Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling.
Ye, Hao; Beamish, Richard J; Glaser, Sarah M; Grant, Sue C H; Hsieh, Chih-Hao; Richards, Laura J; Schnute, Jon T; Sugihara, George
2015-03-31
It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon (Oncorhynchus nerka) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner-recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts.
Vertical Equating: An Empirical Study of the Consistency of Thurstone and Rasch Model Approaches.
Schratz, Mary K.
To explore the appropriateness of the Rasch model for the vertical equating of a multi-level, multi-form achievement test series, both the Rasch model and the traditional Thurstone procedures were applied to the Listening Comprehension subtest scores of the Stanford Achievement Test. Two adjacent levels of these tests were administered in 1981 to…
Ijasini John Tekwa
2016-03-01
Full Text Available A field study was carried out to assess soil loss from ephemeral gully (EG erosion at 6 different locations (Digil, Vimtim, Muvur, Gella, Lamorde and Madanya around the Mubi area between April, 2008 and October, 2009. Each location consisted of 3 watershed sites from where data was collected. EG shape, land use, and conservation practices were noted, while EG length, width, and depth were measured. Physico-chemical properties of the soils were studied in the field and laboratory. Soil loss was both measured and predicted using modeled empirical equations. Results showed that the soils are heterogeneous and lying on flat to hilly topographies with few grasses, shrubs and tree vegetations. The soils comprised of sand fractions that predominated the texture, with considerable silt and clay contents. The empirical soil loss was generally related with the measured soil loss and the predictions were widely reliable at all sites, regardless of season. The measured and empirical aggregate soil loss were more related in terms of volume of soil loss (VSL (r2=0.93 and mass of soil loss (MSL (r2=0.92, than area of soil loss (ASL (r2=0.27. The empirical estimates of VSL and MSL were consistently higher at Muvur (less vegetation and lower at Madanya and Gella (denser vegetations in both years. The maximum efficiency (Mse of the empirical equation in predicting ASL was between 1.41 (Digil and 89.07 (Lamorde, while the Mse was higher at Madanya (2.56 and lowest at Vimtim (15.66 in terms of VSL prediction efficiencies. The Mse also ranged from 1.84 (Madanya to 15.74 (Vimtim in respect of MSL predictions. These results led to the recommendation that soil conservationists, farmers, private and/or government agencies should implement the empirical model in erosion studies around Mubi area.
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.
Semi-Empirical Calibration of the Integral Equation Model for Co-Polarized L-Band Backscattering
Nicolas Baghdadi
2015-10-01
Full Text Available The objective of this paper is to extend the semi-empirical calibration of the backscattering Integral Equation Model (IEM initially proposed for Synthetic Aperture Radar (SAR data at C- and X-bands to SAR data at L-band. A large dataset of radar signal and in situ measurements (soil moisture and surface roughness over bare soil surfaces were used. This dataset was collected over numerous agricultural study sites in France, Luxembourg, Belgium, Germany and Italy using various SAR sensors (AIRSAR, SIR-C, JERS-1, PALSAR-1, ESAR. Results showed slightly better simulations with exponential autocorrelation function than with Gaussian function and with HH than with VV. Using the exponential autocorrelation function, the mean difference between experimental data and Integral Equation Model (IEM simulations is +0.4 dB in HH and −1.2 dB in VV with a Root Mean Square Error (RMSE about 3.5 dB. In order to improve the modeling results of the IEM for a better use in the inversion of SAR data, a semi-empirical calibration of the IEM was performed at L-band in replacing the correlation length derived from field experiments by a fitting parameter. Better agreement was observed between the backscattering coefficient provided by the SAR and that simulated by the calibrated version of the IEM (RMSE about 2.2 dB.
Empirical investigation of e-learning acceptance and assimilation: A structural equation model
Said S. Al-Gahtani
2016-01-01
Full Text Available E-learning has become progressively more vital for academia and corporate training and has potentially become one of the most significant developments and applications in Information Technologies (ITs. This study used a quantitative approach seeking a causative explanation of the decision behavior of individuals toward the acceptance and assimilation of e-learning in academic settings. A survey of 286 participants (students was conducted to collect the research data. Our study framework was based on the third version of the Technology Acceptance Model (i.e., TAM3 and the data were analyzed using structural equation modeling in order to determine the factors that influence the learners’ intention to use e-learning. Results show the predicting (promoting/inhibiting factors of e-learning technology acceptance, while also examining some related post-implementation interventions expected to contribute to the acceptance and assimilation of e-learning systems. Our results also indicate that TAM3 holds well in the Arabian culture and also outline valuable outcomes such as: managerial interventions and controls for better organizational e-learning management that can lead to greater acceptance and effective utilization. Hopefully, this study provides a roadmap to more understanding of the success factors and post-implementation interventions contributing to the acceptance and assimilation of e-learning systems in developing countries.
Young Sik Cho
2016-05-01
Full Text Available Institutional theory argues that the isomorphic nature of quality management (QM practices leads to similar QM implementation and performance among QM-embedded firms. However, contingency theory questions such 'universal effectiveness of QM practices'. Considering these conflicting arguments, this study tests samples from the U.S. and China to examine whether the 'universal effectiveness of QM practices’ across national boundaries actually exists. First, the confirmatory factor analysis was performed to examine the validity of the survey instruments developed in this study. Then, the hypotheses were tested using the structural equation modeling (SEM analysis. The SEM test results indicated that the positive effect of behavioral QM on firm performance was more significant in the U.S. sample than in the China sample. The test results also presented that the relative effect of behavioral QM versus technical QM on firm performance was noticeably different in service firms, according to national economic maturity. The study’s findings demonstrated that a firm's contingency factors, such as national economic maturity and industry type, could result in the heterogeneous implementation of the firm’s TQM program; consequently, the findings weakened the 'universal effectiveness of QM practices'.
Modeling Adsorption Kinetics of Magnesium and Phosphate Ions on Goethite by Empirical Equations
Malihe Talebi Atouei
2017-06-01
Full Text Available Introduction: Natural environments, including soils and sediments, are open and complex systems in which physico-chemical reactions are in semi equilibrium state. In these systems, bioavailability of plant nutrients, like phosphate, is influenced by environmental conditions and concentrations of other ions such as calcium and magnesium. Magnesium is a dominant cation in irrigation water and in the soil solution of calcareous soils. Recent evidences show relative increase in the concentration of magnesium in irrigation water. Because of the importance of chemical kinetics in controlling concentrations of these ions in the soil solution and for understanding their effects of adsorption kinetics of magnesium and phosphate ions, in this research, adsorption kinetics of these two ions on goethite is investigated as function of time and pH in single ion and binary ion systems. The experimental data are described by using the adsorption kinetics equations. These data are of the great importance in better understanding adsorption interactions and ion adsorption mechanism.With respect to the importance of these interactions from both economical and environmental point of view, in this research, the kinetics and thermodynamics of phosphate and Mg2adsorption interactions were investigated as function of pH on soil model mineral goethite in both single and binary ion systems. Materials and Methods: Kinetics experiments were performed in the presence of 0.2 mM magnesium and 0.4 mM phosphate in 0.1 M NaCl background solution and 3 g L-1 goethite concentration as function of pH and time (1, 5, 14, 24, 48. 72 and 168 h in single ion and binary ion systems. After reaction time, the suspensions were centrifuged and a sample of supernatant was taken for measuring ions equilibrium concentrations.Phosphate concentration was measured calorimetrically with the ammonium molybdate blue method by spectrophotometer (Jenway-6505 UV/Vis. Magnesium concentration was
Sørup, Christian Michel; Jacobsen, Peter
2014-01-01
How can emergency department (ED) decision makers contribute to increase patient satisfaction rates? This question has been thoroughly investigated in many hospital departments but not so much in the ED, which has led to a number of untested hypotheses. Maximising value-added activities seen from...... a patient’s perspective has become an essential outcome in health care, meaning that the untested hypotheses are in need of quantitative testing. This study proposes an integrated framework in which four latent constructs reflecting principal aspects of patient care are tested. The four constructs...... are entitled safety and satisfaction, waiting time, information delivery, and infrastructure accordingly. As an empirical foundation, a recently published comprehensive survey in 11 Danish EDs is analysed in depth using structural equation modeling (SEM). Consulting the proposed framework, ED decision makers...
Regularized Structural Equation Modeling.
Jacobucci, Ross; Grimm, Kevin J; McArdle, John J
A new method is proposed that extends the use of regularization in both lasso and ridge regression to structural equation models. The method is termed regularized structural equation modeling (RegSEM). RegSEM penalizes specific parameters in structural equation models, with the goal of creating easier to understand and simpler models. Although regularization has gained wide adoption in regression, very little has transferred to models with latent variables. By adding penalties to specific parameters in a structural equation model, researchers have a high level of flexibility in reducing model complexity, overcoming poor fitting models, and the creation of models that are more likely to generalize to new samples. The proposed method was evaluated through a simulation study, two illustrative examples involving a measurement model, and one empirical example involving the structural part of the model to demonstrate RegSEM's utility.
Moro, Juliano; Denardini, Clezio Marcos; Resende, Laysa Cristina Araújo; Chen, Sony Su; Schuch, Nelson Jorge
2016-06-01
Daytime E-region electric fields play a crucial role in the ionospheric dynamics at the geomagnetic dip latitudes. Due to their importance, there is an interest in accurately measuring and modeling the electric fields for both climatological and near real-time studies. In this work, we present the daytime vertical ( Ez) and eastward ( Ey) electric fields for a reference quiet day (February 7, 2001) at the São Luís Space Observatory, Brazil (SLZ, 2.31°S, 44.16°W). The component Ez is inferred from Doppler shifts of type II echoes (gradient drift instability) and the anisotropic factor, which is computed from ion and electron gyro frequencies as well as ion and electron collision frequencies with neutral molecules. The component Ey depends on the ratio of Hall and Pedersen conductivities and Ez. A magnetic field-line-integrated conductivity model is used to obtain the anisotropic factor for calculating Ez and the ionospheric conductivities for calculating Ey. This model uses the NRLMSISE-00, IRI-2007, and IGRF-11 empirical models as input parameters for neutral atmosphere, ionosphere, and geomagnetic field, respectively. Consequently, it is worth determining the uncertainties (or errors) in Ey and Ez associated with these empirical model outputs in order to precisely define the confidence limit for the estimated electric field components. For this purpose, errors of ±10 % were artificially introduced in the magnitude of each empirical model output before estimating Ey and Ez. The corresponding uncertainties in the ionospheric conductivity and electric field are evaluated considering the individual and cumulative contribution of the artificial errors. The results show that the neutral densities and temperature may be responsible for the largest changes in Ey and Ez, followed by changes in the geomagnetic field intensity and electron and ions compositions.
Zeng, Zhaoyuanling; Wang, Xiaowan; Wang, Zengwu; Guo, Rui; Feng, Ruihua
2017-02-28
To analyze the relationship among hypertension-relevant knowledge, attitude and behavior and to provide evidence for prevention of hypertension. Methods: A total of 5 861 employees with hypertension from 10 provinces were selected, and their data were collected by uniform questionnaires. The structural equation model was established by using LISREL version 8.7. Knowledge, attitude and behavior was set as latent variables, and the observed variables corresponding to latent variables served as explicit variables. The parametric estimation of the structural equation model is based on polyserial correlation coefficients and asymptotical covariance matrix. Results: Knowledge directly affected attitude, and the impact coefficient was 0.84; attitude directly affect behavior, and the impact coefficient was 0.38; knowledge showed indirect effect on behavior; the structural equation model fitted the data well. Conclusion: Hypertension-related knowledge significantly affect attitude, while knowledge and attitude showed slight effect on behavior. There were other factors that affected the patient's behavior. It was suggested that we should fully consider the factors for behavior in health education, and adopt more appropriate measures in hypertension control.
Kessels, Roselinde; Erreygers, Guido
2016-12-01
We present a flexible structural equation modeling (SEM) framework for the regression-based decomposition of rank-dependent indicators of socioeconomic inequality of health and compare it with simple ordinary least squares (OLS) regression. The SEM framework forms the basis for a proper use of the most prominent one- and two-dimensional decompositions and provides an argument for using the bivariate multiple regression model for two-dimensional decomposition. Within the SEM framework, the two-dimensional decomposition integrates the feedback mechanism between health and socioeconomic status and allows for different sets of determinants of these variables. We illustrate the SEM approach and its outperformance of OLS using data from the 2011 Ethiopian Demographic and Health Survey.
A Novel Empirical Equation for Relative Permeability in Low Permeability Reservoirs☆
Yulei Ge; Shurong Li; Kexin Qu
2014-01-01
In this paper, a novel empirical equation is proposed to calculate the relative permeability of low permeability res-ervoir. An improved item is introduced on the basis of Rose empirical formula and Al-Fattah empirical formula, with one simple model to describe oil/water relative permeability. The position displacement idea of bare bones particle swarm optimization is applied to change the mutation operator to improve the RNA genetic algorithm. The param-eters of the new empirical equation are optimized with the hybrid RNA genetic algorithm (HRGA) based on the ex-perimental data. The data is obtained from a typical low permeability reservoir wel 54 core 27-1 in GuDong by unsteady method. We carry out matlab programming simulation with HRGA. The comparison and error analysis show that the empirical equation proposed is more accurate than the Rose empirical formula and the exponential model. The generalization of the empirical equation is also verified.
Variational estimation of the drift for stochastic differential equations from the empirical density
Batz, Philipp; Ruttor, Andreas; Opper, Manfred
2016-08-01
We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation of the Fokker-Planck equation. The minimization of an empirical estimate of the variational functional using kernel based regularization can be performed in closed form. We demonstrate the performance of the method on second order, Langevin-type equations and show how the method can be generalized to other noise models.
Variational estimation of the drift for stochastic differential equations from the empirical density
Batz, Philipp; Opper, Manfred
2016-01-01
We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation of the Fokker-Planck equation. The minimization of an empirical estimate of the variational functional using kernel based regularization can be performed in closed form. We demonstrate the performance of the method on second order, Langevin-type equations and show how the method can be generalized to other noise models.
Rouquette, Alexandra; Badley, Elizabeth M; Falissard, Bruno; Dub, Timothée; Leplege, Alain; Coste, Joël
2015-06-01
The International Classification of Functioning, Disability and Health (ICF) published in 2001 describes the consequences of health conditions with three components of impairments in body structures or functions, activity limitations and participation restrictions. Two of the new features of the conceptual model were the possibility of feedback effects between each ICF component and the introduction of contextual factors conceptualized as moderators of the relationship between the components. The aim of this longitudinal study is to provide empirical evidence of these two kinds of effect. Structural equation modeling was used to analyze data from a French population-based cohort of 548 patients with knee osteoarthritis recruited between April 2007 and March 2009 and followed for three years. Indicators of the body structure and function, activity and participation components of the ICF were derived from self-administered standardized instruments. The measurement model revealed four separate factors for body structures impairments, body functions impairments, activity limitations and participation restrictions. The classic sequence from body impairments to participation restrictions through activity limitations was found at each assessment time. Longitudinal study of the ICF component relationships showed a feedback pathway indicating that the level of participation restrictions at baseline was predictive of activity limitations three years later. Finally, the moderating role of personal (age, sex, mental health, etc.) and environmental factors (family relationships, mobility device use, etc.) was investigated. Three contextual factors (sex, family relationships and walking stick use) were found to be moderators for the relationship between the body impairments and the activity limitations components. Mental health was found to be a mediating factor of the effect of activity limitations on participation restrictions.
Gemitzi, Alexandra; Ajami, Hoori; Richnow, Hans-Hermann
2017-03-01
Groundwater recharge is one of main components of the water budget that is difficult to quantify due to complexity of recharge processes and limited observations. In the present work a simple regression equation for monthly groundwater recharge estimation is developed by relating simulated recharge from a calibrated Soil and Water Assessment tool (SWAT) model to effective precipitation. Monthly groundwater recharge and actual evapotranspiration (AET) were computed by applying a calibrated (SWAT) model for a ten year period (2005-2015) in Vosvozis river basin in NE Greece. SWAT actual evapotranspiration (AET) results were compared to remotely sensed AET values from the MODerate Resolution Imaging Spectroradiometer (MODIS), indicating the integrity of the modeling process. Water isotopes of 2H and 18O, originally presented herein, were used to infer recharge resources in the basin and provided additional evidence of the applicability of the developed formula. Results showed that the developed recharge estimation method can be effectively applied using MODIS evapotranspiration data, without having to adhere to numerical modeling which is many times constrained by the lack of available data especially in poorly gauged basins. Future trends of groundwater recharge up to 2100 using an ensemble of five downscaled climate change projections indicated that annual recharge will increase up to the middle of the present century and gradually decrease thereafter. However, the predicted magnitude is highly variable depending on the Global Climate Model (GCM) used. While winter recharge will likely increase in the future, summer recharge is expected to decrease as a result of temperature rise in the future.
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.
COMPARISON BETWEEN BOUSSINESQ EQUATIONS AND MILD-SLOPE EQUATIONS MODEL
无
2006-01-01
In this paper, the Boussinesq equations and mild-slope equation of wave transformation in near-shore shallow water were introduced and the characteristics of the two forms of equations were compared and analyzed. Meanwhile, a Boussinesq wave model which includes effects of bottom friction, wave breaking and subgrid turbulent mixing is established, slot technique dealing with moving boundary and damping layer dealing with absorbing boundary were established. By adopting empirical nonlinear dispersion relation and including nonlinear term, the mild-slope equation model was modified to take nonlinear effects into account. The two types of models were validated with the experiment results given by Berkhoff and their accuracy was analysed and compared with that of correlated methods.
Structural Equation Model Trees
Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman
2013-01-01
In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…
Empirical Vector Autoregressive Modeling
M. Ooms (Marius)
1993-01-01
textabstractChapter 2 introduces the baseline version of the VAR model, with its basic statistical assumptions that we examine in the sequel. We first check whether the variables in the VAR can be transformed to meet these assumptions. We analyze the univariate characteristics of the series. Import
Empirical Vector Autoregressive Modeling
M. Ooms (Marius)
1993-01-01
textabstractChapter 2 introduces the baseline version of the VAR model, with its basic statistical assumptions that we examine in the sequel. We first check whether the variables in the VAR can be transformed to meet these assumptions. We analyze the univariate characteristics of the series. Import
Empirical Model Building Data, Models, and Reality
Thompson, James R
2011-01-01
Praise for the First Edition "This...novel and highly stimulating book, which emphasizes solving real problems...should be widely read. It will have a positive and lasting effect on the teaching of modeling and statistics in general." - Short Book Reviews This new edition features developments and real-world examples that showcase essential empirical modeling techniques Successful empirical model building is founded on the relationship between data and approximate representations of the real systems that generated that data. As a result, it is essential for researchers who construct these m
2014-11-19
treatment of nonaffine and nonlinear partial differential equations ., ESAIM, Math. Model. Numer. Anal. 41(3) (2007) 575–605. [8] Y. Maday, N. Nguyen, A...and Numerics of Partial Differential Equations , Vol. 4 of Springer INdAM Series, Springer Milan, 2013, pp. 221–235. [2] M. Barrault, Y. Maday, N...Nguyen, A. Patera, An empirical interpolation method: Application to efficient reduced-basis discretization of partial differential equations ., C. R
Vijay K. Garg
1998-01-01
reason for the discrepancy on the pressure surface could be the presence of unsteady effects due to stator-rotor interaction in the experiments which are not modeled in the present computations. Prediction using the two-equation model is in general poorer than that using the zero-equation model, while the former requires at least 40% more computational resources.
Empirically Based, Agent-based models
Elinor Ostrom
2006-12-01
Full Text Available There is an increasing drive to combine agent-based models with empirical methods. An overview is provided of the various empirical methods that are used for different kinds of questions. Four categories of empirical approaches are identified in which agent-based models have been empirically tested: case studies, stylized facts, role-playing games, and laboratory experiments. We discuss how these different types of empirical studies can be combined. The various ways empirical techniques are used illustrate the main challenges of contemporary social sciences: (1 how to develop models that are generalizable and still applicable in specific cases, and (2 how to scale up the processes of interactions of a few agents to interactions among many agents.
Md Shamsul Arefin
2012-12-01
Full Text Available This work presents a technique for the chirality (n, m assignment of semiconducting single wall carbon nanotubes by solving a set of empirical equations of the tight binding model parameters. The empirical equations of the nearest neighbor hopping parameters, relating the term (2n, m with the first and second optical transition energies of the semiconducting single wall carbon nanotubes, are also proposed. They provide almost the same level of accuracy for lower and higher diameter nanotubes. An algorithm is presented to determine the chiral index (n, m of any unknown semiconducting tube by solving these empirical equations using values of radial breathing mode frequency and the first or second optical transition energy from resonant Raman spectroscopy. In this paper, the chirality of 55 semiconducting nanotubes is assigned using the first and second optical transition energies. Unlike the existing methods of chirality assignment, this technique does not require graphical comparison or pattern recognition between existing experimental and theoretical Kataura plot.
Arefin, Md Shamsul
2012-01-01
This work presents a technique for the chirality (n, m) assignment of semiconducting single wall carbon nanotubes by solving a set of empirical equations of the tight binding model parameters. The empirical equations of the nearest neighbor hopping parameters, relating the term (2n− m) with the first and second optical transition energies of the semiconducting single wall carbon nanotubes, are also proposed. They provide almost the same level of accuracy for lower and higher diameter nanotubes. An algorithm is presented to determine the chiral index (n, m) of any unknown semiconducting tube by solving these empirical equations using values of radial breathing mode frequency and the first or second optical transition energy from resonant Raman spectroscopy. In this paper, the chirality of 55 semiconducting nanotubes is assigned using the first and second optical transition energies. Unlike the existing methods of chirality assignment, this technique does not require graphical comparison or pattern recognition between existing experimental and theoretical Kataura plot.
Elman, Howard C.; Forstall, Virginia
2017-04-01
Reduced-order modeling is an efficient approach for solving parameterized discrete partial differential equations when the solution is needed at many parameter values. An offline step approximates the solution space and an online step utilizes this approximation, the reduced basis, to solve a smaller reduced problem at significantly lower cost, producing an accurate estimate of the solution. For nonlinear problems, however, standard methods do not achieve the desired cost savings. Empirical interpolation methods represent a modification of this methodology used for cases of nonlinear operators or nonaffine parameter dependence. These methods identify points in the discretization necessary for representing the nonlinear component of the reduced model accurately, and they incur online computational costs that are independent of the spatial dimension $N$. We will show that empirical interpolation methods can be used to significantly reduce the costs of solving parameterized versions of the Navier-Stokes equations, and that iterative solution methods can be used in place of direct methods to further reduce the costs of solving the algebraic systems arising from reduced-order models.
Zhang, Zhilin; Savenije, Hubert H. G.
2017-07-01
The practical value of the surprisingly simple Van der Burgh equation in predicting saline water intrusion in alluvial estuaries is well documented, but the physical foundation of the equation is still weak. In this paper we provide a connection between the empirical equation and the theoretical literature, leading to a theoretical range of Van der Burgh's coefficient of 1/2 residual circulation. This type of mixing is relevant in the wider part of alluvial estuaries where preferential ebb and flood channels appear. Subsequently, this dispersion equation is combined with the salt balance equation to obtain a new predictive analytical equation for the longitudinal salinity distribution. Finally, the new equation was tested and applied to a large database of observations in alluvial estuaries, whereby the calibrated K values appeared to correspond well to the theoretical range.
Developing Empirically Based Models of Practice.
Blythe, Betty J.; Briar, Scott
1985-01-01
Over the last decade emphasis has shifted from theoretically based models of practice to empirically based models whose elements are derived from clinical research. These models are defined and a developing model of practice through the use of single-case methodology is examined. Potential impediments to this new role are identified. (Author/BL)
Handbook of structural equation modeling
Hoyle, Rick H
2012-01-01
The first comprehensive structural equation modeling (SEM) handbook, this accessible volume presents both the mechanics of SEM and specific SEM strategies and applications. The editor, contributors, and editorial advisory board are leading methodologists who have organized the book to move from simpler material to more statistically complex modeling approaches. Sections cover the foundations of SEM; statistical underpinnings, from assumptions to model modifications; steps in implementation, from data preparation through writing the SEM report; and basic and advanced applications, inclu
Model uncertainty in growth empirics
Prüfer, P.
2008-01-01
This thesis applies so-called Bayesian model averaging (BMA) to three different economic questions substantially exposed to model uncertainty. Chapter 2 addresses a major issue of modern development economics: the analysis of the determinants of pro-poor growth (PPG), which seeks to combine high gro
The Chromospheric Solar Millimeter-wave Cavity; a Common Property in the Semi-empirical Models
Victor, De la Luz; Emanuele, Bertone
2014-01-01
The semi-empirical models of the solar chromosphere are useful in the study of the solar radio emission at millimeter - infrared wavelengths. However, current models do not reproduce the observations of the quiet sun. In this work we present a theoretical study of the radiative transfer equation for four semi- empirical models at these wavelengths. We found that the Chromospheric Solar Milimeter-wave Cavity (CSMC), a region where the atmosphere becomes locally optically thin at millimeter wavelengths, is present in the semi-empirical models under study. We conclude that the CSMC is a general property of the solar chromosphere where the semi-empirical models shows temperature minimum.
STUDY OF NEUROSES: III AN EMPIRICAL MODEL*
Bhatti, Ranbir S.; Channabasavanna, S.M.
1986-01-01
SUMMARY The empirical model presented in this paper is based on observations made on 60 neurotics and 60 normals matched at the individual level. Efforts are made to use the systems approach to present this paradigm synthesising both individual and environmental resources. We are of the opinion that this model is not only useful in understanding the genesis of neuroses rather has utility at the intervention level as well.
Kutílek, M; Jendele, L; Krejca, M
2009-02-16
The accelerated flow in soil pores is responsible for a rapid transport of pollutants from the soil surface to deeper layers up to groundwater. The term preferential flow is used for this type of transport. Our study was aimed at the preferential flow realized in the structural porous domain in bi-modal soils. We compared equations describing the soil water retention function h(theta) and unsaturated hydraulic conductivity K(h), eventually K(theta) modified for bi-modal soils, where theta is the soil water content and h is the pressure head. The analytical description of a curve passing experimental data sets of the soil hydraulic function is typical for the empirical equation characterized by fitting parameters only. If the measured data are described by the equation derived by the physical model without using fitting parameters, we speak about a physically based model. There exist several transitional subtypes between empirical and physically based models. They are denoted as semi-empirical, or semi-physical. We tested 3 models of soil water retention function and 3 models of unsaturated conductivity using experimental data sets of sand, silt, silt loam and loam. All used soils are typical by their bi-modality of the soil porous system. The model efficiency was estimated by RMSE (Root mean square error) and by RSE (Relative square error). The semi-empirical equation of the soil water retention function had the lowest values of RMSE and RSE and was qualified as "optimal" for the formal description of the shape of the water retention function. With this equation, the fit of the modelled data to experiments was the closest one. The fitting parameters smoothed the difference between the model and the physical reality of the soil porous media. The physical equation based upon the model of the pore size distribution did not allow exact fitting of the modelled data to the experimental data due to the rigidity and simplicity of the physical model when compared to the
Empirical generalization assessment of neural network models
Larsen, Jan; Hansen, Lars Kai
1995-01-01
competing models. Since all models are trained on the same data, a key issue is to take this dependency into account. The optimal split of the data set of size N into a cross-validation set of size Nγ and a training set of size N(1-γ) is discussed. Asymptotically (large data sees), γopt→1......This paper addresses the assessment of generalization performance of neural network models by use of empirical techniques. We suggest to use the cross-validation scheme combined with a resampling technique to obtain an estimate of the generalization performance distribution of a specific model...
A review of wildland fire spread modelling, 1990-present 2: Empirical and quasi-empirical models
Sullivan, A L
2007-01-01
In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behaviour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of an empirical or quasi-empirical nature. These models are based solely on the statistical analysis of experimentally obtained data with or without some physical framework for the basis of the relations. Other papers in the series review models of a physical or quasi-physical nature, and mathematical analogues and simulation models. The main relations of empirical models are that of wind speed and fuel moisture content with rate of forward spread. Comparisons are made of the different functional relationships selected by various authors for these variables.
Bayes and empirical Bayes iteration estimators in two seemingly unrelated regression equations
WANG; Lichun
2005-01-01
For a system of two seemingly unrelated regression equations given by {y1=X1β+ε1,y2=X2γ+ε2, (y1 is an m × 1 vector and y2 is an n × 1 vector, m≠ n), employing the covariance adjusted technique, we propose the parametric Bayes and empirical Bayes iteration estimator sequences for regression coefficients. We prove that both the covariance matrices converge monotonically and the Bayes iteration estimator squence is consistent as well. Based on the mean square error (MSE) criterion, we elaborate the superiority of empirical Bayes iteration estimator over the Bayes estimator of single equation when the covariance matrix of errors is unknown. The results obtained in this paper further show the power of the covariance adjusted approach.
Empirical correction of a toy climate model
Allgaier, Nicholas A; Danforth, Christopher M
2011-01-01
Improving the accuracy of forecast models for physical systems such as the atmosphere is a crucial ongoing effort. Errors in state estimation for these often highly nonlinear systems has been the primary focus of recent research, but as that error has been successfully diminished, the role of model error in forecast uncertainty has duly increased. The present study is an investigation of a particular empirical correction procedure that is of special interest because it considers the model a "black box", and therefore can be applied widely with little modification. The procedure involves the comparison of short model forecasts with a reference "truth" system during a training period in order to calculate systematic (1) state-independent model bias and (2) state-dependent error patterns. An estimate of the likelihood of the latter error component is computed from the current state at every timestep of model integration. The effectiveness of this technique is explored in two experiments: (1) a perfect model scen...
Thermoviscous Model Equations in Nonlinear Acoustics
Rasmussen, Anders Rønne
Four nonlinear acoustical wave equations that apply to both perfect gasses and arbitrary fluids with a quadratic equation of state are studied. Shock and rarefaction wave solutions to the equations are studied. In order to assess the accuracy of the wave equations, their solutions are compared...... to solutions of the basic equations from which the wave equations are derived. A straightforward weakly nonlinear equation is the most accurate for shock modeling. A higher order wave equation is the most accurate for modeling of smooth disturbances. Investigations of the linear stability properties...... of solutions to the wave equations, reveal that the solutions may become unstable. Such instabilities are not found in the basic equations. Interacting shocks and standing shocks are investigated....
Analysis of Empirical Software Effort Estimation Models
Basha, Saleem
2010-01-01
Reliable effort estimation remains an ongoing challenge to software engineers. Accurate effort estimation is the state of art of software engineering, effort estimation of software is the preliminary phase between the client and the business enterprise. The relationship between the client and the business enterprise begins with the estimation of the software. The credibility of the client to the business enterprise increases with the accurate estimation. Effort estimation often requires generalizing from a small number of historical projects. Generalization from such limited experience is an inherently under constrained problem. Accurate estimation is a complex process because it can be visualized as software effort prediction, as the term indicates prediction never becomes an actual. This work follows the basics of the empirical software effort estimation models. The goal of this paper is to study the empirical software effort estimation. The primary conclusion is that no single technique is best for all sit...
An empirical behavioral model of price formation
Mike, S
2005-01-01
Although behavioral economics has demonstrated that there are many situations where rational choice is a poor empirical model, it has so far failed to provide quantitative models of economic problems such as price formation. We make a step in this direction by developing empirical models that capture behavioral regularities in trading order placement and cancellation using data from the London Stock Exchange. For order placement we show that the probability of placing an order at a given price is well approximated by a Student distribution with less than two degrees of freedom, centered on the best quoted price. This result is surprising because it implies that trading order placement is symmetric, independent of the bid-ask spread, and the same for buying and selling. We also develop a crude but simple cancellation model that depends on the position of an order relative to the best price and the imbalance between buying and selling orders in the limit order book. These results are combined to construct a sto...
Empirical data validation for model building
Kazarian, Aram
2008-03-01
Optical Proximity Correction (OPC) has become an integral and critical part of process development for advanced technologies with challenging k I requirements. OPC solutions in turn require stable, predictive models to be built that can project the behavior of all structures. These structures must comprehend all geometries that can occur in the layout in order to define the optimal corrections by feature, and thus enable a manufacturing process with acceptable margin. The model is built upon two main component blocks. First, is knowledge of the process conditions which includes the optical parameters (e.g. illumination source, wavelength, lens characteristics, etc) as well as mask definition, resist parameters and process film stack information. Second, is the empirical critical dimension (CD) data collected using this process on specific test features the results of which are used to fit and validate the model and to project resist contours for all allowable feature layouts. The quality of the model therefore is highly dependent on the integrity of the process data collected for this purpose. Since the test pattern suite generally extends to below the resolution limit that the process can support with adequate latitude, the CD measurements collected can often be quite noisy with marginal signal-to-noise ratios. In order for the model to be reliable and a best representation of the process behavior, it is necessary to scrutinize empirical data to ensure that it is not dominated by measurement noise or flyer/outlier points. The primary approach for generating a clean, smooth and dependable empirical data set should be a replicated measurement sampling that can help to statistically reduce measurement noise by averaging. However, it can often be impractical to collect the amount of data needed to ensure a clean data set by this method. An alternate approach is studied in this paper to further smooth the measured data by means of curve fitting to identify remaining
Pan, Feifei; Nieswiadomy, Michael
2016-11-01
Soil moisture in snow-dominated regions has many important applications including evapotranspiration estimation, flood forecasting, water resource and ecosystem services management, weather prediction and climate modeling, and quantification of denudation processes. A simple and robust empirical approach to estimate root-zone soil moisture in snow-dominated regions using a soil moisture diagnostic equation that incorporates snowfall and snowmelt processes is suggested and tested. A five-water-year dataset (10/1/2010-9/30/2015) of daily precipitation, air temperature, snow water equivalent and soil moistures at three depths (i.e., 5 cm, 20 cm, and 50 cm) at each of 12 Snow Telemetry (SNOTEL) sites across Utah (37.583°N-41.883°N, 110.183°W-112.9°W), is applied to test the proposed method. The first three water years are designated as the parameter-estimation period (PEP) and the last two water years are chosen as the model-testing period (MTP). Applying the estimated soil moisture loss function parameters and other empirical parameters in the soil moisture diagnostic equation in the PEP, soil moistures in three soil columns (0-5 cm, 0-20 cm, and 0-50 cm) are estimated in the MTP. The relatively accurate soil moisture estimations compared to the observations at 12 SNOTEL sites (RMSE ⩽ 6.23 (%V/V), average RMSE = 4.28 (%V/V), correlation coefficient ⩾0.75, average correlation coefficient =0.89, the Nash-Sutcliffe efficient coefficient Ec ⩾ 0.24, average Ec = 0.72) indicate that the soil moisture diagnostic equation is capable of accurately estimating soil moisture in snow-dominated regions after the snowfall and snowmelt processes are included in the soil moisture diagnostic equation.
Modelling conjugation with stochastic differential equations
Philipsen, Kirsten Riber; Christiansen, Lasse Engbo; Hasman, Henrik
2010-01-01
Conjugation is an important mechanism involved in the transfer of resistance between bacteria. In this article a stochastic differential equation based model consisting of a continuous time state equation and a discrete time measurement equation is introduced to model growth and conjugation of two...... using a likelihood-ratio test and Akaike's information criterion. Experiments indicating conjugation on the agar plates selecting for transconjugants motivates the introduction of an extended model, for which conjugation on the agar plate is described in the measurement equation. This model is compared...
The Trauma Outcome Process Assessment Model: A Structural Equation Model Examination of Adjustment
Borja, Susan E.; Callahan, Jennifer L.
2009-01-01
This investigation sought to operationalize a comprehensive theoretical model, the Trauma Outcome Process Assessment, and test it empirically with structural equation modeling. The Trauma Outcome Process Assessment reflects a robust body of research and incorporates known ecological factors (e.g., family dynamics, social support) to explain…
Strategic Competence as a Fourth-Order Factor Model: A Structural Equation Modeling Approach
Phakiti, Aek
2008-01-01
This article reports on an empirical study that tests a fourth-order factor model of strategic competence through the use of structural equation modeling (SEM). The study examines the hierarchical relationship of strategic competence to (a) strategic knowledge of cognitive and metacognitive strategy use in general (i.e., trait) and (b) strategic…
Structural Equation Modeling of Travel Choice Dynamics
Golob, Thomas F.
1988-01-01
This research has two objectives. The first objective is to explore the use of the modeling tool called "latent structural equations" (structural equations with latent variables) in the general field of travel behavior analysis and the more specific field of dynamic analysis of travel behavior. The second objective is to apply a latent structural equation model in order to determine the causal relationships between income, car ownership, and mobility. Many transportation researchers ...
Discrete Surface Modelling Using Partial Differential Equations.
Xu, Guoliang; Pan, Qing; Bajaj, Chandrajit L
2006-02-01
We use various nonlinear partial differential equations to efficiently solve several surface modelling problems, including surface blending, N-sided hole filling and free-form surface fitting. The nonlinear equations used include two second order flows, two fourth order flows and two sixth order flows. These nonlinear equations are discretized based on discrete differential geometry operators. The proposed approach is simple, efficient and gives very desirable results, for a range of surface models, possibly having sharp creases and corners.
Modelling conjugation with stochastic differential equations.
Philipsen, K R; Christiansen, L E; Hasman, H; Madsen, H
2010-03-07
Conjugation is an important mechanism involved in the transfer of resistance between bacteria. In this article a stochastic differential equation based model consisting of a continuous time state equation and a discrete time measurement equation is introduced to model growth and conjugation of two Enterococcus faecium strains in a rich exhaustible media. The model contains a new expression for a substrate dependent conjugation rate. A maximum likelihood based method is used to estimate the model parameters. Different models including different noise structure for the system and observations are compared using a likelihood-ratio test and Akaike's information criterion. Experiments indicating conjugation on the agar plates selecting for transconjugants motivates the introduction of an extended model, for which conjugation on the agar plate is described in the measurement equation. This model is compared to the model without plate conjugation. The modelling approach described in this article can be applied generally when modelling dynamical systems.
Empirical Reduced-Order Modeling for Boundary Feedback Flow Control
Seddik M. Djouadi
2008-01-01
Full Text Available This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE- based models in general. Specifically, the proper orthogonal decomposition (POD of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA. This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. An H∞ feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.
Modeling helicity dissipation-rate equation
Yokoi, Nobumitsu
2016-01-01
Transport equation of the dissipation rate of turbulent helicity is derived with the aid of a statistical analytical closure theory of inhomogeneous turbulence. It is shown that an assumption on the helicity scaling with an algebraic relationship between the helicity and its dissipation rate leads to the transport equation of the turbulent helicity dissipation rate without resorting to a heuristic modeling.
Structural Equation Modeling of Multivariate Time Series
du Toit, Stephen H. C.; Browne, Michael W.
2007-01-01
The covariance structure of a vector autoregressive process with moving average residuals (VARMA) is derived. It differs from other available expressions for the covariance function of a stationary VARMA process and is compatible with current structural equation methodology. Structural equation modeling programs, such as LISREL, may therefore be…
Stochastic differential equation model to Prendiville processes
Granita, E-mail: granitafc@gmail.com [Dept. of Mathematical Science, Universiti Teknologi Malaysia, 81310, Johor Malaysia (Malaysia); Bahar, Arifah [Dept. of Mathematical Science, Universiti Teknologi Malaysia, 81310, Johor Malaysia (Malaysia); UTM Center for Industrial & Applied Mathematics (UTM-CIAM) (Malaysia)
2015-10-22
The Prendiville process is another variation of the logistic model which assumes linearly decreasing population growth rate. It is a continuous time Markov chain (CTMC) taking integer values in the finite interval. The continuous time Markov chain can be approximated by stochastic differential equation (SDE). This paper discusses the stochastic differential equation of Prendiville process. The work started with the forward Kolmogorov equation in continuous time Markov chain of Prendiville process. Then it was formulated in the form of a central-difference approximation. The approximation was then used in Fokker-Planck equation in relation to the stochastic differential equation of the Prendiville process. The explicit solution of the Prendiville process was obtained from the stochastic differential equation. Therefore, the mean and variance function of the Prendiville process could be easily found from the explicit solution.
Stochastic differential equation model to Prendiville processes
Granita, Bahar, Arifah
2015-10-01
The Prendiville process is another variation of the logistic model which assumes linearly decreasing population growth rate. It is a continuous time Markov chain (CTMC) taking integer values in the finite interval. The continuous time Markov chain can be approximated by stochastic differential equation (SDE). This paper discusses the stochastic differential equation of Prendiville process. The work started with the forward Kolmogorov equation in continuous time Markov chain of Prendiville process. Then it was formulated in the form of a central-difference approximation. The approximation was then used in Fokker-Planck equation in relation to the stochastic differential equation of the Prendiville process. The explicit solution of the Prendiville process was obtained from the stochastic differential equation. Therefore, the mean and variance function of the Prendiville process could be easily found from the explicit solution.
Semi-empirical model of solar plages
FANG; Cheng
2001-01-01
［1］ Zirin, H., Astrophysics of the Sun, Chapter 7, Cambridge: Cambridge University Press, 1988.［2］ Shine, R. A., Linsky, J. L., Physical properties of solar chromospheric plages II. Chromospheric plage models, Solar Phys., 1974, 39: 49.［3］ Kelch, W. L., Linsky, J. L., Physical properties of solar chromospheric plages III. Models based on CaII and MgII observations, Solar Phys., 1978, 58: 37.［4］ Lemaire, P., Goutlebroze, J. C., Vial, J. C. et al., Physical properties of the solar chromosphere deduced from optically thick lines, A & A, 1981, 103: 160.［5］ Fontenla, J. M., Avrett, E. H., Loeser, R., Energy balance in the solar transition region II. Effects of pressure and energy input on hydrostatic models, ApJ, 1991, 377: 712.［6］ Fontenla, J. M., Avrett, E. H., Loeser, R., Energy balance in the solar transition region III. Helium emission in hydrostatic, constant-abundance models with diffusion, ApJ, 1993, 406: 319.［7］ Pierce, A. K., Slaughter, C., Solar limb darkening I: λλ(30337297), Solar Phys., 1977, 51: 25.［8］ Pierce, A. K., Slaughter, C., Weinberger, D., Solar limb darkening in the interval 740424018*!, II, Solar Phys., 1977, 52: 179.［9］ Nechel, H., Labs, D., The solar radiation between 3300 and 12500*!, Solar Phys., 1984, 90: 205.［10］ Vernazza, J. E., Avrett, E. H., Loeser, R., Structure of the solar chromosphere I. Basic computations and summary of the results, ApJ, 1973, 184: 605.［11］ Mihalas, D., Stellar Atmospheres, San Francisco: W. H. Freeman and Company, 1978.［12］ Fang, C., Hnoux, J. -C., Self-consistent model of flare heated solar chromosphere, A & A, 1983, 118: 139.［13］ Ding, M. D., Fang, C., A semi-empirical model of sunspot penumbra, A & A, 1989, 225: 204.［14］ Vernazza, J. E., Avrett, E. H., Loeser, R., Structure of the solar chromosphere III. Models of the EUV brightness components of the quiet Sun, ApJ Suppl., 1981, 45: 635.［15］ Canfield, R. C., Athey, R
郝金磊; 胡强
2015-01-01
Customer is an important resource of bank. Improving customers’ satisfaction becomes the key to the sustainable development of the commercial bank under the fierce market competition. According to the data from investigation, this article analyses the factors which influence the customer satisfaction of commercial banks via using the structural equation model. The author discovers that the customer satisfaction of commercial bank is influenced significantly by the service quality, the operational capacity, and the environment characteristics, while the customer personal characteristics impact is feeble. In terms of observed variables, service consciousness, service attitude, and service efficiency play an important role in the service quality and customer satisfaction;business varieties, business expenses, and professional skill play a vital role in the operational capacity and customer satisfaction; traffic conditions and hall environment impact significantly on the characteristics of environment. Based on above conclusions, this article takes some measures to improve customer satisfaction of commercial banks.%顾客是银行的重要资源，在日趋激烈的市场竞争中，提高顾客满意度成为商业银行可持续发展的关键所在。以微观调查数据为基础，构建结构方程模型对我国商业银行顾客满意度的影响因素进行了研究。结果表明：商业银行顾客满意度主要受潜变量服务质量、业务能力和环境特征的影响显著，而受顾客个人特征的影响较小；可观测变量服务意识、服务态度和服务效率对服务质量及顾客满意度的影响显著；可观测变量业务种类、业务费用和业务水平对业务能力和顾客满意度的影响显著；可观测变量交通状况和厅内环境对环境特征及顾客满意度的影响显著。基于以上研究结论，提出了提高商业银行顾客满意度的对策建议。
A first course in structural equation modeling
Raykov, Tenko
2012-01-01
In this book, authors Tenko Raykov and George A. Marcoulides introduce students to the basics of structural equation modeling (SEM) through a conceptual, nonmathematical approach. For ease of understanding, the few mathematical formulas presented are used in a conceptual or illustrative nature, rather than a computational one.Featuring examples from EQS, LISREL, and Mplus, A First Course in Structural Equation Modeling is an excellent beginner's guide to learning how to set up input files to fit the most commonly used types of structural equation models with these programs. The basic ideas and methods for conducting SEM are independent of any particular software.Highlights of the Second Edition include: Review of latent change (growth) analysis models at an introductory level Coverage of the popular Mplus program Updated examples of LISREL and EQS A CD that contains all of the text's LISREL, EQS, and Mplus examples.A First Course in Structural Equation Modeling is intended as an introductory book for students...
Distribution of longshore sediment transport along the Indian coast based on empirical model
Chandramohan, P.; Nayak, B.U.
An empirical sediment transport model has been developed based on longshore energy flux equation. Study indicates that annual gross sediment transport rate is high (1.5 x 10 super(6) cubic meters to 2.0 x 10 super(6) cubic meters) along the coasts...
Partial Differential Equations Modeling and Numerical Simulation
Glowinski, Roland
2008-01-01
This book is dedicated to Olivier Pironneau. For more than 250 years partial differential equations have been clearly the most important tool available to mankind in order to understand a large variety of phenomena, natural at first and then those originating from human activity and technological development. Mechanics, physics and their engineering applications were the first to benefit from the impact of partial differential equations on modeling and design, but a little less than a century ago the Schrödinger equation was the key opening the door to the application of partial differential equations to quantum chemistry, for small atomic and molecular systems at first, but then for systems of fast growing complexity. Mathematical modeling methods based on partial differential equations form an important part of contemporary science and are widely used in engineering and scientific applications. In this book several experts in this field present their latest results and discuss trends in the numerical analy...
Structural equation modeling methods and applications
Wang, Jichuan
2012-01-01
A reference guide for applications of SEM using Mplus Structural Equation Modeling: Applications Using Mplus is intended as both a teaching resource and a reference guide. Written in non-mathematical terms, this book focuses on the conceptual and practical aspects of Structural Equation Modeling (SEM). Basic concepts and examples of various SEM models are demonstrated along with recently developed advanced methods, such as mixture modeling and model-based power analysis and sample size estimate for SEM. The statistical modeling program, Mplus, is also featured and provides researchers with a
Stochastic differential equations used to model conjugation
Philipsen, Kirsten Riber; Christiansen, Lasse Engbo
Stochastic differential equations (SDEs) are used to model horizontal transfer of antibiotic resis- tance by conjugation. The model describes the concentration of donor, recipient, transconjugants and substrate. The strength of the SDE model over the traditional ODE models is that the noise can...
Modified Heisenberg Ferromagnet Model and Integrable Equation
无
2005-01-01
We investigate some integrable modified Heisenberg ferromagnet models by using the prolongation structure theory. Through associating them with the motion of curve in Minkowski space, the corresponding coupled integrable equations are presented.
Linear causal modeling with structural equations
Mulaik, Stanley A
2009-01-01
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal
Combat modeling with partial differential equations
Protopopescu, V.; Santoro, R.T.; Dockery, J.; Cox, R.L.; Barnes, J.M.
1987-11-01
A new analytic model based on coupled nonlinear partial differential equations is proposed to describe the temporal and spatial evolution of opposing forces in combat. Analytic descriptions of combat have been developed previously using relatively simpler models based on ordinary differential equations (.e.g, Lanchester's equations of combat) that capture only the global temporal variation of the forces, but not their spatial movement (advance, retreat, flanking maneuver, etc.). The rationale for analytic models and, particularly, the motivation for the present model are reviewed. A detailed description of this model in terms of the mathematical equations together with the possible and plausible military interpretation are presented. Numerical solutions of the nonlinear differential equation model for a large variety of parameters (battlefield length, initial force ratios, initial spatial distribution of forces, boundary conditions, type of interaction, etc.) are implemented. The computational methods and computer programs are described and the results are given in tabular and graphic form. Where possible, the results are compared with the predictions given by the traditional Lanchester equations. Finally, a PC program is described that uses data downloaded from the mainframe computer for rapid analysis of the various combat scenarios. 11 refs., 10 figs., 5 tabs.
2009-10-01
Beattie - Bridgeman Virial expansion The above equations are suitable for moderate pressures and are usually based on either empirical constants...CR 2010-013 October 2009 A Review of Equation of State Models, Chemical Equilibrium Calculations and CERV Code Requirements for SHS Detonation...Defence R&D Canada. A Review of Equation of State Models, Chemical Equilibrium Calculations and CERV Code Requirements for SHS Detonation
Structural Equation Modeling in Special Education Research.
Moore, Alan D.
1995-01-01
This article suggests the use of structural equation modeling in special education research, to analyze multivariate data from both nonexperimental and experimental research. It combines a structural model linking latent variables and a measurement model linking observed variables with latent variables. (Author/DB)
Multiplicity Control in Structural Equation Modeling
Cribbie, Robert A.
2007-01-01
Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…
Global identifiability of linear structural equation models
Drton, Mathias; Sullivant, Seth
2010-01-01
Structural equation models are multivariate statistical models that are defined by specifying noisy functional relationships among random variables. We consider the classical case of linear relationships and additive Gaussian noise terms. We give a necessary and sufficient condition for global identifiability of the model in terms of a mixed graph encoding the linear structural equations and the correlation structure of the error terms. Global identifiability is understood to mean injectivity of the parametrization of the model and is fundamental in particular for applicability of standard statistical methodology.
An empirical model of tropical ocean dynamics
Newman, Matthew; Scott, James D. [University of Colorado, CIRES Climate Diagnostics Center, Boulder, CO (United States); NOAA Earth System Research Laboratory, Physical Sciences Division, Boulder, CO (United States); Alexander, Michael A. [NOAA Earth System Research Laboratory, Physical Sciences Division, Boulder, CO (United States)
2011-11-15
To extend the linear stochastically forced paradigm of tropical sea surface temperature (SST) variability to the subsurface ocean, a linear inverse model (LIM) is constructed from the simultaneous and 3-month lag covariances of observed 3-month running mean anomalies of SST, thermocline depth, and zonal wind stress. This LIM is then used to identify the empirically-determined linear dynamics with physical processes to gauge their relative importance to ENSO evolution. Optimal growth of SST anomalies over several months is triggered by both an initial SST anomaly and a central equatorial Pacific thermocline anomaly that propagates slowly eastward while leading the amplifying SST anomaly. The initial SST and thermocline anomalies each produce roughly half the SST amplification. If interactions between the sea surface and the thermocline are removed in the linear dynamical operator, the SST anomaly undergoes less optimal growth but is also more persistent, and its location shifts from the eastern to central Pacific. Optimal growth is also found to be essentially the result of two stable eigenmodes with similar structure but differing 2- and 4-year periods evolving from initial destructive to constructive interference. Variations among ENSO events could then be a consequence not of changing stability characteristics but of random excitation of these two eigenmodes, which represent different balances between surface and subsurface coupled dynamics. As found in previous studies, the impact of the additional variables on LIM SST forecasts is relatively small for short time scales. Over time intervals greater than about 9 months, however, the additional variables both significantly enhance forecast skill and predict lag covariances and associated power spectra whose closer agreement with observations enhances the validation of the linear model. Moreover, a secondary type of optimal growth exists that is not present in a LIM constructed from SST alone, in which initial SST
Basics of Structural Equation Modeling
Maruyama, Dr Geoffrey M
1997-01-01
With the availability of software programs, such as LISREL, EQS, and AMOS, modeling (SEM) techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and test for the plausibility of hypothesizing for a particular data set. Through the use of careful narrative explanation, Maruyama's text describes the logic underlying SEM approaches, describes how SEM approaches relate to techniques like regression and factor analysis, analyzes the strengths and shortcomings of SEM as compared to alternative methodologies, and explores
String Field Equations from Generalized Sigma Model
Bardakci, K.; Bernardo, L.M.
1997-01-29
We propose a new approach for deriving the string field equations from a general sigma model on the world-sheet. This approach leads to an equation which combines some of the attractive features of both the renormalization group method and the covariant beta function treatment of the massless excitations. It has the advantage of being covariant under a very general set of both local and non-local transformations in the field space. We apply it to the tachyon, massless and first massive level, and show that the resulting field equations reproduce the correct spectrum of a left-right symmetric closed bosonic string.
EMPIRICAL LIKELIHOOD FOR LINEAR MODELS UNDER m-DEPENDENT ERRORS
QinYongsong; JiangBo; LiYufang
2005-01-01
In this paper，the empirical likelihood confidence regions for the regression coefficient in a linear model are constructed under m-dependent errors. It is shown that the blockwise empirical likelihood is a good way to deal with dependent samples.
An Empirical Investigation into a Subsidiary Absorptive Capacity Process Model
Schleimer, Stephanie; Pedersen, Torben
2011-01-01
and empirically test a process model of absorptive capacity. The setting of our empirical study is 213 subsidiaries of multinational enterprises and the focus is on the capacity of these subsidiaries to successfully absorb best practices in marketing strategy from their headquarters. This setting allows us...
Bibliometric Modeling Processes and the Empirical Validity of Lotka's Law.
Nicholls, Paul Travis
1989-01-01
Examines the elements involved in fitting a bibliometric model to empirical data, proposes a consistent methodology for applying Lotka's law, and presents the results of an empirical test of the methodology. The results are discussed in terms of the validity of Lotka's law and the suitability of the proposed methodology. (49 references) (CLB)
Entropic lattice Boltzmann model for Burgers's equation.
Boghosian, Bruce M; Love, Peter; Yepez, Jeffrey
2004-08-15
Entropic lattice Boltzmann models are discrete-velocity models of hydrodynamics that possess a Lyapunov function. This feature makes them useful as nonlinearly stable numerical methods for integrating hydrodynamic equations. Over the last few years, such models have been successfully developed for the Navier-Stokes equations in two and three dimensions, and have been proposed as a new category of subgrid model of turbulence. In the present work we develop an entropic lattice Boltzmann model for Burgers's equation in one spatial dimension. In addition to its pedagogical value as a simple example of such a model, our result is actually a very effective way to simulate Burgers's equation in one dimension. At moderate to high values of viscosity, we confirm that it exhibits no trace of instability. At very small values of viscosity, however, we report the existence of oscillations of bounded amplitude in the vicinity of the shock, where gradient scale lengths become comparable with the grid size. As the viscosity decreases, the amplitude at which these oscillations saturate tends to increase. This indicates that, in spite of their nonlinear stability, entropic lattice Boltzmann models may become inaccurate when the ratio of gradient scale length to grid spacing becomes too small. Similar inaccuracies may limit the utility of the entropic lattice Boltzmann paradigm as a subgrid model of Navier-Stokes turbulence.
Women's Path into Science and Engineering Majors: A Structural Equation Model
Camp, Amanda G.; Gilleland, Diane; Pearson, Carolyn; Vander Putten, Jim
2009-01-01
The intent of this study was to investigate the adequacy of Weidman's (1985, 1989) theoretical undergraduate socialization model as an empirical-based causal model pertaining to women's career path choice into a science or engineering (SE) major via structural equation modeling. Data were obtained from the Beginning Postsecondary Students…
Rodríguez, J; Clemente, G; Sanjuán, N; Bon, J
2014-01-01
The drying kinetics of thyme was analyzed by considering different conditions: air temperature of between 40°C and 70°C , and air velocity of 1 m/s. A theoretical diffusion model and eight different empirical models were fitted to the experimental data. From the theoretical model application, the effective diffusivity per unit area of the thyme was estimated (between 3.68 × 10(-5) and 2.12 × 10 (-4) s(-1)). The temperature dependence of the effective diffusivity was described by the Arrhenius relationship with activation energy of 49.42 kJ/mol. Eight different empirical models were fitted to the experimental data. Additionally, the dependence of the parameters of each model on the drying temperature was determined, obtaining equations that allow estimating the evolution of the moisture content at any temperature in the established range. Furthermore, artificial neural networks were developed and compared with the theoretical and empirical models using the percentage of the relative errors and the explained variance. The artificial neural networks were found to be more accurate predictors of moisture evolution with VAR ≥ 99.3% and ER ≤ 8.7%.
Niang, Oumar; Thioune, Abdoulaye; El Gueirea, Mouhamed Cheikh; Deléchelle, Eric; Lemoine, Jacques
2012-09-01
The major problem with the empirical mode decomposition (EMD) algorithm is its lack of a theoretical framework. So, it is difficult to characterize and evaluate this approach. In this paper, we propose, in the 2-D case, the use of an alternative implementation to the algorithmic definition of the so-called "sifting process" used in the original Huang's EMD method. This approach, especially based on partial differential equations (PDEs), was presented by Niang in previous works, in 2005 and 2007, and relies on a nonlinear diffusion-based filtering process to solve the mean envelope estimation problem. In the 1-D case, the efficiency of the PDE-based method, compared to the original EMD algorithmic version, was also illustrated in a recent paper. Recently, several 2-D extensions of the EMD method have been proposed. Despite some effort, 2-D versions for EMD appear poorly performing and are very time consuming. So in this paper, an extension to the 2-D space of the PDE-based approach is extensively described. This approach has been applied in cases of both signal and image decomposition. The obtained results confirm the usefulness of the new PDE-based sifting process for the decomposition of various kinds of data. Some results have been provided in the case of image decomposition. The effectiveness of the approach encourages its use in a number of signal and image applications such as denoising, detrending, or texture analysis.
Empirical equations to predict conditions for solid deposition in small diameter pipelines
Papavinasam, S.; Doiron, A.; Revie, W. [Natural Resources Canada, Ottawa, ON (Canada). CANMET Materials Technology Lab
2007-03-15
Corrosion of steels is a major concern for the integrity of pipelines. Corrosion is caused by the combined influence of oil, water, carbon dioxide, hydrogen sulfide, temperature, pressure, and flow. Since localized corrosion is one of the more frequent problems, this study investigated how sand affects localized corrosion on an operating carbon and low-alloy steel pipeline. The objective was to determine critical flow rates in smaller diameter pipeline in which solid deposition occurs as a function of pipe position, inclination, and flow rate. Experimental results, video analysis and empirical equations revealed that under high-flow conditions, the sand impinges on the pipe, causing erosion-corrosion. Under low-flow conditions, the sand deposits at localized areas of the pipeline resulting in underfilm corrosion and preventing access of the inhibitor to the surface. The creation of small anode-large cathode areas may also contribute to this higher pitting corrosion rate in the presence of sand. It was also shown that the pipe diameter, inclination, expansion, and fluid flow rate determine whether sand will deposit or not. No guidelines currently exist to predict critical flow below which solid deposition occurs. As such, it is important to predict the conditions at which sand deposits. 6 refs., 2 tabs., 2 figs.
Modeling and Prediction Using Stochastic Differential Equations
Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp
2016-01-01
Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... that describes the variation between subjects. The ODE setup implies that the variation for a single subject is described by a single parameter (or vector), namely the variance (covariance) of the residuals. Furthermore the prediction of the states is given as the solution to the ODEs and hence assumed...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs...
Quality Management in Hospital Departments : Empirical Studies of Organisational Models
Kunkel, Stefan
2008-01-01
The general aim of this thesis was to empirically explore the organisational characteristics of quality systems of hospital departments, to develop and empirically test models for the organisation and implementation of quality systems, and to discuss the clinical implications of the findings. Data were collected from hospital departments through interviews (n=19) and a nation-wide survey (n=386). The interviews were analysed thematically and organisational models were developed. Relationships...
Advanced structural equation modeling issues and techniques
Marcoulides, George A
2013-01-01
By focusing primarily on the application of structural equation modeling (SEM) techniques in example cases and situations, this book provides an understanding and working knowledge of advanced SEM techniques with a minimum of mathematical derivations. The book was written for a broad audience crossing many disciplines, assumes an understanding of graduate level multivariate statistics, including an introduction to SEM.
Structural Equation Modeling in Rehabilitation Counseling Research
Chan, Fong; Lee, Gloria K.; Lee, Eun-Jeong; Kubota, Coleen; Allen, Chase A.
2007-01-01
Structural equation modeling (SEM) has become increasingly popular in counseling, psychology, and rehabilitation research. The purpose of this article is to provide an overview of the basic concepts and applications of SEM in rehabilitation counseling research using the AMOS statistical software program.
Residual models for nonlinear partial differential equations
Garry Pantelis
2005-11-01
Full Text Available Residual terms that appear in nonlinear PDEs that are constructed to generate filtered representations of the variables of the fully resolved system are examined by way of a consistency condition. It is shown that certain commonly used empirical gradient models for the residuals fail the test of consistency and therefore cannot be validated as approximations in any reliable sense. An alternate method is presented for computing the residuals. These residual models are independent of free or artificial parameters and there direct link with the functional form of the system of PDEs which describe the fully resolved system are established.
Soil erodibility is a key factor for estimating soil erosion using physically based models. In this study, a new parameterization approach for estimating erodibility was developed for the Rangeland Hydrology and Erosion Model (RHEM). The approach uses empirical equations that were developed by apply...
A Semi-Empirical Excess Pressure Equation for CO{sub 2}-H{sub 2}O fluids at 400 C, 0--400 MPa
Blencoe, J.G.; Anovitz, L.M.; Singh, J.
1999-09-12
Highly accurate and precise density data for CO{sub 2}-H{sub 2}O mixtures at 400 C 10-400 MPa, were used to develop a modified, B-truncated virial equation for excess pressure (P{sup ex}). This function and empirical equations of state for H{sub 2}O and CO{sub 2} accurately represent the experimentally determined densities, and interpolate smoothly between data points. Integrating the P{sub ex} expression with respect to molar volume yields an equation for excess Helmholta free energy, which can be used to calculate other excess properties of interest. The P{sup ex} modeling method has important advantages over more conventional, alternative approaches.
Bayesian Data-Model Fit Assessment for Structural Equation Modeling
Levy, Roy
2011-01-01
Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…
Fabra, M. Eugenia; Camison, Cesar
2009-01-01
Empirical literature has traditionally analyzed the effect of education on job satisfaction with single-equation models that ignore interrelationships between theoretical explanatory variables. Their results are somewhat inconclusive. We propose estimating a structural equation model to obtain both the direct effects and the set of indirect…
Empirical agent-based modelling challenges and solutions
Barreteau, Olivier
2014-01-01
This instructional book showcases techniques to parameterise human agents in empirical agent-based models (ABM). In doing so, it provides a timely overview of key ABM methodologies and the most innovative approaches through a variety of empirical applications. It features cutting-edge research from leading academics and practitioners, and will provide a guide for characterising and parameterising human agents in empirical ABM. In order to facilitate learning, this text shares the valuable experiences of other modellers in particular modelling situations. Very little has been published in the area of empirical ABM, and this contributed volume will appeal to graduate-level students and researchers studying simulation modeling in economics, sociology, ecology, and trans-disciplinary studies, such as topics related to sustainability. In a similar vein to the instruction found in a cookbook, this text provides the empirical modeller with a set of 'recipes' ready to be implemented. Agent-based modeling (AB...
Kamajaya, Ketut; Umar, Efrizon; Sudjatmi, K. S.
2012-06-01
This study focused on natural convection heat transfer using a vertical rectangular sub-channel and water as the coolant fluid. To conduct this study has been made pipe heaters are equipped with thermocouples. Each heater is equipped with five thermocouples along the heating pipes. The diameter of each heater is 2.54 cm and 45 cm in length. The distance between the central heating and the pitch is 29.5 cm. Test equipment is equipped with a primary cooling system, a secondary cooling system and a heat exchanger. The purpose of this study is to obtain new empirical correlations equations of the vertical rectangular sub-channel, especially for the natural convection heat transfer within a bundle of vertical cylinders rectangular arrangement sub-channels. The empirical correlation equation can support the thermo-hydraulic analysis of research nuclear reactors that utilize cylindrical fuel rods, and also can be used in designing of baffle-free vertical shell and tube heat exchangers. The results of this study that the empirical correlation equations of natural convection heat transfer coefficients with rectangular arrangement is Nu = 6.3357 (Ra.Dh/x)0.0740.
Two-equation turbulence modeling for 3-D hypersonic flows
Bardina, J. E.; Coakley, T. J.; Marvin, J. G.
1992-01-01
An investigation to verify, incorporate and develop two-equation turbulence models for three-dimensional high speed flows is presented. The current design effort of hypersonic vehicles has led to an intensive study of turbulence models for compressible hypersonic flows. This research complements an extensive review of experimental data and the current development of 2D turbulence models. The review of experimental data on 2D and 3D flows includes complex hypersonic flows with pressure profiles, skin friction, wall heat transfer, and turbulence statistics data. In a parallel effort, turbulence models for high speed flows have been tested against flat plate boundary layers, and are being tested against the 2D database. In the present paper, we present the results of 3D Navier-Stokes numerical simulations with an improved k-omega two-equation turbulence model against experimental data and empirical correlations of an adiabatic flat plate boundary layer, a cold wall flat plate boundary layer, and a 3D database flow, the interaction of an oblique shock wave and a thick turbulent boundary layer with a free stream Mach number = 8.18 and Reynolds number = 5 x 10 to the 6th.
The geometry of a vorticity model equation
Escher, Joachim; Wunsch, Marcus
2010-01-01
We provide rigorous evidence of the fact that the modified Constantin-Lax-Majda equation modeling vortex and quasi-geostrophic dynamics describes the geodesic flow on the subgroup of orientation-preserving diffeomorphisms fixing one point, with respect to right-invariant metric induced by the homogeneous Sobolev norm $H^{1/2}$ and show the local existence of the geodesics in the extended group of diffeomorphisms of Sobolev class $H^{k}$ with $k\\ge 2$.
Functional Difference Equations and an Epidemic Model.
1980-06-09
ADDRESS 12. REPORT DATE AIR FORCE OFFICE OF SCIENTIFIC RESEARC 913 June 9, 1980 BOLLING AIR FORCE BASE , WASHINGTON, D.tI,3. NUMBEROFAGS 14. MONITORING...allowed spatial effects in an S - I model to arrive at the equation t S(t,x) = S(t,x).J B(;x, )S(t+6,0) dAdO in some region f cR. If X is the ordered
Empirical questions for collective-behaviour modelling
Nicholas T Ouellette
2015-03-01
The collective behaviour of groups of social animals has been an active topic of study across many disciplines, and has a long history of modelling. Classical models have been successful in capturing the large-scale patterns formed by animal aggregations, but fare less well in accounting for details, particularly for groups that do not display net motion. Inspired by recent measurements of swarming insects, which are not well described by the classical modelling paradigm, I pose a set of questions that must be answered by any collective-behaviour model. By explicitly stating the choices made in response to each of these questions, models can be more easily categorized and compared, and their expected range of validity can be clarified.
Empirical likelihood-based evaluations of Value at Risk models
2009-01-01
Value at Risk (VaR) is a basic and very useful tool in measuring market risks. Numerous VaR models have been proposed in literature. Therefore, it is of great interest to evaluate the efficiency of these models, and to select the most appropriate one. In this paper, we shall propose to use the empirical likelihood approach to evaluate these models. Simulation results and real life examples show that the empirical likelihood method is more powerful and more robust than some of the asymptotic method available in literature.
Empirical Bayes Model Comparisons for Differential Methylation Analysis
Mingxiang Teng
2012-01-01
Full Text Available A number of empirical Bayes models (each with different statistical distribution assumptions have now been developed to analyze differential DNA methylation using high-density oligonucleotide tiling arrays. However, it remains unclear which model performs best. For example, for analysis of differentially methylated regions for conservative and functional sequence characteristics (e.g., enrichment of transcription factor-binding sites (TFBSs, the sensitivity of such analyses, using various empirical Bayes models, remains unclear. In this paper, five empirical Bayes models were constructed, based on either a gamma distribution or a log-normal distribution, for the identification of differential methylated loci and their cell division—(1, 3, and 5 and drug-treatment-(cisplatin dependent methylation patterns. While differential methylation patterns generated by log-normal models were enriched with numerous TFBSs, we observed almost no TFBS-enriched sequences using gamma assumption models. Statistical and biological results suggest log-normal, rather than gamma, empirical Bayes model distribution to be a highly accurate and precise method for differential methylation microarray analysis. In addition, we presented one of the log-normal models for differential methylation analysis and tested its reproducibility by simulation study. We believe this research to be the first extensive comparison of statistical modeling for the analysis of differential DNA methylation, an important biological phenomenon that precisely regulates gene transcription.
Semi-Empirical Models for Buoyancy-Driven Ventilation
Terpager Andersen, Karl
2015-01-01
A literature study is presented on the theories and models dealing with buoyancy-driven ventilation in rooms. The models are categorised into four types according to how the physical process is conceived: column model, fan model, neutral plane model and pressure model. These models are analysed...... and compared with a reference model. Discrepancies and differences are shown, and the deviations are discussed. It is concluded that a reliable buoyancy model based solely on the fundamental flow equations is desirable....
An Empirically Grounded Model of the Adoption of Intellectual Technologies.
Wildemuth, Barbara M.
1992-01-01
Data on adoption of 43 user-developed computing applications in 3 large corporations were analyzed to develop an empirically grounded model of the adoption process for intellectual technologies. A five-stage model consisting of Resource Acquisition, Application Development, Adoption/Renewal, Routinization/Enhancement, and External Adoption was…
Learning-Testing Process in Classroom: An Empirical Simulation Model
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'…
Empirical model for mineralisation of manure nitrogen in soil
Sørensen, Peter; Thomsen, Ingrid Kaag; Schröder, Jaap
2017-01-01
A simple empirical model was developed for estimation of net mineralisation of pig and cattle slurry nitrogen (N) in arable soils under cool and moist climate conditions during the initial 5 years after spring application. The model is based on a Danish 3-year field experiment with measurements...
An Empirical-Mathematical Modelling Approach to Upper Secondary Physics
Angell, Carl; Kind, Per Morten; Henriksen, Ellen K.; Guttersrud, Oystein
2008-01-01
In this paper we describe a teaching approach focusing on modelling in physics, emphasizing scientific reasoning based on empirical data and using the notion of multiple representations of physical phenomena as a framework. We describe modelling activities from a project (PHYS 21) and relate some experiences from implementation of the modelling…
Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation
M. Caporin (Massimiliano); M.J. McAleer (Michael)
2011-01-01
textabstractIn the last 15 years, several Multivariate GARCH (MGARCH) models have appeared in the literature. Recent research has begun to examine MGARCH specifications in terms of their out-of-sample forecasting performance. In this paper, we provide an empirical comparison of a set of models, name
Principles and practice of structural equation modeling
Kline, Rex B
2015-01-01
Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complete, and accessible structural equation modeling (SEM) text. Continuing the tradition of using real data examples from a variety of disciplines, the significantly revised fourth edition incorporates recent developments such as Pearl's graphing theory and the structural causal model (SCM), measurement invariance, and more. Readers gain a comprehensive understanding of all phases of SEM, from data collection and screening to the interpretation and reporting of the results. Learning is enhanced by ex
Continuity of the robustness of contextuality of empirical models
Meng, HuiXian; Cao, HuaiXin; Wang, WenHua; Chen, Liang; Fan, Yajing
2016-10-01
Recently, the robustness of contextuality (RoC) of an empirical model was discussed in [Sci. China-Phys. Mech. Astron. 59, 640303 (2016)], many important properties of the RoC have been proved except for its boundedness and continuity. The aim of this paper is to find an upper bound for the RoC over all of empirical models and prove that the RoC is a continuous function on the set of all empirical models. Lastly, a relationship between the RoC and the extent of violating the noncontextual inequalities is established for an n-cycle contextual box. This relationship implies that the RoC can be used to quantify the contextuality of n-cycle boxes.
A non-quasistatic semi-empirical model for small geometry MOSFETs
Murray, Daniel; Sanchez, Julian J.; Demassa, Thomas A.
1997-09-01
A new charge-oriented semi-empirical non-quasistatic (NQS) model is developed for small geometry MOSFETs that is computationally efficient to be useful for circuit simulation. The NQS model includes the effect of velocity saturation, gate field dependent mobility, charge sharing, drain induced barrier lowering and geometric dependencies of threshold voltage. To model the carrier inertia that causes non-steady state conditions, a non-quasistatic model is adopted. An approximate inversion charge profile is used to reduce the nonlinear current-continuity equation to an ordinary differential equation. The model is valid in all regions of operation (weak, moderate and strong inversion) and is derived without resorting to the approximate arbitrary channel charge partitioning. The results from the proposed model are examined and compared with 2D simulation results and good agreement is obtained for the transient source, drain and gate currents for large signals applied to the gate.
An Application of Structural Equation Modeling for Developing Good Teaching Characteristics Ontology
Phiakoksong, Somjin; Niwattanakul, Suphakit; Angskun, Thara
2013-01-01
Ontology is a knowledge representation technique which aims to make knowledge explicit by defining the core concepts and their relationships. The Structural Equation Modeling (SEM) is a statistical technique which aims to explore the core factors from empirical data and estimates the relationship between these factors. This article presents an…
Li, Spencer D.
2011-01-01
Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…
A limit model for thermoelectric equations
Consiglieri, Luisa
2010-01-01
We analyze the asymptotic behavior corresponding to the arbitrary high conductivity of the heat in the thermoelectric devices. This work deals with a steady-state multidimensional thermistor problem, considering the Joule effect and both spatial and temperature dependent transport coefficients under some real boundary conditions in accordance with the Seebeck-Peltier-Thomson cross-effects. Our first purpose is that the existence of a weak solution holds true under minimal assumptions on the data, as in particular convex domains with Lipschitz boundary. The proof is based on a fixed point argument, compactness methods, and existence and regularity theory for elliptic scalar equations. In this process, we prove W^{1,p}-regularity for Neumann problem to an elliptic second order equation in divergence form with discontinuous coefficient by using the potential theory. The second one is to show the existence of a limit model illustrating the asymptotic situation.
Low Order Empirical Galerkin Models for Feedback Flow Control
Tadmor, Gilead; Noack, Bernd
2005-11-01
Model-based feedback control restrictions on model order and complexity stem from several generic considerations: real time computation, the ability to either measure or reliably estimate the state in real time and avoiding sensitivity to noise, uncertainty and numerical ill-conditioning are high on that list. Empirical POD Galerkin models are attractive in the sense that they are simple and (optimally) efficient, but are notoriously fragile, and commonly fail to capture transients and control effects. In this talk we review recent efforts to enhance empirical Galerkin models and make them suitable for feedback design. Enablers include `subgrid' estimation of turbulence and pressure representations, tunable models using modes from multiple operating points, and actuation models. An invariant manifold defines the model's dynamic envelope. It must be respected and can be exploited in observer and control design. These ideas are benchmarked in the cylinder wake system and validated by a systematic DNS investigation of a 3-dimensional Galerkin model of the controlled wake.
Novel Empirical Equations to Calculate the Impedance of a Strip Dipole Antenna
S. Keyrouz
2013-12-01
Full Text Available This paper investigates the input impedance of strip dipoles since they are the basic elements of folded strip dipole antennas. A novel, simple and accurate design algorithm is presented. Compared to state-of-the art design equations, the new proposed equations are more accurate than those found in the literature and take into consideration the antenna feeding width. These equations reduce the calculation time, when compared to commercial electromagnetic simulation software, allowing for fast antenna designs with very high accuracy. Based on the novel equations, a strip dipole antenna is designed, simulated, manufactured and measured. The simulation results are validated by measurements.
Lattice Boltzmann model for nonlinear convection-diffusion equations.
Shi, Baochang; Guo, Zhaoli
2009-01-01
A lattice Boltzmann model for convection-diffusion equation with nonlinear convection and isotropic-diffusion terms is proposed through selecting equilibrium distribution function properly. The model can be applied to the common real and complex-valued nonlinear evolutionary equations, such as the nonlinear Schrödinger equation, complex Ginzburg-Landau equation, Burgers-Fisher equation, nonlinear heat conduction equation, and sine-Gordon equation, by using a real and complex-valued distribution function and relaxation time. Detailed simulations of these equations are performed, and it is found that the numerical results agree well with the analytical solutions and the numerical solutions reported in previous studies.
Wave equation modelling using Julia programming language
Kim, Ahreum; Ryu, Donghyun; Ha, Wansoo
2016-04-01
Julia is a young high-performance dynamic programming language for scientific computations. It provides an extensive mathematical function library, a clean syntax and its own parallel execution model. We developed 2d wave equation modeling programs using Julia and C programming languages and compared their performance. We used the same modeling algorithm for the two modeling programs. We used Julia version 0.3.9 in this comparison. We declared data type of function arguments and used inbounds macro in the Julia program. Numerical results showed that the C programs compiled with Intel and GNU compilers were faster than Julia program, about 18% and 7%, respectively. Taking the simplicity of dynamic programming language into consideration, Julia can be a novel alternative of existing statically typed programming languages.
POD/DEIM Nonlinear model order reduction of an ADI implicit shallow water equations model
Stefanescu, Razvan
2012-01-01
In the present paper we consider a 2-D shallow-water equations (SWE) model on a $\\beta$-plane solved using an alternating direction fully implicit (ADI) finite-difference scheme on a rectangular domain. The scheme was shown to be unconditionally stable for the linearized equations. The discretization yields a number of nonlinear systems of algebraic equations. We then use a proper orthogonal decomposition (POD) to reduce the dimension of the SWE model. Due to the model nonlinearities, the computational complexity of the reduced model still depends on the number of variables of the full shallow - water equations model. By employing the discrete empirical interpolation method (DEIM) we reduce the computational complexity of the reduced order model due to its depending on the nonlinear full dimension model and regain the full model reduction expected from the POD model. To emphasize the CPU gain in performance due to use of POD/DEIM, we also propose testing an explicit Euler finite difference scheme (EE) as an a...
Comparison of modelled and empirical atmospheric propagation data
Schott, J. R.; Biegel, J. D.
1983-01-01
The radiometric integrity of TM thermal infrared channel data was evaluated and monitored to develop improved radiometric preprocessing calibration techniques for removal of atmospheric effects. Modelled atmospheric transmittance and path radiance were compared with empirical values derived from aircraft underflight data. Aircraft thermal infrared imagery and calibration data were available on two dates as were corresponding atmospheric radiosonde data. The radiosonde data were used as input to the LOWTRAN 5A code which was modified to output atmospheric path radiance in addition to transmittance. The aircraft data were calibrated and used to generate analogous measurements. These data indicate that there is a tendancy for the LOWTRAN model to underestimate atmospheric path radiance and transmittance as compared to empirical data. A plot of transmittance versus altitude for both LOWTRAN and empirical data is presented.
Empirical Modeling of Metal Oxides Dissolution
Kim, Seon-Byeong; Won, Hui-Jun; Park, Sang-Yoon; Moon, Jei-Kwon; Choi, Wang-Kyu [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2015-05-15
There have been tons of studies to examine the dissolution of metal oxides in terms of dissolution kinetics, type of reactants, geometry, etc. However, most of previous studies is the observation of macroscopic dissolution characteristics and might not provide the atomic scale characteristics of dissolution reactions. Even the analysis of microscopic structure of metal oxide with SEM, XRD, etc. during the dissolution does not observe the microscopic characteristics of dissolution mechanism. Computational analysis with well-established dissolution model is the one of the best approaches to understand indirectly the microscopic dissolution behaviour. Various designs of experimental conditions are applied to the in-vitro methods interpreting the dissolution characteristics controlled by each influencing parameter.
周游
2014-01-01
By constructing simultaneous equations and taking advantage of vector auto regression models,this paper makes empirical research on the interrelation among Chinese foreign direct investment,intellectual property protection and export industrial structure from 1990 to 2011. The result shows that:structural optimization of export industry is not conducive to at-tract foreign direct investment,but foreign direct investment is conducive to structural optimization of export industry;It is beneficial to the structural optimization of Chinese export industry and inflow of foreign direct investment by strengthening of intellectual property protection,simultaneously,the structural optimization of Chinese export industry and inflow of foreign direct investment promote the improvement of the level of protection of intellectual property rights.%通过构建联立方程，并利用VAR模型，对我国1990~2011年外商直接投资、知识产权保护和出口产业结构之间相互关系进行实证研究，结果表明：出口产业结构优化不利于我国吸引外商直接投资，但外商直接投资有利于我国出口产业结构优化；加强知识产权保护有利于我国出口产业结构优化和外商直接投资流入，同时出口产业结构优化和外商直接投资流入也促进了我国知识产权保护水平的提高。
Partial differential equation models in macroeconomics.
Achdou, Yves; Buera, Francisco J; Lasry, Jean-Michel; Lions, Pierre-Louis; Moll, Benjamin
2014-11-13
The purpose of this article is to get mathematicians interested in studying a number of partial differential equations (PDEs) that naturally arise in macroeconomics. These PDEs come from models designed to study some of the most important questions in economics. At the same time, they are highly interesting for mathematicians because their structure is often quite difficult. We present a number of examples of such PDEs, discuss what is known about their properties, and list some open questions for future research. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Structural equation modeling for observational studies
Grace, J.B.
2008-01-01
Structural equation modeling (SEM) represents a framework for developing and evaluating complex hypotheses about systems. This method of data analysis differs from conventional univariate and multivariate approaches familiar to most biologists in several ways. First, SEMs are multiequational and capable of representing a wide array of complex hypotheses about how system components interrelate. Second, models are typically developed based on theoretical knowledge and designed to represent competing hypotheses about the processes responsible for data structure. Third, SEM is conceptually based on the analysis of covariance relations. Most commonly, solutions are obtained using maximum-likelihood solution procedures, although a variety of solution procedures are used, including Bayesian estimation. Numerous extensions give SEM a very high degree of flexibility in dealing with nonnormal data, categorical responses, latent variables, hierarchical structure, multigroup comparisons, nonlinearities, and other complicating factors. Structural equation modeling allows researchers to address a variety of questions about systems, such as how different processes work in concert, how the influences of perturbations cascade through systems, and about the relative importance of different influences. I present 2 example applications of SEM, one involving interactions among lynx (Lynx pardinus), mongooses (Herpestes ichneumon), and rabbits (Oryctolagus cuniculus), and the second involving anuran species richness. Many wildlife ecologists may find SEM useful for understanding how populations function within their environments. Along with the capability of the methodology comes a need for care in the proper application of SEM.
Meta-analytic structural equation modelling
Jak, Suzanne
2015-01-01
This book explains how to employ MASEM, the combination of meta-analysis (MA) and structural equation modelling (SEM). It shows how by using MASEM, a single model can be tested to explain the relationships between a set of variables in several studies. This book gives an introduction to MASEM, with a focus on the state of the art approach: the two stage approach of Cheung and Cheung & Chan. Both, the fixed and the random approach to MASEM are illustrated with two applications to real data. All steps that have to be taken to perform the analyses are discussed extensively. All data and syntax files are available online, so that readers can imitate all analyses. By using SEM for meta-analysis, this book shows how to benefit from all available information from all available studies, even if few or none of the studies report about all relationships that feature in the full model of interest.
On the Use of Structural Equation Models in Marketing Modeling
Steenkamp, J.E.B.M.; Baumgartner, H.
2000-01-01
We reflect on the role of structural equation modeling (SEM) in marketing modeling and managerial decision making. We discuss some benefits provided by SEM and alert marketing modelers to several recent developments in SEM in three areas: measurement analysis, analysis of cross-sectional data, and a
Bankruptcy risk model and empirical tests.
Podobnik, Boris; Horvatic, Davor; Petersen, Alexander M; Urosevic, Branko; Stanley, H Eugene
2010-10-26
We analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor--the debt-to-asset ratio R--in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market crashes, implying that firms go bankrupt with larger values of R. Based on the Zipf analysis, we employ Bayes's theorem and relate the conditional probability that a bankrupt firm has a ratio R with the conditional probability of bankruptcy for a firm with a given R value. For 2,737 bankrupt firms, we demonstrate size dependence in assets change during the bankruptcy proceedings. Prepetition firm assets and petition firm assets follow Zipf distributions but with different exponents, meaning that firms with smaller assets adjust their assets more than firms with larger assets during the bankruptcy process. We compare bankrupt firms with nonbankrupt firms by analyzing the assets and liabilities of two large subsets of the US economy: 2,545 Nasdaq members and 1,680 New York Stock Exchange (NYSE) members. We find that both assets and liabilities follow a Pareto distribution. The finding is not a trivial consequence of the Zipf scaling relationship of firm size quantified by employees--although the market capitalization of Nasdaq stocks follows a Pareto distribution, the same distribution does not describe NYSE stocks. We propose a coupled Simon model that simultaneously evolves both assets and debt with the possibility of bankruptcy, and we also consider the possibility of firm mergers.
A Development of Empirical Models for Equipment Condition Monitoring System
Lee, Song Kyu; Baik, Se Jin [KEPCO Engineering and Construction Company, Daejeon (Korea, Republic of); An, Sang Ha [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of)
2010-10-15
A great deal of effort is recently put into on-line monitoring (OLM), specially using empirical model to detect earlier the fault of components or the calibration reduction/extension of instrument. The empirical model is constructed with historical data obtained during operation and it mainly relies on regression techniques. Various models are used in OLM and the role of models is to describe the relation among signals that have been collected. Ultimate goal of empirical models is to best estimate parameter as soon as possible close to actual value. Typically some of the historical data are used for model training, and some data are used for verification and assessment of model performance. Several different models for OLM of nuclear power systems are currently being used. Examples include the ANL Multivariate State Estimation Techniques (MSET) used in EPI center of SmartSignal, the expert state estimation engine (ESEE) used in SureSense software of Expert Microsystems, Process Evaluation and Analysis by Neural Operators (PEANO) OECD of Halden Reactor Project and linear regression model used in RCP seal integrity monitoring system (SIMON) of KEPCO E and C
Owen, Art B
2001-01-01
Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It also facilitates incorporating side information, and it simplifies accounting for censored, truncated, or biased sampling.One of the first books published on the subject, Empirical Likelihood offers an in-depth treatment of this method for constructing confidence regions and testing hypotheses. The author applies empirical likelihood to a range of problems, from those as simple as setting a confidence region for a univariate mean under IID sampling, to problems defined through smooth functions of means, regression models, generalized linear models, estimating equations, or kernel smooths, and to sampling with non-identically distributed data. Abundant figures offer vi...
A first course in differential equations, modeling, and simulation
Smith, Carlos A
2011-01-01
IntroductionAn Introductory ExampleModelingDifferential EquationsForcing FunctionsBook ObjectivesObjects in a Gravitational FieldAn Example Antidifferentiation: Technique for Solving First-Order Ordinary Differential EquationsBack to Section 2-1Another ExampleSeparation of Variables: Technique for Solving First-Order Ordinary Differential Equations Back to Section 2-5Equations, Unknowns, and Degrees of FreedomClassical Solutions of Ordinary Linear Differential EquationsExamples of Differential EquationsDefinition of a Linear Differential EquationIntegrating Factor MethodCharacteristic Equation
Empirically derived neighbourhood rules for urban land-use modelling
Hansen, Henning Sten
2012-01-01
interaction between neighbouring land uses is an important component in urban cellular automata. Nevertheless, this component is often calibrated through trial-and-error estimation. The aim of this project has been to develop an empirically derived landscape metric supporting cellular-automata-based land......-use modelling. Through access to very detailed urban land-use data it has been possible to derive neighbourhood rules empirically, and test their sensitivity to the land-use classification applied, the regional variability of the rules, and their time variance. The developed methodology can be implemented...
An empirical investigation of two competing models of patient satisfaction.
Mishra, D P; Singh, J; Wood, V
1991-01-01
This paper empirically examines two competing models of patient satisfaction. Specifically, a five factor SERVQUAL model proposed by Parasuraman et al. (1988) and a tripartite model posited by Smith, Bloom, and Davis (1986) are examined. The two models are tested via factor analysis based on data collected from a field survey of hospital patients. The results of this study indicate that the five dimensional SERVQUAL model is not supported by data. On the other hand, there is general support for the tripartite model. Implications of our results for health care practitioners and researchers are discussed. Future directions for research are also outlined.
Teaching Modeling with Partial Differential Equations: Several Successful Approaches
Myers, Joseph; Trubatch, David; Winkel, Brian
2008-01-01
We discuss the introduction and teaching of partial differential equations (heat and wave equations) via modeling physical phenomena, using a new approach that encompasses constructing difference equations and implementing these in a spreadsheet, numerically solving the partial differential equations using the numerical differential equation…
Teaching Modeling with Partial Differential Equations: Several Successful Approaches
Myers, Joseph; Trubatch, David; Winkel, Brian
2008-01-01
We discuss the introduction and teaching of partial differential equations (heat and wave equations) via modeling physical phenomena, using a new approach that encompasses constructing difference equations and implementing these in a spreadsheet, numerically solving the partial differential equations using the numerical differential equation…
Applying Meta-Analysis to Structural Equation Modeling
Hedges, Larry V.
2016-01-01
Structural equation models play an important role in the social sciences. Consequently, there is an increasing use of meta-analytic methods to combine evidence from studies that estimate the parameters of structural equation models. Two approaches are used to combine evidence from structural equation models: A direct approach that combines…
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Fuzzy Modeling for Uncertainty Nonlinear Systems with Fuzzy Equations
Raheleh Jafari
2017-01-01
Full Text Available The uncertain nonlinear systems can be modeled with fuzzy equations by incorporating the fuzzy set theory. In this paper, the fuzzy equations are applied as the models for the uncertain nonlinear systems. The nonlinear modeling process is to find the coefficients of the fuzzy equations. We use the neural networks to approximate the coefficients of the fuzzy equations. The approximation theory for crisp models is extended into the fuzzy equation model. The upper bounds of the modeling errors are estimated. Numerical experiments along with comparisons demonstrate the excellent behavior of the proposed method.
An empirical model for friction in cold forging
Bay, Niels; Eriksen, Morten; Tan, Xincai
2002-01-01
With a system of simulative tribology tests for cold forging the friction stress for aluminum, steel and stainless steel provided with typical lubricants for cold forging has been determined for varying normal pressure, surface expansion, sliding length and tool/work piece interface temperature...... of normal pressure and tool/work piece interface temperature. The model is verified by process testing measuring friction at varying reductions in cold forward rod extrusion. KEY WORDS: empirical friction model, cold forging, simulative friction tests....
A Trade Study of Thermosphere Empirical Neutral Density Models
2014-08-01
into the ram direction, and m is the satellite mass. The velocity ?⃗? equals to the satellite velocity in the corotating Earth frame ?⃗?...drag force. In a trade study we have investigated a methodology to assess performances of neutral density models in predicting orbit against a... assess overall errors in orbit prediction expected from empirical density models. They have also been adapted in an analysis tool Satellite Orbital
Empirical modelling for the conceptual design and use of products
Roe, Chris P.; Beynon, Meurig; Fischer, Carlos N
2001-01-01
The process of designing an engineering product usually involves only superficial interaction on the part of the user during the design. This often leads to the product being unsuitable for its target comnmnity. In this paper, we describe an approach called Empirical Modelling that emphasises interaction and experiment throughout the construction of a model that we believe has benefits in respect of usability. We use a case study in digital watch design to illustrate our approach and our ideas.
Models of social entrepreneurship: empirical evidence from Mexico
Wulleman, Marine; Hudon, Marek
2015-01-01
This paper seeks to improve the understanding of social entrepreneurship models based on empirical evidence from Mexico, where social entrepreneurship is currently booming. It aims to supplement existing typologies of social entrepreneurship models. To that end, building on Zahra et al. (2009) typology it begins by providing a new framework classifying the three types of social entrepreneurship. A comparative case study of ten Mexican social enterprises is then elaborated using that framework...
Voter Model Perturbations and Reaction Diffusion Equations
Cox, J Theodore; Perkins, Edwin
2011-01-01
We consider particle systems that are perturbations of the voter model and show that when space and time are rescaled the system converges to a solution of a reaction diffusion equation in dimensions $d \\ge 3$. Combining this result with properties of the PDE, some methods arising from a low density super-Brownian limit theorem, and a block construction, we give general, and often asymptotically sharp, conditions for the existence of non-trivial stationary distributions, and for extinction of one type. As applications, we describe the phase diagrams of three systems when the parameters are close to the voter model: (i) a stochastic spatial Lotka-Volterra model of Neuhauser and Pacala, (ii) a model of the evolution of cooperation of Ohtsuki, Hauert, Lieberman, and Nowak, and (iii) a continuous time version of the non-linear voter model of Molofsky, Durrett, Dushoff, Griffeath, and Levin. The first application confirms a conjecture of Cox and Perkins and the second confirms a conjecture of Ohtsuki et al in the ...
The General Linear Model as Structural Equation Modeling
Graham, James M.
2008-01-01
Statistical procedures based on the general linear model (GLM) share much in common with one another, both conceptually and practically. The use of structural equation modeling path diagrams as tools for teaching the GLM as a body of connected statistical procedures is presented. A heuristic data set is used to demonstrate a variety of univariate…
Equation-free modeling unravels the behavior of complex ecological systems
DeAngelis, Donald L.; Yurek, Simeon
2015-01-01
Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka–Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing “clarity and precision into conjecture” (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.
An empirical comparison of estimation procedures for the von Bertalanffy growth equation
Vaughan, D.S.; Kanciruk, P.
1982-01-01
One non-linear and two linear methods of fitting the von Bertalanffy growth equation to length-age data were compared using Monte Carlo simulations of fish populations while varying the standard error of the length, total sample size, sampling time interval, von Bertalanffy growth parameter, and annual adult survival. The iterative, non-linear method usually produced the most accurate and precise parameter estimates. The non-linear method also provided asymptotic confidence intervals about point estimates, placed fewest constraints on data collection, and was the easiest to use. It is suggested that traditional linear solutions to the von Bertalanffy growth equation be abandoned.
Selection Bias in Educational Transition Models: Theory and Empirical Evidence
Holm, Anders; Jæger, Mads
Most studies using Mare’s (1980, 1981) seminal model of educational transitions find that the effect of family background decreases across transitions. Recently, Cameron and Heckman (1998, 2001) have argued that the “waning coefficients” in the Mare model are driven by selection on unobserved...... the United States, United Kingdom, Denmark, and the Netherlands shows that when we take selection into account the effect of family background variables on educational transitions is largely constant across transitions. We also discuss several difficulties in estimating educational transition models which...... variables. This paper, first, explains theoretically how selection on unobserved variables leads to waning coefficients and, second, illustrates empirically how selection leads to biased estimates of the effect of family background on educational transitions. Our empirical analysis using data from...
Structural equation models from paths to networks
Westland, J Christopher
2015-01-01
This compact reference surveys the full range of available structural equation modeling (SEM) methodologies. It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable. This is the first book to present SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method. This book also surveys the emerging path and network approaches that complement and enhance SEM, and that will grow in importance in the near future. SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists. Latent variable theory and application are comprehensively explained, and methods are presented for extending their power, including guidelines for data preparation, sample size calculation, and the special treatment of Likert scale data. Tables of software, methodologies and fit st...
A note on solutions of an equation modelling arterial deformation
Gordoa, P.R. [Area de Matematica Aplicada, ESCET, Universidad Rey Juan Carlos, C/ Tulipan s/n, 28933 Mostoles, Madrid (Spain)]. E-mail: pilar.gordoa@urjc.es
2007-08-15
The derivation of exact solutions for a partial differential equation modelling arterial deformation in large arteries is considered. Amongst other results, we show that, for any values of the parameters appearing in the equation, solutions in terms of the first Painleve transcendent can be obtained. This is in spite of the non-integrability of the equation. We also establish a connection, via an approximation of the equation under study by the Korteweg-de Vries equation, with the second Painleve equation. Our results thus serve to further demonstrate the wide applicability and importance of the Painleve equations.
Equation of State of Nuclear Matter in Chiral σ-ω Model
CHEN Wei; DONG Dong-Qiao; WEN De-Hua; LIU Guo-Tao; LIU Liang-Gang
2004-01-01
The equation of state of nuclear matter is studied in the 1-loop approximation of chiral linear σ-ω model.By introducing the density-dependent coupling constants, the problem of tachyon pole in the chiral σ-ω model is resolved.The 1-loop contributions ofσ and π mesons to the nucleon's binding energy are included, while the empirical properties of nuclear matter such as saturation density, binding energy, and incompressibility are well reproduced.
Evaluation of theoretical and empirical water vapor sorption isotherm models for soils
Arthur, Emmanuel; Tuller, Markus; Møldrup, Per;
2016-01-01
sorption isotherms of building materials, food, and other industrial products, knowledge about the 24 applicability of these functions for soils is noticeably lacking. We present validation of nine models for characterizing adsorption/desorption isotherms for a water activity range from 0.03 to 0.......93 for 207 soils, widely varying in texture and organic carbon content. 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 the adsorption and desorption data. Regression analysis relating model parameters...
Cristina ENACHE
2011-11-01
Full Text Available The paper propose an analysis based on an empirical model of IT impact on firms performances of Romania. There are presented the model, the equations of the model and the results of statistical processing. All these shown that the ICT impact on firm performance is greater and positive if the information technologies are accompanied by a proactive management policy and an organizational culture.
Bayesian model reduction and empirical Bayes for group (DCM) studies.
Friston, Karl J; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E; van Wijk, Bernadette C M; Ziegler, Gabriel; Zeidman, Peter
2016-03-01
This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level - e.g., dynamic causal models - and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction.
Physical Limitations of Empirical Field Models: Force Balance and Plasma Pressure
Sorin Zaharia; C.Z. Cheng
2002-06-18
In this paper, we study whether the magnetic field of the T96 empirical model can be in force balance with an isotropic plasma pressure distribution. Using the field of T96, we obtain values for the pressure P by solving a Poisson-type equation {del}{sup 2}P = {del} {center_dot} (J x B) in the equatorial plane, and 1-D profiles on the Sun-Earth axis by integrating {del}P = J x B. We work in a flux coordinate system in which the magnetic field is expressed in terms of Euler potentials. Our results lead to the conclusion that the T96 model field cannot be in equilibrium with an isotropic pressure. We also analyze in detail the computation of Birkeland currents using the Vasyliunas relation and the T96 field, which yields unphysical results, again indicating the lack of force balance in the empirical model. The underlying reason for the force imbalance is likely the fact that the derivatives of the least-square fitted model B are not accurate predictions of the actual magnetospheric field derivatives. Finally, we discuss a possible solution to the problem of lack of force balance in empirical field models.
Conceptual Model of IT Infrastructure Capability and Its Empirical Justification
QI Xianfeng; LAN Boxiong; GUO Zhenwei
2008-01-01
Increasing importance has been attached to the value of information technology (IT) infrastructure in today's organizations. The development of efficacious IT infrastructure capability enhances business performance and brings sustainable competitive advantage. This study analyzed the IT infrastructure capability in a holistic way and then presented a concept model of IT capability. IT infrastructure capability was categorized into sharing capability, service capability, and flexibility. This study then empirically tested the model using a set of survey data collected from 145 firms. Three factors emerge from the factor analysis as IT flexibility, IT service capability, and IT sharing capability, which agree with those in the conceptual model built in this study.
Transdiagnostic models of anxiety disorder: Theoretical and empirical underpinnings.
Norton, Peter J; Paulus, Daniel J
2017-08-01
Despite the increasing development, evaluation, and adoption of transdiagnostic cognitive behavioral therapies, relatively little has been written to detail the conceptual and empirical psychopathology framework underlying transdiagnostic models of anxiety and related disorders. In this review, the diagnostic, genetic, neurobiological, developmental, behavioral, cognitive, and interventional data underlying the model are described, with an emphasis on highlighting elements that both support and contradict transdiagnostic conceptualizations. Finally, a transdiagnostic model of anxiety disorder is presented and key areas of future evaluation and refinement are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Empirical intrinsic geometry for nonlinear modeling and time series filtering.
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.
Testing the gravity p-median model empirically
Kenneth Carling
2015-12-01
Full Text Available Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced gravity p-median model offers an extension to the p-median model that account for this. The model is therefore potentially interesting, although it has not yet been implemented and tested empirically. In this paper, we have implemented the model in an empirical problem of locating vehicle inspections, locksmiths, and retail stores of vehicle spare-parts for the purpose of investigating its superiority to the p-median model. We found, however, the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.
An empirical model to estimate ultraviolet erythemal transmissivity
Antón, M.; Serrano, A.; Cancillo, M. L.; García, J. A.
2009-04-01
An empirical model to estimate the solar ultraviolet erythemal irradiance (UVER) for all-weather conditions is presented. This model proposes a power expression with the UV transmissivity as a dependent variable, and the slant ozone column and the clearness index as independent variables. The UVER were measured at three stations in South-Western Spain during a five year period (2001-2005). A dataset corresponding to the period 2001-2004 was used to develop the model and an independent dataset (year 2005) for validation purposes. For all three locations, the empirical model explains more than 95% of UV transmissivity variability due to changes in the two independent variables. In addition, the coefficients of the models show that when the slant ozone amount decreases 1%, UV transmissivity and, therefore, UVER values increase approximately 1.33%-1.35%. The coefficients also show that when the clearness index decreases 1%, UV transmissivity increase 0.75%-0.78%. The validation of the model provided satisfactory results, with low mean absolute bias error (MABE), about 7%-8% for all stations. Finally, a one-day ahead forecast of the UV Index for cloud-free cases is presented, assuming the persistence in the total ozone column. The percentage of days with differences between forecast and experimental UVI lower than ±0.5 unit and ±1 unit is within the range of 28% to 37%, and 60% to 75%, respectively. Therefore, the empirical model proposed in this work provides reliable forecast cloud-free UVI in order to inform the public about the possible harmful effects of UV radiation over-exposure.
An empirical model to estimate ultraviolet erythemal transmissivity
Anton, M.; Serrano, A.; Cancillo, M.L.; Garcia, J.A. [Universidad de Extremadura, Badajoz (Spain). Dept. de Fisica
2009-07-01
An empirical model to estimate the solar ultraviolet erythemal irradiance (UVER) for all-weather conditions is presented. This model proposes a power expression with the UV transmissivity as a dependent variable, and the slant ozone column and the clearness index as independent variables. The UVER were measured at three stations in South-Western Spain during a five year period (2001-2005). A dataset corresponding to the period 2001-2004 was used to develop the model and an independent dataset (year 2005) for validation purposes. For all three locations, the empirical model explains more than 95% of UV transmissivity variability due to changes in the two independent variables. In addition, the coefficients of the models show that when the slant ozone amount decreases 1%, UV transmissivity and, therefore, UVER values increase approximately 1.33%-1.35%. The coefficients also show that when the clearness index decreases 1%, UV transmissivity increase 0.75%-0.78%. The validation of the model provided satisfactory results, with low mean absolute bias error (MABE), about 7%-8% for all stations. Finally, a one-day ahead forecast of the UV Index for cloud-free cases is presented, assuming the persistence in the total ozone column. The percentage of days with differences between forecast and experimental UVI lower than {+-}0.5 unit and {+-}1 unit is within the range of 28% to 37%, and 60% to 75%, respectively. Therefore, the empirical model proposed in this work provides reliable forecast cloud-free UVI in order to inform the public about the possible harmful effects of UV radiation over-exposure. (orig.)
Fitting ARMA Time Series by Structural Equation Models.
van Buuren, Stef
1997-01-01
This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)
Prithvi Simha
2016-03-01
Full Text Available To highlight the shortcomings in conventional methods of extraction, this study investigates the efficacy of Microwave Assisted Extraction (MAE toward bioactive compound recovery from pharmaceutically-significant medicinal plants, Adathoda vasica and Cymbopogon citratus. Initially, the microwave (MW drying behavior of the plant leaves was investigated at different sample loadings, MW power and drying time. Kinetics was analyzed through empirical modeling of drying data against 10 conventional thin-layer drying equations that were further improvised through the incorporation of Arrhenius, exponential and linear-type expressions. 81 semi-empirical Midilli equations were derived and subjected to non-linear regression to arrive at the characteristic drying equations. Bioactive compounds recovery from the leaves was examined under various parameters through a comparative approach that studied MAE against Soxhlet extraction. MAE of A. vasica reported similar yields although drastic reduction in extraction time (210 s as against the average time of 10 h in the Soxhlet apparatus. Extract yield for MAE of C. citratus was higher than the conventional process with optimal parameters determined to be 20 g sample load, 1:20 sample/solvent ratio, extraction time of 150 s and 300 W output power. Scanning Electron Microscopy and Fourier Transform Infrared Spectroscopy were performed to depict changes in internal leaf morphology.
Probabilistic delay differential equation modeling of event-related potentials.
Ostwald, Dirk; Starke, Ludger
2016-08-01
"Dynamic causal models" (DCMs) are a promising approach in the analysis of functional neuroimaging data due to their biophysical interpretability and their consolidation of functional-segregative and functional-integrative propositions. In this theoretical note we are concerned with the DCM framework for electroencephalographically recorded event-related potentials (ERP-DCM). Intuitively, ERP-DCM combines deterministic dynamical neural mass models with dipole-based EEG forward models to describe the event-related scalp potential time-series over the entire electrode space. Since its inception, ERP-DCM has been successfully employed to capture the neural underpinnings of a wide range of neurocognitive phenomena. However, in spite of its empirical popularity, the technical literature on ERP-DCM remains somewhat patchy. A number of previous communications have detailed certain aspects of the approach, but no unified and coherent documentation exists. With this technical note, we aim to close this gap and to increase the technical accessibility of ERP-DCM. Specifically, this note makes the following novel contributions: firstly, we provide a unified and coherent review of the mathematical machinery of the latent and forward models constituting ERP-DCM by formulating the approach as a probabilistic latent delay differential equation model. Secondly, we emphasize the probabilistic nature of the model and its variational Bayesian inversion scheme by explicitly deriving the variational free energy function in terms of both the likelihood expectation and variance parameters. Thirdly, we detail and validate the estimation of the model with a special focus on the explicit form of the variational free energy function and introduce a conventional nonlinear optimization scheme for its maximization. Finally, we identify and discuss a number of computational issues which may be addressed in the future development of the approach.
Developing an Empirical Model for Jet-Surface Interaction Noise
Brown, Clifford A.
2014-01-01
The process of developing an empirical model for jet-surface interaction noise is described and the resulting model evaluated. Jet-surface interaction noise is generated when the high-speed engine exhaust from modern tightly integrated or conventional high-bypass ratio engine aircraft strikes or flows over the airframe surfaces. An empirical model based on an existing experimental database is developed for use in preliminary design system level studies where computation speed and range of configurations is valued over absolute accuracy to select the most promising (or eliminate the worst) possible designs. The model developed assumes that the jet-surface interaction noise spectra can be separated from the jet mixing noise and described as a parabolic function with three coefficients: peak amplitude, spectral width, and peak frequency. These coefficients are fit to functions of surface length and distance from the jet lipline to form a characteristic spectra which is then adjusted for changes in jet velocity and/or observer angle using scaling laws from published theoretical and experimental work. The resulting model is then evaluated for its ability to reproduce the characteristic spectra and then for reproducing spectra measured at other jet velocities and observer angles; successes and limitations are discussed considering the complexity of the jet-surface interaction noise versus the desire for a model that is simple to implement and quick to execute.
Empirical Study and Model of User Acceptance for Personalized Recommendation
Zheng Hua
2013-02-01
Full Text Available Personalized recommendation technology plays an important role in the current e-commerce system, but the user willingness to accept the personalized recommendation and its influencing factors need to be study. In this study, the Theory of Reasoned Action (TRA and Technology Acceptance Model (TAM are used to construct a user acceptance model of personalized recommendation which tested by the empirical method. The results show that perceived usefulness, perceived ease of use, subjective rules and trust tend had an impact on personalized recommendation.
Virtuous organization: A structural equation modeling approach
Majid Zamahani
2013-02-01
Full Text Available For years, the idea of virtue was unfavorable among researchers and virtues were traditionally considered as culture-specific, relativistic and they were supposed to be associated with social conservatism, religious or moral dogmatism, and scientific irrelevance. Virtue and virtuousness have been recently considered seriously among organizational researchers. The proposed study of this paper examines the relationships between leadership, organizational culture, human resource, structure and processes, care for community and virtuous organization. Structural equation modeling is employed to investigate the effects of each variable on other components. The data used in this study consists of questionnaire responses from employees in Payam e Noor University in Yazd province. A total of 250 questionnaires were sent out and a total of 211 valid responses were received. Our results have revealed that all the five variables have positive and significant impacts on virtuous organization. Among the five variables, organizational culture has the most direct impact (0.80 and human resource has the most total impact (0.844 on virtuous organization.
An empirical test of a self-care model of women's responses to battering.
Campbell, J C; Weber, N
2000-01-01
A model of women's responses to battering was constructed based on Orem's theory of self-care deficit and on empirical and clinical observations. The model proposed that the age, educational level, and cultural influences as basic conditioning factors would all be directly related to relational conflict, which would be negatively related to self-care agency (as a mediator) and indirectly related to both outcomes of health and well-being. Using simultaneous structural equation modeling with specification searching, a modified model was derived that eliminated the mediation path but supported direct effects of both abuse and self-care agency on health. The derived model was found to be only a borderline fit with the data, probably due to measurement problems, lack of inclusion of important variables, and small sample size (N = 117). However, there was support for several of the relationships deduced from and/or congruent with Orem's theory.
Modeling Healthcare Processes Using Commitments: An Empirical Evaluation
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
Empirical modeling of the location of the Earth's magnetopause
Machková, Anna; Nemec, Frantisek; Nemecek, Zdenek; Safrankova, Jana
2016-04-01
We systematically examine the location of the magnetopause using a database of 16800 magnetopause crossings registered by 8 different satellites. The analysis is limited to the best sampled region near the subsolar point. We analyze the influence of the Dst and corrected Dst* indices, solar wind flow speed, and the eccentricity of the terrestrial magnetic dipole, i.e., the parameters typically unconsidered in former empirical models. The effects on the magnetopause location are investigated by comparing the observed and model magnetopause distances. We show that the magnetopause distance increases with decreasing Dst index, which can be likely linked to the increasing magnetic field magnitude at the magnetopause due to the enhanced ring current. The magnetopause distance is further higher at the times of higher solar wind flow speeds, in particular during high solar wind dynamic pressures. The eccentricity of the magnetic dipole also results in a statistically observable magnetopause displacement, as the magnetic field magnitude increases at the locations toward which the eccentric dipole is shifted (by about 2.5 percent). Finally, we employ the IGRF internal magnetic field model (accounting thus for the eccentricity of the terrestrial magnetic dipole) and the T96 external magnetic field model (accounting thus for the ring current and the Chapman-Ferraro current). We suggest a simple improvement of existing empirical magnetopause models based on the observed dependencies.
The Kadomtsev{endash}Petviashvili equation as a source of integrable model equations
Maccari, A. [Technical Institute ``G. Cardano,`` Piazza della Resistenza 1, 00015 Monterotondo Rome (Italy)
1996-12-01
A new integrable and nonlinear partial differential equation (PDE) in 2+1 dimensions is obtained, by an asymptotically exact reduction method based on Fourier expansion and spatiotemporal rescaling, from the Kadomtsev{endash}Petviashvili equation. The integrability property is explicitly demonstrated, by exhibiting the corresponding Lax pair, that is obtained by applying the reduction technique to the Lax pair of the Kadomtsev{endash}Petviashvili equation. This model equation is likely to be of applicative relevance, because it may be considered a consistent approximation of a large class of nonlinear evolution PDEs. {copyright} {ital 1996 American Institute of Physics.}
Introduction to computation and modeling for differential equations
Edsberg, Lennart
2008-01-01
An introduction to scientific computing for differential equationsIntroduction to Computation and Modeling for Differential Equations provides a unified and integrated view of numerical analysis, mathematical modeling in applications, and programming to solve differential equations, which is essential in problem-solving across many disciplines, such as engineering, physics, and economics. This book successfully introduces readers to the subject through a unique ""Five-M"" approach: Modeling, Mathematics, Methods, MATLAB, and Multiphysics. This approach facilitates a thorough understanding of h
Testing a new Free Core Nutation empirical model
Belda, Santiago; Ferrándiz, José M.; Heinkelmann, Robert; Nilsson, Tobias; Schuh, Harald
2016-03-01
The Free Core Nutation (FCN) is a free mode of the Earth's rotation caused by the different material characteristics of the Earth's core and mantle. This causes the rotational axes of those layers to slightly diverge from each other, resulting in a wobble of the Earth's rotation axis comparable to nutations. In this paper we focus on estimating empirical FCN models using the observed nutations derived from the VLBI sessions between 1993 and 2013. Assuming a fixed value for the oscillation period, the time-variable amplitudes and phases are estimated by means of multiple sliding window analyses. The effects of using different a priori Earth Rotation Parameters (ERP) in the derivation of models are also addressed. The optimal choice of the fundamental parameters of the model, namely the window width and step-size of its shift, is searched by performing a thorough experimental analysis using real data. The former analyses lead to the derivation of a model with a temporal resolution higher than the one used in the models currently available, with a sliding window reduced to 400 days and a day-by-day shift. It is shown that this new model increases the accuracy of the modeling of the observed Earth's rotation. Besides, empirical models determined from USNO Finals as a priori ERP present a slightly lower Weighted Root Mean Square (WRMS) of residuals than IERS 08 C04 along the whole period of VLBI observations, according to our computations. The model is also validated through comparisons with other recognized models. The level of agreement among them is satisfactory. Let us remark that our estimates give rise to the lowest residuals and seem to reproduce the FCN signal in more detail.
Microscopic models of traveling wave equations
Brunet, Eric; Derrida, Bernard
1999-09-01
Reaction-diffusion problems are often described at a macroscopic scale by partial derivative equations of the type of the Fisher or Kolmogorov-Petrovsky-Piscounov equation. These equations have a continuous family of front solutions, each of them corresponding to a different velocity of the front. By simulating systems of size up to N=1016 particles at the microscopic scale, where particles react and diffuse according to some stochastic rules, we show that a single velocity is selected for the front. This velocity converges logarithmically to the solution of the F-KPP equation with minimal velocity when the number N of particles increases. A simple calculation of the effect introduced by the cutoff due to the microscopic scale allows one to understand the origin of the logarithmic correction.
Rate equation modelling and investigation of quantum cascade detector characteristics
Saha, Sumit; Kumar, Jitendra
2016-10-01
A simple precise transport model has been proposed using rate equation approach for the characterization of a quantum cascade detector. The resonant tunneling transport is incorporated in the rate equation model through a resonant tunneling current density term. All the major scattering processes are included in the rate equation model. The effect of temperature on the quantum cascade detector characteristics has been examined considering the temperature dependent band parameters and the carrier scattering processes. Incorporation of the resonant tunneling process in the rate equation model improves the detector performance appreciably and reproduces the detector characteristics within experimental accuracy.
Xinzhi Liu
1998-01-01
Full Text Available This paper studies a class of high order delay partial differential equations. Employing high order delay differential inequalities, several oscillation criteria are established for such equations subject to two different boundary conditions. Two examples are also given.
USING STRUCTURAL EQUATION MODELING TO INVESTIGATE RELATIONSHIPS AMONG ECOLOGICAL VARIABLES
This paper gives an introductory account of Structural Equation Modeling (SEM) and demonstrates its application using LISRELmodel utilizing environmental data. Using nine EMAP data variables, we analyzed their correlation matrix with an SEM model. The model characterized...
The Whitham Equation as a Model for Surface Water Waves
Moldabayev, Daulet; Dutykh, Denys
2014-01-01
The Whitham equation was proposed as an alternate model equation for the simplified description of uni-directional wave motion at the surface of an inviscid fluid. As the Whitham equation incorporates the full linear dispersion relation of the water wave problem, it is thought to provide a more faithful description of shorter waves of small amplitude than traditional long wave models such as the KdV equation. In this work, we identify a scaling regime in which the Whitham equation can be derived from the Hamiltonian theory of surface water waves. The Whitham equation is integrated numerically, and it is shown that the equation gives a close approximation of inviscid free surface dynamics as described by the Euler equations. The performance of the Whitham equation as a model for free surface dynamics is also compared to two standard free surface models: the KdV and the BBM equation. It is found that in a wide parameter range of amplitudes and wavelengths, the Whitham equation performs on par with or better tha...
Evaluation of model fit in nonlinear multilevel structural equation modeling
Karin eSchermelleh-Engel
2014-03-01
Full Text Available Evaluating model fit in nonlinear multilevel structural equation models (MSEM presents a challenge as no adequate test statistic is available. Nevertheless, using a product indicator approach a likelihood ratio test for linear models is provided which may also be useful for nonlinear MSEM. The main problem with nonlinear models is that product variables are nonnormally distributed. Although robust test statistics have been developed for linear SEM to ensure valid results under the condition of nonnormality, they were not yet investigated for nonlinear MSEM. In a Monte Carlo study, the performance of the robust likelihood ratio test was investigated for models with single-level latent interaction effects using the unconstrained product indicator approach. As overall model fit evaluation has a potential limitation in detecting the lack of fit at a single level even for linear models, level-specific model fit evaluation was also investigated using partially saturated models. Four population models were considered: a model with interaction effects at both levels, an interaction effect at the within-group level, an interaction effect at the between-group level, and a model with no interaction effects at both levels. For these models the number of groups, predictor correlation, and model misspecification was varied. The results indicate that the robust test statistic performed sufficiently well. Advantages of level-specific model fit evaluation for the detection of model misfit are demonstrated.
Evaluation of model fit in nonlinear multilevel structural equation modeling.
Schermelleh-Engel, Karin; Kerwer, Martin; Klein, Andreas G
2014-01-01
Evaluating model fit in nonlinear multilevel structural equation models (MSEM) presents a challenge as no adequate test statistic is available. Nevertheless, using a product indicator approach a likelihood ratio test for linear models is provided which may also be useful for nonlinear MSEM. The main problem with nonlinear models is that product variables are non-normally distributed. Although robust test statistics have been developed for linear SEM to ensure valid results under the condition of non-normality, they have not yet been investigated for nonlinear MSEM. In a Monte Carlo study, the performance of the robust likelihood ratio test was investigated for models with single-level latent interaction effects using the unconstrained product indicator approach. As overall model fit evaluation has a potential limitation in detecting the lack of fit at a single level even for linear models, level-specific model fit evaluation was also investigated using partially saturated models. Four population models were considered: a model with interaction effects at both levels, an interaction effect at the within-group level, an interaction effect at the between-group level, and a model with no interaction effects at both levels. For these models the number of groups, predictor correlation, and model misspecification was varied. The results indicate that the robust test statistic performed sufficiently well. Advantages of level-specific model fit evaluation for the detection of model misfit are demonstrated.
An empirical firn-densification model comprising ice-lences
Reeh, Niels; Fisher, D.A.; Koerner, R.M.
2005-01-01
-density profiles from Canadian Arctic ice-core sites with large melting-refreezing percentages shows good agreement. The model is also used to estimate the long-term surface elevation change in interior Greenland that will result from temperature-driven changes of density-depth profiles. These surface elevation......In the past, several empirical firn-densification models have been developed fitted to measured density-depth profiles from Greenland and Antarctica. These models do not specifically deal with refreezing of meltwater in the firn. Ice lenses are usually indirectly taken into account by choosing...... a suitable value of the surface snow density. In the present study, a simple densification model is developed that specifically accounts for the content of ice lenses in the snowpack. An annual layer is considered to be composed of an ice fraction and a firn fraction. It is assumed that all meltwater formed...
Empirical Analysis of Xinjiang's Bilateral Trade: Gravity Model Approach
CHEN Xuegang; YANG Zhaoping; LIU Xuling
2008-01-01
Based on the basic trade gravity model and Xinjiang's practical situation, new explanatory variables (GDP,GDPpc and SCO) are introduced to build an extended trade gravity model fitting for Xinjiang's bilateral trade. Fromthe empirical analysis of this model, it is proposed that those three variables affect the Xinjiang's bilateral trade posi-tively. Whereas, geographic distance is found to be a significant factor influencing Xinjiang's bilateral trade negatively.Then, by the extended trade gravity model, this article analyzes the present trade situation between Xinjiang and itsmain trade partners quantitatively in 2004. The results indicate that Xinjiang cooperates with its most trade partnerssuccessfully in terms of present economic scale and developing revel. Xinjiang has established successfully trade part-nership with Central Asia, Central Europe and Eastern Europe, Western Europe, East Asia and South Asia. However,the foreign trade development with West Asia is much slower. Finally, some suggestions on developing Xinjiang's for-eign trade are put forward.
Comparison of blade-strike modeling results with empirical data
Ploskey, Gene R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Carlson, Thomas J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2004-03-01
This study is the initial stage of further investigation into the dynamics of injury to fish during passage through a turbine runner. As part of the study, Pacific Northwest National Laboratory (PNNL) estimated the probability of blade strike, and associated injury, as a function of fish length and turbine operating geometry at two adjacent turbines in Powerhouse 1 of Bonneville Dam. Units 5 and 6 had identical intakes, stay vanes, wicket gates, and draft tubes, but Unit 6 had a new runner and curved discharge ring to minimize gaps between the runner hub and blades and between the blade tips and discharge ring. We used a mathematical model to predict blade strike associated with two Kaplan turbines and compared results with empirical data from biological tests conducted in 1999 and 2000. Blade-strike models take into consideration the geometry of the turbine blades and discharges as well as fish length, orientation, and distribution along the runner. The first phase of this study included a sensitivity analysis to consider the effects of difference in geometry and operations between families of turbines on the strike probability response surface. The analysis revealed that the orientation of fish relative to the leading edge of a runner blade and the location that fish pass along the blade between the hub and blade tip are critical uncertainties in blade-strike models. Over a range of discharges, the average prediction of injury from blade strike was two to five times higher than average empirical estimates of visible injury from shear and mechanical devices. Empirical estimates of mortality may be better metrics for comparison to predicted injury rates than other injury measures for fish passing at mid-blade and blade-tip locations.
An Empirical Study of Smoothing Techniques for Language Modeling
Chen, S F; Chen, Stanley F.; Goodman, Joshua T.
1996-01-01
We present an extensive empirical comparison of several smoothing techniques in the domain of language modeling, including those described by Jelinek and Mercer (1980), Katz (1987), and Church and Gale (1991). We investigate for the first time how factors such as training data size, corpus (e.g., Brown versus Wall Street Journal), and n-gram order (bigram versus trigram) affect the relative performance of these methods, which we measure through the cross-entropy of test data. In addition, we introduce two novel smoothing techniques, one a variation of Jelinek-Mercer smoothing and one a very simple linear interpolation technique, both of which outperform existing methods.
Identifying generalized Fitzhugh-Nagumo equation from a numerical solution of Hodgkin-Huxley model
Nikola V. Georgiev
2003-01-01
Full Text Available An analytic time series in the form of numerical solution (in an appropriate finite time interval of the Hodgkin-Huxley current clamped (HHCC system of four differential equations, well known in the neurophysiology as an exact empirical model of excitation of a giant axon of Loligo, is presented. Then we search for a second-order differential equation of generalized Fitzhugh-Nagumo (GFN type, having as a solution the given single component (action potential of the numerical solution. The given time series is used as a basis for reconstructing orders, powers, and coefficients of the polynomial right-hand sides of GFN equation approximately governing the process of action potential. For this purpose, a new geometrical method for determining phase space dimension of the unknown dynamical system (GFN equation and a specific modification of least squares method for identifying unknown coefficients are developed and applied.
Empirical Bayes Credibility Models for Economic Catastrophic Losses by Regions
Jindrová Pavla
2017-01-01
Full Text Available Catastrophic events affect various regions of the world with increasing frequency and intensity. The number of catastrophic events and the amount of economic losses is varying in different world regions. Part of these losses is covered by insurance. Catastrophe events in last years are associated with increases in premiums for some lines of business. The article focus on estimating the amount of net premiums that would be needed to cover the total or insured catastrophic losses in different world regions using Bühlmann and Bühlmann-Straub empirical credibility models based on data from Sigma Swiss Re 2010-2016. The empirical credibility models have been developed to estimate insurance premiums for short term insurance contracts using two ingredients: past data from the risk itself and collateral data from other sources considered to be relevant. In this article we deal with application of these models based on the real data about number of catastrophic events and about the total economic and insured catastrophe losses in seven regions of the world in time period 2009-2015. Estimated credible premiums by world regions provide information how much money in the monitored regions will be need to cover total and insured catastrophic losses in next year.
Empirical Modeling of Plant Gas Fluxes in Controlled Environments
Cornett, Jessie David
1994-01-01
As humans extend their reach beyond the earth, bioregenerative life support systems must replace the resupply and physical/chemical systems now used. The Controlled Ecological Life Support System (CELSS) will utilize plants to recycle the carbon dioxide (CO2) and excrement produced by humans and return oxygen (O2), purified water and food. CELSS design requires knowledge of gas flux levels for net photosynthesis (PS(sub n)), dark respiration (R(sub d)) and evapotranspiration (ET). Full season gas flux data regarding these processes for wheat (Triticum aestivum), soybean (Glycine max) and rice (Oryza sativa) from published sources were used to develop empirical models. Univariate models relating crop age (days after planting) and gas flux were fit by simple regression. Models are either high order (5th to 8th) or more complex polynomials whose curves describe crop development characteristics. The models provide good estimates of gas flux maxima, but are of limited utility. To broaden the applicability, data were transformed to dimensionless or correlation formats and, again, fit by regression. Polynomials, similar to those in the initial effort, were selected as the most appropriate models. These models indicate that, within a cultivar, gas flux patterns appear remarkably similar prior to maximum flux, but exhibit considerable variation beyond this point. This suggests that more broadly applicable models of plant gas flux are feasible, but univariate models defining gas flux as a function of crop age are too simplistic. Multivariate models using CO2 and crop age were fit for PS(sub n), and R(sub d) by multiple regression. In each case, the selected model is a subset of a full third order model with all possible interactions. These models are improvements over the univariate models because they incorporate more than the single factor, crop age, as the primary variable governing gas flux. They are still limited, however, by their reliance on the other environmental
Empirical spatial econometric modelling of small scale neighbourhood
Gerkman, Linda
2012-07-01
The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.
Regime switching model for financial data: Empirical risk analysis
Salhi, Khaled; Deaconu, Madalina; Lejay, Antoine; Champagnat, Nicolas; Navet, Nicolas
2016-11-01
This paper constructs a regime switching model for the univariate Value-at-Risk estimation. Extreme value theory (EVT) and hidden Markov models (HMM) are combined to estimate a hybrid model that takes volatility clustering into account. In the first stage, HMM is used to classify data in crisis and steady periods, while in the second stage, EVT is applied to the previously classified data to rub out the delay between regime switching and their detection. This new model is applied to prices of numerous stocks exchanged on NYSE Euronext Paris over the period 2001-2011. We focus on daily returns for which calibration has to be done on a small dataset. The relative performance of the regime switching model is benchmarked against other well-known modeling techniques, such as stable, power laws and GARCH models. The empirical results show that the regime switching model increases predictive performance of financial forecasting according to the number of violations and tail-loss tests. This suggests that the regime switching model is a robust forecasting variant of power laws model while remaining practical to implement the VaR measurement.
Two Empirical Models for Land-falling Hurricane Gust Factors
Merceret, Franics J.
2008-01-01
Gaussian and lognormal models for gust factors as a function of height and mean windspeed in land-falling hurricanes are presented. The models were empirically derived using data from 2004 hurricanes Frances and Jeanne and independently verified using data from 2005 hurricane Wilma. The data were collected from three wind towers at Kennedy Space Center and Cape Canaveral Air Force Station with instrumentation at multiple levels from 12 to 500 feet above ground level. An additional 200-foot tower was available for the verification. Mean wind speeds from 15 to 60 knots were included in the data. The models provide formulas for the mean and standard deviation of the gust factor given the mean windspeed and height above ground. These statistics may then be used to assess the probability of exceeding a specified peak wind threshold of operational significance given a specified mean wind speed.
A Bayesian modeling approach for generalized semiparametric structural equation models.
Song, Xin-Yuan; Lu, Zhao-Hua; Cai, Jing-Heng; Ip, Edward Hak-Sing
2013-10-01
In behavioral, biomedical, and psychological studies, structural equation models (SEMs) have been widely used for assessing relationships between latent variables. Regression-type structural models based on parametric functions are often used for such purposes. In many applications, however, parametric SEMs are not adequate to capture subtle patterns in the functions over the entire range of the predictor variable. A different but equally important limitation of traditional parametric SEMs is that they are not designed to handle mixed data types-continuous, count, ordered, and unordered categorical. This paper develops a generalized semiparametric SEM that is able to handle mixed data types and to simultaneously model different functional relationships among latent variables. A structural equation of the proposed SEM is formulated using a series of unspecified smooth functions. The Bayesian P-splines approach and Markov chain Monte Carlo methods are developed to estimate the smooth functions and the unknown parameters. Moreover, we examine the relative benefits of semiparametric modeling over parametric modeling using a Bayesian model-comparison statistic, called the complete deviance information criterion (DIC). The performance of the developed methodology is evaluated using a simulation study. To illustrate the method, we used a data set derived from the National Longitudinal Survey of Youth.
Model equations for simulating flows in multistage turbomachinery
Adamczyk, John J.
1996-01-01
A steady, three dimensional average-passage equation system was derived. The purpose was to simulate multistage turbomachinery flows. These equations describe a steady, viscous flow that is periodic from blade passage to blade passage. Moreover, these equations have a closure problem that is similar to that of the Reynolds-average Navier-Stokes equations. A scaled form of the average-passage equation system could provide an improved mathematical model for simulating the flow in the design and in the off-design conditions of a multistage machine.
Dynamic hysteresis modeling including skin effect using diffusion equation model
Hamada, Souad; Louai, Fatima Zohra; Nait-Said, Nasreddine; Benabou, Abdelkader
2016-07-01
An improved dynamic hysteresis model is proposed for the prediction of hysteresis loop of electrical steel up to mean frequencies, taking into account the skin effect. In previous works, the analytical solution of the diffusion equation for low frequency (DELF) was coupled with the inverse static Jiles-Atherton (JA) model in order to represent the hysteresis behavior for a lamination. In the present paper, this approach is improved to ensure the reproducibility of measured hysteresis loops at mean frequency. The results of simulation are compared with the experimental ones. The selected results for frequencies 50 Hz, 100 Hz, 200 Hz and 400 Hz are presented and discussed.
Dynamic hysteresis modeling including skin effect using diffusion equation model
Hamada, Souad, E-mail: souadhamada@yahoo.fr [LSP-IE: Research Laboratory, Electrical Engineering Department, University of Batna, 05000 Batna (Algeria); Louai, Fatima Zohra, E-mail: fz_louai@yahoo.com [LSP-IE: Research Laboratory, Electrical Engineering Department, University of Batna, 05000 Batna (Algeria); Nait-Said, Nasreddine, E-mail: n_naitsaid@yahoo.com [LSP-IE: Research Laboratory, Electrical Engineering Department, University of Batna, 05000 Batna (Algeria); Benabou, Abdelkader, E-mail: Abdelkader.Benabou@univ-lille1.fr [L2EP, Université de Lille1, 59655 Villeneuve d’Ascq (France)
2016-07-15
An improved dynamic hysteresis model is proposed for the prediction of hysteresis loop of electrical steel up to mean frequencies, taking into account the skin effect. In previous works, the analytical solution of the diffusion equation for low frequency (DELF) was coupled with the inverse static Jiles-Atherton (JA) model in order to represent the hysteresis behavior for a lamination. In the present paper, this approach is improved to ensure the reproducibility of measured hysteresis loops at mean frequency. The results of simulation are compared with the experimental ones. The selected results for frequencies 50 Hz, 100 Hz, 200 Hz and 400 Hz are presented and discussed.
Structural equation modeling: building and evaluating causal models: Chapter 8
Grace, James B.; Scheiner, Samuel M.; Schoolmaster, Donald R.
2015-01-01
Scientists frequently wish to study hypotheses about causal relationships, rather than just statistical associations. This chapter addresses the question of how scientists might approach this ambitious task. Here we describe structural equation modeling (SEM), a general modeling framework for the study of causal hypotheses. Our goals are to (a) concisely describe the methodology, (b) illustrate its utility for investigating ecological systems, and (c) provide guidance for its application. Throughout our presentation, we rely on a study of the effects of human activities on wetland ecosystems to make our description of methodology more tangible. We begin by presenting the fundamental principles of SEM, including both its distinguishing characteristics and the requirements for modeling hypotheses about causal networks. We then illustrate SEM procedures and offer guidelines for conducting SEM analyses. Our focus in this presentation is on basic modeling objectives and core techniques. Pointers to additional modeling options are also given.
Empirical likelihood ratio tests for multivariate regression models
WU Jianhong; ZHU Lixing
2007-01-01
This paper proposes some diagnostic tools for checking the adequacy of multivariate regression models including classical regression and time series autoregression. In statistical inference, the empirical likelihood ratio method has been well known to be a powerful tool for constructing test and confidence region. For model checking, however, the naive empirical likelihood (EL) based tests are not of Wilks' phenomenon. Hence, we make use of bias correction to construct the EL-based score tests and derive a nonparametric version of Wilks' theorem. Moreover, by the advantages of both the EL and score test method, the EL-based score tests share many desirable features as follows: They are self-scale invariant and can detect the alternatives that converge to the null at rate n-1/2, the possibly fastest rate for lack-of-fit testing; they involve weight functions, which provides us with the flexibility to choose scores for improving power performance, especially under directional alternatives. Furthermore, when the alternatives are not directional, we construct asymptotically distribution-free maximin tests for a large class of possible alternatives. A simulation study is carried out and an application for a real dataset is analyzed.
A Structural Equation Modeling Analysis of Influences on Juvenile Delinquency
Barrett, David E.; Katsiyannis, Antonis; Zhang, Dalun; Zhang, Dake
2014-01-01
This study examined influences on delinquency and recidivism using structural equation modeling. The sample comprised 199,204 individuals: 99,602 youth whose cases had been processed by the South Carolina Department of Juvenile Justice and a matched control group of 99,602 youth without juvenile records. Structural equation modeling for the…
Reporting Monte Carlo Studies in Structural Equation Modeling
Boomsma, Anne
2013-01-01
In structural equation modeling, Monte Carlo simulations have been used increasingly over the last two decades, as an inventory from the journal Structural Equation Modeling illustrates. Reaching out to a broad audience, this article provides guidelines for reporting Monte Carlo studies in that fiel
Maglevanny, I.I., E-mail: sianko@list.ru [Volgograd State Social Pedagogical University, 27 Lenin Avenue, Volgograd 400131 (Russian Federation); Smolar, V.A.; Nguyen, H.T.T. [Volgograd State Technical University, 28 Lenin Avenue, Volgograd 400131 (Russian Federation)
2013-12-01
A series of simple stopping power (SP) formulas, modified from the relativistic Bethe equation, is presented that is based on the concepts of target effective atomic number and mean excitation energy (MEE). The analytical model function is constructed to approximate experimental or calculated SPs at low electron energies and tend asymptotically to the relativistic Bethe function at high energies. The energy dependencies of our effective values, in contrast with theoretical approaches, are defined empirically by parametrization with tuning parameters. A least-squares fitting routine based on the Levenberg–Marquardt algorithm was developed. We utilize the material parameters and numerical calculations of SPs from optical data using the full Penn-algorithm. Our formula is thought to be applicable for energies above 60 eV. Our simulations of SPs for 41 elemental solids are found to be in good agreement with published numerical results. The flexibility of a general empirical formula is shown. Shortened formulas were developed that are applicable for particular energy ranges, and effective MEEs are proposed that differ from previously recommended values. The presented formulas may be used for analytical calculation of SPs over a broad projectile energy region.
EMPIRE: Nuclear Reaction Model Code System for Data Evaluation
Herman, M.; Capote, R.; Carlson, B. V.; Obložinský, P.; Sin, M.; Trkov, A.; Wienke, H.; Zerkin, V.
2007-12-01
EMPIRE is a modular system of nuclear reaction codes, comprising various nuclear models, and designed for calculations over a broad range of energies and incident particles. A projectile can be a neutron, proton, any ion (including heavy-ions) or a photon. The energy range extends from the beginning of the unresolved resonance region for neutron-induced reactions (∽ keV) and goes up to several hundred MeV for heavy-ion induced reactions. The code accounts for the major nuclear reaction mechanisms, including direct, pre-equilibrium and compound nucleus ones. Direct reactions are described by a generalized optical model (ECIS03) or by the simplified coupled-channels approach (CCFUS). The pre-equilibrium mechanism can be treated by a deformation dependent multi-step direct (ORION + TRISTAN) model, by a NVWY multi-step compound one or by either a pre-equilibrium exciton model with cluster emission (PCROSS) or by another with full angular momentum coupling (DEGAS). Finally, the compound nucleus decay is described by the full featured Hauser-Feshbach model with γ-cascade and width-fluctuations. Advanced treatment of the fission channel takes into account transmission through a multiple-humped fission barrier with absorption in the wells. The fission probability is derived in the WKB approximation within the optical model of fission. Several options for nuclear level densities include the EMPIRE-specific approach, which accounts for the effects of the dynamic deformation of a fast rotating nucleus, the classical Gilbert-Cameron approach and pre-calculated tables obtained with a microscopic model based on HFB single-particle level schemes with collective enhancement. A comprehensive library of input parameters covers nuclear masses, optical model parameters, ground state deformations, discrete levels and decay schemes, level densities, fission barriers, moments of inertia and γ-ray strength functions. The results can be converted into ENDF-6 formatted files using the
Leontev, K. L.
1981-07-01
An expression is obtained for heat capacity differences of materials at a constant pressure and volume, on the basis of the rigorous thermodynamic equation (Kittel, 1976), and by using the Grueneisen law (Kikoin and Kikoin, 1976) of constancy of the ratio of the cubic expansion coefficient to the molar heat capacity. Conditions are determined, where the empirical Nernst and Lindemann (Filippov, 1967) equation is regarded as rigorous.
Empirical model of atomic nitrogen in the upper thermosphere
Engebretson, M. J.; Mauersberger, K.; Kayser, D. C.; Potter, W. E.; Nier, A. O.
1977-01-01
Atomic nitrogen number densities in the upper thermosphere measured by the open source neutral mass spectrometer (OSS) on Atmosphere Explorer-C during 1974 and part of 1975 have been used to construct a global empirical model at an altitude of 375 km based on a spherical harmonic expansion. The most evident features of the model are large diurnal and seasonal variations of atomic nitrogen and only a moderate and latitude-dependent density increase during periods of geomagnetic activity. Maximum and minimum N number densities at 375 km for periods of low solar activity are 3.6 x 10 to the 6th/cu cm at 1500 LST (local solar time) and low latitude in the summer hemisphere and 1.5 x 10 to the 5th/cu cm at 0200 LST at mid-latitudes in the winter hemisphere.
A practical course in differential equations and mathematical modeling
Ibragimov , Nail H
2009-01-01
A Practical Course in Differential Equations and Mathematical Modelling is a unique blend of the traditional methods of ordinary and partial differential equations with Lie group analysis enriched by the author's own theoretical developments. The book which aims to present new mathematical curricula based on symmetry and invariance principles is tailored to develop analytic skills and working knowledge in both classical and Lie's methods for solving linear and nonlinear equations. This approach helps to make courses in differential equations, mathematical modelling, distributions and fundame
EMPIRICAL MODEL FOR HYDROCYCLONES CORRECTED CUT SIZE CALCULATION
André Carlos Silva
2012-12-01
Full Text Available Hydrocyclones are devices worldwide used in mineral processing for desliming, classification, selective classification, thickening and pre-concentration. A hydrocyclone is composed by one cylindrical and one conical section joint together, without any moving parts and it is capable of perform granular material separation in pulp. The mineral particles separation mechanism acting in a hydrocyclone is complex and its mathematical modelling is usually empirical. The most used model for hydrocyclone corrected cut size is proposed by Plitt. Over the years many revisions and corrections to Plitt´s model were proposed. The present paper shows a modification in the Plitt´s model constant, obtained by exponential regression of simulated data for three different hydrocyclones geometry: Rietema, Bradley and Krebs. To validate the proposed model literature data obtained from phosphate ore using fifteen different hydrocyclones geometry are used. The proposed model shows a correlation equals to 88.2% between experimental and calculated corrected cut size, while the correlation obtained using Plitt´s model is 11.5%.
Empirical testing of earthquake recurrence models at source and site
Albarello, D.; Mucciarelli, M.
2012-04-01
Several probabilistic procedures are presently available for seismic hazard assessment (PSHA), based on time-dependent or time-independent models. The result is a number of different outcomes (hazard maps), and to take into account the inherent uncertainty (epistemic), the outcomes of alternative procedures are combined in the frame of logic-tree approaches by scoring each procedure as a function of the respective reliability. This is deduced by evaluating ex-ante (by expert judgements) each element concurring in the relevant PSH computational procedure. This approach appears unsatisfactory also because the value of each procedure depends both on the reliability of each concurring element and on that of their combination: thus, checking the correctness of single elements does not allow evaluating the correctness of the procedure as a whole. Alternative approaches should be based 1) on the ex-post empirical testing of the considered PSH computational models and 2) on the validation of the assumptions underlying concurrent models. The first goal can be achieved comparing the probabilistic forecasts provided by each model with empirical evidence relative to seismic occurrences (e.g., strong-motion data or macroseismic intensity evaluations) during some selected control periods of dimension comparable with the relevant exposure time. About assumptions validation, critical issues are the dimension of the minimum data set necessary to distinguish processes with or without memory, the reliability of mixed data on seismic sources (i.e. historical and palaeoseismological), the completeness of fault catalogues. Some results obtained by the application of these testing procedures in Italy will be shortly outlined.
Evaluation of empirical models and competition indices in ranking canola
A. S Safahani
2012-06-01
Full Text Available In order to evaluate the competitive ability (CA of canola cultivars against wild mustard, two experiments were conducted at the Gorgan Institute in Iran during the 2005-2007 cropping seasons. The experimental factors were canola cultivars (1st year: Zarfam, Option500, Hayola330, Hayola401, Talayh, RGS003 and Sarigol; 2nd year: Zarfam, Hayola330, RGS003 and Option500 and weed density (1st year: control and 30 plants m-2; 2nd year: control, 4, 8 and 16 plants m-2. The result of the first year is experiment indicated that the grain yield and competitive indices differed significantly between the cultivars. Cultivar Zarfam showed a high ability to withstand competition (AWC = 47 %, high competitive indices (CI=1.79 and CI2 = 1.83 and low grain yield in the weed- free plots (1729 kg ha-1. The cultivar Option500, a less competitive cultivar had the lowest ability to withstand competition (AWC = 4 % and the lowest competitive indices (CI = 0.09 and CI2= 0.11 amongst the cultivars. However, the cultivar Option500 showed more grain yield in the weed- free plots (2333 kg ha-1 than cultivar Zarfam. In the second year of the experiment, the result of the yield loss models showed that the lowest and highest yield loss belonged to cultivars Zarfam and Option500 (50 and 95 % respectively. A comparison of different empirical models revealed that the empirical yield loss model based on weed relative leaf area was more reliable for predicting canola yield loss according to a high coefficient of determination (R2=0.99. The relative damage coefficient (q of the weed relative leaf area model showed that wild mustard was more competitive than canola (q>1.
Modeling circadian clocks: From equations to oscillations
Gonze, Didier
2011-01-01
... (such as light and temperature) is greatly helped by mathematical modeling. In the present paper we review some mathematical models for circadian clocks, ranging from abstract, phenomenological models to the most detailed molecular models...
Modelling of nonlinear shoaling based on stochastic evolution equations
Kofoed-Hansen, Henrik; Rasmussen, Jørgen Hvenekær
1998-01-01
A one-dimensional stochastic model is derived to simulate the transformation of wave spectra in shallow water including generation of bound sub- and super-harmonics, near-resonant triad wave interaction and wave breaking. Boussinesq type equations with improved linear dispersion characteristics...... are recast into evolution equations for the complex amplitudes, and serve as the underlying deterministic model. Next, a set of evolution equations for the cumulants is derived. By formally introducing the well-known Gaussian closure hypothesis, nonlinear evolution equations for the power spectrum...... and bispectrum are derived. A simple description of depth-induced wave breaking is incorporated in the model equations, assuming that the total rate of dissipation may be distributed in proportion to the spectral energy density on each discrete frequency. The proposed phase-averaged model is compared...
Adaptation of an empirical model for erythemal ultraviolet irradiance
I. Foyo-Moreno
2007-07-01
Full Text Available In this work we adapt an empirical model to estimate ultraviolet erythemal irradiance (UVER using experimental measurements carried out at seven stations in Spain during four years (2000–2003. The measurements were taken in the framework of the Spanish UVB radiometric network operated and maintained by the Spanish Meteorological Institute. The UVER observations are recorded as half hour average values. The model is valid for all-sky conditions, estimating UVER from the ozone columnar content and parameters usually registered in radiometric networks, such as global broadband hemispherical transmittance and optical air mass. One data set was used to develop the model and another independent set was used to validate it. The model provides satisfactory results, with low mean bias error (MBE for all stations. In fact, MBEs are less than 4% and root mean square errors (RMSE are below 18% (except for one location. The model has also been evaluated to estimate the UV index. The percentage of cases with differences of 0 UVI units is in the range of 61.1% to 72.0%, while the percentage of cases with differences of ±1 UVI unit covers the range of 95.6% to 99.2%. This result confirms the applicability of the model to estimate UVER irradiance and the UV index at those locations in the Iberian Peninsula where there are no UV radiation measurements.
Bayesian structural equation modeling method for hierarchical model validation
Jiang Xiaomo [Department of Civil and Environmental Engineering, Vanderbilt University, Box 1831-B, Nashville, TN 37235 (United States)], E-mail: xiaomo.jiang@vanderbilt.edu; Mahadevan, Sankaran [Department of Civil and Environmental Engineering, Vanderbilt University, Box 1831-B, Nashville, TN 37235 (United States)], E-mail: sankaran.mahadevan@vanderbilt.edu
2009-04-15
A building block approach to model validation may proceed through various levels, such as material to component to subsystem to system, comparing model predictions with experimental observations at each level. Usually, experimental data becomes scarce as one proceeds from lower to higher levels. This paper presents a structural equation modeling approach to make use of the lower-level data for higher-level model validation under uncertainty, integrating several components: lower-level data, higher-level data, computational model, and latent variables. The method proposed in this paper uses latent variables to model two sets of relationships, namely, the computational model to system-level data, and lower-level data to system-level data. A Bayesian network with Markov chain Monte Carlo simulation is applied to represent the two relationships and to estimate the influencing factors between them. Bayesian hypothesis testing is employed to quantify the confidence in the predictive model at the system level, and the role of lower-level data in the model validation assessment at the system level. The proposed methodology is implemented for hierarchical assessment of three validation problems, using discrete observations and time-series data.
Hu, Caihong
2013-04-01
Xiaolandi-Huayuankou region is an important rainstorm centre in the middle Yellow river, which drainage area of 35883km2. A set of forecasting methods applied in this region was formed throughout years of practice. The Xiaohuajian flood forecasting model and empirical model were introduced in this paper. The simulated processes of the Xiaohuajian flood forecasting model include evapotranspiration, infiltration, runoff, river flow. Infiltration and surface runoff are calculated utilizing the Horton model for infiltration into multilayered soil profiles. Overland flow is routed by Nash instantaneous unit hydrograph and Section Muskingum method. The empirical model are simulated using P~Pa~R and empirical relation approach for runoff generation and concentration. The structures of these two models were analyzed and compared in detail. Yihe river basin located in Xiaolandi-Huayuankou region was selected for the purpose of the study. The results show that the accuracy of the two methods are similar, however, the accuracy of Xiaohuajian flood forecasting model for flood forecasting is relatively higher, especially the process of the flood; the accuracy of the empirical methods is much worse, but it can also be accept. The two models are both practicable, so the two models can be combined to apply. The result of the Xiaohuajian flood forecasting model can be used to guide the reservoir for flood control, and the result of empirical methods can be as a reference.
A Tool for Sharing Empirical Models of Climate Impacts
Rising, J.; Kopp, R. E.; Hsiang, S. M.
2013-12-01
Scientists, policy advisors, and the public struggle to synthesize the quickly evolving empirical work on climate change impacts. The Integrated Assessment Models (IAMs) used to estimate the impacts of climate change and the effects of adaptation and mitigation policies can also benefit greatly from recent empirical results (Kopp, Hsiang & Oppenheimer, Impacts World 2013 discussion paper). This paper details a new online tool for exploring, analyzing, combining, and communicating a wide range of impact results, and supporting their integration into IAMs. The tool uses a new database of statistical results, which researchers can expand both in depth (by providing additional results that describing existing relationships) and breadth (by adding new relationships). Scientists can use the tool to quickly perform meta-analyses of related results, using Bayesian techniques to produce pooled and partially-pooled posterior distributions. Policy advisors can apply the statistical results to particular contexts, and combine different kinds of results in a cost-benefit framework. For example, models of the impact of temperature changes on agricultural yields can be first aggregated to build a best-estimate of the effect under given assumptions, then compared across countries using different temperature scenarios, and finally combined to estimate a social cost of carbon. The general public can better understand the many estimates of climate impacts and their range of uncertainty by exploring these results dynamically, with maps, bar charts, and dose-response-style plots. Front page of the climate impacts tool website. Sample "collections" of models, within which all results are estimates of the same fundamental relationship, are shown on the right. Simple pooled result for Gelman's "8 schools" example. Pooled results are calculated analytically, while partial-pooling (Bayesian hierarchical estimation) uses posterior simulations.
Landscape evolution models: A review of their fundamental equations
Chen, Alex; Darbon, Jérôme; Morel, Jean-Michel
2014-08-01
This paper reviews the main physical laws proposed in landscape evolution models (LEMs). It discusses first the main partial differential equations involved in these models and their variants. These equations govern water runoff, stream incision, regolith-bedrock interaction, hillslope evolution, and sedimentation. A synthesis of existing LEMs is proposed. It proposes three models with growing complexity and with a growing number of components: two-equation models with only two components, governing water and bedrock evolution; three-equation models with three components where water, bedrock, and sediment interact; and finally models with four equations and four interacting components, namely water, bedrock, suspended sediment, and regolith. This analysis is not a mere compilation of existing LEMs. It attempts at giving the simplest and most general physically consistent set of equations, coping with all requirements stated in LEMs and LEM software. Three issues are in particular addressed and hopefully resolved. The first one is a correct formulation of the water transport equation down slopes. A general formulation for this equation is proposed, coping not only with the simplest form computing the drainage area but also with a sound energy dissipation argument associated with the Saint-Venant shallow water equations. The second issue arises from the coexistence of two competing modes, namely the detachment-limited erosion mode on hillslopes, and the transport-limited sediment transport on river beds. The third issue (linked to the second) is the fact that no conservation law is available for material in these two modes. A simple solution proposed to resolve these issues is the introduction, as suggested by several authors, of an additional variable for suspended sediment load in water. With only three variables and three equations, the above-mentioned contradictions seem to be eliminated. Several numerical experiments on real digital elevation models (DEMs
Empirical classification of resources in a business model concept
Marko Seppänen
2009-04-01
Full Text Available The concept of the business model has been designed for aiding exploitation of the business potential of an innovation. This exploitation inevitably involves new activities in the organisational context and generates a need to select and arrange the resources of the firm in these new activities. A business model encompasses those resources that a firm has access to and aids in a firm’s effort to create a superior ‘innovation capability’. Selecting and arranging resources to utilise innovations requires resource allocation decisions on multiple fronts as well as poses significant challenges for management of innovations. Although current business model conceptualisations elucidate resources, explicit considerations for the composition and the structures of the resource compositions have remained ambiguous. As a result, current business model conceptualisations fail in their core purpose in assisting the decision-making that must consider the resource allocation in exploiting business opportunities. This paper contributes to the existing discussion regarding the representation of resources as components in the business model concept. The categorized list of resources in business models is validated empirically, using two samples of managers in different positions in several industries. The results indicate that most of the theoretically derived resource items have their equivalents in the business language and concepts used by managers. Thus, the categorisation of the resource components enables further development of the business model concept as well as improves daily communication between managers and their subordinates. Future research could be targeted on linking these components of a business model with each other in order to gain a model to assess the performance of different business model configurations. Furthermore, different applications for the developed resource configuration may be envisioned.
Testing the Empirical Shock Arrival Model using Quadrature Observations
Gopalswamy, N; Xie, H; Yashiro, S
2013-01-01
The empirical shock arrival (ESA) model was developed based on quadrature data from Helios (in-situ) and P-78 (remote-sensing) to predict the Sun-Earth travel time of coronal mass ejections (CMEs) [Gopalswamy et al. 2005a]. The ESA model requires earthward CME speed as input, which is not directly measurable from coronagraphs along the Sun-Earth line. The Solar Terrestrial Relations Observatory (STEREO) and the Solar and Heliospheric Observatory (SOHO) were in quadrature during 2010 - 2012, so the speeds of Earth-directed CMEs were observed with minimal projection effects. We identified a set of 20 full halo CMEs in the field of view of SOHO that were also observed in quadrature by STEREO. We used the earthward speed from STEREO measurements as input to the ESA model and compared the resulting travel times with the observed ones from L1 monitors. We find that the model predicts the CME travel time within about 7.3 hours, which is similar to the predictions by the ENLIL model. We also find that CME-CME and CME...
An Empirical Analysis on Credit Risk Models and its Application
Joocheol Kim
2014-08-01
Full Text Available This study intends to focus on introducing credit default risk with widely used credit risk models in an effort to empirically test whether the models hold their validity, apply to financial institutions which usually are highly levered with various types of debts, and finally reinterpret the results in computing adequate collateral level in the over-the-counter derivatives market. By calculating the distance-to-default values using historical market data for South Korean banks and brokerage firms as suggested in Merton model and KMV’s EDF model, we find that the performance of the introduced models well reflect the credit quality of the sampled financial institutions. Moreover, we suggest that in addition to the given credit ratings of different financial institutions, their distance-to-default values can be utilized in determining the sufficient level of credit support. Our suggested “smoothened” collateral level allows both contractual parties to minimize their costs caused from provision of collateral without undertaking additional credit risk and achieve efficient collateral management.
Acoustic Logging Modeling by Refined Biot's Equations
Plyushchenkov, Boris D.; Turchaninov, Victor I.
An explicit uniform completely conservative finite difference scheme for the refined Biot's equations is proposed. This system is modified according to the modern theory of dynamic permeability and tortuosity in a fluid-saturated elastic porous media. The approximate local boundary transparency conditions are constructed. The acoustic logging device is simulated by the choice of appropriate boundary conditions on its external surface. This scheme and these conditions are satisfactory for exploring borehole acoustic problems in permeable formations in a real axial-symmetrical situation. The developed approach can be adapted for a nonsymmetric case also.
EMPIRICAL MODEL FOR FORMULATION OF CRYSTAL-TOLERANT HLW GLASSES
KRUGER AA; MATYAS J; HUCKLEBERRY AR; VIENNA JD; RODRIGUEZ CA
2012-03-07
Historically, high-level waste (HLW) glasses have been formulated with a low liquideus temperature (T{sub L}), or temperature at which the equilibrium fraction of spinel crystals in the melt is below 1 vol % (T{sub 0.01}), nominally below 1050 C. These constraints cannot prevent the accumulation of large spinel crystals in considerably cooler regions ({approx} 850 C) of the glass discharge riser during melter idling and significantly limit the waste loading, which is reflected in a high volume of waste glass, and would result in high capital, production, and disposal costs. A developed empirical model predicts crystal accumulation in the riser of the melter as a function of concentration of spinel-forming components in glass, and thereby provides guidance in formulating crystal-tolerant glasses that would allow high waste loadings by keeping the spinel crystals small and therefore suspended in the glass.
Excitability in a stochastic differential equation model for calcium puffs.
Rüdiger, S
2014-06-01
Calcium dynamics are essential to a multitude of cellular processes. For many cell types, localized discharges of calcium through small clusters of intracellular channels are building blocks for all spatially extended calcium signals. Because of the large noise amplitude, the validity of noise-approximating model equations for this system has been questioned. Here we revisit the master equations for local calcium release, examine the multiple scales of calcium concentrations in the cluster domain, and derive adapted stochastic differential equations. We show by comparison of discrete and continuous trajectories that the Langevin equations can be made consistent with the master equations even for very small channel numbers. In its deterministic limit, the model reveals that excitability, a dynamical phenomenon observed in many natural systems, is at the core of calcium puffs. The model also predicts a bifurcation from transient to sustained release which may link local and global calcium signals in cells.
Empirical fitness models for hepatitis C virus immunogen design
Hart, Gregory R.; Ferguson, Andrew L.
2015-12-01
Hepatitis C virus (HCV) afflicts 170 million people worldwide, 2%-3% of the global population, and kills 350 000 each year. Prophylactic vaccination offers the most realistic and cost effective hope of controlling this epidemic in the developing world where expensive drug therapies are not available. Despite 20 years of research, the high mutability of the virus and lack of knowledge of what constitutes effective immune responses have impeded development of an effective vaccine. Coupling data mining of sequence databases with spin glass models from statistical physics, we have developed a computational approach to translate clinical sequence databases into empirical fitness landscapes quantifying the replicative capacity of the virus as a function of its amino acid sequence. These landscapes explicitly connect viral genotype to phenotypic fitness, and reveal vulnerable immunological targets within the viral proteome that can be exploited to rationally design vaccine immunogens. We have recovered the empirical fitness landscape for the HCV RNA-dependent RNA polymerase (protein NS5B) responsible for viral genome replication, and validated the predictions of our model by demonstrating excellent accord with experimental measurements and clinical observations. We have used our landscapes to perform exhaustive in silico screening of 16.8 million T-cell immunogen candidates to identify 86 optimal formulations. By reducing the search space of immunogen candidates by over five orders of magnitude, our approach can offer valuable savings in time, expense, and labor for experimental vaccine development and accelerate the search for a HCV vaccine. Abbreviations: HCV—hepatitis C virus, HLA—human leukocyte antigen, CTL—cytotoxic T lymphocyte, NS5B—nonstructural protein 5B, MSA—multiple sequence alignment, PEG-IFN—pegylated interferon.
Soluble Boltzmann equations for internal state and Maxwell models
Futcher, E.; Hoare, M.R.; Hendriks, E.M.; Ernst, M.H.
1980-01-01
We consider a class of scalar nonlinear Boltzmann equations describing the evolution of a microcanonical ensemble in which sub-systems exchange internal energy ‘randomly’ in binary interactions. In the continuous variable version these models can equally be interpreted as Boltzmann equations for Ma
Modeling systems containing alkanolamines with the CPA equation of state
Avlund, Ane Søgaard; Kontogeorgis, Georgios; Michelsen, Michael Locht
2008-01-01
An association model, the cubic-plus-association (CPA) equation of state (EoS), is applied for the first time to a class of multifunctional compounds (alkanolamines). Three alkanolamines of practical and scientific significance are considered; monoethanolamine (MEA), diethanolamine (DEA...... studied using the CPA equation of state (alcohols, amines, and glycols)....
Model equation for simulating flows in multistage turbomachinery
Adamczyk, J. J.
1985-01-01
A steady, three-dimensional average-passage equation system is derived for use in simulating multistage turbomachinery flows. These equations describe a steady, viscous flow that is periodic from blade passage to blade passage. From this system of equations, various reduced forms can be derived for use in simulating the three-dimensional flow field within multistage machinery. It is suggested that a properly scaled form of the averaged-passage equation system would provide an improved mathematical model for simulating the flow in multistage machines at design and, in particular, at off-design conditions.
Transformation of equations in analysis of proportionality through referent models
Romay, E O
2006-01-01
In proportionality of objects, samples or populations, usually we work with Z score of proportionality calculated through referent models, instead directly with the variables of the objects in itself. In these studies we have the necessity to transform, the equations that use the variables of the object, in equations that directly use like variables Z score. In the present work a method is developed to transform the parametric equations, in equations in variables Z using like example the studies of human proportionality from the Phantom stratagem of Ross and Wilson.
An empirical conceptual gully evolution model for channelled sea cliffs
Leyland, Julian; Darby, Stephen E.
2008-12-01
Incised coastal channels are a specific form of incised channel that are found in locations where stream channels flowing to cliffed coasts have the excess energy required to cut down through the cliff to reach the outlet water body. The southern coast of the Isle of Wight, southern England, comprises soft cliffs that vary in height between 15 and 100 m and which are retreating at rates ≤ 1.5 m a - 1 , due to a combination of wave erosion and landslides. In several locations, river channels have cut through the cliffs to create deeply (≤ 45 m) incised gullies, known locally as 'Chines'. The Chines are unusual in that their formation is associated with dynamic shoreline encroachment during a period of rising sea-level, whereas existing models of incised channel evolution emphasise the significance of base level lowering. This paper develops a conceptual model of Chine evolution by applying space for time substitution methods using empirical data gathered from Chine channel surveys and remotely sensed data. The model identifies a sequence of evolutionary stages, which are classified based on a suite of morphometric indices and associated processes. The extent to which individual Chines are in a state of growth or decay is estimated by determining the relative rates of shoreline retreat and knickpoint recession, the former via analysis of historical aerial images and the latter through the use of a stream power erosion model.
Meta-analysis a structural equation modeling approach
Cheung, Mike W-L
2015-01-01
Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the impo
Introduction to Structural Equation Modelling Using SPSS and Amos
Blunch, Niels J
2008-01-01
. Introduction to Structural Equation Modelling using SPSS and AMOS is a complete guide to carrying out your own structural equation modelling project. Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to structural equation modelling (SEM). Each chapter begins with learning objectives, and ends with a list of the new concepts introduced and questions to open up further discussion. Exercises for each chapter, incuding the necessary data, can be downloaded from the book's website. Helpful real life examples are include
Global Empirical Model of the TEC Response to Geomagnetic Activity and Forcing from Below
2014-04-01
AFRL-AFOSR-UK-TR-2014-0025 Global empirical model of the TEC response to geomagnetic activity and forcing from below Dora...April 2014 4. TITLE AND SUBTITLE Global empirical model of the TEC response to geomagnetic activity and forcing from below 5a. CONTRACT NUMBER...the global background TEC model c) Development of global empirical model of TEC response to geomagnetic activity d) On-line implementation of both
An Overview on R Packages for Structural Equation Modeling
Haibin Qiu
2014-05-01
Full Text Available The aim of this study is to present overview on R packages for structural equation modeling. Structural equation modeling, a statistical technique for testing and estimating causal relations using an amalgamation of statistical data and qualitative causal hypotheses, allow both confirmatory and exploratory modeling, meaning they are matched to both hypothesis testing and theory development. R project or R language, a free and popular programming language and computer software surroundings for statistical computing and graphics, is popularly used among statisticians for developing statistical computer software and data analysis. The major finding is that it is necessary to build excellent and enough structural equation modeling packages for R users to do research. Numerous packages for structural equation modeling of R project are introduced in this study and most of them are enclosed in the Comprehensive R Archive Network task view Psychometrics.
A Boussinesq Equation-Based Model for Nearshore Wave Breaking
余建星; 张伟; 王广东; 杨树清
2004-01-01
Based on the wave breaking model by Li and Wang (1999), this work is to apply Dally' s analytical solution to the wave-height decay irstead of the empirical and semi-empirical hypotheses of wave-height distribution within the wave breaking zone. This enhances the applicability of the model. Computational results of shoaling, location of wave breaking, wave-height decay after wave breaking, set-down and set-up for incident regular waves are shown to have good agreement with experimental and field data.
Hybrid empirical--theoretical approach to modeling uranium adsorption
Hull, Larry C.; Grossman, Christopher; Fjeld, Robert A.; Coates, John T.; Elzerman, Alan W
2004-05-01
An estimated 330 metric tons of U are buried in the radioactive waste Subsurface Disposal Area (SDA) at the Idaho National Engineering and Environmental Laboratory (INEEL). An assessment of U transport parameters is being performed to decrease the uncertainty in risk and dose predictions derived from computer simulations of U fate and transport to the underlying Snake River Plain Aquifer. Uranium adsorption isotherms were measured for 14 sediment samples collected from sedimentary interbeds underlying the SDA. The adsorption data were fit with a Freundlich isotherm. The Freundlich n parameter is statistically identical for all 14 sediment samples and the Freundlich K{sub f} parameter is correlated to sediment surface area (r{sup 2}=0.80). These findings suggest an efficient approach to material characterization and implementation of a spatially variable reactive transport model that requires only the measurement of sediment surface area. To expand the potential applicability of the measured isotherms, a model is derived from the empirical observations by incorporating concepts from surface complexation theory to account for the effects of solution chemistry. The resulting model is then used to predict the range of adsorption conditions to be expected in the vadose zone at the SDA based on the range in measured pore water chemistry. Adsorption in the deep vadose zone is predicted to be stronger than in near-surface sediments because the total dissolved carbonate decreases with depth.
Partial Least Squares Structural Equation Modeling with R
Ravand, Hamdollah; Baghaei, Purya
2016-01-01
Structural equation modeling (SEM) has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and…
Study of a pseudo-empirical model approach to characterize plasma actuators
Marziali Bermudez, M [Departamento de Fisica, Facultad de Ciencias Exactas y Naturales, UBA, Ciudad Universitaria Pab. I, Buenos Aires 1428 (Argentina); Sosa, R; Artana, G [Laboratorio de Fluidodinamica, Facultad de Ingenieria, UBA, Av. Paseo Colon 850, Buenos Aires 1063 (Argentina); Grondona, D; Marquez, A; Kelly, H, E-mail: rsosa@fi.uba.ar [Instituto de Fisica del Plasma (CONICET) - Departamento de Fisica, Facultad de Ciencias Exactas y Naturales, UBA, Ciudad Universitaria Pab. I, Buenos Aires 1428 (Argentina)
2011-05-01
The use of plasma actuators is a recent technology that imposes a localized electric force that is used to control air flows. A suitable representation of actuation enables to undertake plasma actuators optimization, to design flow-control strategies, or to analyse the flow stabilization that can be attained by plasma forcing. The problem description may be clearly separated in two regions. An outer region, where the fluid is electrically neutral, in which the flow is described by the Navier-Stokes equation without any forcing term. An inner region, that forms a thin boundary layer, where the fluid is ionized and electric forces are predominant. The outer limit of the inner solution becomes the boundary condition for the outer problem. The outer problem can then be solved with a slip velocity that is issued from the inner solution. Although the solution for the inner problem is quite complex it can be contoured proposing pseudo-empirical models where the slip velocity of the outer problem is determined indirectly from experiments. This pseudo-empirical model approach has been recently tested in different cylinder flows and revealed quite adapted to describe actuated flow behaviour. In this work we determine experimentally the influence of the duty cycle on the slip velocity distribution. The velocity was measured by means of a pitot tube and flow visualizations of the starting vortex (i.e. the induced flow when actuation is activated in a quiescent air) have been done by means of the Schlieren technique. We also performed numerical experiments to simulate the outer region problem when actuation is activated in a quiescent air using a slip velocity distribution as a boundary condition. The experimental and numerical results are in good agreement showing the potential of this pseudo-empirical model approach to characterize the plasma actuation.
ECONOMETRIC APPROACH TO DIFFERENCE EQUATIONS MODELING OF EXCHANGE RATES CHANGES
Josip Arnerić
2010-12-01
Full Text Available Time series models that are commonly used in econometric modeling are autoregressive stochastic linear models (AR and models of moving averages (MA. Mentioned models by their structure are actually stochastic difference equations. Therefore, the objective of this paper is to estimate difference equations containing stochastic (random component. Estimated models of time series will be used to forecast observed data in the future. Namely, solutions of difference equations are closely related to conditions of stationary time series models. Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modeling time varying volatility are GARCH type models and their variants. However, GARCH models will not be analyzed because the purpose of this research is to predict the value of the exchange rate in the levels within conditional mean equation and to determine whether the observed variable has a stable or explosive time path. Based on the estimated difference equation it will be examined whether Croatia is implementing a stable policy of exchange rates.
Dynamic data analysis modeling data with differential equations
Ramsay, James
2017-01-01
This text focuses on the use of smoothing methods for developing and estimating differential equations following recent developments in functional data analysis and building on techniques described in Ramsay and Silverman (2005) Functional Data Analysis. The central concept of a dynamical system as a buffer that translates sudden changes in input into smooth controlled output responses has led to applications of previously analyzed data, opening up entirely new opportunities for dynamical systems. The technical level has been kept low so that those with little or no exposure to differential equations as modeling objects can be brought into this data analysis landscape. There are already many texts on the mathematical properties of ordinary differential equations, or dynamic models, and there is a large literature distributed over many fields on models for real world processes consisting of differential equations. However, a researcher interested in fitting such a model to data, or a statistician interested in...
Methods of mathematical modelling continuous systems and differential equations
Witelski, Thomas
2015-01-01
This book presents mathematical modelling and the integrated process of formulating sets of equations to describe real-world problems. It describes methods for obtaining solutions of challenging differential equations stemming from problems in areas such as chemical reactions, population dynamics, mechanical systems, and fluid mechanics. Chapters 1 to 4 cover essential topics in ordinary differential equations, transport equations and the calculus of variations that are important for formulating models. Chapters 5 to 11 then develop more advanced techniques including similarity solutions, matched asymptotic expansions, multiple scale analysis, long-wave models, and fast/slow dynamical systems. Methods of Mathematical Modelling will be useful for advanced undergraduate or beginning graduate students in applied mathematics, engineering and other applied sciences.
A Framework for Structural Equation Models in General Pedigrees
Morris, Nathan J; Elston, Robert C; Stein, Catherine M
Background/Aims: Structural Equation Modeling (SEM) is an analysis approach that accounts for both the causal relationships between variables and the errors associated with the measurement of these variables...
Deterministic Partial Differential Equation Model for Dose Calculation in Electron Radiotherapy
Duclous, Roland; Frank, Martin
2009-01-01
Treatment with high energy ionizing radiation is one of the main methods in modern cancer therapy that is in clinical use. During the last decades, two main approaches to dose calculation were used, Monte Carlo simulations and semi-empirical models based on Fermi-Eyges theory. A third way to dose calculation has only recently attracted attention in the medical physics community. This approach is based on the deterministic kinetic equations of radiative transfer. Starting from these, we derive a macroscopic partial differential equation model for electron transport in tissue. This model involves an angular closure in the phase space. It is exact for the free-streaming and the isotropic regime. We solve it numerically by a newly developed HLLC scheme based on [BerCharDub], that exactly preserves key properties of the analytical solution on the discrete level. Several numerical results for test cases from the medical physics literature are presented.
Modeling the turbulent kinetic energy equation for compressible, homogeneous turbulence
Aupoix, B.; Blaisdell, G. A.; Reynolds, William C.; Zeman, Otto
1990-01-01
The turbulent kinetic energy transport equation, which is the basis of turbulence models, is investigated for homogeneous, compressible turbulence using direct numerical simulations performed at CTR. It is shown that the partition between dilatational and solenoidal modes is very sensitive to initial conditions for isotropic decaying turbulence but not for sheared flows. The importance of the dilatational dissipation and of the pressure-dilatation term is evidenced from simulations and a transport equation is proposed to evaluate the pressure-dilatation term evolution. This transport equation seems to work well for sheared flows but does not account for initial condition sensitivity in isotropic decay. An improved model is proposed.
Modelling AIDS epidemic and treatment with difference equations
Ramani A
2004-01-01
Full Text Available We propose two models for the description of the dynamics of an AIDS epidemic and of the effect of a combined-drugs AIDS treatment based on difference equations. We show that our interacting population model, despite its extreme simplicity, describes adequately the evolution of an AIDS epidemic. A cellular-automaton analogue of the discrete system of equations is presented as well. In the case of drug treatment, we identify two different regimes corresponding to efficient and inefficient medication. The effect of the discreteness of the equations is also studied.
Modelling AIDS epidemic and treatment with difference equations
A. S. Carstea
2004-07-01
Full Text Available We propose two models for the description of the dynamics of an AIDS epidemic and of the effect of a combined-drugs AIDS treatment based on difference equations. We show that our interacting population model, despite its extreme simplicity, describes adequately the evolution of an AIDS epidemic. A cellular-automaton analogue of the discrete system of equations is presented as well. In the case of drug treatment, we identify two different regimes corresponding to efficient and inefficient medication. The effect of the discreteness of the equations is also studied.
CMB Constraints on Reheating Models with Varying Equation of State
de Freitas, Rodolfo C
2015-01-01
The temperature at the end of reheating and the length of this cosmological phase can be bound to the inflationary observables if one considers the cosmological evolution from the time of Hubble crossing until today. There are many examples in the literature where it is made for single-field inflationary models and a constant equation of state during reheating. We adopt two simple varying equation of state parameters during reheating, combine the allowed range of the reheating parameters with the observational limits of the scalar perturbations spectral index and compare the constraints of some inflationary models with the case of a constant equation of state parameter during reheating.
Huck, P. E.; Bodeker, G. E.; Kremser, S.; McDonald, A. J.; Rex, M.; Struthers, H.
2013-03-01
Two semi-empirical models were developed for the Antarctic stratosphere to relate the shift of species within total chlorine (Cly = HCl + ClONO2 + HOCl + 2 × Cl2 + 2×Cl2O2 + ClO + Cl) into the active forms (here: ClOx = 2×Cl2O2 + ClO), and to relate the rate of ozone destruction to ClOx. These two models provide a fast and computationally inexpensive way to describe the inter- and intra-annual evolution of ClOx and ozone mass deficit (OMD) in the Antarctic spring. The models are based on the underlying physics/chemistry of the system and capture the key chemical and physical processes in the Antarctic stratosphere that determine the interaction between climate change and Antarctic ozone depletion. They were developed considering bulk effects of chemical mechanisms for the duration of the Antarctic vortex period and quantities averaged over the vortex area. The model equations were regressed against observations of daytime ClO and OMD providing a set of empirical fit coefficients. Both semi-empirical models are able to explain much of the intra- and inter-annual variability observed in daily ClOx and OMD time series. This proof-of-concept paper outlines the semi-empirical approach to describing the evolution of Antarctic chlorine activation and ozone depletion.
P. E. Huck
2013-03-01
Full Text Available Two semi-empirical models were developed for the Antarctic stratosphere to relate the shift of species within total chlorine (Cly = HCl + ClONO2 + HOCl + 2 × Cl2 + 2×Cl2O2 + ClO + Cl into the active forms (here: ClOx = 2×Cl2O2 + ClO, and to relate the rate of ozone destruction to ClOx. These two models provide a fast and computationally inexpensive way to describe the inter- and intra-annual evolution of ClOx and ozone mass deficit (OMD in the Antarctic spring. The models are based on the underlying physics/chemistry of the system and capture the key chemical and physical processes in the Antarctic stratosphere that determine the interaction between climate change and Antarctic ozone depletion. They were developed considering bulk effects of chemical mechanisms for the duration of the Antarctic vortex period and quantities averaged over the vortex area. The model equations were regressed against observations of daytime ClO and OMD providing a set of empirical fit coefficients. Both semi-empirical models are able to explain much of the intra- and inter-annual variability observed in daily ClOx and OMD time series. This proof-of-concept paper outlines the semi-empirical approach to describing the evolution of Antarctic chlorine activation and ozone depletion.
Cheung, Mike W.-L.; Cheung, Shu Fai
2016-01-01
Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…
Finite Feedback Cycling in Structural Equation Models
Hayduk, Leslie A.
2009-01-01
In models containing reciprocal effects, or longer causal loops, the usual effect estimates assume that any effect touching a loop initiates an infinite cycling of effects around that loop. The real world, in contrast, might permit only finite feedback cycles. I use a simple hypothetical model to demonstrate that if the world permits only a few…
An empirical model of the quiet daily geomagnetic field variation
Yamazaki, Y.; Yumoto, K.; Cardinal, M.G.; Fraser, B.J.; Hattori, P.; Kakinami, Y.; Liu, J.Y.; Lynn, K.J.W.; Marshall, R.; McNamara, D.; Nagatsuma, T.; Nikiforov, V.M.; Otadoy, R.E.; Ruhimat, M.; Shevtsov, B.M.; Shiokawa, K.; Abe, S.; Uozumi, T.; Yoshikawa, A.
2011-01-01
An empirical model of the quiet daily geomagnetic field variation has been constructed based on geomagnetic data obtained from 21 stations along the 210 Magnetic Meridian of the Circum-pan Pacific Magnetometer Network (CPMN) from 1996 to 2007. Using the least squares fitting method for geomagnetically quiet days (Kp ??? 2+), the quiet daily geomagnetic field variation at each station was described as a function of solar activity SA, day of year DOY, lunar age LA, and local time LT. After interpolation in latitude, the model can describe solar-activity dependence and seasonal dependence of solar quiet daily variations (S) and lunar quiet daily variations (L). We performed a spherical harmonic analysis (SHA) on these S and L variations to examine average characteristics of the equivalent external current systems. We found three particularly noteworthy results. First, the total current intensity of the S current system is largely controlled by solar activity while its focus position is not significantly affected by solar activity. Second, we found that seasonal variations of the S current intensity exhibit north-south asymmetry; the current intensity of the northern vortex shows a prominent annual variation while the southern vortex shows a clear semi-annual variation as well as annual variation. Thirdly, we found that the total intensity of the L current system changes depending on solar activity and season; seasonal variations of the L current intensity show an enhancement during the December solstice, independent of the level of solar activity. Copyright 2011 by the American Geophysical Union.
Mathematical method to build an empirical model for inhaled anesthetic agent wash-in
Grouls René EJ
2011-06-01
Full Text Available Abstract Background The wide range of fresh gas flow - vaporizer setting (FGF - FD combinations used by different anesthesiologists during the wash-in period of inhaled anesthetics indicates that the selection of FGF and FD is based on habit and personal experience. An empirical model could rationalize FGF - FD selection during wash-in. Methods During model derivation, 50 ASA PS I-II patients received desflurane in O2 with an ADU® anesthesia machine with a random combination of a fixed FGF - FD setting. The resulting course of the end-expired desflurane concentration (FA was modeled with Excel Solver, with patient age, height, and weight as covariates; NONMEM was used to check for parsimony. The resulting equation was solved for FD, and prospectively tested by having the formula calculate FD to be used by the anesthesiologist after randomly selecting a FGF, a target FA (FAt, and a specified time interval (1 - 5 min after turning on the vaporizer after which FAt had to be reached. The following targets were tested: desflurane FAt 3.5% after 3.5 min (n = 40, 5% after 5 min (n = 37, and 6% after 4.5 min (n = 37. Results Solving the equation derived during model development for FD yields FD=-(e(-FGF*-0.23+FGF*0.24*(e(FGF*-0.23*FAt*Ht*0.1-e(FGF*-0.23*FGF*2.55+40.46-e(FGF*-0.23*40.46+e(FGF*-0.23+Time/-4.08*40.46-e(Time/-4.08*40.46/((-1+e(FGF*0.24*(-1+e(Time/-4.08*39.29. Only height (Ht could be withheld as a significant covariate. Median performance error and median absolute performance error were -2.9 and 7.0% in the 3.5% after 3.5 min group, -3.4 and 11.4% in the 5% after 5 min group, and -16.2 and 16.2% in the 6% after 4.5 min groups, respectively. Conclusions An empirical model can be used to predict the FGF - FD combinations that attain a target end-expired anesthetic agent concentration with clinically acceptable accuracy within the first 5 min of the start of administration. The sequences are easily calculated in an Excel file and simple to
NN-πNN equations and the chiral bag model
Afnan, I. R.; Blankleider, B.
1985-12-01
The NN-πNN equations that describe, in a unified framework, pion production in nucleon-nucleon scattering, and pion-deuteron and nucleon-nucleon elastic scattering, have been extended to include the N(939) and Δ(1232) on an equal footing. This extension, motivated by the quark models of hadrons, has the bare N and Δ as three quark states with the same spacial wave function, but different spin isospin states. The final equations, referred to as the BB-πBB equations, are consistent with the chiral bag models to the extent that the πNN, πNΔ, and πΔΔ coupling constants and form factors are related, and can be taken from bag models. The resultant equations satisfy two- and three-body unitarity, and are derived by exposing the lowest unitarity cuts in the n-body Green's function. These equations retain important contributions missing from the NN-πNN equations. For pion production and N-N scattering they include the contribution of backward pions in the NN-->NΔ transition potential, which may overcome the problem of small pp-->πd cross section as predicted by the NN-πNN equations. For π-d elastic scattering they include an additional NΔ-->NΔ tensor force that can influence the tensor polarization.
NN-. pi. NN equations and the chiral bag model
Afnan, I.R.; Blankleider, B.
1985-12-01
The NN-..pi..NN equations that describe, in a unified framework, pion production in nucleon-nucleon scattering, and pion-deuteron and nucleon-nucleon elastic scattering, have been extended to include the N(939) and ..delta..(1232) on an equal footing. This extension, motivated by the quark models of hadrons, has the bare N and ..delta.. as three quark states with the same spacial wave function, but different spin isospin states. The final equations, referred to as the BB-..pi..BB equations, are consistent with the chiral bag models to the extent that the ..pi..NN, ..pi..N..delta.., and ..pi delta delta.. coupling constants and form factors are related, and can be taken from bag models. The resultant equations satisfy two- and three-body unitarity, and are derived by exposing the lowest unitarity cuts in the n-body Green's function. These equations retain important contributions missing from the NN-..pi..NN equations. For pion production and N-N scattering they include the contribution of backward pions in the NN..-->..N..delta.. transition potential, which may overcome the problem of small pp..--> pi..d cross section as predicted by the NN-..pi..NN equations. For ..pi..-d elastic scattering they include an additional N..delta -->..N..delta.. tensor force that can influence the tensor polarization.
Empirically tuned model for a precooled MGJT cryoprobe
Skye, H. M.; Passow, K. L.; Nellis, G. F.; Klein, S. A.
Cryosurgery is a medical technique that uses a freezing process to destroy undesirable tissues such as cancerous tumors. The handheld portion of the cryoprobe must be compact and powerful in order to serve as an effective surgical instrument; the next generation of cryoprobes utilizes precooled Mixed Gas Joule-Thomson (pMGJT) cycles to meet these design criteria. The increased refrigeration power available with this more complex cycle improves probe effectiveness by reducing the number of probes and the time required to treat large tissue masses. Selecting mixtures and precooling cycle parameters to meet a cryogenic cooling load in a size-limited application is a challenging design problem. Modeling the precooler and recuperator performance is critical for cycle design, yet existing techniques in the literature typically use highly idealized models of the heat exchangers that neglect pressure drop and assume infinite conductance. These assumptions are questionable for cycles that are required to use compact components. The focus of this research project is to understand how the cycle performance is impacted by transport processes in the heat exchangers and to integrate these findings into an empirically tuned model that can be used for mixture optimization. This effort is carried out through a series of modeling, experimental, and optimization studies. While these results have been applied to the design of a cryosurgical probe, they are also more generally useful in understanding the operation of other compact MGJT systems. A commercially available pMGJT cryoprobe system has been modified in order to integrate a suite of measurement instrumentation that can completely characterize the performance of the individual components as well as the overall system. Measurements include sufficient temperature and pressure sensors to resolve thermodynamic states, as well as flow meters in order to compute the heat and work transfer rates. Temperature sensors are also
Numerical Comparison of Solutions of Kinetic Model Equations
A. A. Frolova
2015-01-01
Full Text Available The collision integral approximation by different model equations has created a whole new trend in the theory of rarefied gas. One widely used model is the Shakhov model (S-model obtained by expansion of inverse collisions integral in a series of Hermite polynomials up to the third order. Using the same expansion with another value of free parameters leads to a linearized ellipsoidal statistical model (ESL.Both model equations (S and ESL have the same properties, as they give the correct relaxation of non-equilibrium stress tensor components and heat flux vector, the correct Prandtl number at the transition to the hydrodynamic regime and do not guarantee the positivity of the distribution function.The article presents numerical comparison of solutions of Shakhov equation, ESL- model and full Boltzmann equation in the four Riemann problems for molecules of hard spheres.We have considered the expansion of two gas flows, contact discontinuity, the problem of the gas counter-flows and the problem of the shock wave structure. For the numerical solution of the kinetic equations the method of discrete ordinates is used.The comparison shows that solution has a weak sensitivity to the form of collision operator in the problem of expansions of two gas flows and results obtained by the model and the kinetic Boltzmann equations coincide.In the problem of the contact discontinuity the solution of model equations differs from full kinetic solutions at the point of the initial discontinuity. The non-equilibrium stress tensor has the maximum errors, the error of the heat flux is much smaller, and the ESL - model gives the exact value of the extremum of heat flux.In the problems of gas counter-flows and shock wave structure the model equations give significant distortion profiles of heat flux and non-equilibrium stress tensor components in front of the shock waves. This behavior is due to fact that in the models under consideration there is no dependency of the
Differential equations and integrable models the $SU(3)$ case
Dorey, P; Dorey, Patrick; Tateo, Roberto
2000-01-01
We exhibit a relationship between the massless $a_2^{(2)}$ integrable quantum field theory and a certain third-order ordinary differential equation, thereby extending a recent result connecting the massless sine-Gordon model to the Schrödinger equation. This forms part of a more general correspondence involving $A_2$-related Bethe ansatz systems and third-order differential equations. A non-linear integral equation for the generalised spectral problem is derived, and some numerical checks are performed. Duality properties are discussed, and a simple variant of the nonlinear equation is suggested as a candidate to describe the finite volume ground state energies of minimal conformal field theories perturbed by the operators $\\phi_{12}$, $\\phi_{21}$ and $\\phi_{15}$. This is checked against previous results obtained using the thermodynamic Bethe ansatz.
Improving the desolvation penalty in empirical protein pK_{a} modeling
Olsson, Mats Henrik Mikael
2012-01-01
Unlike atomistic and continuum models, empirical pk(a) predicting methods need to include desolvation contributions explicitly. This study describes a new empirical desolvation method based on the Born solvation model. The new desolvation model was evaluated by high-level Poisson-Boltzmann...
Empirical agent-based land market: Integrating adaptive economic behavior in urban land-use models
Filatova, Tatiana
2015-01-01
This paper introduces an economic agent-based model of an urban housing market. The RHEA (Risks and Hedonics in Empirical Agent-based land market) model captures natural hazard risks and environmental amenities through hedonic analysis, facilitating empirical agent-based land market modeling. RHEA i
Marczewski, Adam W
2010-10-05
In the article, a new integrated kinetic Langmuir equation (IKL) is derived. The IKL equation is a simple and easy to analyze but complete analytical solution of the kinetic Langmuir model. The IKL is compared with the nth-order, mixed 1,2-order, and multiexponential kinetic equations. The impact of both equilibrium coverage θ(eq) and relative equilibrium uptake u(eq) on kinetics is explained. A newly introduced Langmuir batch equilibrium factor f(eq) that is the product of both parameters θ(eq)u(eq) is used to determine the general kinetic behavior. The analysis of the IKL equation allows us to understand fully the Langmuir kinetics and explains its relation with respect to the empirical pseudo-first-order (PFO, i.e., Lagergren), pseudo-second-order (PSO), and mixed 1,2-order kinetic equations, and it shows the conditions of their possible application based on the Langmuir model. The dependence of the initial adsorption rate on the system properties is analyzed and compared to the earlier published approximate equations.
Schr\\"odinger-Pauli Equation for the Standard Model Extension CPT-Violating Dirac Equation
Gutierrez, Thomas D
2015-01-01
It is instructive to investigate the non-relativistic limit of the simplest Standard Model Extension (SME) CPT-violating Dirac-like equation but with minimal coupling to the electromagnetic fields. In this limit, it becomes an intuitive Schr\\"odinger-Pauli-like equation. This is comparable to the free particle treatment as explored by Kostelecky and Lane, but this exercise only considers the $a$ and $b$ CPT-violating terms and $\\vec{p}/m$ terms to first order. Several toy systems are discussed.
Transport modelling in coastal waters using stochastic differential equations
Charles, W.M.
2007-01-01
In this thesis, the particle model that takes into account the short term correlation behaviour of pollutants dispersion has been developed. An efficient particle model for sediment transport has been developed. We have modified the existing particle model by adding extra equations for the suspensio
Update to Core reporting practices in structural equation modeling.
Schreiber, James B
2016-07-21
This paper is a technical update to "Core Reporting Practices in Structural Equation Modeling."(1) As such, the content covered in this paper includes, sample size, missing data, specification and identification of models, estimation method choices, fit and residual concerns, nested, alternative, and equivalent models, and unique issues within the SEM family of techniques.
Structural Equation Modeling Diagnostics Using R Package Semdiag and EQS
Yuan, Ke-Hai; Zhang, Zhiyong
2012-01-01
Yuan and Hayashi (2010) introduced 2 scatter plots for model and data diagnostics in structural equation modeling (SEM). However, the generation of the plots requires in-depth understanding of their underlying technical details. This article develops and introduces an R package semdiag for easily drawing the 2 plots. With a model specified in EQS…
Hopes and Cautions in Implementing Bayesian Structural Equation Modeling
MacCallum, Robert C.; Edwards, Michael C.; Cai, Li
2012-01-01
Muthen and Asparouhov (2012) have proposed and demonstrated an approach to model specification and estimation in structural equation modeling (SEM) using Bayesian methods. Their contribution builds on previous work in this area by (a) focusing on the translation of conventional SEM models into a Bayesian framework wherein parameters fixed at zero…
Parameter Estimates in Differential Equation Models for Population Growth
Winkel, Brian J.
2011-01-01
We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and two-species competition models. We discuss student-evolved strategies and offer "Mathematica" code for a gradient search approach. We use historical (1930s) data from microbial studies of the Russian biologist,…
Advanced Applications of Structural Equation Modeling in Counseling Psychology Research
Martens, Matthew P.; Haase, Richard F.
2006-01-01
Structural equation modeling (SEM) is a data-analytic technique that allows researchers to test complex theoretical models. Most published applications of SEM involve analyses of cross-sectional recursive (i.e., unidirectional) models, but it is possible for researchers to test more complex designs that involve variables observed at multiple…
A Structural Equation Approach to Models with Spatial Dependence
Oud, J.H.L.; Folmer, H.
2008-01-01
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it poss
A structural equation approach to models with spatial dependence
Oud, J.H.L.; Folmer, H.
2008-01-01
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it poss
Reverberation Modelling Using a Parabolic Equation Method
2012-10-01
et possiblement des échos de cibles. L’objet du présent contrat est une étude du recours à un modèle à équation parabolique, en particulier le...obtained by the ‘PE method’ were primarily compared to results obtained from a proprietary ray-based model provided by Brooke Numerical Services (BNS... Services . Target echo estimates are also compared to the BNS ray model result. In all cases but one the reference data is plotted as a solid red line
Empirical likelihood-based inference in a partially linear model for longitudinal data
无
2008-01-01
A partially linear model with longitudinal data is considered, empirical likelihood to inference for the regression coefficients and the baseline function is investigated, the empirical log-likelihood ratios is proven to be asymptotically chi-squared, and the corresponding confidence regions for the parameters of interest are then constructed. Also by the empirical likelihood ratio functions, we can obtain the maximum empirical likelihood estimates of the regression coefficients and the baseline function, and prove the asymptotic normality. The numerical results are conducted to compare the performance of the empirical likelihood and the normal approximation-based method, and a real example is analysed.
Empirical likelihood-based inference in a partially linear model for longitudinal data
2008-01-01
A partially linear model with longitudinal data is considered, empirical likelihood to infer- ence for the regression coefficients and the baseline function is investigated, the empirical log-likelihood ratios is proven to be asymptotically chi-squared, and the corresponding confidence regions for the pa- rameters of interest are then constructed. Also by the empirical likelihood ratio functions, we can obtain the maximum empirical likelihood estimates of the regression coefficients and the baseline function, and prove the asymptotic normality. The numerical results are conducted to compare the performance of the empirical likelihood and the normal approximation-based method, and a real example is analysed.
Multiple-relaxation-time model for the correct thermohydrodynamic equations.
Zheng, Lin; Shi, Baochang; Guo, Zhaoli
2008-08-01
A coupling lattice Boltzmann equation (LBE) model with multiple relaxation times is proposed for thermal flows with viscous heat dissipation and compression work. In this model the fixed Prandtl number and the viscous dissipation problems in the energy equation, which exist in most of the LBE models, are successfully overcome. The model is validated by simulating the two-dimensional Couette flow, thermal Poiseuille flow, and the natural convection flow in a square cavity. It is found that the numerical results agree well with the analytical solutions and/or other numerical results.
LATTICE BOLTZMANN EQUATION MODEL IN THE CORIOLIS FIELD
FENG SHI-DE; MAO JIANG-YU; ZHANG QIONG
2001-01-01
In a large-scale field of rotational fluid, various unintelligible and surprising dynamic phenomena are produced due to the effect of the Coriolis force. The lattice Boltzmann equation (LBE) model in the Coriolis field is developed based on previous works.[1-4] Geophysical fluid dynamics equations are derived from the model. Numerical simulations have been made on an ideal atmospheric circulation of the Northern Hemisphere by using the model and they reproduce the Rossby wave motion well. Hence the applicability of the model is verified in both theory and experiment.
Model Equilibrium and Empirical Study of Rural Labor Transfer
Qinghua; HUANG; Xiuchuan; XU; Ming; ZHANG; Yue; ZHAO
2013-01-01
We establish the two-sector economy model including the urban sector and the rural sector, derive the labor demand curve of the urban sector and rural sector under the condition of balanced production decisions with benefit maximization, and analyze the labor flow when in the short-term or long-term two-sector economic equilibrium. The results show that rising wages caused by short-term internal and external impact increases the pressure on the employment in two sectors, and the urban sector is difficult to absorb the surplus labor of the rural sector. However, under the conditions of free flow of factors and fully competitive market, the wage variation arising from the long-term endogenous evolution, leads to inversely proportional relationship between the demand for labor in the urban and rural sectors, which is conducive to the transfer of rural labor force. Based on microeconomic survey data of labor flow in urban-rural coordination experimental zones in Chongqing City, this paper makes an empirical study of the main factors having a short-term impact on the labor transfer, and the results show that education level and the opportunity to participate in the training are important factors.
One-equation modeling and validation of dielectric barrier discharge plasma actuator thrust
Yoon, Jae-San; Han, Jae-Hung
2014-10-01
Dielectric barrier discharge (DBD) plasma actuators with an asymmetric electrode configuration can generate a wall-bounded jet without mechanical moving parts, which require considerable modifications of existing aeronautical objects and which incur high maintenance costs. Despite this potential, one factor preventing the wider application of such actuators is the lack of a reliable actuator model. It is difficult to develop such a model because calculating the ion-electric field and fluid interaction consume a high amount calculation effort during the numerical analysis. Thus, the authors proposed a semi-empirical model which predicted the thrust of plasma actuators with a simple equation. It gave a numeric thrust value, and we implemented the value on a computational fluid dynamics (CFD) solver to describe the two-dimensional flow field induced by the actuator. However, the model had a narrow validation range, depending on the empirical formula, and it did not fully consider environment variables. This study presents an improved model by replacing the empirical formulae in the previous model with physical equations that take into account physical phenomena and environmental variables. During this process, additional operation parameters, such as pressure, temperature and ac waveforms, are newly taken to predict the thrust performance of the actuators with a wider range of existing parameters, the thickness of the dielectric barrier, the exposed electrode, the dielectric constant, the ac frequency and the voltage amplitude. Thrust prediction curves from the model are compared to those of earlier experimental results, showing that the average error is less than 5% for more than one hundred instances of data. As in the earlier work, the predicted thrust value is implemented on a CFD solver, and two-dimensional wall-jet velocity profiles induced by the actuator are compared to the previous experimental results.
Empirically modelled Pc3 activity based on solar wind parameters
T. Raita
2010-09-01
Full Text Available It is known that under certain solar wind (SW/interplanetary magnetic field (IMF conditions (e.g. high SW speed, low cone angle the occurrence of ground-level Pc3–4 pulsations is more likely. In this paper we demonstrate that in the event of anomalously low SW particle density, Pc3 activity is extremely low regardless of otherwise favourable SW speed and cone angle. We re-investigate the SW control of Pc3 pulsation activity through a statistical analysis and two empirical models with emphasis on the influence of SW density on Pc3 activity. We utilise SW and IMF measurements from the OMNI project and ground-based magnetometer measurements from the MM100 array to relate SW and IMF measurements to the occurrence of Pc3 activity. Multiple linear regression and artificial neural network models are used in iterative processes in order to identify sets of SW-based input parameters, which optimally reproduce a set of Pc3 activity data. The inclusion of SW density in the parameter set significantly improves the models. Not only the density itself, but other density related parameters, such as the dynamic pressure of the SW, or the standoff distance of the magnetopause work equally well in the model. The disappearance of Pc3s during low-density events can have at least four reasons according to the existing upstream wave theory: 1. Pausing the ion-cyclotron resonance that generates the upstream ultra low frequency waves in the absence of protons, 2. Weakening of the bow shock that implies less efficient reflection, 3. The SW becomes sub-Alfvénic and hence it is not able to sweep back the waves propagating upstream with the Alfvén-speed, and 4. The increase of the standoff distance of the magnetopause (and of the bow shock. Although the models cannot account for the lack of Pc3s during intervals when the SW density is extremely low, the resulting sets of optimal model inputs support the generation of mid latitude Pc3 activity predominantly through
Development of interfacial area transport equation - modeling and experimental benchmark
Ishii, M. [Purdue Univ., West Lafayette, Indiana (United States)
2011-07-01
A dynamic treatment of interfacial area concentration has been studied over the last decade by employing the interfacial area transport equation. When coupled with the two-fluid model, the interfacial area transport equation replaces the flow regime dependent correlations for interfacial area concentration and eliminates potential artificial bifurcation or numerical oscillations stemming from these static correlations. An extensive database has been established to evaluate the model under various two-phase flow conditions. These include adiabatic and heated conditions, vertical and horizontal flow orientations, round, rectangular, annulus and 8×8 rod bundle channel geometries, and normal-gravity and simulated reduced-gravity conditions. This paper reviews the current state-of-the-art in the development of the interfacial area transport equation, available experimental databases and 1D and 3D benchmarking work of the interfacial area transport equation. (author)
Model Equations of Shape Memory Effect - Nitinol
Ion Vela
2010-01-01
Full Text Available Even it has been already confirmed that SMA’s have high potential for robotic actuators, actuators included in space robotics, underwater robotics, robotics for logistics, safety, as well as “green robotics” (robotics for the environment, energy conservation, sustainable development or agriculture, the number of applications of SMA-based actuators is still quite small, especially in applications in which their large strains, high specific work output and structural integration potential are useful,. The paper presents a formulated mathematical model calculated for binary SMA (Ni-Ti, helpful to estimate the stress distribution along with the transformation ratio of a SMA active element.
Basic equations of channel model for underground coal gasification
无
2002-01-01
The underground coal gasification has advantages of zero rubbish, nonpollution, low cost and high safety. According to the characteristics of the gasification, the channel model of chemical fluid mechanics is used to set up the fluid equations and chemical equations by some reasonable suppositions in this paper, which lays a theoretical foundation on requirements of fluid movement rules in the process of underground coal gasification.
QCD Equations of State and the QGP Liquid Model
Letessier, J
2003-01-01
Recent advances in the study of equations of state of thermal lattice Quantum Chromodynamics obtained at non-zero baryon density allow validation of the quark-gluon plasma (QGP) liquid model equations of state (EoS). We study here the properties of the QGP-EoS near to the phase transformation boundary at finite baryon density and show a close agreement with the lattice results.
Controllability in hybrid kinetic equations modeling nonequilibrium multicellular systems.
Bianca, Carlo
2013-01-01
This paper is concerned with the derivation of hybrid kinetic partial integrodifferential equations that can be proposed for the mathematical modeling of multicellular systems subjected to external force fields and characterized by nonconservative interactions. In order to prevent an uncontrolled time evolution of the moments of the solution, a control operator is introduced which is based on the Gaussian thermostat. Specifically, the analysis shows that the moments are solution of a Riccati-type differential equation.
Exploring Factor Model Parameters across Continuous Variables with Local Structural Equation Models.
Hildebrandt, Andrea; Lüdtke, Oliver; Robitzsch, Alexander; Sommer, Christopher; Wilhelm, Oliver
2016-01-01
Using an empirical data set, we investigated variation in factor model parameters across a continuous moderator variable and demonstrated three modeling approaches: multiple-group mean and covariance structure (MGMCS) analyses, local structural equation modeling (LSEM), and moderated factor analysis (MFA). We focused on how to study variation in factor model parameters as a function of continuous variables such as age, socioeconomic status, ability levels, acculturation, and so forth. Specifically, we formalized the LSEM approach in detail as compared with previous work and investigated its statistical properties with an analytical derivation and a simulation study. We also provide code for the easy implementation of LSEM. The illustration of methods was based on cross-sectional cognitive ability data from individuals ranging in age from 4 to 23 years. Variations in factor loadings across age were examined with regard to the age differentiation hypothesis. LSEM and MFA converged with respect to the conclusions. When there was a broad age range within groups and varying relations between the indicator variables and the common factor across age, MGMCS produced distorted parameter estimates. We discuss the pros of LSEM compared with MFA and recommend using the two tools as complementary approaches for investigating moderation in factor model parameters.
Quantum-Dot Semiconductor Optical Amplifiers: State Space Model versus Rate Equation Model
Hussein Taleb
2013-01-01
Full Text Available A simple and accurate dynamic model for QD-SOAs is proposed. The proposed model is based on the state space theory, where by eliminating the distance dependence of the rate equation model of the QD-SOA; we derive a state space model for the device. A comparison is made between the rate equation model and the state space model under both steady state and transient regimes. Simulation results demonstrate that the derived state space model not only is much simpler and faster than the rate equation model, but also it is as accurate as the rate equation model.
Mathematical analysis of partial differential equations modeling electrostatic MEMS
Esposito, Pierpaolo; Guo, Yujin
2010-01-01
Micro- and nanoelectromechanical systems (MEMS and NEMS), which combine electronics with miniature-size mechanical devices, are essential components of modern technology. It is the mathematical model describing "electrostatically actuated" MEMS that is addressed in this monograph. Even the simplified models that the authors deal with still lead to very interesting second- and fourth-order nonlinear elliptic equations (in the stationary case) and to nonlinear parabolic equations (in the dynamic case). While nonlinear eigenvalue problems-where the stationary MEMS models fit-are a well-developed
Modeling Active Aging and Explicit Memory: An Empirical Study.
Ponce de León, Laura Ponce; Lévy, Jean Pierre; Fernández, Tomás; Ballesteros, Soledad
2015-08-01
The rapid growth of the population of older adults and their concomitant psychological status and health needs have captured the attention of researchers and health professionals. To help fill the void of literature available to social workers interested in mental health promotion and aging, the authors provide a model for active aging that uses psychosocial variables. Structural equation modeling was used to examine the relationships among the latent variables of the state of explicit memory, the perception of social resources, depression, and the perception of quality of life in a sample of 184 older adults. The results suggest that explicit memory is not a direct indicator of the perception of quality of life, but it could be considered an indirect indicator as it is positively correlated with perception of social resources and negatively correlated with depression. These last two variables influenced the perception of quality of life directly, the former positively and the latter negatively. The main outcome suggests that the perception of social support improves explicit memory and quality of life and reduces depression in active older adults. The findings also suggest that gerontological professionals should design memory training programs, improve available social resources, and offer environments with opportunities to exercise memory.
Stochastic Differential Equations in Artificial Pancreas Modelling
Duun-Henriksen, Anne Katrine
Type 1 diabetes accounts for approximately 5% of the total diabetes population. It is caused by the destruction of insulin producing β-cells in the pancreas. Various treatment strategies are available today, some of which include advanced technological devices such as an insulin pump and a contin......Type 1 diabetes accounts for approximately 5% of the total diabetes population. It is caused by the destruction of insulin producing β-cells in the pancreas. Various treatment strategies are available today, some of which include advanced technological devices such as an insulin pump...... and a continuous glucose monitor (CGM). Despite these technological advances in the treatment of type 1 diabetes, the disease still poses an enormous and constant challenge for the patients. To obtain tight glucose control the patients are required to assess how much they will eat prior to the meal. They have......, the control algorithm computes the optimal dose adjustment and sends instructions to the insulin pump. To develop control algorithms, mathematical models of the physiological dynamics are needed. They attempt to describe the significant dynamics of the system and hence they approximate the system behavior...
Denitrification in the root zone using a simple empirical model SimDen
Vinther, Finn Pilgaard
2006-01-01
Only by knowing soil type and amount of nitrogen applied, an estimate of the annual denitrification can be obtained with the simple empirical model SimDen.......Only by knowing soil type and amount of nitrogen applied, an estimate of the annual denitrification can be obtained with the simple empirical model SimDen....
Maximum Likelihood Estimation in Meta-Analytic Structural Equation Modeling
Oort, Frans J.; Jak, Suzanne
2016-01-01
Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…
Analyzing Mixed-Dyadic Data Using Structural Equation Models
Peugh, James L.; DiLillo, David; Panuzio, Jillian
2013-01-01
Mixed-dyadic data, collected from distinguishable (nonexchangeable) or indistinguishable (exchangeable) dyads, require statistical analysis techniques that model the variation within dyads and between dyads appropriately. The purpose of this article is to provide a tutorial for performing structural equation modeling analyses of cross-sectional…
Multiplicity Control in Structural Equation Modeling: Incorporating Parameter Dependencies
Smith, Carrie E.; Cribbie, Robert A.
2013-01-01
When structural equation modeling (SEM) analyses are conducted, significance tests for all important model relationships (parameters including factor loadings, covariances, etc.) are typically conducted at a specified nominal Type I error rate ([alpha]). Despite the fact that many significance tests are often conducted in SEM, rarely is…
A Note on Structural Equation Modeling Estimates of Reliability
Yang, Yanyun; Green, Samuel B.
2010-01-01
Reliability can be estimated using structural equation modeling (SEM). Two potential problems with this approach are that estimates may be unstable with small sample sizes and biased with misspecified models. A Monte Carlo study was conducted to investigate the quality of SEM estimates of reliability by themselves and relative to coefficient…
A Structural Equation Model of Expertise in College Physics
Taasoobshirazi, Gita; Carr, Martha
2009-01-01
A model of expertise in physics was tested on a sample of 374 college students in 2 different level physics courses. Structural equation modeling was used to test hypothesized relationships among variables linked to expert performance in physics including strategy use, pictorial representation, categorization skills, and motivation, and these…
A Structural Equation Model for Predicting Business Student Performance
Pomykalski, James J.; Dion, Paul; Brock, James L.
2008-01-01
In this study, the authors developed a structural equation model that accounted for 79% of the variability of a student's final grade point average by using a sample size of 147 students. The model is based on student grades in 4 foundational business courses: introduction to business, macroeconomics, statistics, and using databases. Educators and…
A Bayesian Approach for Analyzing Longitudinal Structural Equation Models
Song, Xin-Yuan; Lu, Zhao-Hua; Hser, Yih-Ing; Lee, Sik-Yum
2011-01-01
This article considers a Bayesian approach for analyzing a longitudinal 2-level nonlinear structural equation model with covariates, and mixed continuous and ordered categorical variables. The first-level model is formulated for measures taken at each time point nested within individuals for investigating their characteristics that are dynamically…
Play Context, Commitment, and Dating Violence: A Structural Equation Model
Gonzalez-Mendez, Rosaura; Hernandez-Cabrera, Juan Andres
2009-01-01
This study develops a structural equation model to describe the effect of two groups of factors (type of commitment and play context) on the violence experienced during intimate partner conflict. After contrasting the model in adolescents and university students, we have confirmed that aggressive play and the simulation of jealousy and anger…
A Structural Equation Model of Conceptual Change in Physics
Taasoobshirazi, Gita; Sinatra, Gale M.
2011-01-01
A model of conceptual change in physics was tested on introductory-level, college physics students. Structural equation modeling was used to test hypothesized relationships among variables linked to conceptual change in physics including an approach goal orientation, need for cognition, motivation, and course grade. Conceptual change in physics…
Parallel Evolutionary Modeling for Nonlinear Ordinary Differential Equations
无
2001-01-01
We introduce a new parallel evolutionary algorithm in modeling dynamic systems by nonlinear higher-order ordinary differential equations (NHODEs). The NHODEs models are much more universal than the traditional linear models. In order to accelerate the modeling process, we propose and realize a parallel evolutionary algorithm using distributed CORBA object on the heterogeneous networking. Some numerical experiments show that the new algorithm is feasible and efficient.
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.
The Hannover Consultation Liaison model: some empirical findings.
Freyberger, H; Künsebeck, H W; Lempa, W; Avenarius, H J; Liedtke, R; Plassman, R; Nordmeyer, J
1985-01-01
Starting from the definitions concerning the concepts 'Liaison medicine' and 'Consultative Psychiatry' we begin with remarks with regard to the Consultation Liaison-Situation in West Germany on the basis of the key-words 'Brief history', 'Independent university units with regard to Psychotherapy and Psychosomatics as well as the connected organization' and 'Teaching procedures'. Following it the Hannover Consultation Liaison model is presented particularly with regard to both the psychosomatic inpatient ward including the functional organization and psychotherapeutic processes as well as the so-called 'Innere Ambulanz' which includes the consultation liaison services in the clinico-medical departments outside Psychiatry and Psychosomatics. Within the 'Innere Ambulanz', which is closely connected to our psychosomatic inpatient ward, the consultation liaison activities and the resulting supportive psychotherapeutic strategies are performed by student auxiliary therapists who are interested in completing their 4-5 months internship-time in our department. We describe both the three supportive psychotherapeutic steps, which may last months to years including subsequent dynamically psychotherapeutic strategies as well as the reactions of the auxiliary therapist function on the students. Furthermore, we may state that there exists no one more optional education procedure of graduate students than the student's confrontation with his partial self-responsibility vis-à-vis a patient who is being supportive-psychotherapeutically treated by him. Specific empirical proofs concerning our patient oriented consultation liaison activities are demonstrated on the basis of previous psychotherapeutic findings in Crohn patients. Here we are able to demonstrate the effectivity of psychotherapy in the case of the supplementarily psychotherapeutically treated patients in comparison to the patients who received medical therapy only. Finally we are able to present quantitative clinico
Empirical evaluation of scoring functions for Bayesian network model selection.
Liu, Zhifa; Malone, Brandon; Yuan, Changhe
2012-01-01
In this work, we empirically evaluate the capability of various scoring functions of Bayesian networks for recovering true underlying structures. Similar investigations have been carried out before, but they typically relied on approximate learning algorithms to learn the network structures. The suboptimal structures found by the approximation methods have unknown quality and may affect the reliability of their conclusions. Our study uses an optimal algorithm to learn Bayesian network structures from datasets generated from a set of gold standard Bayesian networks. Because all optimal algorithms always learn equivalent networks, this ensures that only the choice of scoring function affects the learned networks. Another shortcoming of the previous studies stems from their use of random synthetic networks as test cases. There is no guarantee that these networks reflect real-world data. We use real-world data to generate our gold-standard structures, so our experimental design more closely approximates real-world situations. A major finding of our study suggests that, in contrast to results reported by several prior works, the Minimum Description Length (MDL) (or equivalently, Bayesian information criterion (BIC)) consistently outperforms other scoring functions such as Akaike's information criterion (AIC), Bayesian Dirichlet equivalence score (BDeu), and factorized normalized maximum likelihood (fNML) in recovering the underlying Bayesian network structures. We believe this finding is a result of using both datasets generated from real-world applications rather than from random processes used in previous studies and learning algorithms to select high-scoring structures rather than selecting random models. Other findings of our study support existing work, e.g., large sample sizes result in learning structures closer to the true underlying structure; the BDeu score is sensitive to the parameter settings; and the fNML performs pretty well on small datasets. We also
Continuous Time Structural Equation Modeling with R Package ctsem
Charles C. Driver
2017-04-01
Full Text Available We introduce ctsem, an R package for continuous time structural equation modeling of panel (N > 1 and time series (N = 1 data, using full information maximum likelihood. Most dynamic models (e.g., cross-lagged panel models in the social and behavioural sciences are discrete time models. An assumption of discrete time models is that time intervals between measurements are equal, and that all subjects were assessed at the same intervals. Violations of this assumption are often ignored due to the difficulty of accounting for varying time intervals, therefore parameter estimates can be biased and the time course of effects becomes ambiguous. By using stochastic differential equations to estimate an underlying continuous process, continuous time models allow for any pattern of measurement occasions. By interfacing to OpenMx, ctsem combines the flexible specification of structural equation models with the enhanced data gathering opportunities and improved estimation of continuous time models. ctsem can estimate relationships over time for multiple latent processes, measured by multiple noisy indicators with varying time intervals between observations. Within and between effects are estimated simultaneously by modeling both observed covariates and unobserved heterogeneity. Exogenous shocks with different shapes, group differences, higher order diffusion effects and oscillating processes can all be simply modeled. We first introduce and define continuous time models, then show how to specify and estimate a range of continuous time models using ctsem.
An evolution equation modeling inversion of tulip flames
Dold, J.W. [Univ. of Bristol (United Kingdom). School of Mathematics; Joulin, G. [E.N.S.M.A., Poitiers (France). Lab. d`Energetique et de Detonique
1995-02-01
The authors attempt to reduce the number of physical ingredients needed to model the phenomenon of tulip-flame inversion to a bare minimum. This is achieved by synthesizing the nonlinear, first-order Michelson-Sivashinsky (MS) equation with the second order linear dispersion relation of Landau and Darrieus, which adds only one extra term to the MS equation without changing any of its stationary behavior and without changing its dynamics in the limit of small density change when the MS equation is asymptotically valid. However, as demonstrated by spectral numerical solutions, the resulting second-order nonlinear evolution equation is found to describe the inversion of tulip flames in good qualitative agreement with classical experiments on the phenomenon. This shows that the combined influences of front curvature, geometric nonlinearity and hydrodynamic instability (including its second-order, or inertial effects, which are an essential result of vorticity production at the flame front) are sufficient to reproduce the inversion process.
Applying meta-analysis to structural equation modeling.
Hedges, Larry V
2016-06-01
Structural equation models play an important role in the social sciences. Consequently, there is an increasing use of meta-analytic methods to combine evidence from studies that estimate the parameters of structural equation models. Two approaches are used to combine evidence from structural equation models: A direct approach that combines structural coefficients and an indirect approach that first combines correlation matrices and estimates structural coefficients from the combined correlation matrix. When there is no heterogeneity across studies, direct estimates of structural coefficients from several studies is an appealing approach. Heterogeneity of correlation matrices across studies presents both practical and conceptual problems. An alternative approach to heterogeneity is suggested as an example of how to better handle heterogeneity in this context. Copyright © 2016 John Wiley & Sons, Ltd.
刘红良
2014-01-01
基于美国顾客满意度指数模型、中国高等教育顾客满意度指数模型等相关模型，结合我国职业教育的特点，构建了学生短期岗位实习满意度概念模型及研究假设。研究共收集了221名学生的调查数据，并通过结构方程模型进行检验。结果表明：在学生短期岗位实习时，企业对实习的服务支持、实习的服务支持对学生的实习感知、实习感知对实习体验、实习体验对实习满意、实习满意对实习意愿等均有极显著的正面影响。%Based on the American Customer Satisfaction Index Model and Chinese Higher Education Customer Satisfaction Index Model, as well as the features of Chinese vocational education, a short-term internships satisfaction conceptual model and hypoth-eses were constructed. Data of 221 students was collected and tested through structural equation model. The results showed that there were significantly positive impacts among business on internships service, the internships service on students' perception of internships, internships perception on internships experience, internships experience on internships satisfaction, internships sat-isfaction on internships will respectively.
Job and Professional Leaving Among Newly Licensed RNs: A Structural Equation Model.
Unruh, Lynn; Zhang, Ning Jackie; Chisolm, Latarsha
2016-01-01
With more than 50% of the nursing workforce close to retirement, it is especially important to keep younger nurses in nursing jobs and careers. This study empirically tests a structural equation model of registered nurse (RN) intent to leave the job and profession using data from a survey of newly licensed RNs (NLRNs). Job demands, difficulties and control, intent to leave the job, and intent to leave the profession were latent variables. A number of direct, indirect, and mediating relationships were modeled. Measurement models for all latent variables and the structural model had good fit. The final model showed a path from job demands, difficulties, and control to job satisfaction to intent to leave the job to intent to leave the profession. The results suggest that the process of an NLRN intending to leave the job and profession involves a number of mediators between the work environment and this intent.
Budtz-Jørgensen, Esben; Keiding, Niels; Grandjean, P.
2003-01-01
observational epidemiology; measurement error; multiple endpoints structural equation models; safety standard......observational epidemiology; measurement error; multiple endpoints structural equation models; safety standard...
Phenomenological neutron star equations of state. 3-window modeling of QCD matter
Kojo, Toru [University of Illinois at Urbana-Champaign, Department of Physics, Urbana, Illinois (United States)
2016-03-15
We discuss the 3-window modeling of cold, dense QCD matter equations of state at density relevant to neutron star properties. At low baryon density, n{sub B}
Fateen, Seif-Eddeen K; Khalil, Menna M; Elnabawy, Ahmed O
2013-03-01
Peng-Robinson equation of state is widely used with the classical van der Waals mixing rules to predict vapor liquid equilibria for systems containing hydrocarbons and related compounds. This model requires good values of the binary interaction parameter kij . In this work, we developed a semi-empirical correlation for kij partly based on the Huron-Vidal mixing rules. We obtained values for the adjustable parameters of the developed formula for over 60 binary systems and over 10 categories of components. The predictions of the new equation system were slightly better than the constant-kij model in most cases, except for 10 systems whose predictions were considerably improved with the new correlation.
Seif-Eddeen K. Fateen
2013-03-01
Full Text Available Peng–Robinson equation of state is widely used with the classical van der Waals mixing rules to predict vapor liquid equilibria for systems containing hydrocarbons and related compounds. This model requires good values of the binary interaction parameter kij. In this work, we developed a semi-empirical correlation for kij partly based on the Huron–Vidal mixing rules. We obtained values for the adjustable parameters of the developed formula for over 60 binary systems and over 10 categories of components. The predictions of the new equation system were slightly better than the constant-kij model in most cases, except for 10 systems whose predictions were considerably improved with the new correlation.
Fateen, Seif-Eddeen K.; Khalil, Menna M.; Elnabawy, Ahmed O.
2012-01-01
Peng–Robinson equation of state is widely used with the classical van der Waals mixing rules to predict vapor liquid equilibria for systems containing hydrocarbons and related compounds. This model requires good values of the binary interaction parameter kij. In this work, we developed a semi-empirical correlation for kij partly based on the Huron–Vidal mixing rules. We obtained values for the adjustable parameters of the developed formula for over 60 binary systems and over 10 categories of components. The predictions of the new equation system were slightly better than the constant-kij model in most cases, except for 10 systems whose predictions were considerably improved with the new correlation. PMID:25685411
Foster, N.L.; Paris, C.B.; Kool, J.T.; Baums, I.B.; Stevens, J.R.; Sanchez, J.A.; Bastidas, C.; Agudelo, C.; Bush, P.; Day, O.; Ferrari, R.; Gonzalez, P.; Gore, S.; Guppy, R.; McCartney, M.A.; McCoy, C.; Mendes, J.; Srinivasan, A.; Steiner, S.; Vermeij, M.J.A.; Weil, E.; Mumby, P.J.
2012-01-01
Understanding patterns of connectivity among populations of marine organisms is essential for the development of realistic, spatially explicit models of population dynamics. Two approaches, empirical genetic patterns and oceanographic dispersal modelling, have been used to estimate levels of
Simon WU; Jonathan LI; Gordon HUANG; G.M.ZENG
2004-01-01
The horizontal accuracy of topographic data represented by digital elevation model (DEM) resolution brings about uncertainties in landscape process modeling with raster GIS. This paper presents a study on the effect of topographic variability on cell-based empirical estimation of soil loss and sediment transport. An original DEM of 10m resolution for a case watershed was re-sampled to three realizations of higher grid sizes for a comparative examination. Equations based on the USLE are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams. The study found that the calculated total soil loss from the watershed decreases with the increasing DEM resolution with a linear correlation as spatial variability is reduced by cell aggregation. The USLE topographic factors (LS) extracted from applied DEMs represent spatial variability, and determine the estimations as shown in the modeling results. The commonly used USGS 30m DEM appears to be able to reflect essential spatial variability and suitable for the empirical estimation. The appropriateness of a DEM resolution is dependent upon specific landscape characteristics, applied model and its parameterization. This work attempts to provide a general framework for the research in the DEM-based empirical modeling.
XLISP-Stat Tools for Building Generalised Estimating Equation Models
Thomas Lumley
1996-12-01
Full Text Available This paper describes a set of Lisp-Stat tools for building Generalised Estimating Equation models to analyse longitudinal or clustered measurements. The user interface is based on the built-in regression and generalised linear model prototypes, with the addition of object-based error functions, correlation structures and model formula tools. Residual and deletion diagnostic plots are available on the cluster and observation level and use the dynamic graphics capabilities of Lisp-Stat.
An empirical mixing model for pressurized thermal shock applications
Chexal, V.K.; Chao, J.; Griesbach, T.J.; Nickell, R.E.
1985-04-01
Empirical correlations are developed for the local temperature and velocity distributions in the pressurized water reactor downcomer for pressurized thermal shock scenarios. The correlation is based on Creare test data and has been validated with Science Applications, Inc., experiments and COMMIX code calculations. It provides good agreement under pump flow and natural circulation conditions and gives a conservative estimate under stagnation conditions.
Empirical Bayes Estimation in the Rasch Model: A Simulation.
de Gruijter, Dato N. M.
In a situation where the population distribution of latent trait scores can be estimated, the ordinary maximum likelihood estimator of latent trait scores may be improved upon by taking the estimated population distribution into account. In this paper empirical Bayes estimators are compared with the liklihood estimator for three samples of 300…
Modelling biochemical reaction systems by stochastic differential equations with reflection.
Niu, Yuanling; Burrage, Kevin; Chen, Luonan
2016-05-07
In this paper, we gave a new framework for modelling and simulating biochemical reaction systems by stochastic differential equations with reflection not in a heuristic way but in a mathematical way. The model is computationally efficient compared with the discrete-state Markov chain approach, and it ensures that both analytic and numerical solutions remain in a biologically plausible region. Specifically, our model mathematically ensures that species numbers lie in the domain D, which is a physical constraint for biochemical reactions, in contrast to the previous models. The domain D is actually obtained according to the structure of the corresponding chemical Langevin equations, i.e., the boundary is inherent in the biochemical reaction system. A variant of projection method was employed to solve the reflected stochastic differential equation model, and it includes three simple steps, i.e., Euler-Maruyama method was applied to the equations first, and then check whether or not the point lies within the domain D, and if not perform an orthogonal projection. It is found that the projection onto the closure D¯ is the solution to a convex quadratic programming problem. Thus, existing methods for the convex quadratic programming problem can be employed for the orthogonal projection map. Numerical tests on several important problems in biological systems confirmed the efficiency and accuracy of this approach.
The Fracture Mechanical Markov Chain Fatigue Model Compared with Empirical Data
Gansted, L.; Brincker, Rune; Hansen, Lars Pilegaard
The applicability of the FMF-model (Fracture Mechanical Markov Chain Fatigue Model) introduced in Gansted, L., R. Brincker and L. Pilegaard Hansen (1991) is tested by simulations and compared with empirical data. Two sets of data have been used, the Virkler data (aluminium alloy) and data...... that the FMF-model gives adequate description of the empirical data using model parameters characteristic of the material....
Arrhenius equation for modeling feedyard ammonia emissions using temperature and diet crude protein.
Todd, Richard W; Cole, N Andy; Waldrip, Heidi M; Aiken, Robert M
2013-01-01
Temperature controls many processes of NH volatilization. For example, urea hydrolysis is an enzymatically catalyzed reaction described by the Arrhenius equation. Diet crude protein (CP) controls NH emission by affecting N excretion. Our objectives were to use the Arrhenius equation to model NH emissions from beef cattle () feedyards and test predictions against observed emissions. Per capita NH emission rate (PCER), air temperature (), and CP were measured for 2 yr at two Texas Panhandle feedyards. Data were fitted to analogs of the Arrhenius equation: PCER = () and PCER = (,CP). The models were applied at a third feedyard to predict NH emissions and compare predicted to measured emissions. Predicted mean NH emissions were within -9 and 2% of observed emissions for the () and (T,CP) models, respectively. Annual emission factors calculated from models underestimated annual NH emission by 11% [() model] or overestimated emission by 8% [(,CP) model]. When from a regional weather station and three classes of CP drove the models, the () model overpredicted annual NH emission of the low CP class by 14% and underpredicted emissions of the optimum and high CP classes by 1 and 39%, respectively. The (,CP) model underpredicted NH emissions by 15, 4, and 23% for low, optimum, and high CP classes, respectively. Ammonia emission was successfully modeled using only, but including CP improved predictions. The empirical () and (,CP) models can successfully model NH emissions in the Texas Panhandle. Researchers are encouraged to test the models in other regions where high-quality NH emissions data are available. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Langevin equation model of dispersion in the convective boundary layer
Nasstrom, J S
1998-08-01
This dissertation presents the development and evaluation of a Lagrangian stochastic model of vertical dispersion of trace material in the convective boundary layer (CBL). This model is based on a Langevin equation of motion for a fluid particle, and assumes the fluid vertical velocity probability distribution is skewed and spatially homogeneous. This approach can account for the effect of large-scale, long-lived turbulent structures and skewed vertical velocity distributions found in the CBL. The form of the Langevin equation used has a linear (in velocity) deterministic acceleration and a skewed randomacceleration. For the case of homogeneous fluid velocity statistics, this ""linear-skewed" Langevin equation can be integrated explicitly, resulting in a relatively efficient numerical simulation method. It is shown that this approach is more efficient than an alternative using a "nonlinear-Gaussian" Langevin equation (with a nonlinear deterministic acceleration and a Gaussian random acceleration) assuming homogeneous turbulence, and much more efficient than alternative approaches using Langevin equation models assuming inhomogeneous turbulence. "Reflection" boundary conditions for selecting a new velocity for a particle that encounters a boundary at the top or bottom of the CBL were investigated. These include one method using the standard assumption that the magnitudes of the particle incident and reflected velocities are positively correlated, and two alternatives in which the magnitudes of these velocities are negatively correlated and uncorrelated. The constraint that spatial and velocity distributions of a well-mixed tracer must be the same as those of the fluid, was used to develop the Langevin equation models and the reflection boundary conditions. The two Langevin equation models and three reflection methods were successfully tested using cases for which exact, analytic statistical properties of particle velocity and position are known, including well
Extended master equation models for molecular communication networks
Chou, Chun Tung
2012-01-01
We consider molecular communication networks consisting of transmitters and receivers distributed in a fluidic medium. In such networks, a transmitter sends one or more signalling molecules, which are diffused over the medium, to the receiver to realise the communication. In order to be able to engineer synthetic molecular communication networks, mathematical models for these networks are required. This paper proposes a new stochastic model for molecular communication networks called reaction-diffusion master equation with exogenous input (RDMEX). The key idea behind RDMEX is to model the transmitters as time sequences specify the emission patterns of signalling molecules, while diffusion in the medium and chemical reactions at the receivers are modelled as Markov processes using master equation. An advantage of RDMEX is that it can readily be used to model molecular communication networks with multiple transmitters and receivers. For the case where the reaction kinetics at the receivers is linear, we show ho...
Gaussian Process Structural Equation Models with Latent Variables
Silva, Ricardo
2010-01-01
In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by some causal structure. This corresponds to a family of graphical models known as the structural equation model with latent variables. While linear non-Gaussian variants have been well-studied, inference in nonparametric structural equation models is still underdeveloped. We introduce a sparse Gaussian process parameterization that defines a non-linear structure connecting latent variables, unlike common formulations of Gaussian process latent variable models. An efficient Markov chain Monte Carlo procedure is described. We evaluate the stability of the sampling procedure and the predictive ability of the model compared against the current practice.
Kinetic equations modelling wealth redistribution: a comparison of approaches.
Düring, Bertram; Matthes, Daniel; Toscani, Giuseppe
2008-11-01
Kinetic equations modelling the redistribution of wealth in simple market economies is one of the major topics in the field of econophysics. We present a unifying approach to the qualitative study for a large variety of such models, which is based on a moment analysis in the related homogeneous Boltzmann equation, and on the use of suitable metrics for probability measures. In consequence, we are able to classify the most important feature of the steady wealth distribution, namely the fatness of the Pareto tail, and the dynamical stability of the latter in terms of the model parameters. Our results apply, e.g., to the market model with risky investments [S. Cordier, L. Pareschi, and G. Toscani, J. Stat. Phys. 120, 253 (2005)], and to the model with quenched saving propensities [A. Chatterjee, B. K. Chakrabarti, and S. S. Manna, Physica A 335, 155 (2004)]. Also, we present results from numerical experiments that confirm the theoretical predictions.
Shallow water modeling of Antarctic Bottom Water crossing the equator
Choboter, Paul F.; Swaters, Gordon E.
2004-03-01
The dynamics of abyssal equator-crossing flows are examined by studying simplified models of the flow in the equatorial region in the context of reduced-gravity shallow water theory. A simple "frictional geostrophic" model for one-layer cross-equatorial flow is described, in which geostrophy is replaced at the equator by frictional flow down the pressure gradient. This model is compared via numerical simulations to the one-layer reduced-gravity shallow water model for flow over realistic equatorial Atlantic Ocean bottom topography. It is argued that nonlinear advection is important at key locations where it permits the current to flow against a pressure gradient, a mechanism absent in the frictional geostrophic model and one of the reasons this model predicts less cross-equatorial flow than the shallow water model under similar conditions. Simulations of the shallow water model with an annually varying mass source reproduce the correct amplitude of observed time variability of cross-equatorial flow. The time evolution of volume transport across specific locations suggests that mass is stored in an equatorial basin, which can reduce the amplitude of time dependence of fluid actually proceeding into the Northern Hemisphere as compared to the amount entering the equatorial basin. Observed time series of temperature data at the equator are shown to be consistent with this hypothesis.
Non-Grassmann mechanical model of the Dirac equation
Deriglazov, A. A.; Zamudio, G. P.; Castro, P. S. [Department de Matematica, ICE, Universidade Federal de Juiz de Fora, MG (Brazil); Rizzuti, B. F. [ISB, Universidade Federal do Amazonas, Coari-AM (Brazil)
2012-12-15
We construct a new example of the spinning-particle model without Grassmann variables. The spin degrees of freedom are described on the base of an inner anti-de Sitter space. This produces both {Gamma}{sup {mu}} and {Gamma}{sup {mu}{nu}}-matrices in the course of quantization. Canonical quantization of the model implies the Dirac equation. We present the detailed analysis of both the Lagrangian and the Hamiltonian formulations of the model and obtain the general solution to the classical equations of motion. Comparing Zitterbewegung of the spatial coordinate with the evolution of spin, we ask on the possibility of space-time interpretation for the inner space of spin. We enumerate similarities between our analogous model of the Dirac equation and the two-body system subject to confining potential which admits only the elliptic orbits of the order of de Broglie wavelength. The Dirac equation dictates the perpendicularity of the elliptic orbits to the direction of center-of-mass motion.
Building Context with Tumor Growth Modeling Projects in Differential Equations
Beier, Julie C.; Gevertz, Jana L.; Howard, Keith E.
2015-01-01
The use of modeling projects serves to integrate, reinforce, and extend student knowledge. Here we present two projects related to tumor growth appropriate for a first course in differential equations. They illustrate the use of problem-based learning to reinforce and extend course content via a writing or research experience. Here we discuss…
Multiple Imputation Strategies for Multiple Group Structural Equation Models
Enders, Craig K.; Gottschall, Amanda C.
2011-01-01
Although structural equation modeling software packages use maximum likelihood estimation by default, there are situations where one might prefer to use multiple imputation to handle missing data rather than maximum likelihood estimation (e.g., when incorporating auxiliary variables). The selection of variables is one of the nuances associated…
On the specification of structural equation models for ecological systems
Grace, James B.; Anderson, T. Michael; Olff, Han; Scheiner, Samuel M.
2010-01-01
The use of structural equation modeling (SEM) is often motivated by its utility for investigating complex networks of relationships, but also because of its promise as a means of representing theoretical Concepts using latent variables. In this paper, we discuss characteristics of ecological theory
Investigating Supervisory Relationships and Therapeutic Alliances Using Structural Equation Modeling
DePue, Mary Kristina; Lambie, Glenn W.; Liu, Ren; Gonzalez, Jessica
2016-01-01
The authors used structural equation modeling to examine the contribution of supervisees' supervisory relationship levels to therapeutic alliance (TA) scores with their clients in practicum. Results showed that supervisory relationship scores positively contributed to the TA. Client and counselor ratings of the TA also differed.
Structural Equation Modeling Reporting Practices for Language Assessment
Ockey, Gary J.; Choi, Ikkyu
2015-01-01
Studies that use structural equation modeling (SEM) techniques are increasingly encountered in the language assessment literature. This popularity has created the need for a set of guidelines that can indicate what should be included in a research report and make it possible for research consumers to judge the appropriateness of the…
Robust Structural Equation Modeling with Missing Data and Auxiliary Variables
Yuan, Ke-Hai; Zhang, Zhiyong
2012-01-01
The paper develops a two-stage robust procedure for structural equation modeling (SEM) and an R package "rsem" to facilitate the use of the procedure by applied researchers. In the first stage, M-estimates of the saturated mean vector and covariance matrix of all variables are obtained. Those corresponding to the substantive variables…
Evaluating Interventions with Multimethod Data: A Structural Equation Modeling Approach
Crayen, Claudia; Geiser, Christian; Scheithauer, Herbert; Eid, Michael
2011-01-01
In many intervention and evaluation studies, outcome variables are assessed using a multimethod approach comparing multiple groups over time. In this article, we show how evaluation data obtained from a complex multitrait-multimethod-multioccasion-multigroup design can be analyzed with structural equation models. In particular, we show how the…
Maximum Likelihood Estimation of Nonlinear Structural Equation Models.
Lee, Sik-Yum; Zhu, Hong-Tu
2002-01-01
Developed an EM type algorithm for maximum likelihood estimation of a general nonlinear structural equation model in which the E-step is completed by a Metropolis-Hastings algorithm. Illustrated the methodology with results from a simulation study and two real examples using data from previous studies. (SLD)
Case-Deletion Diagnostics for Nonlinear Structural Equation Models
Lee, Sik-Yum; Lu, Bin
2003-01-01
In this article, a case-deletion procedure is proposed to detect influential observations in a nonlinear structural equation model. The key idea is to develop the diagnostic measures based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm. An one-step pseudo approximation is proposed to reduce the…
Local Influence Analysis of Nonlinear Structural Equation Models
Lee, Sik-Yum; Tang, Nian-Sheng
2004-01-01
By regarding the latent random vectors as hypothetical missing data and based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm, we investigate assessment of local influence of various perturbation schemes in a nonlinear structural equation model. The basic building blocks of local influence analysis…
In-out intermittency in partial differential equation and ordinary differential equation models.
Covas, Eurico; Tavakol, Reza; Ashwin, Peter; Tworkowski, Andrew; Brooke, John M.
2001-06-01
We find concrete evidence for a recently discovered form of intermittency, referred to as in-out intermittency, in both partial differential equation (PDE) and ordinary differential equation (ODE) models of mean field dynamos. This type of intermittency [introduced in P. Ashwin, E. Covas, and R. Tavakol, Nonlinearity 9, 563 (1999)] occurs in systems with invariant submanifolds and, as opposed to on-off intermittency which can also occur in skew product systems, it requires an absence of skew product structure. By this we mean that the dynamics on the attractor intermittent to the invariant manifold cannot be expressed simply as the dynamics on the invariant subspace forcing the transverse dynamics; the transverse dynamics will alter that tangential to the invariant subspace when one is far enough away from the invariant manifold. Since general systems with invariant submanifolds are not likely to have skew product structure, this type of behavior may be of physical relevance in a variety of dynamical settings. The models employed here to demonstrate in-out intermittency are axisymmetric mean-field dynamo models which are often used to study the observed large-scale magnetic variability in the Sun and solar-type stars. The occurrence of this type of intermittency in such models may be of interest in understanding some aspects of such variabilities. (c) 2001 American Institute of Physics.
TIME-IGGCAS model validation:Comparisons with empirical models and observations
2008-01-01
The TIME-IGGCAS (Theoretical Ionospheric Model of the Earth in Institute of Ge- ology and Geophysics, Chinese Academy of Sciences) has been developed re- cently on the basis of previous works. To test its validity, we have made compari- sons of model results with other typical empirical ionospheric models (IRI, NeQuick-ITUR, and TItheridge temperature models) and multi-observations (GPS, Ionosondes, Topex, DMSP, FORMOSAT, and CHAMP) in this paper. Several conclu- sions are obtained from our comparisons. The modeled electron density and elec- tron and ion temperatures are quantitatively in good agreement with those of em- pirical models and observations. TIME-IGGCAS can model the electron density variations versus several factors such as local time, latitude, and season very well and can reproduce most anomalistic features of ionosphere including equatorial anomaly, winter anomaly, and semiannual anomaly. These results imply a good base for the development of ionospheric data assimilation model in the future. TIME-IGGCAS underestimates electron temperature and overestimates ion tem- perature in comparison with either empirical models or observations. The model results have relatively large deviations near sunrise time and sunset time and at the low altitudes. These results give us a reference to improve the model and enhance its performance in the future.
de Guzman, Allan B.; Ines, Joanna Louise C.; Inofinada, Nina Josefa A.; Ituralde, Nielson Louie J.; Janolo, John Robert E.; Jerezo, Jnyv L.; Jhun, Hyae Suk J.
2013-01-01
While a number of empirical studies have been conducted regarding risk for falls among the elderly, there is still a paucity of similar studies in a developing country like the Philippines. This study purports to test through Structural Equation Modeling (SEM) a model that shows the interaction between and among nutrition, balance, fear of…
de Guzman, Allan B.; Ines, Joanna Louise C.; Inofinada, Nina Josefa A.; Ituralde, Nielson Louie J.; Janolo, John Robert E.; Jerezo, Jnyv L.; Jhun, Hyae Suk J.
2013-01-01
While a number of empirical studies have been conducted regarding risk for falls among the elderly, there is still a paucity of similar studies in a developing country like the Philippines. This study purports to test through Structural Equation Modeling (SEM) a model that shows the interaction between and among nutrition, balance, fear of…
Nonzero solutions of nonlinear integral equations modeling infectious disease
Williams, L.R. (Indiana Univ., South Bend); Leggett, R.W.
1982-01-01
Sufficient conditions to insure the existence of periodic solutions to the nonlinear integral equation, x(t) = ..integral../sup t//sub t-tau/f(s,x(s))ds, are given in terms of simple product and product integral inequalities. The equation can be interpreted as a model for the spread of infectious diseases (e.g., gonorrhea or any of the rhinovirus viruses) if x(t) is the proportion of infectives at time t and f(t,x(t)) is the proportion of new infectives per unit time.
Monte, Luigi [ENEA CR Casaccia, Via P. Anguillarese 301 00100 Rome (Italy)], E-mail: luigi.monte@enea.it
2009-06-15
The present work describes a model for predicting the population dynamics of the main components (resources and consumers) of terrestrial ecosystems exposed to ionising radiation. The ecosystem is modelled by the Lotka-Volterra equations with consumer competition. Linear dose-response relationships without threshold are assumed to relate the values of the model parameters to the dose rates. The model accounts for the migration of consumers from areas characterised by different levels of radionuclide contamination. The criteria to select the model parameter values are motivated by accounting for the results of the empirical studies of past decades. Examples of predictions for long-term chronic exposure are reported and discussed.
Monte, Luigi
2009-06-01
The present work describes a model for predicting the population dynamics of the main components (resources and consumers) of terrestrial ecosystems exposed to ionising radiation. The ecosystem is modelled by the Lotka-Volterra equations with consumer competition. Linear dose-response relationships without threshold are assumed to relate the values of the model parameters to the dose rates. The model accounts for the migration of consumers from areas characterised by different levels of radionuclide contamination. The criteria to select the model parameter values are motivated by accounting for the results of the empirical studies of past decades. Examples of predictions for long-term chronic exposure are reported and discussed.
MODELING ORDINARY DIFFERENTIAL EQUATIONS IN MATLAB SIMULINK ®
Ravi Kiran Maddali
2012-01-01
Ordinary differential equations (ODEs) play a vital role in engineering problems. They are used to model continuous dynamical systems as initial and boundary value problems. There are several analytical and numerical methods to solve ODEs. Various numerical methods such as Euler’s method, Runge-Kutta method, etc are so popular in solving these ODEs. MATLAB, the language of technical computation developed by mathworks, is gaining importance both in academic and industry as powerful modeling so...
Structural Identification and Validation in Stochastic Differential Equation based Models
Møller, Jan Kloppenborg; Carstensen, Jacob; Madsen, Henrik
2011-01-01
Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation based experiments. Estimation of parameters in SDEs is, however, possible by combining Kalman filter and likelihood techniques...... as a function of the state variables and global radiation. Further improvements of both the drift and the diffusion term are achieved by comparing simulated densities and data....
Courey, Karim; Wright, Clara; Asfour, Shihab; Onar, Arzu; Bayliss, Jon; Ludwig, Larry
2009-01-01
In this experiment, an empirical model to quantify the probability of occurrence of an electrical short circuit from tin whiskers as a function of voltage was developed. This empirical model can be used to improve existing risk simulation models. FIB and TEM images of a tin whisker confirm the rare polycrystalline structure on one of the three whiskers studied. FIB cross-section of the card guides verified that the tin finish was bright tin.
Lattice Boltzmann model for a steady radiative transfer equation.
Yi, Hong-Liang; Yao, Feng-Ju; Tan, He-Ping
2016-08-01
A complete lattice Boltzmann model (LBM) is proposed for the steady radiative transfer equation (RTE). The RTE can be regarded as a pure convection equation with a source term. To derive the expressions for the equilibrium distribution function and the relaxation time, an artificial isotropic diffusion term is introduced to form a convection-diffusion equation. When the dimensionless relaxation time has a value of 0.5, the lattice Boltzmann equation (LBE) is exactly applicable to the original steady RTE. We also perform a multiscale analysis based on the Chapman-Enskog expansion to recover the macroscopic RTE from the mesoscopic LBE. The D2Q9 model is used to solve the LBE, and the numerical results obtained by the LBM are comparable to the results obtained by other methods or analytical solutions, which demonstrates that the proposed model is highly accurate and stable in simulating multidimensional radiative transfer. In addition, we find that the convergence rate of the LBM depends on the transport properties of RTE: for diffusion-dominated RTE with a large optical thickness, the LBM shows a second-order convergence rate in space, while for convection-dominated RTE with a small optical thickness, a lower convergence rate is observed.
Development of a One-Equation Transition/Turbulence Model
EDWARDS,JACK R.; ROY,CHRISTOPHER J.; BLOTTNER,FREDERICK G.; HASSAN,HASSAN A.
2000-09-26
This paper reports on the development of a unified one-equation model for the prediction of transitional and turbulent flows. An eddy viscosity - transport equation for non-turbulent fluctuation growth based on that proposed by Warren and Hassan (Journal of Aircraft, Vol. 35, No. 5) is combined with the Spalart-Allmaras one-equation model for turbulent fluctuation growth. Blending of the two equations is accomplished through a multidimensional intermittence function based on the work of Dhawan and Narasimha (Journal of Fluid Mechanics, Vol. 3, No. 4). The model predicts both the onset and extent of transition. Low-speed test cases include transitional flow over a flat plate, a single element airfoil, and a multi-element airfoil in landing configuration. High-speed test cases include transitional Mach 3.5 flow over a 5{degree} cone and Mach 6 flow over a flared-cone configuration. Results are compared with experimental data, and the spatial accuracy of selected predictions is analyzed.
Partial differential equations modeling, analysis and numerical approximation
Le Dret, Hervé
2016-01-01
This book is devoted to the study of partial differential equation problems both from the theoretical and numerical points of view. After presenting modeling aspects, it develops the theoretical analysis of partial differential equation problems for the three main classes of partial differential equations: elliptic, parabolic and hyperbolic. Several numerical approximation methods adapted to each of these examples are analyzed: finite difference, finite element and finite volumes methods, and they are illustrated using numerical simulation results. Although parts of the book are accessible to Bachelor students in mathematics or engineering, it is primarily aimed at Masters students in applied mathematics or computational engineering. The emphasis is on mathematical detail and rigor for the analysis of both continuous and discrete problems. .
Short Polymer Modeling using Self-Consistent Integral Equation Method
Kim, Yeongyoon; Park, So Jung; Kim, Jaeup
2014-03-01
Self-consistent field theory (SCFT) is an excellent mean field theoretical tool for predicting the morphologies of polymer based materials. In the standard SCFT, the polymer is modeled as a Gaussian chain which is suitable for a polymer of high molecular weight, but not necessarily for a polymer of low molecular weight. In order to overcome this limitation, Matsen and coworkers have recently developed SCFT of discrete polymer chains in which one polymer is modeled as finite number of beads joined by freely jointed bonds of fixed length. In their model, the diffusion equation of the canonical SCFT is replaced by an iterative integral equation, and the full spectral method is used for the production of the phase diagram of short block copolymers. In this study, for the finite length chain problem, we apply pseudospectral method which is the most efficient numerical scheme to solve the iterative integral equation. We use this new numerical method to investigate two different types of polymer bonds: spring-beads model and freely-jointed chain model. By comparing these results with those of the Gaussian chain model, the influences on the morphologies of diblock copolymer melts due to the chain length and the type of bonds are examined. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (no. 2012R1A1A2043633).
Equation of motion of canonical tensor model and Hamilton-Jacobi equation of general relativity
Chen, Hua; Sato, Yuki
2016-01-01
The canonical tensor model (CTM) is a rank-three tensor model formulated as a totally constrained system in the canonical formalism. The constraint algebra of CTM has a similar structure as that of the ADM formalism of general relativity, and is studied as a discretized model for quantum gravity. In this paper, we analyze the classical equation of motion (EOM) of CTM in a formal continuum limit through a derivative expansion of the tensor up to the forth order, and show that it is the same as the EOM of a coupled system of gravity and a scalar field derived from the Hamilton-Jacobi equation with an appropriate choice of an action. The action contains a scalar field potential of an exponential form, and the system classically respects a dilatational symmetry. We find that the system has a critical dimension, given by six, over which it becomes unstable due to the wrong sign of the scalar kinetic term. In six dimensions, de Sitter spacetime becomes a solution to the EOM, signaling the emergence of a conformal s...
A Confining Model for Charmonium and New Gauge Invariant Field Equations
Hsu, Jong-Ping
2014-01-01
We discuss a confining model for charmonium in which the attractive force are derived from a new type of gauge field equation with a generalized $SU_3$ gauge symmetry. The new gauge transformations involve non-integrable phase factors with vector gauge functions $\\om^a_{\\mu}(x)$. These transformations reduce to the usual $SU_3$ gauge transformations in the special case $\\om^a_\\mu(x) = \\p_\\mu \\xi^a(x)$. Such a generalized gauge symmetry leads to the fourth-order equations for new gauge fields and to the linear confining potentials. The fourth-order field equation implies that the corresponding massless gauge boson has non-definite energy. However, the new gauge boson is permanently confined in a quark system by the linear potential. We use the empirical potentials of the Cornell group for charmonium to obtain the coupling strength $f^2/(4\\pi) \\approx 0.19$ for the strong interaction. Such a confining model of quark dynamics could be compatible with perturbation. The model can be applied to other quark-antiquar...
The development of empirical models to evaluate energy use and energy cost in wastewater collection
Young, David Morgan
This research introduces a unique data analysis method and develops empirical models to evaluate energy use and energy cost in wastewater collection systems using operational variables. From these models, several Best Management Processes (BMPs) are identified that should benefit utilities and positively impact the operation of existing infrastructure as well as the design of new infrastructure. Further, the conclusions generated herein display high transferability to certain manufacturing processes. Therefore, it is anticipated that these findings will also benefit pumping applications outside of the water sector. Wastewater treatment is often the single largest expense at the local government level. Not surprisingly, significant research effort has been expended on examining the energy used in wastewater treatment. However, the energy used in wastewater collection systems remains underexplored despite significant potential for energy savings. Estimates place potential energy savings as high as 60% within wastewater collection; which, if applied across the United States equates to the energy used by nearly 125,000 American homes. Employing three years of data from Renewable Water Resources (ReWa), the largest wastewater utility in the Upstate of South Carolina, this study aims to develop useful empirical equations that will allow utilities to efficiently evaluate the energy use and energy cost of its wastewater collection system. ReWa's participation was motivated, in part, by their recent adoption of the United States Environmental Protection Agency "Effective Utility Strategies" within which exists a focus on energy management. The study presented herein identifies two primary variables related to the energy use and cost associated with wastewater collection: Specific Energy (Es) and Specific Cost (Cs). These two variables were found to rely primarily on the volume pumped by the individual pump stations and exhibited similar power functions for the three year
Saygın, Selen Deviren; Basaran, Mustafa; Ozcan, Ali Ugur; Dolarslan, Melda; Timur, Ozgur Burhan; Yilman, F Ebru; Erpul, Gunay
2011-09-01
Land degradation by soil erosion is one of the most serious problems and environmental issues in many ecosystems of arid and semi-arid regions. Especially, the disturbed areas have greater soil detachability and transportability capacity. Evaluation of land degradation in terms of soil erodibility, by using geostatistical modeling, is vital to protect and reclaim susceptible areas. Soil erodibility, described as the ability of soils to resist erosion, can be measured either directly under natural or simulated rainfall conditions, or indirectly estimated by empirical regression models. This study compares three empirical equations used to determine the soil erodibility factor of revised universal soil loss equation prediction technology based on their geospatial performances in the semi-arid catchment of the Saraykoy II Irrigation Dam located in Cankiri, Turkey. A total of 311 geo-referenced soil samples were collected with irregular intervals from the top soil layer (0-10 cm). Geostatistical analysis was performed with the point values of each equation to determine its spatial pattern. Results showed that equations that used soil organic matter in combination with the soil particle size better agreed with the variations in land use and topography of the catchment than the one using only the particle size distribution. It is recommended that the equations which dynamically integrate soil intrinsic properties with land use, topography, and its influences on the local microclimates, could be successfully used to geospatially determine sites highly susceptible to water erosion, and therefore, to select the agricultural and bio-engineering control measures needed.
Quasi-hydrostatic Primitive Equations for Ocean Global Circulation Models
Carine LUCAS; Madalina PETCU; Antoine ROUSSEAU
2010-01-01
Global existence of weak and strong solutions to the quasi-hydrostatic primitive equations is studied in this paper.This model,that derives from the full non-hydrostatic model for geophysical fluid dynamics in the zero-limit of the aspect ratio,is more realistic than the classical hydrostatic model,since the traditional approximation that consists in neglecting a part of the Coriolis force is relaxed.After justifying the derivation of the model,the authors provide a rigorous proof of global existence of weak solutions,and well-posedness for strong solutions in dimension three.
Structural Equation Modeling with Mplus Basic Concepts, Applications, and Programming
Byrne, Barbara M
2011-01-01
Modeled after Barbara Byrne's other best-selling structural equation modeling (SEM) books, this practical guide reviews the basic concepts and applications of SEM using Mplus Versions 5 & 6. The author reviews SEM applications based on actual data taken from her own research. Using non-mathematical language, it is written for the novice SEM user. With each application chapter, the author "walks" the reader through all steps involved in testing the SEM model including: an explanation of the issues addressed illustrated and annotated testing of the hypothesized and post hoc models expl
Gonçalves, O. D.; Boldt, S.; Kasch, K. U.
2016-09-01
This work aims at measuring the scattering cross sections for white beams and the verification of a semi-empirical model predicting scattered energy spectra of an X-ray beam produced by an industrial X-ray tube (Pantack Sievert, 120 kV, tungsten target) incident on a water sample. Both, theoretical and semi-empirical results presented are based on the form factor approach with results well corresponding to performed measurements. The elastic (Rayleigh) scattering cross sections are based on Thomson scattering with a form factor correction as published by Morin (1982). The inelastic (Compton) contribution is based on the Klein Nishina equation (Klein and Nishina, 1929) multiplied by the incoherent scattering factors calculated by Hubbel et al. (1975). Two major results are presented: first, the experimental integrated in energy cross sections corresponds with theoretical cross sections obtained at the mean energy of the measured scattered spectra at a given angle. Secondly, the measured scattered spectra at a given angle correspond to those obtained utilizing the semi-empirical model as proposed here. A good correspondence of experimental results and model predictions can be shown. The latter, therefore, proves to be a useful method to calculate the scattering contributions in a number of applications as for example cone beam tomography.
Bloch-Redfield equations for modeling light-harvesting complexes
Jeske, Jan; Plenio, Martin B; Huelga, Susana F; Cole, Jared H
2014-01-01
We challenge the commonly held view that Bloch-Redfield equations are a less powerful tool than phenomenological Lindblad equations for modeling exciton transport in photosynthetic complexes. This view predominantly originates from the misuse of the secular approximation. We provide a detailed description of how to model both coherent oscillations and several types of noise, giving explicit examples. All issues with non-positivity are overcome by a consistent straightforward physical noise model. Herein also lies the strength of the Bloch-Redfield approach because it facilitates the analysis of noise-effects by linking them back to physical parameters of the noise environment. This includes temporal and spatial correlations and the strength and type of interaction between the noise and the system of interest. Finally we analyze a prototypical dimer system as well as a 7-site Fenna-Matthews-Olson (FMO) complex in regards to spatial correlation length of the noise, noise strength, temperature and their connecti...
Study of a model equation in detonation theory: multidimensional effects
Faria, Luiz M; Rosales, Rodolfo R
2015-01-01
We extend the reactive Burgers equation presented in Kasimov et al. Phys. Rev. Lett., 110 (2013) and Faria et al. SIAM J. Appl. Maths, 74 (2014), to include multidimensional effects. Furthermore, we explain how the model can be rationally justified following the ideas of the asymptotic theory developed in Faria et al. JFM (2015). The proposed model is a forced version of the unsteady small disturbance transonic flow equations. We show that for physically reasonable choices of forcing functions, traveling wave solutions akin to detonation waves exist. It is demonstrated that multidimensional effects play an important role in the stability and dynamics of the traveling waves. Numerical simulations indicate that solutions of the model tend to form multi-dimensional patterns analogous to cells in gaseous detonations.
A stochastic differential equation model for transcriptional regulatory networks
Quirk Michelle D
2007-05-01
Full Text Available Abstract Background This work explores the quantitative characteristics of the local transcriptional regulatory network based on the availability of time dependent gene expression data sets. The dynamics of the gene expression level are fitted via a stochastic differential equation model, yielding a set of specific regulators and their contribution. Results We show that a beta sigmoid function that keeps track of temporal parameters is a novel prototype of a regulatory function, with the effect of improving the performance of the profile prediction. The stochastic differential equation model follows well the dynamic of the gene expression levels. Conclusion When adapted to biological hypotheses and combined with a promoter analysis, the method proposed here leads to improved models of the transcriptional regulatory networks.
P. E. Huck
2012-10-01
Full Text Available Two semi-empirical models were developed for the Antarctic stratosphere to relate the shift of species within total chlorine (Cl_{y} = HCl + ClONO_{2} + HOCl + 2 × Cl_{2} + 2 × Cl_{2}O_{2} + ClO + Cl into the active forms (here: ClO_{x} = 2 × Cl_{2}O_{2} + ClO, and to relate the rate of ozone destruction to ClO_{x}. These two models provide a fast and computationally inexpensive way to describe the inter- and intra-annual evolution of ClO_{x} and ozone mass deficit (OMD in the Antarctic spring. The models are based on the underlying physics/chemistry of the system and capture the key chemical and physical processes in the Antarctic stratosphere that determine the interaction between climate change and Antarctic ozone depletion. They were developed considering bulk effects of chemical mechanisms for the duration of the Antarctic vortex period and quantities averaged over the vortex area. The model equations were regressed against observations of daytime ClO and OMD providing a set of empirical fit coefficients. Both semi-empirical models are able to explain much of the intra- and inter-annual variability observed in daily ClO_{x} and OMD time series. This proof-of-concept paper outlines the semi-empirical approach to describing the evolution of Antarctic chlorine activation and ozone depletion.
THE DYSON-SCHWINGER EQUATION FOR A MODEL WITH INSTANTONS - THE SCHWINGER MODEL
Adam, C.
1995-01-01
Using the exact path integral solution of the Schwinger model -- a model where instantons are present -- the Dyson-Schwinger equation is shown to hold by explicit computation. It turns out that the Dyson-Schwinger equation separately holds for every instanton sector. This is due to Theta-invariance of the Schwinger model.
Excited TBA equations I: Massive tricritical Ising model
Pearce, Paul A. E-mail: p.pearce@ms.unimelb.edu.au; Chim, Leung E-mail: leung.chim@dsto.defence.gov.au; Ahn, Changrim E-mail: ahn@dante.ewha.ac.kr
2001-05-14
We consider the massive tricritical Ising model M(4,5) perturbed by the thermal operator phi (cursive,open) Greek{sub 1,3} in a cylindrical geometry and apply integrable boundary conditions, labelled by the Kac labels (r,s), that are natural off-critical perturbations of known conformal boundary conditions. We derive massive thermodynamic Bethe ansatz (TBA) equations for all excitations by solving, in the continuum scaling limit, the TBA functional equation satisfied by the double-row transfer matrices of the A{sub 4} lattice model of Andrews, Baxter and Forrester (ABF) in Regime III. The complete classification of excitations, in terms of (m,n) systems, is precisely the same as at the conformal tricritical point. Our methods also apply on a torus but we first consider (r,s) boundaries on the cylinder because the classification of states is simply related to fermionic representations of single Virasoro characters {chi}{sub r,s}(q). We study the TBA equations analytically and numerically to determine the conformal UV and free particle IR spectra and the connecting massive flows. The TBA equations in Regime IV and massless RG flows are studied in Part II.
GDP model for Chinese energy modeling based on empirical production function
HiroshiYAGITA; BaorenWEI; AtsushiINABA; MasayukiSAGISAKA; KeikoHIROTA; KiyoyukiMINATO
2003-01-01
In many energy models, GDP is an exogenous variable, so that variables within energy model are not able to change the value of GDP. Based on empirical production function, a GDP model has been established in this paper using capital stock, urbanization rate and population size as independent variables. It has been found that urbanization rate is a kind of integrated indicator of labor quantity and the education level of labors in China. And it also takes away the labor surplus in rural area in China. The forecasting results show that the model is robust. The results have the same tendency as the results from famous CGE model and the results from responsible Chinese authorities, and the numbers of GDP growth rates are also similar in 50 years. It has been concluded that the model is a good candidate for energy model as an endogenous vadable.
Constructing stochastic models from deterministic process equations by propensity adjustment
Wu Jialiang
2011-11-01
Full Text Available Abstract Background Gillespie's stochastic simulation algorithm (SSA for chemical reactions admits three kinds of elementary processes, namely, mass action reactions of 0th, 1st or 2nd order. All other types of reaction processes, for instance those containing non-integer kinetic orders or following other types of kinetic laws, are assumed to be convertible to one of the three elementary kinds, so that SSA can validly be applied. However, the conversion to elementary reactions is often difficult, if not impossible. Within deterministic contexts, a strategy of model reduction is often used. Such a reduction simplifies the actual system of reactions by merging or approximating intermediate steps and omitting reactants such as transient complexes. It would be valuable to adopt a similar reduction strategy to stochastic modelling. Indeed, efforts have been devoted to manipulating the chemical master equation (CME in order to achieve a proper propensity function for a reduced stochastic system. However, manipulations of CME are almost always complicated, and successes have been limited to relative simple cases. Results We propose a rather general strategy for converting a deterministic process model into a corresponding stochastic model and characterize the mathematical connections between the two. The deterministic framework is assumed to be a generalized mass action system and the stochastic analogue is in the format of the chemical master equation. The analysis identifies situations: where a direct conversion is valid; where internal noise affecting the system needs to be taken into account; and where the propensity function must be mathematically adjusted. The conversion from deterministic to stochastic models is illustrated with several representative examples, including reversible reactions with feedback controls, Michaelis-Menten enzyme kinetics, a genetic regulatory motif, and stochastic focusing. Conclusions The construction of a stochastic
Digiovanni, K. A.; Montalto, F. A.; Gaffin, S.; Rosenzweig, C.
2010-12-01
Green roofs and other urban green spaces can provide a variety of valuable benefits including reduction of the urban heat island effect, reduction of stormwater runoff, carbon sequestration, oxygen generation, air pollution mitigation etc. As many of these benefits are directly linked to the processes of evaporation and transpiration, accurate and representative estimation of urban evapotranspiration (ET) is a necessary tool for predicting and quantifying such benefits. However, many common ET estimation procedures were developed for agricultural applications, and thus carry inherent assumptions that may only be rarely applicable to urban green spaces. Various researchers have identified the estimation of expected urban ET rates as critical, yet poorly studied components of urban green space performance prediction and cite that further evaluation is needed to reconcile differences in predictions from varying ET modeling approaches. A small scale green roof lysimeter setup situated on the green roof of the Ethical Culture Fieldston School in the Bronx, NY has been the focus of ongoing monitoring initiated in June 2009. The experimental setup includes a 0.6 m by 1.2 m Lysimeter replicating the anatomy of the 500 m2 green roof of the building, with a roof membrane, drainage layer, 10 cm media depth, and planted with a variety of Sedum species. Soil moisture sensors and qualitative runoff measurements are also recorded in the Lysimeter, while a weather station situated on the rooftop records climatologic data. Direct quantification of actual evapotranspiration (AET) from the green roof weighing lysimeter was achieved through a mass balance approaches during periods absent of precipitation and drainage. A comparison of AET to estimates of potential evapotranspiration (PET) calculated from empirically and physically based ET models was performed in order to evaluate the applicability of conventional ET equations for the estimation of ET from green roofs. Results have
Generalized latent variable modeling multilevel, longitudinal, and structural equation models
Skrondal, Anders
2004-01-01
METHODOLOGY THE OMNI-PRESENCE OF LATENT VARIABLES Introduction 'True' variable measured with error Hypothetical constructs Unobserved heterogeneity Missing values and counterfactuals Latent responses Generating flexible distributions Combining information Summary MODELING DIFFERENT RESPONSE PROCESSES Introduction Generalized linear models Extensions of generalized linear models Latent response formulation Modeling durations or survival Summary and further reading CLASSICAL LATENT VARIABLE MODELS Introduction Multilevel regression models Factor models and item respons
BOJAN D. DJORDJEVIC
2007-12-01
Full Text Available Although many cubic equations of state coupled with van der Waals-one fluid mixing rules including temperature dependent interaction parameters are sufficient for representing phase equilibria and excess properties (excess molar enthalpy HE, excess molar volume VE, etc., difficulties appear in the correlation and prediction of thermodynamic properties of complex mixtures at various temperature and pressure ranges. Great progress has been made by a new approach based on CEOS/GE models. This paper reviews the last six-year of progress achieved in modelling of the volumetric properties for complex binary and ternary systems of non-electrolytes by the CEOS and CEOS/GE approaches. In addition, the vdW1 and TCBT models were used to estimate the excess molar volume VE of ternary systems methanol + chloroform + benzene and 1-propanol + chloroform + benzene, as well as the corresponding binaries methanol + chloroform, chloroform + benzene, 1-propanol + chloroform and 1-propanol + benzene at 288.15–313.15 K and atmospheric pressure. Also, prediction of VE for both ternaries by empirical models (Radojković, Kohler, Jackob–Fitzner, Colinet, Tsao–Smith, Toop, Scatchard, Rastogi was performed.
Structural equation modeling in the context of clinical research
2017-01-01
Structural equation modeling (SEM) has been widely used in economics, sociology and behavioral science. However, its use in clinical medicine is quite limited, probably due to technical difficulties. Because SEM is particularly suitable for analysis of complex relationships among observed variables, it must have potential applications to clinical medicine. The article introduces basic ideas of SEM in the context of clinical medicine. A simulated dataset is employed to show how to do model specification, model fit, visualization and assessment of goodness-of-fit. The first example fits a SEM with continuous outcome variable using sem() function, and the second explores the binary outcome variable using lavaan() function. PMID:28361067
Two-equation modeling of turbulent rotating flows
Cazalbou, Jean-Bernard; Chassaing, Patrick; Dufour, Guillaume; CARBONNEAU, Xavier
2005-01-01
The possibility to take into account the effects of the Coriolis acceleration on turbulence is examined in the framework of two-equation eddy-viscosity models. General results on the physical consistency of such turbulence models are derived from a dynamical-system approach to situations of time-evolving homogeneous turbulence in a rotating frame. Application of this analysis to a (k,epsilon) model fitted with an existing Coriolis correction [J. H. G. Howard, S. V. Patankar, and R. M. Bordynu...
Using Graph and Vertex Entropy to Compare Empirical Graphs with Theoretical Graph Models
Tomasz Kajdanowicz
2016-09-01
Full Text Available Over the years, several theoretical graph generation models have been proposed. Among the most prominent are: the Erdős–Renyi random graph model, Watts–Strogatz small world model, Albert–Barabási preferential attachment model, Price citation model, and many more. Often, researchers working with real-world data are interested in understanding the generative phenomena underlying their empirical graphs. They want to know which of the theoretical graph generation models would most probably generate a particular empirical graph. In other words, they expect some similarity assessment between the empirical graph and graphs artificially created from theoretical graph generation models. Usually, in order to assess the similarity of two graphs, centrality measure distributions are compared. For a theoretical graph model this means comparing the empirical graph to a single realization of a theoretical graph model, where the realization is generated from the given model using an arbitrary set of parameters. The similarity between centrality measure distributions can be measured using standard statistical tests, e.g., the Kolmogorov–Smirnov test of distances between cumulative distributions. However, this approach is both error-prone and leads to incorrect conclusions, as we show in our experiments. Therefore, we propose a new method for graph comparison and type classification by comparing the entropies of centrality measure distributions (degree centrality, betweenness centrality, closeness centrality. We demonstrate that our approach can help assign the empirical graph to the most similar theoretical model using a simple unsupervised learning method.
John Jack P. RIEGEL III; David DAVISON
2016-01-01
Historically, there has been little correlation between the material properties used in (1) empirical formulae, (2) analytical formulations, and (3) numerical models. The various regressions and models may each provide excellent agreement for the depth of penetration into semi-infinite targets. But the input parameters for the empirically based procedures may have little in common with either the analytical model or the numerical model. This paper builds on previous work by Riegel and Anderson (2014) to show how the Effective Flow Stress (EFS) strength model, based on empirical data, can be used as the average flow stress in the analytical Walker–Anderson Penetration model (WAPEN) (Anderson and Walker, 1991) and how the same value may be utilized as an effective von Mises yield strength in numerical hydrocode simulations to predict the depth of penetration for eroding projectiles at impact velocities in the mechanical response regime of the materials. The method has the benefit of allowing the three techniques (empirical, analytical, and numerical) to work in tandem. The empirical method can be used for many shot line calculations, but more advanced analytical or numerical models can be employed when necessary to address specific geometries such as edge effects or layering that are not treated by the simpler methods. Developing complete constitutive relationships for a material can be costly. If the only concern is depth of penetration, such a level of detail may not be required. The effective flow stress can be determined from a small set of depth of penetration experiments in many cases, especially for long penetrators such as the L/D=10 ones considered here, making it a very practical approach. In the process of performing this effort, the authors considered numerical simulations by other researchers based on the same set of experimental data that the authors used for their empirical and analytical assessment. The goals were to establish a baseline with a full
John (Jack P. Riegel III
2016-04-01
Full Text Available Historically, there has been little correlation between the material properties used in (1 empirical formulae, (2 analytical formulations, and (3 numerical models. The various regressions and models may each provide excellent agreement for the depth of penetration into semi-infinite targets. But the input parameters for the empirically based procedures may have little in common with either the analytical model or the numerical model. This paper builds on previous work by Riegel and Anderson (2014 to show how the Effective Flow Stress (EFS strength model, based on empirical data, can be used as the average flow stress in the analytical Walker–Anderson Penetration model (WAPEN (Anderson and Walker, 1991 and how the same value may be utilized as an effective von Mises yield strength in numerical hydrocode simulations to predict the depth of penetration for eroding projectiles at impact velocities in the mechanical response regime of the materials. The method has the benefit of allowing the three techniques (empirical, analytical, and numerical to work in tandem. The empirical method can be used for many shot line calculations, but more advanced analytical or numerical models can be employed when necessary to address specific geometries such as edge effects or layering that are not treated by the simpler methods. Developing complete constitutive relationships for a material can be costly. If the only concern is depth of penetration, such a level of detail may not be required. The effective flow stress can be determined from a small set of depth of penetration experiments in many cases, especially for long penetrators such as the L/D = 10 ones considered here, making it a very practical approach. In the process of performing this effort, the authors considered numerical simulations by other researchers based on the same set of experimental data that the authors used for their empirical and analytical assessment. The goals were to establish a
Study of a Model Equation in Detonation Theory
Faria, Luiz
2014-04-24
Here we analyze properties of an equation that we previously proposed to model the dynamics of unstable detonation waves [A. R. Kasimov, L. M. Faria, and R. R. Rosales, Model for shock wave chaos, Phys. Rev. Lett., 110 (2013), 104104]. The equation is ut+ 1/2 (u2-uu (0-, t))x=f (x, u (0-, t)), x > 0, t < 0. It describes a detonation shock at x = 0 with the reaction zone in x > 0. We investigate the nature of the steady-state solutions of this nonlocal hyperbolic balance law, the linear stability of these solutions, and the nonlinear dynamics. We establish the existence of instability followed by a cascade of period-doubling bifurcations leading to chaos. © 2014 Society for Industrial and Applied Mathematics.
Hydrodynamic Burnett equations for inelastic Maxwell models of granular gases
Khalil, Nagi; Garzó, Vicente; Santos, Andrés
2014-05-01
The hydrodynamic Burnett equations and the associated transport coefficients are exactly evaluated for generalized inelastic Maxwell models. In those models, the one-particle distribution function obeys the inelastic Boltzmann equation, with a velocity-independent collision rate proportional to the γ power of the temperature. The pressure tensor and the heat flux are obtained to second order in the spatial gradients of the hydrodynamic fields with explicit expressions for all the Burnett transport coefficients as functions of γ, the coefficient of normal restitution, and the dimensionality of the system. Some transport coefficients that are related in a simple way in the elastic limit become decoupled in the inelastic case. As a byproduct, existing results in the literature for three-dimensional elastic systems are recovered, and a generalization to any dimension of the system is given. The structure of the present results is used to estimate the Burnett coefficients for inelastic hard spheres.
Modeling tree crown dynamics with 3D partial differential equations.
Beyer, Robert; Letort, Véronique; Cournède, Paul-Henry
2014-01-01
We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth toward light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.
Modeling Tree Crown Dynamics with 3D Partial Differential Equations
Robert eBeyer
2014-07-01
Full Text Available We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth towards light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.
Multiple Group Analysis in Multilevel Structural Equation Model Across Level 1 Groups.
Ryu, Ehri
2015-01-01
This article introduces and evaluates a procedure for conducting multiple group analysis in multilevel structural equation model across Level 1 groups (MG1-MSEM; Ryu, 2014). When group membership is at Level 1, multiple group analysis raises two issues that cannot be solved by a simple extension of the standard multiple group analysis in single-level structural equation model. First, the Level 2 data are not independent between Level 1 groups. Second, the standard procedure fails to take into account the dependency between members of different Level 1 groups within the same cluster. The MG1-MSEM approach provides solutions to these problems. In MG1-MSEM, the Level 1 mean structure is necessary to represent the differences between Level 1 groups within clusters. The Level 2 model is the same regardless of Level 1 group membership. A simulation study examined the performance of MUML (Muthén's maximum likelihood) estimation in MG1-MSEM. The MG1-MSEM approach is illustrated for both a multilevel path model and a multilevel factor model using empirical data sets.
Hojka, Vladimir; Stastny, Petr; Rehak, Tomas; Gołas, Artur; Mostowik, Aleksandra; Zawart, Marek; Musálek, Martin
2016-09-01
While tests of basic motor abilities such as speed, maximum strength or endurance are well recognized, testing of complex motor functions such as agility remains unresolved in current literature. Therefore, the aim of this review was to evaluate which main factor or factor structures quantitatively determine agility. In methodological detail, this review focused on research that explained or described the relationships between latent variables in a factorial model of agility using approaches such as principal component analysis, factor analysis and structural equation modeling. Four research studies met the defined inclusion criteria. No quantitative empirical research was found that tried to verify the quality of the whole suggested model of the main factors determining agility through the use of a structural equation modeling (SEM) approach or a confirmatory factor analysis. From the whole structure of agility, only change of direction speed (CODS) and some of its subtests were appropriately analyzed. The combination of common CODS tests is reliable and useful to estimate performance in sub-elite athletes; however, for elite athletes, CODS tests must be specific to the needs of a particular sport discipline. Sprinting and jumping tests are stronger factors for CODS than explosive strength and maximum strength tests. The authors suggest the need to verify the agility factorial model by a second generation data analysis technique such as SEM.
Tropospheric Refraction Modeling Using Ray-Tracing and Parabolic Equation
P. Pechac
2005-12-01
Full Text Available Refraction phenomena that occur in the lower atmospheresignificantly influence the performance of wireless communicationsystems. This paper provides an overview of corresponding computationalmethods. Basic properties of the lower atmosphere are mentioned.Practical guidelines for radiowave propagation modeling in the loweratmosphere using ray-tracing and parabolic equation methods are given.In addition, a calculation of angle-of-arrival spectra is introducedfor multipath propagation simulations.
Structural Equation Modeling with Lisrel: An Initial Vision
Naresh K Malhotra
2014-05-01
Full Text Available LISREL is considered one of the most robust software packages for Structural Equation Modeling with covariance matrices, while it is also considered complex and difficult to use. In this special issue of the Brazilian Journal of Marketing, we aim to present the main functions of LISREL, its features and, through a didactic example, reduce the perceived difficulty of using it. We also provide helpful guidelines to properly using this technique.
Empirical Evaluation of a Mathematical Model of Ethnolinguistic Vitality: The Case of Voro
Ehala, Martin; Niglas, Katrin
2007-01-01
The paper presents the results of an empirical evaluation of a mathematical model of ethnolinguistic vitality. The model adds several new factors to the set used in previous models of ethnolinguistic vitality and operationalises it in a manner that would make it easier to compare the vitality of different groups. According to the model, the…
Stochastic Differential Equation-Based Flexible Software Reliability Growth Model
P. K. Kapur
2009-01-01
Full Text Available Several software reliability growth models (SRGMs have been developed by software developers in tracking and measuring the growth of reliability. As the size of software system is large and the number of faults detected during the testing phase becomes large, so the change of the number of faults that are detected and removed through each debugging becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. In such a situation, we can model the software fault detection process as a stochastic process with continuous state space. In this paper, we propose a new software reliability growth model based on Itô type of stochastic differential equation. We consider an SDE-based generalized Erlang model with logistic error detection function. The model is estimated and validated on real-life data sets cited in literature to show its flexibility. The proposed model integrated with the concept of stochastic differential equation performs comparatively better than the existing NHPP-based models.
Extended master equation models for molecular communication networks.
Chou, Chun Tung
2013-06-01
We consider molecular communication networks consisting of transmitters and receivers distributed in a fluidic medium. In such networks, a transmitter sends one or more signaling molecules, which are diffused over the medium, to the receiver to realize the communication. In order to be able to engineer synthetic molecular communication networks, mathematical models for these networks are required. This paper proposes a new stochastic model for molecular communication networks called reaction-diffusion master equation with exogenous input (RDMEX). The key idea behind RDMEX is to model the transmitters as time series of signaling molecule counts, while diffusion in the medium and chemical reactions at the receivers are modeled as Markov processes using master equation. An advantage of RDMEX is that it can readily be used to model molecular communication networks with multiple transmitters and receivers. For the case where the reaction kinetics at the receivers is linear, we show how RDMEX can be used to determine the mean and covariance of the receiver output signals, and derive closed-form expressions for the mean receiver output signal of the RDMEX model. These closed-form expressions reveal that the output signal of a receiver can be affected by the presence of other receivers. Numerical examples are provided to demonstrate the properties of the model.
Moment equations and dynamics of a household SIS epidemiological model.
Hiebeler, David
2006-08-01
An SIS epidemiological model of individuals partitioned into households is studied, where infections take place either within or between households, the latter generally happening much less frequently. The model is explored using stochastic spatial simulations, as well as mathematical models which consist of an infinite system of ordinary differential equations for the moments of the distribution describing the proportions of individuals who are infectious among households. Various moment-closure approximations are used to truncate the system of ODEs to finite systems of equations. These approximations can sometimes lead to a system of ill-behaved ODEs which predict moments which become negative or unbounded. A reparametrization of the ODEs is then developed, which forces all moments to satisfy necessary constraints. Changing the proportion of contacts within and between households does not change the endemic equilibrium, but does affect the amount of time it takes to approach the fixed point; increasing the proportion of contacts within households slows the spread of the infection toward endemic equilibrium. The system of moment equations does describe this phenomenon, although less accurately in the limit as the proportion of between-household contacts approaches zero. The results indicate that although controlling the movement of individuals does not affect the long-term frequency of an infection with SIS dynamics, it can have a large effect on the time-scale of the dynamics, which may provide an opportunity for other controls such as immunizations to be applied.
Temporal structure of neuronal population oscillations with empirical model decomposition
Li, Xiaoli
2006-08-01
Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.
Empirical modeling and data analysis for engineers and applied scientists
Pardo, Scott A
2016-01-01
This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions. While science is about discovery, the primary paradigm of engineering and "applied science" is design. Scientists are in the discovery business and want, in general, to understand the natural world rather than to alter it. In contrast, engineers and applied scientists design products, processes, and solutions to problems. That said, statistics, as a discipline, is mostly oriented toward the discovery paradigm. Young engineers come out of their degree programs having taken courses such as "Statistics for Engineers and Scientists" without any clear idea as to how they can use statistical methods to help them design products or processes. Many seem to think that statistics is only useful for demonstrating that a device or process actually does what it was designed to do. Statistics courses emphasize creati...
Partial Least Squares Structural Equation Modeling with R
Hamdollah Ravand
2016-09-01
Full Text Available Structural equation modeling (SEM has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and restrictions (e.g. normality and relatively large sample sizes that could discourage practitioners from applying the model. Partial least squares SEM (PLS-SEM is a nonparametric technique which makes no distributional assumptions and can be estimated with small sample sizes. In this paper a general introduction to PLS-SEM is given and is compared with conventional SEM. Next, step by step procedures, along with R functions, are presented to estimate the model. A data set is analyzed and the outputs are interpreted
semPLS: Structural Equation Modeling Using Partial Least Squares
Armin Monecke
2012-05-01
Full Text Available Structural equation models (SEM are very popular in many disciplines. The partial least squares (PLS approach to SEM offers an alternative to covariance-based SEM, which is especially suited for situations when data is not normally distributed. PLS path modelling is referred to as soft-modeling-technique with minimum demands regarding mea- surement scales, sample sizes and residual distributions. The semPLS package provides the capability to estimate PLS path models within the R programming environment. Different setups for the estimation of factor scores can be used. Furthermore it contains modular methods for computation of bootstrap confidence intervals, model parameters and several quality indices. Various plot functions help to evaluate the model. The well known mobile phone dataset from marketing research is used to demonstrate the features of the package.
González, B. Jorge; von Davier, Matthias
2013-01-01
Based on Lord's criterion of equity of equating, van der Linden (this issue) revisits the so-called local equating method and offers alternative as well as new thoughts on several topics including the types of transformations, symmetry, reliability, and population invariance appropriate for equating. A remarkable aspect is to define equating…
Optimizing irrigation and nitrogen for wheat through empirical modeling under semi-arid environment.
Saeed, Umer; Wajid, Syed Aftab; Khaliq, Tasneem; Zahir, Zahir Ahmad
2017-04-01
Nitrogen fertilizer availability to plants is strongly linked with water availability. Excessive or insufficient use of nitrogen can cause reduction in grain yield of wheat and environmental issues. The per capita per annum water availability in Pakistan has reduced to less than 1000 m(3) and is expected to reach 800 m(3) during 2025. Irrigating crops with 3 or more than 3 in. of depth without measuring volume of water is not a feasible option anymore. Water productivity and economic return of grain yield can be improved by efficient management of water and nitrogen fertilizer. A study was conducted at post-graduate agricultural research station, University of Agriculture Faisalabad, during 2012-2013 and 2013-2014 to optimize volume of water per irrigation and nitrogen application. Split plot design with three replications was used to conduct experiment; four irrigation levels (I300 = 300 mm, I240 = 240 mm, I180 = 180 mm, I120 = 120 mm for whole growing season at critical growth stages) and four nitrogen levels (N60 = 60 kg ha(-1), N120 = 120 kg ha(-1), N180 = 180 kg ha(-1), and N240 = 240 kg ha(-1)) were randomized as main and sub-plot factors, respectively. The recorded data on grain yield was used to develop empirical regression models. The results based on quadratic equations and economic analysis showed 164, 162, 158, and 107 kg ha(-1) nitrogen as economic optimum with I300, I240, I180, and I120 mm water, respectively, during 2012-2013. During 2013-2014, quadratic equations and economic analysis showed 165, 162, 161, and 117 kg ha(-1) nitrogen as economic optimum with I300, I240, I180, and I120 mm water, respectively. The optimum irrigation level was obtained by fitting economic optimum nitrogen as function of total water. Equations predicted 253 mm as optimum irrigation water for whole growing season during 2012-2013 and 256 mm water as optimum for 2013-2014. The results also revealed that reducing irrigation from I300 to
Vertical spectral representation in primitive equation models of the atmosphere
Mizzi, A.; Tribbia, J. [National Center for Atmospheric Research, Boulder, CO (United States); Curry, J. [Univ. of Colorado, Boulder, CO (United States)
1995-08-01
Attempts to represent the vertical structure in primitive equation models of the atmosphere with the spectral method have been unsuccessful to date. Linear stability analysis showed that small time steps were required for computational stability near the upper boundary with a vertical spectral representation and found it necessary to use an artificial constraint to force temperature to zero when pressure was zero to control the upper-level horizontal velocities. This ad hoc correction is undesirable, and an analysis that shows such a correction is unnecessary is presented. By formulating the model in terms of velocity and geopotential and then using the hydrostatic equation to calculate temperature from geopotential, temperature is necessarily zero when pressure is zero. The authors applied this technique to the dry-adiabatic primitive equations on the equatorial {beta} and tropical f planes. Vertical and horizontal normal modes were used as the spectral basis functions. The vertical modes are based on vertical normal modes, and the horizontal modes are normal modes for the primitive equations on a {beta} or f plane. The results show that the upper-level velocities do not necessarily increase, total energy is conserved, and kinetic energy is bounded. The authors found an upper-level temporal oscillation in the horizontal domain integral of the horizontal velocity components that is related to mass and velocity field imbalances in the initial conditions or introduced during the integration. Through nonlinear normal-mode initialization, the authors effectively removed the initial condition imbalance and reduced the amplitude of this oscillation. It is hypothesized that the vertical spectral representation makes the model more sensitive to initial condition imbalances, or it introduces imbalance during the integration through vertical spectral truncation. 20 refs., 12 figs.
Modeling Inflation Using a Non-Equilibrium Equation of Exchange
Chamberlain, Robert G.
2013-01-01
Inflation is a change in the prices of goods that takes place without changes in the actual values of those goods. The Equation of Exchange, formulated clearly in a seminal paper by Irving Fisher in 1911, establishes an equilibrium relationship between the price index P (also known as "inflation"), the economy's aggregate output Q (also known as "the real gross domestic product"), the amount of money available for spending M (also known as "the money supply"), and the rate at which money is reused V (also known as "the velocity of circulation of money"). This paper offers first a qualitative discussion of what can cause these factors to change and how those causes might be controlled, then develops a quantitative model of inflation based on a non-equilibrium version of the Equation of Exchange. Causal relationships are different from equations in that the effects of changes in the causal variables take time to play out-often significant amounts of time. In the model described here, wages track prices, but only after a distributed lag. Prices change whenever the money supply, aggregate output, or the velocity of circulation of money change, but only after a distributed lag. Similarly, the money supply depends on the supplies of domestic and foreign money, which depend on the monetary base and a variety of foreign transactions, respectively. The spreading of delays mitigates the shocks of sudden changes to important inputs, but the most important aspect of this model is that delays, which often have dramatic consequences in dynamic systems, are explicitly incorporated.macroeconomics, inflation, equation of exchange, non-equilibrium, Athena Project
Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging
Naoya Sueishi
2013-07-01
Full Text Available This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a correct model, for estimating a specific parameter of interest. Then, this study investigates a generalized empirical likelihood-based model averaging estimator that minimizes the asymptotic mean squared error. A simulation study suggests that our averaging estimator can be a useful alternative to existing post-selection estimators.
The Interface Between Theory and Data in Structural Equation Models
Grace, James B.; Bollen, Kenneth A.
2006-01-01
Structural equation modeling (SEM) holds the promise of providing natural scientists the capacity to evaluate complex multivariate hypotheses about ecological systems. Building on its predecessors, path analysis and factor analysis, SEM allows for the incorporation of both observed and unobserved (latent) variables into theoretically based probabilistic models. In this paper we discuss the interface between theory and data in SEM and the use of an additional variable type, the composite, for representing general concepts. In simple terms, composite variables specify the influences of collections of other variables and can be helpful in modeling general relationships of the sort commonly of interest to ecologists. While long recognized as a potentially important element of SEM, composite variables have received very limited use, in part because of a lack of theoretical consideration, but also because of difficulties that arise in parameter estimation when using conventional solution procedures. In this paper we present a framework for discussing composites and demonstrate how the use of partially reduced form models can help to overcome some of the parameter estimation and evaluation problems associated with models containing composites. Diagnostic procedures for evaluating the most appropriate and effective use of composites are illustrated with an example from the ecological literature. It is argued that an ability to incorporate composite variables into structural equation models may be particularly valuable in the study of natural systems, where concepts are frequently multifaceted and the influences of suites of variables are often of interest.
焉石
2015-01-01
为了探讨和比较中、韩短道速滑教练员领导行为与运动员意志品质间的关系，采用AMOS结构方程模型并利用《运动领导行为量表》（Chelladurai）和《BTL-L-YZ2.0运动员意志品质量表》（李佑发）分别对中国88名、韩国81名短道速滑运动员进行了心理测量。结果表明，中国方面，教练员的训练指导行为和奖励行为对运动员的自觉性具有显著正向影响；民主行为对运动员独立性具有显著正向影响；训练指导行为对运动员坚韧性具有显著正向影响。而韩国方面，教练员唯独专制行为对运动员的自觉性、果断性及坚韧性具有显著负向影响。通过比较提示我们，教练员领导行为对运动员意志品质形成具有影响作用，而且不同文化背景下，针对提高运动员的意志品质，教练员应该采取与该文化背景相适宜的领导行为，对提升我国短道速滑运动员意志品质具有理论意义和实践意义。%In order to study and compare the relation between Chinese and Korean speed-skating coaches' leader behaviors and the volitional qualtiy of athletes,with the AMOS structural equation model,and by using“Athletic Leader Behaviors Scale”(Chelladurai) and“BTL-L-YZ2.0 Volitional Quality of Athletes Scale”(Li Youfa),88 Chinese speed skaters and 81 Korean speed skaters are carroed out psychological measurements. The results show that in China,the leader behaviors and rewarding behaviors for training of speed skating coaches have a significant positive influence on the self-consciousness of athletes. Democratic behaviors have a significant positive influence on independence of athletes. In Korea, autocratic behaviors have significant negative effects on on the athletes' self-consciousness,decisiveness and tenacity. By comparison,it is noticed that leader behaviors of coaches play a role in the fomation of volitional quality of athletes. And in different cutural
Fisher, Monica A.; Taylor, George W.; West, Brady T.; McCarthy, Ellen T.
2011-01-01
Periodontal disease is associated with diabetes, heart disease, and chronic kidney disease (CKD), an effect postulated to be due in part to endovascular inflammation. While a bidirectional relationship between CKD and periodontal disease is plausible, it has not been previously reported in the literature. Over 11 200 adults 18 years or older were identified in the Third National Health and Nutrition Examination Survey. Analyses were conducted in two stages. First, multivariable logistic regression models were fitted to test the hypothesis that periodontal disease was independently associated with CKD. Given the potential that the periodontal disease and CKD relationship may be bidirectional, a two-step analytic approach was used that involved 1) tests for mediation, and 2) structural equation models to examine more complex direct and indirect effects of periodontal disease on CKD, and vice versa. In two separate models periodontal disease (ORAdj =1.62 (95% CI: 1.17-2.26) and edentulism (ORAdj = 1.83 (1.31-2.55) and periodontal disease score (ORAdj = 1.01 (1.01-1.02) were associated with CKD, when simultaneously adjusting for 14 other factors. Three of four structural equation models were most plausible suggesting bidirectional relationships. Collectively, these analyses provide for the first time empirical support for a bidirectional relationship between CKD and periodontal disease, and mediation of that relationship by diabetes duration and hypertension. PMID:20927035
An integral equation model for warm and hot dense mixtures
Starrett, C E; Daligault, J; Hamel, S
2014-01-01
In Starrett and Saumon [Phys. Rev. E 87, 013104 (2013)] a model for the calculation of electronic and ionic structures of warm and hot dense matter was described and validated. In that model the electronic structure of one "atom" in a plasma is determined using a density functional theory based average-atom (AA) model, and the ionic structure is determined by coupling the AA model to integral equations governing the fluid structure. That model was for plasmas with one nuclear species only. Here we extend it to treat plasmas with many nuclear species, i.e. mixtures, and apply it to a carbon-hydrogen mixture relevant to inertial confinement fusion experiments. Comparison of the predicted electronic and ionic structures with orbital-free and Kohn-Sham molecular dynamics simulations reveals excellent agreement wherever chemical bonding is not significant.
Coarse Analysis of Microscopic Models using Equation-Free Methods
Marschler, Christian
-dimensional models. The goal of this thesis is to investigate such high-dimensional multiscale models and extract relevant low-dimensional information from them. Recently developed mathematical tools allow to reach this goal: a combination of so-called equation-free methods with numerical bifurcation analysis....... Applications include the learning behavior in the barn owl’s auditory system, traffic jam formation in an optimal velocity model for circular car traffic and oscillating behavior of pedestrian groups in a counter-flow through a corridor with narrow door. The methods do not only quantify interesting properties...... factor for the complexity of models, e.g., in real-time applications. With the increasing amount of data generated by computer simulations a challenge is to extract valuable information from the models in order to help scientists and managers in a decision-making process. Although the dynamics...
Structural Equation Modeling: Theory and Applications in Forest Management
Tzeng Yih Lam
2012-01-01
Full Text Available Forest ecosystem dynamics are driven by a complex array of simultaneous cause-and-effect relationships. Understanding this complex web requires specialized analytical techniques such as Structural Equation Modeling (SEM. The SEM framework and implementation steps are outlined in this study, and we then demonstrate the technique by application to overstory-understory relationships in mature Douglas-fir forests in the northwestern USA. A SEM model was formulated with (1 a path model representing the effects of successively higher layers of vegetation on late-seral herbs through processes such as light attenuation and (2 a measurement model accounting for measurement errors. The fitted SEM model suggested a direct negative effect of light attenuation on late-seral herbs cover but a direct positive effect of northern aspect. Moreover, many processes have indirect effects mediated through midstory vegetation. SEM is recommended as a forest management tool for designing silvicultural treatments and systems for attaining complex arrays of management objectives.
Cause and cure of sloppiness in ordinary differential equation models.
Tönsing, Christian; Timmer, Jens; Kreutz, Clemens
2014-08-01
Data-based mathematical modeling of biochemical reaction networks, e.g., by nonlinear ordinary differential equation (ODE) models, has been successfully applied. In this context, parameter estimation and uncertainty analysis is a major task in order to assess the quality of the description of the system by the model. Recently, a broadened eigenvalue spectrum of the Hessian matrix of the objective function covering orders of magnitudes was observed and has been termed as sloppiness. In this work, we investigate the origin of sloppiness from structures in the sensitivity matrix arising from the properties of the model topology and the experimental design. Furthermore, we present strategies using optimal experimental design methods in order to circumvent the sloppiness issue and present nonsloppy designs for a benchmark model.
Structural equation models of VMT growth in US urbanised areas.
Ewing, Reid; Hamidi, Shima; Gallivan, Frank; Nelson, Arthur C.; Grace, James B.
2014-01-01
Vehicle miles travelled (VMT) is a primary performance indicator for land use and transportation, bringing with it both positive and negative externalities. This study updates and refines previous work on VMT in urbanised areas, using recent data, additional metrics and structural equation modelling (SEM). In a cross-sectional model for 2010, population, income and freeway capacity are positively related to VMT, while gasoline prices, development density and transit service levels are negatively related. Findings of the cross-sectional model are generally confirmed in a more tightly controlled longitudinal study of changes in VMT between 2000 and 2010, the first model of its kind. The cross-sectional and longitudinal models together, plus the transportation literature generally, give us a basis for generalising across studies to arrive at elasticity values of VMT with respect to different urban variables.
Linsky, Jeffrey; Fontenla, Juan; France, Kevin
2016-05-01
We present a semi-empirical model of the photosphere, chromosphere, transition region, and corona for the M2 dwarf star GJ832, which hosts two exoplanets. The atmospheric model uses a modification of the Solar Radiation Physical Modeling tools developed by Fontenla and collaborators. These computer codes model non-LTE spectral line formation for 52 atoms and ions and include a large number of lines from 20 abundant diatomic molecules that are present in the much cooler photosphere and chromosphere of this star. We constructed the temperature distribution to fit Hubble Space Telescope observations of chromospheric lines (e.g., MgII), transition region lines (CII, CIV, SiIV, and NV), and the UV continuum. Temperatures in the coronal portion of the model are consistent with ROSAT and XMM-Newton X-ray observations and the FeXII 124.2 nm line. The excellent fit of the model to the data demonstrates that the highly developed model atmosphere code developed to explain regions of the solar atmosphere with different activity levels has wide applicability to stars, including this M star with an effective temperature 2200 K cooler than the Sun. We describe similarities and differences between the M star model and models of the quiet and active Sun.
Calculus for cognitive scientists partial differential equation models
Peterson, James K
2016-01-01
This book shows cognitive scientists in training how mathematics, computer science and science can be usefully and seamlessly intertwined. It is a follow-up to the first two volumes on mathematics for cognitive scientists, and includes the mathematics and computational tools needed to understand how to compute the terms in the Fourier series expansions that solve the cable equation. The latter is derived from first principles by going back to cellular biology and the relevant biophysics. A detailed discussion of ion movement through cellular membranes, and an explanation of how the equations that govern such ion movement leading to the standard transient cable equation are included. There are also solutions for the cable model using separation of variables, as well an explanation of why Fourier series converge and a description of the implementation of MatLab tools to compute the solutions. Finally, the standard Hodgkin - Huxley model is developed for an excitable neuron and is solved using MatLab.
An improved shallow water equation model for water animation
Ai, Mingjing; Du, Anding; Xu, Han; Niu, Jianwei
2017-03-01
In this paper, we proposed a new scheme for simulating water flows under shallow water assumption. The method is an extension of traditional shallow water equations. In contrast to traditional methods, we design a dynamic coordinate system for modeling in order to efficiently simulate water flows. Within this system, we derive our specialized shallow water equations directly from the Navier-Stockes equation. At the same time, we develop an implicit mechanism for solving the advection term and a vector projection operator for solving the external forces acting on water. We also present a two-way coupling method for simulating the interaction between water and rigid solid. The experimental results show that the proposed scheme can achieve a more realistic and accurate water model compared with the traditional methods, especially when the solid surfaces are too steep. Also we demonstrate the efficiency of our method in several scenes, all run at least 50 frames per second on average which allows real-time simulation.
Application of Stochastic Partial Differential Equations to Reservoir Property Modelling
Potsepaev, R.
2010-09-06
Existing algorithms of geostatistics for stochastic modelling of reservoir parameters require a mapping (the \\'uvt-transform\\') into the parametric space and reconstruction of a stratigraphic co-ordinate system. The parametric space can be considered to represent a pre-deformed and pre-faulted depositional environment. Existing approximations of this mapping in many cases cause significant distortions to the correlation distances. In this work we propose a coordinate free approach for modelling stochastic textures through the application of stochastic partial differential equations. By avoiding the construction of a uvt-transform and stratigraphic coordinates, one can generate realizations directly in the physical space in the presence of deformations and faults. In particular the solution of the modified Helmholtz equation driven by Gaussian white noise is a zero mean Gaussian stationary random field with exponential correlation function (in 3-D). This equation can be used to generate realizations in parametric space. In order to sample in physical space we introduce a stochastic elliptic PDE with tensor coefficients, where the tensor is related to correlation anisotropy and its variation is physical space.
Empirical Likelihood for Mixed-effects Error-in-variables Model
Qiu-hua Chen; Ping-shou Zhong; Heng-jian Cui
2009-01-01
This paper mainly introduces the method of empirical likelihood and its applications on two dif-ferent models.We discuss the empirical likelihood inference on fixed-effect parameter in mixed-effects model with error-in-variables.We first consider a linear mixed-effects model with measurement errors in both fixed and random effects.We construct the empirical likelihood confidence regions for the fixed-effects parameters and the mean parameters of random-effects.The limiting distribution of the empirical log likelihood ratio at the true parameter is χ2p+q,where p,q are dimension of fixed and random effects respectively.Then we discuss empirical likelihood inference in a semi-linear error-in-variable mixed-effects model.Under certain conditions,it is shown that the empirical log likelihood ratio at the true parameter also converges to χ2p+q.Simulations illustrate that the proposed confidence region has a coverage probability more closer to the nominal level than normal approximation based confidence region.
Generalized elastic model yields a fractional Langevin equation description.
Taloni, Alessandro; Chechkin, Aleksei; Klafter, Joseph
2010-04-23
Starting from a generalized elastic model which accounts for the stochastic motion of several physical systems such as membranes, (semi)flexible polymers, and fluctuating interfaces among others, we derive the fractional Langevin equation (FLE) for a probe particle in such systems, in the case of thermal initial conditions. We show that this FLE is the only one fulfilling the fluctuation-dissipation relation within a new family of fractional Brownian motion equations. The FLE for the time-dependent fluctuations of the donor-acceptor distance in a protein is shown to be recovered. When the system starts from nonthermal conditions, the corresponding FLE, which does not fulfill the fluctuation-dissipation relation, is derived.
Correlations in a generalized elastic model: fractional Langevin equation approach.
Taloni, Alessandro; Chechkin, Aleksei; Klafter, Joseph
2010-12-01
The generalized elastic model (GEM) provides the evolution equation which governs the stochastic motion of several many-body systems in nature, such as polymers, membranes, and growing interfaces. On the other hand a probe (tracer) particle in these systems performs a fractional Brownian motion due to the spatial interactions with the other system's components. The tracer's anomalous dynamics can be described by a fractional Langevin equation (FLE) with a space-time correlated noise. We demonstrate that the description given in terms of GEM coincides with that furnished by the relative FLE, by showing that the correlation functions of the stochastic field obtained within the FLE framework agree with the corresponding quantities calculated from the GEM. Furthermore we show that the Fox H -function formalism appears to be very convenient to describe the correlation properties within the FLE approach.
Scale invariant cosmology II: model equations and properties
Maeder, Andre
2016-01-01
We want to establish the basic properties of a scale invariant cosmology, that also accounts for the hypothesis of scale invariance of the empty space at large scales. We write the basic analytical properties of the scale invariant cosmological models. The hypothesis of scale invariance of the empty space at large scale brings interesting simplifications in the scale invariant equations for cosmology. There is one new term, depending on the scale factor of the scale invariant cosmology, that opposes to gravity and favours an accelerated expansion. We first consider a zero-density model and find an accelerated expansion, going like t square. In models with matter present, the displacements due to the new term make a significant contribution Omega_l to the energy-density of the Universe, satisfying an equation of the form Omega_m + Omega_k + Omega_l = 1. Unlike the Friedman's models, there is a whole family of flat models (k=0) with different density parameters Omega_m smaller than 1. We examine the basic relat...
Modeling rapid mass movements using the shallow water equations
S. Hergarten
2014-11-01
Full Text Available We propose a new method to model rapid mass movements on complex topography using the shallow water equations in Cartesian coordinates. These equations are the widely used standard approximation for the flow of water in rivers and shallow lakes, but the main prerequisite for their application – an almost horizontal fluid table – is in general not satisfied for avalanches and debris flows in steep terrain. Therefore, we have developed appropriate correction terms for large topographic gradients. In this study we present the mathematical formulation of these correction terms and their implementation in the open source flow solver GERRIS. This novel approach is evaluated by simulating avalanches on synthetic and finally natural topographies and the widely used Voellmy flow resistance law. The results are tested against analytical solutions and the commercial avalanche model RAMMS. The overall results are in excellent agreement with the reference system RAMMS, and the deviations between the different models are far below the uncertainties in the determination of the relevant fluid parameters and involved avalanche volumes in reality. As this code is freely available and open source, it can be easily extended by additional fluid models or source areas, making this model suitable for simulating several types of rapid mass movements. It therefore provides a valuable tool assisting regional scale natural hazard studies.
On an evolution equation in a cell motility model
Mizuhara, Matthew S.; Berlyand, Leonid; Rybalko, Volodymyr; Zhang, Lei
2016-04-01
This paper deals with the evolution equation of a curve obtained as the sharp interface limit of a non-linear system of two reaction-diffusion PDEs. This system was introduced as a phase-field model of (crawling) motion of eukaryotic cells on a substrate. The key issue is the evolution of the cell membrane (interface curve) which involves shape change and net motion. This issue can be addressed both qualitatively and quantitatively by studying the evolution equation of the sharp interface limit for this system. However, this equation is non-linear and non-local and existence of solutions presents a significant analytical challenge. We establish existence of solutions for a wide class of initial data in the so-called subcritical regime. Existence is proved in a two step procedure. First, for smooth (H2) initial data we use a regularization technique. Second, we consider non-smooth initial data that are more relevant from the application point of view. Here, uniform estimates on the time when solutions exist rely on a maximum principle type argument. We also explore the long time behavior of the model using both analytical and numerical tools. We prove the nonexistence of traveling wave solutions with nonzero velocity. Numerical experiments show that presence of non-linearity and asymmetry of the initial curve results in a net motion which distinguishes it from classical volume preserving curvature motion. This is done by developing an algorithm for efficient numerical resolution of the non-local term in the evolution equation.
Institutions and foreign direct investment (FDI) in Malaysia: empirical evidence using ARDL model
Abdul Karim, Zulkefly; Zaidi, Mohd Azlan Shah; Ismail, Mohd Adib; Abdul Karim, Bakri
2011-01-01
Since 1990’s, institution factors have been regarded as playing important roles in stimulating foreign direct investments (FDI). However, empirical studies on their importance in affecting FDI are still lacking especially for small open economies. This paper attempts to investigate the role of institutions upon the inflow of foreign direct investment (FDI) in a small open economy of Malaysia. Using bounds testing approach (ARDL model), the empirical findings reveal that there exists a long ru...
Time-varying disaster risk models: An empirical assessment of the Rietz-Barro hypothesis
Irarrazabal, Alfonso; Parra-Alvarez, Juan Carlos
This paper revisits the fit of disaster risk models where a representative agent has recursive preferences and the probability of a macroeconomic disaster changes over time. We calibrate the model as in Wachter (2013) and perform two sets of tests to assess the empirical performance of the model ...
Zee, van der F.A.
1997-01-01
This study explores the relevance and applicability of political economy models for the explanation of agricultural policies. Part I (chapters 4-7) takes a general perspective and evaluates the empirical applicability of voting models and interest group models to agricultural policy
Zee, van der F.A.
1997-01-01
This study explores the relevance and applicability of political economy models for the explanation of agricultural policies. Part I (chapters 4-7) takes a general perspective and evaluates the empirical applicability of voting models and interest group models to agricultural policy formation in ind
Zee, van der F.A.
1997-01-01
This study explores the relevance and applicability of political economy models for the explanation of agricultural policies. Part I (chapters 4-7) takes a general perspective and evaluates the empirical applicability of voting models and interest group models to agricultural policy formati
Empirical LTE Smartphone Power Model with DRX Operation for System Level Simulations
Lauridsen, Mads; Noël, Laurent; Mogensen, Preben
2013-01-01
An LTE smartphone power model is presented to enable academia and industry to evaluate users’ battery life on system level. The model is based on empirical measurements on a smartphone using a second generation LTE chipset, and the model includes functions of receive and transmit data rates...
Knight, Raymond A; Sims-Knight, Judith E
2003-06-01
A unified model of the origin of sexual aggression against women on both adult and juvenile sexual offender samples has been developed and successfully tested. This model proposed three major causal paths to sexual coercion against women. In the first path, physical and verbal abuse was hypothesized to produce callousness and lack of emotionality, which disinhibited sexual drive and sexual fantasies. These in turn disinhibited hostile sexual fantasies, and led to sexual coercion. In the second causal path, sexual abuse contributed directly to the disinhibition of sexual drive and sexual fantasies, which through hostile sexual fantasies led to sexual coercion. The third path operated through early antisocial behavior, including aggressive acts. It developed as a result of both physical/verbal abuse and callousness/lack of emotion. It in turn directly affected sexual coercion and worked indirectly through the hostile sexual fantasies path. In the present study, the anonymous responses of a group of 168 blue-collar, community males to an inventory (the Multidimensional Assessment of Sex and Aggression) were used in a structural equation model to test the validity of this model. Moreover, this model was pitted against (Malamuth's (1998)) two-path model. Whereas the three-path model had an excellent fit with the data (CFI =.951, RMSEA =.047), the two-path model fit less well (CFI =.857, RMSEA =.079). These results indicate the superiority of the three-path model and suggest that it constitutes a solid, empirically disconfirmable heuristic for the etiology of sexual coercion against women.
Taylor, H. A., Jr.; Mayr, H. G.; Niemann, H. B.; Larson, J.
1985-01-01
In-situ measurements of positive ion composition of the ionosphere of Venus are combined in an empirical model which is a key element for the Venus International Reference Atmosphere (VIRA) model. The ion data are obtained from the Pioneer Venus Orbiter Ion Mass Spectrometer (OIMS) which obtained daily measurements beginning in December 1978 and extending to July 1980 when the uncontrolled rise of satellite periapsis height precluded further measurements in the main body of the ionosphere. For this period, measurements of 12 ion species are sorted into altitude and local time bins with altitude extending from 150 to 1000 km. The model results exhibit the appreciable nightside ionosphere found at Venus, the dominance of atomic oxygen ions in the dayside upper ionosphere and the increase in prominence of atomic oxygen and deuterium ions on the nightside. Short term variations, such as the abrupt changes observed in the ionopause, cannot be represented in the model.
Lucca Botturi
2006-06-01
Full Text Available This paper reports the results of an empirical study that investigated the instructional design process of three teams involved in the development of an e-learning unit. The teams declared they were using the same fast-prototyping design and development model, and were composed of the same roles (although with a different number of SMEs. Results indicate that the design and development model actually informs the activities of the group, but that it is interpreted and adapted by the team for the specific project. Thus, the actual practice model of each team can be regarded as an emergent feature. This analysis delivers insights concerning issues about team communication, shared understanding, individual perspectives and the implementation of prescriptive instructional design models.
Empirical Estimation of Hybrid Model: A Controlled Case Study
Sadaf Un Nisa; M. Rizwan Jameel Qureshi
2012-01-01
Scrum and Extreme Programming (XP) are frequently used models among all agile models whereas Rational Unified Process (RUP) is one of the widely used conventional plan driven software development models. The agile and plan driven approaches both have their own strengths and weaknesses. Although RUP model has certain drawbacks, such as tendency to be over budgeted, slow in adaptation to rapidly changing requirements and reputation of being impractical for small and fast paced projects. XP mode...
An Empirical Comparison of Default Swap Pricing Models
P. Houweling (Patrick); A.C.F. Vorst (Ton)
2002-01-01
textabstractAbstract: In this paper we compare market prices of credit default swaps with model prices. We show that a simple reduced form model with a constant recovery rate outperforms the market practice of directly comparing bonds' credit spreads to default swap premiums. We find that the model
Equation-based model for the stock market
Xavier, Paloma O. C.; Atman, A. P. F.; de Magalhães, A. R. Bosco
2017-09-01
We propose a stock market model which is investigated in the forms of difference and differential equations whose variables correspond to the demand or supply of each agent and to the price. In the model, agents are driven by the behavior of their trust contact network as well by fundamental analysis. By means of the deterministic version of the model, the connection between such drive mechanisms and the price is analyzed: imitation behavior promotes market instability, finitude of resources is associated to stock index stability, and high sensitivity to the fair price provokes price oscillations. Long-range correlations in the price temporal series and heavy-tailed distribution of returns are observed for the version of the model which considers different proposals for stochasticity of microeconomic and macroeconomic origins.
Bayesian structural equation modeling in sport and exercise psychology.
Stenling, Andreas; Ivarsson, Andreas; Johnson, Urban; Lindwall, Magnus
2015-08-01
Bayesian statistics is on the rise in mainstream psychology, but applications in sport and exercise psychology research are scarce. In this article, the foundations of Bayesian analysis are introduced, and we will illustrate how to apply Bayesian structural equation modeling in a sport and exercise psychology setting. More specifically, we contrasted a confirmatory factor analysis on the Sport Motivation Scale II estimated with the most commonly used estimator, maximum likelihood, and a Bayesian approach with weakly informative priors for cross-loadings and correlated residuals. The results indicated that the model with Bayesian estimation and weakly informative priors provided a good fit to the data, whereas the model estimated with a maximum likelihood estimator did not produce a well-fitting model. The reasons for this discrepancy between maximum likelihood and Bayesian estimation are discussed as well as potential advantages and caveats with the Bayesian approach.
Using of Structural Equation Modeling Techniques in Cognitive Levels Validation
Natalija Curkovic
2012-10-01
Full Text Available When constructing knowledge tests, cognitive level is usually one of the dimensions comprising the test specifications with each item assigned to measure a particular level. Recently used taxonomies of the cognitive levels most often represent some modification of the original Bloom’s taxonomy. There are many concerns in current literature about existence of predefined cognitive levels. The aim of this article is to investigate can structural equation modeling techniques confirm existence of different cognitive levels. For the purpose of the research, a Croatian final high-school Mathematics exam was used (N = 9626. Confirmatory factor analysis and structural regression modeling were used to test three different models. Structural equation modeling techniques did not support existence of different cognitive levels in this case. There is more than one possible explanation for that finding. Some other techniques that take into account nonlinear behaviour of the items as well as qualitative techniques might be more useful for the purpose of the cognitive levels validation. Furthermore, it seems that cognitive levels were not efficient descriptors of the items and so improvements are needed in describing the cognitive skills measured by items.
Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling
Price, Larry R.; Laird, Angela R.; Fox, Peter T.; Ingham, Roger J.
2009-01-01
The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a "true" or population path model was then…
Andrews, Benjamin J.
The phenomena of creep and fatigue have each been thoroughly studied. More recently, attempts have been made to predict the damage evolution in engineering materials due to combined creep and fatigue loading, but these formulations have been strictly empirical and have not been used successfully outside of a narrow set of conditions. This work proposes a new creep-fatigue crack growth model based on constitutive creep equations (adjusted to experimental data) and Paris law fatigue crack growth. Predictions from this model are compared to experimental data in two steels: modified 9Cr-1Mo steel and AISI 316L stainless steel. Modified 9Cr-1Mo steel is a high-strength steel used in the construction of pressure vessels and piping for nuclear and conventional power plants, especially for high temperature applications. Creep-fatigue and pure creep experimental data from the literature are compared to model predictions, and they show good agreement. Material constants for the constitutive creep model are obtained for AISI 316L stainless steel, an alloy steel widely used for temperature and corrosion resistance for such components as exhaust manifolds, furnace parts, heat exchangers and jet engine parts. Model predictions are compared to pure creep experimental data, with satisfactory results. Assumptions and constraints inherent in the implementation of the present model are examined. They include: spatial discretization, similitude, plane stress constraint and linear elasticity. It is shown that the implementation of the present model had a non-trivial impact on the model solutions in 316L stainless steel, especially the spatial discretization. Based on these studies, the following conclusions are drawn: 1. The constitutive creep model consistently performs better than the Nikbin, Smith and Webster (NSW) model for predicting creep and creep-fatigue crack extension. 2. Given a database of uniaxial creep test data, a constitutive material model such as the one developed for
Model equation for strongly focused finite-amplitude sound beams
Kamakura; Ishiwata; Matsuda
2000-06-01
A model equation that describes the propagation of sound beams in a fluid is developed using the oblate spheroidal coordinate system. This spheroidal beam equation (SBE) is a parabolic equation and has a specific application to a theoretical prediction on focused, high-frequency beams from a circular aperture. The aperture angle does not have to be small. The theoretical background is basically along the same analytical lines as the composite method (CM) reported previously [B. Ystad and J. Berntsen, Acustica 82, 698-706 (1996)]. Numerical examples are displayed for the amplitudes of sound pressure along and across the beam axis when sinusoidal waves are radiated from the source with uniform amplitude distribution. The primitive approach to linear field analysis is readily extended to the case where harmonic generation in finite-amplitude sound beams becomes significant due to the inherent nonlinearity of the medium. The theory provides the propagation and beam pattern profiles that differ from the CM solution for each harmonic component.
Short guide to direct gravitational field modelling with Hotine's equations
Sebera, Josef; Wagner, Carl A.; Bezděk, Aleš; Klokočník, Jaroslav
2013-03-01
This paper presents a unified approach to the least squares spherical harmonic analysis of the acceleration vector and Eötvös tensor (gravitational gradients) in an arbitrary orientation. The Jacobian matrices are based on Hotine's equations that hold in the Earth-fixed Cartesian frame and do not need any derivatives of the associated Legendre functions. The implementation was confirmed through closed-loop tests in which the simulated input is inverted in the least square sense using the rotated Hotine's equations. The precision achieved is at the level of rounding error with RMS about 10^{-12}{-}10^{-14} m in terms of the height anomaly. The second validation of the linear model is done with help from the standard ellipsoidal correction for the gravity disturbance that can be computed with an analytic expression as well as with the rotated equations. Although the analytic expression for this correction is only of a limited accuracy at the submillimeter level, it was used for an independent validation. Finally, the equivalent of the ellipsoidal correction, called the effect of the normal, has been numerically obtained also for other gravitational functionals and some of their combinations. Most of the numerical investigations are provided up to spherical harmonic degree 70, with degree 80 for the computation time comparison using real GRACE data. The relevant Matlab source codes for the design matrices are provided.
Latent Utility Shocks in a Structural Empirical Asset Pricing Model
Christensen, Bent Jesper; Raahauge, Peter
We consider a random utility extension of the fundamental Lucas (1978) equilibriumasset pricing model. The resulting structural model leads naturally to a likelihoodfunction. We estimate the model using U.S. asset market data from 1871 to2000, using both dividends and earnings as state variables....... We find that current dividendsdo not forecast future utility shocks, whereas current utility shocks do forecastfuture dividends. The estimated structural model produces a sequence of predictedutility shocks which provide better forecasts of future long-horizon stock market returnsthan the classical...... dividend-price ratio.KEYWORDS: Randomutility, asset pricing, maximumlikelihood, structuralmodel,return predictability...
Theoretical and Empirical Review of Asset Pricing Models: A Structural Synthesis
Saban Celik
2012-01-01
Full Text Available The purpose of this paper is to give a comprehensive theoretical review devoted to asset pricing models by emphasizing static and dynamic versions in the line with their empirical investigations. A considerable amount of financial economics literature devoted to the concept of asset pricing and their implications. The main task of asset pricing model can be seen as the way to evaluate the present value of the pay offs or cash flows discounted for risk and time lags. The difficulty coming from discounting process is that the relevant factors that affect the pay offs vary through the time whereas the theoretical framework is still useful to incorporate the changing factors into an asset pricing models. This paper fills the gap in literature by giving a comprehensive review of the models and evaluating the historical stream of empirical investigations in the form of structural empirical review.
Empirical Validation of a Thermal Model of a Complex Roof Including Phase Change Materials
Guichard, Stéphane; Bigot, Dimitri; Malet-Damour, Bruno; Libelle, Teddy; Boyer, Harry
2015-01-01
This paper deals with the empirical validation of a building thermal model using a phase change material (PCM) in a complex roof. A mathematical model dedicated to phase change materials based on the heat apparent capacity method was implemented in a multi-zone building simulation code, the aim being to increase understanding of the thermal behavior of the whole building with PCM technologies. To empirically validate the model, the methodology is based both on numerical and experimental studies. A parametric sensitivity analysis was performed and a set of parameters of the thermal model have been identified for optimization. The use of a generic optimization program called GenOpt coupled to the building simulation code enabled to determine the set of adequate parameters. We first present the empirical validation methodology and main results of previous work. We then give an overview of GenOpt and its coupling with the building simulation code. Finally, once the optimization results are obtained, comparisons o...
Empirical Estimation of Hybrid Model: A Controlled Case Study
Sadaf Un Nisa
2012-07-01
Full Text Available Scrum and Extreme Programming (XP are frequently used models among all agile models whereas Rational Unified Process (RUP is one of the widely used conventional plan driven software development models. The agile and plan driven approaches both have their own strengths and weaknesses. Although RUP model has certain drawbacks, such as tendency to be over budgeted, slow in adaptation to rapidly changing requirements and reputation of being impractical for small and fast paced projects. XP model has certain drawbacks such as weak documentation and poor performance for medium and large development projects. XP has a concrete set of engineering practices that emphasizes on team work where managers, customers and developers are all equal partners in collaborative teams. Scrum is more concerned with the project management. It has seven practices namely Scrum Master, Scrum teams, Product Backlog, Sprint, Sprint Planning Meeting, Daily Scrum Meeting and Sprint Review. Keeping above mentioned context in view, this paper intends to propose a hybrid model naming SPRUP model by combining strengths of Scrum, XP and RUP by eliminating their weaknesses to produce high quality software. The proposed SPRUP model is validated through a controlled case study.
Empirical Analysis of Farm Credit Risk under the Structure Model
Yan, Yan
2009-01-01
The study measures farm credit risk by using farm records collected by Farm Business Farm Management (FBFM) during the period 1995-2004. The study addresses the following questions: (1) whether farm's financial position is fully described by the structure model, (2) what are the determinants of farm capital structure under the structure model, (3)…
Empirical assessment of a threshold model for sylvatic plague
Davis, Stephen; Leirs, Herwig; Viljugrein, H.
2007-01-01
Plague surveillance programmes established in Kazakhstan, Central Asia, during the previous century, have generated large plague archives that have been used to parameterize an abundance threshold model for sylvatic plague in great gerbil (Rhombomys opimus) populations. Here, we assess the model...
Drugs and Crime: An Empirically Based, Interdisciplinary Model
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…
Empirical Analysis of Farm Credit Risk under the Structure Model
Yan, Yan
2009-01-01
The study measures farm credit risk by using farm records collected by Farm Business Farm Management (FBFM) during the period 1995-2004. The study addresses the following questions: (1) whether farm's financial position is fully described by the structure model, (2) what are the determinants of farm capital structure under the structure model, (3)…
Drugs and Crime: An Empirically Based, Interdisciplinary Model
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…
Hybrid modeling and empirical analysis of automobile supply chain network
Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying
2017-05-01
Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.
Partial differential equation models in the socio-economic sciences
Burger, Martin
2014-10-06
Mathematical models based on partial differential equations (PDEs) have become an integral part of quantitative analysis in most branches of science and engineering, recently expanding also towards biomedicine and socio-economic sciences. The application of PDEs in the latter is a promising field, but widely quite open and leading to a variety of novel mathematical challenges. In this introductory article of the Theme Issue, we will provide an overview of the field and its recent boosting topics. Moreover, we will put the contributions to the Theme Issue in an appropriate perspective.
New equation of state models for hydrodynamic applications
Young, David A.; Barbee, Troy W.; Rogers, Forrest J.
1998-07-01
Two new theoretical methods for computing the equation of state of hot, dense matter are discussed. The ab initio phonon theory gives a first-principles calculation of lattice frequencies, which can be used to compare theory and experiment for isothermal and shock compression of solids. The ACTEX dense plasma theory has been improved to allow it to be compared directly with ultrahigh pressure shock data on low-Z materials. The comparisons with experiment are good, suggesting that these models will be useful in generating global EOS tables for hydrodynamic simulations.
New equation of state model for hydrodynamic applications
Young, D.A.; Barbee, T.W. III; Rogers, F.J.
1997-07-01
Two new theoretical methods for computing the equation of state of hot, dense matter are discussed.The ab initio phonon theory gives a first-principles calculation of lattice frequencies, which can be used to compare theory and experiment for isothermal and shock compression of solids. The ACTEX dense plasma theory has been improved to allow it to be compared directly with ultrahigh pressure shock data on low-Z materials. The comparisons with experiment are good, suggesting that these models will be useful in generating global EOS tables for hydrodynamic simulations.
New equation of state models for hydrodynamic applications
Young, D.A.; Barbee, T.W. III; Rogers, F.J. [Physics Department, Lawrence Livermore National Laboratory, Livermore, California 94551 (United States)
1998-07-01
Two new theoretical methods for computing the equation of state of hot, dense matter are discussed. The ab initio phonon theory gives a first-principles calculation of lattice frequencies, which can be used to compare theory and experiment for isothermal and shock compression of solids. The ACTEX dense plasma theory has been improved to allow it to be compared directly with ultrahigh pressure shock data on low-Z materials. The comparisons with experiment are good, suggesting that these models will be useful in generating global EOS tables for hydrodynamic simulations. {copyright} {ital 1998 American Institute of Physics.}
Equation oriented method for Rectisol wash modeling and analysis☆
Ning Gao; Chi Zhai; Wei Sun; Xingyu Zhang
2015-01-01
Rectisol process is more efficient in comparison with other physical or chemical absorption methods for gas pu-rification. To implement a real time simulation of Rectisol process, thermodynamic model and simulation strat-egy are needed. In this paper, a method of modified statistical associated fluid theory with perturbation theory is used to predict thermodynamic behavior of process. As Rectisol process is a highly heat-integrated process with many loops, a method of equation oriented strategy, sequential quadratic programming, is used as the solver and the process converges perfectly. Then analyses are conducted with this simulator.
A mathematical model on fractional Lotka-Volterra equations.
Das, S; Gupta, P K
2011-05-21
The article presents the solutions of Lotka-Volterra equations of fractional-order time derivatives with the help of analytical method of nonlinear problem called the homotopy perturbation method (HPM). By using initial values, the explicit solutions of predator and prey populations for different particular cases have been derived. The numerical solutions show that only a few iterations are needed to obtain accurate approximate solutions. The method performs extremely well in terms of efficiency and simplicity to solve this historical biological model. Copyright © 2011 Elsevier Ltd. All rights reserved.
Integrable Cosmological Models From Higher Dimensional Einstein Equations
Sano, M; Sano, Masakazu; Suzuki, Hisao
2007-01-01
We consider the cosmological models for the higher dimensional spacetime which includes the curvatures of our space as well as the curvatures of the internal space. We find that the condition for the integrability of the cosmological equations is that the total space-time dimensions are D=10 or D=11 which is exactly the conditions for superstrings or M-theory. We obtain analytic solutions with generic initial conditions in the four dimensional Einstein frame and study the accelerating universe when both our space and the internal space have negative curvatures.
Bloch-Redfield equations for modeling light-harvesting complexes.
Jeske, Jan; Ing, David J; Plenio, Martin B; Huelga, Susana F; Cole, Jared H
2015-02-14
We challenge the misconception that Bloch-Redfield equations are a less powerful tool than phenomenological Lindblad equations for modeling exciton transport in photosynthetic complexes. This view predominantly originates from an indiscriminate use of the secular approximation. We provide a detailed description of how to model both coherent oscillations and several types of noise, giving explicit examples. All issues with non-positivity are overcome by a consistent straightforward physical noise model. Herein also lies the strength of the Bloch-Redfield approach because it facilitates the analysis of noise-effects by linking them back to physical parameters of the noise environment. This includes temporal and spatial correlations and the strength and type of interaction between the noise and the system of interest. Finally, we analyze a prototypical dimer system as well as a 7-site Fenna-Matthews-Olson complex in regards to spatial correlation length of the noise, noise strength, temperature, and their connection to the transfer time and transfer probability.
FLEXIBILITY ANALYSIS IN AN INFORMATION ECONOMY: STRUCTURAL EQUATION MODELING
Ricardo da Silva
2006-11-01
Full Text Available This paper analyzes the new concept of flexibility in organizations – of relevance both at micro and macro level. Information Economy (IE modern function is specifically analyzed. The purpose of this paper is not limited to the study of information economy flexibility, but extends its focus to other areas of organization and economic studies, having as reference the proposed model. Although not covering all aspects regarding objectives and hypotheses, results obtained demonstrate that subsequent studies can lead to success experiences, since the models presented are: stability in relation to the deviations presented in the resulting equations; values that are very close to what is desirable for adjustment indexes, factorial loads, t-values, extracted variances and reliability; as well as other necessary aspects for the application of the technique. The approach focuses the analysis of information economy flexibility based on structural equations modeling to serve as reference for the development of adaptation phenomenon studies in relation to structures, strategies and organizational processes, against the environmental dynamics contemporary society is faced with.
Structural Equation Modeling: Applications in ecological and evolutionary biology research
Pugesek, Bruce H.; von Eye, Alexander; Tomer, Adrian
2003-01-01
This book presents an introduction to the methodology of structural equation modeling, illustrates its use, and goes on to argue that it has revolutionary implications for the study of natural systems. A major theme of this book is that we have, up to this point, attempted to study systems primarily using methods (such as the univariate model) that were designed only for considering individual processes. Understanding systems requires the capacity to examine simultaneous influences and responses. Structural equation modeling (SEM) has such capabilities. It also possesses many other traits that add strength to its utility as a means of making scientific progress. In light of the capabilities of SEM, it can be argued that much of ecological theory is currently locked in an immature state that impairs its relevance. It is further argued that the principles of SEM are capable of leading to the development and evaluation of multivariate theories of the sort vitally needed for the conservation of natural systems. Supplementary information can be found at the authors website, http://www.jamesbgrace.com/. Details why multivariate analyses should be used to study ecological systems Exposes unappreciated weakness in many current popular analyses Emphasizes the future methodological developments needed to advance our understanding of ecological systems.
MODELING ORDINARY DIFFERENTIAL EQUATIONS IN MATLAB SIMULINK ®
Ravi Kiran Maddali
2012-07-01
Full Text Available Ordinary differential equations (ODEs play a vital role in engineering problems. They are used to model continuous dynamical systems as initial and boundary value problems. There are several analytical and numerical methods to solve ODEs. Various numerical methods such as Euler’s method, Runge-Kutta method, etc are so popular in solving these ODEs. MATLAB, the language of technical computation developed by mathworks, is gaining importance both in academic and industry as powerful modeling software. SIMULINK®,is a tool in MATLAB for simulating both continuous and discrete dynamical systems. In SIMULINK®, we can simulate the behavior of a system by representing the system in terms of a block diagram with interconnections between the blocks and there by simulate its behavior over certain period of time. The study of ODEs has variety of applications in disciplines like aerospace, electronics, communication, medicine, finance, economics, and physiology. In this article, the technique of modeling and simulation of first order differential equations in SIMULINK, which can be further extended to higher order systems, is discussed.
Stochastic empirical loading and dilution model (SELDM) version 1.0.0
Granato, Gregory E.
2013-01-01
, flows, and loads on receiving waters by storm and by year. Unlike deterministic hydrologic models, SELDM is not calibrated by changing values of input variables to match a historical record of values. Instead, input values for SELDM are based on site characteristics and representative statistics for each hydrologic variable. Thus, SELDM is an empirical model based on data and statistics rather than theoretical physiochemical equations. SELDM is a lumped parameter model because the highway site, the upstream basin, and the lake basin each are represented as a single homogeneous unit. Each of these source areas is represented by average basin properties, and results from SELDM are calculated as point estimates for the site of interest. Use of the lumped parameter approach facilitates rapid specification of model parameters to develop planning-level estimates with available data. The approach allows for parsimony in the required inputs to and outputs from the model and flexibility in the use of the model. For example, SELDM can be used to model runoff from various land covers or land uses by using the highway-site definition as long as representative water quality and impervious-fraction data are available.
Stochastic differential equation model for cerebellar granule cell excitability.
Saarinen, Antti; Linne, Marja-Leena; Yli-Harja, Olli
2008-02-29
Neurons in the brain express intrinsic dynamic behavior which is known to be stochastic in nature. A crucial question in building models of neuronal excitability is how to be able to mimic the dynamic behavior of the biological counterpart accurately and how to perform simulations in the fastest possible way. The well-established Hodgkin-Huxley formalism has formed to a large extent the basis for building biophysically and anatomically detailed models of neurons. However, the deterministic Hodgkin-Huxley formalism does not take into account the stochastic behavior of voltage-dependent ion channels. Ion channel stochasticity is shown to be important in adjusting the transmembrane voltage dynamics at or close to the threshold of action potential firing, at the very least in small neurons. In order to achieve a better understanding of the dynamic behavior of a neuron, a new modeling and simulation approach based on stochastic differential equations and Brownian motion is developed. The basis of the work is a deterministic one-compartmental multi-conductance model of the cerebellar granule cell. This model includes six different types of voltage-dependent conductances described by Hodgkin-Huxley formalism and simple calcium dynamics. A new model for the granule cell is developed by incorporating stochasticity inherently present in the ion channel function into the gating variables of conductances. With the new stochastic model, the irregular electrophysiological activity of an in vitro granule cell is reproduced accurately, with the same parameter values for which the membrane potential of the original deterministic model exhibits regular behavior. The irregular electrophysiological activity includes experimentally observed random subthreshold oscillations, occasional spontaneous spikes, and clusters of action potentials. As a conclusion, the new stochastic differential equation model of the cerebellar granule cell excitability is found to expand the range of dynamics
Simulating sympathetic detonation using the hydrodynamic models and constitutive equations
Kim, Bo Hoon; Kim, Min Sung; Yoh, Jack J. [Dept. of Mechanical and Aerospace Engineering, Seoul National University, Seoul (Korea, Republic of); Sun, Tae Boo [Hanwha Corporation Defense Rand D Center, Daejeon (Korea, Republic of)
2016-12-15
A Sympathetic detonation (SD) is a detonation of an explosive charge by a nearby explosion. Most of times it is unintended while the impact of blast fragments or strong shock waves from the initiating donor explosive is the cause of SD. We investigate the SD of a cylindrical explosive charge (64 % RDX, 20 % Al, 16 % HTPB) contained in a steel casing. The constitutive relations for high explosive are obtained from a thermo-chemical code that provides the size effect data without the rate stick data typically used for building the rate law and equation of state. A full size SD test of eight pallet-packaged artillery shells is performed that provides the pressure data while the hydrodynamic model with proper constitutive relations for reactive materials and the fragmentation model for steel casing is conducted to replicate the experimental findings. The work presents a novel effort to accurately model and reproduce the sympathetic detonation event with a reduced experimental effort.
Differential equations models for interacting wild and transgenic mosquito populations.
Li, Jia
2008-07-01
We formulate and study continuous-time models, based on systems of ordinary differential equations, for interacting wild and transgenic mosquito populations. We assume that the mosquito mating rate is either constant, proportional to total mosquito population size, or has a Holling-II-type functional form. The focus is on the model with the Holling-II-type functional mating rate that incorporates Allee effects, in order to account for mating difficulty when the size of the total mosquito populations is small. We investigate the existence and stability of both boundary and positive equilibria. We show that the Holling-II-type model is the more realistic and, by means of numerical simulations, that it exhibits richer dynamics.
Equation of State of the Two-Dimensional Hubbard Model
Cocchi, Eugenio; Miller, Luke A.; Drewes, Jan H.; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Köhl, Michael
2016-04-01
The subtle interplay between kinetic energy, interactions, and dimensionality challenges our comprehension of strongly correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions 0 ≲U /t ≲20 and temperatures, down to kBT /t =0.63 (2 ) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities, and double occupancies over the whole doping range, and, hence, our results constitute benchmarks for state-of-the-art theoretical approaches.
Computationally efficient statistical differential equation modeling using homogenization
Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.
2013-01-01
Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.
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.
Empirical Study on Deep Learning Models for Question Answering
Yu, Yang; Zhang, Wei; Hang, Chung-Wei; Xiang, Bing; Zhou, Bowen
2015-01-01
In this paper we explore deep learning models with memory component or attention mechanism for question answering task. We combine and compare three models, Neural Machine Translation, Neural Turing Machine, and Memory Networks for a simulated QA data set. This paper is the first one that uses Neural Machine Translation and Neural Turing Machines for solving QA tasks. Our results suggest that the combination of attention and memory have potential to solve certain QA problem.
Empirical modelling of NO{sub x} emissions
Pedersen, L.S.; Lans, R. van der; Glarborg, P.; Dam-Johansen, K. [Technical University of Denmark Lyngby (Denmark). Dept. of Chemical Engineering
1998-12-31
The applicability of predicting nitrogen oxide emissions and burnout from swirling pulverised coal flames using ideal chemical reactors was investigated. The flow pattern inside the furnace was modified as was the mixing between the combustion air and the fuel inside the reactors using a first order reaction for dissolution of air into the combustion zone. Devolatilisation is assumed to occur much faster than char combustion, with HCN as the primary volatile fuel nitrogen product. Char oxidation is modelled by a single film model with changing particle size and density. Oxidation of HCN is modelled with two reaction channels. The temperature is input from measurements. The model was verified against experimental data obtained from the cylindrical, 5 meter long and 0.5 m diameter Mitsui Babcock Energy Ltd., test-rig (160 kW{sub th}) for a Colombian, a Polish and a South African coal. The model was able to predict the NO concentration and carbon in ash reasonably well, and could predict relative differences in NO concentrations between the three coals. However, the simple reaction mechanism for the formation of NO from HCN fails at a primary stoichiometry below 0.9 for staged combustion. A short sensitivity analysis was performed for the most important parameters, which showed that the model is sensitive towards the particle size distribution. Although the model has only been tested against the small scale test-rig, the data have been compared with full scale tests conducted by ELSAM in Denmark with the same coals. In these tests NO emissions varied but the relative differences between the coals were identical. This means that the model can indirectly predict the NO emissions, depending on coal type, from the full scale power stations. 23 refs., 20 figs., 6 tabs.
An Empirical Comparison of Probability Models for Dependency Grammar
Eisner, J
1997-01-01
This technical report is an appendix to Eisner (1996): it gives superior experimental results that were reported only in the talk version of that paper. Eisner (1996) trained three probability models on a small set of about 4,000 conjunction-free, dependency-grammar parses derived from the Wall Street Journal section of the Penn Treebank, and then evaluated the models on a held-out test set, using a novel O(n^3) parsing algorithm. The present paper describes some details of the experiments and repeats them with a larger training set of 25,000 sentences. As reported at the talk, the more extensive training yields greatly improved performance. Nearly half the sentences are parsed with no misattachments; two-thirds are parsed with at most one misattachment. Of the models described in the original written paper, the best score is still obtained with the generative (top-down) "model C." However, slightly better models are also explored, in particular, two variants on the comprehension (bottom-up) "model B." The be...
The example of modeling of logistics processes using differential equations
Ryczyński, Jacek
2017-07-01
The article describes the use of differential calculus to determine the form of differential equations family of curves. Form of differential equations obtained by eliminating the parameters of the equations describing the different family of curves. Elimination of the parameters has been performed several times by differentiation starting equations. Received appropriate form of differential equations for the case of family circles, family of curves of the second degree and the families of the logistic function.
Evaluation of Regression Models of Balance Calibration Data Using an Empirical Criterion
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.
Ramlall, Indranarain
2016-01-01
This book explains in a rigorous, concise and practical manner all the vital components embedded in structural equation modelling. Focusing on R and stata to implement and perform various structural equation models.
Libor and Swap Market Models for the Pricing of Interest Rate Derivatives : An Empirical Analysis
de Jong, F.C.J.M.; Driessen, J.J.A.G.; Pelsser, A.
2000-01-01
In this paper we empirically analyze and compare the Libor and Swap Market Models, developed by Brace, Gatarek, and Musiela (1997) and Jamshidian (1997), using paneldata on prices of US caplets and swaptions.A Libor Market Model can directly be calibrated to observed prices of caplets, whereas a
Empirical modeling of soot formation in shock-tube pyrolysis of aromatic hydrocarbons
Frenklach, M.; Clary, D. W.; Matula, R. A.
1986-01-01
A method for empirical modeling of soot formation during shock-tube pyrolysis of aromatic hydrocarbons is developed. The method is demonstrated using data obtained in pyrolysis of argon-diluted mixtures of toluene behind reflected shock waves. The developed model is in good agreement with experiment.
Computer Model of the Empirical Knowledge of Physics Formation: Coordination with Testing Results
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…
An Empirically Based Method of Q-Matrix Validation for the DINA Model: Development and Applications
de la Torre, Jimmy
2008-01-01
Most model fit analyses in cognitive diagnosis assume that a Q matrix is correct after it has been constructed, without verifying its appropriateness. Consequently, any model misfit attributable to the Q matrix cannot be addressed and remedied. To address this concern, this paper proposes an empirically based method of validating a Q matrix used…
A stochastic differential equation model of diurnal cortisol patterns
Brown, E. N.; Meehan, P. M.; Dempster, A. P.
2001-01-01
Circadian modulation of episodic bursts is recognized as the normal physiological pattern of diurnal variation in plasma cortisol levels. The primary physiological factors underlying these diurnal patterns are the ultradian timing of secretory events, circadian modulation of the amplitude of secretory events, infusion of the hormone from the adrenal gland into the plasma, and clearance of the hormone from the plasma by the liver. Each measured plasma cortisol level has an error arising from the cortisol immunoassay. We demonstrate that all of these three physiological principles can be succinctly summarized in a single stochastic differential equation plus measurement error model and show that physiologically consistent ranges of the model parameters can be determined from published reports. We summarize the model parameters in terms of the multivariate Gaussian probability density and establish the plausibility of the model with a series of simulation studies. Our framework makes possible a sensitivity analysis in which all model parameters are allowed to vary simultaneously. The model offers an approach for simultaneously representing cortisol's ultradian, circadian, and kinetic properties. Our modeling paradigm provides a framework for simulation studies and data analysis that should be readily adaptable to the analysis of other endocrine hormone systems.
Empirical slip and viscosity model performance for microscale gas flows.
Gallis, Michail A.; Boyd, Iain D. (University of Michigan, Ann Arbor, MI); McNenly, Matthew J. (University of Michigan, Ann Arbor, MI)
2004-07-01
For the simple geometries of Couette and Poiseuille flows, the velocity profile maintains a similar shape from continuum to free molecular flow. Therefore, modifications to the fluid viscosity and slip boundary conditions can improve the continuum based Navier-Stokes solution in the non-continuum non-equilibrium regime. In this investigation, the optimal modifications are found by a linear least-squares fit of the Navier-Stokes solution to the non-equilibrium solution obtained using the direct simulation Monte Carlo (DSMC) method. Models are then constructed for the Knudsen number dependence of the viscosity correction and the slip model from a database of DSMC solutions for Couette and Poiseuille flows of argon and nitrogen gas, with Knudsen numbers ranging from 0.01 to 10. Finally, the accuracy of the models is measured for non-equilibrium cases both in and outside the DSMC database. Flows outside the database include: combined Couette and Poiseuille flow, partial wall accommodation, helium gas, and non-zero convective acceleration. The models reproduce the velocity profiles in the DSMC database within an L{sub 2} error norm of 3% for Couette flows and 7% for Poiseuille flows. However, the errors in the model predictions outside the database are up to five times larger.
J. G. Coen van Hasselt
2014-01-01
Full Text Available This work describes a first population pharmacokinetic (PK model for free and total cefazolin during pregnancy, which can be used for dose regimen optimization. Secondly, analysis of PK studies in pregnant patients is challenging due to study design limitations. We therefore developed a semiphysiological modeling approach, which leveraged gestation-induced changes in creatinine clearance (CrCL into a population PK model. This model was then compared to the conventional empirical covariate model. First, a base two-compartmental PK model with a linear protein binding was developed. The empirical covariate model for gestational changes consisted of a linear relationship between CL and gestational age. The semiphysiological model was based on the base population PK model and a separately developed mixed-effect model for gestation-induced change in CrCL. Estimates for baseline clearance (CL were 0.119 L/min (RSE 58% and 0.142 L/min (RSE 44% for the empirical and semiphysiological models, respectively. Both models described the available PK data comparably well. However, as the semiphysiological model was based on prior knowledge of gestation-induced changes in renal function, this model may have improved predictive performance. This work demonstrates how a hybrid semiphysiological population PK approach may be of relevance in order to derive more informative inferences.
Computer Model of the Empirical Knowledge of Physics Formation: Coordination with Testing Results
Robert V. Mayer
2016-06-01
Full Text Available 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 are studied only on the theoretical level (speculative or ideally. The determination of the forgetting coefficients of the facts of the first, second and third categories and coordination of imitating model with distribution of empirical information in the school physics course and testing results is carried out. The graphs of dependence of empirical knowledge for various physics sections and facts categories on time are given.
Empirical and modeled synoptic cloud climatology of the Arctic Ocean
Barry, R. G.; Newell, J. P.; Schweiger, A.; Crane, R. G.
1986-01-01
A set of cloud cover data were developed for the Arctic during the climatically important spring/early summer transition months. Parallel with the determination of mean monthly cloud conditions, data for different synoptic pressure patterns were also composited as a means of evaluating the role of synoptic variability on Arctic cloud regimes. In order to carry out this analysis, a synoptic classification scheme was developed for the Arctic using an objective typing procedure. A second major objective was to analyze model output of pressure fields and cloud parameters from a control run of the Goddard Institue for Space Studies climate model for the same area and to intercompare the synoptic climatatology of the model with that based on the observational data.
Development of Solar Wind Model Driven by Empirical Heat Flux and Pressure Terms
Sittler, Edward C., Jr.; Ofman, L.; Selwa, M.; Kramar, M.
2008-01-01
We are developing a time stationary self-consistent 2D MHD model of the solar corona and solar wind as suggested by Sittler et al. (2003). Sittler & Guhathakurta (1999) developed a semiempirical steady state model (SG model) of the solar wind in a multipole 3-streamer structure, with the model constrained by Skylab observations. Guhathakurta et al. (2006) presented a more recent version of their initial work. Sittler et al. (2003) modified the SG model by investigating time dependent MHD, ad hoc heating term with heat conduction and empirical heating solutions. Next step of development of 2D MHD models was performed by Sittler & Ofman (2006). They derived effective temperature and effective heat flux from the data-driven SG model and fit smooth analytical functions to be used in MHD calculations. Improvements of the Sittler & Ofman (2006) results now show a convergence of the 3-streamer topology into a single equatorial streamer at altitudes > 2 R(sub S). This is a new result and shows we are now able to reproduce observations of an equatorially confined streamer belt. In order to allow our solutions to be applied to more general applications, we extend that model by using magnetogram data and PFSS model as a boundary condition. Initial results were presented by Selwa et al. (2008). We choose solar minimum magnetogram data since during solar maximum the boundary conditions are more complex and the coronal magnetic field may not be described correctly by PFSS model. As the first step we studied the simplest 2D MHD case with variable heat conduction, and with empirical heat input combined with empirical momentum addition for the fast solar wind. We use realistic magnetic field data based on NSO/GONG data, and plan to extend the study to 3D. This study represents the first attempt of fully self-consistent realistic model based on real data and including semi-empirical heat flux and semi-empirical effective pressure terms.
Temperature characteristics of quantum dot devices: Rate vs. Master Equation Models
Berg, Tommy Winther; Bischoff, Svend; Magnúsdóttir, Ingibjörg;
2001-01-01
The change of transparency current with temperature for quantum dot devices depends strongly on whether a rate or master equation model is used. The master equation model successfully explains experimental observations of negative characteristic temperatures.......The change of transparency current with temperature for quantum dot devices depends strongly on whether a rate or master equation model is used. The master equation model successfully explains experimental observations of negative characteristic temperatures....
On the specification of structural equation models for ecological systems
Grace, J.B.; Michael, Anderson T.; Han, O.; Scheiner, S.M.
2010-01-01
The use of structural equation modeling (SEM) is often motivated by its utility for investigating complex networks of relationships, but also because of its promise as a means of representing theoretical concepts using latent variables. In this paper, we discuss characteristics of ecological theory and some of the challenges for proper specification of theoretical ideas in structural equation models (SE models). In our presentation, we describe some of the requirements for classical latent variable models in which observed variables (indicators) are interpreted as the effects of underlying causes. We also describe alternative model specifications in which indicators are interpreted as having causal influences on the theoretical concepts. We suggest that this latter nonclassical specification (which involves another variable type-the composite) will often be appropriate for ecological studies because of the multifaceted nature of our theoretical concepts. In this paper, we employ the use of meta-models to aid the translation of theory into SE models and also to facilitate our ability to relate results back to our theories. We demonstrate our approach by showing how a synthetic theory of grassland biodiversity can be evaluated using SEM and data from a coastal grassland. In this example, the theory focuses on the responses of species richness to abiotic stress and disturbance, both directly and through intervening effects on community biomass. Models examined include both those based on classical forms (where each concept is represented using a single latent variable) and also ones in which the concepts are recognized to be multifaceted and modeled as such. To address the challenge of matching SE models with the conceptual level of our theory, two approaches are illustrated, compositing and aggregation. Both approaches are shown to have merits, with the former being preferable for cases where the multiple facets of a concept have widely differing effects in the
An Empirical Model of Wage Dispersion with Sorting
Bagger, Jesper; Lentz, Rasmus
This paper studies wage dispersion in an equilibrium on-the-job-search model with endogenous search intensity. Workers differ in their permanent skill level and firms differ with respect to productivity. Positive (negative) sorting results if the match production function is supermodular...
Empirical validation data sets for double skin facade models
Kalyanova, Olena; Jensen, Rasmus Lund; Heiselberg, Per
2008-01-01
During recent years application of double skin facades (DSF) has greatly increased. However, successful application depends heavily on reliable and validated models for simulation of the DSF performance and this in turn requires access to high quality experimental data. Three sets of accurate emp...
Neural networks in economic modelling : An empirical study
Verkooijen, W.J.H.
1996-01-01
This dissertation addresses the statistical aspects of neural networks and their usability for solving problems in economics and finance. Neural networks are discussed in a framework of modelling which is generally accepted in econometrics. Within this framework a neural network is regarded as a sta
An Empirical Study of a Solo Performance Assessment Model
Russell, Brian E.
2015-01-01
The purpose of this study was to test a hypothesized model of solo music performance assessment. Specifically, this study investigates the influence of technique and musical expression on perceptions of overall performance quality. The Aural Musical Performance Quality (AMPQ) measure was created to measure overall performance quality, technique,…
An Empirical Generative Framework for Computational Modeling of Language Acquisition
Waterfall, Heidi R.; Sandbank, Ben; Onnis, Luca; Edelman, Shimon
2010-01-01
This paper reports progress in developing a computer model of language acquisition in the form of (1) a generative grammar that is (2) algorithmically learnable from realistic corpus data, (3) viable in its large-scale quantitative performance and (4) psychologically real. First, we describe new algorithmic methods for unsupervised learning of…
Empirical genome evolution models root the tree of life.
Harish, Ajith; Kurland, Charles G
2017-07-01
A reliable phylogenetic reconstruction of the evolutionary history of contemporary species depends on a robust identification of the universal common ancestor (UCA) at the root of the Tree of Life (ToL). That root polarizes the tree so that the evolutionary succession of ancestors to descendants is discernable. In effect, the root determines the branching order and the direction of character evolution. Typically, conventional phylogenetic analyses implement time-reversible models of evolution for which character evolution is un-polarized. Such practices leave the root and the direction of character evolution undefined by the data used to construct such trees. In such cases, rooting relies on theoretic assumptions and/or the use of external data to interpret unrooted trees. The most common rooting method, the outgroup method is clearly inapplicable to the ToL, which has no outgroup. Both here and in the accompanying paper (Harish and Kurland, 2017) we have explored the theoretical and technical issues related to several rooting methods. We demonstrate (1) that Genome-level characters and evolution models are necessary for species phylogeny reconstructions. By the same token, standard practices exploiting sequence-based methods that implement gene-scale substitution models do not root species trees; (2) Modeling evolution of complex genomic characters and processes that are non-reversible and non-stationary is required to reconstruct the polarized evolution of the ToL; (3) Rooting experiments and Bayesian model selection tests overwhelmingly support the earlier finding that akaryotes and eukaryotes are sister clades that descend independently from UCA (Harish and Kurland, 2013); (4) Consistent ancestral state reconstructions from independent genome samplings confirm the previous finding that UCA features three fourths of the unique protein domain-superfamilies encoded by extant genomes. Copyright © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie
Generalized multiplicative error models: Asymptotic inference and empirical analysis
Li, Qian
This dissertation consists of two parts. The first part focuses on extended Multiplicative Error Models (MEM) that include two extreme cases for nonnegative series. These extreme cases are common phenomena in high-frequency financial time series. The Location MEM(p,q) model incorporates a location parameter so that the series are required to have positive lower bounds. The estimator for the location parameter turns out to be the minimum of all the observations and is shown to be consistent. The second case captures the nontrivial fraction of zero outcomes feature in a series and combines a so-called Zero-Augmented general F distribution with linear MEM(p,q). Under certain strict stationary and moment conditions, we establish a consistency and asymptotic normality of the semiparametric estimation for these two new models. The second part of this dissertation examines the differences and similarities between trades in the home market and trades in the foreign market of cross-listed stocks. We exploit the multiplicative framework to model trading duration, volume per trade and price volatility for Canadian shares that are cross-listed in the New York Stock Exchange (NYSE) and the Toronto Stock Exchange (TSX). We explore the clustering effect, interaction between trading variables, and the time needed for price equilibrium after a perturbation for each market. The clustering effect is studied through the use of univariate MEM(1,1) on each variable, while the interactions among duration, volume and price volatility are captured by a multivariate system of MEM(p,q). After estimating these models by a standard QMLE procedure, we exploit the Impulse Response function to compute the calendar time for a perturbation in these variables to be absorbed into price variance, and use common statistical tests to identify the difference between the two markets in each aspect. These differences are of considerable interest to traders, stock exchanges and policy makers.
Reduction of static field equation of Faddeev model to first order PDE
Hirayama, Minoru [Department of Mathematics and Physics, Shanghai University of Electric Power, Pinglian road 2103, Shanghai 200090 (China); Shi Changguang [Department of Mathematics and Physics, Shanghai University of Electric Power, Pinglian road 2103, Shanghai 200090 (China)], E-mail: shichangguang@shiep.edu.cn
2007-09-06
A method to solve the static field equation of the Faddeev model is presented. For a special combination of the concerned field, we adopt a form which is compatible with the field equation and involves two arbitrary complex functions. As a result, the static field equation is reduced to a set of first order partial differential equations.
A fractional diffusion equation model for cancer tumor
Iyiola, Olaniyi Samuel; Zaman, F. D.
2014-10-01
In this article, we consider cancer tumor models and investigate the need for fractional order derivative as compared to the classical first order derivative in time. Three different cases of the net killing rate are taken into account including the case where net killing rate of the cancer cells is dependent on the concentration of the cells. At first, we use a relatively new analytical technique called q-Homotopy Analysis Method on the resulting time-fractional partial differential equations to obtain analytical solution in form of convergent series with easily computable components. Our numerical analysis enables us to give some recommendations on the appropriate order (fractional) of derivative in time to be used in modeling cancer tumor.
A partial differential equation model of metastasized prostatic cancer.
Friedman, Avner; Jain, Harsh Vardhan
2013-06-01
Biochemically failing metastatic prostate cancer is typically treated with androgen ablation. However, due to the emergence of castration-resistant cells that can survive in low androgen concentrations, such therapy eventually fails. Here, we develop a partial differential equation model of the growth and response to treatment of prostate cancer that has metastasized to the bone. Existence and uniqueness results are derived for the resulting free boundary problem. In particular, existence and uniqueness of solutions for all time are proven for the radially symmetric case. Finally, numerical simulations of a tumor growing in 2-dimensions with radial symmetry are carried in order to evaluate the therapeutic potential of different treatment strategies. These simulations are able to reproduce a variety of clinically observed responses to treatment, and suggest treatment strategies that may result in tumor remission, underscoring our model's potential to make a significant contribution in the field of prostate cancer therapeutics.
Explicit estimating equations for semiparametric generalized linear latent variable models
Ma, Yanyuan
2010-07-05
We study generalized linear latent variable models without requiring a distributional assumption of the latent variables. Using a geometric approach, we derive consistent semiparametric estimators. We demonstrate that these models have a property which is similar to that of a sufficient complete statistic, which enables us to simplify the estimating procedure and explicitly to formulate the semiparametric estimating equations. We further show that the explicit estimators have the usual root n consistency and asymptotic normality. We explain the computational implementation of our method and illustrate the numerical performance of the estimators in finite sample situations via extensive simulation studies. The advantage of our estimators over the existing likelihood approach is also shown via numerical comparison. We employ the method to analyse a real data example from economics. © 2010 Royal Statistical Society.
Empirical study on entropy models of cellular manufacturing systems
Zhifeng Zhang; Renbin Xiao
2009-01-01
From the theoretical point of view,the states of manufacturing resources can be monitored and assessed through the amount of information needed to describe their technological structure and operational state.The amount of information needed to describe cellular manufacturing systems is investigated by two measures:the structural entropy and the operational entropy.Based on the Shannon entropy,the models of the structural entropy and the operational entropy of cellular manufacturing systems are developed,and the cognizance of the states of manufacturing resources is also illustrated.Scheduling is introduced to measure the entropy models of cellular manufacturing systems,and the feasible concepts of maximum schedule horizon and schedule adherence are advanced to quantitatively evaluate the effectiveness of schedules.Finally,an example is used to demonstrate the validity of the proposed methodology.
Including Finite Surface Span Effects in Empirical Jet-Surface Interaction Noise Models
Brown, Clifford A.
2016-01-01
The effect of finite span on the jet-surface interaction noise source and the jet mixing noise shielding and reflection effects is considered using recently acquired experimental data. First, the experimental setup and resulting data are presented with particular attention to the role of surface span on far-field noise. These effects are then included in existing empirical models that have previously assumed that all surfaces are semi-infinite. This extended abstract briefly describes the experimental setup and data leaving the empirical modeling aspects for the final paper.
AN EMPIRICAL MODEL OF ONLINE BUYING CONTINUANCE INTENTION
ORZAN Gheorghe; Claudia ICONARU; MACOVEI Octav-Ionut
2012-01-01
The aim of this paper is to propose, test and validate a model of consumers` continuance intention to buy online as a main function of affective attitude towards using the Internet for purchasing goods and services and the overall satisfaction towards the decision of buying online. The confirmation of initial expectations regarding online buying is the main predictor of online consumers` satisfaction and online consumers` perceived usefulness of online buying. Affective attitude is mediating ...
PROPOSAL OF AN EMPIRICAL MODEL FOR SUPPLIERS SELECTION
Paulo Ávila
2015-03-01
Full Text Available The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, trough the literature review, there were identified five broad suppliers selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. Thereafter, a survey was elaborated and companies were contacted in order to answer which factors have more relevance in their decisions to choose the suppliers. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP method or Simple Multi-Attribute Rating Technique (SMART. The result of the research undertaken by the authors is a reference model that represents a decision making support for the suppliers/partners selection process.
Empirically Grounded Agent-Based Models of Innovation Diffusion: A Critical Review
Zhang, Haifeng
2016-01-01
Innovation diffusion has been studied extensively in a variety of disciplines, including sociology, economics, marketing, ecology, and computer science. Traditional literature on innovation diffusion has been dominated by models of aggregate behavior and trends. However, the agent-based modeling (ABM) paradigm is gaining popularity as it captures agent heterogeneity and enables fine-grained modeling of interactions mediated by social and geographic networks. While most ABM work on innovation diffusion is theoretical, empirically grounded models are increasingly important, particularly in guiding policy decisions. We present a critical review of empirically grounded agent-based models of innovation diffusion, developing a categorization of this research based on types of agent models as well as applications. By connecting the modeling methodologies in the fields of information and innovation diffusion, we suggest that the maximum likelihood estimation framework widely used in the former is a promising paradigm...
2003-01-01
An efficient numerical method is developed for the numerical solution of non-linear wave equations typified by the regularized long wave equation (RLW) and its generalization (GRLW). The method developed uses a pseudo-spectral (Fourier transform) treatment of the space dependence together with a linearized implicit scheme in time. An important advantage to be gained from the use of this method, is the ability to vary the mesh length, thereby reducing the computational time. Using a linearized...
Sahbi FARHANI
2012-01-01
Full Text Available This paper considers tests of parameters instability and structural change with known, unknown or multiple breakpoints. The results apply to a wide class of parametric models that are suitable for estimation by strong rules for detecting the number of breaks in a time series. For that, we use Chow, CUSUM, CUSUM of squares, Wald, likelihood ratio and Lagrange multiplier tests. Each test implicitly uses an estimate of a change point. We conclude with an empirical analysis on two different models (ARMA model and simple linear regression model.
Structural Equation Modeling for Analyzing Erythrocyte Fatty Acids in Framingham
James V. Pottala
2014-01-01
Full Text Available Research has shown that several types of erythrocyte fatty acids (i.e., omega-3, omega-6, and trans are associated with risk for cardiovascular diseases. However, there are complex metabolic and dietary relations among fatty acids, which induce correlations that are typically ignored when using them as risk predictors. A latent variable approach could summarize these complex relations into a few latent variable scores for use in statistical models. Twenty-two red blood cell (RBC fatty acids were measured in Framingham (N = 3196. The correlation matrix of the fatty acids was modeled using structural equation modeling; the model was tested for goodness-of-fit and gender invariance. Thirteen fatty acids were summarized by three latent variables, and gender invariance was rejected so separate models were developed for men and women. A score was developed for the polyunsaturated fatty acid (PUFA latent variable, which explained about 30% of the variance in the data. The PUFA score included loadings in opposing directions among three omega-3 and three omega-6 fatty acids, and incorporated the biosynthetic and dietary relations among them. Whether the PUFA factor score can improve the performance of risk prediction in cardiovascular diseases remains to be tested.
A model of deep ecotourism development and its empirical study
无
2007-01-01
Ecotourism requires the harmony of all factors involved in tourism system for a multilateral benefit.Based on such cognition,a concept of deep ecotourism development is put forward which includes two connotations:on the one hand,it should give prominence to the display of the eco-culture of the tourist destination and tourists'eco-experience.in which way the development behavior on the tourist destination and the tourists' behavior will beregulated;on the other hand,it implies the deep harmony among tourist entrepreneurs and tourists,the local governments and the local residents,as well as tourist activities and the ecological environment in the tourism development for the multilateral benefit of every element involved and sustainable tourism development.The common sense is that the degrees in a certain tourism destination will differ and that consequently four levels of ecotourism are divided-very shallow ecotourism,shallow ecotourism,deep ecotourism and very deep ecotourism.To move shallow ecotourism toward deep one,two models of"foursubjects and two wings"and"connecting the two wings"of deep ecotourism development system are introduced to make ecotourism industry favorable to the display of eco-culture and the Sustainable development of the destination community.With the two models,a case study of ecotourism development in Louguantal National Forest Park was made as a demonstration.The ultimate purpose is to build an ideal new Shangri-La.
Yip, Theo C M; Tsang, Daniel C W; Ng, Kelvin T W; Lo, Irene M C
2009-01-01
The effectiveness of using biodegradable EDDS (S,S-ethylenediaminedisuccinic acid) for metal extraction has drawn increasing attention in recent years. In this study, an empirical model, which utilized the initial metal distribution in soils and a set of parameter values independently determined from sequential extraction, was developed for estimating the time-dependent heavy metal extraction by EDDS from single-metal and multi-metal contaminated soils. The model simulation provided a satisfactory description of the experimental results of the 7-d extraction kinetics of Cu, Zn, and Pb in both artificially contaminated and field-contaminated soils. Thus, independent and prior assessment of extraction efficiency would be available to facilitate the engineering applications of EDDS. Furthermore, a simple empirical equation using the initial metal distribution was also proposed to estimate the extraction efficiency at equilibrium. It was found that, for the same type of soils, higher extraction efficiency was achieved in multi-metal contaminated soils than in single-metal contaminated soils. The differences were 4-9%, 9-16%, and 21-31% for Cu, Zn, and Pb, respectively, probably due to the larger proportion of exchangeable and carbonate fractions of sorbed Zn and Pb in multi-metal contaminated soils. EDDS-promoted mineral dissolution, on the other hand, was more significant in multi-metal contaminated soils as a result of the higher EDDS concentration applied to the soils of higher total metal content.
Xuemin Cheng
2016-10-01
Full Text Available The thermal environment is an important factor in the design of optical systems. This study investigated the thermal analysis technology of optical systems for navigation guidance and control in supersonic aircraft by developing empirical equations for the front temperature gradient and rear thermal diffusion distance, and for basic factors such as flying parameters and the structure of the optical system. Finite element analysis (FEA was used to study the relationship between flying and front dome parameters and the system temperature field. Systematic deduction was then conducted based on the effects of the temperature field on the physical geometry and ray tracing performance of the front dome and rear optical lenses, by deriving the relational expressions between the system temperature field and the spot size and positioning precision of the rear optical lens. The optical systems used for navigation guidance and control in supersonic aircraft when the flight speed is in the range of 1–5 Ma were analysed using the derived equations. Using this new method it was possible to control the precision within 10% when considering the light spot received by the four-quadrant detector, and computation time was reduced compared with the traditional method of separately analysing the temperature field of the front dome and rear optical lens using FEA. Thus, the method can effectively increase the efficiency of parameter analysis and computation in an airborne optical system, facilitating the systematic, effective and integrated thermal analysis of airborne optical systems for navigation guidance and control.
Cheng, Xuemin; Yang, Yikang; Hao, Qun
2016-10-17
The thermal environment is an important factor in the design of optical systems. This study investigated the thermal analysis technology of optical systems for navigation guidance and control in supersonic aircraft by developing empirical equations for the front temperature gradient and rear thermal diffusion distance, and for basic factors such as flying parameters and the structure of the optical system. Finite element analysis (FEA) was used to study the relationship between flying and front dome parameters and the system temperature field. Systematic deduction was then conducted based on the effects of the temperature field on the physical geometry and ray tracing performance of the front dome and rear optical lenses, by deriving the relational expressions between the system temperature field and the spot size and positioning precision of the rear optical lens. The optical systems used for navigation guidance and control in supersonic aircraft when the flight speed is in the range of 1-5 Ma were analysed using the derived equations. Using this new method it was possible to control the precision within 10% when considering the light spot received by the four-quadrant detector, and computation time was reduced compared with the traditional method of separately analysing the temperature field of the front dome and rear optical lens using FEA. Thus, the method can effectively increase the efficiency of parameter analysis and computation in an airborne optical system, facilitating the systematic, effective and integrated thermal analysis of airborne optical systems for navigation guidance and control.
Quantifying uncertainty, variability and likelihood for ordinary differential equation models
Weisse, Andrea Y
2010-10-28
Abstract Background In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space. Results The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability. Conclusions While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.
Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study.
Tîrnăucă, Cristina; Montaña, José L; Ontañón, Santiago; González, Avelino J; Pardo, Luis M
2016-06-24
Imagine an agent that performs tasks according to different strategies. The goal of Behavioral Recognition (BR) is to identify which of the available strategies is the one being used by the agent, by simply observing the agent's actions and the environmental conditions during a certain period of time. The goal of Behavioral Cloning (BC) is more ambitious. In this last case, the learner must be able to build a model of the behavior of the agent. In both settings, the only assumption is that the learner has access to a training set that contains instances of observed behavioral traces for each available strategy. This paper studies a machine learning approach based on Probabilistic Finite Automata (PFAs), capable of achieving both the recognition and cloning tasks. We evaluate the performance of PFAs in the context of a simulated learning environment (in this case, a virtual Roomba vacuum cleaner robot), and compare it with a collection of other machine learning approaches.
Cycle length maximization in PWRs using empirical core models
Okafor, K.C.; Aldemir, T.
1987-01-01
The problem of maximizing cycle length in nuclear reactors through optimal fuel and poison management has been addressed by many investigators. An often-used neutronic modeling technique is to find correlations between the state and control variables to describe the response of the core to changes in the control variables. In this study, a set of linear correlations, generated by two-dimensional diffusion-depletion calculations, is used to find the enrichment distribution that maximizes cycle length for the initial core of a pressurized water reactor (PWR). These correlations (a) incorporate the effect of composition changes in all the control zones on a given fuel assembly and (b) are valid for a given range of control variables. The advantage of using such correlations is that the cycle length maximization problem can be reduced to a linear programming problem.
New Exact Solutions for New Model Nonlinear Partial Differential Equation
A. Maher
2013-01-01
Full Text Available In this paper we propose a new form of Padé-II equation, namely, a combined Padé-II and modified Padé-II equation. The mapping method is a promising method to solve nonlinear evaluation equations. Therefore, we apply it, to solve the combined Padé-II and modified Padé-II equation. Exact travelling wave solutions are obtained and expressed in terms of hyperbolic functions, trigonometric functions, rational functions, and elliptic functions.
Ivan Puga-Gonzalez
Full Text Available Post-conflict affiliation between former opponents and bystanders occurs in several species of non-human primates. It is classified in four categories of which affiliation received by the former victim, 'consolation', has received most attention. The hypotheses of cognitive constraint and social constraint are inadequate to explain its occurrence. The cognitive constraint hypothesis is contradicted by recent evidence of 'consolation' in monkeys and the social constraint hypothesis lacks information why 'consolation' actually happens. Here, we combine a computational model and an empirical study to investigate the minimum cognitive requirements for post-conflict affiliation. In the individual-based model, individuals are steered by cognitively simple behavioural rules. Individuals group and when nearby each other they fight if they are likely to win, otherwise, they may groom, especially when anxious. We parameterize the model after empirical data of a tolerant species, the Tonkean macaque (Macaca tonkeana. We find evidence for the four categories of post-conflict affiliation in the model and in the empirical data. We explain how in the model these patterns emerge from the combination of a weak hierarchy, social facilitation, risk-sensitive aggression, interactions with partners close-by and grooming as tension-reduction mechanism. We indicate how this may function as a new explanation for empirical data.
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.
Puga-Gonzalez, Ivan; Butovskaya, Marina; Thierry, Bernard; Hemelrijk, Charlotte Korinna
2014-01-01
Post-conflict affiliation between former opponents and bystanders occurs in several species of non-human primates. It is classified in four categories of which affiliation received by the former victim, 'consolation', has received most attention. The hypotheses of cognitive constraint and social constraint are inadequate to explain its occurrence. The cognitive constraint hypothesis is contradicted by recent evidence of 'consolation' in monkeys and the social constraint hypothesis lacks information why 'consolation' actually happens. Here, we combine a computational model and an empirical study to investigate the minimum cognitive requirements for post-conflict affiliation. In the individual-based model, individuals are steered by cognitively simple behavioural rules. Individuals group and when nearby each other they fight if they are likely to win, otherwise, they may groom, especially when anxious. We parameterize the model after empirical data of a tolerant species, the Tonkean macaque (Macaca tonkeana). We find evidence for the four categories of post-conflict affiliation in the model and in the empirical data. We explain how in the model these patterns emerge from the combination of a weak hierarchy, social facilitation, risk-sensitive aggression, interactions with partners close-by and grooming as tension-reduction mechanism. We indicate how this may function as a new explanation for empirical data.
Computer modeling of flow and transport interactions for compressible Navier-Stokes equations
Rahman, Mohamed Mizanur
A unified numerical algorithm to simulate viscous flow with heat transfer over a wide range of Mach number and Reynolds number is developed. The governing equations used to model the numerical simulations are the 2-D compressible viscous Navier-Stokes equations. The numerical procedure is based on MacCormack's explicit 'predictor corrector' time dependent finite difference scheme. For an explicit scheme, a great number of iterations is required to get a converged steady solution because of a small time step. Vectorizing and parallelizing the code greatly alleviates this problem by reducing the total job running time manifold. The numerical algorithm, thus developed, is used to simulate such demanding and interacting flow problems as convection heat transfer in a cavity flow heat transfer enhancement by eddy-promoters, laminar/turbulent shock boundary layer interactions and unsteady shock boundary layer interactions over a compression corner. A detailed analysis of all important flow features that characterize such flows and the mechanisms that are involved, is performed for each individual case. The flow physics are discussed and new insights are provided. Results are compared with experimental data where available and the empirical relations between different flow properties or parameters are either established or verified where possible. Apart from these, some algorithm related questions, such as grid sensitivity, boundary conditions, convergence criteria, effects of artificial viscosity and the numerical stability are investigated.
Trade-FDI linkages in a simultaneous equations system of gravity models for german regional data
Mitze, Timo Friedel; Alecke, Björn; Untiedt, Gerhard
2010-01-01
Abstract. Using regional data, we analyze the nature of German trade-FDI linkages within the EU27 for a system of gravity equations. Starting from a macroeconomic perspective, our analysis supports earlier empirical evidence for Germany in finding substitutive links between trade and outward FDI...
Model Identification Using Stochastic Differential Equation Grey-Box Models in Diabetes
Duun-Henriksen, Anne Katrine; Schmidt, Signe; Røge, Rikke Meldgaard
2013-01-01
BACKGROUND: The acceptance of virtual preclinical testing of control algorithms is growing and thus also the need for robust and reliable models. Models based on ordinary differential equations (ODEs) can rarely be validated with standard statistical tools. Stochastic differential equations (SDEs......) offer the possibility of building models that can be validated statistically and that are capable of predicting not only a realistic trajectory, but also the uncertainty of the prediction. In an SDE, the prediction error is split into two noise terms. This separation ensures that the errors...... are uncorrelated and provides the possibility to pinpoint model deficiencies. METHODS: An identifiable model of the glucoregulatory system in a type 1 diabetes mellitus (T1DM) patient is used as the basis for development of a stochastic-differential-equation-based grey-box model (SDE-GB). The parameters...
Goličnik, Marko
2011-06-01
Many pharmacodynamic processes can be described by the nonlinear saturation kinetics that are most frequently based on the hyperbolic Michaelis-Menten equation. Thus, various time-dependent solutions for drugs obeying such kinetics can be expressed in terms of the Lambert W(x)-omega function. However, unfortunately, computer programs that can perform the calculations for W(x) are not widely available. To avoid this problem, the replacement of the integrated Michaelis-Menten equation with an empiric integrated 1--exp alternative model equation was proposed recently by Keller et al. (Ther Drug Monit. 2009;31:783-785), although, as shown here, it was not necessary. Simulated concentrations of model drugs obeying Michaelis-Menten elimination kinetics were generated by two approaches: 1) calculation of time-course data based on an approximation equation W2*(x) performed using Microsoft Excel; and 2) calculation of reference time-course data based on an exact W(x) function built in to the Wolfram Mathematica. I show here that the W2*(x) function approximates the actual W(x) accurately. W2*(x) is expressed in terms of elementary mathematical functions and, consequently, it can be easily implemented using any of the widely available software. Hence, with the example of a hypothetical drug, I demonstrate here that an equation based on this approximation is far better, because it is nearly equivalent to the original solution, whereas the same characteristics cannot be fully confirmed for the 1--exp model equation. The W2*(x) equation proposed here might have an important role as a useful shortcut in optional software to estimate kinetic parameters from experimental data for drugs, and it might represent an easy and universal analytical tool for simulating and designing dosing regimens.