System identification application using Hammerstein model
Indian Academy of Sciences (India)
Saban Ozer
results of the Hammerstein model focused on this study. *For correspondence. 597 ..... Example 1: In this sample study, considering the block structure given in ..... Graduate School of Natural and Applied Science, Turkey. [20] Cui M, Liu H, Li Z ...
Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches
DEFF Research Database (Denmark)
Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam
2009-01-01
In this paper nonlinear fault detection for in-service monitoring and decision support systems for ships will be presented. The ship is described as a nonlinear system, and the stochastic wave elevation and the associated ship responses are conveniently modelled in frequency domain. The transform....... The transformation from time domain to frequency domain has been conducted by use of Volterra theory. The paper takes as an example fault detection of a containership on which a decision support system has been installed....
Multilinear Model of Heat Exchanger with Hammerstein Structure
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Dragan Pršić
2016-01-01
Full Text Available The multilinear model control design approach is based on the approximation of the nonlinear model of the system by a set of linear models. The paper presents the method of creation of a bank of linear models of the two-pass shell and tube heat exchanger. The nonlinear model is assumed to have a Hammerstein structure. The set of linear models is formed by decomposition of the nonlinear steady-state characteristic by using the modified Included Angle Dividing method. Two modifications of this method are proposed. The first one refers to the addition to the algorithm for decomposition, which reduces the number of linear segments. The second one refers to determination of the threshold value. The dependence between decomposition of the nonlinear characteristic and the linear dynamics of the closed-loop system is established. The decoupling process is more formal and it can be easily implemented by using software tools. Due to its simplicity, the method is particularly suitable in complex systems, such as heat exchanger networks.
Model-based Acceleration Control of Turbofan Engines with a Hammerstein-Wiener Representation
Wang, Jiqiang; Ye, Zhifeng; Hu, Zhongzhi; Wu, Xin; Dimirovsky, Georgi; Yue, Hong
2017-05-01
Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing model-based acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study.
Model Predictive Control Based on Kalman Filter for Constrained Hammerstein-Wiener Systems
Directory of Open Access Journals (Sweden)
Man Hong
2013-01-01
Full Text Available To precisely track the reactor temperature in the entire working condition, the constrained Hammerstein-Wiener model describing nonlinear chemical processes such as in the continuous stirred tank reactor (CSTR is proposed. A predictive control algorithm based on the Kalman filter for constrained Hammerstein-Wiener systems is designed. An output feedback control law regarding the linear subsystem is derived by state observation. The size of reaction heat produced and its influence on the output are evaluated by the Kalman filter. The observation and evaluation results are calculated by the multistep predictive approach. Actual control variables are computed while considering the constraints of the optimal control problem in a finite horizon through the receding horizon. The simulation example of the CSTR tester shows the effectiveness and feasibility of the proposed algorithm.
Recursive wind speed forecasting based on Hammerstein Auto-Regressive model
International Nuclear Information System (INIS)
Ait Maatallah, Othman; Achuthan, Ajit; Janoyan, Kerop; Marzocca, Pier
2015-01-01
Highlights: • Developed a new recursive WSF model for 1–24 h horizon based on Hammerstein model. • Nonlinear HAR model successfully captured chaotic dynamics of wind speed time series. • Recursive WSF intrinsic error accumulation corrected by applying rotation. • Model verified for real wind speed data from two sites with different characteristics. • HAR model outperformed both ARIMA and ANN models in terms of accuracy of prediction. - Abstract: A new Wind Speed Forecasting (WSF) model, suitable for a short term 1–24 h forecast horizon, is developed by adapting Hammerstein model to an Autoregressive approach. The model is applied to real data collected for a period of three years (2004–2006) from two different sites. The performance of HAR model is evaluated by comparing its prediction with the classical Autoregressive Integrated Moving Average (ARIMA) model and a multi-layer perceptron Artificial Neural Network (ANN). Results show that the HAR model outperforms both the ARIMA model and ANN model in terms of root mean square error (RMSE), mean absolute error (MAE), and Mean Absolute Percentage Error (MAPE). When compared to the conventional models, the new HAR model can better capture various wind speed characteristics, including asymmetric (non-gaussian) wind speed distribution, non-stationary time series profile, and the chaotic dynamics. The new model is beneficial for various applications in the renewable energy area, particularly for power scheduling
Chen, Sheng; Hong, Xia; Khalaf, Emad F; Alsaadi, Fuad E; Harris, Chris J
2017-12-01
Complex-valued (CV) B-spline neural network approach offers a highly effective means for identifying and inverting practical Hammerstein systems. Compared with its conventional CV polynomial-based counterpart, a CV B-spline neural network has superior performance in identifying and inverting CV Hammerstein systems, while imposing a similar complexity. This paper reviews the optimality of the CV B-spline neural network approach. Advantages of B-spline neural network approach as compared with the polynomial based modeling approach are extensively discussed, and the effectiveness of the CV neural network-based approach is demonstrated in a real-world application. More specifically, we evaluate the comparative performance of the CV B-spline and polynomial-based approaches for the nonlinear iterative frequency-domain decision feedback equalization (NIFDDFE) of single-carrier Hammerstein channels. Our results confirm the superior performance of the CV B-spline-based NIFDDFE over its CV polynomial-based counterpart.
Rebillat, Marc; Schoukens, Maarten
2018-05-01
Linearity is a common assumption for many real-life systems, but in many cases the nonlinear behavior of systems cannot be ignored and must be modeled and estimated. Among the various existing classes of nonlinear models, Parallel Hammerstein Models (PHM) are interesting as they are at the same time easy to interpret as well as to estimate. One way to estimate PHM relies on the fact that the estimation problem is linear in the parameters and thus that classical least squares (LS) estimation algorithms can be used. In that area, this article introduces a regularized LS estimation algorithm inspired on some of the recently developed regularized impulse response estimation techniques. Another mean to estimate PHM consists in using parametric or non-parametric exponential sine sweeps (ESS) based methods. These methods (LS and ESS) are founded on radically different mathematical backgrounds but are expected to tackle the same issue. A methodology is proposed here to compare them with respect to (i) their accuracy, (ii) their computational cost, and (iii) their robustness to noise. Tests are performed on simulated systems for several values of methods respective parameters and of signal to noise ratio. Results show that, for a given set of data points, the ESS method is less demanding in computational resources than the LS method but that it is also less accurate. Furthermore, the LS method needs parameters to be set in advance whereas the ESS method is not subject to conditioning issues and can be fully non-parametric. In summary, for a given set of data points, ESS method can provide a first, automatic, and quick overview of a nonlinear system than can guide more computationally demanding and precise methods, such as the regularized LS one proposed here.
WH-EA: An Evolutionary Algorithm for Wiener-Hammerstein System Identification
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J. Zambrano
2018-01-01
Full Text Available Current methods to identify Wiener-Hammerstein systems using Best Linear Approximation (BLA involve at least two steps. First, BLA is divided into obtaining front and back linear dynamics of the Wiener-Hammerstein model. Second, a refitting procedure of all parameters is carried out to reduce modelling errors. In this paper, a novel approach to identify Wiener-Hammerstein systems in a single step is proposed. This approach is based on a customized evolutionary algorithm (WH-EA able to look for the best BLA split, capturing at the same time the process static nonlinearity with high precision. Furthermore, to correct possible errors in BLA estimation, the locations of poles and zeros are subtly modified within an adequate search space to allow a fine-tuning of the model. The performance of the proposed approach is analysed by using a demonstration example and a nonlinear system identification benchmark.
Hammerstein system represention of financial volatility processes
Capobianco, E.
2002-05-01
We show new modeling aspects of stock return volatility processes, by first representing them through Hammerstein Systems, and by then approximating the observed and transformed dynamics with wavelet-based atomic dictionaries. We thus propose an hybrid statistical methodology for volatility approximation and non-parametric estimation, and aim to use the information embedded in a bank of volatility sources obtained by decomposing the observed signal with multiresolution techniques. Scale dependent information refers both to market activity inherent to different temporally aggregated trading horizons, and to a variable degree of sparsity in representing the signal. A decomposition of the expansion coefficients in least dependent coordinates is then implemented through Independent Component Analysis. Based on the described steps, the features of volatility can be more effectively detected through global and greedy algorithms.
Directory of Open Access Journals (Sweden)
Jean-Francois Couchouron
2002-01-01
Full Text Available We apply Monch type fixed point theorems for acyclic multivalued maps to the solvability of inclusions of Hammerstein type in Banach spaces. Our approach makes possible to unify and improve the existence theories for nonlinear evolution problems and abstract integral inclusions of Volterra and Fredholm type.
Recursive parameter estimation for Hammerstein-Wiener systems using modified EKF algorithm.
Yu, Feng; Mao, Zhizhong; Yuan, Ping; He, Dakuo; Jia, Mingxing
2017-09-01
This paper focuses on the recursive parameter estimation for the single input single output Hammerstein-Wiener system model, and the study is then extended to a rarely mentioned multiple input single output Hammerstein-Wiener system. Inspired by the extended Kalman filter algorithm, two basic recursive algorithms are derived from the first and the second order Taylor approximation. Based on the form of the first order approximation algorithm, a modified algorithm with larger parameter convergence domain is proposed to cope with the problem of small parameter convergence domain of the first order one and the application limit of the second order one. The validity of the modification on the expansion of convergence domain is shown from the convergence analysis and is demonstrated with two simulation cases. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Iterative Solutions of Nonlinear Integral Equations of Hammerstein Type
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Abebe R. Tufa
2015-11-01
Full Text Available Let H be a real Hilbert space. Let F,K : H → H be Lipschitz monotone mappings with Lipschtiz constants L1and L2, respectively. Suppose that the Hammerstein type equation u + KFu = 0 has a solution in H. It is our purpose in this paper to construct a new explicit iterative sequence and prove strong convergence of the sequence to a solution of the generalized Hammerstein type equation. The results obtained in this paper improve and extend known results in the literature.
An approximation method for nonlinear integral equations of Hammerstein type
International Nuclear Information System (INIS)
Chidume, C.E.; Moore, C.
1989-05-01
The solution of a nonlinear integral equation of Hammerstein type in Hilbert spaces is approximated by means of a fixed point iteration method. Explicit error estimates are given and, in some cases, convergence is shown to be at least as fast as a geometric progression. (author). 25 refs
Finite-dimensional approximation for operator equations of Hammerstein type
International Nuclear Information System (INIS)
Buong, N.
1992-11-01
The purpose of this paper is to establish convergence rate for a method of finite-dimensional approximation to solve operator equation of Hammerstein type in real reflexive Banach space. In order to consider a numerical example an iteration method is proposed in Hilbert space. (author). 25 refs
Directory of Open Access Journals (Sweden)
Ignacio Santamaría
2008-04-01
Full Text Available This paper treats the identification of nonlinear systems that consist of a cascade of a linear channel and a nonlinearity, such as the well-known Wiener and Hammerstein systems. In particular, we follow a supervised identification approach that simultaneously identifies both parts of the nonlinear system. Given the correct restrictions on the identification problem, we show how kernel canonical correlation analysis (KCCA emerges as the logical solution to this problem. We then extend the proposed identification algorithm to an adaptive version allowing to deal with time-varying systems. In order to avoid overfitting problems, we discuss and compare three possible regularization techniques for both the batch and the adaptive versions of the proposed algorithm. Simulations are included to demonstrate the effectiveness of the presented algorithm.
Identificación Robusta de Modelos Wiener y Hammerstein
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Silvina I. Biagiola
2009-04-01
Full Text Available Resumen: Los modelos orientados a bloques han mostrado ser útiles y eficaces como representaciones no lineales en muchas aplicaciones. Son modelos simples y a la vez válidos en una región más amplia que un modelo lineal invariante en el tiempo. En cuanto a su estructura, consisten en una cascada integrada por una dinámica lineal y un bloque estático no lineal.Si bien existen en la literatura numerosos trabajos que abordan la identificación nominal de estos modelos, el problema de identificación robusta en presencia de incertidumbre no ha sido cabalmente tratado.En este trabajo, se consideran dos clases de modelos orientados a bloques: modelos Wiener y Hammerstein. Empleando una representación paramétrica, se propone describir la incertidumbre como un conjunto de parámetros, cuyos valores se obtienen resolviendo un problema de optimización. El algoritmo de identificación desarrollado se ilustra mediante ejemplos de simulación. Palabras clave: Wiener, Hammerstein, Identificación, Incertidumbre, Optimización
DEFF Research Database (Denmark)
Nielsen, Kræn V.; Blanke, Mogens; Eriksson, Lars
2017-01-01
Taking offspring in a problem of ship emission reduction by exhaust gas recirculation control for large diesel engines, an underlying generic estimation challenge is formulated as a problem of joint state and parameter estimation for a class of multiple-input single-output Hammerstein systems...... observer is shown on simulated cases, on tests with a large diesel engine on test bed and on tests with a container vessel....
Solving Hammerstein Type Integral Equation by New Discrete Adomian Decomposition Methods
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Huda O. Bakodah
2013-01-01
Full Text Available New discrete Adomian decomposition methods are presented by using some identified Clenshaw-Curtis quadrature rules. We investigate two mixed quadrature rules one of precision five and the other of precision seven. The first rule is formed by using the Fejér second rule of precision three and Simpson rule of precision three, while the second rule is formed by using the Fejér second rule of precision five and the Boole rule of precision five. Our methods were applied to a nonlinear integral equation of the Hammerstein type and some examples are given to illustrate the validity of our methods.
International Nuclear Information System (INIS)
Ofoedu, Eric U.; Malonza, David M.
2010-07-01
In this paper we study the hybrid iterative scheme to find a common element of a set of solutions of generalized mixed equilibrium problem, a set of common fixed points of finite family of weak relatively nonexpansive mapping, and null spaces of finite family of γ-inverse strongly monotone mappings in a 2-uniformly convex and uniformly smooth real Banach space. Our results extend, improve and generalize the results of several authors which were announced recently. An application of our theorem to the solution of equations of Hammerstein-type is of independent interest. (author)
Spatio-temporal modeling of nonlinear distributed parameter systems
Li, Han-Xiong
2011-01-01
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s
A muscle model for hybrid muscle activation
Directory of Open Access Journals (Sweden)
Klauer Christian
2015-09-01
Full Text Available To develop model-based control strategies for Functional Electrical Stimulation (FES in order to support weak voluntary muscle contractions, a hybrid model for describing joint motions induced by concurrent voluntary-and FES induced muscle activation is proposed. It is based on a Hammerstein model – as commonly used in feedback controlled FES – and exemplarily applied to describe the shoulder abduction joint angle. Main component of a Hammerstein muscle model is usually a static input nonlinearity depending on the stimulation intensity. To additionally incorporate voluntary contributions, we extended the static non-linearity by a second input describing the intensity of the voluntary contribution that is estimated by electromyography (EMG measurements – even during active FES. An Artificial Neural Network (ANN is used to describe the static input non-linearity. The output of the ANN drives a second-order linear dynamical system that describes the combined muscle activation and joint angle dynamics. The tunable parameters are adapted to the individual subject by a system identification approach using previously recorded I/O-data. The model has been validated in two healthy subjects yielding RMS values for the joint angle error of 3.56° and 3.44°, respectively.
Computationally efficient model predictive control algorithms a neural network approach
Ławryńczuk, Maciej
2014-01-01
This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: · A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. · Implementation details of the MPC algorithms for feedforward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. · The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). · The MPC algorithms with neural approximation with no on-line linearization. · The MPC algorithms with guaranteed stability and robustness. · Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require d...
International Nuclear Information System (INIS)
Shipler, D.B.; Napier, B.A.
1992-07-01
This report details the conceptual approaches to be used in calculating radiation doses to individuals throughout the various periods of operations at the Hanford Site. The report considers the major environmental transport pathways--atmospheric, surface water, and ground water--and projects and appropriate modeling technique for each. The modeling sequence chosen for each pathway depends on the available data on doses, the degree of confidence justified by such existing data, and the level of sophistication deemed appropriate for the particular pathway and time period being considered
ROBUST CONTROL OF END-TIDAL CO2 USING THE H∞ LOOP-SHAPING APPROACH
Directory of Open Access Journals (Sweden)
Anake Pomprapa
2013-12-01
Full Text Available Mechanically ventilated patients require appropriate settings of respiratory control variables to maintain acceptable gas exchange. To control the carbon dioxide (CO2 level effectively and automatically, system identification based on a human subject was performed using a linear affine model and a nonlinear Hammerstein structure. Subsequently, a robust controller was designed using the H∞ loop-shaping approach, which synthesizes the optimal controller based on a specific objective by achieving stability with guaranteed performance. For demonstration purposes, the closed-loop control ventilation system was successfully tested in a human volunteer. The experimental results indicate that the blood CO2 level may indeed be controlled noninvasively by measuring end-tidal CO2 from expired air. Keeping the limited amount of experimental data in mind, we conclude that H∞ loop-shaping may be a promising technique for control of mechanical ventilation in patients with respiratory insufficiency.
Material Modelling - Composite Approach
DEFF Research Database (Denmark)
Nielsen, Lauge Fuglsang
1997-01-01
is successfully justified comparing predicted results with experimental data obtained in the HETEK-project on creep, relaxation, and shrinkage of very young concretes cured at a temperature of T = 20^o C and a relative humidity of RH = 100%. The model is also justified comparing predicted creep, shrinkage......, and internal stresses caused by drying shrinkage with experimental results reported in the literature on the mechanical behavior of mature concretes. It is then concluded that the model presented applied in general with respect to age at loading.From a stress analysis point of view the most important finding...... in this report is that cement paste and concrete behave practically as linear-viscoelastic materials from an age of approximately 10 hours. This is a significant age extension relative to earlier studies in the literature where linear-viscoelastic behavior is only demonstrated from ages of a few days. Thus...
Recursive Subspace Identification of AUV Dynamic Model under General Noise Assumption
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Zheping Yan
2014-01-01
Full Text Available A recursive subspace identification algorithm for autonomous underwater vehicles (AUVs is proposed in this paper. Due to the advantages at handling nonlinearities and couplings, the AUV model investigated here is for the first time constructed as a Hammerstein model with nonlinear feedback in the linear part. To better take the environment and sensor noises into consideration, the identification problem is concerned as an errors-in-variables (EIV one which means that the identification procedure is under general noise assumption. In order to make the algorithm recursively, propagator method (PM based subspace approach is extended into EIV framework to form the recursive identification method called PM-EIV algorithm. With several identification experiments carried out by the AUV simulation platform, the proposed algorithm demonstrates its effectiveness and feasibility.
Energy Technology Data Exchange (ETDEWEB)
Zhou, Ping; Song, Heda; Wang, Hong; Chai, Tianyou
2017-09-01
Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improve modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.
Evaporator modeling - A hybrid approach
International Nuclear Information System (INIS)
Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun
2009-01-01
In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis
HEDR modeling approach: Revision 1
International Nuclear Information System (INIS)
Shipler, D.B.; Napier, B.A.
1994-05-01
This report is a revision of the previous Hanford Environmental Dose Reconstruction (HEDR) Project modeling approach report. This revised report describes the methods used in performing scoping studies and estimating final radiation doses to real and representative individuals who lived in the vicinity of the Hanford Site. The scoping studies and dose estimates pertain to various environmental pathways during various periods of time. The original report discussed the concepts under consideration in 1991. The methods for estimating dose have been refined as understanding of existing data, the scope of pathways, and the magnitudes of dose estimates were evaluated through scoping studies
A Bayesian approach to model uncertainty
International Nuclear Information System (INIS)
Buslik, A.
1994-01-01
A Bayesian approach to model uncertainty is taken. For the case of a finite number of alternative models, the model uncertainty is equivalent to parameter uncertainty. A derivation based on Savage's partition problem is given
System Behavior Models: A Survey of Approaches
2016-06-01
OF FIGURES Spiral Model .................................................................................................3 Figure 1. Approaches in... spiral model was chosen for researching and structuring this thesis, shown in Figure 1. This approach allowed multiple iterations of source material...applications and refining through iteration. 3 Spiral Model Figure 1. D. SCOPE The research is limited to a literature review, limited
Nonlinear State Space Modeling and System Identification for Electrohydraulic Control
Directory of Open Access Journals (Sweden)
Jun Yan
2013-01-01
Full Text Available The paper deals with nonlinear modeling and identification of an electrohydraulic control system for improving its tracking performance. We build the nonlinear state space model for analyzing the highly nonlinear system and then develop a Hammerstein-Wiener (H-W model which consists of a static input nonlinear block with two-segment polynomial nonlinearities, a linear time-invariant dynamic block, and a static output nonlinear block with single polynomial nonlinearity to describe it. We simplify the H-W model into a linear-in-parameters structure by using the key term separation principle and then use a modified recursive least square method with iterative estimation of internal variables to identify all the unknown parameters simultaneously. It is found that the proposed H-W model approximates the actual system better than the independent Hammerstein, Wiener, and ARX models. The prediction error of the H-W model is about 13%, 54%, and 58% less than the Hammerstein, Wiener, and ARX models, respectively.
Learning Actions Models: Qualitative Approach
DEFF Research Database (Denmark)
Bolander, Thomas; Gierasimczuk, Nina
2015-01-01
In dynamic epistemic logic, actions are described using action models. In this paper we introduce a framework for studying learnability of action models from observations. We present first results concerning propositional action models. First we check two basic learnability criteria: finite ident...
Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P
2015-11-01
This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Global energy modeling - A biophysical approach
Energy Technology Data Exchange (ETDEWEB)
Dale, Michael
2010-09-15
This paper contrasts the standard economic approach to energy modelling with energy models using a biophysical approach. Neither of these approaches includes changing energy-returns-on-investment (EROI) due to declining resource quality or the capital intensive nature of renewable energy sources. Both of these factors will become increasingly important in the future. An extension to the biophysical approach is outlined which encompasses a dynamic EROI function that explicitly incorporates technological learning. The model is used to explore several scenarios of long-term future energy supply especially concerning the global transition to renewable energy sources in the quest for a sustainable energy system.
International Nuclear Information System (INIS)
Kara, Tolgay; Eker, Ilyas
2004-01-01
Modeling and identification of mechanical systems constitute an essential stage in practical control design and applications. Controllers commanding systems that operate at varying conditions or require high precision operation raise the need for a nonlinear approach in modeling and identification. Most mechanical systems used in industry are composed of masses moving under the action of position and velocity dependent forces. These forces exhibit nonlinear behavior in certain regions of operation. For a multi-mass rotational system, the nonlinearities, like Coulomb friction and dead zone, significantly influence the system operation when the rotation changes direction. The paper presents nonlinear modeling and identification of a DC motor rotating in two directions together with real time experiments. Linear and nonlinear models for the system are obtained for identification purposes, and the major nonlinearities in the system, such as Coulomb friction and dead zone, are investigated and integrated in the nonlinear model. The Hammerstein nonlinear system approach is used for identification of the nonlinear system model. Online identification of the linear and nonlinear system models is performed using the recursive least squares method. Results of the real time experiments are graphically and numerically presented, and the advantages of the nonlinear identification approach are revealed
A Unified Approach to Modeling and Programming
DEFF Research Database (Denmark)
Madsen, Ole Lehrmann; Møller-Pedersen, Birger
2010-01-01
of this paper is to go back to the future and get inspiration from SIMULA and propose a unied approach. In addition to reintroducing the contributions of SIMULA and the Scandinavian approach to object-oriented programming, we do this by discussing a number of issues in modeling and programming and argue3 why we......SIMULA was a language for modeling and programming and provided a unied approach to modeling and programming in contrast to methodologies based on structured analysis and design. The current development seems to be going in the direction of separation of modeling and programming. The goal...
Multiple Model Approaches to Modelling and Control,
DEFF Research Database (Denmark)
on the ease with which prior knowledge can be incorporated. It is interesting to note that researchers in Control Theory, Neural Networks,Statistics, Artificial Intelligence and Fuzzy Logic have more or less independently developed very similar modelling methods, calling them Local ModelNetworks, Operating......, and allows direct incorporation of high-level and qualitative plant knowledge into themodel. These advantages have proven to be very appealing for industrial applications, and the practical, intuitively appealing nature of the framework isdemonstrated in chapters describing applications of local methods...... to problems in the process industries, biomedical applications and autonomoussystems. The successful application of the ideas to demanding problems is already encouraging, but creative development of the basic framework isneeded to better allow the integration of human knowledge with automated learning...
Geometrical approach to fluid models
International Nuclear Information System (INIS)
Kuvshinov, B.N.; Schep, T.J.
1997-01-01
Differential geometry based upon the Cartan calculus of differential forms is applied to investigate invariant properties of equations that describe the motion of continuous media. The main feature of this approach is that physical quantities are treated as geometrical objects. The geometrical notion of invariance is introduced in terms of Lie derivatives and a general procedure for the construction of local and integral fluid invariants is presented. The solutions of the equations for invariant fields can be written in terms of Lagrange variables. A generalization of the Hamiltonian formalism for finite-dimensional systems to continuous media is proposed. Analogously to finite-dimensional systems, Hamiltonian fluids are introduced as systems that annihilate an exact two-form. It is shown that Euler and ideal, charged fluids satisfy this local definition of a Hamiltonian structure. A new class of scalar invariants of Hamiltonian fluids is constructed that generalizes the invariants that are related with gauge transformations and with symmetries (Noether). copyright 1997 American Institute of Physics
Current approaches to gene regulatory network modelling
Directory of Open Access Journals (Sweden)
Brazma Alvis
2007-09-01
Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.
Distributed simulation a model driven engineering approach
Topçu, Okan; Oğuztüzün, Halit; Yilmaz, Levent
2016-01-01
Backed by substantive case studies, the novel approach to software engineering for distributed simulation outlined in this text demonstrates the potent synergies between model-driven techniques, simulation, intelligent agents, and computer systems development.
Service creation: a model-based approach
Quartel, Dick; van Sinderen, Marten J.; Ferreira Pires, Luis
1999-01-01
This paper presents a model-based approach to support service creation. In this approach, services are assumed to be created from (available) software components. The creation process may involve multiple design steps in which the requested service is repeatedly decomposed into more detailed
Models of galaxies - The modal approach
International Nuclear Information System (INIS)
Lin, C.C.; Lowe, S.A.
1990-01-01
The general viability of the modal approach to the spiral structure in normal spirals and the barlike structure in certain barred spirals is discussed. The usefulness of the modal approach in the construction of models of such galaxies is examined, emphasizing the adoption of a model appropriate to observational data for both the spiral structure of a galaxy and its basic mass distribution. 44 refs
Multiscale approach to equilibrating model polymer melts
DEFF Research Database (Denmark)
Svaneborg, Carsten; Ali Karimi-Varzaneh, Hossein; Hojdis, Nils
2016-01-01
We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed...
Application of various FLD modelling approaches
Banabic, D.; Aretz, H.; Paraianu, L.; Jurco, P.
2005-07-01
This paper focuses on a comparison between different modelling approaches to predict the forming limit diagram (FLD) for sheet metal forming under a linear strain path using the recently introduced orthotropic yield criterion BBC2003 (Banabic D et al 2005 Int. J. Plasticity 21 493-512). The FLD models considered here are a finite element based approach, the well known Marciniak-Kuczynski model, the modified maximum force criterion according to Hora et al (1996 Proc. Numisheet'96 Conf. (Dearborn/Michigan) pp 252-6), Swift's diffuse (Swift H W 1952 J. Mech. Phys. Solids 1 1-18) and Hill's classical localized necking approach (Hill R 1952 J. Mech. Phys. Solids 1 19-30). The FLD of an AA5182-O aluminium sheet alloy has been determined experimentally in order to quantify the predictive capabilities of the models mentioned above.
Risk Modelling for Passages in Approach Channel
Directory of Open Access Journals (Sweden)
Leszek Smolarek
2013-01-01
Full Text Available Methods of multivariate statistics, stochastic processes, and simulation methods are used to identify and assess the risk measures. This paper presents the use of generalized linear models and Markov models to study risks to ships along the approach channel. These models combined with simulation testing are used to determine the time required for continuous monitoring of endangered objects or period at which the level of risk should be verified.
Set-Theoretic Approach to Maturity Models
DEFF Research Database (Denmark)
Lasrado, Lester Allan
Despite being widely accepted and applied, maturity models in Information Systems (IS) have been criticized for the lack of theoretical grounding, methodological rigor, empirical validations, and ignorance of multiple and non-linear paths to maturity. This PhD thesis focuses on addressing...... these criticisms by incorporating recent developments in configuration theory, in particular application of set-theoretic approaches. The aim is to show the potential of employing a set-theoretic approach for maturity model research and empirically demonstrating equifinal paths to maturity. Specifically...... methodological guidelines consisting of detailed procedures to systematically apply set theoretic approaches for maturity model research and provides demonstrations of it application on three datasets. The thesis is a collection of six research papers that are written in a sequential manner. The first paper...
Mathematical Modeling Approaches in Plant Metabolomics.
Fürtauer, Lisa; Weiszmann, Jakob; Weckwerth, Wolfram; Nägele, Thomas
2018-01-01
The experimental analysis of a plant metabolome typically results in a comprehensive and multidimensional data set. To interpret metabolomics data in the context of biochemical regulation and environmental fluctuation, various approaches of mathematical modeling have been developed and have proven useful. In this chapter, a general introduction to mathematical modeling is presented and discussed in context of plant metabolism. A particular focus is laid on the suitability of mathematical approaches to functionally integrate plant metabolomics data in a metabolic network and combine it with other biochemical or physiological parameters.
SLS Navigation Model-Based Design Approach
Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas
2018-01-01
The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and
Stochastic approaches to inflation model building
International Nuclear Information System (INIS)
Ramirez, Erandy; Liddle, Andrew R.
2005-01-01
While inflation gives an appealing explanation of observed cosmological data, there are a wide range of different inflation models, providing differing predictions for the initial perturbations. Typically models are motivated either by fundamental physics considerations or by simplicity. An alternative is to generate large numbers of models via a random generation process, such as the flow equations approach. The flow equations approach is known to predict a definite structure to the observational predictions. In this paper, we first demonstrate a more efficient implementation of the flow equations exploiting an analytic solution found by Liddle (2003). We then consider alternative stochastic methods of generating large numbers of inflation models, with the aim of testing whether the structures generated by the flow equations are robust. We find that while typically there remains some concentration of points in the observable plane under the different methods, there is significant variation in the predictions amongst the methods considered
Model validation: a systemic and systematic approach
International Nuclear Information System (INIS)
Sheng, G.; Elzas, M.S.; Cronhjort, B.T.
1993-01-01
The term 'validation' is used ubiquitously in association with the modelling activities of numerous disciplines including social, political natural, physical sciences, and engineering. There is however, a wide range of definitions which give rise to very different interpretations of what activities the process involves. Analyses of results from the present large international effort in modelling radioactive waste disposal systems illustrate the urgent need to develop a common approach to model validation. Some possible explanations are offered to account for the present state of affairs. The methodology developed treats model validation and code verification in a systematic fashion. In fact, this approach may be regarded as a comprehensive framework to assess the adequacy of any simulation study. (author)
A Conceptual Modeling Approach for OLAP Personalization
Garrigós, Irene; Pardillo, Jesús; Mazón, Jose-Norberto; Trujillo, Juan
Data warehouses rely on multidimensional models in order to provide decision makers with appropriate structures to intuitively analyze data with OLAP technologies. However, data warehouses may be potentially large and multidimensional structures become increasingly complex to be understood at a glance. Even if a departmental data warehouse (also known as data mart) is used, these structures would be also too complex. As a consequence, acquiring the required information is more costly than expected and decision makers using OLAP tools may get frustrated. In this context, current approaches for data warehouse design are focused on deriving a unique OLAP schema for all analysts from their previously stated information requirements, which is not enough to lighten the complexity of the decision making process. To overcome this drawback, we argue for personalizing multidimensional models for OLAP technologies according to the continuously changing user characteristics, context, requirements and behaviour. In this paper, we present a novel approach to personalizing OLAP systems at the conceptual level based on the underlying multidimensional model of the data warehouse, a user model and a set of personalization rules. The great advantage of our approach is that a personalized OLAP schema is provided for each decision maker contributing to better satisfy their specific analysis needs. Finally, we show the applicability of our approach through a sample scenario based on our CASE tool for data warehouse development.
Variational approach to chiral quark models
Energy Technology Data Exchange (ETDEWEB)
Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira
1987-03-01
A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation.
A variational approach to chiral quark models
International Nuclear Information System (INIS)
Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira.
1987-01-01
A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation. (author)
A Set Theoretical Approach to Maturity Models
DEFF Research Database (Denmark)
Lasrado, Lester; Vatrapu, Ravi; Andersen, Kim Normann
2016-01-01
characterized by equifinality, multiple conjunctural causation, and case diversity. We prescribe methodological guidelines consisting of a six-step procedure to systematically apply set theoretic methods to conceptualize, develop, and empirically derive maturity models and provide a demonstration......Maturity Model research in IS has been criticized for the lack of theoretical grounding, methodological rigor, empirical validations, and ignorance of multiple and non-linear paths to maturity. To address these criticisms, this paper proposes a novel set-theoretical approach to maturity models...
A hybrid modeling approach for option pricing
Hajizadeh, Ehsan; Seifi, Abbas
2011-11-01
The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.
Heat transfer modeling an inductive approach
Sidebotham, George
2015-01-01
This innovative text emphasizes a "less-is-more" approach to modeling complicated systems such as heat transfer by treating them first as "1-node lumped models" that yield simple closed-form solutions. The author develops numerical techniques for students to obtain more detail, but also trains them to use the techniques only when simpler approaches fail. Covering all essential methods offered in traditional texts, but with a different order, Professor Sidebotham stresses inductive thinking and problem solving as well as a constructive understanding of modern, computer-based practice. Readers learn to develop their own code in the context of the material, rather than just how to use packaged software, offering a deeper, intrinsic grasp behind models of heat transfer. Developed from over twenty-five years of lecture notes to teach students of mechanical and chemical engineering at The Cooper Union for the Advancement of Science and Art, the book is ideal for students and practitioners across engineering discipl...
Nonperturbative approach to the attractive Hubbard model
International Nuclear Information System (INIS)
Allen, S.; Tremblay, A.-M. S.
2001-01-01
A nonperturbative approach to the single-band attractive Hubbard model is presented in the general context of functional-derivative approaches to many-body theories. As in previous work on the repulsive model, the first step is based on a local-field-type ansatz, on enforcement of the Pauli principle and a number of crucial sumrules. The Mermin-Wagner theorem in two dimensions is automatically satisfied. At this level, two-particle self-consistency has been achieved. In the second step of the approximation, an improved expression for the self-energy is obtained by using the results of the first step in an exact expression for the self-energy, where the high- and low-frequency behaviors appear separately. The result is a cooperon-like formula. The required vertex corrections are included in this self-energy expression, as required by the absence of a Migdal theorem for this problem. Other approaches to the attractive Hubbard model are critically compared. Physical consequences of the present approach and agreement with Monte Carlo simulations are demonstrated in the accompanying paper (following this one)
Quasirelativistic quark model in quasipotential approach
Matveev, V A; Savrin, V I; Sissakian, A N
2002-01-01
The relativistic particles interaction is described within the frames of quasipotential approach. The presentation is based on the so called covariant simultaneous formulation of the quantum field theory, where by the theory is considered on the spatial-like three-dimensional hypersurface in the Minkowski space. Special attention is paid to the methods of plotting various quasipotentials as well as to the applications of the quasipotential approach to describing the characteristics of the relativistic particles interaction in the quark models, namely: the hadrons elastic scattering amplitudes, the mass spectra and widths mesons decays, the cross sections of the deep inelastic leptons scattering on the hadrons
A multiscale modeling approach for biomolecular systems
Energy Technology Data Exchange (ETDEWEB)
Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)
2015-04-15
This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.
A new approach for developing adjoint models
Farrell, P. E.; Funke, S. W.
2011-12-01
Many data assimilation algorithms rely on the availability of gradients of misfit functionals, which can be efficiently computed with adjoint models. However, the development of an adjoint model for a complex geophysical code is generally very difficult. Algorithmic differentiation (AD, also called automatic differentiation) offers one strategy for simplifying this task: it takes the abstraction that a model is a sequence of primitive instructions, each of which may be differentiated in turn. While extremely successful, this low-level abstraction runs into time-consuming difficulties when applied to the whole codebase of a model, such as differentiating through linear solves, model I/O, calls to external libraries, language features that are unsupported by the AD tool, and the use of multiple programming languages. While these difficulties can be overcome, it requires a large amount of technical expertise and an intimate familiarity with both the AD tool and the model. An alternative to applying the AD tool to the whole codebase is to assemble the discrete adjoint equations and use these to compute the necessary gradients. With this approach, the AD tool must be applied to the nonlinear assembly operators, which are typically small, self-contained units of the codebase. The disadvantage of this approach is that the assembly of the discrete adjoint equations is still very difficult to perform correctly, especially for complex multiphysics models that perform temporal integration; as it stands, this approach is as difficult and time-consuming as applying AD to the whole model. In this work, we have developed a library which greatly simplifies and automates the alternate approach of assembling the discrete adjoint equations. We propose a complementary, higher-level abstraction to that of AD: that a model is a sequence of linear solves. The developer annotates model source code with library calls that build a 'tape' of the operators involved and their dependencies, and
Eutrophication Modeling Using Variable Chlorophyll Approach
International Nuclear Information System (INIS)
Abdolabadi, H.; Sarang, A.; Ardestani, M.; Mahjoobi, E.
2016-01-01
In this study, eutrophication was investigated in Lake Ontario to identify the interactions among effective drivers. The complexity of such phenomenon was modeled using a system dynamics approach based on a consideration of constant and variable stoichiometric ratios. The system dynamics approach is a powerful tool for developing object-oriented models to simulate complex phenomena that involve feedback effects. Utilizing stoichiometric ratios is a method for converting the concentrations of state variables. During the physical segmentation of the model, Lake Ontario was divided into two layers, i.e., the epilimnion and hypolimnion, and differential equations were developed for each layer. The model structure included 16 state variables related to phytoplankton, herbivorous zooplankton, carnivorous zooplankton, ammonium, nitrate, dissolved phosphorus, and particulate and dissolved carbon in the epilimnion and hypolimnion during a time horizon of one year. The results of several tests to verify the model, close to 1 Nash-Sutcliff coefficient (0.98), the data correlation coefficient (0.98), and lower standard errors (0.96), have indicated well-suited model’s efficiency. The results revealed that there were significant differences in the concentrations of the state variables in constant and variable stoichiometry simulations. Consequently, the consideration of variable stoichiometric ratios in algae and nutrient concentration simulations may be applied in future modeling studies to enhance the accuracy of the results and reduce the likelihood of inefficient control policies.
Hong, Sehee; Kim, Soyoung
2018-01-01
There are basically two modeling approaches applicable to analyzing an actor-partner interdependence model: the multilevel modeling (hierarchical linear model) and the structural equation modeling. This article explains how to use these two models in analyzing an actor-partner interdependence model and how these two approaches work differently. As an empirical example, marital conflict data were used to analyze an actor-partner interdependence model. The multilevel modeling and the structural equation modeling produced virtually identical estimates for a basic model. However, the structural equation modeling approach allowed more realistic assumptions on measurement errors and factor loadings, rendering better model fit indices.
Evolutionary modeling-based approach for model errors correction
Directory of Open Access Journals (Sweden)
S. Q. Wan
2012-08-01
Full Text Available The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963 equation as a prediction model and the Lorenz equation with a periodic evolutionary function as an accurate representation of reality to generate "observational data."
On the basis of the intelligent features of evolutionary modeling (EM, including self-organization, self-adaptive and self-learning, the dynamic information contained in the historical data can be identified and extracted by computer automatically. Thereby, a new approach is proposed to estimate model errors based on EM in the present paper. Numerical tests demonstrate the ability of the new approach to correct model structural errors. In fact, it can actualize the combination of the statistics and dynamics to certain extent.
MODELS OF TECHNOLOGY ADOPTION: AN INTEGRATIVE APPROACH
Directory of Open Access Journals (Sweden)
Andrei OGREZEANU
2015-06-01
Full Text Available The interdisciplinary study of information technology adoption has developed rapidly over the last 30 years. Various theoretical models have been developed and applied such as: the Technology Acceptance Model (TAM, Innovation Diffusion Theory (IDT, Theory of Planned Behavior (TPB, etc. The result of these many years of research is thousands of contributions to the field, which, however, remain highly fragmented. This paper develops a theoretical model of technology adoption by integrating major theories in the field: primarily IDT, TAM, and TPB. To do so while avoiding mess, an approach that goes back to basics in independent variable type’s development is proposed; emphasizing: 1 the logic of classification, and 2 psychological mechanisms behind variable types. Once developed these types are then populated with variables originating in empirical research. Conclusions are developed on which types are underpopulated and present potential for future research. I end with a set of methodological recommendations for future application of the model.
Interfacial Fluid Mechanics A Mathematical Modeling Approach
Ajaev, Vladimir S
2012-01-01
Interfacial Fluid Mechanics: A Mathematical Modeling Approach provides an introduction to mathematical models of viscous flow used in rapidly developing fields of microfluidics and microscale heat transfer. The basic physical effects are first introduced in the context of simple configurations and their relative importance in typical microscale applications is discussed. Then,several configurations of importance to microfluidics, most notably thin films/droplets on substrates and confined bubbles, are discussed in detail. Topics from current research on electrokinetic phenomena, liquid flow near structured solid surfaces, evaporation/condensation, and surfactant phenomena are discussed in the later chapters. This book also: Discusses mathematical models in the context of actual applications such as electrowetting Includes unique material on fluid flow near structured surfaces and phase change phenomena Shows readers how to solve modeling problems related to microscale multiphase flows Interfacial Fluid Me...
A new modelling approach for zooplankton behaviour
Keiyu, A. Y.; Yamazaki, H.; Strickler, J. R.
We have developed a new simulation technique to model zooplankton behaviour. The approach utilizes neither the conventional artificial intelligence nor neural network methods. We have designed an adaptive behaviour network, which is similar to BEER [(1990) Intelligence as an adaptive behaviour: an experiment in computational neuroethology, Academic Press], based on observational studies of zooplankton behaviour. The proposed method is compared with non- "intelligent" models—random walk and correlated walk models—as well as observed behaviour in a laboratory tank. Although the network is simple, the model exhibits rich behavioural patterns similar to live copepods.
Continuum modeling an approach through practical examples
Muntean, Adrian
2015-01-01
This book develops continuum modeling skills and approaches the topic from three sides: (1) derivation of global integral laws together with the associated local differential equations, (2) design of constitutive laws and (3) modeling boundary processes. The focus of this presentation lies on many practical examples covering aspects such as coupled flow, diffusion and reaction in porous media or microwave heating of a pizza, as well as traffic issues in bacterial colonies and energy harvesting from geothermal wells. The target audience comprises primarily graduate students in pure and applied mathematics as well as working practitioners in engineering who are faced by nonstandard rheological topics like those typically arising in the food industry.
Global Environmental Change: An integrated modelling approach
International Nuclear Information System (INIS)
Den Elzen, M.
1993-01-01
Two major global environmental problems are dealt with: climate change and stratospheric ozone depletion (and their mutual interactions), briefly surveyed in part 1. In Part 2 a brief description of the integrated modelling framework IMAGE 1.6 is given. Some specific parts of the model are described in more detail in other Chapters, e.g. the carbon cycle model, the atmospheric chemistry model, the halocarbon model, and the UV-B impact model. In Part 3 an uncertainty analysis of climate change and stratospheric ozone depletion is presented (Chapter 4). Chapter 5 briefly reviews the social and economic uncertainties implied by future greenhouse gas emissions. Chapters 6 and 7 describe a model and sensitivity analysis pertaining to the scientific uncertainties and/or lacunae in the sources and sinks of methane and carbon dioxide, and their biogeochemical feedback processes. Chapter 8 presents an uncertainty and sensitivity analysis of the carbon cycle model, the halocarbon model, and the IMAGE model 1.6 as a whole. Part 4 presents the risk assessment methodology as applied to the problems of climate change and stratospheric ozone depletion more specifically. In Chapter 10, this methodology is used as a means with which to asses current ozone policy and a wide range of halocarbon policies. Chapter 11 presents and evaluates the simulated globally-averaged temperature and sea level rise (indicators) for the IPCC-1990 and 1992 scenarios, concluding with a Low Risk scenario, which would meet the climate targets. Chapter 12 discusses the impact of sea level rise on the frequency of the Dutch coastal defence system (indicator) for the IPCC-1990 scenarios. Chapter 13 presents projections of mortality rates due to stratospheric ozone depletion based on model simulations employing the UV-B chain model for a number of halocarbon policies. Chapter 14 presents an approach for allocating future emissions of CO 2 among regions. (Abstract Truncated)
Crime Modeling using Spatial Regression Approach
Saleh Ahmar, Ansari; Adiatma; Kasim Aidid, M.
2018-01-01
Act of criminality in Indonesia increased both variety and quantity every year. As murder, rape, assault, vandalism, theft, fraud, fencing, and other cases that make people feel unsafe. Risk of society exposed to crime is the number of reported cases in the police institution. The higher of the number of reporter to the police institution then the number of crime in the region is increasing. In this research, modeling criminality in South Sulawesi, Indonesia with the dependent variable used is the society exposed to the risk of crime. Modelling done by area approach is the using Spatial Autoregressive (SAR) and Spatial Error Model (SEM) methods. The independent variable used is the population density, the number of poor population, GDP per capita, unemployment and the human development index (HDI). Based on the analysis using spatial regression can be shown that there are no dependencies spatial both lag or errors in South Sulawesi.
Merging Digital Surface Models Implementing Bayesian Approaches
Sadeq, H.; Drummond, J.; Li, Z.
2016-06-01
In this research different DSMs from different sources have been merged. The merging is based on a probabilistic model using a Bayesian Approach. The implemented data have been sourced from very high resolution satellite imagery sensors (e.g. WorldView-1 and Pleiades). It is deemed preferable to use a Bayesian Approach when the data obtained from the sensors are limited and it is difficult to obtain many measurements or it would be very costly, thus the problem of the lack of data can be solved by introducing a priori estimations of data. To infer the prior data, it is assumed that the roofs of the buildings are specified as smooth, and for that purpose local entropy has been implemented. In addition to the a priori estimations, GNSS RTK measurements have been collected in the field which are used as check points to assess the quality of the DSMs and to validate the merging result. The model has been applied in the West-End of Glasgow containing different kinds of buildings, such as flat roofed and hipped roofed buildings. Both quantitative and qualitative methods have been employed to validate the merged DSM. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the well established Maximum Likelihood model and showed similar quantitative statistical results and better qualitative results. Although the proposed model has been applied on DSMs that were derived from satellite imagery, it can be applied to any other sourced DSMs.
MERGING DIGITAL SURFACE MODELS IMPLEMENTING BAYESIAN APPROACHES
Directory of Open Access Journals (Sweden)
H. Sadeq
2016-06-01
Full Text Available In this research different DSMs from different sources have been merged. The merging is based on a probabilistic model using a Bayesian Approach. The implemented data have been sourced from very high resolution satellite imagery sensors (e.g. WorldView-1 and Pleiades. It is deemed preferable to use a Bayesian Approach when the data obtained from the sensors are limited and it is difficult to obtain many measurements or it would be very costly, thus the problem of the lack of data can be solved by introducing a priori estimations of data. To infer the prior data, it is assumed that the roofs of the buildings are specified as smooth, and for that purpose local entropy has been implemented. In addition to the a priori estimations, GNSS RTK measurements have been collected in the field which are used as check points to assess the quality of the DSMs and to validate the merging result. The model has been applied in the West-End of Glasgow containing different kinds of buildings, such as flat roofed and hipped roofed buildings. Both quantitative and qualitative methods have been employed to validate the merged DSM. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the well established Maximum Likelihood model and showed similar quantitative statistical results and better qualitative results. Although the proposed model has been applied on DSMs that were derived from satellite imagery, it can be applied to any other sourced DSMs.
Energy Technology Data Exchange (ETDEWEB)
Chandrasekhar Potluri,; Madhavi Anugolu; Marco P. Schoen; D. Subbaram Naidu
2013-08-01
In this work, an array of three surface Electrography (sEMG) sensors are used to acquired muscle extension and contraction signals for 18 healthy test subjects. The skeletal muscle force is estimated using the acquired sEMG signals and a Non-linear Wiener Hammerstein model, relating the two signals in a dynamic fashion. The model is obtained from using System Identification (SI) algorithm. The obtained force models for each sensor are fused using a proposed fuzzy logic concept with the intent to improve the force estimation accuracy and resilience to sensor failure or misalignment. For the fuzzy logic inference system, the sEMG entropy, the relative error, and the correlation of the force signals are considered for defining the membership functions. The proposed fusion algorithm yields an average of 92.49% correlation between the actual force and the overall estimated force output. In addition, the proposed fusionbased approach is implemented on a test platform. Experiments indicate an improvement in finger/hand force estimation.
A nationwide modelling approach to decommissioning - 16182
International Nuclear Information System (INIS)
Kelly, Bernard; Lowe, Andy; Mort, Paul
2009-01-01
In this paper we describe a proposed UK national approach to modelling decommissioning. For the first time, we shall have an insight into optimizing the safety and efficiency of a national decommissioning strategy. To do this we use the General Case Integrated Waste Algorithm (GIA), a universal model of decommissioning nuclear plant, power plant, waste arisings and the associated knowledge capture. The model scales from individual items of plant through cells, groups of cells, buildings, whole sites and then on up to a national scale. We describe the national vision for GIA which can be broken down into three levels: 1) the capture of the chronological order of activities that an experienced decommissioner would use to decommission any nuclear facility anywhere in the world - this is Level 1 of GIA; 2) the construction of an Operational Research (OR) model based on Level 1 to allow rapid what if scenarios to be tested quickly (Level 2); 3) the construction of a state of the art knowledge capture capability that allows future generations to learn from our current decommissioning experience (Level 3). We show the progress to date in developing GIA in levels 1 and 2. As part of level 1, GIA has assisted in the development of an IMechE professional decommissioning qualification. Furthermore, we describe GIA as the basis of a UK-Owned database of decommissioning norms for such things as costs, productivity, durations etc. From level 2, we report on a pilot study that has successfully tested the basic principles for the OR numerical simulation of the algorithm. We then highlight the advantages of applying the OR modelling approach nationally. In essence, a series of 'what if...' scenarios can be tested that will improve the safety and efficiency of decommissioning. (authors)
Modeling in transport phenomena a conceptual approach
Tosun, Ismail
2007-01-01
Modeling in Transport Phenomena, Second Edition presents and clearly explains with example problems the basic concepts and their applications to fluid flow, heat transfer, mass transfer, chemical reaction engineering and thermodynamics. A balanced approach is presented between analysis and synthesis, students will understand how to use the solution in engineering analysis. Systematic derivations of the equations and the physical significance of each term are given in detail, for students to easily understand and follow up the material. There is a strong incentive in science and engineering to
Nuclear physics for applications. A model approach
International Nuclear Information System (INIS)
Prussin, S.G.
2007-01-01
Written by a researcher and teacher with experience at top institutes in the US and Europe, this textbook provides advanced undergraduates minoring in physics with working knowledge of the principles of nuclear physics. Simplifying models and approaches reveal the essence of the principles involved, with the mathematical and quantum mechanical background integrated in the text where it is needed and not relegated to the appendices. The practicality of the book is enhanced by numerous end-of-chapter problems and solutions available on the Wiley homepage. (orig.)
Pedagogic process modeling: Humanistic-integrative approach
Directory of Open Access Journals (Sweden)
Boritko Nikolaj M.
2007-01-01
Full Text Available The paper deals with some current problems of modeling the dynamics of the subject-features development of the individual. The term "process" is considered in the context of the humanistic-integrative approach, in which the principles of self education are regarded as criteria for efficient pedagogic activity. Four basic characteristics of the pedagogic process are pointed out: intentionality reflects logicality and regularity of the development of the process; discreteness (stageability in dicates qualitative stages through which the pedagogic phenomenon passes; nonlinearity explains the crisis character of pedagogic processes and reveals inner factors of self-development; situationality requires a selection of pedagogic conditions in accordance with the inner factors, which would enable steering the pedagogic process. Offered are two steps for singling out a particular stage and the algorithm for developing an integrative model for it. The suggested conclusions might be of use for further theoretic research, analyses of educational practices and for realistic predicting of pedagogical phenomena. .
Behavioral modelling and predistortion of wideband wireless transmitters
Ghannouchi, Fadhel M; Helaoui, Mohamed
2015-01-01
Covers theoretical and practical aspects related to the behavioral modelling and predistortion of wireless transmitters and power amplifiers. It includes simulation software that enables the users to apply the theory presented in the book. In the first section, the reader is given the general background of nonlinear dynamic systems along with their behavioral modelling from all its aspects. In the second part, a comprehensive compilation of behavioral models formulations and structures is provided including memory polynomial based models, box oriented models such as Hammerstein-based and Wiene
A novel approach to pipeline tensioner modeling
Energy Technology Data Exchange (ETDEWEB)
O' Grady, Robert; Ilie, Daniel; Lane, Michael [MCS Software Division, Galway (Ireland)
2009-07-01
As subsea pipeline developments continue to move into deep and ultra-deep water locations, there is an increasing need for the accurate prediction of expected pipeline fatigue life. A significant factor that must be considered as part of this process is the fatigue damage sustained by the pipeline during installation. The magnitude of this installation-related damage is governed by a number of different agents, one of which is the dynamic behavior of the tensioner systems during pipe-laying operations. There are a variety of traditional finite element methods for representing dynamic tensioner behavior. These existing methods, while basic in nature, have been proven to provide adequate forecasts in terms of the dynamic variation in typical installation parameters such as top tension and sagbend/overbend strain. However due to the simplicity of these current approaches, some of them tend to over-estimate the frequency of tensioner pay out/in under dynamic loading. This excessive level of pay out/in motion results in the prediction of additional stress cycles at certain roller beds, which in turn leads to the prediction of unrealistic fatigue damage to the pipeline. This unwarranted fatigue damage then equates to an over-conservative value for the accumulated damage experienced by a pipeline weld during installation, and so leads to a reduction in the estimated fatigue life for the pipeline. This paper describes a novel approach to tensioner modeling which allows for greater control over the velocity of dynamic tensioner pay out/in and so provides a more accurate estimation of fatigue damage experienced by the pipeline during installation. The paper reports on a case study, as outlined in the proceeding section, in which a comparison is made between results from this new tensioner model and from a more conventional approach. The comparison considers typical installation parameters as well as an in-depth look at the predicted fatigue damage for the two methods
Modelling nonlinear viscoelastic behaviours of loudspeaker suspensions-like structures
Maillou, Balbine; Lotton, Pierrick; Novak, Antonin; Simon, Laurent
2018-03-01
Mechanical properties of an electrodynamic loudspeaker are mainly determined by its suspensions (surround and spider) that behave nonlinearly and typically exhibit frequency dependent viscoelastic properties such as creep effect. The paper aims at characterizing the mechanical behaviour of electrodynamic loudspeaker suspensions at low frequencies using nonlinear identification techniques developed in recent years. A Generalized Hammerstein based model can take into account both frequency dependency and nonlinear properties. As shown in the paper, the model generalizes existing nonlinear or viscoelastic models commonly used for loudspeaker modelling. It is further experimentally shown that a possible input-dependent law may play a key role in suspension characterization.
Approaches and models of intercultural education
Directory of Open Access Journals (Sweden)
Iván Manuel Sánchez Fontalvo
2013-10-01
Full Text Available Needed to be aware of the need to build an intercultural society, awareness must be assumed in all social spheres, where stands the role play education. A role of transcendental, since it must promote educational spaces to form people with virtues and powers that allow them to live together / as in multicultural contexts and social diversities (sometimes uneven in an increasingly globalized and interconnected world, and foster the development of feelings of civic belonging shared before the neighborhood, city, region and country, allowing them concern and critical judgement to marginalization, poverty, misery and inequitable distribution of wealth, causes of structural violence, but at the same time, wanting to work for the welfare and transformation of these scenarios. Since these budgets, it is important to know the approaches and models of intercultural education that have been developed so far, analysing their impact on the contexts educational where apply.
Transport modeling: An artificial immune system approach
Directory of Open Access Journals (Sweden)
Teodorović Dušan
2006-01-01
Full Text Available This paper describes an artificial immune system approach (AIS to modeling time-dependent (dynamic, real time transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies for different antigens (different traffic "scenarios". This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.
System approach to modeling of industrial technologies
Toropov, V. S.; Toropov, E. S.
2018-03-01
The authors presented a system of methods for modeling and improving industrial technologies. The system consists of information and software. The information part is structured information about industrial technologies. The structure has its template. The template has several essential categories used to improve the technological process and eliminate weaknesses in the process chain. The base category is the physical effect that takes place when the technical process proceeds. The programming part of the system can apply various methods of creative search to the content stored in the information part of the system. These methods pay particular attention to energy transformations in the technological process. The system application will allow us to systematize the approach to improving technologies and obtaining new technical solutions.
ECOMOD - An ecological approach to radioecological modelling
International Nuclear Information System (INIS)
Sazykina, Tatiana G.
2000-01-01
A unified methodology is proposed to simulate the dynamic processes of radionuclide migration in aquatic food chains in parallel with their stable analogue elements. The distinguishing feature of the unified radioecological/ecological approach is the description of radionuclide migration along with dynamic equations for the ecosystem. The ability of the methodology to predict the results of radioecological experiments is demonstrated by an example of radionuclide (iron group) accumulation by a laboratory culture of the algae Platymonas viridis. Based on the unified methodology, the 'ECOMOD' radioecological model was developed to simulate dynamic radioecological processes in aquatic ecosystems. It comprises three basic modules, which are operated as a set of inter-related programs. The 'ECOSYSTEM' module solves non-linear ecological equations, describing the biomass dynamics of essential ecosystem components. The 'RADIONUCLIDE DISTRIBUTION' module calculates the radionuclide distribution in abiotic and biotic components of the aquatic ecosystem. The 'DOSE ASSESSMENT' module calculates doses to aquatic biota and doses to man from aquatic food chains. The application of the ECOMOD model to reconstruct the radionuclide distribution in the Chernobyl Cooling Pond ecosystem in the early period after the accident shows good agreement with observations
Modelling Approach In Islamic Architectural Designs
Directory of Open Access Journals (Sweden)
Suhaimi Salleh
2014-06-01
Full Text Available Architectural designs contribute as one of the main factors that should be considered in minimizing negative impacts in planning and structural development in buildings such as in mosques. In this paper, the ergonomics perspective is revisited which hence focuses on the conditional factors involving organisational, psychological, social and population as a whole. This paper tries to highlight the functional and architectural integration with ecstatic elements in the form of decorative and ornamental outlay as well as incorporating the building structure such as wall, domes and gates. This paper further focuses the mathematical aspects of the architectural designs such as polar equations and the golden ratio. These designs are modelled into mathematical equations of various forms, while the golden ratio in mosque is verified using two techniques namely, the geometric construction and the numerical method. The exemplary designs are taken from theSabah Bandaraya Mosque in Likas, Kota Kinabalu and the Sarawak State Mosque in Kuching,while the Universiti Malaysia Sabah Mosque is used for the Golden Ratio. Results show thatIslamic architectural buildings and designs have long had mathematical concepts and techniques underlying its foundation, hence, a modelling approach is needed to rejuvenate these Islamic designs.
An integrated approach to permeability modeling using micro-models
Energy Technology Data Exchange (ETDEWEB)
Hosseini, A.H.; Leuangthong, O.; Deutsch, C.V. [Society of Petroleum Engineers, Canadian Section, Calgary, AB (Canada)]|[Alberta Univ., Edmonton, AB (Canada)
2008-10-15
An important factor in predicting the performance of steam assisted gravity drainage (SAGD) well pairs is the spatial distribution of permeability. Complications that make the inference of a reliable porosity-permeability relationship impossible include the presence of short-scale variability in sand/shale sequences; preferential sampling of core data; and uncertainty in upscaling parameters. Micro-modelling is a simple and effective method for overcoming these complications. This paper proposed a micro-modeling approach to account for sampling bias, small laminated features with high permeability contrast, and uncertainty in upscaling parameters. The paper described the steps and challenges of micro-modeling and discussed the construction of binary mixture geo-blocks; flow simulation and upscaling; extended power law formalism (EPLF); and the application of micro-modeling and EPLF. An extended power-law formalism to account for changes in clean sand permeability as a function of macroscopic shale content was also proposed and tested against flow simulation results. There was close agreement between the model and simulation results. The proposed methodology was also applied to build the porosity-permeability relationship for laminated and brecciated facies of McMurray oil sands. Experimental data was in good agreement with the experimental data. 8 refs., 17 figs.
Risk communication: a mental models approach
National Research Council Canada - National Science Library
Morgan, M. Granger (Millett Granger)
2002-01-01
... information about risks. The procedure uses approaches from risk and decision analysis to identify the most relevant information; it also uses approaches from psychology and communication theory to ensure that its message is understood. This book is written in nontechnical terms, designed to make the approach feasible for anyone willing to try it. It is illustrat...
A Multi-Model Approach for System Diagnosis
DEFF Research Database (Denmark)
Niemann, Hans Henrik; Poulsen, Niels Kjølstad; Bækgaard, Mikkel Ask Buur
2007-01-01
A multi-model approach for system diagnosis is presented in this paper. The relation with fault diagnosis as well as performance validation is considered. The approach is based on testing a number of pre-described models and find which one is the best. It is based on an active approach......,i.e. an auxiliary input to the system is applied. The multi-model approach is applied on a wind turbine system....
Computational and Game-Theoretic Approaches for Modeling Bounded Rationality
L. Waltman (Ludo)
2011-01-01
textabstractThis thesis studies various computational and game-theoretic approaches to economic modeling. Unlike traditional approaches to economic modeling, the approaches studied in this thesis do not rely on the assumption that economic agents behave in a fully rational way. Instead, economic
A Discrete Monetary Economic Growth Model with the MIU Approach
Directory of Open Access Journals (Sweden)
Wei-Bin Zhang
2008-01-01
Full Text Available This paper proposes an alternative approach to economic growth with money. The production side is the same as the Solow model, the Ramsey model, and the Tobin model. But we deal with behavior of consumers differently from the traditional approaches. The model is influenced by the money-in-the-utility (MIU approach in monetary economics. It provides a mechanism of endogenous saving which the Solow model lacks and avoids the assumption of adding up utility over a period of time upon which the Ramsey approach is based.
Mathematical Modelling Approach in Mathematics Education
Arseven, Ayla
2015-01-01
The topic of models and modeling has come to be important for science and mathematics education in recent years. The topic of "Modeling" topic is especially important for examinations such as PISA which is conducted at an international level and measures a student's success in mathematics. Mathematical modeling can be defined as using…
A Multivariate Approach to Functional Neuro Modeling
DEFF Research Database (Denmark)
Mørch, Niels J.S.
1998-01-01
by the application of linear and more flexible, nonlinear microscopic regression models to a real-world dataset. The dependency of model performance, as quantified by generalization error, on model flexibility and training set size is demonstrated, leading to the important realization that no uniformly optimal model......, provides the basis for a generalization theoretical framework relating model performance to model complexity and dataset size. Briefly summarized the major topics discussed in the thesis include: - An introduction of the representation of functional datasets by pairs of neuronal activity patterns...... exists. - Model visualization and interpretation techniques. The simplicity of this task for linear models contrasts the difficulties involved when dealing with nonlinear models. Finally, a visualization technique for nonlinear models is proposed. A single observation emerges from the thesis...
Rival approaches to mathematical modelling in immunology
Andrew, Sarah M.; Baker, Christopher T. H.; Bocharov, Gennady A.
2007-08-01
In order to formulate quantitatively correct mathematical models of the immune system, one requires an understanding of immune processes and familiarity with a range of mathematical techniques. Selection of an appropriate model requires a number of decisions to be made, including a choice of the modelling objectives, strategies and techniques and the types of model considered as candidate models. The authors adopt a multidisciplinary perspective.
A hybrid agent-based approach for modeling microbiological systems.
Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing
2008-11-21
Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.
Numerical modelling approach for mine backfill
Indian Academy of Sciences (India)
Muhammad Zaka Emad
2017-07-24
Jul 24, 2017 ... conditions. This paper discusses a numerical modelling strategy for modelling mine backfill material. The .... placed in an ore pass that leads the ore to the ore bin and crusher, from ... 1 year, depending on the mine plan.
Uncertainty in biology a computational modeling approach
Gomez-Cabrero, David
2016-01-01
Computational modeling of biomedical processes is gaining more and more weight in the current research into the etiology of biomedical problems and potential treatment strategies. Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process. This book wants to address four main issues related to the building and validation of computational models of biomedical processes: Modeling establishment under uncertainty Model selection and parameter fitting Sensitivity analysis and model adaptation Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples. This book is intended for graduate stude...
OILMAP: A global approach to spill modeling
International Nuclear Information System (INIS)
Spaulding, M.L.; Howlett, E.; Anderson, E.; Jayko, K.
1992-01-01
OILMAP is an oil spill model system suitable for use in both rapid response mode and long-range contingency planning. It was developed for a personal computer and employs full-color graphics to enter data, set up spill scenarios, and view model predictions. The major components of OILMAP include environmental data entry and viewing capabilities, the oil spill models, and model prediction display capabilities. Graphic routines are provided for entering wind data, currents, and any type of geographically referenced data. Several modes of the spill model are available. The surface trajectory mode is intended for quick spill response. The weathering model includes the spreading, evaporation, entrainment, emulsification, and shoreline interaction of oil. The stochastic and receptor models simulate a large number of trajectories from a single site for generating probability statistics. Each model and the algorithms they use are described. Several additional capabilities are planned for OILMAP, including simulation of tactical spill response and subsurface oil transport. 8 refs
Relaxed memory models: an operational approach
Boudol , Gérard; Petri , Gustavo
2009-01-01
International audience; Memory models define an interface between programs written in some language and their implementation, determining which behaviour the memory (and thus a program) is allowed to have in a given model. A minimal guarantee memory models should provide to the programmer is that well-synchronized, that is, data-race free code has a standard semantics. Traditionally, memory models are defined axiomatically, setting constraints on the order in which memory operations are allow...
Modeling composting kinetics: A review of approaches
Hamelers, H.V.M.
2004-01-01
Composting kinetics modeling is necessary to design and operate composting facilities that comply with strict market demands and tight environmental legislation. Current composting kinetics modeling can be characterized as inductive, i.e. the data are the starting point of the modeling process and
Conformally invariant models: A new approach
International Nuclear Information System (INIS)
Fradkin, E.S.; Palchik, M.Ya.; Zaikin, V.N.
1996-02-01
A pair of mathematical models of quantum field theory in D dimensions is analyzed, particularly, a model of a charged scalar field defined by two generations of secondary fields in the space of even dimensions D>=4 and a model of a neutral scalar field defined by two generations of secondary fields in two-dimensional space. 6 refs
A systemic approach to modelling of radiobiological effects
International Nuclear Information System (INIS)
Obaturov, G.M.
1988-01-01
Basic principles of the systemic approach to modelling of the radiobiological effects at different levels of cell organization have been formulated. The methodology is proposed for theoretical modelling of the effects at these levels
Serpentinization reaction pathways: implications for modeling approach
Energy Technology Data Exchange (ETDEWEB)
Janecky, D.R.
1986-01-01
Experimental seawater-peridotite reaction pathways to form serpentinites at 300/sup 0/C, 500 bars, can be accurately modeled using the EQ3/6 codes in conjunction with thermodynamic and kinetic data from the literature and unpublished compilations. These models provide both confirmation of experimental interpretations and more detailed insight into hydrothermal reaction processes within the oceanic crust. The accuracy of these models depends on careful evaluation of the aqueous speciation model, use of mineral compositions that closely reproduce compositions in the experiments, and definition of realistic reactive components in terms of composition, thermodynamic data, and reaction rates.
Consumer preference models: fuzzy theory approach
Turksen, I. B.; Wilson, I. A.
1993-12-01
Consumer preference models are widely used in new product design, marketing management, pricing and market segmentation. The purpose of this article is to develop and test a fuzzy set preference model which can represent linguistic variables in individual-level models implemented in parallel with existing conjoint models. The potential improvements in market share prediction and predictive validity can substantially improve management decisions about what to make (product design), for whom to make it (market segmentation) and how much to make (market share prediction).
A visual approach for modeling spatiotemporal relations
R.L. Guimarães (Rodrigo); C.S.S. Neto; L.F.G. Soares
2008-01-01
htmlabstractTextual programming languages have proven to be difficult to learn and to use effectively for many people. For this sake, visual tools can be useful to abstract the complexity of such textual languages, minimizing the specification efforts. In this paper we present a visual approach for
PRODUCT TRIAL PROCESSING (PTP): A MODEL APPROACH ...
African Journals Online (AJOL)
Admin
This study is a theoretical approach to consumer's processing of product trail, and equally explored ... consumer's first usage experience with a company's brand or product that is most important in determining ... product, what it is really marketing is the expected ..... confidence, thus there is a positive relationship between ...
Nonlinear Modeling of the PEMFC Based On NNARX Approach
Shan-Jen Cheng; Te-Jen Chang; Kuang-Hsiung Tan; Shou-Ling Kuo
2015-01-01
Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accurac...
Development of a Conservative Model Validation Approach for Reliable Analysis
2015-01-01
CIE 2015 August 2-5, 2015, Boston, Massachusetts, USA [DRAFT] DETC2015-46982 DEVELOPMENT OF A CONSERVATIVE MODEL VALIDATION APPROACH FOR RELIABLE...obtain a conservative simulation model for reliable design even with limited experimental data. Very little research has taken into account the...3, the proposed conservative model validation is briefly compared to the conventional model validation approach. Section 4 describes how to account
Comparison of two novel approaches to model fibre reinforced concrete
Radtke, F.K.F.; Simone, A.; Sluys, L.J.
2009-01-01
We present two approaches to model fibre reinforced concrete. In both approaches, discrete fibre distributions and the behaviour of the fibre-matrix interface are explicitly considered. One approach employs the reaction forces from fibre to matrix while the other is based on the partition of unity
Modeling thrombin generation: plasma composition based approach.
Brummel-Ziedins, Kathleen E; Everse, Stephen J; Mann, Kenneth G; Orfeo, Thomas
2014-01-01
Thrombin has multiple functions in blood coagulation and its regulation is central to maintaining the balance between hemorrhage and thrombosis. Empirical and computational methods that capture thrombin generation can provide advancements to current clinical screening of the hemostatic balance at the level of the individual. In any individual, procoagulant and anticoagulant factor levels together act to generate a unique coagulation phenotype (net balance) that is reflective of the sum of its developmental, environmental, genetic, nutritional and pharmacological influences. Defining such thrombin phenotypes may provide a means to track disease progression pre-crisis. In this review we briefly describe thrombin function, methods for assessing thrombin dynamics as a phenotypic marker, computationally derived thrombin phenotypes versus determined clinical phenotypes, the boundaries of normal range thrombin generation using plasma composition based approaches and the feasibility of these approaches for predicting risk.
A simple approach to modeling ductile failure.
Energy Technology Data Exchange (ETDEWEB)
Wellman, Gerald William
2012-06-01
Sandia National Laboratories has the need to predict the behavior of structures after the occurrence of an initial failure. In some cases determining the extent of failure, beyond initiation, is required, while in a few cases the initial failure is a design feature used to tailor the subsequent load paths. In either case, the ability to numerically simulate the initiation and propagation of failures is a highly desired capability. This document describes one approach to the simulation of failure initiation and propagation.
A new approach for modeling composite materials
Alcaraz de la Osa, R.; Moreno, F.; Saiz, J. M.
2013-03-01
The increasing use of composite materials is due to their ability to tailor materials for special purposes, with applications evolving day by day. This is why predicting the properties of these systems from their constituents, or phases, has become so important. However, assigning macroscopical optical properties for these materials from the bulk properties of their constituents is not a straightforward task. In this research, we present a spectral analysis of three-dimensional random composite typical nanostructures using an Extension of the Discrete Dipole Approximation (E-DDA code), comparing different approaches and emphasizing the influences of optical properties of constituents and their concentration. In particular, we hypothesize a new approach that preserves the individual nature of the constituents introducing at the same time a variation in the optical properties of each discrete element that is driven by the surrounding medium. The results obtained with this new approach compare more favorably with the experiment than previous ones. We have also applied it to a non-conventional material composed of a metamaterial embedded in a dielectric matrix. Our version of the Discrete Dipole Approximation code, the EDDA code, has been formulated specifically to tackle this kind of problem, including materials with either magnetic and tensor properties.
An Integrated Approach to Modeling Evacuation Behavior
2011-02-01
A spate of recent hurricanes and other natural disasters have drawn a lot of attention to the evacuation decision of individuals. Here we focus on evacuation models that incorporate two economic phenomena that seem to be increasingly important in exp...
Infectious disease modeling a hybrid system approach
Liu, Xinzhi
2017-01-01
This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.
On Combining Language Models: Oracle Approach
National Research Council Canada - National Science Library
Hacioglu, Kadri; Ward, Wayne
2001-01-01
In this paper, we address the of combining several language models (LMs). We find that simple interpolation methods, like log-linear and linear interpolation, improve the performance but fall short of the performance of an oracle...
Advanced language modeling approaches, case study: Expert search
Hiemstra, Djoerd
2008-01-01
This tutorial gives a clear and detailed overview of advanced language modeling approaches and tools, including the use of document priors, translation models, relevance models, parsimonious models and expectation maximization training. Expert search will be used as a case study to explain the
Approaches to modelling hydrology and ecosystem interactions
Silberstein, Richard P.
2014-05-01
As the pressures of industry, agriculture and mining on groundwater resources increase there is a burgeoning un-met need to be able to capture these multiple, direct and indirect stresses in a formal framework that will enable better assessment of impact scenarios. While there are many catchment hydrological models and there are some models that represent ecological states and change (e.g. FLAMES, Liedloff and Cook, 2007), these have not been linked in any deterministic or substantive way. Without such coupled eco-hydrological models quantitative assessments of impacts from water use intensification on water dependent ecosystems under changing climate are difficult, if not impossible. The concept would include facility for direct and indirect water related stresses that may develop around mining and well operations, climate stresses, such as rainfall and temperature, biological stresses, such as diseases and invasive species, and competition such as encroachment from other competing land uses. Indirect water impacts could be, for example, a change in groundwater conditions has an impact on stream flow regime, and hence aquatic ecosystems. This paper reviews previous work examining models combining ecology and hydrology with a view to developing a conceptual framework linking a biophysically defensable model that combines ecosystem function with hydrology. The objective is to develop a model capable of representing the cumulative impact of multiple stresses on water resources and associated ecosystem function.
Constructing a justice model based on Sen's capability approach
Yüksel, Sevgi; Yuksel, Sevgi
2008-01-01
The thesis provides a possible justice model based on Sen's capability approach. For this goal, we first analyze the general structure of a theory of justice, identifying the main variables and issues. Furthermore, based on Sen (2006) and Kolm (1998), we look at 'transcendental' and 'comparative' approaches to justice and concentrate on the sufficiency condition for the comparative approach. Then, taking Rawls' theory of justice as a starting point, we present how Sen's capability approach em...
Challenges and opportunities for integrating lake ecosystem modelling approaches
Mooij, Wolf M.; Trolle, Dennis; Jeppesen, Erik; Arhonditsis, George; Belolipetsky, Pavel V.; Chitamwebwa, Deonatus B.R.; Degermendzhy, Andrey G.; DeAngelis, Donald L.; Domis, Lisette N. De Senerpont; Downing, Andrea S.; Elliott, J. Alex; Ruberto, Carlos Ruberto; Gaedke, Ursula; Genova, Svetlana N.; Gulati, Ramesh D.; Hakanson, Lars; Hamilton, David P.; Hipsey, Matthew R.; Hoen, Jochem 't; Hulsmann, Stephan; Los, F. Hans; Makler-Pick, Vardit; Petzoldt, Thomas; Prokopkin, Igor G.; Rinke, Karsten; Schep, Sebastiaan A.; Tominaga, Koji; Van Dam, Anne A.; Van Nes, Egbert H.; Wells, Scott A.; Janse, Jan H.
2010-01-01
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative
An ontology-based approach for modelling architectural styles
Pahl, Claus; Giesecke, Simon; Hasselbring, Wilhelm
2007-01-01
peer-reviewed The conceptual modelling of software architectures is of central importance for the quality of a software system. A rich modelling language is required to integrate the different aspects of architecture modelling, such as architectural styles, structural and behavioural modelling, into a coherent framework.We propose an ontological approach for architectural style modelling based on description logic as an abstract, meta-level modelling instrument. Architect...
Mathematical modelling a case studies approach
Illner, Reinhard; McCollum, Samantha; Roode, Thea van
2004-01-01
Mathematical modelling is a subject without boundaries. It is the means by which mathematics becomes useful to virtually any subject. Moreover, modelling has been and continues to be a driving force for the development of mathematics itself. This book explains the process of modelling real situations to obtain mathematical problems that can be analyzed, thus solving the original problem. The presentation is in the form of case studies, which are developed much as they would be in true applications. In many cases, an initial model is created, then modified along the way. Some cases are familiar, such as the evaluation of an annuity. Others are unique, such as the fascinating situation in which an engineer, armed only with a slide rule, had 24 hours to compute whether a valve would hold when a temporary rock plug was removed from a water tunnel. Each chapter ends with a set of exercises and some suggestions for class projects. Some projects are extensive, as with the explorations of the predator-prey model; oth...
The simplified models approach to constraining supersymmetry
Energy Technology Data Exchange (ETDEWEB)
Perez, Genessis [Institut fuer Theoretische Physik, Karlsruher Institut fuer Technologie (KIT), Wolfgang-Gaede-Str. 1, 76131 Karlsruhe (Germany); Kulkarni, Suchita [Laboratoire de Physique Subatomique et de Cosmologie, Universite Grenoble Alpes, CNRS IN2P3, 53 Avenue des Martyrs, 38026 Grenoble (France)
2015-07-01
The interpretation of the experimental results at the LHC are model dependent, which implies that the searches provide limited constraints on scenarios such as supersymmetry (SUSY). The Simplified Models Spectra (SMS) framework used by ATLAS and CMS collaborations is useful to overcome this limitation. SMS framework involves a small number of parameters (all the properties are reduced to the mass spectrum, the production cross section and the branching ratio) and hence is more generic than presenting results in terms of soft parameters. In our work, the SMS framework was used to test Natural SUSY (NSUSY) scenario. To accomplish this task, two automated tools (SModelS and Fastlim) were used to decompose the NSUSY parameter space in terms of simplified models and confront the theoretical predictions against the experimental results. The achievement of both, just as the strengths and limitations, are here expressed for the NSUSY scenario.
Lightweight approach to model traceability in a CASE tool
Vileiniskis, Tomas; Skersys, Tomas; Pavalkis, Saulius; Butleris, Rimantas; Butkiene, Rita
2017-07-01
A term "model-driven" is not at all a new buzzword within the ranks of system development community. Nevertheless, the ever increasing complexity of model-driven approaches keeps fueling all kinds of discussions around this paradigm and pushes researchers forward to research and develop new and more effective ways to system development. With the increasing complexity, model traceability, and model management as a whole, becomes indispensable activities of model-driven system development process. The main goal of this paper is to present a conceptual design and implementation of a practical lightweight approach to model traceability in a CASE tool.
New approaches for modeling type Ia supernovae
International Nuclear Information System (INIS)
Zingale, Michael; Almgren, Ann S.; Bell, John B.; Day, Marcus S.; Rendleman, Charles A.; Woosley, Stan
2007-01-01
Type Ia supernovae (SNe Ia) are the largest thermonuclear explosions in the Universe. Their light output can be seen across great distances and has led to the discovery that the expansion rate of the Universe is accelerating. Despite the significance of SNe Ia, there are still a large number of uncertainties in current theoretical models. Computational modeling offers the promise to help answer the outstanding questions. However, even with today's supercomputers, such calculations are extremely challenging because of the wide range of length and timescales. In this paper, we discuss several new algorithms for simulations of SNe Ia and demonstrate some of their successes
Chancroid transmission dynamics: a mathematical modeling approach.
Bhunu, C P; Mushayabasa, S
2011-12-01
Mathematical models have long been used to better understand disease transmission dynamics and how to effectively control them. Here, a chancroid infection model is presented and analyzed. The disease-free equilibrium is shown to be globally asymptotically stable when the reproduction number is less than unity. High levels of treatment are shown to reduce the reproduction number suggesting that treatment has the potential to control chancroid infections in any given community. This result is also supported by numerical simulations which show a decline in chancroid cases whenever the reproduction number is less than unity.
A kinetic approach to magnetospheric modeling
International Nuclear Information System (INIS)
Whipple, E.C. Jr.
1979-01-01
The earth's magnetosphere is caused by the interaction between the flowing solar wind and the earth's magnetic dipole, with the distorted magnetic field in the outer parts of the magnetosphere due to the current systems resulting from this interaction. It is surprising that even the conceptually simple problem of the collisionless interaction of a flowing plasma with a dipole magnetic field has not been solved. A kinetic approach is essential if one is to take into account the dispersion of particles with different energies and pitch angles and the fact that particles on different trajectories have different histories and may come from different sources. Solving the interaction problem involves finding the various types of possible trajectories, populating them with particles appropriately, and then treating the electric and magnetic fields self-consistently with the resulting particle densities and currents. This approach is illustrated by formulating a procedure for solving the collisionless interaction problem on open field lines in the case of a slowly flowing magnetized plasma interacting with a magnetic dipole
A kinetic approach to magnetospheric modeling
Whipple, E. C., Jr.
1979-01-01
The earth's magnetosphere is caused by the interaction between the flowing solar wind and the earth's magnetic dipole, with the distorted magnetic field in the outer parts of the magnetosphere due to the current systems resulting from this interaction. It is surprising that even the conceptually simple problem of the collisionless interaction of a flowing plasma with a dipole magnetic field has not been solved. A kinetic approach is essential if one is to take into account the dispersion of particles with different energies and pitch angles and the fact that particles on different trajectories have different histories and may come from different sources. Solving the interaction problem involves finding the various types of possible trajectories, populating them with particles appropriately, and then treating the electric and magnetic fields self-consistently with the resulting particle densities and currents. This approach is illustrated by formulating a procedure for solving the collisionless interaction problem on open field lines in the case of a slowly flowing magnetized plasma interacting with a magnetic dipole.
Fractal approach to computer-analytical modelling of tree crown
International Nuclear Information System (INIS)
Berezovskaya, F.S.; Karev, G.P.; Kisliuk, O.F.; Khlebopros, R.G.; Tcelniker, Yu.L.
1993-09-01
In this paper we discuss three approaches to the modeling of a tree crown development. These approaches are experimental (i.e. regressive), theoretical (i.e. analytical) and simulation (i.e. computer) modeling. The common assumption of these is that a tree can be regarded as one of the fractal objects which is the collection of semi-similar objects and combines the properties of two- and three-dimensional bodies. We show that a fractal measure of crown can be used as the link between the mathematical models of crown growth and light propagation through canopy. The computer approach gives the possibility to visualize a crown development and to calibrate the model on experimental data. In the paper different stages of the above-mentioned approaches are described. The experimental data for spruce, the description of computer system for modeling and the variant of computer model are presented. (author). 9 refs, 4 figs
A novel approach to modeling atmospheric convection
Goodman, A.
2016-12-01
The inadequate representation of clouds continues to be a large source of uncertainty in the projections from global climate models (GCMs). With continuous advances in computational power, however, the ability for GCMs to explicitly resolve cumulus convection will soon be realized. For this purpose, Jung and Arakawa (2008) proposed the Vector Vorticity Model (VVM), in which vorticity is the predicted variable instead of momentum. This has the advantage of eliminating the pressure gradient force within the framework of an anelastic system. However, the VVM was designed for use on a planar quadrilateral grid, making it unsuitable for implementation in global models discretized on the sphere. Here we have proposed a modification to the VVM where instead the curl of the horizontal vorticity is the primary predicted variable. This allows us to maintain the benefits of the original VVM while working within the constraints of a non-quadrilateral mesh. We found that our proposed model produced results from a warm bubble simulation that were consistent with the VVM. Further improvements that can be made to the VVM are also discussed.
INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...
Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec
A new approach to model mixed hydrates
Czech Academy of Sciences Publication Activity Database
Hielscher, S.; Vinš, Václav; Jäger, A.; Hrubý, Jan; Breitkopf, C.; Span, R.
2018-01-01
Roč. 459, March (2018), s. 170-185 ISSN 0378-3812 R&D Projects: GA ČR(CZ) GA17-08218S Institutional support: RVO:61388998 Keywords : gas hydrate * mixture * modeling Subject RIV: BJ - Thermodynamics Impact factor: 2.473, year: 2016 https://www.sciencedirect.com/science/article/pii/S0378381217304983
Energy and development : A modelling approach
van Ruijven, B.J.|info:eu-repo/dai/nl/304834521
2008-01-01
Rapid economic growth of developing countries like India and China implies that these countries become important actors in the global energy system. Examples of this impact are the present day oil shortages and rapidly increasing emissions of greenhouse gases. Global energy models are used explore
Modeling Approaches for Describing Microbial Population Heterogeneity
DEFF Research Database (Denmark)
Lencastre Fernandes, Rita
environmental conditions. Three cases are presented and discussed in this thesis. Common to all is the use of S. cerevisiae as model organism, and the use of cell size and cell cycle position as single-cell descriptors. The first case focuses on the experimental and mathematical description of a yeast...
Energy and Development. A Modelling Approach
International Nuclear Information System (INIS)
Van Ruijven, B.J.
2008-01-01
Rapid economic growth of developing countries like India and China implies that these countries become important actors in the global energy system. Examples of this impact are the present day oil shortages and rapidly increasing emissions of greenhouse gases. Global energy models are used to explore possible future developments of the global energy system and identify policies to prevent potential problems. Such estimations of future energy use in developing countries are very uncertain. Crucial factors in the future energy use of these regions are electrification, urbanisation and income distribution, issues that are generally not included in present day global energy models. Model simulations in this thesis show that current insight in developments in low-income regions lead to a wide range of expected energy use in 2030 of the residential and transport sectors. This is mainly caused by many different model calibration options that result from the limited data availability for model development and calibration. We developed a method to identify the impact of model calibration uncertainty on future projections. We developed a new model for residential energy use in India, in collaboration with the Indian Institute of Science. Experiments with this model show that the impact of electrification and income distribution is less univocal than often assumed. The use of fuelwood, with related health risks, can decrease rapidly if the income of poor groups increases. However, there is a trade off in terms of CO2 emissions because these groups gain access to electricity and the ownership of appliances increases. Another issue is the potential role of new technologies in developing countries: will they use the opportunities of leapfrogging? We explored the potential role of hydrogen, an energy carrier that might play a central role in a sustainable energy system. We found that hydrogen only plays a role before 2050 under very optimistic assumptions. Regional energy
Integration models: multicultural and liberal approaches confronted
Janicki, Wojciech
2012-01-01
European societies have been shaped by their Christian past, upsurge of international migration, democratic rule and liberal tradition rooted in religious tolerance. Boosting globalization processes impose new challenges on European societies, striving to protect their diversity. This struggle is especially clearly visible in case of minorities trying to resist melting into mainstream culture. European countries' legal systems and cultural policies respond to these efforts in many ways. Respecting identity politics-driven group rights seems to be the most common approach, resulting in creation of a multicultural society. However, the outcome of respecting group rights may be remarkably contradictory to both individual rights growing out from liberal tradition, and to reinforced concept of integration of immigrants into host societies. The hereby paper discusses identity politics upturn in the context of both individual rights and integration of European societies.
Modelling thermal plume impacts - Kalpakkam approach
International Nuclear Information System (INIS)
Rao, T.S.; Anup Kumar, B.; Narasimhan, S.V.
2002-01-01
A good understanding of temperature patterns in the receiving waters is essential to know the heat dissipation from thermal plumes originating from coastal power plants. The seasonal temperature profiles of the Kalpakkam coast near Madras Atomic Power Station (MAPS) thermal out fall site are determined and analysed. It is observed that the seasonal current reversal in the near shore zone is one of the major mechanisms for the transport of effluents away from the point of mixing. To further refine our understanding of the mixing and dilution processes, it is necessary to numerically simulate the coastal ocean processes by parameterising the key factors concerned. In this paper, we outline the experimental approach to achieve this objective. (author)
Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach
Energy Technology Data Exchange (ETDEWEB)
Liao, James C. [Univ. of California, Los Angeles, CA (United States)
2016-10-01
Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.
Nuclear security assessment with Markov model approach
International Nuclear Information System (INIS)
Suzuki, Mitsutoshi; Terao, Norichika
2013-01-01
Nuclear security risk assessment with the Markov model based on random event is performed to explore evaluation methodology for physical protection in nuclear facilities. Because the security incidences are initiated by malicious and intentional acts, expert judgment and Bayes updating are used to estimate scenario and initiation likelihood, and it is assumed that the Markov model derived from stochastic process can be applied to incidence sequence. Both an unauthorized intrusion as Design Based Threat (DBT) and a stand-off attack as beyond-DBT are assumed to hypothetical facilities, and performance of physical protection and mitigation and minimization of consequence are investigated to develop the assessment methodology in a semi-quantitative manner. It is shown that cooperation between facility operator and security authority is important to respond to the beyond-DBT incidence. (author)
An Approach for Modeling Supplier Resilience
2016-04-30
interests include resilience modeling of supply chains, reliability engineering, and meta- heuristic optimization. [m.hosseini@ou.edu] Abstract...be availability , or the extent to which the products produced by the supply chain are available for use (measured as a ratio of uptime to total time...of the use of the product). Available systems are important in many industries, particularly in the Department of Defense, where weapons systems
Tumour resistance to cisplatin: a modelling approach
International Nuclear Information System (INIS)
Marcu, L; Bezak, E; Olver, I; Doorn, T van
2005-01-01
Although chemotherapy has revolutionized the treatment of haematological tumours, in many common solid tumours the success has been limited. Some of the reasons for the limitations are: the timing of drug delivery, resistance to the drug, repopulation between cycles of chemotherapy and the lack of complete understanding of the pharmacokinetics and pharmacodynamics of a specific agent. Cisplatin is among the most effective cytotoxic agents used in head and neck cancer treatments. When modelling cisplatin as a single agent, the properties of cisplatin only have to be taken into account, reducing the number of assumptions that are considered in the generalized chemotherapy models. The aim of the present paper is to model the biological effect of cisplatin and to simulate the consequence of cisplatin resistance on tumour control. The 'treated' tumour is a squamous cell carcinoma of the head and neck, previously grown by computer-based Monte Carlo techniques. The model maintained the biological constitution of a tumour through the generation of stem cells, proliferating cells and non-proliferating cells. Cell kinetic parameters (mean cell cycle time, cell loss factor, thymidine labelling index) were also consistent with the literature. A sensitivity study on the contribution of various mechanisms leading to drug resistance is undertaken. To quantify the extent of drug resistance, the cisplatin resistance factor (CRF) is defined as the ratio between the number of surviving cells of the resistant population and the number of surviving cells of the sensitive population, determined after the same treatment time. It is shown that there is a supra-linear dependence of CRF on the percentage of cisplatin-DNA adducts formed, and a sigmoid-like dependence between CRF and the percentage of cells killed in resistant tumours. Drug resistance is shown to be a cumulative process which eventually can overcome tumour regression leading to treatment failure
Tumour resistance to cisplatin: a modelling approach
Energy Technology Data Exchange (ETDEWEB)
Marcu, L [School of Chemistry and Physics, University of Adelaide, North Terrace, SA 5000 (Australia); Bezak, E [School of Chemistry and Physics, University of Adelaide, North Terrace, SA 5000 (Australia); Olver, I [Faculty of Medicine, University of Adelaide, North Terrace, SA 5000 (Australia); Doorn, T van [School of Chemistry and Physics, University of Adelaide, North Terrace, SA 5000 (Australia)
2005-01-07
Although chemotherapy has revolutionized the treatment of haematological tumours, in many common solid tumours the success has been limited. Some of the reasons for the limitations are: the timing of drug delivery, resistance to the drug, repopulation between cycles of chemotherapy and the lack of complete understanding of the pharmacokinetics and pharmacodynamics of a specific agent. Cisplatin is among the most effective cytotoxic agents used in head and neck cancer treatments. When modelling cisplatin as a single agent, the properties of cisplatin only have to be taken into account, reducing the number of assumptions that are considered in the generalized chemotherapy models. The aim of the present paper is to model the biological effect of cisplatin and to simulate the consequence of cisplatin resistance on tumour control. The 'treated' tumour is a squamous cell carcinoma of the head and neck, previously grown by computer-based Monte Carlo techniques. The model maintained the biological constitution of a tumour through the generation of stem cells, proliferating cells and non-proliferating cells. Cell kinetic parameters (mean cell cycle time, cell loss factor, thymidine labelling index) were also consistent with the literature. A sensitivity study on the contribution of various mechanisms leading to drug resistance is undertaken. To quantify the extent of drug resistance, the cisplatin resistance factor (CRF) is defined as the ratio between the number of surviving cells of the resistant population and the number of surviving cells of the sensitive population, determined after the same treatment time. It is shown that there is a supra-linear dependence of CRF on the percentage of cisplatin-DNA adducts formed, and a sigmoid-like dependence between CRF and the percentage of cells killed in resistant tumours. Drug resistance is shown to be a cumulative process which eventually can overcome tumour regression leading to treatment failure.
ISM Approach to Model Offshore Outsourcing Risks
Directory of Open Access Journals (Sweden)
Sunand Kumar
2014-07-01
Full Text Available In an effort to achieve a competitive advantage via cost reductions and improved market responsiveness, organizations are increasingly employing offshore outsourcing as a major component of their supply chain strategies. But as evident from literature number of risks such as Political risk, Risk due to cultural differences, Compliance and regulatory risk, Opportunistic risk and Organization structural risk, which adversely affect the performance of offshore outsourcing in a supply chain network. This also leads to dissatisfaction among different stake holders. The main objective of this paper is to identify and understand the mutual interaction among various risks which affect the performance of offshore outsourcing. To this effect, authors have identified various risks through extant review of literature. From this information, an integrated model using interpretive structural modelling (ISM for risks affecting offshore outsourcing is developed and the structural relationships between these risks are modeled. Further, MICMAC analysis is done to analyze the driving power and dependency of risks which shall be helpful to managers to identify and classify important criterions and to reveal the direct and indirect effects of each criterion on offshore outsourcing. Results show that political risk and risk due to cultural differences are act as strong drivers.
Remote sensing approach to structural modelling
International Nuclear Information System (INIS)
El Ghawaby, M.A.
1989-01-01
Remote sensing techniques are quite dependable tools in investigating geologic problems, specially those related to structural aspects. The Landsat imagery provides discrimination between rock units, detection of large scale structures as folds and faults, as well as small scale fabric elements such as foliation and banding. In order to fulfill the aim of geologic application of remote sensing, some essential surveying maps might be done from images prior to the structural interpretation: land-use, land-form drainage pattern, lithological unit and structural lineament maps. Afterwards, the field verification should lead to interpretation of a comprehensive structural model of the study area to apply for the target problem. To deduce such a model, there are two ways of analysis the interpreter may go through: the direct and the indirect methods. The direct one is needed in cases where the resources or the targets are controlled by an obvious or exposed structural element or pattern. The indirect way is necessary for areas where the target is governed by a complicated structural pattern. Some case histories of structural modelling methods applied successfully for exploration of radioactive minerals, iron deposits and groundwater aquifers in Egypt are presented. The progress in imagery, enhancement and integration of remote sensing data with the other geophysical and geochemical data allow a geologic interpretation to be carried out which become better than that achieved with either of the individual data sets. 9 refs
A moving approach for the Vector Hysteron Model
Energy Technology Data Exchange (ETDEWEB)
Cardelli, E. [Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia (Italy); Faba, A., E-mail: antonio.faba@unipg.it [Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia (Italy); Laudani, A. [Department of Engineering, Roma Tre University, Via V. Volterra 62, 00146 Rome (Italy); Quondam Antonio, S. [Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia (Italy); Riganti Fulginei, F.; Salvini, A. [Department of Engineering, Roma Tre University, Via V. Volterra 62, 00146 Rome (Italy)
2016-04-01
A moving approach for the VHM (Vector Hysteron Model) is here described, to reconstruct both scalar and rotational magnetization of electrical steels with weak anisotropy, such as the non oriented grain Silicon steel. The hysterons distribution is postulated to be function of the magnetization state of the material, in order to overcome the practical limitation of the congruency property of the standard VHM approach. By using this formulation and a suitable accommodation procedure, the results obtained indicate that the model is accurate, in particular in reproducing the experimental behavior approaching to the saturation region, allowing a real improvement respect to the previous approach.
Agribusiness model approach to territorial food development
Directory of Open Access Journals (Sweden)
Murcia Hector Horacio
2011-04-01
Full Text Available
Several research efforts have coordinated the academic program of Agricultural Business Management from the University De La Salle (Bogota D.C., to the design and implementation of a sustainable agribusiness model applied to food development, with territorial projection. Rural development is considered as a process that aims to improve the current capacity and potential of the inhabitant of the sector, which refers not only to production levels and productivity of agricultural items. It takes into account the guidelines of the Organization of the United Nations “Millennium Development Goals” and considered the concept of sustainable food and agriculture development, including food security and nutrition in an integrated interdisciplinary context, with holistic and systemic dimension. Analysis is specified by a model with an emphasis on sustainable agribusiness production chains related to agricultural food items in a specific region. This model was correlated with farm (technical objectives, family (social purposes and community (collective orientations projects. Within this dimension are considered food development concepts and methodologies of Participatory Action Research (PAR. Finally, it addresses the need to link the results to low-income communities, within the concepts of the “new rurality”.
Engineering approach to modeling of piled systems
International Nuclear Information System (INIS)
Coombs, R.F.; Silva, M.A.G. da
1980-01-01
Available methods of analysis of piled systems subjected to dynamic excitation invade areas of mathematics usually beyond the reach of a practising engineer. A simple technique that avoids that conflict is proposed, at least for preliminary studies, and its application, compared with other methods, is shown to be satisfactory. A corrective factor for parameters currently used to represent transmitting boundaries is derived for a finite strip that models an infinite layer. The influence of internal damping on the dynamic stiffness of the layer and on radiation damping is analysed. (Author) [pt
Jackiw-Pi model: A superfield approach
Gupta, Saurabh
2014-12-01
We derive the off-shell nilpotent and absolutely anticommuting Becchi-Rouet-Stora-Tyutin (BRST) as well as anti-BRST transformations s ( a) b corresponding to the Yang-Mills gauge transformations of 3D Jackiw-Pi model by exploiting the "augmented" super-field formalism. We also show that the Curci-Ferrari restriction, which is a hallmark of any non-Abelian 1-form gauge theories, emerges naturally within this formalism and plays an instrumental role in providing the proof of absolute anticommutativity of s ( a) b .
Applied Regression Modeling A Business Approach
Pardoe, Iain
2012-01-01
An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a
Implicit moral evaluations: A multinomial modeling approach.
Cameron, C Daryl; Payne, B Keith; Sinnott-Armstrong, Walter; Scheffer, Julian A; Inzlicht, Michael
2017-01-01
Implicit moral evaluations-i.e., immediate, unintentional assessments of the wrongness of actions or persons-play a central role in supporting moral behavior in everyday life. Yet little research has employed methods that rigorously measure individual differences in implicit moral evaluations. In five experiments, we develop a new sequential priming measure-the Moral Categorization Task-and a multinomial model that decomposes judgment on this task into multiple component processes. These include implicit moral evaluations of moral transgression primes (Unintentional Judgment), accurate moral judgments about target actions (Intentional Judgment), and a directional tendency to judge actions as morally wrong (Response Bias). Speeded response deadlines reduced Intentional Judgment but not Unintentional Judgment (Experiment 1). Unintentional Judgment was stronger toward moral transgression primes than non-moral negative primes (Experiments 2-4). Intentional Judgment was associated with increased error-related negativity, a neurophysiological indicator of behavioral control (Experiment 4). Finally, people who voted for an anti-gay marriage amendment had stronger Unintentional Judgment toward gay marriage primes (Experiment 5). Across Experiments 1-4, implicit moral evaluations converged with moral personality: Unintentional Judgment about wrong primes, but not negative primes, was negatively associated with psychopathic tendencies and positively associated with moral identity and guilt proneness. Theoretical and practical applications of formal modeling for moral psychology are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.
Modeling Saturn's Inner Plasmasphere: Cassini's Closest Approach
Moore, L.; Mendillo, M.
2005-05-01
Ion densities from the three-dimensional Saturn-Thermosphere-Ionosphere-Model (STIM, Moore et al., 2004) are extended above the plasma exobase using the formalism of Pierrard and Lemaire (1996, 1998), which evaluates the balance of gravitational, centrifugal and electric forces on the plasma. The parameter space of low-energy ionospheric contributions to Saturn's plasmasphere is explored by comparing results that span the observed extremes of plasma temperature, 650 K to 1700 K, and a range of velocity distributions, Lorentzian (or Kappa) to Maxwellian. Calculations are made for plasma densities along the path of the Cassini spacecraft's orbital insertion on 1 July 2004. These calculations neglect any ring or satellite sources of plasma, which are most likely minor contributors at 1.3 Saturn radii. Modeled densities will be compared with Cassini measurements as they become available. Moore, L.E., M. Mendillo, I.C.F. Mueller-Wodarg, and D.L. Murr, Icarus, 172, 503-520, 2004. Pierrard, V. and J. Lemaire, J. Geophys. Res., 101, 7923-7934, 1996. Pierrard, V. and J. Lemaire, J. Geophys. Res., 103, 4117, 1998.
Keyring models: An approach to steerability
Miller, Carl A.; Colbeck, Roger; Shi, Yaoyun
2018-02-01
If a measurement is made on one half of a bipartite system, then, conditioned on the outcome, the other half has a new reduced state. If these reduced states defy classical explanation—that is, if shared randomness cannot produce these reduced states for all possible measurements—the bipartite state is said to be steerable. Determining which states are steerable is a challenging problem even for low dimensions. In the case of two-qubit systems, a criterion is known for T-states (that is, those with maximally mixed marginals) under projective measurements. In the current work, we introduce the concept of keyring models—a special class of local hidden state models. When the measurements made correspond to real projectors, these allow us to study steerability beyond T-states. Using keyring models, we completely solve the steering problem for real projective measurements when the state arises from mixing a pure two-qubit state with uniform noise. We also give a partial solution in the case when the uniform noise is replaced by independent depolarizing channels.
Mathematical Modeling in Mathematics Education: Basic Concepts and Approaches
Erbas, Ayhan Kürsat; Kertil, Mahmut; Çetinkaya, Bülent; Çakiroglu, Erdinç; Alacaci, Cengiz; Bas, Sinem
2014-01-01
Mathematical modeling and its role in mathematics education have been receiving increasing attention in Turkey, as in many other countries. The growing body of literature on this topic reveals a variety of approaches to mathematical modeling and related concepts, along with differing perspectives on the use of mathematical modeling in teaching and…
A BEHAVIORAL-APPROACH TO LINEAR EXACT MODELING
ANTOULAS, AC; WILLEMS, JC
1993-01-01
The behavioral approach to system theory provides a parameter-free framework for the study of the general problem of linear exact modeling and recursive modeling. The main contribution of this paper is the solution of the (continuous-time) polynomial-exponential time series modeling problem. Both
A modular approach to numerical human body modeling
Forbes, P.A.; Griotto, G.; Rooij, L. van
2007-01-01
The choice of a human body model for a simulated automotive impact scenario must take into account both accurate model response and computational efficiency as key factors. This study presents a "modular numerical human body modeling" approach which allows the creation of a customized human body
A Bayesian approach for quantification of model uncertainty
International Nuclear Information System (INIS)
Park, Inseok; Amarchinta, Hemanth K.; Grandhi, Ramana V.
2010-01-01
In most engineering problems, more than one model can be created to represent an engineering system's behavior. Uncertainty is inevitably involved in selecting the best model from among the models that are possible. Uncertainty in model selection cannot be ignored, especially when the differences between the predictions of competing models are significant. In this research, a methodology is proposed to quantify model uncertainty using measured differences between experimental data and model outcomes under a Bayesian statistical framework. The adjustment factor approach is used to propagate model uncertainty into prediction of a system response. A nonlinear vibration system is used to demonstrate the processes for implementing the adjustment factor approach. Finally, the methodology is applied on the engineering benefits of a laser peening process, and a confidence band for residual stresses is established to indicate the reliability of model prediction.
A Networks Approach to Modeling Enzymatic Reactions.
Imhof, P
2016-01-01
Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes. © 2016 Elsevier Inc. All rights reserved.
Carbonate rock depositional models: A microfacies approach
Energy Technology Data Exchange (ETDEWEB)
Carozzi, A.V.
1988-01-01
Carbonate rocks contain more than 50% by weight carbonate minerals such as calcite, dolomite, and siderite. Understanding how these rocks form can lead to more efficient methods of petroleum exploration. Micofacies analysis techniques can be used as a method of predicting models of sedimentation for carbonate rocks. Micofacies in carbonate rocks can be seen clearly only in thin sections under a microscope. This section analysis of carbonate rocks is a tool that can be used to understand depositional environments, diagenetic evolution of carbonate rocks, and the formation of porosity and permeability in carbonate rocks. The use of micofacies analysis techniques is applied to understanding the origin and formation of carbonate ramps, carbonate platforms, and carbonate slopes and basins. This book will be of interest to students and professionals concerned with the disciplines of sedimentary petrology, sedimentology, petroleum geology, and palentology.
Risk prediction model: Statistical and artificial neural network approach
Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim
2017-04-01
Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.
Directory of Open Access Journals (Sweden)
Ramiro M. Irastorza
2015-01-01
Full Text Available Small diameter tissue-engineered arteries improve their mechanical and functional properties when they are mechanically stimulated. Applying a suitable stress and/or strain with or without a cycle to the scaffolds and cells during the culturing process resides in our ability to generate a suitable mechanical model. Collagen gel is one of the most used scaffolds in vascular tissue engineering, mainly because it is the principal constituent of the extracellular matrix for vascular cells in human. The mechanical modeling of such a material is not a trivial task, mainly for its viscoelastic nature. Computational and experimental methods for developing a suitable model for collagen gels are of primary importance for the field. In this research, we focused on mechanical properties of collagen gels under unconfined compression. First, mechanical viscoelastic models are discussed and framed in the control system theory. Second, models are fitted using system identification. Several models are evaluated and two nonlinear models are proposed: Mooney-Rivlin inspired and Hammerstein models. The results suggest that Mooney-Rivlin and Hammerstein models succeed in describing the mechanical behavior of collagen gels for cyclic tests on scaffolds (with best fitting parameters 58.3% and 75.8%, resp.. When Akaike criterion is used, the best is the Mooney-Rivlin inspired model.
Irastorza, Ramiro M; Drouin, Bernard; Blangino, Eugenia; Mantovani, Diego
2015-01-01
Small diameter tissue-engineered arteries improve their mechanical and functional properties when they are mechanically stimulated. Applying a suitable stress and/or strain with or without a cycle to the scaffolds and cells during the culturing process resides in our ability to generate a suitable mechanical model. Collagen gel is one of the most used scaffolds in vascular tissue engineering, mainly because it is the principal constituent of the extracellular matrix for vascular cells in human. The mechanical modeling of such a material is not a trivial task, mainly for its viscoelastic nature. Computational and experimental methods for developing a suitable model for collagen gels are of primary importance for the field. In this research, we focused on mechanical properties of collagen gels under unconfined compression. First, mechanical viscoelastic models are discussed and framed in the control system theory. Second, models are fitted using system identification. Several models are evaluated and two nonlinear models are proposed: Mooney-Rivlin inspired and Hammerstein models. The results suggest that Mooney-Rivlin and Hammerstein models succeed in describing the mechanical behavior of collagen gels for cyclic tests on scaffolds (with best fitting parameters 58.3% and 75.8%, resp.). When Akaike criterion is used, the best is the Mooney-Rivlin inspired model.
A dual model approach to ground water recovery trench design
International Nuclear Information System (INIS)
Clodfelter, C.L.; Crouch, M.S.
1992-01-01
The design of trenches for contaminated ground water recovery must consider several variables. This paper presents a dual-model approach for effectively recovering contaminated ground water migrating toward a trench by advection. The approach involves an analytical model to determine the vertical influence of the trench and a numerical flow model to determine the capture zone within the trench and the surrounding aquifer. The analytical model is utilized by varying trench dimensions and head values to design a trench which meets the remediation criteria. The numerical flow model is utilized to select the type of backfill and location of sumps within the trench. The dual-model approach can be used to design a recovery trench which effectively captures advective migration of contaminants in the vertical and horizontal planes
Virtuous organization: A structural equation modeling approach
Directory of Open Access Journals (Sweden)
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.
A systemic approach for modeling soil functions
Vogel, Hans-Jörg; Bartke, Stephan; Daedlow, Katrin; Helming, Katharina; Kögel-Knabner, Ingrid; Lang, Birgit; Rabot, Eva; Russell, David; Stößel, Bastian; Weller, Ulrich; Wiesmeier, Martin; Wollschläger, Ute
2018-03-01
The central importance of soil for the functioning of terrestrial systems is increasingly recognized. Critically relevant for water quality, climate control, nutrient cycling and biodiversity, soil provides more functions than just the basis for agricultural production. Nowadays, soil is increasingly under pressure as a limited resource for the production of food, energy and raw materials. This has led to an increasing demand for concepts assessing soil functions so that they can be adequately considered in decision-making aimed at sustainable soil management. The various soil science disciplines have progressively developed highly sophisticated methods to explore the multitude of physical, chemical and biological processes in soil. It is not obvious, however, how the steadily improving insight into soil processes may contribute to the evaluation of soil functions. Here, we present to a new systemic modeling framework that allows for a consistent coupling between reductionist yet observable indicators for soil functions with detailed process understanding. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. The non-linear character of these interactions produces stability and resilience of soil with respect to functional characteristics. We anticipate that this new conceptional framework will integrate the various soil science disciplines and help identify important future research questions at the interface between disciplines. It allows the overwhelming complexity of soil systems to be adequately coped with and paves the way for steadily improving our capability to assess soil functions based on scientific understanding.
Modeling of phase equilibria with CPA using the homomorph approach
DEFF Research Database (Denmark)
Breil, Martin Peter; Tsivintzelis, Ioannis; Kontogeorgis, Georgios
2011-01-01
For association models, like CPA and SAFT, a classical approach is often used for estimating pure-compound and mixture parameters. According to this approach, the pure-compound parameters are estimated from vapor pressure and liquid density data. Then, the binary interaction parameters, kij, are ...
Modular Modelling and Simulation Approach - Applied to Refrigeration Systems
DEFF Research Database (Denmark)
Sørensen, Kresten Kjær; Stoustrup, Jakob
2008-01-01
This paper presents an approach to modelling and simulation of the thermal dynamics of a refrigeration system, specifically a reefer container. A modular approach is used and the objective is to increase the speed and flexibility of the developed simulation environment. The refrigeration system...
A Constructive Neural-Network Approach to Modeling Psychological Development
Shultz, Thomas R.
2012-01-01
This article reviews a particular computational modeling approach to the study of psychological development--that of constructive neural networks. This approach is applied to a variety of developmental domains and issues, including Piagetian tasks, shift learning, language acquisition, number comparison, habituation of visual attention, concept…
The Intersystem Model of Psychotherapy: An Integrated Systems Treatment Approach
Weeks, Gerald R.; Cross, Chad L.
2004-01-01
This article introduces the intersystem model of psychotherapy and discusses its utility as a truly integrative and comprehensive approach. The foundation of this conceptually complex approach comes from dialectic metatheory; hence, its derivation requires an understanding of both foundational and integrational constructs. The article provides a…
Bystander Approaches: Empowering Students to Model Ethical Sexual Behavior
Lynch, Annette; Fleming, Wm. Michael
2005-01-01
Sexual violence on college campuses is well documented. Prevention education has emerged as an alternative to victim-- and perpetrator--oriented approaches used in the past. One sexual violence prevention education approach focuses on educating and empowering the bystander to become a point of ethical intervention. In this model, bystanders to…
Modelling road accidents: An approach using structural time series
Junus, Noor Wahida Md; Ismail, Mohd Tahir
2014-09-01
In this paper, the trend of road accidents in Malaysia for the years 2001 until 2012 was modelled using a structural time series approach. The structural time series model was identified using a stepwise method, and the residuals for each model were tested. The best-fitted model was chosen based on the smallest Akaike Information Criterion (AIC) and prediction error variance. In order to check the quality of the model, a data validation procedure was performed by predicting the monthly number of road accidents for the year 2012. Results indicate that the best specification of the structural time series model to represent road accidents is the local level with a seasonal model.
Numerical approaches to expansion process modeling
Directory of Open Access Journals (Sweden)
G. V. Alekseev
2017-01-01
Full Text Available Forage production is currently undergoing a period of intensive renovation and introduction of the most advanced technologies and equipment. More and more often such methods as barley toasting, grain extrusion, steaming and grain flattening, boiling bed explosion, infrared ray treatment of cereals and legumes, followed by flattening, and one-time or two-time granulation of the purified whole grain without humidification in matrix presses By grinding the granules. These methods require special apparatuses, machines, auxiliary equipment, created on the basis of different methods of compiled mathematical models. When roasting, simulating the heat fields arising in the working chamber, provide such conditions, the decomposition of a portion of the starch to monosaccharides, which makes the grain sweetish, but due to protein denaturation the digestibility of the protein and the availability of amino acids decrease somewhat. Grain is roasted mainly for young animals in order to teach them to eat food at an early age, stimulate the secretory activity of digestion, better development of the masticatory muscles. In addition, the high temperature is detrimental to bacterial contamination and various types of fungi, which largely avoids possible diseases of the gastrointestinal tract. This method has found wide application directly on the farms. Apply when used in feeding animals and legumes: peas, soy, lupine and lentils. These feeds are preliminarily ground, and then cooked or steamed for 1 hour for 30–40 minutes. In the feed mill. Such processing of feeds allows inactivating the anti-nutrients in them, which reduce the effectiveness of their use. After processing, legumes are used as protein supplements in an amount of 25–30% of the total nutritional value of the diet. But it is recommended to cook and steal a grain of good quality. A poor-quality grain that has been stored for a long time and damaged by pathogenic micro flora is subject to
Modelling and Generating Ajax Applications : A Model-Driven Approach
Gharavi, V.; Mesbah, A.; Van Deursen, A.
2008-01-01
Preprint of paper published in: IWWOST 2008 - 7th International Workshop on Web-Oriented Software Technologies, 14-15 July 2008 AJAX is a promising and rapidly evolving approach for building highly interactive web applications. In AJAX, user interface components and the event-based interaction
Understanding Gulf War Illness: An Integrative Modeling Approach
2017-10-01
using a novel mathematical model. The computational biology approach will enable the consortium to quickly identify targets of dysfunction and find... computer / mathematical paradigms for evaluation of treatment strategies 12-30 50% Develop pilot clinical trials on basis of animal studies 24-36 60...the goal of testing chemical treatments. The immune and autonomic biomarkers will be tested using a computational modeling approach allowing for a
A Structural Modeling Approach to a Multilevel Random Coefficients Model.
Rovine, Michael J.; Molenaar, Peter C. M.
2000-01-01
Presents a method for estimating the random coefficients model using covariance structure modeling and allowing one to estimate both fixed and random effects. The method is applied to real and simulated data, including marriage data from J. Belsky and M. Rovine (1990). (SLD)
Data Analysis A Model Comparison Approach, Second Edition
Judd, Charles M; Ryan, Carey S
2008-01-01
This completely rewritten classic text features many new examples, insights and topics including mediational, categorical, and multilevel models. Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis. Noted for its model-comparison approach and unified framework based on the general linear model, the book provides readers with a greater understanding of a variety of statistical procedures. This consistent framework, including consistent vocabulary and notation, is used throughout to develop fewer but more powerful model building techniques. T
A novel approach to modeling and diagnosing the cardiovascular system
Energy Technology Data Exchange (ETDEWEB)
Keller, P.E.; Kangas, L.J.; Hashem, S.; Kouzes, R.T. [Pacific Northwest Lab., Richland, WA (United States); Allen, P.A. [Life Link, Richland, WA (United States)
1995-07-01
A novel approach to modeling and diagnosing the cardiovascular system is introduced. A model exhibits a subset of the dynamics of the cardiovascular behavior of an individual by using a recurrent artificial neural network. Potentially, a model will be incorporated into a cardiovascular diagnostic system. This approach is unique in that each cardiovascular model is developed from physiological measurements of an individual. Any differences between the modeled variables and the variables of an individual at a given time are used for diagnosis. This approach also exploits sensor fusion to optimize the utilization of biomedical sensors. The advantage of sensor fusion has been demonstrated in applications including control and diagnostics of mechanical and chemical processes.
Synthesis of industrial applications of local approach to fracture models
International Nuclear Information System (INIS)
Eripret, C.
1993-03-01
This report gathers different applications of local approach to fracture models to various industrial configurations, such as nuclear pressure vessel steel, cast duplex stainless steels, or primary circuit welds such as bimetallic welds. As soon as models are developed on the basis of microstructural observations, damage mechanisms analyses, and fracture process, the local approach to fracture proves to solve problems where classical fracture mechanics concepts fail. Therefore, local approach appears to be a powerful tool, which completes the standard fracture criteria used in nuclear industry by exhibiting where and why those classical concepts become unvalid. (author). 1 tab., 18 figs., 25 refs
Mathematical models for therapeutic approaches to control HIV disease transmission
Roy, Priti Kumar
2015-01-01
The book discusses different therapeutic approaches based on different mathematical models to control the HIV/AIDS disease transmission. It uses clinical data, collected from different cited sources, to formulate the deterministic as well as stochastic mathematical models of HIV/AIDS. It provides complementary approaches, from deterministic and stochastic points of view, to optimal control strategy with perfect drug adherence and also tries to seek viewpoints of the same issue from different angles with various mathematical models to computer simulations. The book presents essential methods and techniques for students who are interested in designing epidemiological models on HIV/AIDS. It also guides research scientists, working in the periphery of mathematical modeling, and helps them to explore a hypothetical method by examining its consequences in the form of a mathematical modelling and making some scientific predictions. The model equations, mathematical analysis and several numerical simulations that are...
A model-driven approach to information security compliance
Correia, Anacleto; Gonçalves, António; Teodoro, M. Filomena
2017-06-01
The availability, integrity and confidentiality of information are fundamental to the long-term survival of any organization. Information security is a complex issue that must be holistically approached, combining assets that support corporate systems, in an extended network of business partners, vendors, customers and other stakeholders. This paper addresses the conception and implementation of information security systems, conform the ISO/IEC 27000 set of standards, using the model-driven approach. The process begins with the conception of a domain level model (computation independent model) based on information security vocabulary present in the ISO/IEC 27001 standard. Based on this model, after embedding in the model mandatory rules for attaining ISO/IEC 27001 conformance, a platform independent model is derived. Finally, a platform specific model serves the base for testing the compliance of information security systems with the ISO/IEC 27000 set of standards.
A Model-Driven Approach for Telecommunications Network Services Definition
Chiprianov, Vanea; Kermarrec, Yvon; Alff, Patrick D.
Present day Telecommunications market imposes a short concept-to-market time for service providers. To reduce it, we propose a computer-aided, model-driven, service-specific tool, with support for collaborative work and for checking properties on models. We started by defining a prototype of the Meta-model (MM) of the service domain. Using this prototype, we defined a simple graphical modeling language specific for service designers. We are currently enlarging the MM of the domain using model transformations from Network Abstractions Layers (NALs). In the future, we will investigate approaches to ensure the support for collaborative work and for checking properties on models.
An approach for activity-based DEVS model specification
DEFF Research Database (Denmark)
Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram
2016-01-01
Creation of DEVS models has been advanced through Model Driven Architecture and its frameworks. The overarching role of the frameworks has been to help develop model specifications in a disciplined fashion. Frameworks can provide intermediary layers between the higher level mathematical models...... and their corresponding software specifications from both structural and behavioral aspects. Unlike structural modeling, developing models to specify behavior of systems is known to be harder and more complex, particularly when operations with non-trivial control schemes are required. In this paper, we propose specifying...... activity-based behavior modeling of parallel DEVS atomic models. We consider UML activities and actions as fundamental units of behavior modeling, especially in the presence of recent advances in the UML 2.5 specifications. We describe in detail how to approach activity modeling with a set of elemental...
Modelling diversity in building occupant behaviour: a novel statistical approach
DEFF Research Database (Denmark)
Haldi, Frédéric; Calì, Davide; Andersen, Rune Korsholm
2016-01-01
We propose an advanced modelling framework to predict the scope and effects of behavioural diversity regarding building occupant actions on window openings, shading devices and lighting. We develop a statistical approach based on generalised linear mixed models to account for the longitudinal nat...
Sensitivity analysis approaches applied to systems biology models.
Zi, Z
2011-11-01
With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.
A qualitative evaluation approach for energy system modelling frameworks
DEFF Research Database (Denmark)
Wiese, Frauke; Hilpert, Simon; Kaldemeyer, Cord
2018-01-01
properties define how useful it is in regard to the existing challenges. For energy system models, evaluation methods exist, but we argue that many decisions upon properties are rather made on the model generator or framework level. Thus, this paper presents a qualitative approach to evaluate frameworks...
Modeling Alaska boreal forests with a controlled trend surface approach
Mo Zhou; Jingjing Liang
2012-01-01
An approach of Controlled Trend Surface was proposed to simultaneously take into consideration large-scale spatial trends and nonspatial effects. A geospatial model of the Alaska boreal forest was developed from 446 permanent sample plots, which addressed large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of...
Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling
Kayastha, N.
2014-01-01
Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of
Towards modeling future energy infrastructures - the ELECTRA system engineering approach
DEFF Research Database (Denmark)
Uslar, Mathias; Heussen, Kai
2016-01-01
of the IEC 62559 use case template as well as needed changes to cope particularly with the aspects of controller conflicts and Greenfield technology modeling. From the original envisioned use of the standards, we show a possible transfer on how to properly deal with a Greenfield approach when modeling....
A Model-Driven Approach to e-Course Management
Savic, Goran; Segedinac, Milan; Milenkovic, Dušica; Hrin, Tamara; Segedinac, Mirjana
2018-01-01
This paper presents research on using a model-driven approach to the development and management of electronic courses. We propose a course management system which stores a course model represented as distinct machine-readable components containing domain knowledge of different course aspects. Based on this formally defined platform-independent…
A study of multidimensional modeling approaches for data warehouse
Yusof, Sharmila Mat; Sidi, Fatimah; Ibrahim, Hamidah; Affendey, Lilly Suriani
2016-08-01
Data warehouse system is used to support the process of organizational decision making. Hence, the system must extract and integrate information from heterogeneous data sources in order to uncover relevant knowledge suitable for decision making process. However, the development of data warehouse is a difficult and complex process especially in its conceptual design (multidimensional modeling). Thus, there have been various approaches proposed to overcome the difficulty. This study surveys and compares the approaches of multidimensional modeling and highlights the issues, trend and solution proposed to date. The contribution is on the state of the art of the multidimensional modeling design.
Gray-box modelling approach for description of storage tunnel
DEFF Research Database (Denmark)
Harremoës, Poul; Carstensen, Jacob
1999-01-01
The dynamics of a storage tunnel is examined using a model based on on-line measured data and a combination of simple deterministic and black-box stochastic elements. This approach, called gray-box modeling, is a new promising methodology for giving an on-line state description of sewer systems...... of the water in the overflow structures. The capacity of a pump draining the storage tunnel is estimated for two different rain events, revealing that the pump was malfunctioning during the first rain event. The proposed modeling approach can be used in automated online surveillance and control and implemented...
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
Learning the Task Management Space of an Aircraft Approach Model
Krall, Joseph; Menzies, Tim; Davies, Misty
2014-01-01
Validating models of airspace operations is a particular challenge. These models are often aimed at finding and exploring safety violations, and aim to be accurate representations of real-world behavior. However, the rules governing the behavior are quite complex: nonlinear physics, operational modes, human behavior, and stochastic environmental concerns all determine the responses of the system. In this paper, we present a study on aircraft runway approaches as modeled in Georgia Tech's Work Models that Compute (WMC) simulation. We use a new learner, Genetic-Active Learning for Search-Based Software Engineering (GALE) to discover the Pareto frontiers defined by cognitive structures. These cognitive structures organize the prioritization and assignment of tasks of each pilot during approaches. We discuss the benefits of our approach, and also discuss future work necessary to enable uncertainty quantification.
Subspace identification of Hammer stein models using support vector machines
International Nuclear Information System (INIS)
Al-Dhaifallah, Mujahed
2011-01-01
System identification is the art of finding mathematical tools and algorithms that build an appropriate mathematical model of a system from measured input and output data. Hammerstein model, consisting of a memoryless nonlinearity followed by a dynamic linear element, is often a good trade-off as it can represent some dynamic nonlinear systems very accurately, but is nonetheless quite simple. Moreover, the extensive knowledge about LTI system representations can be applied to the dynamic linear block. On the other hand, finding an effective representation for the nonlinearity is an active area of research. Recently, support vector machines (SVMs) and least squares support vector machines (LS-SVMs) have demonstrated powerful abilities in approximating linear and nonlinear functions. In contrast with other approximation methods, SVMs do not require a-priori structural information. Furthermore, there are well established methods with guaranteed convergence (ordinary least squares, quadratic programming) for fitting LS-SVMs and SVMs. The general objective of this research is to develop new subspace algorithms for Hammerstein systems based on SVM regression.
A novel approach of modeling continuous dark hydrogen fermentation.
Alexandropoulou, Maria; Antonopoulou, Georgia; Lyberatos, Gerasimos
2018-02-01
In this study a novel modeling approach for describing fermentative hydrogen production in a continuous stirred tank reactor (CSTR) was developed, using the Aquasim modeling platform. This model accounts for the key metabolic reactions taking place in a fermentative hydrogen producing reactor, using fixed stoichiometry but different reaction rates. Biomass yields are determined based on bioenergetics. The model is capable of describing very well the variation in the distribution of metabolic products for a wide range of hydraulic retention times (HRT). The modeling approach is demonstrated using the experimental data obtained from a CSTR, fed with food industry waste (FIW), operating at different HRTs. The kinetic parameters were estimated through fitting to the experimental results. Hydrogen and total biogas production rates were predicted very well by the model, validating the basic assumptions regarding the implicated stoichiometric biochemical reactions and their kinetic rates. Copyright © 2017 Elsevier Ltd. All rights reserved.
An integrated modeling approach to age invariant face recognition
Alvi, Fahad Bashir; Pears, Russel
2015-03-01
This Research study proposes a novel method for face recognition based on Anthropometric features that make use of an integrated approach comprising of a global and personalized models. The system is aimed to at situations where lighting, illumination, and pose variations cause problems in face recognition. A Personalized model covers the individual aging patterns while a Global model captures general aging patterns in the database. We introduced a de-aging factor that de-ages each individual in the database test and training sets. We used the k nearest neighbor approach for building a personalized model and global model. Regression analysis was applied to build the models. During the test phase, we resort to voting on different features. We used FG-Net database for checking the results of our technique and achieved 65 percent Rank 1 identification rate.
Benchmarking novel approaches for modelling species range dynamics.
Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E
2016-08-01
Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches
On a model-based approach to radiation protection
International Nuclear Information System (INIS)
Waligorski, M.P.R.
2002-01-01
There is a preoccupation with linearity and absorbed dose as the basic quantifiers of radiation hazard. An alternative is the fluence approach, whereby radiation hazard may be evaluated, at least in principle, via an appropriate action cross section. In order to compare these approaches, it may be useful to discuss them as quantitative descriptors of survival and transformation-like endpoints in cell cultures in vitro - a system thought to be relevant to modelling radiation hazard. If absorbed dose is used to quantify these biological endpoints, then non-linear dose-effect relations have to be described, and, e.g. after doses of densely ionising radiation, dose-correction factors as high as 20 are required. In the fluence approach only exponential effect-fluence relationships can be readily described. Neither approach alone exhausts the scope of experimentally observed dependencies of effect on dose or fluence. Two-component models, incorporating a suitable mixture of the two approaches, are required. An example of such a model is the cellular track structure theory developed by Katz over thirty years ago. The practical consequences of modelling radiation hazard using this mixed two-component approach are discussed. (author)
Modeling gene expression measurement error: a quasi-likelihood approach
Directory of Open Access Journals (Sweden)
Strimmer Korbinian
2003-03-01
Full Text Available Abstract Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale. Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood. Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic variance structure of the data. As the quasi-likelihood behaves (almost like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also
A review of function modeling: Approaches and applications
Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.
2008-01-01
This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research fields of artificial intelligence, design theory, and maintenance are discussed. In this discussion the goals are to highlight the features of various classical approaches in relation to FM, to delin...
Top-down approach to unified supergravity models
International Nuclear Information System (INIS)
Hempfling, R.
1994-03-01
We introduce a new approach for studying unified supergravity models. In this approach all the parameters of the grand unified theory (GUT) are fixed by imposing the corresponding number of low energy observables. This determines the remaining particle spectrum whose dependence on the low energy observables can now be investigated. We also include some SUSY threshold corrections that have previously been neglected. In particular the SUSY threshold corrections to the fermion masses can have a significant impact on the Yukawa coupling unification. (orig.)
Intelligent Transportation and Evacuation Planning A Modeling-Based Approach
Naser, Arab
2012-01-01
Intelligent Transportation and Evacuation Planning: A Modeling-Based Approach provides a new paradigm for evacuation planning strategies and techniques. Recently, evacuation planning and modeling have increasingly attracted interest among researchers as well as government officials. This interest stems from the recent catastrophic hurricanes and weather-related events that occurred in the southeastern United States (Hurricane Katrina and Rita). The evacuation methods that were in place before and during the hurricanes did not work well and resulted in thousands of deaths. This book offers insights into the methods and techniques that allow for implementing mathematical-based, simulation-based, and integrated optimization and simulation-based engineering approaches for evacuation planning. This book also: Comprehensively discusses the application of mathematical models for evacuation and intelligent transportation modeling Covers advanced methodologies in evacuation modeling and planning Discusses principles a...
An object-oriented approach to energy-economic modeling
Energy Technology Data Exchange (ETDEWEB)
Wise, M.A.; Fox, J.A.; Sands, R.D.
1993-12-01
In this paper, the authors discuss the experiences in creating an object-oriented economic model of the U.S. energy and agriculture markets. After a discussion of some central concepts, they provide an overview of the model, focusing on the methodology of designing an object-oriented class hierarchy specification based on standard microeconomic production functions. The evolution of the model from the class definition stage to programming it in C++, a standard object-oriented programming language, will be detailed. The authors then discuss the main differences between writing the object-oriented program versus a procedure-oriented program of the same model. Finally, they conclude with a discussion of the advantages and limitations of the object-oriented approach based on the experience in building energy-economic models with procedure-oriented approaches and languages.
Multi-model approach to characterize human handwriting motion.
Chihi, I; Abdelkrim, A; Benrejeb, M
2016-02-01
This paper deals with characterization and modelling of human handwriting motion from two forearm muscle activity signals, called electromyography signals (EMG). In this work, an experimental approach was used to record the coordinates of a pen tip moving on the (x, y) plane and EMG signals during the handwriting act. The main purpose is to design a new mathematical model which characterizes this biological process. Based on a multi-model approach, this system was originally developed to generate letters and geometric forms written by different writers. A Recursive Least Squares algorithm is used to estimate the parameters of each sub-model of the multi-model basis. Simulations show good agreement between predicted results and the recorded data.
Wave Resource Characterization Using an Unstructured Grid Modeling Approach
Directory of Open Access Journals (Sweden)
Wei-Cheng Wu
2018-03-01
Full Text Available This paper presents a modeling study conducted on the central Oregon coast for wave resource characterization, using the unstructured grid Simulating WAve Nearshore (SWAN model coupled with a nested grid WAVEWATCH III® (WWIII model. The flexibility of models with various spatial resolutions and the effects of open boundary conditions simulated by a nested grid WWIII model with different physics packages were evaluated. The model results demonstrate the advantage of the unstructured grid-modeling approach for flexible model resolution and good model skills in simulating the six wave resource parameters recommended by the International Electrotechnical Commission in comparison to the observed data in Year 2009 at National Data Buoy Center Buoy 46050. Notably, spectral analysis indicates that the ST4 physics package improves upon the ST2 physics package’s ability to predict wave power density for large waves, which is important for wave resource assessment, load calculation of devices, and risk management. In addition, bivariate distributions show that the simulated sea state of maximum occurrence with the ST4 physics package matched the observed data better than with the ST2 physics package. This study demonstrated that the unstructured grid wave modeling approach, driven by regional nested grid WWIII outputs along with the ST4 physics package, can efficiently provide accurate wave hindcasts to support wave resource characterization. Our study also suggests that wind effects need to be considered if the dimension of the model domain is greater than approximately 100 km, or O (102 km.
A comprehensive dynamic modeling approach for giant magnetostrictive material actuators
International Nuclear Information System (INIS)
Gu, Guo-Ying; Zhu, Li-Min; Li, Zhi; Su, Chun-Yi
2013-01-01
In this paper, a comprehensive modeling approach for a giant magnetostrictive material actuator (GMMA) is proposed based on the description of nonlinear electromagnetic behavior, the magnetostrictive effect and frequency response of the mechanical dynamics. It maps the relationships between current and magnetic flux at the electromagnetic part to force and displacement at the mechanical part in a lumped parameter form. Towards this modeling approach, the nonlinear hysteresis effect of the GMMA appearing only in the electrical part is separated from the linear dynamic plant in the mechanical part. Thus, a two-module dynamic model is developed to completely characterize the hysteresis nonlinearity and the dynamic behaviors of the GMMA. The first module is a static hysteresis model to describe the hysteresis nonlinearity, and the cascaded second module is a linear dynamic plant to represent the dynamic behavior. To validate the proposed dynamic model, an experimental platform is established. Then, the linear dynamic part and the nonlinear hysteresis part of the proposed model are identified in sequence. For the linear part, an approach based on axiomatic design theory is adopted. For the nonlinear part, a Prandtl–Ishlinskii model is introduced to describe the hysteresis nonlinearity and a constrained quadratic optimization method is utilized to identify its coefficients. Finally, experimental tests are conducted to demonstrate the effectiveness of the proposed dynamic model and the corresponding identification method. (paper)
Directory of Open Access Journals (Sweden)
Ali Moeini
2015-01-01
Full Text Available Regarding the ecommerce growth, websites play an essential role in business success. Therefore, many authors have offered website evaluation models since 1995. Although, the multiplicity and diversity of evaluation models make it difficult to integrate them into a single comprehensive model. In this paper a quantitative method has been used to integrate previous models into a comprehensive model that is compatible with them. In this approach the researcher judgment has no role in integration of models and the new model takes its validity from 93 previous models and systematic quantitative approach.
Smeared crack modelling approach for corrosion-induced concrete damage
DEFF Research Database (Denmark)
Thybo, Anna Emilie Anusha; Michel, Alexander; Stang, Henrik
2017-01-01
In this paper a smeared crack modelling approach is used to simulate corrosion-induced damage in reinforced concrete. The presented modelling approach utilizes a thermal analogy to mimic the expansive nature of solid corrosion products, while taking into account the penetration of corrosion...... products into the surrounding concrete, non-uniform precipitation of corrosion products, and creep. To demonstrate the applicability of the presented modelling approach, numerical predictions in terms of corrosion-induced deformations as well as formation and propagation of micro- and macrocracks were......-induced damage phenomena in reinforced concrete. Moreover, good agreements were also found between experimental and numerical data for corrosion-induced deformations along the circumference of the reinforcement....
A model-data based systems approach to process intensification
DEFF Research Database (Denmark)
Gani, Rafiqul
. Their developments, however, are largely due to experiment based trial and error approaches and while they do not require validation, they can be time consuming and resource intensive. Also, one may ask, can a truly new intensified unit operation be obtained in this way? An alternative two-stage approach is to apply...... a model-based synthesis method to systematically generate and evaluate alternatives in the first stage and an experiment-model based validation in the second stage. In this way, the search for alternatives is done very quickly, reliably and systematically over a wide range, while resources are preserved...... for focused validation of only the promising candidates in the second-stage. This approach, however, would be limited to intensification based on “known” unit operations, unless the PI process synthesis/design is considered at a lower level of aggregation, namely the phenomena level. That is, the model-based...
METHODOLOGICAL APPROACHES FOR MODELING THE RURAL SETTLEMENT DEVELOPMENT
Directory of Open Access Journals (Sweden)
Gorbenkova Elena Vladimirovna
2017-10-01
Full Text Available Subject: the paper describes the research results on validation of a rural settlement developmental model. The basic methods and approaches for solving the problem of assessment of the urban and rural settlement development efficiency are considered. Research objectives: determination of methodological approaches to modeling and creating a model for the development of rural settlements. Materials and methods: domestic and foreign experience in modeling the territorial development of urban and rural settlements and settlement structures was generalized. The motivation for using the Pentagon-model for solving similar problems was demonstrated. Based on a systematic analysis of existing development models of urban and rural settlements as well as the authors-developed method for assessing the level of agro-towns development, the systems/factors that are necessary for a rural settlement sustainable development are identified. Results: we created the rural development model which consists of five major systems that include critical factors essential for achieving a sustainable development of a settlement system: ecological system, economic system, administrative system, anthropogenic (physical system and social system (supra-structure. The methodological approaches for creating an evaluation model of rural settlements development were revealed; the basic motivating factors that provide interrelations of systems were determined; the critical factors for each subsystem were identified and substantiated. Such an approach was justified by the composition of tasks for territorial planning of the local and state administration levels. The feasibility of applying the basic Pentagon-model, which was successfully used for solving the analogous problems of sustainable development, was shown. Conclusions: the resulting model can be used for identifying and substantiating the critical factors for rural sustainable development and also become the basis of
An algebraic approach to modeling in software engineering
International Nuclear Information System (INIS)
Loegel, C.J.; Ravishankar, C.V.
1993-09-01
Our work couples the formalism of universal algebras with the engineering techniques of mathematical modeling to develop a new approach to the software engineering process. Our purpose in using this combination is twofold. First, abstract data types and their specification using universal algebras can be considered a common point between the practical requirements of software engineering and the formal specification of software systems. Second, mathematical modeling principles provide us with a means for effectively analyzing real-world systems. We first use modeling techniques to analyze a system and then represent the analysis using universal algebras. The rest of the software engineering process exploits properties of universal algebras that preserve the structure of our original model. This paper describes our software engineering process and our experience using it on both research and commercial systems. We need a new approach because current software engineering practices often deliver software that is difficult to develop and maintain. Formal software engineering approaches use universal algebras to describe ''computer science'' objects like abstract data types, but in practice software errors are often caused because ''real-world'' objects are improperly modeled. There is a large semantic gap between the customer's objects and abstract data types. In contrast, mathematical modeling uses engineering techniques to construct valid models for real-world systems, but these models are often implemented in an ad hoc manner. A combination of the best features of both approaches would enable software engineering to formally specify and develop software systems that better model real systems. Software engineering, like mathematical modeling, should concern itself first and foremost with understanding a real system and its behavior under given circumstances, and then with expressing this knowledge in an executable form
Towards a 3d Spatial Urban Energy Modelling Approach
Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.
2013-09-01
Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies
Modelling of ductile and cleavage fracture by local approach
International Nuclear Information System (INIS)
Samal, M.K.; Dutta, B.K.; Kushwaha, H.S.
2000-08-01
This report describes the modelling of ductile and cleavage fracture processes by local approach. It is now well known that the conventional fracture mechanics method based on single parameter criteria is not adequate to model the fracture processes. It is because of the existence of effect of size and geometry of flaw, loading type and rate on the fracture resistance behaviour of any structure. Hence, it is questionable to use same fracture resistance curves as determined from standard tests in the analysis of real life components because of existence of all the above effects. So, there is need to have a method in which the parameters used for the analysis will be true material properties, i.e. independent of geometry and size. One of the solutions to the above problem is the use of local approaches. These approaches have been extensively studied and applied to different materials (including SA33 Gr.6) in this report. Each method has been studied and reported in a separate section. This report has been divided into five sections. Section-I gives a brief review of the fundamentals of fracture process. Section-II deals with modelling of ductile fracture by locally uncoupled type of models. In this section, the critical cavity growth parameters of the different models have been determined for the primary heat transport (PHT) piping material of Indian pressurised heavy water reactor (PHWR). A comparative study has been done among different models. The dependency of the critical parameters on stress triaxiality factor has also been studied. It is observed that Rice and Tracey's model is the most suitable one. But, its parameters are not fully independent of triaxiality factor. For this purpose, a modification to Rice and Tracery's model is suggested in Section-III. Section-IV deals with modelling of ductile fracture process by locally coupled type of models. Section-V deals with the modelling of cleavage fracture process by Beremins model, which is based on Weibulls
Atomistic approach for modeling metal-semiconductor interfaces
DEFF Research Database (Denmark)
Stradi, Daniele; Martinez, Umberto; Blom, Anders
2016-01-01
realistic metal-semiconductor interfaces and allows for a direct comparison between theory and experiments via the I–V curve. In particular, it will be demonstrated how doping — and bias — modifies the Schottky barrier, and how finite size models (the slab approach) are unable to describe these interfaces......We present a general framework for simulating interfaces using an atomistic approach based on density functional theory and non-equilibrium Green's functions. The method includes all the relevant ingredients, such as doping and an accurate value of the semiconductor band gap, required to model...
Systems and context modeling approach to requirements analysis
Ahuja, Amrit; Muralikrishna, G.; Patwari, Puneet; Subhrojyoti, C.; Swaminathan, N.; Vin, Harrick
2014-08-01
Ensuring completeness and correctness of the requirements for a complex system such as the SKA is challenging. Current system engineering practice includes developing a stakeholder needs definition, a concept of operations, and defining system requirements in terms of use cases and requirements statements. We present a method that enhances this current practice into a collection of system models with mutual consistency relationships. These include stakeholder goals, needs definition and system-of-interest models, together with a context model that participates in the consistency relationships among these models. We illustrate this approach by using it to analyze the SKA system requirements.
An approach to multiscale modelling with graph grammars.
Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried
2014-09-01
Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.
A robust quantitative near infrared modeling approach for blend monitoring.
Mohan, Shikhar; Momose, Wataru; Katz, Jeffrey M; Hossain, Md Nayeem; Velez, Natasha; Drennen, James K; Anderson, Carl A
2018-01-30
This study demonstrates a material sparing Near-Infrared modeling approach for powder blend monitoring. In this new approach, gram scale powder mixtures are subjected to compression loads to simulate the effect of scale using an Instron universal testing system. Models prepared by the new method development approach (small-scale method) and by a traditional method development (blender-scale method) were compared by simultaneously monitoring a 1kg batch size blend run. Both models demonstrated similar model performance. The small-scale method strategy significantly reduces the total resources expended to develop Near-Infrared calibration models for on-line blend monitoring. Further, this development approach does not require the actual equipment (i.e., blender) to which the method will be applied, only a similar optical interface. Thus, a robust on-line blend monitoring method can be fully developed before any large-scale blending experiment is viable, allowing the blend method to be used during scale-up and blend development trials. Copyright © 2017. Published by Elsevier B.V.
Deep Appearance Models: A Deep Boltzmann Machine Approach for Face Modeling
Duong, Chi Nhan; Luu, Khoa; Quach, Kha Gia; Bui, Tien D.
2016-01-01
The "interpretation through synthesis" approach to analyze face images, particularly Active Appearance Models (AAMs) method, has become one of the most successful face modeling approaches over the last two decades. AAM models have ability to represent face images through synthesis using a controllable parameterized Principal Component Analysis (PCA) model. However, the accuracy and robustness of the synthesized faces of AAM are highly depended on the training sets and inherently on the genera...
Peltola, Olli; Raivonen, Maarit; Li, Xuefei; Vesala, Timo
2018-02-01
Emission via bubbling, i.e. ebullition, is one of the main methane (CH4) emission pathways from wetlands to the atmosphere. Direct measurement of gas bubble formation, growth and release in the peat-water matrix is challenging and in consequence these processes are relatively unknown and are coarsely represented in current wetland CH4 emission models. In this study we aimed to evaluate three ebullition modelling approaches and their effect on model performance. This was achieved by implementing the three approaches in one process-based CH4 emission model. All the approaches were based on some kind of threshold: either on CH4 pore water concentration (ECT), pressure (EPT) or free-phase gas volume (EBG) threshold. The model was run using 4 years of data from a boreal sedge fen and the results were compared with eddy covariance measurements of CH4 fluxes.Modelled annual CH4 emissions were largely unaffected by the different ebullition modelling approaches; however, temporal variability in CH4 emissions varied an order of magnitude between the approaches. Hence the ebullition modelling approach drives the temporal variability in modelled CH4 emissions and therefore significantly impacts, for instance, high-frequency (daily scale) model comparison and calibration against measurements. The modelling approach based on the most recent knowledge of the ebullition process (volume threshold, EBG) agreed the best with the measured fluxes (R2 = 0.63) and hence produced the most reasonable results, although there was a scale mismatch between the measurements (ecosystem scale with heterogeneous ebullition locations) and model results (single horizontally homogeneous peat column). The approach should be favoured over the two other more widely used ebullition modelling approaches and researchers are encouraged to implement it into their CH4 emission models.
Software sensors based on the grey-box modelling approach
DEFF Research Database (Denmark)
Carstensen, J.; Harremoës, P.; Strube, Rune
1996-01-01
In recent years the grey-box modelling approach has been applied to wastewater transportation and treatment Grey-box models are characterized by the combination of deterministic and stochastic terms to form a model where all the parameters are statistically identifiable from the on......-box model for the specific dynamics is identified. Similarly, an on-line software sensor for detecting the occurrence of backwater phenomena can be developed by comparing the dynamics of a flow measurement with a nearby level measurement. For treatment plants it is found that grey-box models applied to on......-line measurements. With respect to the development of software sensors, the grey-box models possess two important features. Firstly, the on-line measurements can be filtered according to the grey-box model in order to remove noise deriving from the measuring equipment and controlling devices. Secondly, the grey...
Bianchi VI0 and III models: self-similar approach
International Nuclear Information System (INIS)
Belinchon, Jose Antonio
2009-01-01
We study several cosmological models with Bianchi VI 0 and III symmetries under the self-similar approach. We find new solutions for the 'classical' perfect fluid model as well as for the vacuum model although they are really restrictive for the equation of state. We also study a perfect fluid model with time-varying constants, G and Λ. As in other studied models we find that the behaviour of G and Λ are related. If G behaves as a growing time function then Λ is a positive decreasing time function but if G is decreasing then Λ 0 is negative. We end by studying a massive cosmic string model, putting special emphasis in calculating the numerical values of the equations of state. We show that there is no SS solution for a string model with time-varying constants.
Environmental Radiation Effects on Mammals A Dynamical Modeling Approach
Smirnova, Olga A
2010-01-01
This text is devoted to the theoretical studies of radiation effects on mammals. It uses the framework of developed deterministic mathematical models to investigate the effects of both acute and chronic irradiation in a wide range of doses and dose rates on vital body systems including hematopoiesis, small intestine and humoral immunity, as well as on the development of autoimmune diseases. Thus, these models can contribute to the development of the system and quantitative approaches in radiation biology and ecology. This text is also of practical use. Its modeling studies of the dynamics of granulocytopoiesis and thrombocytopoiesis in humans testify to the efficiency of employment of the developed models in the investigation and prediction of radiation effects on these hematopoietic lines. These models, as well as the properly identified models of other vital body systems, could provide a better understanding of the radiation risks to health. The modeling predictions will enable the implementation of more ef...
Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.
Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C
2014-05-01
Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.
A new approach to Naturalness in SUSY models
Ghilencea, D M
2013-01-01
We review recent results that provide a new approach to the old problem of naturalness in supersymmetric models, without relying on subjective definitions for the fine-tuning associated with {\\it fixing} the EW scale (to its measured value) in the presence of quantum corrections. The approach can address in a model-independent way many questions related to this problem. The results show that naturalness and its measure (fine-tuning) are an intrinsic part of the likelihood to fit the data that {\\it includes} the EW scale. One important consequence is that the additional {\\it constraint} of fixing the EW scale, usually not imposed in the data fits of the models, impacts on their overall likelihood to fit the data (or chi^2/ndf, ndf: number of degrees of freedom). This has negative implications for the viability of currently popular supersymmetric extensions of the Standard Model.
Model selection and inference a practical information-theoretic approach
Burnham, Kenneth P
1998-01-01
This book is unique in that it covers the philosophy of model-based data analysis and an omnibus strategy for the analysis of empirical data The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data Kullback-Leibler information represents a fundamental quantity in science and is Hirotugu Akaike's basis for model selection The maximized log-likelihood function can be bias-corrected to provide an estimate of expected, relative Kullback-Leibler information This leads to Akaike's Information Criterion (AIC) and various extensions and these are relatively simple and easy to use in practice, but little taught in statistics classes and far less understood in the applied sciences than should be the case The information theoretic approaches provide a unified and rigorous theory, an extension of likelihood theory, an important application of information theory, and are ...
Merits of a Scenario Approach in Dredge Plume Modelling
DEFF Research Database (Denmark)
Pedersen, Claus; Chu, Amy Ling Chu; Hjelmager Jensen, Jacob
2011-01-01
Dredge plume modelling is a key tool for quantification of potential impacts to inform the EIA process. There are, however, significant uncertainties associated with the modelling at the EIA stage when both dredging methodology and schedule are likely to be a guess at best as the dredging...... contractor would rarely have been appointed. Simulation of a few variations of an assumed full dredge period programme will generally not provide a good representation of the overall environmental risks associated with the programme. An alternative dredge plume modelling strategy that attempts to encapsulate...... uncertainties associated with preliminary dredging programmes by using a scenario-based modelling approach is presented. The approach establishes a set of representative and conservative scenarios for key factors controlling the spill and plume dispersion and simulates all combinations of e.g. dredge, climatic...
Regularization of quantum gravity in the matrix model approach
International Nuclear Information System (INIS)
Ueda, Haruhiko
1991-02-01
We study divergence problem of the partition function in the matrix model approach for two-dimensional quantum gravity. We propose a new model V(φ) = 1/2Trφ 2 + g 4 /NTrφ 4 + g'/N 4 Tr(φ 4 ) 2 and show that in the sphere case it has no divergence problem and the critical exponent is of pure gravity. (author)
PASSENGER TRAFFIC MOVEMENT MODELLING BY THE CELLULAR-AUTOMAT APPROACH
Directory of Open Access Journals (Sweden)
T. Mikhaylovskaya
2009-01-01
Full Text Available The mathematical model of passenger traffic movement developed on the basis of the cellular-automat approach is considered. The program realization of the cellular-automat model of pedastrians streams movement in pedestrian subways at presence of obstacles, at subway structure narrowing is presented. The optimum distances between the obstacles and the angle of subway structure narrowing providing pedastrians stream safe movement and traffic congestion occurance are determined.
Cheng, C. M.; Peng, Z. K.; Zhang, W. M.; Meng, G.
2017-03-01
Nonlinear problems have drawn great interest and extensive attention from engineers, physicists and mathematicians and many other scientists because most real systems are inherently nonlinear in nature. To model and analyze nonlinear systems, many mathematical theories and methods have been developed, including Volterra series. In this paper, the basic definition of the Volterra series is recapitulated, together with some frequency domain concepts which are derived from the Volterra series, including the general frequency response function (GFRF), the nonlinear output frequency response function (NOFRF), output frequency response function (OFRF) and associated frequency response function (AFRF). The relationship between the Volterra series and other nonlinear system models and nonlinear problem solving methods are discussed, including the Taylor series, Wiener series, NARMAX model, Hammerstein model, Wiener model, Wiener-Hammerstein model, harmonic balance method, perturbation method and Adomian decomposition. The challenging problems and their state of arts in the series convergence study and the kernel identification study are comprehensively introduced. In addition, a detailed review is then given on the applications of Volterra series in mechanical engineering, aeroelasticity problem, control engineering, electronic and electrical engineering.
The Generalised Ecosystem Modelling Approach in Radiological Assessment
International Nuclear Information System (INIS)
Klos, Richard
2008-03-01
An independent modelling capability is required by SSI in order to evaluate dose assessments carried out in Sweden by, amongst others, SKB. The main focus is the evaluation of the long-term radiological safety of radioactive waste repositories for both spent fuel and low-level radioactive waste. To meet the requirement for an independent modelling tool for use in biosphere dose assessments, SSI through its modelling team CLIMB commissioned the development of a new model in 2004, a project to produce an integrated model of radionuclides in the landscape. The generalised ecosystem modelling approach (GEMA) is the result. GEMA is a modular system of compartments representing the surface environment. It can be configured, through water and solid material fluxes, to represent local details in the range of ecosystem types found in the past, present and future Swedish landscapes. The approach is generic but fine tuning can be carried out using local details of the surface drainage system. The modular nature of the modelling approach means that GEMA modules can be linked to represent large scale surface drainage features over an extended domain in the landscape. System change can also be managed in GEMA, allowing a flexible and comprehensive model of the evolving landscape to be constructed. Environmental concentrations of radionuclides can be calculated and the GEMA dose pathway model provides a means of evaluating the radiological impact of radionuclide release to the surface environment. This document sets out the philosophy and details of GEMA and illustrates the functioning of the model with a range of examples featuring the recent CLIMB review of SKB's SR-Can assessment
The Generalised Ecosystem Modelling Approach in Radiological Assessment
Energy Technology Data Exchange (ETDEWEB)
Klos, Richard
2008-03-15
An independent modelling capability is required by SSI in order to evaluate dose assessments carried out in Sweden by, amongst others, SKB. The main focus is the evaluation of the long-term radiological safety of radioactive waste repositories for both spent fuel and low-level radioactive waste. To meet the requirement for an independent modelling tool for use in biosphere dose assessments, SSI through its modelling team CLIMB commissioned the development of a new model in 2004, a project to produce an integrated model of radionuclides in the landscape. The generalised ecosystem modelling approach (GEMA) is the result. GEMA is a modular system of compartments representing the surface environment. It can be configured, through water and solid material fluxes, to represent local details in the range of ecosystem types found in the past, present and future Swedish landscapes. The approach is generic but fine tuning can be carried out using local details of the surface drainage system. The modular nature of the modelling approach means that GEMA modules can be linked to represent large scale surface drainage features over an extended domain in the landscape. System change can also be managed in GEMA, allowing a flexible and comprehensive model of the evolving landscape to be constructed. Environmental concentrations of radionuclides can be calculated and the GEMA dose pathway model provides a means of evaluating the radiological impact of radionuclide release to the surface environment. This document sets out the philosophy and details of GEMA and illustrates the functioning of the model with a range of examples featuring the recent CLIMB review of SKB's SR-Can assessment
Reduced modeling of signal transduction – a modular approach
Directory of Open Access Journals (Sweden)
Ederer Michael
2007-09-01
Full Text Available Abstract Background Combinatorial complexity is a challenging problem in detailed and mechanistic mathematical modeling of signal transduction. This subject has been discussed intensively and a lot of progress has been made within the last few years. A software tool (BioNetGen was developed which allows an automatic rule-based set-up of mechanistic model equations. In many cases these models can be reduced by an exact domain-oriented lumping technique. However, the resulting models can still consist of a very large number of differential equations. Results We introduce a new reduction technique, which allows building modularized and highly reduced models. Compared to existing approaches further reduction of signal transduction networks is possible. The method also provides a new modularization criterion, which allows to dissect the model into smaller modules that are called layers and can be modeled independently. Hallmarks of the approach are conservation relations within each layer and connection of layers by signal flows instead of mass flows. The reduced model can be formulated directly without previous generation of detailed model equations. It can be understood and interpreted intuitively, as model variables are macroscopic quantities that are converted by rates following simple kinetics. The proposed technique is applicable without using complex mathematical tools and even without detailed knowledge of the mathematical background. However, we provide a detailed mathematical analysis to show performance and limitations of the method. For physiologically relevant parameter domains the transient as well as the stationary errors caused by the reduction are negligible. Conclusion The new layer based reduced modeling method allows building modularized and strongly reduced models of signal transduction networks. Reduced model equations can be directly formulated and are intuitively interpretable. Additionally, the method provides very good
A nonlinear complementarity approach for the national energy modeling system
International Nuclear Information System (INIS)
Gabriel, S.A.; Kydes, A.S.
1995-01-01
The National Energy Modeling System (NEMS) is a large-scale mathematical model that computes equilibrium fuel prices and quantities in the U.S. energy sector. At present, to generate these equilibrium values, NEMS sequentially solves a collection of linear programs and nonlinear equations. The NEMS solution procedure then incorporates the solutions of these linear programs and nonlinear equations in a nonlinear Gauss-Seidel approach. The authors describe how the current version of NEMS can be formulated as a particular nonlinear complementarity problem (NCP), thereby possibly avoiding current convergence problems. In addition, they show that the NCP format is equally valid for a more general form of NEMS. They also describe several promising approaches for solving the NCP form of NEMS based on recent Newton type methods for general NCPs. These approaches share the feature of needing to solve their direction-finding subproblems only approximately. Hence, they can effectively exploit the sparsity inherent in the NEMS NCP
Non-frontal Model Based Approach to Forensic Face Recognition
Dutta, A.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan
2012-01-01
In this paper, we propose a non-frontal model based approach which ensures that a face recognition system always gets to compare images having similar view (or pose). This requires a virtual suspect reference set that consists of non-frontal suspect images having pose similar to the surveillance
A Behavioral Decision Making Modeling Approach Towards Hedging Services
Pennings, J.M.E.; Candel, M.J.J.M.; Egelkraut, T.M.
2003-01-01
This paper takes a behavioral approach toward the market for hedging services. A behavioral decision-making model is developed that provides insight into how and why owner-managers decide the way they do regarding hedging services. Insight into those choice processes reveals information needed by
Export of microplastics from land to sea. A modelling approach
Siegfried, Max; Koelmans, A.A.; Besseling, E.; Kroeze, C.
2017-01-01
Quantifying the transport of plastic debris from river to sea is crucial for assessing the risks of plastic debris to human health and the environment. We present a global modelling approach to analyse the composition and quantity of point-source microplastic fluxes from European rivers to the sea.
The Bipolar Approach: A Model for Interdisciplinary Art History Courses.
Calabrese, John A.
1993-01-01
Describes a college level art history course based on the opposing concepts of Classicism and Romanticism. Contends that all creative work, such as film or architecture, can be categorized according to this bipolar model. Includes suggestions for objects to study and recommends this approach for art education at all education levels. (CFR)
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…
A review of function modeling : Approaches and applications
Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.
2008-01-01
This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research
A novel Monte Carlo approach to hybrid local volatility models
A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)
2017-01-01
textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.
Model-independent approach for dark matter phenomenology
Indian Academy of Sciences (India)
We have studied the phenomenology of dark matter at the ILC and cosmic positron experiments based on model-independent approach. We have found a strong correlation between dark matter signatures at the ILC and those in the indirect detection experiments of dark matter. Once the dark matter is discovered in the ...
Model-independent approach for dark matter phenomenology ...
Indian Academy of Sciences (India)
Abstract. We have studied the phenomenology of dark matter at the ILC and cosmic positron experiments based on model-independent approach. We have found a strong correlation between dark matter signatures at the ILC and those in the indirect detec- tion experiments of dark matter. Once the dark matter is discovered ...
The variational approach to the Glashow-Weinberg-Salam model
International Nuclear Information System (INIS)
Manka, R.; Sladkowski, J.
1987-01-01
The variational approach to the Glashow-Weinberg-Salam model, based on canonical quantization, is presented. It is shown that taking into consideration the Becchi-Rouet-Stora symmetry leads to the correct, temperature-dependent, effective potential. This generalization of the Weinberg-Coleman potential leads to a phase transition of the first kind
Methodological Approach for Modeling of Multienzyme in-pot Processes
DEFF Research Database (Denmark)
Andrade Santacoloma, Paloma de Gracia; Roman Martinez, Alicia; Sin, Gürkan
2011-01-01
This paper presents a methodological approach for modeling multi-enzyme in-pot processes. The methodology is exemplified stepwise through the bi-enzymatic production of N-acetyl-D-neuraminic acid (Neu5Ac) from N-acetyl-D-glucosamine (GlcNAc). In this case study, sensitivity analysis is also used ...
An Approach to Quality Estimation in Model-Based Development
DEFF Research Database (Denmark)
Holmegaard, Jens Peter; Koch, Peter; Ravn, Anders Peter
2004-01-01
We present an approach to estimation of parameters for design space exploration in Model-Based Development, where synthesis of a system is done in two stages. Component qualities like space, execution time or power consumption are defined in a repository by platform dependent values. Connectors...
EXTENDE MODEL OF COMPETITIVITY THROUG APPLICATION OF NEW APPROACH DIRECTIVES
Directory of Open Access Journals (Sweden)
Slavko Arsovski
2009-03-01
Full Text Available The basic subject of this work is the model of new approach impact on quality and safety products, and competency of our companies. This work represents real hypothesis on the basis of expert's experiences, in regard to that the infrastructure with using new approach directives wasn't examined until now, it isn't known which product or industry of Serbia is related to directives of the new approach and CE mark, and it is not known which are effects of the use of the CE mark. This work should indicate existing quality reserves and product's safety, the level of possible competency improvement and increasing the profit by discharging new approach directive requires.
Setting conservation management thresholds using a novel participatory modeling approach.
Addison, P F E; de Bie, K; Rumpff, L
2015-10-01
We devised a participatory modeling approach for setting management thresholds that show when management intervention is required to address undesirable ecosystem changes. This approach was designed to be used when management thresholds: must be set for environmental indicators in the face of multiple competing objectives; need to incorporate scientific understanding and value judgments; and will be set by participants with limited modeling experience. We applied our approach to a case study where management thresholds were set for a mat-forming brown alga, Hormosira banksii, in a protected area management context. Participants, including management staff and scientists, were involved in a workshop to test the approach, and set management thresholds to address the threat of trampling by visitors to an intertidal rocky reef. The approach involved trading off the environmental objective, to maintain the condition of intertidal reef communities, with social and economic objectives to ensure management intervention was cost-effective. Ecological scenarios, developed using scenario planning, were a key feature that provided the foundation for where to set management thresholds. The scenarios developed represented declines in percent cover of H. banksii that may occur under increased threatening processes. Participants defined 4 discrete management alternatives to address the threat of trampling and estimated the effect of these alternatives on the objectives under each ecological scenario. A weighted additive model was used to aggregate participants' consequence estimates. Model outputs (decision scores) clearly expressed uncertainty, which can be considered by decision makers and used to inform where to set management thresholds. This approach encourages a proactive form of conservation, where management thresholds and associated actions are defined a priori for ecological indicators, rather than reacting to unexpected ecosystem changes in the future. © 2015 The
Accurate phenotyping: Reconciling approaches through Bayesian model averaging.
Directory of Open Access Journals (Sweden)
Carla Chia-Ming Chen
Full Text Available Genetic research into complex diseases is frequently hindered by a lack of clear biomarkers for phenotype ascertainment. Phenotypes for such diseases are often identified on the basis of clinically defined criteria; however such criteria may not be suitable for understanding the genetic composition of the diseases. Various statistical approaches have been proposed for phenotype definition; however our previous studies have shown that differences in phenotypes estimated using different approaches have substantial impact on subsequent analyses. Instead of obtaining results based upon a single model, we propose a new method, using Bayesian model averaging to overcome problems associated with phenotype definition. Although Bayesian model averaging has been used in other fields of research, this is the first study that uses Bayesian model averaging to reconcile phenotypes obtained using multiple models. We illustrate the new method by applying it to simulated genetic and phenotypic data for Kofendred personality disorder-an imaginary disease with several sub-types. Two separate statistical methods were used to identify clusters of individuals with distinct phenotypes: latent class analysis and grade of membership. Bayesian model averaging was then used to combine the two clusterings for the purpose of subsequent linkage analyses. We found that causative genetic loci for the disease produced higher LOD scores using model averaging than under either individual model separately. We attribute this improvement to consolidation of the cores of phenotype clusters identified using each individual method.
An Alternative Approach to the Extended Drude Model
Gantzler, N. J.; Dordevic, S. V.
2018-05-01
The original Drude model, proposed over a hundred years ago, is still used today for the analysis of optical properties of solids. Within this model, both the plasma frequency and quasiparticle scattering rate are constant, which makes the model rather inflexible. In order to circumvent this problem, the so-called extended Drude model was proposed, which allowed for the frequency dependence of both the quasiparticle scattering rate and the effective mass. In this work we will explore an alternative approach to the extended Drude model. Here, one also assumes that the quasiparticle scattering rate is frequency dependent; however, instead of the effective mass, the plasma frequency becomes frequency-dependent. This alternative model is applied to the high Tc superconductor Bi2Sr2CaCu2O8+δ (Bi2212) with Tc = 92 K, and the results are compared and contrasted with the ones obtained from the conventional extended Drude model. The results point to several advantages of this alternative approach to the extended Drude model.
Multiphysics modeling using COMSOL a first principles approach
Pryor, Roger W
2011-01-01
Multiphysics Modeling Using COMSOL rapidly introduces the senior level undergraduate, graduate or professional scientist or engineer to the art and science of computerized modeling for physical systems and devices. It offers a step-by-step modeling methodology through examples that are linked to the Fundamental Laws of Physics through a First Principles Analysis approach. The text explores a breadth of multiphysics models in coordinate systems that range from 1D to 3D and introduces the readers to the numerical analysis modeling techniques employed in the COMSOL Multiphysics software. After readers have built and run the examples, they will have a much firmer understanding of the concepts, skills, and benefits acquired from the use of computerized modeling techniques to solve their current technological problems and to explore new areas of application for their particular technological areas of interest.
Evaluation of Workflow Management Systems - A Meta Model Approach
Directory of Open Access Journals (Sweden)
Michael Rosemann
1998-11-01
Full Text Available The automated enactment of processes through the use of workflow management systems enables the outsourcing of the control flow from application systems. By now a large number of systems, that follow different workflow paradigms, are available. This leads to the problem of selecting the appropriate workflow management system for a given situation. In this paper we outline the benefits of a meta model approach for the evaluation and comparison of different workflow management systems. After a general introduction on the topic of meta modeling the meta models of the workflow management systems WorkParty (Siemens Nixdorf and FlowMark (IBM are compared as an example. These product specific meta models can be generalized to meta reference models, which helps to specify a workflow methodology. Exemplary, an organisational reference meta model is presented, which helps users in specifying their requirements for a workflow management system.
Generalised additive modelling approach to the fermentation process of glutamate.
Liu, Chun-Bo; Li, Yun; Pan, Feng; Shi, Zhong-Ping
2011-03-01
In this work, generalised additive models (GAMs) were used for the first time to model the fermentation of glutamate (Glu). It was found that three fermentation parameters fermentation time (T), dissolved oxygen (DO) and oxygen uptake rate (OUR) could capture 97% variance of the production of Glu during the fermentation process through a GAM model calibrated using online data from 15 fermentation experiments. This model was applied to investigate the individual and combined effects of T, DO and OUR on the production of Glu. The conditions to optimize the fermentation process were proposed based on the simulation study from this model. Results suggested that the production of Glu can reach a high level by controlling concentration levels of DO and OUR to the proposed optimization conditions during the fermentation process. The GAM approach therefore provides an alternative way to model and optimize the fermentation process of Glu. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.
Validation of Slosh Modeling Approach Using STAR-CCM+
Benson, David J.; Ng, Wanyi
2018-01-01
Without an adequate understanding of propellant slosh, the spacecraft attitude control system may be inadequate to control the spacecraft or there may be an unexpected loss of science observation time due to higher slosh settling times. Computational fluid dynamics (CFD) is used to model propellant slosh. STAR-CCM+ is a commercially available CFD code. This paper seeks to validate the CFD modeling approach via a comparison between STAR-CCM+ liquid slosh modeling results and experimental, empirically, and analytically derived results. The geometries examined are a bare right cylinder tank and a right cylinder with a single ring baffle.
Feedback structure based entropy approach for multiple-model estimation
Institute of Scientific and Technical Information of China (English)
Shen-tu Han; Xue Anke; Guo Yunfei
2013-01-01
The variable-structure multiple-model (VSMM) approach, one of the multiple-model (MM) methods, is a popular and effective approach in handling problems with mode uncertainties. The model sequence set adaptation (MSA) is the key to design a better VSMM. However, MSA methods in the literature have big room to improve both theoretically and practically. To this end, we propose a feedback structure based entropy approach that could find the model sequence sets with the smallest size under certain conditions. The filtered data are fed back in real time and can be used by the minimum entropy (ME) based VSMM algorithms, i.e., MEVSMM. Firstly, the full Markov chains are used to achieve optimal solutions. Secondly, the myopic method together with particle filter (PF) and the challenge match algorithm are also used to achieve sub-optimal solutions, a trade-off between practicability and optimality. The numerical results show that the proposed algorithm provides not only refined model sets but also a good robustness margin and very high accuracy.
Polynomial Chaos Expansion Approach to Interest Rate Models
Directory of Open Access Journals (Sweden)
Luca Di Persio
2015-01-01
Full Text Available The Polynomial Chaos Expansion (PCE technique allows us to recover a finite second-order random variable exploiting suitable linear combinations of orthogonal polynomials which are functions of a given stochastic quantity ξ, hence acting as a kind of random basis. The PCE methodology has been developed as a mathematically rigorous Uncertainty Quantification (UQ method which aims at providing reliable numerical estimates for some uncertain physical quantities defining the dynamic of certain engineering models and their related simulations. In the present paper, we use the PCE approach in order to analyze some equity and interest rate models. In particular, we take into consideration those models which are based on, for example, the Geometric Brownian Motion, the Vasicek model, and the CIR model. We present theoretical as well as related concrete numerical approximation results considering, without loss of generality, the one-dimensional case. We also provide both an efficiency study and an accuracy study of our approach by comparing its outputs with the ones obtained adopting the Monte Carlo approach, both in its standard and its enhanced version.
Popularity Modeling for Mobile Apps: A Sequential Approach.
Zhu, Hengshu; Liu, Chuanren; Ge, Yong; Xiong, Hui; Chen, Enhong
2015-07-01
The popularity information in App stores, such as chart rankings, user ratings, and user reviews, provides an unprecedented opportunity to understand user experiences with mobile Apps, learn the process of adoption of mobile Apps, and thus enables better mobile App services. While the importance of popularity information is well recognized in the literature, the use of the popularity information for mobile App services is still fragmented and under-explored. To this end, in this paper, we propose a sequential approach based on hidden Markov model (HMM) for modeling the popularity information of mobile Apps toward mobile App services. Specifically, we first propose a popularity based HMM (PHMM) to model the sequences of the heterogeneous popularity observations of mobile Apps. Then, we introduce a bipartite based method to precluster the popularity observations. This can help to learn the parameters and initial values of the PHMM efficiently. Furthermore, we demonstrate that the PHMM is a general model and can be applicable for various mobile App services, such as trend based App recommendation, rating and review spam detection, and ranking fraud detection. Finally, we validate our approach on two real-world data sets collected from the Apple Appstore. Experimental results clearly validate both the effectiveness and efficiency of the proposed popularity modeling approach.
Common modelling approaches for training simulators for nuclear power plants
International Nuclear Information System (INIS)
1990-02-01
Training simulators for nuclear power plant operating staff have gained increasing importance over the last twenty years. One of the recommendations of the 1983 IAEA Specialists' Meeting on Nuclear Power Plant Training Simulators in Helsinki was to organize a Co-ordinated Research Programme (CRP) on some aspects of training simulators. The goal statement was: ''To establish and maintain a common approach to modelling for nuclear training simulators based on defined training requirements''. Before adapting this goal statement, the participants considered many alternatives for defining the common aspects of training simulator models, such as the programming language used, the nature of the simulator computer system, the size of the simulation computers, the scope of simulation. The participants agreed that it was the training requirements that defined the need for a simulator, the scope of models and hence the type of computer complex that was required, the criteria for fidelity and verification, and was therefore the most appropriate basis for the commonality of modelling approaches. It should be noted that the Co-ordinated Research Programme was restricted, for a variety of reasons, to consider only a few aspects of training simulators. This report reflects these limitations, and covers only the topics considered within the scope of the programme. The information in this document is intended as an aid for operating organizations to identify possible modelling approaches for training simulators for nuclear power plants. 33 refs
An approach to ductile fracture resistance modelling in pipeline steels
Energy Technology Data Exchange (ETDEWEB)
Pussegoda, L.N.; Fredj, A. [BMT Fleet Technology Ltd., Kanata (Canada)
2009-07-01
Ductile fracture resistance studies of high grade steels in the pipeline industry often included analyses of the crack tip opening angle (CTOA) parameter using 3-point bend steel specimens. The CTOA is a function of specimen ligament size in high grade materials. Other resistance measurements may include steady state fracture propagation energy, critical fracture strain, and the adoption of damage mechanisms. Modelling approaches for crack propagation were discussed in this abstract. Tension tests were used to calibrate damage model parameters. Results from the tests were then applied to the crack propagation in a 3-point bend specimen using modern 1980 vintage steels. Limitations and approaches to overcome the difficulties associated with crack propagation modelling were discussed.
High dimensions - a new approach to fermionic lattice models
International Nuclear Information System (INIS)
Vollhardt, D.
1991-01-01
The limit of high spatial dimensions d, which is well-established in the theory of classical and localized spin models, is shown to be a fruitful approach also to itinerant fermion systems, such as the Hubbard model and the periodic Anderson model. Many investigations which are probability difficult in finite dimensions, become tractable in d=∞. At the same time essential features of systems in d=3 and even lower dimensions are very well described by the results obtained in d=∞. A wide range of applications of this new concept (e.g., in perturbation theory, Fermi liquid theory, variational approaches, exact results, etc.) is discussed and the state-of-the-art is reviewed. (orig.)
A fuzzy approach for modelling radionuclide in lake system
International Nuclear Information System (INIS)
Desai, H.K.; Christian, R.A.; Banerjee, J.; Patra, A.K.
2013-01-01
Radioactive liquid waste is generated during operation and maintenance of Pressurised Heavy Water Reactors (PHWRs). Generally low level liquid waste is diluted and then discharged into the near by water-body through blowdown water discharge line as per the standard waste management practice. The effluents from nuclear installations are treated adequately and then released in a controlled manner under strict compliance of discharge criteria. An attempt was made to predict the concentration of 3 H released from Kakrapar Atomic Power Station at Ratania Regulator, about 2.5 km away from the discharge point, where human exposure is expected. Scarcity of data and complex geometry of the lake prompted the use of Heuristic approach. Under this condition, Fuzzy rule based approach was adopted to develop a model, which could predict 3 H concentration at Ratania Regulator. Three hundred data were generated for developing the fuzzy rules, in which input parameters were water flow from lake and 3 H concentration at discharge point. The Output was 3 H concentration at Ratania Regulator. These data points were generated by multiple regression analysis of the original data. Again by using same methodology hundred data were generated for the validation of the model, which were compared against the predicted output generated by using Fuzzy Rule based approach. Root Mean Square Error of the model came out to be 1.95, which showed good agreement by Fuzzy model of natural ecosystem. -- Highlights: • Uncommon approach (Fuzzy Rule Base) of modelling radionuclide dispersion in Lake. • Predicts 3 H released from Kakrapar Atomic Power Station at a point of human exposure. • RMSE of fuzzy model is 1.95, which means, it has well imitated natural ecosystem
Modeling energy fluxes in heterogeneous landscapes employing a mosaic approach
Klein, Christian; Thieme, Christoph; Priesack, Eckart
2015-04-01
Recent studies show that uncertainties in regional and global climate and weather simulations are partly due to inadequate descriptions of the energy flux exchanges between the land surface and the atmosphere. One major shortcoming is the limitation of the grid-cell resolution, which is recommended to be about at least 3x3 km² in most models due to limitations in the model physics. To represent each individual grid cell most models select one dominant soil type and one dominant land use type. This resolution, however, is often too coarse in regions where the spatial diversity of soil and land use types are high, e.g. in Central Europe. An elegant method to avoid the shortcoming of grid cell resolution is the so called mosaic approach. This approach is part of the recently developed ecosystem model framework Expert-N 5.0. The aim of this study was to analyze the impact of the characteristics of two managed fields, planted with winter wheat and potato, on the near surface soil moistures and on the near surface energy flux exchanges of the soil-plant-atmosphere interface. The simulated energy fluxes were compared with eddy flux tower measurements between the respective fields at the research farm Scheyern, North-West of Munich, Germany. To perform these simulations, we coupled the ecosystem model Expert-N 5.0 to an analytical footprint model. The coupled model system has the ability to calculate the mixing ratio of the surface energy fluxes at a given point within one grid cell (in this case at the flux tower between the two fields). This approach accounts for the differences of the two soil types, of land use managements, and of canopy properties due to footprint size dynamics. Our preliminary simulation results show that a mosaic approach can improve modeling and analyzing energy fluxes when the land surface is heterogeneous. In this case our applied method is a promising approach to extend weather and climate models on the regional and on the global scale.
A global sensitivity analysis approach for morphogenesis models
Boas, Sonja E. M.
2015-11-21
Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.
A global sensitivity analysis approach for morphogenesis models.
Boas, Sonja E M; Navarro Jimenez, Maria I; Merks, Roeland M H; Blom, Joke G
2015-11-21
Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such 'black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all 'black-box' models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.
DEFF Research Database (Denmark)
Simonsen, Kent Inge; Kristensen, Lars Michael
2013-01-01
Formal modelling of protocols is often aimed at one specific purpose such as verification or automatically generating an implementation. This leads to models that are useful for one purpose, but not for others. Being able to derive models for verification and implementation from a single model...... is beneficial both in terms of reduced total modelling effort and confidence that the verification results are valid also for the implementation model. In this paper we introduce the concept of a descriptive specification model and an approach based on refining a descriptive model to target both verification...... how this model can be refined to target both verification and implementation....
Unraveling the Mechanisms of Manual Therapy: Modeling an Approach.
Bialosky, Joel E; Beneciuk, Jason M; Bishop, Mark D; Coronado, Rogelio A; Penza, Charles W; Simon, Corey B; George, Steven Z
2018-01-01
Synopsis Manual therapy interventions are popular among individual health care providers and their patients; however, systematic reviews do not strongly support their effectiveness. Small treatment effect sizes of manual therapy interventions may result from a "one-size-fits-all" approach to treatment. Mechanistic-based treatment approaches to manual therapy offer an intriguing alternative for identifying patients likely to respond to manual therapy. However, the current lack of knowledge of the mechanisms through which manual therapy interventions inhibit pain limits such an approach. The nature of manual therapy interventions further confounds such an approach, as the related mechanisms are likely a complex interaction of factors related to the patient, the provider, and the environment in which the intervention occurs. Therefore, a model to guide both study design and the interpretation of findings is necessary. We have previously proposed a model suggesting that the mechanical force from a manual therapy intervention results in systemic neurophysiological responses leading to pain inhibition. In this clinical commentary, we provide a narrative appraisal of the model and recommendations to advance the study of manual therapy mechanisms. J Orthop Sports Phys Ther 2018;48(1):8-18. doi:10.2519/jospt.2018.7476.
Implementation of Reseptive Esteemy Approach Model in Learning Reading Literature
Directory of Open Access Journals (Sweden)
Titin Nurhayatin
2017-03-01
Full Text Available Research on the implementation of aesthetic model of receptive aesthetic approach in learning to read the literature on the background of the low quality of results and learning process of Indonesian language, especially the study of literature. Students as prospective teachers of Indonesian language are expected to have the ability to speak, have literature, and their learning in a balanced manner in accordance with the curriculum demands. This study examines the effectiveness, quality, acceptability, and sustainability of the aesthetic approach of receptions in improving students' literary skills. Based on these problems, this study is expected to produce a learning model that contributes high in improving the quality of results and the process of learning literature. This research was conducted on the students of Language Education Program, Indonesian Literature and Regional FKIP Pasundan University. The research method used is experiment with randomized type pretest-posttest control group design. Based on preliminary and final test data obtained in the experimental class the average preliminary test was 55.86 and the average final test was 76.75. From the preliminary test data in the control class the average score was 55.07 and the average final test was 68.76. These data suggest that there is a greater increase in grades in the experimental class using the aesthetic approach of the reception compared with the increase in values in the control class using a conventional approach. The results show that the aesthetic approach of receptions is more effective than the conventional approach in literary reading. Based on observations, acceptance, and views of sustainability, the aesthetic approach of receptions in literary learning is expected to be an alternative and solution in overcoming the problems of literary learning and improving the quality of Indonesian learning outcomes and learning process.
Polynomial fuzzy model-based approach for underactuated surface vessels
DEFF Research Database (Denmark)
Khooban, Mohammad Hassan; Vafamand, Navid; Dragicevic, Tomislav
2018-01-01
The main goal of this study is to introduce a new polynomial fuzzy model-based structure for a class of marine systems with non-linear and polynomial dynamics. The suggested technique relies on a polynomial Takagi–Sugeno (T–S) fuzzy modelling, a polynomial dynamic parallel distributed compensation...... surface vessel (USV). Additionally, in order to overcome the USV control challenges, including the USV un-modelled dynamics, complex nonlinear dynamics, external disturbances and parameter uncertainties, the polynomial fuzzy model representation is adopted. Moreover, the USV-based control structure...... and a sum-of-squares (SOS) decomposition. The new proposed approach is a generalisation of the standard T–S fuzzy models and linear matrix inequality which indicated its effectiveness in decreasing the tracking time and increasing the efficiency of the robust tracking control problem for an underactuated...
Bayesian approach to errors-in-variables in regression models
Rozliman, Nur Aainaa; Ibrahim, Adriana Irawati Nur; Yunus, Rossita Mohammad
2017-05-01
In many applications and experiments, data sets are often contaminated with error or mismeasured covariates. When at least one of the covariates in a model is measured with error, Errors-in-Variables (EIV) model can be used. Measurement error, when not corrected, would cause misleading statistical inferences and analysis. Therefore, our goal is to examine the relationship of the outcome variable and the unobserved exposure variable given the observed mismeasured surrogate by applying the Bayesian formulation to the EIV model. We shall extend the flexible parametric method proposed by Hossain and Gustafson (2009) to another nonlinear regression model which is the Poisson regression model. We shall then illustrate the application of this approach via a simulation study using Markov chain Monte Carlo sampling methods.
A hidden Markov model approach to neuron firing patterns.
Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G
1996-11-01
Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing.
Practical modeling approaches for geological storage of carbon dioxide.
Celia, Michael A; Nordbotten, Jan M
2009-01-01
The relentless increase of anthropogenic carbon dioxide emissions and the associated concerns about climate change have motivated new ideas about carbon-constrained energy production. One technological approach to control carbon dioxide emissions is carbon capture and storage, or CCS. The underlying idea of CCS is to capture the carbon before it emitted to the atmosphere and store it somewhere other than the atmosphere. Currently, the most attractive option for large-scale storage is in deep geological formations, including deep saline aquifers. Many physical and chemical processes can affect the fate of the injected CO2, with the overall mathematical description of the complete system becoming very complex. Our approach to the problem has been to reduce complexity as much as possible, so that we can focus on the few truly important questions about the injected CO2, most of which involve leakage out of the injection formation. Toward this end, we have established a set of simplifying assumptions that allow us to derive simplified models, which can be solved numerically or, for the most simplified cases, analytically. These simplified models allow calculation of solutions to large-scale injection and leakage problems in ways that traditional multicomponent multiphase simulators cannot. Such simplified models provide important tools for system analysis, screening calculations, and overall risk-assessment calculations. We believe this is a practical and important approach to model geological storage of carbon dioxide. It also serves as an example of how complex systems can be simplified while retaining the essential physics of the problem.
A fuzzy approach for modelling radionuclide in lake system.
Desai, H K; Christian, R A; Banerjee, J; Patra, A K
2013-10-01
Radioactive liquid waste is generated during operation and maintenance of Pressurised Heavy Water Reactors (PHWRs). Generally low level liquid waste is diluted and then discharged into the near by water-body through blowdown water discharge line as per the standard waste management practice. The effluents from nuclear installations are treated adequately and then released in a controlled manner under strict compliance of discharge criteria. An attempt was made to predict the concentration of (3)H released from Kakrapar Atomic Power Station at Ratania Regulator, about 2.5 km away from the discharge point, where human exposure is expected. Scarcity of data and complex geometry of the lake prompted the use of Heuristic approach. Under this condition, Fuzzy rule based approach was adopted to develop a model, which could predict (3)H concentration at Ratania Regulator. Three hundred data were generated for developing the fuzzy rules, in which input parameters were water flow from lake and (3)H concentration at discharge point. The Output was (3)H concentration at Ratania Regulator. These data points were generated by multiple regression analysis of the original data. Again by using same methodology hundred data were generated for the validation of the model, which were compared against the predicted output generated by using Fuzzy Rule based approach. Root Mean Square Error of the model came out to be 1.95, which showed good agreement by Fuzzy model of natural ecosystem. Copyright © 2013 Elsevier Ltd. All rights reserved.
Anthropomorphic Coding of Speech and Audio: A Model Inversion Approach
Directory of Open Access Journals (Sweden)
W. Bastiaan Kleijn
2005-06-01
Full Text Available Auditory modeling is a well-established methodology that provides insight into human perception and that facilitates the extraction of signal features that are most relevant to the listener. The aim of this paper is to provide a tutorial on perceptual speech and audio coding using an invertible auditory model. In this approach, the audio signal is converted into an auditory representation using an invertible auditory model. The auditory representation is quantized and coded. Upon decoding, it is then transformed back into the acoustic domain. This transformation converts a complex distortion criterion into a simple one, thus facilitating quantization with low complexity. We briefly review past work on auditory models and describe in more detail the components of our invertible model and its inversion procedure, that is, the method to reconstruct the signal from the output of the auditory model. We summarize attempts to use the auditory representation for low-bit-rate coding. Our approach also allows the exploitation of the inherent redundancy of the human auditory system for the purpose of multiple description (joint source-channel coding.
A modal approach to modeling spatially distributed vibration energy dissipation.
Energy Technology Data Exchange (ETDEWEB)
Segalman, Daniel Joseph
2010-08-01
The nonlinear behavior of mechanical joints is a confounding element in modeling the dynamic response of structures. Though there has been some progress in recent years in modeling individual joints, modeling the full structure with myriad frictional interfaces has remained an obstinate challenge. A strategy is suggested for structural dynamics modeling that can account for the combined effect of interface friction distributed spatially about the structure. This approach accommodates the following observations: (1) At small to modest amplitudes, the nonlinearity of jointed structures is manifest primarily in the energy dissipation - visible as vibration damping; (2) Correspondingly, measured vibration modes do not change significantly with amplitude; and (3) Significant coupling among the modes does not appear to result at modest amplitudes. The mathematical approach presented here postulates the preservation of linear modes and invests all the nonlinearity in the evolution of the modal coordinates. The constitutive form selected is one that works well in modeling spatially discrete joints. When compared against a mathematical truth model, the distributed dissipation approximation performs well.
A Bayesian Approach for Structural Learning with Hidden Markov Models
Directory of Open Access Journals (Sweden)
Cen Li
2002-01-01
Full Text Available Hidden Markov Models(HMM have proved to be a successful modeling paradigm for dynamic and spatial processes in many domains, such as speech recognition, genomics, and general sequence alignment. Typically, in these applications, the model structures are predefined by domain experts. Therefore, the HMM learning problem focuses on the learning of the parameter values of the model to fit the given data sequences. However, when one considers other domains, such as, economics and physiology, model structure capturing the system dynamic behavior is not available. In order to successfully apply the HMM methodology in these domains, it is important that a mechanism is available for automatically deriving the model structure from the data. This paper presents a HMM learning procedure that simultaneously learns the model structure and the maximum likelihood parameter values of a HMM from data. The HMM model structures are derived based on the Bayesian model selection methodology. In addition, we introduce a new initialization procedure for HMM parameter value estimation based on the K-means clustering method. Experimental results with artificially generated data show the effectiveness of the approach.
A Novel Approach to Implement Takagi-Sugeno Fuzzy Models.
Chang, Chia-Wen; Tao, Chin-Wang
2017-09-01
This paper proposes new algorithms based on the fuzzy c-regressing model algorithm for Takagi-Sugeno (T-S) fuzzy modeling of the complex nonlinear systems. A fuzzy c-regression state model (FCRSM) algorithm is a T-S fuzzy model in which the functional antecedent and the state-space-model-type consequent are considered with the available input-output data. The antecedent and consequent forms of the proposed FCRSM consists mainly of two advantages: one is that the FCRSM has low computation load due to only one input variable is considered in the antecedent part; another is that the unknown system can be modeled to not only the polynomial form but also the state-space form. Moreover, the FCRSM can be extended to FCRSM-ND and FCRSM-Free algorithms. An algorithm FCRSM-ND is presented to find the T-S fuzzy state-space model of the nonlinear system when the input-output data cannot be precollected and an assumed effective controller is available. In the practical applications, the mathematical model of controller may be hard to be obtained. In this case, an online tuning algorithm, FCRSM-FREE, is designed such that the parameters of a T-S fuzzy controller and the T-S fuzzy state model of an unknown system can be online tuned simultaneously. Four numerical simulations are given to demonstrate the effectiveness of the proposed approach.
Approach to Organizational Structure Modelling in Construction Companies
Directory of Open Access Journals (Sweden)
Ilin Igor V.
2016-01-01
Full Text Available Effective management system is one of the key factors of business success nowadays. Construction companies usually have a portfolio of independent projects running at the same time. Thus it is reasonable to take into account project orientation of such kind of business while designing the construction companies’ management system, which main components are business process system and organizational structure. The paper describes the management structure designing approach, based on the project-oriented nature of the construction projects, and propose a model of the organizational structure for the construction company. Application of the proposed approach will enable to assign responsibilities within the organizational structure in construction projects effectively and thus to shorten the time for projects allocation and to provide its smoother running. The practical case of using the approach also provided in the paper.
A Composite Modelling Approach to Decision Support by the Use of the CBA-DK Model
DEFF Research Database (Denmark)
Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen
2007-01-01
This paper presents a decision support system for assessment of transport infrastructure projects. The composite modelling approach, COSIMA, combines a cost-benefit analysis by use of the CBA-DK model with multi-criteria analysis applying the AHP and SMARTER techniques. The modelling uncertaintie...
The place of quantitative energy models in a prospective approach
International Nuclear Information System (INIS)
Taverdet-Popiolek, N.
2009-01-01
Futurology above all depends on having the right mind set. Gaston Berger summarizes the prospective approach in 5 five main thrusts: prepare for the distant future, be open-minded (have a systems and multidisciplinary approach), carry out in-depth analyzes (draw out actors which are really determinant or the future, as well as established shed trends), take risks (imagine risky but flexible projects) and finally think about humanity, futurology being a technique at the service of man to help him build a desirable future. On the other hand, forecasting is based on quantified models so as to deduce 'conclusions' about the future. In the field of energy, models are used to draw up scenarios which allow, for instance, measuring medium or long term effects of energy policies on greenhouse gas emissions or global welfare. Scenarios are shaped by the model's inputs (parameters, sets of assumptions) and outputs. Resorting to a model or projecting by scenario is useful in a prospective approach as it ensures coherence for most of the variables that have been identified through systems analysis and that the mind on its own has difficulty to grasp. Interpretation of each scenario must be carried out in the light o the underlying framework of assumptions (the backdrop), developed during the prospective stage. When the horizon is far away (very long-term), the worlds imagined by the futurologist contain breaks (technological, behavioural and organizational) which are hard to integrate into the models. It is here that the main limit for the use of models in futurology is located. (author)
Application of declarative modeling approaches for external events
International Nuclear Information System (INIS)
Anoba, R.C.
2005-01-01
Probabilistic Safety Assessments (PSAs) are increasingly being used as a tool for supporting the acceptability of design, procurement, construction, operation, and maintenance activities at Nuclear Power Plants. Since the issuance of Generic Letter 88-20 and subsequent IPE/IPEEE assessments, the NRC has issued several Regulatory Guides such as RG 1.174 to describe the use of PSA in risk-informed regulation activities. Most PSA have the capability to address internal events including internal floods. As the more demands are being placed for using the PSA to support risk-informed applications, there has been a growing need to integrate other eternal events (Seismic, Fire, etc.) into the logic models. Most external events involve spatial dependencies and usually impact the logic models at the component level. Therefore, manual insertion of external events impacts into a complex integrated fault tree model may be too cumbersome for routine uses of the PSA. Within the past year, a declarative modeling approach has been developed to automate the injection of external events into the PSA. The intent of this paper is to introduce the concept of declarative modeling in the context of external event applications. A declarative modeling approach involves the definition of rules for injection of external event impacts into the fault tree logic. A software tool such as the EPRI's XInit program can be used to interpret the pre-defined rules and automatically inject external event elements into the PSA. The injection process can easily be repeated, as required, to address plant changes, sensitivity issues, changes in boundary conditions, etc. External event elements may include fire initiating events, seismic initiating events, seismic fragilities, fire-induced hot short events, special human failure events, etc. This approach has been applied at a number of US nuclear power plants including a nuclear power plant in Romania. (authors)
Understanding complex urban systems multidisciplinary approaches to modeling
Gurr, Jens; Schmidt, J
2014-01-01
Understanding Complex Urban Systems takes as its point of departure the insight that the challenges of global urbanization and the complexity of urban systems cannot be understood – let alone ‘managed’ – by sectoral and disciplinary approaches alone. But while there has recently been significant progress in broadening and refining the methodologies for the quantitative modeling of complex urban systems, in deepening the theoretical understanding of cities as complex systems, or in illuminating the implications for urban planning, there is still a lack of well-founded conceptual thinking on the methodological foundations and the strategies of modeling urban complexity across the disciplines. Bringing together experts from the fields of urban and spatial planning, ecology, urban geography, real estate analysis, organizational cybernetics, stochastic optimization, and literary studies, as well as specialists in various systems approaches and in transdisciplinary methodologies of urban analysis, the volum...
A Variational Approach to the Modeling of MIMO Systems
Directory of Open Access Journals (Sweden)
Jraifi A
2007-01-01
Full Text Available Motivated by the study of the optimization of the quality of service for multiple input multiple output (MIMO systems in 3G (third generation, we develop a method for modeling MIMO channel . This method, which uses a statistical approach, is based on a variational form of the usual channel equation. The proposed equation is given by with scalar variable . Minimum distance of received vectors is used as the random variable to model MIMO channel. This variable is of crucial importance for the performance of the transmission system as it captures the degree of interference between neighbors vectors. Then, we use this approach to compute numerically the total probability of errors with respect to signal-to-noise ratio (SNR and then predict the numbers of antennas. By fixing SNR variable to a specific value, we extract informations on the optimal numbers of MIMO antennas.
On quantum approach to modeling of plasmon photovoltaic effect
DEFF Research Database (Denmark)
Kluczyk, Katarzyna; David, Christin; Jacak, Witold Aleksander
2017-01-01
Surface plasmons in metallic nanostructures including metallically nanomodified solar cells are conventionally studied and modeled by application of the Mie approach to plasmons or by the finite element solution of differential Maxwell equations with imposed boundary and material constraints (e...... to the semiconductor solar cell mediated by surface plasmons in metallic nanoparticles deposited on the top of the battery. In addition, short-ranged electron-electron interaction in metals is discussed in the framework of the semiclassical hydrodynamic model. The significance of the related quantum corrections......-aided photovoltaic phenomena. Quantum corrections considerably improve both the Mie and COMSOL approaches in this case. We present the semiclassical random phase approximation description of plasmons in metallic nanoparticles and apply the quantumFermi golden rule scheme to assess the sunlight energy transfer...
Innovation Networks New Approaches in Modelling and Analyzing
Pyka, Andreas
2009-01-01
The science of graphs and networks has become by now a well-established tool for modelling and analyzing a variety of systems with a large number of interacting components. Starting from the physical sciences, applications have spread rapidly to the natural and social sciences, as well as to economics, and are now further extended, in this volume, to the concept of innovations, viewed broadly. In an abstract, systems-theoretical approach, innovation can be understood as a critical event which destabilizes the current state of the system, and results in a new process of self-organization leading to a new stable state. The contributions to this anthology address different aspects of the relationship between innovation and networks. The various chapters incorporate approaches in evolutionary economics, agent-based modeling, social network analysis and econophysics and explore the epistemic tension between insights into economics and society-related processes, and the insights into new forms of complex dynamics.
Hypercompetitive Environments: An Agent-based model approach
Dias, Manuel; Araújo, Tanya
Information technology (IT) environments are characterized by complex changes and rapid evolution. Globalization and the spread of technological innovation have increased the need for new strategic information resources, both from individual firms and management environments. Improvements in multidisciplinary methods and, particularly, the availability of powerful computational tools, are giving researchers an increasing opportunity to investigate management environments in their true complex nature. The adoption of a complex systems approach allows for modeling business strategies from a bottom-up perspective — understood as resulting from repeated and local interaction of economic agents — without disregarding the consequences of the business strategies themselves to individual behavior of enterprises, emergence of interaction patterns between firms and management environments. Agent-based models are at the leading approach of this attempt.
Modeling fabrication of nuclear components: An integrative approach
Energy Technology Data Exchange (ETDEWEB)
Hench, K.W.
1996-08-01
Reduction of the nuclear weapons stockpile and the general downsizing of the nuclear weapons complex has presented challenges for Los Alamos. One is to design an optimized fabrication facility to manufacture nuclear weapon primary components in an environment of intense regulation and shrinking budgets. This dissertation presents an integrative two-stage approach to modeling the casting operation for fabrication of nuclear weapon primary components. The first stage optimizes personnel radiation exposure for the casting operation layout by modeling the operation as a facility layout problem formulated as a quadratic assignment problem. The solution procedure uses an evolutionary heuristic technique. The best solutions to the layout problem are used as input to the second stage - a simulation model that assesses the impact of competing layouts on operational performance. The focus of the simulation model is to determine the layout that minimizes personnel radiation exposures and nuclear material movement, and maximizes the utilization of capacity for finished units.
Injury prevention risk communication: A mental models approach
DEFF Research Database (Denmark)
Austin, Laurel Cecelia; Fischhoff, Baruch
2012-01-01
fail to see risks, do not make use of available protective interventions or misjudge the effectiveness of protective measures. If these misunderstandings can be reduced through context-appropriate risk communications, then their improved mental models may help people to engage more effectively...... and create an expert model of the risk situation, interviewing lay people to elicit their comparable mental models, and developing and evaluating communication interventions designed to close the gaps between lay people and experts. This paper reviews the theory and method behind this research stream...... interventions on the most critical opportunities to reduce risks. That research often seeks to identify the ‘mental models’ that underlie individuals' interpretations of their circumstances and the outcomes of possible actions. In the context of injury prevention, a mental models approach would ask why people...
Variational approach to thermal masses in compactified models
Energy Technology Data Exchange (ETDEWEB)
Dominici, Daniele [Dipartimento di Fisica e Astronomia Università di Firenze and INFN - Sezione di Firenze,Via G. Sansone 1, 50019 Sesto Fiorentino (Italy); Roditi, Itzhak [Centro Brasileiro de Pesquisas Físicas - CBPF/MCT,Rua Dr. Xavier Sigaud 150, 22290-180, Rio de Janeiro, RJ (Brazil)
2015-08-20
We investigate by means of a variational approach the effective potential of a 5DU(1) scalar model at finite temperature and compactified on S{sup 1} and S{sup 1}/Z{sub 2} as well as the corresponding 4D model obtained through a trivial dimensional reduction. We are particularly interested in the behavior of the thermal masses of the scalar field with respect to the Wilson line phase and the results obtained are compared with those coming from a one-loop effective potential calculation. We also explore the nature of the phase transition.
Surrogate based approaches to parameter inference in ocean models
Knio, Omar
2016-01-06
This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.
Risk Modeling Approaches in Terms of Volatility Banking Transactions
Directory of Open Access Journals (Sweden)
Angelica Cucşa (Stratulat
2016-01-01
Full Text Available The inseparability of risk and banking activity is one demonstrated ever since banking systems, the importance of the topic being presend in current life and future equally in the development of banking sector. Banking sector development is done in the context of the constraints of nature and number of existing risks and those that may arise, and serves as limiting the risk of banking activity. We intend to develop approaches to analyse risk through mathematical models by also developing a model for the Romanian capital market 10 active trading picks that will test investor reaction in controlled and uncontrolled conditions of risk aggregated with harmonised factors.
The experimental and shell model approach to 100Sn
International Nuclear Information System (INIS)
Grawe, H.; Maier, K.H.; Fitzgerald, J.B.; Heese, J.; Spohr, K.; Schubart, R.; Gorska, M.; Rejmund, M.
1995-01-01
The present status of experimental approach to 100 Sn and its shell model structure is given. New developments in experimental techniques, such as low background isomer spectroscopy and charged particle detection in 4π are surveyed. Based on recent experimental data shell model calculations are used to predict the structure of the single- and two-nucleon neighbours of 100 Sn. The results are compared to the systematic of Coulomb energies and spin-orbit splitting and discussed with respect to future experiments. (author). 51 refs, 11 figs, 1 tab
THE SIGNAL APPROACH TO MODELLING THE BALANCE OF PAYMENT CRISIS
Directory of Open Access Journals (Sweden)
O. Chernyak
2016-12-01
Full Text Available The paper considers and presents synthesis of theoretical models of balance of payment crisis and investigates the most effective ways to model the crisis in Ukraine. For mathematical formalization of balance of payment crisis, comparative analysis of the effectiveness of different calculation methods of Exchange Market Pressure Index was performed. A set of indicators that signal the growing likelihood of balance of payments crisis was defined using signal approach. With the help of minimization function thresholds indicators were selected, the crossing of which signalize increase in the probability of balance of payment crisis.
Surrogate based approaches to parameter inference in ocean models
Knio, Omar
2016-01-01
This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.
An interdisciplinary approach for earthquake modelling and forecasting
Han, P.; Zhuang, J.; Hattori, K.; Ogata, Y.
2016-12-01
Earthquake is one of the most serious disasters, which may cause heavy casualties and economic losses. Especially in the past two decades, huge/mega earthquakes have hit many countries. Effective earthquake forecasting (including time, location, and magnitude) becomes extremely important and urgent. To date, various heuristically derived algorithms have been developed for forecasting earthquakes. Generally, they can be classified into two types: catalog-based approaches and non-catalog-based approaches. Thanks to the rapid development of statistical seismology in the past 30 years, now we are able to evaluate the performances of these earthquake forecast approaches quantitatively. Although a certain amount of precursory information is available in both earthquake catalogs and non-catalog observations, the earthquake forecast is still far from satisfactory. In most case, the precursory phenomena were studied individually. An earthquake model that combines self-exciting and mutually exciting elements was developed by Ogata and Utsu from the Hawkes process. The core idea of this combined model is that the status of the event at present is controlled by the event itself (self-exciting) and all the external factors (mutually exciting) in the past. In essence, the conditional intensity function is a time-varying Poisson process with rate λ(t), which is composed of the background rate, the self-exciting term (the information from past seismic events), and the external excitation term (the information from past non-seismic observations). This model shows us a way to integrate the catalog-based forecast and non-catalog-based forecast. Against this background, we are trying to develop a new earthquake forecast model which combines catalog-based and non-catalog-based approaches.
Modeling workforce demand in North Dakota: a System Dynamics approach
Muminova, Adiba
2015-01-01
This study investigates the dynamics behind the workforce demand and attempts to predict the potential effects of future changes in oil prices on workforce demand in North Dakota. The study attempts to join System Dynamics and Input-Output models in order to overcome shortcomings in both of the approaches and gain a more complete understanding of the issue of workforce demand. A system dynamics simulation of workforce demand within different economic sector...
CFD Modeling of Wall Steam Condensation: Two-Phase Flow Approach versus Homogeneous Flow Approach
International Nuclear Information System (INIS)
Mimouni, S.; Mechitoua, N.; Foissac, A.; Hassanaly, M.; Ouraou, M.
2011-01-01
The present work is focused on the condensation heat transfer that plays a dominant role in many accident scenarios postulated to occur in the containment of nuclear reactors. The study compares a general multiphase approach implemented in NEPTUNE C FD with a homogeneous model, of widespread use for engineering studies, implemented in Code S aturne. The model implemented in NEPTUNE C FD assumes that liquid droplets form along the wall within nucleation sites. Vapor condensation on droplets makes them grow. Once the droplet diameter reaches a critical value, gravitational forces compensate surface tension force and then droplets slide over the wall and form a liquid film. This approach allows taking into account simultaneously the mechanical drift between the droplet and the gas, the heat and mass transfer on droplets in the core of the flow and the condensation/evaporation phenomena on the walls. As concern the homogeneous approach, the motion of the liquid film due to the gravitational forces is neglected, as well as the volume occupied by the liquid. Both condensation models and compressible procedures are validated and compared to experimental data provided by the TOSQAN ISP47 experiment (IRSN Saclay). Computational results compare favorably with experimental data, particularly for the Helium and steam volume fractions.
A multi-model ensemble approach to seabed mapping
Diesing, Markus; Stephens, David
2015-06-01
Seabed habitat mapping based on swath acoustic data and ground-truth samples is an emergent and active marine science discipline. Significant progress could be achieved by transferring techniques and approaches that have been successfully developed and employed in such fields as terrestrial land cover mapping. One such promising approach is the multiple classifier system, which aims at improving classification performance by combining the outputs of several classifiers. Here we present results of a multi-model ensemble applied to multibeam acoustic data covering more than 5000 km2 of seabed in the North Sea with the aim to derive accurate spatial predictions of seabed substrate. A suite of six machine learning classifiers (k-Nearest Neighbour, Support Vector Machine, Classification Tree, Random Forest, Neural Network and Naïve Bayes) was trained with ground-truth sample data classified into seabed substrate classes and their prediction accuracy was assessed with an independent set of samples. The three and five best performing models were combined to classifier ensembles. Both ensembles led to increased prediction accuracy as compared to the best performing single classifier. The improvements were however not statistically significant at the 5% level. Although the three-model ensemble did not perform significantly better than its individual component models, we noticed that the five-model ensemble did perform significantly better than three of the five component models. A classifier ensemble might therefore be an effective strategy to improve classification performance. Another advantage is the fact that the agreement in predicted substrate class between the individual models of the ensemble could be used as a measure of confidence. We propose a simple and spatially explicit measure of confidence that is based on model agreement and prediction accuracy.
Modeling AEC—New Approaches to Study Rare Genetic Disorders
Koch, Peter J.; Dinella, Jason; Fete, Mary; Siegfried, Elaine C.; Koster, Maranke I.
2015-01-01
Ankyloblepharon-ectodermal defects-cleft lip/palate (AEC) syndrome is a rare monogenetic disorder that is characterized by severe abnormalities in ectoderm-derived tissues, such as skin and its appendages. A major cause of morbidity among affected infants is severe and chronic skin erosions. Currently, supportive care is the only available treatment option for AEC patients. Mutations in TP63, a gene that encodes key regulators of epidermal development, are the genetic cause of AEC. However, it is currently not clear how mutations in TP63 lead to the various defects seen in the patients’ skin. In this review, we will discuss current knowledge of the AEC disease mechanism obtained by studying patient tissue and genetically engineered mouse models designed to mimic aspects of the disorder. We will then focus on new approaches to model AEC, including the use of patient cells and stem cell technology to replicate the disease in a human tissue culture model. The latter approach will advance our understanding of the disease and will allow for the development of new in vitro systems to identify drugs for the treatment of skin erosions in AEC patients. Further, the use of stem cell technology, in particular induced pluripotent stem cells (iPSC), will enable researchers to develop new therapeutic approaches to treat the disease using the patient’s own cells (autologous keratinocyte transplantation) after correction of the disease-causing mutations. PMID:24665072
Policy harmonized approach for the EU agricultural sector modelling
Directory of Open Access Journals (Sweden)
G. SALPUTRA
2008-12-01
Full Text Available Policy harmonized (PH approach allows for the quantitative assessment of the impact of various elements of EU CAP direct support schemes, where the production effects of direct payments are accounted through reaction prices formed by producer price and policy price add-ons. Using the AGMEMOD model the impacts of two possible EU agricultural policy scenarios upon beef production have been analysed full decoupling with a switch from historical to regional Single Payment scheme or alternatively with re-distribution of country direct payment envelopes via introduction of EU-wide flat area payment. The PH approach, by systematizing and harmonizing the management and use of policy data, ensures that projected differential policy impacts arising from changes in common EU policies reflect the likely actual differential impact as opposed to differences in how common policies are implemented within analytical models. In the second section of the paper the AGMEMOD models structure is explained. The policy harmonized evaluation method is presented in the third section. Results from an application of the PH approach are presented and discussed in the papers penultimate section, while section 5 concludes.;
Data and Dynamics Driven Approaches for Modelling and Forecasting the Red Sea Chlorophyll
Dreano, Denis
2017-01-01
concentration and have practical applications for fisheries operation and harmful algae blooms monitoring. Modelling approaches can be divided between physics- driven (dynamical) approaches, and data-driven (statistical) approaches. Dynamical models are based
A Statistical Approach For Modeling Tropical Cyclones. Synthetic Hurricanes Generator Model
Energy Technology Data Exchange (ETDEWEB)
Pasqualini, Donatella [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-05-11
This manuscript brie y describes a statistical ap- proach to generate synthetic tropical cyclone tracks to be used in risk evaluations. The Synthetic Hur- ricane Generator (SynHurG) model allows model- ing hurricane risk in the United States supporting decision makers and implementations of adaptation strategies to extreme weather. In the literature there are mainly two approaches to model hurricane hazard for risk prediction: deterministic-statistical approaches, where the storm key physical parameters are calculated using physi- cal complex climate models and the tracks are usually determined statistically from historical data; and sta- tistical approaches, where both variables and tracks are estimated stochastically using historical records. SynHurG falls in the second category adopting a pure stochastic approach.
Object-Oriented Approach to Modeling Units of Pneumatic Systems
Directory of Open Access Journals (Sweden)
Yu. V. Kyurdzhiev
2014-01-01
Full Text Available The article shows the relevance of the approaches to the object-oriented programming when modeling the pneumatic units (PU.Based on the analysis of the calculation schemes of aggregates pneumatic systems two basic objects, namely a cavity flow and a material point were highlighted.Basic interactions of objects are defined. Cavity-cavity interaction: ex-change of matter and energy with the flows of mass. Cavity-point interaction: force interaction, exchange of energy in the form of operation. Point-point in-teraction: force interaction, elastic interaction, inelastic interaction, and inter-vals of displacement.The authors have developed mathematical models of basic objects and interactions. Models and interaction of elements are implemented in the object-oriented programming.Mathematical models of elements of PU design scheme are implemented in derived from the base class. These classes implement the models of flow cavity, piston, diaphragm, short channel, diaphragm to be open by a given law, spring, bellows, elastic collision, inelastic collision, friction, PU stages with a limited movement, etc.A numerical integration of differential equations for the mathematical models of PU design scheme elements is based on the Runge-Kutta method of the fourth order. On request each class performs a tact of integration i.e. calcu-lation of the coefficient method.The paper presents an integration algorithm of the system of differential equations. All objects of the PU design scheme are placed in a unidirectional class list. Iterator loop cycle initiates the integration tact of all the objects in the list. One in four iteration makes a transition to the next step of integration. Calculation process stops when any object shows a shutdowns flag.The proposed approach was tested in the calculation of a number of PU designs. With regard to traditional approaches to modeling, the authors-proposed method features in easy enhancement, code reuse, high reliability
Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches
Directory of Open Access Journals (Sweden)
Sudin eBhattacharya
2012-12-01
Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.
Multiscale modeling of alloy solidification using a database approach
Tan, Lijian; Zabaras, Nicholas
2007-11-01
A two-scale model based on a database approach is presented to investigate alloy solidification. Appropriate assumptions are introduced to describe the behavior of macroscopic temperature, macroscopic concentration, liquid volume fraction and microstructure features. These assumptions lead to a macroscale model with two unknown functions: liquid volume fraction and microstructure features. These functions are computed using information from microscale solutions of selected problems. This work addresses the selection of sample problems relevant to the interested problem and the utilization of data from the microscale solution of the selected sample problems. A computationally efficient model, which is different from the microscale and macroscale models, is utilized to find relevant sample problems. In this work, the computationally efficient model is a sharp interface solidification model of a pure material. Similarities between the sample problems and the problem of interest are explored by assuming that the liquid volume fraction and microstructure features are functions of solution features extracted from the solution of the computationally efficient model. The solution features of the computationally efficient model are selected as the interface velocity and thermal gradient in the liquid at the time the sharp solid-liquid interface passes through. An analytical solution of the computationally efficient model is utilized to select sample problems relevant to solution features obtained at any location of the domain of the problem of interest. The microscale solution of selected sample problems is then utilized to evaluate the two unknown functions (liquid volume fraction and microstructure features) in the macroscale model. The temperature solution of the macroscale model is further used to improve the estimation of the liquid volume fraction and microstructure features. Interpolation is utilized in the feature space to greatly reduce the number of required
Overview of the FEP analysis approach to model development
International Nuclear Information System (INIS)
Bailey, L.
1998-01-01
This report heads a suite of documents describing the Nirex model development programme. The programme is designed to provide a clear audit trail from the identification of significant features, events and processes (FEPs) to the models and modelling processes employed within a detailed safety assessment. A five stage approach has been adopted, which provides a systematic framework for addressing uncertainty and for the documentation of all modelling decisions and assumptions. The five stages are as follows: Stage 1: EP Analysis - compilation and structuring of a FEP database; Stage 2: Scenario and Conceptual Model Development; Stage 3: Mathematical Model Development; Stage 4: Software Development; Stage 5: confidence Building. This report describes the development and structuring of a FEP database as a Master Directed Diagram (MDD) and explains how this may be used to identify different modelling scenarios, based upon the identification of scenario -defining FEPs. The methodology describes how the possible evolution of a repository system can be addressed in terms of a base scenario, a broad and reasonable representation of the 'natural' evolution of the system, and a number of variant scenarios, representing the effects of probabilistic events and processes. The MDD has been used to identify conceptual models to represent the base scenario and the interactions between these conceptual models have been systematically reviewed using a matrix diagram technique. This has led to the identification of modelling requirements for the base scenario, against which existing assessment software capabilities have been reviewed. A mechanism for combining probabilistic scenario-defining FEPs to construct multi-FEP variant scenarios has been proposed and trialled using the concept of a 'timeline', a defined sequence of events, from which consequences can be assessed. An iterative approach, based on conservative modelling principles, has been proposed for the evaluation of
A multi-model approach to X-ray pulsars
Directory of Open Access Journals (Sweden)
Schönherr G.
2014-01-01
Full Text Available The emission characteristics of X-ray pulsars are governed by magnetospheric accretion within the Alfvén radius, leading to a direct coupling of accretion column properties and interactions at the magnetosphere. The complexity of the physical processes governing the formation of radiation within the accreted, strongly magnetized plasma has led to several sophisticated theoretical modelling efforts over the last decade, dedicated to either the formation of the broad band continuum, the formation of cyclotron resonance scattering features (CRSFs or the formation of pulse profiles. While these individual approaches are powerful in themselves, they quickly reach their limits when aiming at a quantitative comparison to observational data. Too many fundamental parameters, describing the formation of the accretion columns and the systems’ overall geometry are unconstrained and different models are often based on different fundamental assumptions, while everything is intertwined in the observed, highly phase-dependent spectra and energy-dependent pulse profiles. To name just one example: the (phase variable line width of the CRSFs is highly dependent on the plasma temperature, the existence of B-field gradients (geometry and observation angle, parameters which, in turn, drive the continuum radiation and are driven by the overall two-pole geometry for the light bending model respectively. This renders a parallel assessment of all available spectral and timing information by a compatible across-models-approach indispensable. In a collaboration of theoreticians and observers, we have been working on a model unification project over the last years, bringing together theoretical calculations of the Comptonized continuum, Monte Carlo simulations and Radiation Transfer calculations of CRSFs as well as a General Relativity (GR light bending model for ray tracing of the incident emission pattern from both magnetic poles. The ultimate goal is to implement a
A DYNAMICAL SYSTEM APPROACH IN MODELING TECHNOLOGY TRANSFER
Directory of Open Access Journals (Sweden)
Hennie Husniah
2016-05-01
Full Text Available In this paper we discuss a mathematical model of two parties technology transfer from a leader to a follower. The model is reconstructed via dynamical system approach from a known standard Raz and Assa model and we found some important conclusion which have not been discussed in the original model. The model assumes that in the absence of technology transfer from a leader to a follower, both the leader and the follower have a capability to grow independently with a known upper limit of the development. We obtain a rich mathematical structure of the steady state solution of the model. We discuss a special situation in which the upper limit of the technological development of the follower is higher than that of the leader, but the leader has started earlier than the follower in implementing the technology. In this case we show a paradox stating that the follower is unable to reach its original upper limit of the technological development could appear whenever the transfer rate is sufficiently high. We propose a new model to increase realism so that any technological transfer rate could only has a positive effect in accelerating the rate of growth of the follower in reaching its original upper limit of the development.
Predicting the emission from an incineration plant - a modelling approach
International Nuclear Information System (INIS)
Rohyiza Baan
2004-01-01
The emissions from combustion process of Municipal Solid Waste (MSW) have become an important issue in incineration technology. Resulting from unstable combustion conditions, the formation of undesirable compounds such as CO, SO 2 , NO x , PM 10 and dioxin become the source of pollution concentration in the atmosphere. The impact of emissions on criteria air pollutant concentrations could be obtained directly using ambient air monitoring equipment or predicted using dispersion modelling. Literature shows that the complicated atmospheric processes that occur in nature can be described using mathematical models. This paper will highlight the air dispersion model as a tool to relate and simulate the release and dispersion of air pollutants in the atmosphere. The technique is based on a programming approach to develop the air dispersion ground level concentration model with the use of Gaussian and Pasquil equation. This model is useful to study the consequences of various sources of air pollutant and estimating the amount of pollutants released into the air from existing emission sources. From this model, it was found that the difference in percentage of data between actual conditions and the model's prediction is about 5%. (Author)
Modeling human diseases: an education in interactions and interdisciplinary approaches
Directory of Open Access Journals (Sweden)
Leonard Zon
2016-06-01
Full Text Available Traditionally, most investigators in the biomedical arena exploit one model system in the course of their careers. Occasionally, an investigator will switch models. The selection of a suitable model system is a crucial step in research design. Factors to consider include the accuracy of the model as a reflection of the human disease under investigation, the numbers of animals needed and ease of husbandry, its physiology and developmental biology, and the ability to apply genetics and harness the model for drug discovery. In my lab, we have primarily used the zebrafish but combined it with other animal models and provided a framework for others to consider the application of developmental biology for therapeutic discovery. Our interdisciplinary approach has led to many insights into human diseases and to the advancement of candidate drugs to clinical trials. Here, I draw on my experiences to highlight the importance of combining multiple models, establishing infrastructure and genetic tools, forming collaborations, and interfacing with the medical community for successful translation of basic findings to the clinic.
A novel approach to multihazard modeling and simulation.
Smith, Silas W; Portelli, Ian; Narzisi, Giuseppe; Nelson, Lewis S; Menges, Fabian; Rekow, E Dianne; Mincer, Joshua S; Mishra, Bhubaneswar; Goldfrank, Lewis R
2009-06-01
To develop and apply a novel modeling approach to support medical and public health disaster planning and response using a sarin release scenario in a metropolitan environment. An agent-based disaster simulation model was developed incorporating the principles of dose response, surge response, and psychosocial characteristics superimposed on topographically accurate geographic information system architecture. The modeling scenarios involved passive and active releases of sarin in multiple transportation hubs in a metropolitan city. Parameters evaluated included emergency medical services, hospital surge capacity (including implementation of disaster plan), and behavioral and psychosocial characteristics of the victims. In passive sarin release scenarios of 5 to 15 L, mortality increased nonlinearly from 0.13% to 8.69%, reaching 55.4% with active dispersion, reflecting higher initial doses. Cumulative mortality rates from releases in 1 to 3 major transportation hubs similarly increased nonlinearly as a function of dose and systemic stress. The increase in mortality rate was most pronounced in the 80% to 100% emergency department occupancy range, analogous to the previously observed queuing phenomenon. Effective implementation of hospital disaster plans decreased mortality and injury severity. Decreasing ambulance response time and increasing available responding units reduced mortality among potentially salvageable patients. Adverse psychosocial characteristics (excess worry and low compliance) increased demands on health care resources. Transfer to alternative urban sites was possible. An agent-based modeling approach provides a mechanism to assess complex individual and systemwide effects in rare events.
Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach.
Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J
2016-01-01
Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.
A comprehensive approach to age-dependent dosimetric modeling
International Nuclear Information System (INIS)
Leggett, R.W.; Cristy, M.; Eckerman, K.F.
1986-01-01
In the absence of age-specific biokinetic models, current retention models of the International Commission on Radiological Protection (ICRP) frequently are used as a point of departure for evaluation of exposures to the general population. These models were designed and intended for estimation of long-term integrated doses to the adult worker. Their format and empirical basis preclude incorporation of much valuable physiological information and physiologically reasonable assumptions that could be used in characterizing the age-specific behavior of radioelements in humans. In this paper we discuss a comprehensive approach to age-dependent dosimetric modeling in which consideration is given not only to changes with age in masses and relative geometries of body organs and tissues but also to best available physiological and radiobiological information relating to the age-specific biobehavior of radionuclides. This approach is useful in obtaining more accurate estimates of long-term dose commitments as a function of age at intake, but it may be particularly valuable in establishing more accurate estimates of dose rate as a function of age. Age-specific dose rates are needed for a proper analysis of the potential effects on estimates or risk of elevated dose rates per unit intake in certain stages of life, elevated response per unit dose received during some stages of life, and age-specific non-radiogenic competing risks
A comprehensive approach to age-dependent dosimetric modeling
International Nuclear Information System (INIS)
Leggett, R.W.; Cristy, M.; Eckerman, K.F.
1987-01-01
In the absence of age-specific biokinetic models, current retention models of the International Commission of Radiological Protection (ICRP) frequently are used as a point of departure for evaluation of exposures to the general population. These models were designed and intended for estimation of long-term integrated doses to the adult worker. Their format and empirical basis preclude incorporation of much valuable physiological information and physiologically reasonable assumptions that could be used in characterizing the age-specific behavior of radioelements in humans. In this paper a comprehensive approach to age-dependent dosimetric modeling is discussed in which consideration is given not only to changes with age in masses and relative geometries of body organs and tissues but also to best available physiological and radiobiological information relating to the age-specific biobehavior of radionuclides. This approach is useful in obtaining more accurate estimates of long-term dose commitments as a function of age at intake, but it may be particularly valuable in establishing more accurate estimates of dose rate as a function of age. Age-specific dose rates are needed for a proper analysis of the potential effects on estimates of risk of elevated dose rates per unit intake in certain stages of life, elevated response per unit dose received during some stages of life, and age-specific non-radiogenic competing risks. 16 refs.; 3 figs.; 1 table
Micromechanical modeling and inverse identification of damage using cohesive approaches
International Nuclear Information System (INIS)
Blal, Nawfal
2013-01-01
In this study a micromechanical model is proposed for a collection of cohesive zone models embedded between two each elements of a standard cohesive-volumetric finite element method. An equivalent 'matrix-inclusions' composite is proposed as a representation of the cohesive-volumetric discretization. The overall behaviour is obtained using homogenization approaches (Hashin Shtrikman scheme and the P. Ponte Castaneda approach). The derived model deals with elastic, brittle and ductile materials. It is available whatever the triaxiality loading rate and the shape of the cohesive law, and leads to direct relationships between the overall material properties and the local cohesive parameters and the mesh density. First, rigorous bounds on the normal and tangential cohesive stiffnesses are obtained leading to a suitable control of the inherent artificial elastic loss induced by intrinsic cohesive models. Second, theoretical criteria on damageable and ductile cohesive parameters are established (cohesive peak stress, critical separation, cohesive failure energy,... ). These criteria allow a practical calibration of the cohesive zone parameters as function of the overall material properties and the mesh length. The main interest of such calibration is its promising capacity to lead to a mesh-insensitive overall response in surface damage. (author) [fr
A piecewise modeling approach for climate sensitivity studies: Tests with a shallow-water model
Shao, Aimei; Qiu, Chongjian; Niu, Guo-Yue
2015-10-01
In model-based climate sensitivity studies, model errors may grow during continuous long-term integrations in both the "reference" and "perturbed" states and hence the climate sensitivity (defined as the difference between the two states). To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.
Numerical modelling of carbonate platforms and reefs: approaches and opportunities
Energy Technology Data Exchange (ETDEWEB)
Dalmasso, H.; Montaggioni, L.F.; Floquet, M. [Universite de Provence, Marseille (France). Centre de Sedimentologie-Palaeontologie; Bosence, D. [Royal Holloway University of London, Egham (United Kingdom). Dept. of Geology
2001-07-01
This paper compares different computing procedures that have been utilized in simulating shallow-water carbonate platform development. Based on our geological knowledge we can usually give a rather accurate qualitative description of the mechanisms controlling geological phenomena. Further description requires the use of computer stratigraphic simulation models that allow quantitative evaluation and understanding of the complex interactions of sedimentary depositional carbonate systems. The roles of modelling include: (1) encouraging accuracy and precision in data collection and process interpretation (Watney et al., 1999); (2) providing a means to quantitatively test interpretations concerning the control of various mechanisms on producing sedimentary packages; (3) predicting or extrapolating results into areas of limited control; (4) gaining new insights regarding the interaction of parameters; (5) helping focus on future studies to resolve specific problems. This paper addresses two main questions, namely: (1) What are the advantages and disadvantages of various types of models? (2) How well do models perform? In this paper we compare and discuss the application of five numerical models: CARBONATE (Bosence and Waltham, 1990), FUZZIM (Nordlund, 1999), CARBPLAT (Bosscher, 1992), DYNACARB (Li et al., 1993), PHIL (Bowman, 1997) and SEDPAK (Kendall et al., 1991). The comparison, testing and evaluation of these models allow one to gain a better knowledge and understanding of controlling parameters of carbonate platform development, which are necessary for modelling. Evaluating numerical models, critically comparing results from models using different approaches, and pushing experimental tests to their limits, provide an effective vehicle to improve and develop new numerical models. A main feature of this paper is to closely compare the performance between two numerical models: a forward model (CARBONATE) and a fuzzy logic model (FUZZIM). These two models use common
Modeling the cometary environment using a fluid approach
Shou, Yinsi
Comets are believed to have preserved the building material of the early solar system and to hold clues to the origin of life on Earth. Abundant remote observations of comets by telescopes and the in-situ measurements by a handful of space missions reveal that the cometary environments are complicated by various physical and chemical processes among the neutral gases and dust grains released from comets, cometary ions, and the solar wind in the interplanetary space. Therefore, physics-based numerical models are in demand to interpret the observational data and to deepen our understanding of the cometary environment. In this thesis, three models using a fluid approach, which include important physical and chemical processes underlying the cometary environment, have been developed to study the plasma, neutral gas, and the dust grains, respectively. Although models based on the fluid approach have limitations in capturing all of the correct physics for certain applications, especially for very low gas density environment, they are computationally much more efficient than alternatives. In the simulations of comet 67P/Churyumov-Gerasimenko at various heliocentric distances with a wide range of production rates, our multi-fluid cometary neutral gas model and multi-fluid cometary dust model have achieved comparable results to the Direct Simulation Monte Carlo (DSMC) model, which is based on a kinetic approach that is valid in all collisional regimes. Therefore, our model is a powerful alternative to the particle-based model, especially for some computationally intensive simulations. Capable of accounting for the varying heating efficiency under various physical conditions in a self-consistent way, the multi-fluid cometary neutral gas model is a good tool to study the dynamics of the cometary coma with different production rates and heliocentric distances. The modeled H2O expansion speeds reproduce the general trend and the speed's nonlinear dependencies of production rate
Statistical approach for uncertainty quantification of experimental modal model parameters
DEFF Research Database (Denmark)
Luczak, M.; Peeters, B.; Kahsin, M.
2014-01-01
Composite materials are widely used in manufacture of aerospace and wind energy structural components. These load carrying structures are subjected to dynamic time-varying loading conditions. Robust structural dynamics identification procedure impose tight constraints on the quality of modal models...... represent different complexity levels ranging from coupon, through sub-component up to fully assembled aerospace and wind energy structural components made of composite materials. The proposed method is demonstrated on two application cases of a small and large wind turbine blade........ This paper aims at a systematic approach for uncertainty quantification of the parameters of the modal models estimated from experimentally obtained data. Statistical analysis of modal parameters is implemented to derive an assessment of the entire modal model uncertainty measure. Investigated structures...
Formal approach to modeling of modern Information Systems
Directory of Open Access Journals (Sweden)
Bálint Molnár
2016-01-01
Full Text Available Most recently, the concept of business documents has started to play double role. On one hand, a business document (word processing text or calculation sheet can be used as specification tool, on the other hand the business document is an immanent constituent of business processes, thereby essential component of business Information Systems. The recent tendency is that the majority of documents and their contents within business Information Systems remain in semi-structured format and a lesser part of documents is transformed into schemas of structured databases. In order to keep the emerging situation in hand, we suggest the creation (1 a theoretical framework for modeling business Information Systems; (2 and a design method for practical application based on the theoretical model that provides the structuring principles. The modeling approach that focuses on documents and their interrelationships with business processes assists in perceiving the activities of modern Information Systems.
A distributed approach for parameters estimation in System Biology models
International Nuclear Information System (INIS)
Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.
2009-01-01
Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.
International energy market dynamics: a modelling approach. Tome 1
International Nuclear Information System (INIS)
Nachet, S.
1996-01-01
This work is an attempt to model international energy market and reproduce the behaviour of both energy demand and supply. Energy demand was represented using sector versus source approach. For developing countries, existing link between economic and energy sectors were analysed. Energy supply is exogenous for energy sources other than oil and natural gas. For hydrocarbons, exploration-production process was modelled and produced figures as production yield, exploration effort index, etc. The model built is econometric and is solved using a software that was constructed for this purpose. We explore the energy market future using three scenarios and obtain projections by 2010 for energy demand per source and oil natural gas supply per region. Economic variables are used to produce different indicators as energy intensity, energy per capita, etc. (author). 378 refs., 26 figs., 35 tabs., 11 appends
International energy market dynamics: a modelling approach. Tome 2
International Nuclear Information System (INIS)
Nachet, S.
1996-01-01
This work is an attempt to model international energy market and reproduce the behaviour of both energy demand and supply. Energy demand was represented using sector versus source approach. For developing countries, existing link between economic and energy sectors were analysed. Energy supply is exogenous for energy sources other than oil and natural gas. For hydrocarbons, exploration-production process was modelled and produced figures as production yield, exploration effort index, ect. The model build is econometric and is solved using a software that was constructed for this purpose. We explore the energy market future using three scenarios and obtain projections by 2010 for energy demand per source and oil and natural gas supply per region. Economic variables are used to produce different indicators as energy intensity, energy per capita, etc. (author). 378 refs., 26 figs., 35 tabs., 11 appends
Electrochemo-hydrodynamics modeling approach for a uranium electrowinning cell
Energy Technology Data Exchange (ETDEWEB)
Kim, K.R.; Paek, S.; Ahn, D.H., E-mail: krkim1@kaeri.re.kr, E-mail: swpaek@kaeri.re.kr, E-mail: dhahn2@kaeri.re.kr [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Park, J.Y.; Hwang, I.S., E-mail: d486916@snu.ac.kr, E-mail: hisline@snu.ac.kr [Department of Nuclear Engineering, Seoul National University (Korea, Republic of)
2011-07-01
This study demonstrated a simulation based on fully coupling of electrochemical kinetics with 3- dimensional transport of ionic species in a flowing molten-salt electrolyte through a simplified channel cell of uranium electro winner. Dependences of ionic electro-transport on the velocity of stationary electrolyte flow were studied using a coupling approach of electrochemical reaction model. The present model was implemented in a commercially available computational fluid dynamics (CFD) platform, Ansys-CFX, using its customization ability via user defined functions. The main parameters characterizing the effect of the turbulent flow of an electrolyte between two planar electrodes were demonstrated by means of CFD-based multiphysics simulation approach. Simulation was carried out for the case of uranium electrowinning characteristics in a stream of molten salt electrolyte. This approach was taken into account the concentration profile at the electrode surface, to represent the variation of the diffusion limited current density as a function of the flow characteristics and of applied current density. It was able to predict conventional current voltage relation in addition to details of electrolyte fluid dynamics and electrochemical variable, such as flow field, species concentrations, potential, and current distributions throughout the current driven cell. (author)
Electrochemo-hydrodynamics modeling approach for a uranium electrowinning cell
International Nuclear Information System (INIS)
Kim, K.R.; Paek, S.; Ahn, D.H.; Park, J.Y.; Hwang, I.S.
2011-01-01
This study demonstrated a simulation based on fully coupling of electrochemical kinetics with 3- dimensional transport of ionic species in a flowing molten-salt electrolyte through a simplified channel cell of uranium electro winner. Dependences of ionic electro-transport on the velocity of stationary electrolyte flow were studied using a coupling approach of electrochemical reaction model. The present model was implemented in a commercially available computational fluid dynamics (CFD) platform, Ansys-CFX, using its customization ability via user defined functions. The main parameters characterizing the effect of the turbulent flow of an electrolyte between two planar electrodes were demonstrated by means of CFD-based multiphysics simulation approach. Simulation was carried out for the case of uranium electrowinning characteristics in a stream of molten salt electrolyte. This approach was taken into account the concentration profile at the electrode surface, to represent the variation of the diffusion limited current density as a function of the flow characteristics and of applied current density. It was able to predict conventional current voltage relation in addition to details of electrolyte fluid dynamics and electrochemical variable, such as flow field, species concentrations, potential, and current distributions throughout the current driven cell. (author)
New business models for electric cars-A holistic approach
International Nuclear Information System (INIS)
Kley, Fabian; Lerch, Christian; Dallinger, David
2011-01-01
Climate change and global resource shortages have led to rethinking traditional individual mobility services based on combustion engines. As the consequence of technological improvements, the first electric vehicles are now being introduced and greater market penetration can be expected. But any wider implementation of battery-powered electrical propulsion systems in the future will give rise to new challenges for both the traditional automotive industry and other new players, e.g. battery manufacturers, the power supply industry and other service providers. Different application cases of electric vehicles are currently being discussed which means that numerous business models could emerge, leading to new shares in value creation and involving new players. Consequently, individual stakeholders are uncertain about which business models are really effective with regard to targeting a profitable overall concept. Therefore, this paper aims to define a holistic approach to developing business models for electric mobility, which analyzes the system as a whole on the one hand and provides decision support for affected enterprises on the other. To do so, the basic elements of electric mobility are considered and topical approaches to business models for various stakeholders are discussed. The paper concludes by presenting a systemic instrument for business models based on morphological methods. - Highlights: → We present a systemic instrument to analyze business models for electric vehicles. → Provide decision support for an enterprises dealing with electric vehicle innovations. → Combine business aspects of the triad between vehicles concepts, infrastructure as well as system integration. → In the market, activities in all domains have been initiated, but often with undefined or unclear structures.
A probabilistic approach to the drag-based model
Napoletano, Gianluca; Forte, Roberta; Moro, Dario Del; Pietropaolo, Ermanno; Giovannelli, Luca; Berrilli, Francesco
2018-02-01
The forecast of the time of arrival (ToA) of a coronal mass ejection (CME) to Earth is of critical importance for our high-technology society and for any future manned exploration of the Solar System. As critical as the forecast accuracy is the knowledge of its precision, i.e. the error associated to the estimate. We propose a statistical approach for the computation of the ToA using the drag-based model by introducing the probability distributions, rather than exact values, as input parameters, thus allowing the evaluation of the uncertainty on the forecast. We test this approach using a set of CMEs whose transit times are known, and obtain extremely promising results: the average value of the absolute differences between measure and forecast is 9.1h, and half of these residuals are within the estimated errors. These results suggest that this approach deserves further investigation. We are working to realize a real-time implementation which ingests the outputs of automated CME tracking algorithms as inputs to create a database of events useful for a further validation of the approach.
Leader communication approaches and patient safety: An integrated model.
Mattson, Malin; Hellgren, Johnny; Göransson, Sara
2015-06-01
Leader communication is known to influence a number of employee behaviors. When it comes to the relationship between leader communication and safety, the evidence is more scarce and ambiguous. The aim of the present study is to investigate whether and in what way leader communication relates to safety outcomes. The study examines two leader communication approaches: leader safety priority communication and feedback to subordinates. These approaches were assumed to affect safety outcomes via different employee behaviors. Questionnaire data, collected from 221 employees at two hospital wards, were analyzed using structural equation modeling. The two examined communication approaches were both positively related to safety outcomes, although leader safety priority communication was mediated by employee compliance and feedback communication by organizational citizenship behaviors. The findings suggest that leader communication plays a vital role in improving organizational and patient safety and that different communication approaches seem to positively affect different but equally essential employee safety behaviors. The results highlights the necessity for leaders to engage in one-way communication of safety values as well as in more relational feedback communication with their subordinates in order to enhance patient safety. Copyright © 2015 Elsevier Ltd. and National Safety Council. Published by Elsevier Ltd. All rights reserved.
Magnetic field approaches in dc thermal plasma modelling
International Nuclear Information System (INIS)
Freton, P; Gonzalez, J J; Masquere, M; Reichert, Frank
2011-01-01
The self-induced magnetic field has an important role in thermal plasma configurations generated by electric arcs as it generates velocity through Lorentz forces. In the models a good representation of the magnetic field is thus necessary. Several approaches exist to calculate the self-induced magnetic field such as the Maxwell-Ampere formulation, the vector potential approach combined with different kinds of boundary conditions or the Biot and Savart (B and S) formulation. The calculation of the self-induced magnetic field is alone a difficult problem and only few papers of the thermal plasma community speak on this subject. In this study different approaches with different boundary conditions are applied on two geometries to compare the methods and their limitations. The calculation time is also one of the criteria for the choice of the method and a compromise must be found between method precision and computation time. The study shows the importance of the current carrying path representation in the electrode on the deduced magnetic field. The best compromise consists of using the B and S formulation on the walls and/or edges of the calculation domain to determine the boundary conditions and to solve the vector potential in a 2D system. This approach provides results identical to those obtained using the B and S formulation over the entire domain but with a considerable decrease in calculation time.
Linear mixed-effects modeling approach to FMRI group analysis.
Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W
2013-06-01
Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity
Directory of Open Access Journals (Sweden)
Xiao-meng Song
2013-01-01
Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.
Model predictive control approach for a CPAP-device
Directory of Open Access Journals (Sweden)
Scheel Mathias
2017-09-01
Full Text Available The obstructive sleep apnoea syndrome (OSAS is characterized by a collapse of the upper respiratory tract, resulting in a reduction of the blood oxygen- and an increase of the carbon dioxide (CO2 - concentration, which causes repeated sleep disruptions. The gold standard to treat the OSAS is the continuous positive airway pressure (CPAP therapy. The continuous pressure keeps the upper airway open and prevents the collapse of the upper respiratory tract and the pharynx. Most of the available CPAP-devices cannot maintain the pressure reference [1]. In this work a model predictive control approach is provided. This control approach has the possibility to include the patient’s breathing effort into the calculation of the control variable. Therefore a patient-individualized control strategy can be developed.
Optimizing nitrogen fertilizer use: Current approaches and simulation models
International Nuclear Information System (INIS)
Baethgen, W.E.
2000-01-01
Nitrogen (N) is the most common limiting nutrient in agricultural systems throughout the world. Crops need sufficient available N to achieve optimum yields and adequate grain-protein content. Consequently, sub-optimal rates of N fertilizers typically cause lower economical benefits for farmers. On the other hand, excessive N fertilizer use may result in environmental problems such as nitrate contamination of groundwater and emission of N 2 O and NO. In spite of the economical and environmental importance of good N fertilizer management, the development of optimum fertilizer recommendations is still a major challenge in most agricultural systems. This article reviews the approaches most commonly used for making N recommendations: expected yield level, soil testing and plant analysis (including quick tests). The paper introduces the application of simulation models that complement traditional approaches, and includes some examples of current applications in Africa and South America. (author)
Modeling of problems of projection: A non-countercyclic approach
Directory of Open Access Journals (Sweden)
Jason Ginsburg
2016-06-01
Full Text Available This paper describes a computational implementation of the recent Problems of Projection (POP approach to the study of language (Chomsky 2013; 2015. While adopting the basic proposals of POP, notably with respect to how labeling occurs, we a attempt to formalize the basic proposals of POP, and b develop new proposals that overcome some problems with POP that arise with respect to cyclicity, labeling, and wh-movement operations. We show how this approach accounts for simple declarative sentences, ECM constructions, and constructions that involve long-distance movement of a wh-phrase (including the that-trace effect. We implemented these proposals with a computer model that automatically constructs step-by-step derivations of target sentences, thus making it possible to verify that these proposals work.
Anomalous superconductivity in the tJ model; moment approach
DEFF Research Database (Denmark)
Sørensen, Mads Peter; Rodriguez-Nunez, J.J.
1997-01-01
By extending the moment approach of Nolting (Z, Phys, 225 (1972) 25) in the superconducting phase, we have constructed the one-particle spectral functions (diagonal and off-diagonal) for the tJ model in any dimensions. We propose that both the diagonal and the off-diagonal spectral functions...... Hartree shift which in the end result enlarges the bandwidth of the free carriers allowing us to take relative high values of J/t and allowing superconductivity to live in the T-c-rho phase diagram, in agreement with numerical calculations in a cluster, We have calculated the static spin susceptibility......, chi(T), and the specific heat, C-v(T), within the moment approach. We find that all the relevant physical quantities show the signature of superconductivity at T-c in the form of kinks (anomalous behavior) or jumps, for low density, in agreement with recent published literature, showing a generic...
P.C. Austin (Peter); D. van Klaveren (David); Y. Vergouwe (Yvonne); D. Nieboer (Daan); D.S. Lee (Douglas); E.W. Steyerberg (Ewout)
2016-01-01
textabstractObjective: Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting: We
CM5: A pre-Swarm magnetic field model based upon the comprehensive modeling approach
DEFF Research Database (Denmark)
Sabaka, T.; Olsen, Nils; Tyler, Robert
2014-01-01
We have developed a model based upon the very successful Comprehensive Modeling (CM) approach using recent CHAMP, Ørsted, SAC-C and observatory hourly-means data from September 2000 to the end of 2013. This CM, called CM5, was derived from the algorithm that will provide a consistent line of Leve...
Axial turbomachine modelling with a 1D axisymmetric approach
International Nuclear Information System (INIS)
Tauveron, Nicolas; Saez, Manuel; Ferrand, Pascal; Leboeuf, Francis
2007-01-01
This work concerns the design and safety analysis of direct cycle gas cooled reactor. The estimation of compressor and turbine performances in transient operations is of high importance for the designer. The first goal of this study is to provide a description of compressor behaviour in unstable conditions with a better understanding than the models based on performance maps ('traditional' 0D approach). A supplementary objective is to provide a coherent description of the turbine behaviour. The turbomachine modelling approach consists in the solution of 1D axisymmetric Navier-Stokes equations on an axial grid inside the turbomachine: mass, axial momentum, circumferential momentum and total-enthalpy balances are written. Blade forces are taken into account by using compressor or turbine blade cascade steady correlations. A particular effort has been developed to generate or test correlations in low mass flow and negative mass flow regimes, based on experimental data. The model is tested on open literature cases of the gas turbine aircraft community. For compressor and turbine, steady situations are fairly described, especially for medium and high mass flow rate. The dynamic behaviour of compressor is also quite well described, even in unstable operation (surge): qualitative tendencies (role of plenum volume and role of throttle) and some quantitative characteristics (frequency) are in a good agreement with experimental data. The application to transient simulations of gas cooled nuclear reactors is concentrated on the hypothetical 10 in. break accident. The results point out the importance of the location of the pipe rupture in a hypothetical break event. In some detailed cases, compressor surge and back flow through the circuit can occur. In order to be used in a design phase, a simplified model of surge has also been developed. This simplified model is applied to the gas fast reactor (GFR) and compared quite favourably with 1D axisymmetric simulation results
A parsimonious approach to modeling animal movement data.
Directory of Open Access Journals (Sweden)
Yann Tremblay
Full Text Available Animal tracking is a growing field in ecology and previous work has shown that simple speed filtering of tracking data is not sufficient and that improvement of tracking location estimates are possible. To date, this has required methods that are complicated and often time-consuming (state-space models, resulting in limited application of this technique and the potential for analysis errors due to poor understanding of the fundamental framework behind the approach. We describe and test an alternative and intuitive approach consisting of bootstrapping random walks biased by forward particles. The model uses recorded data accuracy estimates, and can assimilate other sources of data such as sea-surface temperature, bathymetry and/or physical boundaries. We tested our model using ARGOS and geolocation tracks of elephant seals that also carried GPS tags in addition to PTTs, enabling true validation. Among pinnipeds, elephant seals are extreme divers that spend little time at the surface, which considerably impact the quality of both ARGOS and light-based geolocation tracks. Despite such low overall quality tracks, our model provided location estimates within 4.0, 5.5 and 12.0 km of true location 50% of the time, and within 9, 10.5 and 20.0 km 90% of the time, for above, equal or below average elephant seal ARGOS track qualities, respectively. With geolocation data, 50% of errors were less than 104.8 km (<0.94 degrees, and 90% were less than 199.8 km (<1.80 degrees. Larger errors were due to lack of sea-surface temperature gradients. In addition we show that our model is flexible enough to solve the obstacle avoidance problem by assimilating high resolution coastline data. This reduced the number of invalid on-land location by almost an order of magnitude. The method is intuitive, flexible and efficient, promising extensive utilization in future research.
Ensembles modeling approach to study Climate Change impacts on Wheat
Ahmed, Mukhtar; Claudio, Stöckle O.; Nelson, Roger; Higgins, Stewart
2017-04-01
Simulations of crop yield under climate variability are subject to uncertainties, and quantification of such uncertainties is essential for effective use of projected results in adaptation and mitigation strategies. In this study we evaluated the uncertainties related to crop-climate models using five crop growth simulation models (CropSyst, APSIM, DSSAT, STICS and EPIC) and 14 general circulation models (GCMs) for 2 representative concentration pathways (RCP) of atmospheric CO2 (4.5 and 8.5 W m-2) in the Pacific Northwest (PNW), USA. The aim was to assess how different process-based crop models could be used accurately for estimation of winter wheat growth, development and yield. Firstly, all models were calibrated for high rainfall, medium rainfall, low rainfall and irrigated sites in the PNW using 1979-2010 as the baseline period. Response variables were related to farm management and soil properties, and included crop phenology, leaf area index (LAI), biomass and grain yield of winter wheat. All five models were run from 2000 to 2100 using the 14 GCMs and 2 RCPs to evaluate the effect of future climate (rainfall, temperature and CO2) on winter wheat phenology, LAI, biomass, grain yield and harvest index. Simulated time to flowering and maturity was reduced in all models except EPIC with some level of uncertainty. All models generally predicted an increase in biomass and grain yield under elevated CO2 but this effect was more prominent under rainfed conditions than irrigation. However, there was uncertainty in the simulation of crop phenology, biomass and grain yield under 14 GCMs during three prediction periods (2030, 2050 and 2070). We concluded that to improve accuracy and consistency in simulating wheat growth dynamics and yield under a changing climate, a multimodel ensemble approach should be used.
Vector-model-supported approach in prostate plan optimization
International Nuclear Information System (INIS)
Liu, Eva Sau Fan; Wu, Vincent Wing Cheung; Harris, Benjamin; Lehman, Margot; Pryor, David; Chan, Lawrence Wing Chi
2017-01-01
Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration
Vector-model-supported approach in prostate plan optimization
Energy Technology Data Exchange (ETDEWEB)
Liu, Eva Sau Fan [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Wu, Vincent Wing Cheung [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Harris, Benjamin [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Lehman, Margot; Pryor, David [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); School of Medicine, University of Queensland (Australia); Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong)
2017-07-01
Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration
A NEW APPROACH OF DIGITAL BRIDGE SURFACE MODEL GENERATION
Directory of Open Access Journals (Sweden)
H. Ju
2012-07-01
Full Text Available Bridge areas present difficulties for orthophotos generation and to avoid “collapsed” bridges in the orthoimage, operator assistance is required to create the precise DBM (Digital Bridge Model, which is, subsequently, used for the orthoimage generation. In this paper, a new approach of DBM generation, based on fusing LiDAR (Light Detection And Ranging data and aerial imagery, is proposed. The no precise exterior orientation of the aerial image is required for the DBM generation. First, a coarse DBM is produced from LiDAR data. Then, a robust co-registration between LiDAR intensity and aerial image using the orientation constraint is performed. The from-coarse-to-fine hybrid co-registration approach includes LPFFT (Log-Polar Fast Fourier Transform, Harris Corners, PDF (Probability Density Function feature descriptor mean-shift matching, and RANSAC (RANdom Sample Consensus as main components. After that, bridge ROI (Region Of Interest from LiDAR data domain is projected to the aerial image domain as the ROI in the aerial image. Hough transform linear features are extracted in the aerial image ROI. For the straight bridge, the 1st order polynomial function is used; whereas, for the curved bridge, 2nd order polynomial function is used to fit those endpoints of Hough linear features. The last step is the transformation of the smooth bridge boundaries from aerial image back to LiDAR data domain and merge them with the coarse DBM. Based on our experiments, this new approach is capable of providing precise DBM which can be further merged with DTM (Digital Terrain Model derived from LiDAR data to obtain the precise DSM (Digital Surface Model. Such a precise DSM can be used to improve the orthophoto product quality.
Data mining approach to model the diagnostic service management.
Lee, Sun-Mi; Lee, Ae-Kyung; Park, Il-Su
2006-01-01
Korea has National Health Insurance Program operated by the government-owned National Health Insurance Corporation, and diagnostic services are provided every two year for the insured and their family members. Developing a customer relationship management (CRM) system using data mining technology would be useful to improve the performance of diagnostic service programs. Under these circumstances, this study developed a model for diagnostic service management taking into account the characteristics of subjects using a data mining approach. This study could be further used to develop an automated CRM system contributing to the increase in the rate of receiving diagnostic services.
Convex models and probabilistic approach of nonlinear fatigue failure
International Nuclear Information System (INIS)
Qiu Zhiping; Lin Qiang; Wang Xiaojun
2008-01-01
This paper is concerned with the nonlinear fatigue failure problem with uncertainties in the structural systems. In the present study, in order to solve the nonlinear problem by convex models, the theory of ellipsoidal algebra with the help of the thought of interval analysis is applied. In terms of the inclusion monotonic property of ellipsoidal functions, the nonlinear fatigue failure problem with uncertainties can be solved. A numerical example of 25-bar truss structures is given to illustrate the efficiency of the presented method in comparison with the probabilistic approach
Algebraic approach to small-world network models
Rudolph-Lilith, Michelle; Muller, Lyle E.
2014-01-01
We introduce an analytic model for directed Watts-Strogatz small-world graphs and deduce an algebraic expression of its defining adjacency matrix. The latter is then used to calculate the small-world digraph's asymmetry index and clustering coefficient in an analytically exact fashion, valid nonasymptotically for all graph sizes. The proposed approach is general and can be applied to all algebraically well-defined graph-theoretical measures, thus allowing for an analytical investigation of finite-size small-world graphs.
New Approaches in Reuseable Booster System Life Cycle Cost Modeling
Zapata, Edgar
2013-01-01
This paper presents the results of a 2012 life cycle cost (LCC) study of hybrid Reusable Booster Systems (RBS) conducted by NASA Kennedy Space Center (KSC) and the Air Force Research Laboratory (AFRL). The work included the creation of a new cost estimating model and an LCC analysis, building on past work where applicable, but emphasizing the integration of new approaches in life cycle cost estimation. Specifically, the inclusion of industry processes/practices and indirect costs were a new and significant part of the analysis. The focus of LCC estimation has traditionally been from the perspective of technology, design characteristics, and related factors such as reliability. Technology has informed the cost related support to decision makers interested in risk and budget insight. This traditional emphasis on technology occurs even though it is well established that complex aerospace systems costs are mostly about indirect costs, with likely only partial influence in these indirect costs being due to the more visible technology products. Organizational considerations, processes/practices, and indirect costs are traditionally derived ("wrapped") only by relationship to tangible product characteristics. This traditional approach works well as long as it is understood that no significant changes, and by relation no significant improvements, are being pursued in the area of either the government acquisition or industry?s indirect costs. In this sense then, most launch systems cost models ignore most costs. The alternative was implemented in this LCC study, whereby the approach considered technology and process/practices in balance, with as much detail for one as the other. This RBS LCC study has avoided point-designs, for now, instead emphasizing exploring the trade-space of potential technology advances joined with potential process/practice advances. Given the range of decisions, and all their combinations, it was necessary to create a model of the original model
New Approaches in Reusable Booster System Life Cycle Cost Modeling
Zapata, Edgar
2013-01-01
This paper presents the results of a 2012 life cycle cost (LCC) study of hybrid Reusable Booster Systems (RBS) conducted by NASA Kennedy Space Center (KSC) and the Air Force Research Laboratory (AFRL). The work included the creation of a new cost estimating model and an LCC analysis, building on past work where applicable, but emphasizing the integration of new approaches in life cycle cost estimation. Specifically, the inclusion of industry processes/practices and indirect costs were a new and significant part of the analysis. The focus of LCC estimation has traditionally been from the perspective of technology, design characteristics, and related factors such as reliability. Technology has informed the cost related support to decision makers interested in risk and budget insight. This traditional emphasis on technology occurs even though it is well established that complex aerospace systems costs are mostly about indirect costs, with likely only partial influence in these indirect costs being due to the more visible technology products. Organizational considerations, processes/practices, and indirect costs are traditionally derived ("wrapped") only by relationship to tangible product characteristics. This traditional approach works well as long as it is understood that no significant changes, and by relation no significant improvements, are being pursued in the area of either the government acquisition or industry?s indirect costs. In this sense then, most launch systems cost models ignore most costs. The alternative was implemented in this LCC study, whereby the approach considered technology and process/practices in balance, with as much detail for one as the other. This RBS LCC study has avoided point-designs, for now, instead emphasizing exploring the trade-space of potential technology advances joined with potential process/practice advances. Given the range of decisions, and all their combinations, it was necessary to create a model of the original model
Modelling and simulating retail management practices: a first approach
Siebers, Peer-Olaf; Aickelin, Uwe; Celia, Helen; Clegg, Chris
2010-01-01
Multi-agent systems offer a new and exciting way of understanding the world of work. We apply agent-based modeling and simulation to investigate a set of problems\\ud in a retail context. Specifically, we are working to understand the relationship between people management practices on the shop-floor and retail performance. Despite the fact we are working within a relatively novel and complex domain, it is clear that using an agent-based approach offers great potential for improving organizati...
Truncated conformal space approach to scaling Lee-Yang model
International Nuclear Information System (INIS)
Yurov, V.P.; Zamolodchikov, Al.B.
1989-01-01
A numerical approach to 2D relativstic field theories is suggested. Considering a field theory model as an ultraviolet conformal field theory perturbed by suitable relevant scalar operator one studies it in finite volume (on a circle). The perturbed Hamiltonian acts in the conformal field theory space of states and its matrix elements can be extracted from the conformal field theory. Truncation of the space at reasonable level results in a finite dimensional problem for numerical analyses. The nonunitary field theory with the ultraviolet region controlled by the minimal conformal theory μ(2/5) is studied in detail. 9 refs.; 17 figs
A coordination chemistry approach for modeling trace element adsorption
International Nuclear Information System (INIS)
Bourg, A.C.M.
1986-01-01
The traditional distribution coefficient, Kd, is highly dependent on the water chemistry and the surface properties of the geological system being studied and is therefore quite inappropriate for use in predictive models. Adsorption, one of the many processes included in Kd values, is described here using a coordination chemistry approach. The concept of adsorption of cationic trace elements by solid hydrous oxides can be applied to natural solids. The adsorption process is thus understood in terms of a classical complexation leading to the formation of surface (heterogeneous) ligands. Applications of this concept to some freshwater, estuarine and marine environments are discussed. (author)
Design of Multithreaded Software The Entity-Life Modeling Approach
Sandén, Bo I
2011-01-01
This book assumes familiarity with threads (in a language such as Ada, C#, or Java) and introduces the entity-life modeling (ELM) design approach for certain kinds of multithreaded software. ELM focuses on "reactive systems," which continuously interact with the problem environment. These "reactive systems" include embedded systems, as well as such interactive systems as cruise controllers and automated teller machines.Part I covers two fundamentals: program-language thread support and state diagramming. These are necessary for understanding ELM and are provided primarily for reference. P
Graphene growth process modeling: a physical-statistical approach
Wu, Jian; Huang, Qiang
2014-09-01
As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.
An approach to modelling radiation damage by fast ionizing particles
International Nuclear Information System (INIS)
Thomas, G.E.
1987-01-01
The paper presents a statistical approach to modelling radiation damage in small biological structures such as enzymes, viruses, and some cells. Irreparable damage is assumed to be caused by the occurrence of ionizations within sensitive regions. For structures containing double-stranded DNA, one or more ionizations occurring within each strand of the DNA will cause inactivation; for simpler structures without double-stranded DNA a single ionization within the structure will be sufficient for inactivation. Damaging ionizations occur along tracks of primary irradiating particles or along tracks of secondary particles released at primary ionizations. An inactivation probability is derived for each damage mechanism, expressed in integral form in terms of the radius of the biological structure (assumed spherical), rate of ionization along primary tracks, and maximum energy for secondary particles. The performance of each model is assessed by comparing results from the model with those derived from data from various experimental studies extracted from the literature. For structures where a single ionization is sufficient for inactivation, the model gives qualitatively promising results; for larger more complex structures containing double-stranded DNA, the model requires further refinements. (author)
Sweat loss prediction using a multi-model approach.
Xu, Xiaojiang; Santee, William R
2011-07-01
A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.
A new approach for modeling dry deposition velocity of particles
Giardina, M.; Buffa, P.
2018-05-01
The dry deposition process is recognized as an important pathway among the various removal processes of pollutants in the atmosphere. In this field, there are several models reported in the literature useful to predict the dry deposition velocity of particles of different diameters but many of them are not capable of representing dry deposition phenomena for several categories of pollutants and deposition surfaces. Moreover, their applications is valid for specific conditions and if the data in that application meet all of the assumptions required of the data used to define the model. In this paper a new dry deposition velocity model based on an electrical analogy schema is proposed to overcome the above issues. The dry deposition velocity is evaluated by assuming that the resistances that affect the particle flux in the Quasi-Laminar Sub-layers can be combined to take into account local features of the mutual influence of inertial impact processes and the turbulent one. Comparisons with the experimental data from literature indicate that the proposed model allows to capture with good agreement the main dry deposition phenomena for the examined environmental conditions and deposition surfaces to be determined. The proposed approach could be easily implemented within atmospheric dispersion modeling codes and efficiently addressing different deposition surfaces for several particle pollution.
Numerical approaches to model perturbation fire in turing pattern formations
Campagna, R.; Brancaccio, M.; Cuomo, S.; Mazzoleni, S.; Russo, L.; Siettos, K.; Giannino, F.
2017-11-01
Turing patterns were observed in chemical, physical and biological systems described by coupled reaction-diffusion equations. Several models have been formulated proposing the water as the causal mechanism of vegetation pattern formation, but this isn't an exhaustive hypothesis in some natural environments. An alternative explanation has been related to the plant-soil negative feedback. In Marasco et al. [1] the authors explored the hypothesis that both mechanisms contribute in the formation of regular and irregular vegetation patterns. The mathematical model consists in three partial differential equations (PDEs) that take into account for a dynamic balance between biomass, water and toxic compounds. A numerical approach is mandatory also to investigate on the predictions of this kind of models. In this paper we start from the mathematical model described in [1], set the model parameters such that the biomass reaches a stable spatial pattern (spots) and present preliminary studies about the occurrence of perturbing events, such as wildfire, that can affect the regularity of the biomass configuration.
Kinetics approach to modeling of polymer additive degradation in lubricants
Institute of Scientific and Technical Information of China (English)
llyaI.KUDISH; RubenG.AIRAPETYAN; Michael; J.; COVITCH
2001-01-01
A kinetics problem for a degrading polymer additive dissolved in a base stock is studied.The polymer degradation may be caused by the combination of such lubricant flow parameters aspressure, elongational strain rate, and temperature as well as lubricant viscosity and the polymercharacteristics (dissociation energy, bead radius, bond length, etc.). A fundamental approach tothe problem of modeling mechanically induced polymer degradation is proposed. The polymerdegradation is modeled on the basis of a kinetic equation for the density of the statistical distribu-tion of polymer molecules as a function of their molecular weight. The integrodifferential kineticequation for polymer degradation is solved numerically. The effects of pressure, elongational strainrate, temperature, and lubricant viscosity on the process of lubricant degradation are considered.The increase of pressure promotes fast degradation while the increase of temperature delaysdegradation. A comparison of a numerically calculated molecular weight distribution with an ex-perimental one obtained in bench tests showed that they are in excellent agreement with eachother.
Global GPS Ionospheric Modelling Using Spherical Harmonic Expansion Approach
Directory of Open Access Journals (Sweden)
Byung-Kyu Choi
2010-12-01
Full Text Available In this study, we developed a global ionosphere model based on measurements from a worldwide network of global positioning system (GPS. The total number of the international GPS reference stations for development of ionospheric model is about 100 and the spherical harmonic expansion approach as a mathematical method was used. In order to produce the ionospheric total electron content (TEC based on grid form, we defined spatial resolution of 2.0 degree and 5.0 degree in latitude and longitude, respectively. Two-dimensional TEC maps were constructed within the interval of one hour, and have a high temporal resolution compared to global ionosphere maps which are produced by several analysis centers. As a result, we could detect the sudden increase of TEC by processing GPS observables on 29 October, 2003 when the massive solar flare took place.
Static models, recursive estimators and the zero-variance approach
Rubino, Gerardo
2016-01-07
When evaluating dependability aspects of complex systems, most models belong to the static world, where time is not an explicit variable. These models suffer from the same problems than dynamic ones (stochastic processes), such as the frequent combinatorial explosion of the state spaces. In the Monte Carlo domain, on of the most significant difficulties is the rare event situation. In this talk, we describe this context and a recent technique that appears to be at the top performance level in the area, where we combined ideas that lead to very fast estimation procedures with another approach called zero-variance approximation. Both ideas produced a very efficient method that has the right theoretical property concerning robustness, the Bounded Relative Error one. Some examples illustrate the results.
Comparison of different approaches of modelling in a masonry building
Saba, M.; Meloni, D.
2017-12-01
The present work has the objective to model a simple masonry building, through two different modelling methods in order to assess their validity in terms of evaluation of static stresses. Have been chosen two of the most commercial software used to address this kind of problem, which are of S.T.A. Data S.r.l. and Sismicad12 of Concrete S.r.l. While the 3Muri software adopts the Frame by Macro Elements Method (FME), which should be more schematic and more efficient, Sismicad12 software uses the Finite Element Method (FEM), which guarantees accurate results, with greater computational burden. Remarkably differences of the static stresses, for such a simple structure between the two approaches have been found, and an interesting comparison and analysis of the reasons is proposed.
Ordered LOGIT Model approach for the determination of financial distress.
Kinay, B
2010-01-01
Nowadays, as a result of the global competition encountered, numerous companies come up against financial distresses. To predict and take proactive approaches for those problems is quite important. Thus, the prediction of crisis and financial distress is essential in terms of revealing the financial condition of companies. In this study, financial ratios relating to 156 industrial firms that are quoted in the Istanbul Stock Exchange are used and probabilities of financial distress are predicted by means of an ordered logit regression model. By means of Altman's Z Score, the dependent variable is composed by scaling the level of risk. Thus, a model that can compose an early warning system and predict financial distress is proposed.
Model-Based Systems Engineering Approach to Managing Mass Margin
Chung, Seung H.; Bayer, Todd J.; Cole, Bjorn; Cooke, Brian; Dekens, Frank; Delp, Christopher; Lam, Doris
2012-01-01
When designing a flight system from concept through implementation, one of the fundamental systems engineering tasks ismanaging the mass margin and a mass equipment list (MEL) of the flight system. While generating a MEL and computing a mass margin is conceptually a trivial task, maintaining consistent and correct MELs and mass margins can be challenging due to the current practices of maintaining duplicate information in various forms, such as diagrams and tables, and in various media, such as files and emails. We have overcome this challenge through a model-based systems engineering (MBSE) approach within which we allow only a single-source-of-truth. In this paper we describe the modeling patternsused to capture the single-source-of-truth and the views that have been developed for the Europa Habitability Mission (EHM) project, a mission concept study, at the Jet Propulsion Laboratory (JPL).
The Use of Modeling Approach for Teaching Exponential Functions
Nunes, L. F.; Prates, D. B.; da Silva, J. M.
2017-12-01
This work presents a discussion related to the teaching and learning of mathematical contents related to the study of exponential functions in a freshman students group enrolled in the first semester of the Science and Technology Bachelor’s (STB of the Federal University of Jequitinhonha and Mucuri Valleys (UFVJM). As a contextualization tool strongly mentioned in the literature, the modelling approach was used as an educational teaching tool to produce contextualization in the teaching-learning process of exponential functions to these students. In this sense, were used some simple models elaborated with the GeoGebra software and, to have a qualitative evaluation of the investigation and the results, was used Didactic Engineering as a methodology research. As a consequence of this detailed research, some interesting details about the teaching and learning process were observed, discussed and described.
TRIF - an intermediate approach to environmental tritium modelling
International Nuclear Information System (INIS)
Higgins, N.A.
1997-01-01
The movement of tritium through the environment, from an initial atmospheric release to selected end points in the food chain, involves a series of closely coupled and complex processes which are, consequently, difficult to model. TRIF (tritium transfer into food) provides a semi-empirical approach to this transport problem, which can be adjusted to bridge the gap between simple steady state approximations and a fully coupled model of tritium dispersion and migration (Higgins et al., 1996). TRIF provides a time-dependent description of the behaviour of tritium in the form of tritium gas (HT) and tritiated water (HTO) as it enters and moves through the food chain into pasture, crops and animals. This includes a representation of the production and movement of organically bound tritium (OBT). (Author)
Modeling Electronic Circular Dichroism within the Polarizable Embedding Approach
DEFF Research Database (Denmark)
Nørby, Morten S; Olsen, Jógvan Magnus Haugaard; Steinmann, Casper
2017-01-01
We present a systematic investigation of the key components needed to model single chromophore electronic circular dichroism (ECD) within the polarizable embedding (PE) approach. By relying on accurate forms of the embedding potential, where especially the inclusion of local field effects...... are in focus, we show that qualitative agreement between rotatory strength parameters calculated by full quantum mechanical calculations and the more efficient embedding calculations can be obtained. An important aspect in the computation of reliable absorption parameters is the need for conformational...... sampling. We show that a significant number of snapshots are needed to avoid artifacts in the calculated electronic circular dichroism parameters due to insufficient configurational sampling, thus highlighting the efficiency of the PE model....
A Workflow-Oriented Approach To Propagation Models In Heliophysics
Directory of Open Access Journals (Sweden)
Gabriele Pierantoni
2014-01-01
Full Text Available The Sun is responsible for the eruption of billions of tons of plasma andthe generation of near light-speed particles that propagate throughout the solarsystem and beyond. If directed towards Earth, these events can be damaging toour tecnological infrastructure. Hence there is an effort to understand the causeof the eruptive events and how they propagate from Sun to Earth. However, thephysics governing their propagation is not well understood, so there is a need todevelop a theoretical description of their propagation, known as a PropagationModel, in order to predict when they may impact Earth. It is often difficultto define a single propagation model that correctly describes the physics ofsolar eruptive events, and even more difficult to implement models capable ofcatering for all these complexities and to validate them using real observational data.In this paper, we envisage that workflows offer both a theoretical andpractical framerwork for a novel approach to propagation models. We definea mathematical framework that aims at encompassing the different modalitieswith which workflows can be used, and provide a set of generic building blockswritten in the TAVERNA workflow language that users can use to build theirown propagation models. Finally we test both the theoretical model and thecomposite building blocks of the workflow with a real Science Use Case that wasdiscussed during the 4th CDAW (Coordinated Data Analysis Workshop eventheld by the HELIO project. We show that generic workflow building blocks canbe used to construct a propagation model that succesfully describes the transitof solar eruptive events toward Earth and predict a correct Earth-impact time
A modeling approach for compounds affecting body composition.
Gennemark, Peter; Jansson-Löfmark, Rasmus; Hyberg, Gina; Wigstrand, Maria; Kakol-Palm, Dorota; Håkansson, Pernilla; Hovdal, Daniel; Brodin, Peter; Fritsch-Fredin, Maria; Antonsson, Madeleine; Ploj, Karolina; Gabrielsson, Johan
2013-12-01
Body composition and body mass are pivotal clinical endpoints in studies of welfare diseases. We present a combined effort of established and new mathematical models based on rigorous monitoring of energy intake (EI) and body mass in mice. Specifically, we parameterize a mechanistic turnover model based on the law of energy conservation coupled to a drug mechanism model. Key model variables are fat-free mass (FFM) and fat mass (FM), governed by EI and energy expenditure (EE). An empirical Forbes curve relating FFM to FM was derived experimentally for female C57BL/6 mice. The Forbes curve differs from a previously reported curve for male C57BL/6 mice, and we thoroughly analyse how the choice of Forbes curve impacts model predictions. The drug mechanism function acts on EI or EE, or both. Drug mechanism parameters (two to three parameters) and system parameters (up to six free parameters) could be estimated with good precision (coefficients of variation typically mass and FM changes at different drug provocations using a similar model for man. Surprisingly, model simulations indicate that an increase in EI (e.g. 10 %) was more efficient than an equal lowering of EI. Also, the relative change in body mass and FM is greater in man than in mouse at the same relative change in either EI or EE. We acknowledge that this assumes the same drug mechanism impact across the two species. A set of recommendations regarding the Forbes curve, vehicle control groups, dual action on EI and loss, and translational aspects are discussed. This quantitative approach significantly improves data interpretation, disease system understanding, safety assessment and translation across species.
Reconstructing plateau icefields: Evaluating empirical and modelled approaches
Pearce, Danni; Rea, Brice; Barr, Iestyn
2013-04-01
Glacial landforms are widely utilised to reconstruct former glacier geometries with a common aim to estimate the Equilibrium Line Altitudes (ELAs) and from these, infer palaeoclimatic conditions. Such inferences may be studied on a regional scale and used to correlate climatic gradients across large distances (e.g., Europe). In Britain, the traditional approach uses geomorphological mapping with hand contouring to derive the palaeo-ice surface. Recently, ice surface modelling enables an equilibrium profile reconstruction tuned using the geomorphology. Both methods permit derivation of palaeo-climate but no study has compared the two methods for the same ice-mass. This is important because either approach may result in differences in glacier limits, ELAs and palaeo-climate. This research uses both methods to reconstruct a plateau icefield and quantifies the results from a cartographic and geometrical aspect. Detailed geomorphological mapping of the Tweedsmuir Hills in the Southern Uplands, Scotland (c. 320 km2) was conducted to examine the extent of Younger Dryas (YD; 12.9 -11.7 cal. ka BP) glaciation. Landform evidence indicates a plateau icefield configuration of two separate ice-masses during the YD covering an area c. 45 km2 and 25 km2. The interpreted age is supported by new radiocarbon dating of basal stratigraphies and Terrestrial Cosmogenic Nuclide Analysis (TCNA) of in situ boulders. Both techniques produce similar configurations however; the model results in a coarser resolution requiring further processing if a cartographic map is required. When landforms are absent or fragmentary (e.g., trimlines and lateral moraines), like in many accumulation zones on plateau icefields, the geomorphological approach increasingly relies on extrapolation between lines of evidence and on the individual's perception of how the ice-mass ought to look. In some locations this results in an underestimation of the ice surface compared to the modelled surface most likely due to
The redshift distribution of cosmological samples: a forward modeling approach
Energy Technology Data Exchange (ETDEWEB)
Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina, E-mail: joerg.herbel@phys.ethz.ch, E-mail: tomasz.kacprzak@phys.ethz.ch, E-mail: adam.amara@phys.ethz.ch, E-mail: alexandre.refregier@phys.ethz.ch, E-mail: claudio.bruderer@phys.ethz.ch, E-mail: andrina.nicola@phys.ethz.ch [Institute for Astronomy, Department of Physics, ETH Zürich, Wolfgang-Pauli-Strasse 27, 8093 Zürich (Switzerland)
2017-08-01
Determining the redshift distribution n ( z ) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n ( z ) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc(UFig) (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n ( z ) distributions for the acceptable models. We demonstrate the method by determining n ( z ) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n ( z ) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.
The redshift distribution of cosmological samples: a forward modeling approach
Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina
2017-08-01
Determining the redshift distribution n(z) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n(z) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc{UFig} (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n(z) distributions for the acceptable models. We demonstrate the method by determining n(z) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n(z) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.
The redshift distribution of cosmological samples: a forward modeling approach
International Nuclear Information System (INIS)
Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina
2017-01-01
Determining the redshift distribution n ( z ) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n ( z ) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc(UFig) (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n ( z ) distributions for the acceptable models. We demonstrate the method by determining n ( z ) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n ( z ) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.
A quality risk management model approach for cell therapy manufacturing.
Lopez, Fabio; Di Bartolo, Chiara; Piazza, Tommaso; Passannanti, Antonino; Gerlach, Jörg C; Gridelli, Bruno; Triolo, Fabio
2010-12-01
International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell-based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator-introduced variations, and affected by heterogeneity of the processed organs/tissues and lot-dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell-based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo-quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed. © 2010 Society for Risk Analysis.
[New approaches in pharmacology: numerical modelling and simulation].
Boissel, Jean-Pierre; Cucherat, Michel; Nony, Patrice; Dronne, Marie-Aimée; Kassaï, Behrouz; Chabaud, Sylvie
2005-01-01
The complexity of pathophysiological mechanisms is beyond the capabilities of traditional approaches. Many of the decision-making problems in public health, such as initiating mass screening, are complex. Progress in genomics and proteomics, and the resulting extraordinary increase in knowledge with regard to interactions between gene expression, the environment and behaviour, the customisation of risk factors and the need to combine therapies that individually have minimal though well documented efficacy, has led doctors to raise new questions: how to optimise choice and the application of therapeutic strategies at the individual rather than the group level, while taking into account all the available evidence? This is essentially a problem of complexity with dimensions similar to the previous ones: multiple parameters with nonlinear relationships between them, varying time scales that cannot be ignored etc. Numerical modelling and simulation (in silico investigations) have the potential to meet these challenges. Such approaches are considered in drug innovation and development. They require a multidisciplinary approach, and this will involve modification of the way research in pharmacology is conducted.
THE FAIRSHARES MODEL: AN ETHICAL APPROACH TO SOCIAL ENTERPRISE DEVELOPMENT?
Directory of Open Access Journals (Sweden)
Rory James Ridley-Duff
2015-07-01
Full Text Available This paper is based on the keynote address to the 14th International Association of Public and Non-Profit Marketing (IAPNM conference. It explore the question "What impact do ethical values in the FairShares Model have on social entrepreneurial behaviour?" In the first part, three broad approaches to social enterprise are set out: co-operative and mutual enterprises (CMEs, social and responsible businesses (SRBs and charitable trading activities (CTAs. The ethics that guide each approach are examined to provide a conceptual framework for examining FairShares as a case study. In the second part, findings are scrutinised in terms of the ethical values and principles that are activated when FairShares is applied to practice. The paper contributes to knowledge by giving an example of the way OpenSource technology (Loomio has been used to translate 'espoused theories' into 'theories in use' to advance social enterprise development. The review of FairShares using the conceptual framework suggests there is a fourth approach based on multi-stakeholder co-operation to create 'associative democracy' in the workplace.
Engineering approach to model and compute electric power markets settlements
International Nuclear Information System (INIS)
Kumar, J.; Petrov, V.
2006-01-01
Back-office accounting settlement activities are an important part of market operations in Independent System Operator (ISO) organizations. A potential way to measure ISO market design correctness is to analyze how well market price signals create incentives or penalties for creating an efficient market to achieve market design goals. Market settlement rules are an important tool for implementing price signals which are fed back to participants via the settlement activities of the ISO. ISO's are currently faced with the challenge of high volumes of data resulting from the increasing size of markets and ever-changing market designs, as well as the growing complexity of wholesale energy settlement business rules. This paper analyzed the problem and presented a practical engineering solution using an approach based on mathematical formulation and modeling of large scale calculations. The paper also presented critical comments on various differences in settlement design approaches to electrical power market design, as well as further areas of development. The paper provided a brief introduction to the wholesale energy market settlement systems and discussed problem formulation. An actual settlement implementation framework and discussion of the results and conclusions were also presented. It was concluded that a proper engineering approach to this domain can yield satisfying results by formalizing wholesale energy settlements. Significant improvements were observed in the initial preparation phase, scoping and effort estimation, implementation and testing. 5 refs., 2 figs
Different approach to the modeling of nonfree particle diffusion
Buhl, Niels
2018-03-01
A new approach to the modeling of nonfree particle diffusion is presented. The approach uses a general setup based on geometric graphs (networks of curves), which means that particle diffusion in anything from arrays of barriers and pore networks to general geometric domains can be considered and that the (free random walk) central limit theorem can be generalized to cover also the nonfree case. The latter gives rise to a continuum-limit description of the diffusive motion where the effect of partially absorbing barriers is accounted for in a natural and non-Markovian way that, in contrast to the traditional approach, quantifies the absorptivity of a barrier in terms of a dimensionless parameter in the range 0 to 1. The generalized theorem gives two general analytic expressions for the continuum-limit propagator: an infinite sum of Gaussians and an infinite sum of plane waves. These expressions entail the known method-of-images and Laplace eigenfunction expansions as special cases and show how the presence of partially absorbing barriers can lead to phenomena such as line splitting and band gap formation in the plane wave wave-number spectrum.
Thin inclusion approach for modelling of heterogeneous conducting materials
Lavrov, Nikolay; Smirnova, Alevtina; Gorgun, Haluk; Sammes, Nigel
Experimental data show that heterogeneous nanostructure of solid oxide and polymer electrolyte fuel cells could be approximated as an infinite set of fiber-like or penny-shaped inclusions in a continuous medium. Inclusions can be arranged in a cluster mode and regular or random order. In the newly proposed theoretical model of nanostructured material, the most attention is paid to the small aspect ratio of structural elements as well as to some model problems of electrostatics. The proposed integral equation for electric potential caused by the charge distributed over the single circular or elliptic cylindrical conductor of finite length, as a single unit of a nanostructured material, has been asymptotically simplified for the small aspect ratio and solved numerically. The result demonstrates that surface density changes slightly in the middle part of the thin domain and has boundary layers localized near the edges. It is anticipated, that contribution of boundary layer solution to the surface density is significant and cannot be governed by classic equation for smooth linear charge. The role of the cross-section shape is also investigated. Proposed approach is sufficiently simple, robust and allows extension to either regular or irregular system of various inclusions. This approach can be used for the development of the system of conducting inclusions, which are commonly present in nanostructured materials used for solid oxide and polymer electrolyte fuel cell (PEMFC) materials.
A Modeling Approach for Plastic-Metal Laser Direct Joining
Lutey, Adrian H. A.; Fortunato, Alessandro; Ascari, Alessandro; Romoli, Luca
2017-09-01
Laser processing has been identified as a feasible approach to direct joining of metal and plastic components without the need for adhesives or mechanical fasteners. The present work sees development of a modeling approach for conduction and transmission laser direct joining of these materials based on multi-layer optical propagation theory and numerical heat flow simulation. The scope of this methodology is to predict process outcomes based on the calculated joint interface and upper surface temperatures. Three representative cases are considered for model verification, including conduction joining of PBT and aluminum alloy, transmission joining of optically transparent PET and stainless steel, and transmission joining of semi-transparent PA 66 and stainless steel. Conduction direct laser joining experiments are performed on black PBT and 6082 anticorodal aluminum alloy, achieving shear loads of over 2000 N with specimens of 2 mm thickness and 25 mm width. Comparison with simulation results shows that consistently high strength is achieved where the peak interface temperature is above the plastic degradation temperature. Comparison of transmission joining simulations and published experimental results confirms these findings and highlights the influence of plastic layer optical absorption on process feasibility.
A modelling approach to designing microstructures in thermal barrier coatings
International Nuclear Information System (INIS)
Gupta, M.; Nylen, P.; Wigren, J.
2013-01-01
Thermomechanical properties of Thermal Barrier Coatings (TBCs) are strongly influenced by coating defects, such as delaminations and pores, thus making it essential to have a fundamental understanding of microstructure-property relationships in TBCs to produce a desired coating. Object-Oriented Finite element analysis (OOF) has been shown previously as an effective tool for evaluating thermal and mechanical material behaviour, as this method is capable of incorporating the inherent material microstructure as input to the model. In this work, OOF was used to predict the thermal conductivity and effective Young's modulus of TBC topcoats. A Design of Experiments (DoE) was conducted by varying selected parameters for spraying Yttria-Stabilised Zirconia (YSZ) topcoat. The microstructure was assessed with SEM, and image analysis was used to characterize the porosity content. The relationships between microstructural features and properties predicted by modelling are discussed. The microstructural features having the most beneficial effect on properties were sprayed with a different spray gun so as to verify the results obtained from modelling. Characterisation of the coatings included microstructure evaluation, thermal conductivity and lifetime measurements. The modelling approach in combination with experiments undertaken in this study was shown to be an effective way to achieve coatings with optimised thermo-mechanical properties.
Numerical modelling of diesel spray using the Eulerian multiphase approach
International Nuclear Information System (INIS)
Vujanović, Milan; Petranović, Zvonimir; Edelbauer, Wilfried; Baleta, Jakov; Duić, Neven
2015-01-01
Highlights: • Numerical model for fuel disintegration was presented. • Fuel liquid and vapour were calculated. • Good agreement with experimental data was shown for various combinations of injection and chamber pressure. - Abstract: This research investigates high pressure diesel fuel injection into the combustion chamber by performing computational simulations using the Euler–Eulerian multiphase approach. Six diesel-like conditions were simulated for which the liquid fuel jet was injected into a pressurised inert environment (100% N 2 ) through a 205 μm nozzle hole. The analysis was focused on the liquid jet and vapour penetration, describing spatial and temporal spray evolution. For this purpose, an Eulerian multiphase model was implemented, variations of the sub-model coefficients were performed, and their impact on the spray formation was investigated. The final set of sub-model coefficients was applied to all operating points. Several simulations of high pressure diesel injections (50, 80, and 120 MPa) combined with different chamber pressures (5.4 and 7.2 MPa) were carried out and results were compared to the experimental data. The predicted results share a similar spray cloud shape for all conditions with the different vapour and liquid penetration length. The liquid penetration is shortened with the increase in chamber pressure, whilst the vapour penetration is more pronounced by elevating the injection pressure. Finally, the results showed good agreement when compared to the measured data, and yielded the correct trends for both the liquid and vapour penetrations under different operating conditions
Testing adaptive toolbox models: a Bayesian hierarchical approach.
Scheibehenne, Benjamin; Rieskamp, Jörg; Wagenmakers, Eric-Jan
2013-01-01
Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox framework. How can a toolbox model be quantitatively specified? How can the number of toolbox strategies be limited to prevent uncontrolled strategy sprawl? How can a toolbox model be formally tested against alternative theories? The authors show how these challenges can be met by using Bayesian inference techniques. By means of parameter recovery simulations and the analysis of empirical data across a variety of domains (i.e., judgment and decision making, children's cognitive development, function learning, and perceptual categorization), the authors illustrate how Bayesian inference techniques allow toolbox models to be quantitatively specified, strategy sprawl to be contained, and toolbox models to be rigorously tested against competing theories. The authors demonstrate that their approach applies at the individual level but can also be generalized to the group level with hierarchical Bayesian procedures. The suggested Bayesian inference techniques represent a theoretical and methodological advancement for toolbox theories of cognition and behavior.
Replacement model of city bus: A dynamic programming approach
Arifin, Dadang; Yusuf, Edhi
2017-06-01
This paper aims to develop a replacement model of city bus vehicles operated in Bandung City. This study is driven from real cases encountered by the Damri Company in the efforts to improve services to the public. The replacement model propounds two policy alternatives: First, to maintain or keep the vehicles, and second is to replace them with new ones taking into account operating costs, revenue, salvage value, and acquisition cost of a new vehicle. A deterministic dynamic programming approach is used to solve the model. The optimization process was heuristically executed using empirical data of Perum Damri. The output of the model is to determine the replacement schedule and the best policy if the vehicle has passed the economic life. Based on the results, the technical life of the bus is approximately 20 years old, while the economic life is an average of 9 (nine) years. It means that after the bus is operated for 9 (nine) years, managers should consider the policy of rejuvenation.
An interdisciplinary approach to modeling tritium transfer into the environment
International Nuclear Information System (INIS)
Galeriu, D; Melintescu, A.
2005-01-01
More robust radiological assessment models are required to support the safety case for the nuclear industry. Heavy water reactors, fuel processing plants, radiopharmaceutical factories, and the future fusion reactor, all have large tritium loads. While of low probability, large accidental tritium releases cannot be ignored. For Romania that uses CANDU600 for nuclear energy, tritium is the national radionuclide. Tritium enters directly into the life cycle in many physicochemical forms. Tritiated water (HTO) is leaked from most nuclear installations but is partially converted into organically bound tritium (OBT) through plant and animal metabolic processes. Hydrogen and carbon are elemental components of major nutrients and animal tissues and their radioisotopes must be modeled differently from those of most other radionuclides. Tritium transfer from atmosphere to plant and conversion into organically bound tritium strongly depend on plant characteristics, season, and weather conditions. In order to cope with this large variability and avoid expensive calibration experiments, we developed a model using knowledge of plant physiology, agrometeorology, soil sciences, hydrology, and climatology. The transfer of tritiated water to plant was modeled with resistance approach including sparse canopy. The canopy resistance was modeled using the Jarvis-Calvet approach modified in order to make direct use of the canopy photosynthesis rate. The crop growth model WOFOST was used for photosynthesis rate both for canopy resistance and formation of organically bound tritium. Using this formalism, the tritium transfer parameters were directly linked to processes and parameters known from agricultural sciences. Model predictions for tritium in wheat were close to a factor two, according to experimental data without any calibration. The model was also tested on rice and soybean and can be applied for various plants and environmental conditions. For sparse canopy, the model used coupled
Predicting future glacial lakes in Austria using different modelling approaches
Otto, Jan-Christoph; Helfricht, Kay; Prasicek, Günther; Buckel, Johannes; Keuschnig, Markus
2017-04-01
Glacier retreat is one of the most apparent consequences of temperature rise in the 20th and 21th centuries in the European Alps. In Austria, more than 240 new lakes have formed in glacier forefields since the Little Ice Age. A similar signal is reported from many mountain areas worldwide. Glacial lakes can constitute important environmental and socio-economic impacts on high mountain systems including water resource management, sediment delivery, natural hazards, energy production and tourism. Their development significantly modifies the landscape configuration and visual appearance of high mountain areas. Knowledge on the location, number and extent of these future lakes can be used to assess potential impacts on high mountain geo-ecosystems and upland-lowland interactions. Information on new lakes is critical to appraise emerging threads and potentials for society. The recent development of regional ice thickness models and their combination with high resolution glacier surface data allows predicting the topography below current glaciers by subtracting ice thickness from glacier surface. Analyzing these modelled glacier bed surfaces reveals overdeepenings that represent potential locations for future lakes. In order to predict the location of future glacial lakes below recent glaciers in the Austrian Alps we apply different ice thickness models using high resolution terrain data and glacier outlines. The results are compared and validated with ice thickness data from geophysical surveys. Additionally, we run the models on three different glacier extents provided by the Austrian Glacier Inventories from 1969, 1998 and 2006. Results of this historical glacier extent modelling are compared to existing glacier lakes and discussed focusing on geomorphological impacts on lake evolution. We discuss model performance and observed differences in the results in order to assess the approach for a realistic prediction of future lake locations. The presentation delivers
An Approach to Enforcing Clark-Wilson Model in Role-based Access Control Model
Institute of Scientific and Technical Information of China (English)
LIANGBin; SHIWenchang; SUNYufang; SUNBo
2004-01-01
Using one security model to enforce another is a prospective solution to multi-policy support. In this paper, an approach to the enforcing Clark-Wilson data integrity model in the Role-based access control (RBAC) model is proposed. An enforcement construction with great feasibility is presented. In this construction, a direct way to enforce the Clark-Wilson model is provided, the corresponding relations among users, transformation procedures, and constrained data items are strengthened; the concepts of task and subtask are introduced to enhance the support to least-privilege. The proposed approach widens the applicability of RBAC. The theoretical foundation for adopting Clark-Wilson model in a RBAC system with small cost is offered to meet the requirements of multi-policy support and policy flexibility.
Modelling the Heat Consumption in District Heating Systems using a Grey-box approach
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg; Madsen, Henrik
2006-01-01
identification of an overall model structure followed by data-based modelling, whereby the details of the model are identified. This approach is sometimes called grey-box modelling, but the specific approach used here does not require states to be specified. Overall, the paper demonstrates the power of the grey......-box approach. (c) 2005 Elsevier B.V. All rights reserved....
Artificial intelligence-based modeling and control of fluidized bed combustion
Energy Technology Data Exchange (ETDEWEB)
Ikonen, E.; Leppaekoski, K. (Univ. of Oulu, Dept. of Process and Environmental Engineering (Finland)). email: enso.ikonen@oulu.fi
2009-07-01
AI-inspired techniques have a lot to offer when developing methods for advanced identification, monitoring, control and optimization of industrial processes, such as power plants. Advanced control methods have been extensively examined in the research of the Power Plant Automation group at the Systems Engineering Laboratory, e.g., in fuel inventory modelling, combustion power control, modelling and control of flue gas oxygen, drum control, modelling and control of superheaters, or in optimization of flue-gas emissions. Most engineering approaches to artificial intelligence (AI) are characterized by two fundamental properties: the ability to learn from various sources and the ability to deal with plant complexity. Learning systems that are able to operate in uncertain environments based on incomplete information are commonly referred to as being intelligent. A number of other approaches exist, characterized by these properties, but not easily categorized as AI-systems. Advanced control methods (adaptive, predictive, multivariable, robust, etc.) are based on the availability of a model of the process to be controlled. Hence identification of processes becomes a key issue, leading to the use of adaptation and learning techniques. A typical learning control system concerns a selection of learning techniques applied for updating a process model, which in turn is used for the controller design. When design of learning control systems is complemented with concerns for dealing with uncertainties or vaguenesses in models, measurements, or even objectives, particularly close connections exist between advanced process control and methods of artificial intelligence and machine learning. Needs for advanced techniques are typically characterized by the desire to properly handle plant non-linearities, the multivariable nature of the dynamic problems, and the necessity to adapt to changing plant conditions. In the field of fluidized bed combustion (FBC) control, the many promising
Banking Crisis Early Warning Model based on a Bayesian Model Averaging Approach
Directory of Open Access Journals (Sweden)
Taha Zaghdoudi
2016-08-01
Full Text Available The succession of banking crises in which most have resulted in huge economic and financial losses, prompted several authors to study their determinants. These authors constructed early warning models to prevent their occurring. It is in this same vein as our study takes its inspiration. In particular, we have developed a warning model of banking crises based on a Bayesian approach. The results of this approach have allowed us to identify the involvement of the decline in bank profitability, deterioration of the competitiveness of the traditional intermediation, banking concentration and higher real interest rates in triggering bank crisis.
Modeling healthcare authorization and claim submissions using the openEHR dual-model approach
2011-01-01
Background The TISS standard is a set of mandatory forms and electronic messages for healthcare authorization and claim submissions among healthcare plans and providers in Brazil. It is not based on formal models as the new generation of health informatics standards suggests. The objective of this paper is to model the TISS in terms of the openEHR archetype-based approach and integrate it into a patient-centered EHR architecture. Methods Three approaches were adopted to model TISS. In the first approach, a set of archetypes was designed using ENTRY subclasses. In the second one, a set of archetypes was designed using exclusively ADMIN_ENTRY and CLUSTERs as their root classes. In the third approach, the openEHR ADMIN_ENTRY is extended with classes designed for authorization and claim submissions, and an ISM_TRANSITION attribute is added to the COMPOSITION class. Another set of archetypes was designed based on this model. For all three approaches, templates were designed to represent the TISS forms. Results The archetypes based on the openEHR RM (Reference Model) can represent all TISS data structures. The extended model adds subclasses and an attribute to the COMPOSITION class to represent information on authorization and claim submissions. The archetypes based on all three approaches have similar structures, although rooted in different classes. The extended openEHR RM model is more semantically aligned with the concepts involved in a claim submission, but may disrupt interoperability with other systems and the current tools must be adapted to deal with it. Conclusions Modeling the TISS standard by means of the openEHR approach makes it aligned with ISO recommendations and provides a solid foundation on which the TISS can evolve. Although there are few administrative archetypes available, the openEHR RM is expressive enough to represent the TISS standard. This paper focuses on the TISS but its results may be extended to other billing processes. A complete
Modeling healthcare authorization and claim submissions using the openEHR dual-model approach
Directory of Open Access Journals (Sweden)
Freire Sergio M
2011-10-01
Full Text Available Abstract Background The TISS standard is a set of mandatory forms and electronic messages for healthcare authorization and claim submissions among healthcare plans and providers in Brazil. It is not based on formal models as the new generation of health informatics standards suggests. The objective of this paper is to model the TISS in terms of the openEHR archetype-based approach and integrate it into a patient-centered EHR architecture. Methods Three approaches were adopted to model TISS. In the first approach, a set of archetypes was designed using ENTRY subclasses. In the second one, a set of archetypes was designed using exclusively ADMIN_ENTRY and CLUSTERs as their root classes. In the third approach, the openEHR ADMIN_ENTRY is extended with classes designed for authorization and claim submissions, and an ISM_TRANSITION attribute is added to the COMPOSITION class. Another set of archetypes was designed based on this model. For all three approaches, templates were designed to represent the TISS forms. Results The archetypes based on the openEHR RM (Reference Model can represent all TISS data structures. The extended model adds subclasses and an attribute to the COMPOSITION class to represent information on authorization and claim submissions. The archetypes based on all three approaches have similar structures, although rooted in different classes. The extended openEHR RM model is more semantically aligned with the concepts involved in a claim submission, but may disrupt interoperability with other systems and the current tools must be adapted to deal with it. Conclusions Modeling the TISS standard by means of the openEHR approach makes it aligned with ISO recommendations and provides a solid foundation on which the TISS can evolve. Although there are few administrative archetypes available, the openEHR RM is expressive enough to represent the TISS standard. This paper focuses on the TISS but its results may be extended to other billing
Export of microplastics from land to sea. A modelling approach.
Siegfried, Max; Koelmans, Albert A; Besseling, Ellen; Kroeze, Carolien
2017-12-15
Quantifying the transport of plastic debris from river to sea is crucial for assessing the risks of plastic debris to human health and the environment. We present a global modelling approach to analyse the composition and quantity of point-source microplastic fluxes from European rivers to the sea. The model accounts for different types and sources of microplastics entering river systems via point sources. We combine information on these sources with information on sewage management and plastic retention during river transport for the largest European rivers. Sources of microplastics include personal care products, laundry, household dust and tyre and road wear particles (TRWP). Most of the modelled microplastics exported by rivers to seas are synthetic polymers from TRWP (42%) and plastic-based textiles abraded during laundry (29%). Smaller sources are synthetic polymers and plastic fibres in household dust (19%) and microbeads in personal care products (10%). Microplastic export differs largely among European rivers, as a result of differences in socio-economic development and technological status of sewage treatment facilities. About two-thirds of the microplastics modelled in this study flow into the Mediterranean and Black Sea. This can be explained by the relatively low microplastic removal efficiency of sewage treatment plants in the river basins draining into these two seas. Sewage treatment is generally more efficient in river basins draining into the North Sea, the Baltic Sea and the Atlantic Ocean. We use our model to explore future trends up to the year 2050. Our scenarios indicate that in the future river export of microplastics may increase in some river basins, but decrease in others. Remarkably, for many basins we calculate a reduction in river export of microplastics from point-sources, mainly due to an anticipated improvement in sewage treatment. Copyright © 2017 Elsevier Ltd. All rights reserved.
BioModels: expanding horizons to include more modelling approaches and formats.
Glont, Mihai; Nguyen, Tung V N; Graesslin, Martin; Hälke, Robert; Ali, Raza; Schramm, Jochen; Wimalaratne, Sarala M; Kothamachu, Varun B; Rodriguez, Nicolas; Swat, Maciej J; Eils, Jurgen; Eils, Roland; Laibe, Camille; Malik-Sheriff, Rahuman S; Chelliah, Vijayalakshmi; Le Novère, Nicolas; Hermjakob, Henning
2018-01-04
BioModels serves as a central repository of mathematical models representing biological processes. It offers a platform to make mathematical models easily shareable across the systems modelling community, thereby supporting model reuse. To facilitate hosting a broader range of model formats derived from diverse modelling approaches and tools, a new infrastructure for BioModels has been developed that is available at http://www.ebi.ac.uk/biomodels. This new system allows submitting and sharing of a wide range of models with improved support for formats other than SBML. It also offers a version-control backed environment in which authors and curators can work collaboratively to curate models. This article summarises the features available in the current system and discusses the potential benefit they offer to the users over the previous system. In summary, the new portal broadens the scope of models accepted in BioModels and supports collaborative model curation which is crucial for model reproducibility and sharing. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Mesoscopic approach to modeling elastic-plastic polycrystalline material behaviour
International Nuclear Information System (INIS)
Kovac, M.; Cizelj, L.
2001-01-01
Extreme loadings during severe accident conditions might cause failure or rupture of the pressure boundary of a reactor coolant system. Reliable estimation of the extreme deformations can be crucial to determine the consequences of such an accident. One of important drawbacks of classical continuum mechanics is idealization of inhomogenous microstructure of materials. This paper discusses the mesoscopic approach to modeling the elastic-plastic behavior of a polycrystalline material. The main idea is to divide the continuum (e.g., polycrystalline aggregate) into a set of sub-continua (grains). The overall properties of the polycrystalline aggregate are therefore determined by the number of grains in the aggregate and properties of randomly shaped and oriented grains. The random grain structure is modeled with Voronoi tessellation and random orientations of crystal lattices are assumed. The elastic behavior of monocrystal grains is assumed to be anisotropic. Crystal plasticity is used to describe plastic response of monocrystal grains. Finite element method is used to obtain numerical solutions of strain and stress fields. The analysis is limited to two-dimensional models.(author)
Implementation of a Novel Educational Modeling Approach for Cloud Computing
Directory of Open Access Journals (Sweden)
Sara Ouahabi
2014-12-01
Full Text Available The Cloud model is cost-effective because customers pay for their actual usage without upfront costs, and scalable because it can be used more or less depending on the customers’ needs. Due to its advantages, Cloud has been increasingly adopted in many areas, such as banking, e-commerce, retail industry, and academy. For education, cloud is used to manage the large volume of educational resources produced across many universities in the cloud. Keep interoperability between content in an inter-university Cloud is not always easy. Diffusion of pedagogical contents on the Cloud by different E-Learning institutions leads to heterogeneous content which influence the quality of teaching offered by university to teachers and learners. From this reason, comes the idea of using IMS-LD coupled with metadata in the cloud. This paper presents the implementation of our previous educational modeling by combining an application in J2EE with Reload editor that consists of modeling heterogeneous content in the cloud. The new approach that we followed focuses on keeping interoperability between Educational Cloud content for teachers and learners and facilitates the task of identification, reuse, sharing, adapting teaching and learning resources in the Cloud.
MASKED AREAS IN SHEAR PEAK STATISTICS: A FORWARD MODELING APPROACH
International Nuclear Information System (INIS)
Bard, D.; Kratochvil, J. M.; Dawson, W.
2016-01-01
The statistics of shear peaks have been shown to provide valuable cosmological information beyond the power spectrum, and will be an important constraint of models of cosmology in forthcoming astronomical surveys. Surveys include masked areas due to bright stars, bad pixels etc., which must be accounted for in producing constraints on cosmology from shear maps. We advocate a forward-modeling approach, where the impacts of masking and other survey artifacts are accounted for in the theoretical prediction of cosmological parameters, rather than correcting survey data to remove them. We use masks based on the Deep Lens Survey, and explore the impact of up to 37% of the survey area being masked on LSST and DES-scale surveys. By reconstructing maps of aperture mass the masking effect is smoothed out, resulting in up to 14% smaller statistical uncertainties compared to simply reducing the survey area by the masked area. We show that, even in the presence of large survey masks, the bias in cosmological parameter estimation produced in the forward-modeling process is ≈1%, dominated by bias caused by limited simulation volume. We also explore how this potential bias scales with survey area and evaluate how much small survey areas are impacted by the differences in cosmological structure in the data and simulated volumes, due to cosmic variance
A Dynamic Approach to Modeling Dependence Between Human Failure Events
Energy Technology Data Exchange (ETDEWEB)
Boring, Ronald Laurids [Idaho National Laboratory
2015-09-01
In practice, most HRA methods use direct dependence from THERP—the notion that error be- gets error, and one human failure event (HFE) may increase the likelihood of subsequent HFEs. In this paper, we approach dependence from a simulation perspective in which the effects of human errors are dynamically modeled. There are three key concepts that play into this modeling: (1) Errors are driven by performance shaping factors (PSFs). In this context, the error propagation is not a result of the presence of an HFE yielding overall increases in subsequent HFEs. Rather, it is shared PSFs that cause dependence. (2) PSFs have qualities of lag and latency. These two qualities are not currently considered in HRA methods that use PSFs. Yet, to model the effects of PSFs, it is not simply a matter of identifying the discrete effects of a particular PSF on performance. The effects of PSFs must be considered temporally, as the PSFs will have a range of effects across the event sequence. (3) Finally, there is the concept of error spilling. When PSFs are activated, they not only have temporal effects but also lateral effects on other PSFs, leading to emergent errors. This paper presents the framework for tying together these dynamic dependence concepts.
A Bayesian approach to the modelling of α Cen A
Bazot, M.; Bourguignon, S.; Christensen-Dalsgaard, J.
2012-12-01
Determining the physical characteristics of a star is an inverse problem consisting of estimating the parameters of models for the stellar structure and evolution, and knowing certain observable quantities. We use a Bayesian approach to solve this problem for α Cen A, which allows us to incorporate prior information on the parameters to be estimated, in order to better constrain the problem. Our strategy is based on the use of a Markov chain Monte Carlo (MCMC) algorithm to estimate the posterior probability densities of the stellar parameters: mass, age, initial chemical composition, etc. We use the stellar evolutionary code ASTEC to model the star. To constrain this model both seismic and non-seismic observations were considered. Several different strategies were tested to fit these values, using either two free parameters or five free parameters in ASTEC. We are thus able to show evidence that MCMC methods become efficient with respect to more classical grid-based strategies when the number of parameters increases. The results of our MCMC algorithm allow us to derive estimates for the stellar parameters and robust uncertainties thanks to the statistical analysis of the posterior probability densities. We are also able to compute odds for the presence of a convective core in α Cen A. When using core-sensitive seismic observational constraints, these can rise above ˜40 per cent. The comparison of results to previous studies also indicates that these seismic constraints are of critical importance for our knowledge of the structure of this star.
Parameter Estimation of Structural Equation Modeling Using Bayesian Approach
Directory of Open Access Journals (Sweden)
Dewi Kurnia Sari
2016-05-01
Full Text Available Leadership is a process of influencing, directing or giving an example of employees in order to achieve the objectives of the organization and is a key element in the effectiveness of the organization. In addition to the style of leadership, the success of an organization or company in achieving its objectives can also be influenced by the commitment of the organization. Where organizational commitment is a commitment created by each individual for the betterment of the organization. The purpose of this research is to obtain a model of leadership style and organizational commitment to job satisfaction and employee performance, and determine the factors that influence job satisfaction and employee performance using SEM with Bayesian approach. This research was conducted at Statistics FNI employees in Malang, with 15 people. The result of this study showed that the measurement model, all significant indicators measure each latent variable. Meanwhile in the structural model, it was concluded there are a significant difference between the variables of Leadership Style and Organizational Commitment toward Job Satisfaction directly as well as a significant difference between Job Satisfaction on Employee Performance. As for the influence of Leadership Style and variable Organizational Commitment on Employee Performance directly declared insignificant.
Hybrid empirical--theoretical approach to modeling uranium adsorption
International Nuclear Information System (INIS)
Hull, Larry C.; Grossman, Christopher; Fjeld, Robert A.; Coates, John T.; Elzerman, Alan W.
2004-01-01
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 f parameter is correlated to sediment surface area (r 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
Experimental oligopolies modeling: A dynamic approach based on heterogeneous behaviors
Cerboni Baiardi, Lorenzo; Naimzada, Ahmad K.
2018-05-01
In the rank of behavioral rules, imitation-based heuristics has received special attention in economics (see [14] and [12]). In particular, imitative behavior is considered in order to understand the evidences arising in experimental oligopolies which reveal that the Cournot-Nash equilibrium does not emerge as unique outcome and show that an important component of the production at the competitive level is observed (see e.g.[1,3,9] or [7,10]). By considering the pioneering groundbreaking approach of [2], we build a dynamical model of linear oligopolies where heterogeneous decision mechanisms of players are made explicit. In particular, we consider two different types of quantity setting players characterized by different decision mechanisms that coexist and operate simultaneously: agents that adaptively adjust their choices towards the direction that increases their profit are embedded with imitator agents. The latter ones use a particular form of proportional imitation rule that considers the awareness about the presence of strategic interactions. It is noteworthy that the Cournot-Nash outcome is a stationary state of our models. Our thesis is that the chaotic dynamics arousing from a dynamical model, where heterogeneous players are considered, are capable to qualitatively reproduce the outcomes of experimental oligopolies.
Mobile phone use while driving: a hybrid modeling approach.
Márquez, Luis; Cantillo, Víctor; Arellana, Julián
2015-05-01
The analysis of the effects that mobile phone use produces while driving is a topic of great interest for the scientific community. There is consensus that using a mobile phone while driving increases the risk of exposure to traffic accidents. The purpose of this research is to evaluate the drivers' behavior when they decide whether or not to use a mobile phone while driving. For that, a hybrid modeling approach that integrates a choice model with the latent variable "risk perception" was used. It was found that workers and individuals with the highest education level are more prone to use a mobile phone while driving than others. Also, "risk perception" is higher among individuals who have been previously fined and people who have been in an accident or almost been in an accident. It was also found that the tendency to use mobile phones while driving increases when the traffic speed reduces, but it decreases when the fine increases. Even though the urgency of the phone call is the most important explanatory variable in the choice model, the cost of the fine is an important attribute in order to control mobile phone use while driving. Copyright © 2015 Elsevier Ltd. All rights reserved.
Sulfur Deactivation of NOx Storage Catalysts: A Multiscale Modeling Approach
Directory of Open Access Journals (Sweden)
Rankovic N.
2013-09-01
Full Text Available Lean NOx Trap (LNT catalysts, a promising solution for reducing the noxious nitrogen oxide emissions from the lean burn and Diesel engines, are technologically limited by the presence of sulfur in the exhaust gas stream. Sulfur stemming from both fuels and lubricating oils is oxidized during the combustion event and mainly exists as SOx (SO2 and SO3 in the exhaust. Sulfur oxides interact strongly with the NOx trapping material of a LNT to form thermodynamically favored sulfate species, consequently leading to the blockage of NOx sorption sites and altering the catalyst operation. Molecular and kinetic modeling represent a valuable tool for predicting system behavior and evaluating catalytic performances. The present paper demonstrates how fundamental ab initio calculations can be used as a valuable source for designing kinetic models developed in the IFP Exhaust library, intended for vehicle simulations. The concrete example we chose to illustrate our approach was SO3 adsorption on the model NOx storage material, BaO. SO3 adsorption was described for various sites (terraces, surface steps and kinks and bulk for a closer description of a real storage material. Additional rate and sensitivity analyses provided a deeper understanding of the poisoning phenomena.
A Simple Approach to Account for Climate Model Interdependence in Multi-Model Ensembles
Herger, N.; Abramowitz, G.; Angelil, O. M.; Knutti, R.; Sanderson, B.
2016-12-01
Multi-model ensembles are an indispensable tool for future climate projection and its uncertainty quantification. Ensembles containing multiple climate models generally have increased skill, consistency and reliability. Due to the lack of agreed-on alternatives, most scientists use the equally-weighted multi-model mean as they subscribe to model democracy ("one model, one vote").Different research groups are known to share sections of code, parameterizations in their model, literature, or even whole model components. Therefore, individual model runs do not represent truly independent estimates. Ignoring this dependence structure might lead to a false model consensus, wrong estimation of uncertainty and effective number of independent models.Here, we present a way to partially address this problem by selecting a subset of CMIP5 model runs so that its climatological mean minimizes the RMSE compared to a given observation product. Due to the cancelling out of errors, regional biases in the ensemble mean are reduced significantly.Using a model-as-truth experiment we demonstrate that those regional biases persist into the future and we are not fitting noise, thus providing improved observationally-constrained projections of the 21st century. The optimally selected ensemble shows significantly higher global mean surface temperature projections than the original ensemble, where all the model runs are considered. Moreover, the spread is decreased well beyond that expected from the decreased ensemble size.Several previous studies have recommended an ensemble selection approach based on performance ranking of the model runs. Here, we show that this approach can perform even worse than randomly selecting ensemble members and can thus be harmful. We suggest that accounting for interdependence in the ensemble selection process is a necessary step for robust projections for use in impact assessments, adaptation and mitigation of climate change.
Assessing testamentary and decision-making capacity: Approaches and models.
Purser, Kelly; Rosenfeld, Tuly
2015-09-01
The need for better and more accurate assessments of testamentary and decision-making capacity grows as Australian society ages and incidences of mentally disabling conditions increase. Capacity is a legal determination, but one on which medical opinion is increasingly being sought. The difficulties inherent within capacity assessments are exacerbated by the ad hoc approaches adopted by legal and medical professionals based on individual knowledge and skill, as well as the numerous assessment paradigms that exist. This can negatively affect the quality of assessments, and results in confusion as to the best way to assess capacity. This article begins by assessing the nature of capacity. The most common general assessment models used in Australia are then discussed, as are the practical challenges associated with capacity assessment. The article concludes by suggesting a way forward to satisfactorily assess legal capacity given the significant ramifications of getting it wrong.
Benchmarking of computer codes and approaches for modeling exposure scenarios
International Nuclear Information System (INIS)
Seitz, R.R.; Rittmann, P.D.; Wood, M.I.; Cook, J.R.
1994-08-01
The US Department of Energy Headquarters established a performance assessment task team (PATT) to integrate the activities of DOE sites that are preparing performance assessments for the disposal of newly generated low-level waste. The PATT chartered a subteam with the task of comparing computer codes and exposure scenarios used for dose calculations in performance assessments. This report documents the efforts of the subteam. Computer codes considered in the comparison include GENII, PATHRAE-EPA, MICROSHIELD, and ISOSHLD. Calculations were also conducted using spreadsheets to provide a comparison at the most fundamental level. Calculations and modeling approaches are compared for unit radionuclide concentrations in water and soil for the ingestion, inhalation, and external dose pathways. Over 30 tables comparing inputs and results are provided
A Dynamic Linear Modeling Approach to Public Policy Change
DEFF Research Database (Denmark)
Loftis, Matthew; Mortensen, Peter Bjerre
2017-01-01
Theories of public policy change, despite their differences, converge on one point of strong agreement. The relationship between policy and its causes can and does change over time. This consensus yields numerous empirical implications, but our standard analytical tools are inadequate for testing...... them. As a result, the dynamic and transformative relationships predicted by policy theories have been left largely unexplored in time-series analysis of public policy. This paper introduces dynamic linear modeling (DLM) as a useful statistical tool for exploring time-varying relationships in public...... policy. The paper offers a detailed exposition of the DLM approach and illustrates its usefulness with a time series analysis of U.S. defense policy from 1957-2010. The results point the way for a new attention to dynamics in the policy process and the paper concludes with a discussion of how...
Advanced Computational Modeling Approaches for Shock Response Prediction
Derkevorkian, Armen; Kolaini, Ali R.; Peterson, Lee
2015-01-01
Motivation: (1) The activation of pyroshock devices such as explosives, separation nuts, pin-pullers, etc. produces high frequency transient structural response, typically from few tens of Hz to several hundreds of kHz. (2) Lack of reliable analytical tools makes the prediction of appropriate design and qualification test levels a challenge. (3) In the past few decades, several attempts have been made to develop methodologies that predict the structural responses to shock environments. (4) Currently, there is no validated approach that is viable to predict shock environments overt the full frequency range (i.e., 100 Hz to 10 kHz). Scope: (1) Model, analyze, and interpret space structural systems with complex interfaces and discontinuities, subjected to shock loads. (2) Assess the viability of a suite of numerical tools to simulate transient, non-linear solid mechanics and structural dynamics problems, such as shock wave propagation.
Systems approaches to computational modeling of the oral microbiome
Directory of Open Access Journals (Sweden)
Dimiter V. Dimitrov
2013-07-01
Full Text Available Current microbiome research has generated tremendous amounts of data providing snapshots of molecular activity in a variety of organisms, environments, and cell types. However, turning this knowledge into whole system level of understanding on pathways and processes has proven to be a challenging task. In this review we highlight the applicability of bioinformatics and visualization techniques to large collections of data in order to better understand the information that contains related diet – oral microbiome – host mucosal transcriptome interactions. In particular we focus on systems biology of Porphyromonas gingivalis in the context of high throughput computational methods tightly integrated with translational systems medicine. Those approaches have applications for both basic research, where we can direct specific laboratory experiments in model organisms and cell cultures, to human disease, where we can validate new mechanisms and biomarkers for prevention and treatment of chronic disorders
Informing Public Perceptions About Climate Change: A 'Mental Models' Approach.
Wong-Parodi, Gabrielle; Bruine de Bruin, Wändi
2017-10-01
As the specter of climate change looms on the horizon, people will face complex decisions about whether to support climate change policies and how to cope with climate change impacts on their lives. Without some grasp of the relevant science, they may find it hard to make informed decisions. Climate experts therefore face the ethical need to effectively communicate to non-expert audiences. Unfortunately, climate experts may inadvertently violate the maxims of effective communication, which require sharing communications that are truthful, brief, relevant, clear, and tested for effectiveness. Here, we discuss the 'mental models' approach towards developing communications, which aims to help experts to meet the maxims of effective communications, and to better inform the judgments and decisions of non-expert audiences.
Agents, Bayes, and Climatic Risks - a modular modelling approach
Directory of Open Access Journals (Sweden)
A. Haas
2005-01-01
Full Text Available When insurance firms, energy companies, governments, NGOs, and other agents strive to manage climatic risks, it is by no way clear what the aggregate outcome should and will be. As a framework for investigating this subject, we present the LAGOM model family. It is based on modules depicting learning social agents. For managing climate risks, our agents use second order probabilities and update them by means of a Bayesian mechanism while differing in priors and risk aversion. The interactions between these modules and the aggregate outcomes of their actions are implemented using further modules. The software system is implemented as a series of parallel processes using the CIAMn approach. It is possible to couple modules irrespective of the language they are written in, the operating system under which they are run, and the physical location of the machine.
Agents, Bayes, and Climatic Risks - a modular modelling approach
Haas, A.; Jaeger, C.
2005-08-01
When insurance firms, energy companies, governments, NGOs, and other agents strive to manage climatic risks, it is by no way clear what the aggregate outcome should and will be. As a framework for investigating this subject, we present the LAGOM model family. It is based on modules depicting learning social agents. For managing climate risks, our agents use second order probabilities and update them by means of a Bayesian mechanism while differing in priors and risk aversion. The interactions between these modules and the aggregate outcomes of their actions are implemented using further modules. The software system is implemented as a series of parallel processes using the CIAMn approach. It is possible to couple modules irrespective of the language they are written in, the operating system under which they are run, and the physical location of the machine.
A path integral approach to the Hodgkin-Huxley model
Baravalle, Roman; Rosso, Osvaldo A.; Montani, Fernando
2017-11-01
To understand how single neurons process sensory information, it is necessary to develop suitable stochastic models to describe the response variability of the recorded spike trains. Spikes in a given neuron are produced by the synergistic action of sodium and potassium of the voltage-dependent channels that open or close the gates. Hodgkin and Huxley (HH) equations describe the ionic mechanisms underlying the initiation and propagation of action potentials, through a set of nonlinear ordinary differential equations that approximate the electrical characteristics of the excitable cell. Path integral provides an adequate approach to compute quantities such as transition probabilities, and any stochastic system can be expressed in terms of this methodology. We use the technique of path integrals to determine the analytical solution driven by a non-Gaussian colored noise when considering the HH equations as a stochastic system. The different neuronal dynamics are investigated by estimating the path integral solutions driven by a non-Gaussian colored noise q. More specifically we take into account the correlational structures of the complex neuronal signals not just by estimating the transition probability associated to the Gaussian approach of the stochastic HH equations, but instead considering much more subtle processes accounting for the non-Gaussian noise that could be induced by the surrounding neural network and by feedforward correlations. This allows us to investigate the underlying dynamics of the neural system when different scenarios of noise correlations are considered.
A Gaussian graphical model approach to climate networks
Energy Technology Data Exchange (ETDEWEB)
Zerenner, Tanja, E-mail: tanjaz@uni-bonn.de [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Friederichs, Petra; Hense, Andreas [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany); Lehnertz, Klaus [Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn (Germany); Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany)
2014-06-15
Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately.
A Unified Approach to Model-Based Planning and Execution
Muscettola, Nicola; Dorais, Gregory A.; Fry, Chuck; Levinson, Richard; Plaunt, Christian; Norvig, Peter (Technical Monitor)
2000-01-01
Writing autonomous software is complex, requiring the coordination of functionally and technologically diverse software modules. System and mission engineers must rely on specialists familiar with the different software modules to translate requirements into application software. Also, each module often encodes the same requirement in different forms. The results are high costs and reduced reliability due to the difficulty of tracking discrepancies in these encodings. In this paper we describe a unified approach to planning and execution that we believe provides a unified representational and computational framework for an autonomous agent. We identify the four main components whose interplay provides the basis for the agent's autonomous behavior: the domain model, the plan database, the plan running module, and the planner modules. This representational and problem solving approach can be applied at all levels of the architecture of a complex agent, such as Remote Agent. In the rest of the paper we briefly describe the Remote Agent architecture. The new agent architecture proposed here aims at achieving the full Remote Agent functionality. We then give the fundamental ideas behind the new agent architecture and point out some implication of the structure of the architecture, mainly in the area of reactivity and interaction between reactive and deliberative decision making. We conclude with related work and current status.
A Gaussian graphical model approach to climate networks
International Nuclear Information System (INIS)
Zerenner, Tanja; Friederichs, Petra; Hense, Andreas; Lehnertz, Klaus
2014-01-01
Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately
Using graph approach for managing connectivity in integrative landscape modelling
Rabotin, Michael; Fabre, Jean-Christophe; Libres, Aline; Lagacherie, Philippe; Crevoisier, David; Moussa, Roger
2013-04-01
In cultivated landscapes, a lot of landscape elements such as field boundaries, ditches or banks strongly impact water flows, mass and energy fluxes. At the watershed scale, these impacts are strongly conditionned by the connectivity of these landscape elements. An accurate representation of these elements and of their complex spatial arrangements is therefore of great importance for modelling and predicting these impacts.We developped in the framework of the OpenFLUID platform (Software Environment for Modelling Fluxes in Landscapes) a digital landscape representation that takes into account the spatial variabilities and connectivities of diverse landscape elements through the application of the graph theory concepts. The proposed landscape representation consider spatial units connected together to represent the flux exchanges or any other information exchanges. Each spatial unit of the landscape is represented as a node of a graph and relations between units as graph connections. The connections are of two types - parent-child connection and up/downstream connection - which allows OpenFLUID to handle hierarchical graphs. Connections can also carry informations and graph evolution during simulation is possible (connections or elements modifications). This graph approach allows a better genericity on landscape representation, a management of complex connections and facilitate development of new landscape representation algorithms. Graph management is fully operational in OpenFLUID for developers or modelers ; and several graph tools are available such as graph traversal algorithms or graph displays. Graph representation can be managed i) manually by the user (for example in simple catchments) through XML-based files in easily editable and readable format or ii) by using methods of the OpenFLUID-landr library which is an OpenFLUID library relying on common open-source spatial libraries (ogr vector, geos topologic vector and gdal raster libraries). Open
Validation of an employee satisfaction model: A structural equation model approach
Ophillia Ledimo; Nico Martins
2015-01-01
The purpose of this study was to validate an employee satisfaction model and to determine the relationships between the different dimensions of the concept, using the structural equation modelling approach (SEM). A cross-sectional quantitative survey design was used to collect data from a random sample of (n=759) permanent employees of a parastatal organisation. Data was collected using the Employee Satisfaction Survey (ESS) to measure employee satisfaction dimensions. Following the steps of ...
Personalization of models with many model parameters: an efficient sensitivity analysis approach.
Donders, W P; Huberts, W; van de Vosse, F N; Delhaas, T
2015-10-01
Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific applications of models that enhance diagnosis or aid decision-making. Variance-based sensitivity analysis methods, which apportion each fraction of the output uncertainty (variance) to the effects of individual input parameters or their interactions, are considered the gold standard. The variance portions are called the Sobol sensitivity indices and can be estimated by a Monte Carlo (MC) approach (e.g., Saltelli's method [1]) or by employing a metamodel (e.g., the (generalized) polynomial chaos expansion (gPCE) [2, 3]). All these methods require a large number of model evaluations when estimating the Sobol sensitivity indices for models with many parameters [4]. To reduce the computational cost, we introduce a two-step approach. In the first step, a subset of important parameters is identified for each output of interest using the screening method of Morris [5]. In the second step, a quantitative variance-based sensitivity analysis is performed using gPCE. Efficient sampling strategies are introduced to minimize the number of model runs required to obtain the sensitivity indices for models considering multiple outputs. The approach is tested using a model that was developed for predicting post-operative flows after creation of a vascular access for renal failure patients. We compare the sensitivity indices obtained with the novel two-step approach with those obtained from a reference analysis that applies Saltelli's MC method. The two-step approach was found to yield accurate estimates of the sensitivity indices at two orders of magnitude lower computational cost. Copyright © 2015 John Wiley & Sons, Ltd.
Numerical modeling of underground openings behavior with a viscoplastic approach
International Nuclear Information System (INIS)
Kleine, A.
2007-01-01
Nature is complex and must be approached in total modesty by engineers seeking to predict the behavior of underground openings. The engineering of industrial projects in underground situations, with high economic and social stakes (Alpine mountain crossings, nuclear waste repository), mean striving to gain better understanding of the behavioral mechanisms of the openings to be designed. This improvement necessarily involves better physical representativeness of macroscopic mechanisms and the provision of prediction tools suited to the expectations and needs of the engineers. The calculation tools developed in this work is in step with this concern for satisfying industrial needs and developing knowledge related to the rheology of geo-materials. These developments led to the proposing of a mechanical constitutive model, suited to lightly fissured rocks, comparable to continuous media, while integrating more particularly the effect of time. Thread of this study, the problematics ensued from the subject of the thesis is precisely about the rock mass delayed behavior in numerical modeling and its consequences on underground openings design. Based on physical concepts of reference, defined in several scales (macro/meso/micro), the developed constitutive model is translated in a mathematical formalism in order to be numerically implemented. Numerical applications presented as illustrations fall mainly within the framework of nuclear waste repository problems. They concern two very different configurations of underground openings: the AECL's underground canadian laboratory, excavated in the Lac du Bonnet granite, and the GMR gallery of Bure's laboratory (Meuse/Haute-Marne), dug in argillaceous rock. In this two cases, this constitutive model use highlights the gains to be obtained from allowing for delayed behavior regarding the accuracy of numerical tunnel behavior predictions in the short, medium and long terms. (author)
Healthcare waste management: an interpretive structural modeling approach.
Thakur, Vikas; Anbanandam, Ramesh
2016-06-13
Purpose - The World Health Organization identified infectious healthcare waste as a threat to the environment and human health. India's current medical waste management system has limitations, which lead to ineffective and inefficient waste handling practices. Hence, the purpose of this paper is to: first, identify the important barriers that hinder India's healthcare waste management (HCWM) systems; second, classify operational, tactical and strategical issues to discuss the managerial implications at different management levels; and third, define all barriers into four quadrants depending upon their driving and dependence power. Design/methodology/approach - India's HCWM system barriers were identified through the literature, field surveys and brainstorming sessions. Interrelationships among all the barriers were analyzed using interpretive structural modeling (ISM). Fuzzy-Matrice d'Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis was used to classify HCWM barriers into four groups. Findings - In total, 25 HCWM system barriers were identified and placed in 12 different ISM model hierarchy levels. Fuzzy-MICMAC analysis placed eight barriers in the second quadrant, five in third and 12 in fourth quadrant to define their relative ISM model importance. Research limitations/implications - The study's main limitation is that all the barriers were identified through a field survey and barnstorming sessions conducted only in Uttarakhand, Northern State, India. The problems in implementing HCWM practices may differ with the region, hence, the current study needs to be replicated in different Indian states to define the waste disposal strategies for hospitals. Practical implications - The model will help hospital managers and Pollution Control Boards, to plan their resources accordingly and make policies, targeting key performance areas. Originality/value - The study is the first attempt to identify India's HCWM system barriers and prioritize
A Review of Accident Modelling Approaches for Complex Critical Sociotechnical Systems
National Research Council Canada - National Science Library
Qureshi, Zahid H
2008-01-01
.... This report provides a review of key traditional accident modelling approaches and their limitations, and describes new system-theoretic approaches to the modelling and analysis of accidents in safety-critical systems...
From scores to face templates: a model-based approach.
Mohanty, Pranab; Sarkar, Sudeep; Kasturi, Rangachar
2007-12-01
Regeneration of templates from match scores has security and privacy implications related to any biometric authentication system. We propose a novel paradigm to reconstruct face templates from match scores using a linear approach. It proceeds by first modeling the behavior of the given face recognition algorithm by an affine transformation. The goal of the modeling is to approximate the distances computed by a face recognition algorithm between two faces by distances between points, representing these faces, in an affine space. Given this space, templates from an independent image set (break-in) are matched only once with the enrolled template of the targeted subject and match scores are recorded. These scores are then used to embed the targeted subject in the approximating affine (non-orthogonal) space. Given the coordinates of the targeted subject in the affine space, the original template of the targeted subject is reconstructed using the inverse of the affine transformation. We demonstrate our ideas using three, fundamentally different, face recognition algorithms: Principal Component Analysis (PCA) with Mahalanobis cosine distance measure, Bayesian intra-extrapersonal classifier (BIC), and a feature-based commercial algorithm. To demonstrate the independence of the break-in set with the gallery set, we select face templates from two different databases: Face Recognition Grand Challenge (FRGC) and Facial Recognition Technology (FERET) Database (FERET). With an operational point set at 1 percent False Acceptance Rate (FAR) and 99 percent True Acceptance Rate (TAR) for 1,196 enrollments (FERET gallery), we show that at most 600 attempts (score computations) are required to achieve a 73 percent chance of breaking in as a randomly chosen target subject for the commercial face recognition system. With similar operational set up, we achieve a 72 percent and 100 percent chance of breaking in for the Bayesian and PCA based face recognition systems, respectively. With
Zhu, Xiaoshu
2013-01-01
The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…
Bottom friction. A practical approach to modelling coastal oceanography
Bolanos, Rodolfo; Jensen, Palle; Kofoed-Hansen, Henrik; Tornsfeldt Sørensen, Jacob
2017-04-01
Coastal processes imply the interaction of the atmosphere, the sea, the coastline and the bottom. The spatial gradients in this area are normally large, induced by orographic and bathymetric features. Although nowadays it is possible to obtain high-resolution bathymetry, the details of the seabed, e.g. sediment type, presence of biological material and living organisms are not available. Additionally, these properties as well as bathymetry can also be highly dynamic. These bottom characteristics are very important to describe the boundary layer of currents and waves and control to a large degree the dissipation of flows. The bottom friction is thus typically a calibration parameter in numerical modelling of coastal processes. In this work, we assess this process and put it into context of other physical processes uncertainties influencing wind-waves and currents in the coastal areas. A case study in the North Sea is used, particularly the west coast of Denmark, where water depth of less than 30 m cover a wide fringe along the coast, where several offshore wind farm developments are being carried out. We use the hydrodynamic model MIKE 21 HD and the spectral wave model MIKE 21 SW to simulate atmosphere and tidal induced flows and the wind wave generation and propagation. Both models represent state of the art and have been developed for flexible meshes, ideal for coastal oceanography as they can better represent coastlines and allow a variable spatial resolution within the domain. Sensitivity tests to bottom friction formulations are carried out into context of other processes (e.g. model forcing uncertainties, wind and wave interactions, wind drag coefficient). Additionally, a map of varying bottom properties is generated based on a literature survey to explore the impact of the spatial variability. Assessment of different approaches is made in order to establish a best practice regarding bottom friction and coastal oceanographic modelling. Its contribution is also
Forecasting wind-driven wildfires using an inverse modelling approach
Directory of Open Access Journals (Sweden)
O. Rios
2014-06-01
Full Text Available A technology able to rapidly forecast wildfire dynamics would lead to a paradigm shift in the response to emergencies, providing the Fire Service with essential information about the ongoing fire. This paper presents and explores a novel methodology to forecast wildfire dynamics in wind-driven conditions, using real-time data assimilation and inverse modelling. The forecasting algorithm combines Rothermel's rate of spread theory with a perimeter expansion model based on Huygens principle and solves the optimisation problem with a tangent linear approach and forward automatic differentiation. Its potential is investigated using synthetic data and evaluated in different wildfire scenarios. The results show the capacity of the method to quickly predict the location of the fire front with a positive lead time (ahead of the event in the order of 10 min for a spatial scale of 100 m. The greatest strengths of our method are lightness, speed and flexibility. We specifically tailor the forecast to be efficient and computationally cheap so it can be used in mobile systems for field deployment and operativeness. Thus, we put emphasis on producing a positive lead time and the means to maximise it.
A Systematic Approach to Modelling Change Processes in Construction Projects
Directory of Open Access Journals (Sweden)
Ibrahim Motawa
2012-11-01
Full Text Available Modelling change processes within construction projects isessential to implement changes efficiently. Incomplete informationon the project variables at the early stages of projects leads toinadequate knowledge of future states and imprecision arisingfrom ambiguity in project parameters. This lack of knowledge isconsidered among the main source of changes in construction.Change identification and evaluation, in addition to predictingits impacts on project parameters, can help in minimising thedisruptive effects of changes. This paper presents a systematicapproach to modelling change process within construction projectsthat helps improve change identification and evaluation. Theapproach represents the key decisions required to implementchanges. The requirements of an effective change processare presented first. The variables defined for efficient changeassessment and diagnosis are then presented. Assessmentof construction changes requires an analysis for the projectcharacteristics that lead to change and also analysis of therelationship between the change causes and effects. The paperconcludes that, at the early stages of a project, projects with a highlikelihood of change occurrence should have a control mechanismover the project characteristics that have high influence on theproject. It also concludes, for the relationship between changecauses and effects, the multiple causes of change should bemodelled in a way to enable evaluating the change effects moreaccurately. The proposed approach is the framework for tacklingsuch conclusions and can be used for evaluating change casesdepending on the available information at the early stages ofconstruction projects.
Dynamical system approach to running Λ cosmological models
International Nuclear Information System (INIS)
Stachowski, Aleksander; Szydlowski, Marek
2016-01-01
We study the dynamics of cosmological models with a time dependent cosmological term. We consider five classes of models; two with the non-covariant parametrization of the cosmological term Λ: Λ(H)CDM cosmologies, Λ(a)CDM cosmologies, and three with the covariant parametrization of Λ: Λ(R)CDM cosmologies, where R(t) is the Ricci scalar, Λ(φ)-cosmologies with diffusion, Λ(X)-cosmologies, where X = (1)/(2)g"α"β∇_α∇_βφ is a kinetic part of the density of the scalar field. We also consider the case of an emergent Λ(a) relation obtained from the behaviour of trajectories in a neighbourhood of an invariant submanifold. In the study of the dynamics we used dynamical system methods for investigating how an evolutionary scenario can depend on the choice of special initial conditions. We show that the methods of dynamical systems allow one to investigate all admissible solutions of a running Λ cosmology for all initial conditions. We interpret Alcaniz and Lima's approach as a scaling cosmology. We formulate the idea of an emergent cosmological term derived directly from an approximation of the exact dynamics. We show that some non-covariant parametrization of the cosmological term like Λ(a), Λ(H) gives rise to the non-physical behaviour of trajectories in the phase space. This behaviour disappears if the term Λ(a) is emergent from the covariant parametrization. (orig.)
Do recommender systems benefit users? a modeling approach
Yeung, Chi Ho
2016-04-01
Recommender systems are present in many web applications to guide purchase choices. They increase sales and benefit sellers, but whether they benefit customers by providing relevant products remains less explored. While in many cases the recommended products are relevant to users, in other cases customers may be tempted to purchase the products only because they are recommended. Here we introduce a model to examine the benefit of recommender systems for users, and find that recommendations from the system can be equivalent to random draws if one always follows the recommendations and seldom purchases according to his or her own preference. Nevertheless, with sufficient information about user preferences, recommendations become accurate and an abrupt transition to this accurate regime is observed for some of the studied algorithms. On the other hand, we find that high estimated accuracy indicated by common accuracy metrics is not necessarily equivalent to high real accuracy in matching users with products. This disagreement between estimated and real accuracy serves as an alarm for operators and researchers who evaluate recommender systems merely with accuracy metrics. We tested our model with a real dataset and observed similar behaviors. Finally, a recommendation approach with improved accuracy is suggested. These results imply that recommender systems can benefit users, but the more frequently a user purchases the recommended products, the less relevant the recommended products are in matching user taste.
Driving profile modeling and recognition based on soft computing approach.
Wahab, Abdul; Quek, Chai; Tan, Chin Keong; Takeda, Kazuya
2009-04-01
Advancements in biometrics-based authentication have led to its increasing prominence and are being incorporated into everyday tasks. Existing vehicle security systems rely only on alarms or smart card as forms of protection. A biometric driver recognition system utilizing driving behaviors is a highly novel and personalized approach and could be incorporated into existing vehicle security system to form a multimodal identification system and offer a greater degree of multilevel protection. In this paper, detailed studies have been conducted to model individual driving behavior in order to identify features that may be efficiently and effectively used to profile each driver. Feature extraction techniques based on Gaussian mixture models (GMMs) are proposed and implemented. Features extracted from the accelerator and brake pedal pressure were then used as inputs to a fuzzy neural network (FNN) system to ascertain the identity of the driver. Two fuzzy neural networks, namely, the evolving fuzzy neural network (EFuNN) and the adaptive network-based fuzzy inference system (ANFIS), are used to demonstrate the viability of the two proposed feature extraction techniques. The performances were compared against an artificial neural network (NN) implementation using the multilayer perceptron (MLP) network and a statistical method based on the GMM. Extensive testing was conducted and the results show great potential in the use of the FNN for real-time driver identification and verification. In addition, the profiling of driver behaviors has numerous other potential applications for use by law enforcement and companies dealing with buses and truck drivers.
Stability of rotor systems: A complex modelling approach
DEFF Research Database (Denmark)
Kliem, Wolfhard; Pommer, Christian; Stoustrup, Jakob
1998-01-01
The dynamics of a large class of rotor systems can be modelled by a linearized complex matrix differential equation of second order, Mz + (D + iG)(z) over dot + (K + iN)z = 0, where the system matrices M, D, G, K and N are real symmetric. Moreover M and K are assumed to be positive definite and D...... approach applying bounds of appropriate Rayleigh quotients. The rotor systems tested are: a simple Laval rotor, a Laval rotor with additional elasticity and damping in the bearings, and a number of rotor systems with complex symmetric 4 x 4 randomly generated matrices.......The dynamics of a large class of rotor systems can be modelled by a linearized complex matrix differential equation of second order, Mz + (D + iG)(z) over dot + (K + iN)z = 0, where the system matrices M, D, G, K and N are real symmetric. Moreover M and K are assumed to be positive definite and D...
Maximum likelihood approach for several stochastic volatility models
International Nuclear Information System (INIS)
Camprodon, Jordi; Perelló, Josep
2012-01-01
Volatility measures the amplitude of price fluctuations. Despite it being one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method which assumes that price and volatility follow a two-dimensional diffusion process where volatility is the stochastic diffusion coefficient of the log-price dynamics. We apply this method to the simplest versions of the expOU, the OU and the Heston stochastic volatility models and we study their performance in terms of the log-price probability, the volatility probability, and its Mean First-Passage Time. The approach has some predictive power on the future returns amplitude by only knowing the current volatility. The assumed models do not consider long-range volatility autocorrelation and the asymmetric return-volatility cross-correlation but the method still yields very naturally these two important stylized facts. We apply the method to different market indices and with a good performance in all cases. (paper)
Evaluation of approaches focused on modelling of organic carbon stocks using the RothC model
Koco, Štefan; Skalský, Rastislav; Makovníková, Jarmila; Tarasovičová, Zuzana; Barančíková, Gabriela
2014-05-01
The aim of current efforts in the European area is the protection of soil organic matter, which is included in all relevant documents related to the protection of soil. The use of modelling of organic carbon stocks for anticipated climate change, respectively for land management can significantly help in short and long-term forecasting of the state of soil organic matter. RothC model can be applied in the time period of several years to centuries and has been tested in long-term experiments within a large range of soil types and climatic conditions in Europe. For the initialization of the RothC model, knowledge about the carbon pool sizes is essential. Pool size characterization can be obtained from equilibrium model runs, but this approach is time consuming and tedious, especially for larger scale simulations. Due to this complexity we search for new possibilities how to simplify and accelerate this process. The paper presents a comparison of two approaches for SOC stocks modelling in the same area. The modelling has been carried out on the basis of unique input of land use, management and soil data for each simulation unit separately. We modeled 1617 simulation units of 1x1 km grid on the territory of agroclimatic region Žitný ostrov in the southwest of Slovakia. The first approach represents the creation of groups of simulation units based on the evaluation of results for simulation unit with similar input values. The groups were created after the testing and validation of modelling results for individual simulation units with results of modelling the average values of inputs for the whole group. Tests of equilibrium model for interval in the range 5 t.ha-1 from initial SOC stock showed minimal differences in results comparing with result for average value of whole interval. Management inputs data from plant residues and farmyard manure for modelling of carbon turnover were also the same for more simulation units. Combining these groups (intervals of initial
International Nuclear Information System (INIS)
Fazio, C; Guastella, I; Tarantino, G
2007-01-01
In this paper, we describe a pedagogical approach to elastic body movement based on measurements of the contact times between a metallic rod and small bodies colliding with it and on modelling of the experimental results by using a microcomputer-based laboratory and simulation tools. The experiments and modelling activities have been built in the context of the laboratory of mechanical wave propagation of the two-year graduate teacher education programme of Palermo's University. Some considerations about observed modifications in trainee teachers' attitudes in utilizing experiments and modelling are discussed
Modeling amorphization of tetrahedral structures under local approaches
International Nuclear Information System (INIS)
Jesurum, C.E.; Pulim, V.; Berger, B.; Hobbs, L.W.
1997-01-01
Many crystalline ceramics can be topologically disordered (amorphized) by disordering radiation events involving high-energy collision cascades or (in some cases) successive single-atom displacements. The authors are interested in both the potential for disorder and the possible aperiodic structures adopted following the disordering event. The potential for disordering is related to connectivity, and among those structures of interest are tetrahedral networks (such as SiO 2 , SiC and Si 3 N 4 ) comprising corner-shared tetrahedral units whose connectivities are easily evaluated. In order to study the response of these networks to radiation, the authors have chosen to model their assembly according to the (simple) local rules that each corner obeys in connecting to another tetrahedron; in this way they easily erect large computer models of any crystalline polymorphic form. Amorphous structures can be similarly grown by application of altered rules. They have adopted a simple model of irradiation in which all bonds in the neighborhood of a designated tetrahedron are destroyed, and they reform the bonds in this region according to a set of (possibly different) local rules appropriate to the environmental conditions. When a tetrahedron approaches the boundary of this neighborhood, it undergoes an optimization step in which a spring is inserted between two corners of compatible tetrahedra when they are within a certain distance of one another; component forces are then applied that act to minimize the distance between these corners and minimize the deviation from the rules. The resulting structure is then analyzed for the complete adjacency matrix, irreducible ring statistics, and bond angle distributions
A developmental approach to learning causal models for cyber security
Mugan, Jonathan
2013-05-01
To keep pace with our adversaries, we must expand the scope of machine learning and reasoning to address the breadth of possible attacks. One approach is to employ an algorithm to learn a set of causal models that describes the entire cyber network and each host end node. Such a learning algorithm would run continuously on the system and monitor activity in real time. With a set of causal models, the algorithm could anticipate novel attacks, take actions to thwart them, and predict the second-order effects flood of information, and the algorithm would have to determine which streams of that flood were relevant in which situations. This paper will present the results of efforts toward the application of a developmental learning algorithm to the problem of cyber security. The algorithm is modeled on the principles of human developmental learning and is designed to allow an agent to learn about the computer system in which it resides through active exploration. Children are flexible learners who acquire knowledge by actively exploring their environment and making predictions about what they will find,1, 2 and our algorithm is inspired by the work of the developmental psychologist Jean Piaget.3 Piaget described how children construct knowledge in stages and learn new concepts on top of those they already know. Developmental learning allows our algorithm to focus on subsets of the environment that are most helpful for learning given its current knowledge. In experiments, the algorithm was able to learn the conditions for file exfiltration and use that knowledge to protect sensitive files.
Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches
Farley, Kevin J.; Meyer, Joe; Balistrieri, Laurie S.; DeSchamphelaere, Karl; Iwasaki, Yuichi; Janssen, Colin; Kamo, Masashi; Lofts, Steve; Mebane, Christopher A.; Naito, Wataru; Ryan, Adam C.; Santore, Robert C.; Tipping, Edward
2015-01-01
As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the U.S. Geological Survey (USA), HDR⎪HydroQual, Inc. (USA), and the Centre for Ecology and Hydrology (UK) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME Workshop in Brussels, Belgium (May 2012), is provided herein. Overall, the models were found to be similar in structure (free ion activities computed by WHAM; specific or non-specific binding of metals/cations in or on the organism; specification of metal potency factors and/or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single versus multiple types of binding site on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong inter-relationships among the model parameters (log KM values, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed.
A Cyclical Approach to Continuum Modeling: A Conceptual Model of Diabetic Foot Care
Directory of Open Access Journals (Sweden)
Martha L. Carvour
2017-12-01
Full Text Available “Cascade” or “continuum” models have been developed for a number of diseases and conditions. These models define the desired, successive steps in care for that disease or condition and depict the proportion of the population that has completed each step. These models may be used to compare care across subgroups or populations and to identify and evaluate interventions intended to improve outcomes on the population level. Previous cascade or continuum models have been limited by several factors. These models are best suited to processes with stepwise outcomes—such as screening, diagnosis, and treatment—with a single defined outcome (e.g., treatment or cure for each member of the population. However, continuum modeling is not well developed for complex processes with non-sequential or recurring steps or those without singular outcomes. As shown here using the example of diabetic foot care, the concept of continuum modeling may be re-envisioned with a cyclical approach. Cyclical continuum modeling may permit incorporation of non-sequential and recurring steps into a single continuum, while recognizing the presence of multiple desirable outcomes within the population. Cyclical models may simultaneously represent the distribution of clinical severity and clinical resource use across a population, thereby extending the benefits of traditional continuum models to complex processes for which population-based monitoring is desired. The models may also support communication with other stakeholders in the process of care, including health care providers and patients.
Farquharson, C.; Long, J.; Lu, X.; Lelievre, P. G.
2017-12-01
Real-life geology is complex, and so, even when allowing for the diffusive, low resolution nature of geophysical electromagnetic methods, we need Earth models that can accurately represent this complexity when modelling and inverting electromagnetic data. This is particularly the case for the scales, detail and conductivity contrasts involved in mineral and hydrocarbon exploration and development, but also for the larger scale of lithospheric studies. Unstructured tetrahedral meshes provide a flexible means of discretizing a general, arbitrary Earth model. This is important when wanting to integrate a geophysical Earth model with a geological Earth model parameterized in terms of surfaces. Finite-element and finite-volume methods can be derived for computing the electric and magnetic fields in a model parameterized using an unstructured tetrahedral mesh. A number of such variants have been proposed and have proven successful. However, the efficiency and accuracy of these methods can be affected by the "quality" of the tetrahedral discretization, that is, how many of the tetrahedral cells in the mesh are long, narrow and pointy. This is particularly the case if one wants to use an iterative technique to solve the resulting linear system of equations. One approach to deal with this issue is to develop sophisticated model and mesh building and manipulation capabilities in order to ensure that any mesh built from geological information is of sufficient quality for the electromagnetic modelling. Another approach is to investigate other methods of synthesizing the electromagnetic fields. One such example is a "meshfree" approach in which the electromagnetic fields are synthesized using a mesh that is distinct from the mesh used to parameterized the Earth model. There are then two meshes, one describing the Earth model and one used for the numerical mathematics of computing the fields. This means that there are no longer any quality requirements on the model mesh, which
A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models
International Nuclear Information System (INIS)
Troffaes, Matthias C.M.; Walter, Gero; Kelly, Dana
2014-01-01
In a standard Bayesian approach to the alpha-factor model for common-cause failure, a precise Dirichlet prior distribution models epistemic uncertainty in the alpha-factors. This Dirichlet prior is then updated with observed data to obtain a posterior distribution, which forms the basis for further inferences. In this paper, we adapt the imprecise Dirichlet model of Walley to represent epistemic uncertainty in the alpha-factors. In this approach, epistemic uncertainty is expressed more cautiously via lower and upper expectations for each alpha-factor, along with a learning parameter which determines how quickly the model learns from observed data. For this application, we focus on elicitation of the learning parameter, and find that values in the range of 1 to 10 seem reasonable. The approach is compared with Kelly and Atwood's minimally informative Dirichlet prior for the alpha-factor model, which incorporated precise mean values for the alpha-factors, but which was otherwise quite diffuse. Next, we explore the use of a set of Gamma priors to model epistemic uncertainty in the marginal failure rate, expressed via a lower and upper expectation for this rate, again along with a learning parameter. As zero counts are generally less of an issue here, we find that the choice of this learning parameter is less crucial. Finally, we demonstrate how both epistemic uncertainty models can be combined to arrive at lower and upper expectations for all common-cause failure rates. Thereby, we effectively provide a full sensitivity analysis of common-cause failure rates, properly reflecting epistemic uncertainty of the analyst on all levels of the common-cause failure model
Modelling and approaching pragmatic interoperability of distributed geoscience data
Ma, Xiaogang
2010-05-01
, intention, procedure, consequence, etc.) of local pragmatic contexts and thus context-dependent. Elimination of these elements will inevitably lead to information loss in semantic mediation between local ontologies. Correspondingly, understanding and effect of exchanged data in a new context may differ from that in its original context. Another problem is the dilemma on how to find a balance between flexibility and standardization of local ontologies, because ontologies are not fixed, but continuously evolving. It is commonly realized that we cannot use a unified ontology to replace all local ontologies because they are context-dependent and need flexibility. However, without coordination of standards, freely developed local ontologies and databases will bring enormous work of mediation between them. Finding a balance between standardization and flexibility for evolving ontologies, in a practical sense, requires negotiations (i.e. conversations, agreements and collaborations) between different local pragmatic contexts. The purpose of this work is to set up a computer-friendly model representing local pragmatic contexts (i.e. geodata sources), and propose a practical semantic negotiation procedure for approaching pragmatic interoperability between local pragmatic contexts. Information agents, objective facts and subjective dimensions are reviewed as elements of a conceptual model for representing pragmatic contexts. The author uses them to draw a practical semantic negotiation procedure approaching pragmatic interoperability of distributed geodata. The proposed conceptual model and semantic negotiation procedure were encoded with Description Logic, and then applied to analyze and manipulate semantic negotiations between different local ontologies within the National Mineral Resources Assessment (NMRA) project of China, which involves multi-source and multi-subject geodata sharing.
Reliability assessment using degradation models: bayesian and classical approaches
Directory of Open Access Journals (Sweden)
Marta Afonso Freitas
2010-04-01
Full Text Available Traditionally, reliability assessment of devices has been based on (accelerated life tests. However, for highly reliable products, little information about reliability is provided by life tests in which few or no failures are typically observed. Since most failures arise from a degradation mechanism at work for which there are characteristics that degrade over time, one alternative is monitor the device for a period of time and assess its reliability from the changes in performance (degradation observed during that period. The goal of this article is to illustrate how degradation data can be modeled and analyzed by using "classical" and Bayesian approaches. Four methods of data analysis based on classical inference are presented. Next we show how Bayesian methods can also be used to provide a natural approach to analyzing degradation data. The approaches are applied to a real data set regarding train wheels degradation.Tradicionalmente, o acesso à confiabilidade de dispositivos tem sido baseado em testes de vida (acelerados. Entretanto, para produtos altamente confiáveis, pouca informação a respeito de sua confiabilidade é fornecida por testes de vida no quais poucas ou nenhumas falhas são observadas. Uma vez que boa parte das falhas é induzida por mecanismos de degradação, uma alternativa é monitorar o dispositivo por um período de tempo e acessar sua confiabilidade através das mudanças em desempenho (degradação observadas durante aquele período. O objetivo deste artigo é ilustrar como dados de degradação podem ser modelados e analisados utilizando-se abordagens "clássicas" e Bayesiana. Quatro métodos de análise de dados baseados em inferência clássica são apresentados. A seguir, mostramos como os métodos Bayesianos podem também ser aplicados para proporcionar uma abordagem natural à análise de dados de degradação. As abordagens são aplicadas a um banco de dados real relacionado à degradação de rodas de trens.
Muenich, R. L.; Kalcic, M. M.; Teshager, A. D.; Long, C. M.; Wang, Y. C.; Scavia, D.
2017-12-01
Thanks to the availability of open-source software, online tutorials, and advanced software capabilities, watershed modeling has expanded its user-base and applications significantly in the past thirty years. Even complicated models like the Soil and Water Assessment Tool (SWAT) are being used and documented in hundreds of peer-reviewed publications each year, and likely more applied in practice. These models can help improve our understanding of present, past, and future conditions, or analyze important "what-if" management scenarios. However, baseline data and methods are often adopted and applied without rigorous testing. In multiple collaborative projects, we have evaluated the influence of some of these common approaches on model results. Specifically, we examined impacts of baseline data and assumptions involved in manure application, combined sewer overflows, and climate data incorporation across multiple watersheds in the Western Lake Erie Basin. In these efforts, we seek to understand the impact of using typical modeling data and assumptions, versus using improved data and enhanced assumptions on model outcomes and thus ultimately, study conclusions. We provide guidance for modelers as they adopt and apply data and models for their specific study region. While it is difficult to quantitatively assess the full uncertainty surrounding model input data and assumptions, recognizing the impacts of model input choices is important when considering actions at the both the field and watershed scales.
Gusev, E Yu; Chereshnev, V A
2013-01-01
Theoretical and methodological approaches to description of systemic inflammation as general pathological process are discussed. It is shown, that there is a need of integration of wide range of types of researches to develop a model of systemic inflammation.
Box-wing model approach for solar radiation pressure modelling in a multi-GNSS scenario
Tobias, Guillermo; Jesús García, Adrián
2016-04-01
The solar radiation pressure force is the largest orbital perturbation after the gravitational effects and the major error source affecting GNSS satellites. A wide range of approaches have been developed over the years for the modelling of this non gravitational effect as part of the orbit determination process. These approaches are commonly divided into empirical, semi-analytical and analytical, where their main difference relies on the amount of knowledge of a-priori physical information about the properties of the satellites (materials and geometry) and their attitude. It has been shown in the past that the pre-launch analytical models fail to achieve the desired accuracy mainly due to difficulties in the extrapolation of the in-orbit optical and thermic properties, the perturbations in the nominal attitude law and the aging of the satellite's surfaces, whereas empirical models' accuracies strongly depend on the amount of tracking data used for deriving the models, and whose performances are reduced as the area to mass ratio of the GNSS satellites increases, as it happens for the upcoming constellations such as BeiDou and Galileo. This paper proposes to use basic box-wing model for Galileo complemented with empirical parameters, based on the limited available information about the Galileo satellite's geometry. The satellite is modelled as a box, representing the satellite bus, and a wing representing the solar panel. The performance of the model will be assessed for GPS, GLONASS and Galileo constellations. The results of the proposed approach have been analyzed over a one year period. In order to assess the results two different SRP models have been used. Firstly, the proposed box-wing model and secondly, the new CODE empirical model, ECOM2. The orbit performances of both models are assessed using Satellite Laser Ranging (SLR) measurements, together with the evaluation of the orbit prediction accuracy. This comparison shows the advantages and disadvantages of
Space-Wise approach for airborne gravity data modelling
Sampietro, D.; Capponi, M.; Mansi, A. H.; Gatti, A.; Marchetti, P.; Sansò, F.
2017-05-01
Regional gravity field modelling by means of remove-compute-restore procedure is nowadays widely applied in different contexts: it is the most used technique for regional gravimetric geoid determination, and it is also used in exploration geophysics to predict grids of gravity anomalies (Bouguer, free-air, isostatic, etc.), which are useful to understand and map geological structures in a specific region. Considering this last application, due to the required accuracy and resolution, airborne gravity observations are usually adopted. However, due to the relatively high acquisition velocity, presence of atmospheric turbulence, aircraft vibration, instrumental drift, etc., airborne data are usually contaminated by a very high observation error. For this reason, a proper procedure to filter the raw observations in both the low and high frequencies should be applied to recover valuable information. In this work, a software to filter and grid raw airborne observations is presented: the proposed solution consists in a combination of an along-track Wiener filter and a classical Least Squares Collocation technique. Basically, the proposed procedure is an adaptation to airborne gravimetry of the Space-Wise approach, developed by Politecnico di Milano to process data coming from the ESA satellite mission GOCE. Among the main differences with respect to the satellite application of this approach, there is the fact that, while in processing GOCE data the stochastic characteristics of the observation error can be considered a-priori well known, in airborne gravimetry, due to the complex environment in which the observations are acquired, these characteristics are unknown and should be retrieved from the dataset itself. The presented solution is suited for airborne data analysis in order to be able to quickly filter and grid gravity observations in an easy way. Some innovative theoretical aspects focusing in particular on the theoretical covariance modelling are presented too
An evaluation of gas release modelling approaches as to their applicability in fuel behaviour models
International Nuclear Information System (INIS)
Mattila, L.J.; Sairanen, R.T.
1980-01-01
The release of fission gas from uranium oxide fuel to the voids in the fuel rod affects in many ways the behaviour of LWR fuel rods both during normal operating conditions including anticipated transients and during off-normal and accident conditions. The current trend towards significantly increased discharge burnup of LWR fuel will increase the importance of fission gas release considerations both from the design and safety viewpoints. In the paper fission gas release models are classified to 5 categories on the basis of complexity and physical sophistication. For each category, the basic approach common to the models included in the category is described, a few representative models of the category are singled out and briefly commented in some cases, the advantages and drawbacks of the approach are listed and discussed and conclusions on the practical feasibility of the approach are drawn. The evaluation is based on both literature survey and our experience in working with integral fuel behaviour models. The work has included verification efforts, attempts to improve certain features of the codes and engineering applications. The classification of fission gas release models regarding their applicability in fuel behaviour codes can of course be done only in a coarse manner. The boundaries between the different categories are vague and a model may be well refined in a way which transfers it to a higher category. Some current trends in fuel behaviour research are discussed which seem to motivate further extensive efforts in fission product release modelling and are certain to affect the prioritizing of the efforts. (author)
Peng, Changhui; Guiot, Joel; Wu, Haibin; Jiang, Hong; Luo, Yiqi
2011-05-01
It is increasingly being recognized that global ecological research requires novel methods and strategies in which to combine process-based ecological models and data in cohesive, systematic ways. Model-data fusion (MDF) is an emerging area of research in ecology and palaeoecology. It provides a new quantitative approach that offers a high level of empirical constraint over model predictions based on observations using inverse modelling and data assimilation (DA) techniques. Increasing demands to integrate model and data methods in the past decade has led to MDF utilization in palaeoecology, ecology and earth system sciences. This paper reviews key features and principles of MDF and highlights different approaches with regards to DA. After providing a critical evaluation of the numerous benefits of MDF and its current applications in palaeoecology (i.e., palaeoclimatic reconstruction, palaeovegetation and palaeocarbon storage) and ecology (i.e. parameter and uncertainty estimation, model error identification, remote sensing and ecological forecasting), the paper discusses method limitations, current challenges and future research direction. In the ongoing data-rich era of today's world, MDF could become an important diagnostic and prognostic tool in which to improve our understanding of ecological processes while testing ecological theory and hypotheses and forecasting changes in ecosystem structure, function and services. © 2011 Blackwell Publishing Ltd/CNRS.
Testing Process Predictions of Models of Risky Choice: A Quantitative Model Comparison Approach
Directory of Open Access Journals (Sweden)
Thorsten ePachur
2013-09-01
Full Text Available This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or nonlinear functions thereof and the separate evaluation of risky options (expectation models. Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models. We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter, Gigerenzer, & Hertwig, 2006, and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up and direction of search (i.e., gamble-wise vs. reason-wise. In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly; acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988 called similarity. In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies.
Testing process predictions of models of risky choice: a quantitative model comparison approach
Pachur, Thorsten; Hertwig, Ralph; Gigerenzer, Gerd; Brandstätter, Eduard
2013-01-01
This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or non-linear functions thereof) and the separate evaluation of risky options (expectation models). Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models). We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter et al., 2006), and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up) and direction of search (i.e., gamble-wise vs. reason-wise). In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly); acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988) called “similarity.” In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies. PMID:24151472
Discrete Variational Approach for Modeling Laser-Plasma Interactions
Reyes, J. Paxon; Shadwick, B. A.
2014-10-01
The traditional approach for fluid models of laser-plasma interactions begins by approximating fields and derivatives on a grid in space and time, leading to difference equations that are manipulated to create a time-advance algorithm. In contrast, by introducing the spatial discretization at the level of the action, the resulting Euler-Lagrange equations have particular differencing approximations that will exactly satisfy discrete versions of the relevant conservation laws. For example, applying a spatial discretization in the Lagrangian density leads to continuous-time, discrete-space equations and exact energy conservation regardless of the spatial grid resolution. We compare the results of two discrete variational methods using the variational principles from Chen and Sudan and Brizard. Since the fluid system conserves energy and momentum, the relative errors in these conserved quantities are well-motivated physically as figures of merit for a particular method. This work was supported by the U. S. Department of Energy under Contract No. DE-SC0008382 and by the National Science Foundation under Contract No. PHY-1104683.
Separable potential approach in the folding model. Pt. 2
International Nuclear Information System (INIS)
Lee, C.L.; Robson, D.
1982-01-01
A microscopic folding formalism using a separable potential approach is applied to the elastic scattering of the n-α system. Starting with a separable nucleon-nucleon (NN) potential model, a sum of separable nucleon-nucleus potentials is obtained. A simple structure of the α-particle is assumed and the Tabakin, the Doleschall and the Strobel NN potentials are considered. These phenomenological interactions are of Yukawa or gaussian form with variable parameters for each partial wave. Spin-orbit and tensor forces are included. The resulting potentials developed from our folding calculations give approximately the same ssub(1/2) phase shifts for the n-α elastic scattering. However, in the psub(1/2) and psub(3/2) phase-shift analysis, an effective interaction derived from the NN potential is necessary to reproduce the resonances. One free energy independent parameter is introduced in our approximate G-matrix concept to give a good fit for the phase shifts. Single-nucleon knockout exchange (SNKE) is considered throughout. (orig.)
A new approach for modelling variability in residential construction projects
Directory of Open Access Journals (Sweden)
Mehrdad Arashpour
2013-06-01
Full Text Available The construction industry is plagued by long cycle times caused by variability in the supply chain. Variations or undesirable situations are the result of factors such as non-standard practices, work site accidents, inclement weather conditions and faults in design. This paper uses a new approach for modelling variability in construction by linking relative variability indicators to processes. Mass homebuilding sector was chosen as the scope of the analysis because data is readily available. Numerous simulation experiments were designed by varying size of capacity buffers in front of trade contractors, availability of trade contractors, and level of variability in homebuilding processes. The measurements were shown to lead to an accurate determination of relationships between these factors and production parameters. The variability indicator was found to dramatically affect the tangible performance measures such as home completion rates. This study provides for future analysis of the production homebuilding sector, which may lead to improvements in performance and a faster product delivery to homebuyers.
A new approach for modelling variability in residential construction projects
Directory of Open Access Journals (Sweden)
Mehrdad Arashpour
2013-06-01
Full Text Available The construction industry is plagued by long cycle times caused by variability in the supply chain. Variations or undesirable situations are the result of factors such as non-standard practices, work site accidents, inclement weather conditions and faults in design. This paper uses a new approach for modelling variability in construction by linking relative variability indicators to processes. Mass homebuilding sector was chosen as the scope of the analysis because data is readily available. Numerous simulation experiments were designed by varying size of capacity buffers in front of trade contractors, availability of trade contractors, and level of variability in homebuilding processes. The measurements were shown to lead to an accurate determination of relationships between these factors and production parameters. The variability indicator was found to dramatically affect the tangible performance measures such as home completion rates. This study provides for future analysis of the production homebuilding sector, which may lead to improvements in performance and a faster product delivery to homebuyers.
An approach to accidents modeling based on compounds road environments.
Fernandes, Ana; Neves, Jose
2013-04-01
The most common approach to study the influence of certain road features on accidents has been the consideration of uniform road segments characterized by a unique feature. However, when an accident is related to the road infrastructure, its cause is usually not a single characteristic but rather a complex combination of several characteristics. The main objective of this paper is to describe a methodology developed in order to consider the road as a complete environment by using compound road environments, overcoming the limitations inherented in considering only uniform road segments. The methodology consists of: dividing a sample of roads into segments; grouping them into quite homogeneous road environments using cluster analysis; and identifying the influence of skid resistance and texture depth on road accidents in each environment by using generalized linear models. The application of this methodology is demonstrated for eight roads. Based on real data from accidents and road characteristics, three compound road environments were established where the pavement surface properties significantly influence the occurrence of accidents. Results have showed clearly that road environments where braking maneuvers are more common or those with small radii of curvature and high speeds require higher skid resistance and texture depth as an important contribution to the accident prevention. Copyright © 2013 Elsevier Ltd. All rights reserved.
A MIMIC approach to modeling the underground economy in Taiwan
Wang, David Han-Min; Lin, Jer-Yan; Yu, Tiffany Hui-Kuang
2006-11-01
The size of underground economy (UE) expansion usually increases the tax gap, impose a burden on the economy, and results in tax distortions. This study uses the MIMIC approach to model the causal variables and indicating variables to estimate the UE in Taiwan. We also focus on testing the data for non-stationarity and perform diagnostic tests. By using annual time-series data for Taiwan from 1961 to 2003, it is found that the estimated size of the UE varies from 11.0% to 13.1% before 1988, and from 10.6% to 11.8% from 1989 onwards. That the size of the UE experienced a substantial downward shift in 1989 indicates that there was a structural break. The UE is significantly and positively affected by such casual variables as the logarithm of real government consumption and currency inflation, but is negatively affected by the tax burden at 5% significant level. Unemployment rate and crime rate are not significantly correlated with the UE in this study.
Modeling approach for safety of high activity waste disposal
International Nuclear Information System (INIS)
Serres, Christophe; Besnus, Francois
2005-01-01
This paper presents two examples of numerical modeling studies performed by IRSN for assessing geochemical interactions and the role of engineered barriers for the confinement of radionuclides. These examples illustrate the ability of numerical calculations to contribute to the long-term safety assessment approach. In the first example, disturbances and interactions between cementitious materials, bentonite and clayey host rock are tackled by numerical calculations at process level that enable addressing main issues of interest for performance assessment, e.g. extension and intensity of mineralogical transformations and alkaline plume spreading in the vicinity of the disposal tunnels. Once main disturbances and their effects on confinement properties of repository barriers have been identified and quantified, one may assess the role of each barrier on the overall safety of the repository for various scenarios of evolution. This assessment is tackled by integrated level calculations allowing quantifying radionuclide confinement performance of the whole repository for different stages of alteration of its components. The second example highlights the role played by bentonite engineered barriers, plugs and seals as hydraulic and migration barrier in presence of an excavation damaged zone around the vaults, drifts and shafts for different hydrogeological settings. (author)
BUSINESS MODEL IN ELECTRICITY INDUSTRY USING BUSINESS MODEL CANVAS APPROACH; THE CASE OF PT. XYZ
Directory of Open Access Journals (Sweden)
Achmad Arief Wicaksono
2017-01-01
Full Text Available The magnitude of opportunities and project values of electricity system in Indonesia encourages PT. XYZ to develop its business in electrical sector which requires business development strategies. This study aims to identify company's business model using Business Model Canvas approach, formulate business development strategy alternatives, and determine the prioritized business development strategy which is appropriate to the manufacturing business model for PT. XYZ. This study utilized a descriptive approach and the nine elements of the Business Model Canvas. Alternative formulation and priority determination of the strategies were obtained by using Strengths, Weaknesses, Opportunities, Threats (SWOT analysis and pairwise comparison. The results of this study are the improvement of Business Model Canvas on the elements of key resources, key activities, key partners and customer segment. In terms of SWOT analysis on the nine elements of the Business Model Canvas for the first business development, the results show an expansion on the power plant construction project as the main contractor, an increase in sales in its core business in supporting equipment industry of oil and gas, a development in the second business i.e. an investment in the electricity sector as an independent renewable emery-based power producer. On its first business development, PT. XYZ selected three Business Model Canvas elements which become the priorities of the company i.e. key resources weighing 0.252, key activities weighing 0.240, and key partners weighing 0.231. On its second business development, the company selected three elements to become their the priorities i.e. key partners weighing 0.225, customer segments weighing 0.217, and key resources weighing 0.215.Keywords: business model canvas, SWOT, pairwise comparison, business model
Zheng, Y.; Wu, B.; Wu, X.
2015-12-01
Integrated hydrological models (IHMs) consider surface water and subsurface water as a unified system, and have been widely adopted in basin-scale water resources studies. However, due to IHMs' mathematical complexity and high computational cost, it is difficult to implement them in an iterative model evaluation process (e.g., Monte Carlo Simulation, simulation-optimization analysis, etc.), which diminishes their applicability for supporting decision-making in real-world situations. Our studies investigated how to effectively use complex IHMs to address real-world water issues via surrogate modeling. Three surrogate modeling approaches were considered, including 1) DYCORS (DYnamic COordinate search using Response Surface models), a well-established response surface-based optimization algorithm; 2) SOIM (Surrogate-based Optimization for Integrated surface water-groundwater Modeling), a response surface-based optimization algorithm that we developed specifically for IHMs; and 3) Probabilistic Collocation Method (PCM), a stochastic response surface approach. Our investigation was based on a modeling case study in the Heihe River Basin (HRB), China's second largest endorheic river basin. The GSFLOW (Coupled Ground-Water and Surface-Water Flow Model) model was employed. Two decision problems were discussed. One is to optimize, both in time and in space, the conjunctive use of surface water and groundwater for agricultural irrigation in the middle HRB region; and the other is to cost-effectively collect hydrological data based on a data-worth evaluation. Overall, our study results highlight the value of incorporating an IHM in making decisions of water resources management and hydrological data collection. An IHM like GSFLOW can provide great flexibility to formulating proper objective functions and constraints for various optimization problems. On the other hand, it has been demonstrated that surrogate modeling approaches can pave the path for such incorporation in real
Risk evaluation of uranium mining: A geochemical inverse modelling approach
Rillard, J.; Zuddas, P.; Scislewski, A.
2011-12-01
It is well known that uranium extraction operations can increase risks linked to radiation exposure. The toxicity of uranium and associated heavy metals is the main environmental concern regarding exploitation and processing of U-ore. In areas where U mining is planned, a careful assessment of toxic and radioactive element concentrations is recommended before the start of mining activities. A background evaluation of harmful elements is important in order to prevent and/or quantify future water contamination resulting from possible migration of toxic metals coming from ore and waste water interaction. Controlled leaching experiments were carried out to investigate processes of ore and waste (leached ore) degradation, using samples from the uranium exploitation site located in Caetité-Bahia, Brazil. In experiments in which the reaction of waste with water was tested, we found that the water had low pH and high levels of sulphates and aluminium. On the other hand, in experiments in which ore was tested, the water had a chemical composition comparable to natural water found in the region of Caetité. On the basis of our experiments, we suggest that waste resulting from sulphuric acid treatment can induce acidification and salinization of surface and ground water. For this reason proper storage of waste is imperative. As a tool to evaluate the risks, a geochemical inverse modelling approach was developed to estimate the water-mineral interaction involving the presence of toxic elements. We used a method earlier described by Scislewski and Zuddas 2010 (Geochim. Cosmochim. Acta 74, 6996-7007) in which the reactive surface area of mineral dissolution can be estimated. We found that the reactive surface area of rock parent minerals is not constant during time but varies according to several orders of magnitude in only two months of interaction. We propose that parent mineral heterogeneity and particularly, neogenic phase formation may explain the observed variation of the
The brush model - a new approach to numerical modeling of matrix diffusion in fractured clay stone
International Nuclear Information System (INIS)
Lege, T.; Shao, H.
1998-01-01
A special approach for numerical modeling of contaminant transport in fractured clay stone is presented. The rock matrix and the fractures are simulated with individual formulations for FE grids and transport, coupled into a single model. The capacity of the rock matrix to take up contaminants is taken into consideration with a discrete simulation of matrix diffusion. Thus, the natural process of retardation due to matrix diffusion can be better simulated than by a standard introduction of an empirical parameter into the transport equation. Transport in groundwater in fractured clay stone can be simulated using a model called a 'brush model'. The 'brush handle' is discretized by 2-D finite elements. Advective-dispersive transport in groundwater in the fractures is assumed. The contaminant diffuses into 1D finite elements perpendicular to the fractures, i.e., the 'bristles of the brush'. The conclusion is drawn that matrix diffusion is an important property of fractured clay stone for contaminant retardation. (author)
An approach to model validation and model-based prediction -- polyurethane foam case study.
Energy Technology Data Exchange (ETDEWEB)
Dowding, Kevin J.; Rutherford, Brian Milne
2003-07-01
Enhanced software methodology and improved computing hardware have advanced the state of simulation technology to a point where large physics-based codes can be a major contributor in many systems analyses. This shift toward the use of computational methods has brought with it new research challenges in a number of areas including characterization of uncertainty, model validation, and the analysis of computer output. It is these challenges that have motivated the work described in this report. Approaches to and methods for model validation and (model-based) prediction have been developed recently in the engineering, mathematics and statistical literatures. In this report we have provided a fairly detailed account of one approach to model validation and prediction applied to an analysis investigating thermal decomposition of polyurethane foam. A model simulates the evolution of the foam in a high temperature environment as it transforms from a solid to a gas phase. The available modeling and experimental results serve as data for a case study focusing our model validation and prediction developmental efforts on this specific thermal application. We discuss several elements of the ''philosophy'' behind the validation and prediction approach: (1) We view the validation process as an activity applying to the use of a specific computational model for a specific application. We do acknowledge, however, that an important part of the overall development of a computational simulation initiative is the feedback provided to model developers and analysts associated with the application. (2) We utilize information obtained for the calibration of model parameters to estimate the parameters and quantify uncertainty in the estimates. We rely, however, on validation data (or data from similar analyses) to measure the variability that contributes to the uncertainty in predictions for specific systems or units (unit-to-unit variability). (3) We perform statistical
Autonomous formation flight of helicopters: Model predictive control approach
Chung, Hoam
Formation flight is the primary movement technique for teams of helicopters. However, the potential for accidents is greatly increased when helicopter teams are required to fly in tight formations and under harsh conditions. This dissertation proposes that the automation of helicopter formations is a realistic solution capable of alleviating risks. Helicopter formation flight operations in battlefield situations are highly dynamic and dangerous, and, therefore, we maintain that both a high-level formation management system and a distributed coordinated control algorithm should be implemented to help ensure safe formations. The starting point for safe autonomous formation flights is to design a distributed control law attenuating external disturbances coming into a formation, so that each vehicle can safely maintain sufficient clearance between it and all other vehicles. While conventional methods are limited to homogeneous formations, our decentralized model predictive control (MPC) approach allows for heterogeneity in a formation. In order to avoid the conservative nature inherent in distributed MPC algorithms, we begin by designing a stable MPC for individual vehicles, and then introducing carefully designed inter-agent coupling terms in a performance index. Thus the proposed algorithm works in a decentralized manner, and can be applied to the problem of helicopter formations comprised of heterogenous vehicles. Individual vehicles in a team may be confronted by various emerging situations that will require the capability for in-flight reconfiguration. We propose the concept of a formation manager to manage separation, join, and synchronization of flight course changes. The formation manager accepts an operator's commands, information from neighboring vehicles, and its own vehicle states. Inside the formation manager, there are multiple modes and complex mode switchings represented as a finite state machine (FSM). Based on the current mode and collected
High-resolution urban flood modelling - a joint probability approach
Hartnett, Michael; Olbert, Agnieszka; Nash, Stephen
2017-04-01
The hydrodynamic modelling of rapid flood events due to extreme climatic events in urban environment is both a complex and challenging task. The horizontal resolution necessary to resolve complexity of urban flood dynamics is a critical issue; the presence of obstacles of varying shapes and length scales, gaps between buildings and the complex geometry of the city such as slopes affect flow paths and flood levels magnitudes. These small scale processes require a high resolution grid to be modelled accurately (2m or less, Olbert et al., 2015; Hunter et al., 2008; Brown et al., 2007) and, therefore, altimetry data of at least the same resolution. Along with availability of high-resolution LiDAR data and computational capabilities, as well as state of the art nested modelling approaches, these problems can now be overcome. Flooding and drying, domain definition, frictional resistance and boundary descriptions are all important issues to be addressed when modelling urban flooding. In recent years, the number of urban flood models dramatically increased giving a good insight into various modelling problems and solutions (Mark et al., 2004; Mason et al., 2007; Fewtrell et al., 2008; Shubert et al., 2008). Despite extensive modelling work conducted for fluvial (e.g. Mignot et al., 2006; Hunter et al., 2008; Yu and Lane, 2006) and coastal mechanisms of flooding (e.g. Gallien et al., 2011; Yang et al., 2012), the amount of investigations into combined coastal-fluvial flooding is still very limited (e.g. Orton et al., 2012; Lian et al., 2013). This is surprising giving the extent of flood consequences when both mechanisms occur simultaneously, which usually happens when they are driven by one process such as a storm. The reason for that could be the fact that the likelihood of joint event is much smaller than those of any of the two contributors occurring individually, because for fast moving storms the rainfall-driven fluvial flood arrives usually later than the storm surge
Mechanical disequilibria in two-phase flow models: approaches by relaxation and by a reduced model
International Nuclear Information System (INIS)
Labois, M.
2008-10-01
This thesis deals with hyperbolic models for the simulation of compressible two-phase flows, to find alternatives to the classical bi-fluid model. We first establish a hierarchy of two-phase flow models, obtained according to equilibrium hypothesis between the physical variables of each phase. The use of Chapman-Enskog expansions enables us to link the different existing models to each other. Moreover, models that take into account small physical unbalances are obtained by means of expansion to the order one. The second part of this thesis focuses on the simulation of flows featuring velocity unbalances and pressure balances, in two different ways. First, a two-velocity two-pressure model is used, where non-instantaneous velocity and pressure relaxations are applied so that a balancing of these variables is obtained. A new one-velocity one-pressure dissipative model is then proposed, where the arising of second-order terms enables us to take into account unbalances between the phase velocities. We develop a numerical method based on a fractional step approach for this model. (author)
Scheduling models in farm management : a new approach
Wijngaard, P.J.M.
1988-01-01
Three operational planning models to calculate schedules for an arable farm are examined. These models are a linear programming model, a dynamic programming model and a simulation model. They are examined at different levels of aggregation and relaxation in a retrospective way. Also a
Risk prediction model for knee pain in the Nottingham community: a Bayesian modelling approach.
Fernandes, G S; Bhattacharya, A; McWilliams, D F; Ingham, S L; Doherty, M; Zhang, W
2017-03-20
Twenty-five percent of the British population over the age of 50 years experiences knee pain. Knee pain can limit physical ability and cause distress and bears significant socioeconomic costs. The objectives of this study were to develop and validate the first risk prediction model for incident knee pain in the Nottingham community and validate this internally within the Nottingham cohort and externally within the Osteoarthritis Initiative (OAI) cohort. A total of 1822 participants from the Nottingham community who were at risk for knee pain were followed for 12 years. Of this cohort, two-thirds (n = 1203) were used to develop the risk prediction model, and one-third (n = 619) were used to validate the model. Incident knee pain was defined as pain on most days for at least 1 month in the past 12 months. Predictors were age, sex, body mass index, pain elsewhere, prior knee injury and knee alignment. A Bayesian logistic regression model was used to determine the probability of an OR >1. The Hosmer-Lemeshow χ 2 statistic (HLS) was used for calibration, and ROC curve analysis was used for discrimination. The OAI cohort from the United States was also used to examine the performance of the model. A risk prediction model for knee pain incidence was developed using a Bayesian approach. The model had good calibration, with an HLS of 7.17 (p = 0.52) and moderate discriminative ability (ROC 0.70) in the community. Individual scenarios are given using the model. However, the model had poor calibration (HLS 5866.28, p prediction model for knee pain, regardless of underlying structural changes of knee osteoarthritis, in the community using a Bayesian modelling approach. The model appears to work well in a community-based population but not in individuals with a higher risk for knee osteoarthritis, and it may provide a convenient tool for use in primary care to predict the risk of knee pain in the general population.
Exploring mouthfeel in model wines: Sensory-to-instrumental approaches.
Laguna, Laura; Sarkar, Anwesha; Bryant, Michael G; Beadling, Andrew R; Bartolomé, Begoña; Victoria Moreno-Arribas, M
2017-12-01
Wine creates a group of oral-tactile stimulations not related to taste or aroma, such as astringency or fullness; better known as mouthfeel. During wine consumption, mouthfeel is affected by ethanol content, phenolic compounds and their interactions with the oral components. Mouthfeel arises through changes in the salivary film when wine is consumed. In order to understand the role of each wine component, eight different model wines with/without ethanol (8%), glycerol (10g/L) and commercial tannins (1g/L) were described using a trained panel. Descriptive analysis techniques were used to train the panel and measure the intensity of the mouthfeel attributes. Alongside, the suitability of different instrumental techniques (rheology, particle size, tribology and microstructure, using Transmission Electron Microscopy (TEM)) to measure wine mouthfeel sensation was investigated. Panelists discriminated samples based on their tactile-related components (ethanol, glycerol and tannins) at the levels found naturally in wine. Higher scores were found for all sensory attributes in the samples containing ethanol. Sensory astringency was associated mainly with the addition of tannins to the wine model and glycerol did not seem to play a discriminating role at the levels found in red wines. Visual viscosity was correlated with instrumental viscosity (R=0.815, p=0.014). Hydrodynamic diameter of saliva showed an increase in presence of tannins (almost 2.5-3-folds). However, presence of ethanol or glycerol decreased hydrodynamic diameter. These results were related with the sensory astringency and earthiness as well as with the formation of nano-complexes as observed by TEM. Rheologically, the most viscous samples were those containing glycerol or tannins. Tribology results showed that at a boundary lubrication regime, differences in traction coefficient lubrication were due by the presence of glycerol. However, no differences in traction coefficients were observed in presence
Kuroishi, Y.; Lemoine, F. G.; Rowlands, D. D.
2006-12-01
The latest gravimetric geoid model for Japan, JGEOID2004, suffers from errors at long wavelengths (around 1000 km) in a range of +/- 30 cm. The model was developed by combining surface gravity data with a global marine altimetric gravity model, using EGM96 as a foundation, and the errors at long wavelength are presumably attributed to EGM96 errors. The Japanese islands and their vicinity are located in a region of plate convergence boundaries, producing substantial gravity and geoid undulations in a wide range of wavelengths. Because of the geometry of the islands and trenches, precise information on gravity in the surrounding oceans should be incorporated in detail, even if the geoid model is required to be accurate only over land. The Kuroshio Current, which runs south of Japan, causes high sea surface variability, making altimetric gravity field determination complicated. To reduce the long-wavelength errors in the geoid model, we are investigating GRACE data for regional gravity field modeling at long wavelengths in the vicinity of Japan. Our approach is based on exclusive use of inter- satellite range-rate data with calibrated accelerometer data and attitude data, for regional or global gravity field recovery. In the first step, we calibrate accelerometer data in terms of scales and biases by fitting dynamically calculated orbits to GPS-determined precise orbits. The calibration parameters of accelerometer data thus obtained are used in the second step to recover a global/regional gravity anomaly field. This approach is applied to GRACE data obtained for the year 2005 and resulting global/regional gravity models are presented and discussed.
Modeling alcohol use disorder severity: an integrative structural equation modeling approach
Directory of Open Access Journals (Sweden)
Nathasha R Moallem
2013-07-01
Full Text Available Background: Alcohol dependence is a complex psychological disorder whose phenomenology changes as the disorder progresses. Neuroscience has provided a variety of theories and evidence for the development, maintenance, and severity of addiction; however, clinically, it has been difficult to evaluate alcohol use disorder (AUD severity. Objective: This study seeks to evaluate and validate a data-driven approach to capturing alcohol severity in a community sample. Method: Participants were non-treatment seeking problem drinkers (n = 283. A structural equation modeling (SEM approach was used to (a verify the latent factor structure of the indices of AUD severity; and (b test the relationship between the AUD severity factor and measures of alcohol use, affective symptoms, and motivation to change drinking. Results: The model was found to fit well, with all chosen indices of AUD severity loading significantly and positively onto the severity factor. In addition, the paths from the alcohol use, motivation, and affective factors accounted for 68% of the variance in AUD severity. Greater AUD severity was associated with greater alcohol use, increased affective symptoms, and higher motivation to change.Conclusions: Unlike the categorical diagnostic criteria, the AUD severity factor is comprised of multiple quantitative dimensions of impairment observed across the progression of the disorder. The AUD severity factor was validated by testing it in relation to other outcomes such as alcohol use, affective symptoms, and motivation for change. Clinically, this approach to AUD severity can be used to inform treatment planning and ultimately to improve outcomes.
Numerical Modelling Approaches for Sediment Transport in Sewer Systems
DEFF Research Database (Denmark)
Mark, Ole
A study of the sediment transport processes in sewers has been carried out. Based on this study a mathematical modelling system has been developed to describe the transport processes of sediments and dissolved matter in sewer systems. The modelling system consists of three sub-models which...... constitute the basic modelling system necessary to give a discription of the most dominant physical transport processes concerning particles and dissolved matter in sewer systems: A surface model. An advection-dispersion model. A sediment transport model....
Modeling in applied sciences a kinetic theory approach
Pulvirenti, Mario
2000-01-01
Modeling complex biological, chemical, and physical systems, in the context of spatially heterogeneous mediums, is a challenging task for scientists and engineers using traditional methods of analysis Modeling in Applied Sciences is a comprehensive survey of modeling large systems using kinetic equations, and in particular the Boltzmann equation and its generalizations An interdisciplinary group of leading authorities carefully develop the foundations of kinetic models and discuss the connections and interactions between model theories, qualitative and computational analysis and real-world applications This book provides a thoroughly accessible and lucid overview of the different aspects, models, computations, and methodology for the kinetic-theory modeling process Topics and Features * Integrated modeling perspective utilized in all chapters * Fluid dynamics of reacting gases * Self-contained introduction to kinetic models * Becker–Doring equations * Nonlinear kinetic models with chemical reactions * Kinet...
Directory of Open Access Journals (Sweden)
Mohammad Hajigholizadeh
2018-03-01
Full Text Available The erosion and sediment transport processes in shallow waters, which are discussed in this paper, begin when water droplets hit the soil surface. The transport mechanism caused by the consequent rainfall-runoff process determines the amount of generated sediment that can be transferred downslope. Many significant studies and models are performed to investigate these processes, which differ in terms of their effecting factors, approaches, inputs and outputs, model structure and the manner that these processes represent. This paper attempts to review the related literature concerning sediment transport modelling in shallow waters. A classification based on the representational processes of the soil erosion and sediment transport models (empirical, conceptual, physical and hybrid is adopted, and the commonly-used models and their characteristics are listed. This review is expected to be of interest to researchers and soil and water conservation managers who are working on erosion and sediment transport phenomena in shallow waters. The paper format should be helpful for practitioners to identify and generally characterize the types of available models, their strengths and their basic scope of applicability.
The threshold bias model: a mathematical model for the nomothetic approach of suicide.
Folly, Walter Sydney Dutra
2011-01-01
Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health.
Modeling urban building energy use: A review of modeling approaches and procedures
Energy Technology Data Exchange (ETDEWEB)
Li, Wenliang; Zhou, Yuyu; Cetin, Kristen; Eom, Jiyong; Wang, Yu; Chen, Gang; Zhang, Xuesong
2017-12-01
With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration.
Hajigholizadeh, Mohammad; Melesse, Assefa M; Fuentes, Hector R
2018-03-14
The erosion and sediment transport processes in shallow waters, which are discussed in this paper, begin when water droplets hit the soil surface. The transport mechanism caused by the consequent rainfall-runoff process determines the amount of generated sediment that can be transferred downslope. Many significant studies and models are performed to investigate these processes, which differ in terms of their effecting factors, approaches, inputs and outputs, model structure and the manner that these processes represent. This paper attempts to review the related literature concerning sediment transport modelling in shallow waters. A classification based on the representational processes of the soil erosion and sediment transport models (empirical, conceptual, physical and hybrid) is adopted, and the commonly-used models and their characteristics are listed. This review is expected to be of interest to researchers and soil and water conservation managers who are working on erosion and sediment transport phenomena in shallow waters. The paper format should be helpful for practitioners to identify and generally characterize the types of available models, their strengths and their basic scope of applicability.
Integrated design approach of the pebble bed modular using models
International Nuclear Information System (INIS)
Venter, P.J.
2005-01-01
The Pebble Bed Modular Reactor (PBMR) is the first pebble bed reactor that will be utilised in a high temperature direct Brayton cycle configuration. This implies that there are a number of unique features in the PBMR that extend from the German experience base. One of the challenges in the design of the PBMR is managing the integrated design process between the designers, the physicists and the analysts. This integrated design process is managed through model-based development work. Three-dimensional CAD models are constructed of the components and parts in the reactor. From the CAD models, CFD models, neutronic models, shielding models, FEM models and other thermodynamic models are derived. These models range from very simple models to extremely detailed and complex models. The models are used in legacy software as well as commercial off-the-shelf software. The different models are also used in code-to-code comparisons to verify the results. This paper will briefly discuss the different models and the interaction between the models, showing the iterative design process that is used in the development of the reactor at PBMR. (author)
A Knowledge Model Sharing Based Approach to Privacy-Preserving Data Mining
Hongwei Tian; Weining Zhang; Shouhuai Xu; Patrick Sharkey
2012-01-01
Privacy-preserving data mining (PPDM) is an important problem and is currently studied in three approaches: the cryptographic approach, the data publishing, and the model publishing. However, each of these approaches has some problems. The cryptographic approach does not protect privacy of learned knowledge models and may have performance and scalability issues. The data publishing, although is popular, may suffer from too much utility loss for certain types of data mining applications. The m...
Biotic interactions in the face of climate change: a comparison of three modelling approaches.
Directory of Open Access Journals (Sweden)
Anja Jaeschke
Full Text Available Climate change is expected to alter biotic interactions, and may lead to temporal and spatial mismatches of interacting species. Although the importance of interactions for climate change risk assessments is increasingly acknowledged in observational and experimental studies, biotic interactions are still rarely incorporated in species distribution models. We assessed the potential impacts of climate change on the obligate interaction between Aeshna viridis and its egg-laying plant Stratiotes aloides in Europe, based on an ensemble modelling technique. We compared three different approaches for incorporating biotic interactions in distribution models: (1 We separately modelled each species based on climatic information, and intersected the future range overlap ('overlap approach'. (2 We modelled the potential future distribution of A. viridis with the projected occurrence probability of S. aloides as further predictor in addition to climate ('explanatory variable approach'. (3 We calibrated the model of A. viridis in the current range of S. aloides and multiplied the future occurrence probabilities of both species ('reference area approach'. Subsequently, all approaches were compared to a single species model of A. viridis without interactions. All approaches projected a range expansion for A. viridis. Model performance on test data and amount of range gain differed depending on the biotic interaction approach. All interaction approaches yielded lower range gains (up to 667% lower than the model without interaction. Regarding the contribution of algorithm and approach to the overall uncertainty, the main part of explained variation stems from the modelling algorithm, and only a small part is attributed to the modelling approach. The comparison of the no-interaction model with the three interaction approaches emphasizes the importance of including obligate biotic interactions in projective species distribution modelling. We recommend the use of
A Csup(*)-algebra approach to the Schwinger model
International Nuclear Information System (INIS)
Carey, A.L.; Hurst, C.A.
1981-01-01
If cutoffs are introduced then existing results in the literature show that the Schwinger model is dynamically equivalent to a boson model with quadratic Hamiltonian. However, the process of quantising the Schwinger model destroys local gauge invariance. Gauge invariance is restored by the addition of a counterterm, which may be seen as a finite renormalisation, whereupon the Schwinger model becomes dynamically equivalent to a linear boson gauge theory. This linear model is exactly soluble. We find that different treatments of the supplementary (i.e. Lorentz) condition lead to boson models with rather different properties. We choose one model and construct, from the gauge invariant subalgebra, a class of inequivalent charge sectors. We construct sectors which coincide with those found by Lowenstein and Swieca for the Schwinger model. A reconstruction of the Hilbert space on which the Schwinger model exists is described and fermion operators on this space are defined. (orig.)
The workshop on ecosystems modelling approaches for South ...
African Journals Online (AJOL)
for South African fisheries management, at which this ... considerable data collection and complex analysis at not insubstantial cost. ..... The simulation approaches in terms of accounting for uncertainty used in the Revised Management ...
Experimental Validation of Various Temperature Modells for Semi-Physical Tyre Model Approaches
Hackl, Andreas; Scherndl, Christoph; Hirschberg, Wolfgang; Lex, Cornelia
2017-10-01
With increasing level of complexity and automation in the area of automotive engineering, the simulation of safety relevant Advanced Driver Assistance Systems (ADAS) leads to increasing accuracy demands in the description of tyre contact forces. In recent years, with improvement in tyre simulation, the needs for coping with tyre temperatures and the resulting changes in tyre characteristics are rising significantly. Therefore, experimental validation of three different temperature model approaches is carried out, discussed and compared in the scope of this article. To investigate or rather evaluate the range of application of the presented approaches in combination with respect of further implementation in semi-physical tyre models, the main focus lies on the a physical parameterisation. Aside from good modelling accuracy, focus is held on computational time and complexity of the parameterisation process. To evaluate this process and discuss the results, measurements from a Hoosier racing tyre 6.0 / 18.0 10 LCO C2000 from an industrial flat test bench are used. Finally the simulation results are compared with the measurement data.
A Boolean Approach to Airline Business Model Innovation
DEFF Research Database (Denmark)
Hvass, Kristian Anders
Research in business model innovation has identified its significance in creating a sustainable competitive advantage for a firm, yet there are few empirical studies identifying which combination of business model activities lead to success and therefore deserve innovative attention. This study...... analyzes the business models of North America low-cost carriers from 2001 to 2010 using a Boolean minimization algorithm to identify which combinations of business model activities lead to operational profitability. The research aim is threefold: complement airline literature in the realm of business model...... innovation, introduce Boolean minimization methods to the field, and propose alternative business model activities to North American carriers striving for positive operating results....
Fuzzy Investment Portfolio Selection Models Based on Interval Analysis Approach
Directory of Open Access Journals (Sweden)
Haifeng Guo
2012-01-01
Full Text Available This paper employs fuzzy set theory to solve the unintuitive problem of the Markowitz mean-variance (MV portfolio model and extend it to a fuzzy investment portfolio selection model. Our model establishes intervals for expected returns and risk preference, which can take into account investors' different investment appetite and thus can find the optimal resolution for each interval. In the empirical part, we test this model in Chinese stocks investment and find that this model can fulfill different kinds of investors’ objectives. Finally, investment risk can be decreased when we add investment limit to each stock in the portfolio, which indicates our model is useful in practice.
Skersys, Tomas; Butleris, Rimantas; Kapocius, Kestutis
2013-10-01
Approaches for the analysis and specification of business vocabularies and rules are very relevant topics in both Business Process Management and Information Systems Development disciplines. However, in common practice of Information Systems Development, the Business modeling activities still are of mostly empiric nature. In this paper, basic aspects of the approach for business vocabularies' semi-automated extraction from business process models are presented. The approach is based on novel business modeling-level OMG standards "Business Process Model and Notation" (BPMN) and "Semantics for Business Vocabularies and Business Rules" (SBVR), thus contributing to OMG's vision about Model-Driven Architecture (MDA) and to model-driven development in general.
Static models, recursive estimators and the zero-variance approach
Rubino, Gerardo
2016-01-01
When evaluating dependability aspects of complex systems, most models belong to the static world, where time is not an explicit variable. These models suffer from the same problems than dynamic ones (stochastic processes), such as the frequent
Intelligence and the brain: a model-based approach
Kievit, R.A.; van Rooijen, H.; Wicherts, J.M.; Waldorp, L.J.; Kan, K.-J.; Scholte, H.S.; Borsboom, D.
2012-01-01
Various biological correlates of general intelligence (g) have been reported. Despite this, however, the relationship between neurological measurements and g is not fully clear. We use structural equation modeling to model the relationship between behavioral Wechsler Adult Intelligence Scale (WAIS)
A comparison of various modelling approaches applied to Cholera ...
African Journals Online (AJOL)
linear models, ARIMA time series modelling, and dynamic regression are ... to certain environmental parameters, and to investigate the feasibility of .... in the SSA literature, the term noise is used to refer to both stochastic noise, as well as.
Comparison of various modelling approaches applied to cholera case data
CSIR Research Space (South Africa)
Van Den Bergh, F
2008-06-01
Full Text Available cross-wavelet technique, which is used to compute lead times for co-varying variables, and suggests transformations that enhance co-varying behaviour. Several statistical modelling techniques, including generalised linear models, ARIMA time series...
Cost model validation: a technical and cultural approach
Hihn, J.; Rosenberg, L.; Roust, K.; Warfield, K.
2001-01-01
This paper summarizes how JPL's parametric mission cost model (PMCM) has been validated using both formal statistical methods and a variety of peer and management reviews in order to establish organizational acceptance of the cost model estimates.
Data-Driven Photovoltaic System Modeling Based on Nonlinear System Identification
Directory of Open Access Journals (Sweden)
Ayedh Alqahtani
2016-01-01
Full Text Available Solar photovoltaic (PV energy sources are rapidly gaining potential growth and popularity compared to conventional fossil fuel sources. As the merging of PV systems with existing power sources increases, reliable and accurate PV system identification is essential, to address the highly nonlinear change in PV system dynamic and operational characteristics. This paper deals with the identification of a PV system characteristic with a switch-mode power converter. Measured input-output data are collected from a real PV panel to be used for the identification. The data are divided into estimation and validation sets. The identification methodology is discussed. A Hammerstein-Wiener model is identified and selected due to its suitability to best capture the PV system dynamics, and results and discussion are provided to demonstrate the accuracy of the selected model structure.
Identification of a parametric, discrete-time model of ankle stiffness.
Guarin, Diego L; Jalaleddini, Kian; Kearney, Robert E
2013-01-01
Dynamic ankle joint stiffness defines the relationship between the position of the ankle and the torque acting about it and can be separated into intrinsic and reflex components. Under stationary conditions, intrinsic stiffness can described by a linear second order system while reflex stiffness is described by Hammerstein system whose input is delayed velocity. Given that reflex and intrinsic torque cannot be measured separately, there has been much interest in the development of system identification techniques to separate them analytically. To date, most methods have been nonparametric and as a result there is no direct link between the estimated parameters and those of the stiffness model. This paper presents a novel algorithm for identification of a discrete-time model of ankle stiffness. Through simulations we show that the algorithm gives unbiased results even in the presence of large, non-white noise. Application of the method to experimental data demonstrates that it produces results consistent with previous findings.
An Analytics Approach to Adaptive Maturity Models using Organizational Characteristics
Baars, T.; Mijnhardt, F.; Vlaanderen, K.; Spruit, M.
2016-01-01
Ever since the first incarnations of maturity models, critics have voiced several concerns with these frameworks. Indeed, a lack of model fit and oversimplification of the real world can be attributed to the rigidity of these models, which assumes that each organization that uses the framework is
A Structural Equation Approach to Models with Spatial Dependence
Oud, Johan H. L.; Folmer, Henk
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
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
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
Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach
Klauer, Karl Christoph
2010-01-01
Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…
Modeling of hydrodynamic cavitation reactors: a unified approach
Moholkar, V.S.; Pandit, A.B.
2001-01-01
An attempt has been made to present a unified theoretical model for the cavitating flow in a hydrodynamic cavitation reactor using the nonlinear continuum mixture model for two-phase flow as the basis. This model has been used to describe the radial motion of bubble in the cavitating flow in two
Modeling HIV-1 intracellular replication: two simulation approaches
Zarrabi, N.; Mancini, E.; Tay, J.; Shahand, S.; Sloot, P.M.A.
2010-01-01
Many mathematical and computational models have been developed to investigate the complexity of HIV dynamics, immune response and drug therapy. However, there are not many models which consider the dynamics of virus intracellular replication at a single level. We propose a model of HIV intracellular
Adopting a Models-Based Approach to Teaching Physical Education
Casey, Ashley; MacPhail, Ann
2018-01-01
Background: The popularised notion of models-based practice (MBP) is one that focuses on the delivery of a model, e.g. Cooperative Learning, Sport Education, Teaching Personal and Social Responsibility, Teaching Games for Understanding. Indeed, while an abundance of research studies have examined the delivery of a single model and some have…
Self-consistent approach for neutral community models with speciation
Haegeman, Bart; Etienne, Rampal S.
Hubbell's neutral model provides a rich theoretical framework to study ecological communities. By incorporating both ecological and evolutionary time scales, it allows us to investigate how communities are shaped by speciation processes. The speciation model in the basic neutral model is
Exploring component-based approaches in forest landscape modeling
H. S. He; D. R. Larsen; D. J. Mladenoff
2002-01-01
Forest management issues are increasingly required to be addressed in a spatial context, which has led to the development of spatially explicit forest landscape models. The numerous processes, complex spatial interactions, and diverse applications in spatial modeling make the development of forest landscape models difficult for any single research group. New...
Optimum workforce-size model using dynamic programming approach
African Journals Online (AJOL)
This paper presents an optimum workforce-size model which determines the minimum number of excess workers (overstaffing) as well as the minimum total recruitment cost during a specified planning horizon. The model is an extension of other existing dynamic programming models for manpower planning in the sense ...
Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction
Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro
Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.