non-linear stochastic differential equations. The consentaneous model successfully reproduces empirical probability and power spectral densities of volatility. This approach is qualitatively different from models built using fractional Brownian motion. In this contribution we investigate burst and inter-burst duration statistics of volatility in the financial markets employing the consentaneous model. Our analysis provides an evidence that empirical statistical properties of burst and inter-burst duration can be explained by non-linear stochastic differential equations driving the volatility in the financial markets. This serves as an strong argument that long-range memory in finance can have spurious nature.
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.
An Empirical Model for Vane-Type Vortex Generators in a Navier-Stokes Code

NASA Technical Reports Server (NTRS)

Dudek, Julianne C.

2005-01-01

An empirical model which simulates the effects of vane-type vortex generators in ducts was incorporated into the Wind-US Navier-Stokes computational fluid dynamics code. The model enables the effects of the vortex generators to be simulated without defining the details of the geometry within the grid, and makes it practical for researchers to evaluate multiple combinations of vortex generator arrangements. The model determines the strength of each vortex based on the generator geometry and the local flow conditions. Validation results are presented for flow in a straight pipe with a counter-rotating vortex generator arrangement, and the results are compared with experimental data and computational simulations using a gridded vane generator. Results are also presented for vortex generator arrays in two S-duct diffusers, along with accompanying experimental data. The effects of grid resolution and turbulence model are also examined.
An accurate European option pricing model under Fractional Stable Process based on Feynman Path Integral

NASA Astrophysics Data System (ADS)

Ma, Chao; Ma, Qinghua; Yao, Haixiang; Hou, Tiancheng

2018-03-01

In this paper, we propose to use the Fractional Stable Process (FSP) for option pricing. The FSP is one of the few candidates to directly model a number of desired empirical properties of asset price risk neutral dynamics. However, pricing the vanilla European option under FSP is difficult and problematic. In the paper, built upon the developed Feynman Path Integral inspired techniques, we present a novel computational model for option pricing, i.e. the Fractional Stable Process Path Integral (FSPPI) model under a general fractional stable distribution that tackles this problem. Numerical and empirical experiments show that the proposed pricing model provides a correction of the Black-Scholes pricing error - overpricing long term options, underpricing short term options; overpricing out-of-the-money options, underpricing in-the-money options without any additional structures such as stochastic volatility and a jump process.
Computational ligand-based rational design: Role of conformational sampling and force fields in model development.

PubMed

Shim, Jihyun; Mackerell, Alexander D

2011-05-01

A significant number of drug discovery efforts are based on natural products or high throughput screens from which compounds showing potential therapeutic effects are identified without knowledge of the target molecule or its 3D structure. In such cases computational ligand-based drug design (LBDD) can accelerate the drug discovery processes. LBDD is a general approach to elucidate the relationship of a compound's structure and physicochemical attributes to its biological activity. The resulting structure-activity relationship (SAR) may then act as the basis for the prediction of compounds with improved biological attributes. LBDD methods range from pharmacophore models identifying essential features of ligands responsible for their activity, quantitative structure-activity relationships (QSAR) yielding quantitative estimates of activities based on physiochemical properties, and to similarity searching, which explores compounds with similar properties as well as various combinations of the above. A number of recent LBDD approaches involve the use of multiple conformations of the ligands being studied. One of the basic components to generate multiple conformations in LBDD is molecular mechanics (MM), which apply an empirical energy function to relate conformation to energies and forces. The collection of conformations for ligands is then combined with functional data using methods ranging from regression analysis to neural networks, from which the SAR is determined. Accordingly, for effective application of LBDD for SAR determinations it is important that the compounds be accurately modelled such that the appropriate range of conformations accessible to the ligands is identified. Such accurate modelling is largely based on use of the appropriate empirical force field for the molecules being investigated and the approaches used to generate the conformations. The present chapter includes a brief overview of currently used SAR methods in LBDD followed by a more detailed presentation of issues and limitations associated with empirical energy functions and conformational sampling methods.
Boldness by habituation and social interactions: a model.

PubMed

Oosten, Johanneke E; Magnhagen, Carin; Hemelrijk, Charlotte K

2010-04-01

Most studies of animal personality attribute personality to genetic traits. But a recent study by Magnhagen and Staffan (Behav Ecol Sociobiol 57:295-303, 2005) on young perch in small groups showed that boldness, a central personality trait, is also shaped by social interactions and by previous experience. The authors measured boldness by recording the duration that an individual spent near a predator and the speed with which it fed there. They found that duration near the predator increased over time and was higher the higher the average boldness of other group members. In addition, the feeding rate of shy individuals was reduced if other members of the same group were bold. The authors supposed that these behavioral dynamics were caused by genetic differences, social interactions, and habituation to the predator. However, they did not quantify exactly how this could happen. In the present study, we therefore use an agent-based model to investigate whether these three factors may explain the empirical findings. We choose an agent-based model because this type of model is especially suited to study the relation between behavior at an individual level and behavioral dynamics at a group level. In our model, individuals were either hiding in vegetation or feeding near a predator, whereby their behavior was affected by habituation and by two social mechanisms: social facilitation to approach the predator and competition over food. We show that even if we start the model with identical individuals, these three mechanisms were sufficient to reproduce the behavioral dynamics of the empirical study, including the consistent differences among individuals. Moreover, if we start the model with individuals that already differ in boldness, the behavioral dynamics produced remained the same. Our results indicate the importance of previous experience and social interactions when studying animal personality empirically.
Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

NASA Astrophysics Data System (ADS)

Hasanzadeh Nafari, Roozbeh; Amadio, Mattia; Ngo, Tuan; Mysiak, Jaroslav

2017-07-01

The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT), on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA), which represents the confidence limits that exist around the parameterized functional depth-damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a three-fold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 % mean absolute error), especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy.
Are recent empirical directivity models sufficient in capturing near-fault directivity effect?

NASA Astrophysics Data System (ADS)

Chen, Yen-Shin; Cotton, Fabrice; Pagani, Marco; Weatherill, Graeme; Reshi, Owais; Mai, Martin

2017-04-01

It has been widely observed that the ground motion variability in the near field can be significantly higher than that commonly reported in published GMPEs, and this has been suggested to be a consequence of directivity. To capture the spatial variation in ground motion amplitude and frequency caused by the near-fault directivity effect, several models for engineering applications have been developed using empirical or, more recently, the combination of empirical and simulation data. Many research works have indicated that the large velocity pulses mainly observed in the near-field are primarily related to slip heterogeneity (i.e., asperities), suggesting that the slip heterogeneity is a more dominant controlling factor than the rupture velocity or source rise time function. The first generation of broadband directivity models for application in ground motion prediction do not account for heterogeneity of slip and rupture speed. With the increased availability of strong motion recordings (e.g., NGA-West 2 database) in the near-fault region, the directivity models moved from broadband to narrowband models to include the magnitude dependence of the period of the rupture directivity pulses, wherein the pulses are believed to be closely related to the heterogeneity of slip distribution. After decades of directivity models development, does the latest generation of models - i.e. the one including narrowband directivity models - better capture the near-fault directivity effects, particularly in presence of strong slip heterogeneity? To address this question, a set of simulated motions for an earthquake rupture scenario, with various kinematic slip models and hypocenter locations, are used as a basis for a comparison with the directivity models proposed by the NGA-West 2 project for application with ground motion prediction equations incorporating a narrowband directivity model. The aim of this research is to gain better insights on the accuracy of narrowband directivity models under conditions commonly encountered in the real world. Our preliminary result shows that empirical models including directivity factors better predict physics based ground-motion and their spatial variability than classical empirical models. However, the results clearly indicate that it is still a challenge for the directivity models to capture the strong directivity effect if a high level of slip heterogeneity is involved during the source rupture process.
Climate data induced uncertainty in model-based estimations of terrestrial primary productivity

NASA Astrophysics Data System (ADS)

Wu, Zhendong; Ahlström, Anders; Smith, Benjamin; Ardö, Jonas; Eklundh, Lars; Fensholt, Rasmus; Lehsten, Veiko

2017-06-01

Model-based estimations of historical fluxes and pools of the terrestrial biosphere differ substantially. These differences arise not only from differences between models but also from differences in the environmental and climatic data used as input to the models. Here we investigate the role of uncertainties in historical climate data by performing simulations of terrestrial gross primary productivity (GPP) using a process-based dynamic vegetation model (LPJ-GUESS) forced by six different climate datasets. We find that the climate induced uncertainty, defined as the range among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 11 Pg C yr-1 globally (9% of mean GPP). We also assessed a hypothetical maximum climate data induced uncertainty by combining climate variables from different datasets, which resulted in significantly larger uncertainties of 41 Pg C yr-1 globally or 32% of mean GPP. The uncertainty is partitioned into components associated to the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (climate data range) and the apparent sensitivity of the modeled GPP to the driver (apparent model sensitivity). We find that LPJ-GUESS overestimates GPP compared to empirically based GPP data product in all land cover classes except for tropical forests. Tropical forests emerge as a disproportionate source of uncertainty in GPP estimation both in the simulations and empirical data products. The tropical forest uncertainty is most strongly associated with shortwave radiation and precipitation forcing, of which climate data range contributes higher to overall uncertainty than apparent model sensitivity to forcing. Globally, precipitation dominates the climate induced uncertainty over nearly half of the vegetated land area, which is mainly due to climate data range and less so due to the apparent model sensitivity. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than apparent model sensitivity to forcing. Our study highlights the need to better constrain tropical climate, and demonstrates that uncertainty caused by climatic forcing data must be considered when comparing and evaluating carbon cycle model results and empirical datasets.
The impact of overstory density on reproduction establishment in the Missouri Ozarks: models for simulating regeneration stochastically

Treesearch

Lance A. Vickers; David R. Larsen; Daniel C. Dey; Benjamin O. Knapp; John M. Kabrick

2017-01-01

Predicting the effects of silvicultural choices on regeneration has been difficult with the tools available to foresters. In an effort to improve this, we developed a collection of reproduction establishment models based on stand development hypotheses and parameterized with empirical data for several species in the Missouri Ozarks. These models estimate third-year...
Willingness to Communicate in English: A Microsystem Model in the Iranian EFL Classroom Context

ERIC Educational Resources Information Center

Khajavy, Gholam Hassan; Ghonsooly, Behzad; Fatemi, Azar Hosseini; Choi, Charles W.

2016-01-01

This study examined willingness to communicate (WTC) in English among Iranian EFL learners in the classroom context. For this purpose, a second language willingness to communicate (L2WTC) model based on WTC theory (MacIntyre, Clément, Dörnyei, and Noels, 1998) and empirical studies was proposed and tested using structural equation modeling (SEM).…
Chemically Reactive Nitrogen Trace Species in the Planetary Boundary Layer

DTIC Science & Technology

1996-01-01

56 Biogenic NO Budget Used in the EPA Regional Oxidant Model ......... 58 Conclusions and...Regional Oxidant Model (ROM) ............................... 59 Table 2.4. Air and soil temperatures and average NO flux using W illiam s’ m odel...1985; Penkett, 1988). Yienger and Levy (1995) developed an empirically based model to estimate soil NOx emissions on a global scale. They have reported
Dynamic Self-Organization and Early Lexical Development in Children

ERIC Educational Resources Information Center

Li, Ping; Zhao, Xiaowei; Whinney, Brian Mac

2007-01-01

In this study we present a self-organizing connectionist model of early lexical development. We call this model DevLex-II, based on the earlier DevLex model. DevLex-II can simulate a variety of empirical patterns in children's acquisition of words. These include a clear vocabulary spurt, effects of word frequency and length on age of acquisition,…
First-order fire effects models for land Management: Overview and issues

Treesearch

Elizabeth D. Reinhardt; Matthew B. Dickinson

2010-01-01

We give an overview of the science application process at work in supporting fire management. First-order fire effects models, such as those discussed in accompanying papers, are the building blocks of software systems designed for application to landscapes over time scales from days to centuries. Fire effects may be modeled using empirical, rule based, or process...
The Complexity of Teacher Questions in Chemistry Classrooms: An Empirical Analysis on the Basis of Two Competence Models

ERIC Educational Resources Information Center

Nehring, Andreas; Päßler, Andreas; Tiemann, Rüdiger

2017-01-01

With regard to the moderate performance of German students in international large-scale assessments, one branch of German science education research is concerned with the construction and evaluation of competence models. Based on the theory-driven definition of competence levels, these models imply a correlation between the complexity of a…
Using landscape analysis to assess and model tsunami damage in Aceh province, Sumatra

Treesearch

Louis R. Iverson; Anantha Prasad

2007-01-01

The nearly unprecedented loss of life resulting from the earthquake and tsunami of December 26,2004, was greatest in the province of Aceh, Sumatra (Indonesia). We evaluated tsunami damage and built empirical vulnerability models of damage/no damage based on elevation, distance from shore, vegetation, and exposure. We found that highly predictive models are possible and...
Measurement of the equilibrium charge state distributions of Ni, Co, and Cu beams in Mo at 2 MeV/u: Review and evaluation of the relevant semi-empirical models

NASA Astrophysics Data System (ADS)

Gastis, P.; Perdikakis, G.; Robertson, D.; Almus, R.; Anderson, T.; Bauder, W.; Collon, P.; Lu, W.; Ostdiek, K.; Skulski, M.

2016-04-01

Equilibrium charge state distributions of stable 60Ni, 59Co, and 63Cu beams passing through a 1 μm thick Mo foil were measured at beam energies of 1.84 MeV/u, 2.09 MeV/u, and 2.11 MeV/u respectively. A 1-D position sensitive Parallel Grid Avalanche Counter detector (PGAC) was used at the exit of a spectrograph magnet, enabling us to measure the intensity of several charge states simultaneously. The number of charge states measured for each beam constituted more than 99% of the total equilibrium charge state distribution for that element. Currently, little experimental data exists for equilibrium charge state distributions for heavy ions with 19 ≲Zp,Zt ≲ 54 (Zp and Zt, are the projectile's and target's atomic numbers respectively). Hence the success of the semi-empirical models in predicting typical characteristics of equilibrium CSDs (mean charge states and distribution widths), has not been thoroughly tested at the energy region of interest. A number of semi-empirical models from the literature were evaluated in this study, regarding their ability to reproduce the characteristics of the measured charge state distributions. The evaluated models were selected from the literature based on whether they are suitable for the given range of atomic numbers and on their frequent use by the nuclear physics community. Finally, an attempt was made to combine model predictions for the mean charge state, the distribution width and the distribution shape, to come up with a more reliable model. We discuss this new ;combinatorial; prescription and compare its results with our experimental data and with calculations using the other semi-empirical models studied in this work.

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