Models for setting ATM parameter values
DEFF Research Database (Denmark)
Blaabjerg, Søren; Gravey, A.; Romæuf, L.
1996-01-01
essential to set traffic characteristic values that are relevant to the considered cell stream, and that ensure that the amount of non-conforming traffic is small. Using a queueing model representation for the GCRA formalism, several methods are available for choosing the traffic characteristics. This paper......In ATM networks, a user should negotiate at connection set-up a traffic contract which includes traffic characteristics and requested QoS. The traffic characteristics currently considered are the Peak Cell Rate, the Sustainable Cell Rate, the Intrinsic Burst Tolerance and the Cell Delay Variation...... (CDV) tolerance(s). The values taken by these traffic parameters characterize the so-called ''Worst Case Traffic'' that is used by CAC procedures for accepting a new connection and allocating resources to it. Conformance to the negotiated traffic characteristics is defined, at the ingress User...
A New Five-Parameter Fréchet Model for Extreme Values
Directory of Open Access Journals (Sweden)
Muhammad Ahsan ul Haq
2017-09-01
Full Text Available A new five parameter Fréchet model for Extreme Values was proposed and studied. Various mathematical properties including moments, quantiles, and moment generating function were derived. Incomplete moments and probability weighted moments were also obtained. The maximum likelihood method was used to estimate the model parameters. The flexibility of the derived model was accessed using two real data set applications.
Radcliffe, D E; Lin, Z; Risse, L M; Romeis, J J; Jackson, C R
2009-01-01
Lake Allatoona is a large reservoir north of Atlanta, GA, that drains an area of about 2870 km2 scheduled for a phosphorus (P) total maximum daily load (TMDL). The Soil and Water Assessment Tool (SWAT) model has been widely used for watershed-scale modeling of P, but there is little guidance on how to estimate P-related parameters, especially those related to in-stream P processes. In this paper, methods are demonstrated to individually estimate SWAT soil-related P parameters and to collectively estimate P parameters related to stream processes. Stream related parameters were obtained using the nutrient uptake length concept. In a manner similar to experiments conducted by stream ecologists, a small point source is simulated in a headwater sub-basin of the SWAT models, then the in-stream parameter values are adjusted collectively to get an uptake length of P similar to the values measured in the streams in the region. After adjusting the in-stream parameters, the P uptake length estimated in the simulations ranged from 53 to 149 km compared to uptake lengths measured by ecologists in the region of 11 to 85 km. Once the a priori P-related parameter set was developed, the SWAT models of main tributaries to Lake Allatoona were calibrated for daily transport. Models using SWAT P parameters derived from the methods in this paper outperformed models using default parameter values when predicting total P (TP) concentrations in streams during storm events and TP annual loads to Lake Allatoona.
Site-specific parameter values for the Nuclear Regulatory Commission's food pathway dose model
International Nuclear Information System (INIS)
Hamby, D.M.
1992-01-01
Routine operations at the Savannah River Site (SRS) in Western South Carolina result in radionuclide releases to the atmosphere and to the Savannah River. The resulting radiation doses to the off-site maximum individual and the off-site population within 80 km of the SRS are estimated on a yearly basis. These estimates are currently generated using dose models prescribed for the commercial nuclear power industry by the Nuclear Regulatory Commission (NRC). The NRC provides default values for dose-model parameters for facilities without resources to develop site-specific values. A survey of land- and water-use characteristics for the Savannah River area has been conducted to determine site-specific values for water recreation, consumption, and agricultural parameters used in the NRC Regulatory Guide 1.109 (1977) dosimetric models. These site parameters include local characteristics of meat, milk, and vegetable production; recreational and commercial activities on the Savannah River; and meat, milk, vegetable, and seafood consumption rates. This paper describes how parameter data were obtained at the Savannah River Site and the impacts of such data on off-site dose. Dose estimates using site-specific parameter values are compared to estimates using the NRC default values
Parameter values for the long-term nuclear waste management food chain model LIMCAL
International Nuclear Information System (INIS)
Zach, Reto.
1982-09-01
Eighteen parameters of LIMCAL, a comprehensive food chain model for predicting ICRP 26 50-year committed effective dose equivalents to man due to long-term nuclear waste management are reviewed. The parameters are: soil bulk density, plowlayer depth, soil surface layer depth, resusupension factor, atmospheric dust load, deposition velocity, plant interception fraction, plant environmental half-time, translocation factor, time of above-ground exposure, plant yield, holdup time, animals' feed consumption rate, animals' water consumption rate, man's water consumption rate, food type calorie conversion factors, man's total caloric intake rate and food type calorie fractions. LIMCAL has both traditional and unique parameters. The former occur in most of the currently used assessment models for nuclear installations, whereas the latter do not. For each of the parameters of LIMCAL, a suitable generic value for long-term nuclear waste management was determined. Thus, the general literature and the values currently used or recommended by various agencies were reviewed
Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models.
Cuba, Christian E; Valle, Alexander R; Ayala-Charca, Giancarlo; Villota, Elizabeth R; Coronado, Alberto M
2015-09-01
Biomolecular networks that present oscillatory behavior are ubiquitous in nature. While some design principles for robust oscillations have been identified, it is not well understood how these oscillations are affected when the kinetic parameters are constantly changing or are not precisely known, as often occurs in cellular environments. Many models of diverse complexity level, for systems such as circadian rhythms, cell cycle or the p53 network, have been proposed. Here we assess the influence of hundreds of different parameter sets on the sensitivities of two configurations of a well-known oscillatory system, the p53 core network. We show that, for both models and all parameter sets, the parameter related to the p53 positive feedback, i.e. self-promotion, is the only one that presents sizeable sensitivities on extrema, periods and delay. Moreover, varying the parameter set values to change the dynamical characteristics of the response is more restricted in the simple model, whereas the complex model shows greater tunability. These results highlight the importance of the presence of specific network patterns, in addition to the role of parameter values, when we want to characterize oscillatory biochemical systems.
Recommended Parameter Values for GENII Modeling of Radionuclides in Routine Air and Water Releases
Energy Technology Data Exchange (ETDEWEB)
Snyder, Sandra F. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Arimescu, Carmen [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Napier, Bruce A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hay, Tristan R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2012-11-01
The GENII v2 code is used to estimate dose to individuals or populations from the release of radioactive materials into air or water. Numerous parameter values are required for input into this code. User-defined parameters cover the spectrum from chemical data, meteorological data, agricultural data, and behavioral data. This document is a summary of parameter values that reflect conditions in the United States. Reasonable regional and age-dependent data is summarized. Data availability and quality varies. The set of parameters described address scenarios for chronic air emissions or chronic releases to public waterways. Considerations for the special tritium and carbon-14 models are briefly addressed. GENIIv2.10.0 is the current software version that this document supports.
Uncertainty analyses of the calibrated parameter values of a water quality model
Rode, M.; Suhr, U.; Lindenschmidt, K.-E.
2003-04-01
For river basin management water quality models are increasingly used for the analysis and evaluation of different management measures. However substantial uncertainties exist in parameter values depending on the available calibration data. In this paper an uncertainty analysis for a water quality model is presented, which considers the impact of available model calibration data and the variance of input variables. The investigation was conducted based on four extensive flowtime related longitudinal surveys in the River Elbe in the years 1996 to 1999 with varying discharges and seasonal conditions. For the model calculations the deterministic model QSIM of the BfG (Germany) was used. QSIM is a one dimensional water quality model and uses standard algorithms for hydrodynamics and phytoplankton dynamics in running waters, e.g. Michaelis Menten/Monod kinetics, which are used in a wide range of models. The multi-objective calibration of the model was carried out with the nonlinear parameter estimator PEST. The results show that for individual flow time related measuring surveys very good agreements between model calculation and measured values can be obtained. If these parameters are applied to deviating boundary conditions, substantial errors in model calculation can occur. These uncertainties can be decreased with an increased calibration database. More reliable model parameters can be identified, which supply reasonable results for broader boundary conditions. The extension of the application of the parameter set on a wider range of water quality conditions leads to a slight reduction of the model precision for the specific water quality situation. Moreover the investigations show that highly variable water quality variables like the algal biomass always allow a smaller forecast accuracy than variables with lower coefficients of variation like e.g. nitrate.
Systematically too low values of the cranking model collective inertia parameters
International Nuclear Information System (INIS)
Dudek, I.; Dudek, W.; Lukasiak-Ruchowska, E.; Skalski, I.
1980-01-01
Deformed Nilsson and Woods-Saxon potentials were employed for generating single particle states used henceforth for calculating the inertia tensor (cranking model and monopole pairing) and the collective energy surfaces (Strutinsky method). The deformation was parametrized in terms of quadrupole and hexadecapole degrees of freedom. The classical energy expression obtained from the inertia tensor and energy surfaces was quantized and the resulting stationary Schroedinger equation was solved using the approximate method. The second Isup(π) = 0 + 2 collective level energies were calculated for the Rare Earth and Actinide nuclei and the results compared with the experimental data. The vibrational level energies agree with the experimental ones much better for spherical nuclei for both single particle potentials; the discrepancies for deformed nuclei overestimate the experimental results by roughly a factor of two. It is argued that coupling of the axially symmetric quadrupole degrees of freedom to non-axial and hexadecapole ones does not affect the conclusions about systematically too low mass parameter values. The alternative explanation of the systematic deviations from the 0 + 2 level energies could be a systematically too high stiffness of the energy surfaces obrained with the Strutinsky method. (orig.)
International Nuclear Information System (INIS)
Baseilhac, P.; Fateev, V.A.
1998-01-01
We calculate the vacuum expectation values of local fields for the two-parameter family of integrable field theories introduced and studied by Fateev (1996). Using this result we propose an explicit expression for the vacuum expectation values of local operators in parafermionic sine-Gordon models and in integrable perturbed SU(2) coset conformal field theories. (orig.)
New Values of Cross-Talk Parameters for Twisted Pair Model
Milos Kozak; Lukas Cepa; Jiri Vodrazka
2010-01-01
Near-end Crosstalk (NEXT) and Far-end Crosstalk (FEXT) of unshielded twisted pair (UTP) cable are the main factors limiting the information capacity in data transmission. Crosstalk depends mostly on the frequency. Frequency dependent transfer functions and crosstalk attenuation may be obtained by measurement, but for the analytical description of the transmission channel's parameters is useful to define functions modelling the crosstalk. The paper describes the measuri...
Sensitivity of precipitation to parameter values in the community atmosphere model version 5
Energy Technology Data Exchange (ETDEWEB)
Johannesson, Gardar; Lucas, Donald; Qian, Yun; Swiler, Laura Painton; Wildey, Timothy Michael
2014-03-01
One objective of the Climate Science for a Sustainable Energy Future (CSSEF) program is to develop the capability to thoroughly test and understand the uncertainties in the overall climate model and its components as they are being developed. The focus on uncertainties involves sensitivity analysis: the capability to determine which input parameters have a major influence on the output responses of interest. This report presents some initial sensitivity analysis results performed by Lawrence Livermore National Laboratory (LNNL), Sandia National Laboratories (SNL), and Pacific Northwest National Laboratory (PNNL). In the 2011-2012 timeframe, these laboratories worked in collaboration to perform sensitivity analyses of a set of CAM5, 2° runs, where the response metrics of interest were precipitation metrics. The three labs performed their sensitivity analysis (SA) studies separately and then compared results. Overall, the results were quite consistent with each other although the methods used were different. This exercise provided a robustness check of the global sensitivity analysis metrics and identified some strongly influential parameters.
Li, Yi Zhe; Zhang, Ting Long; Liu, Qiu Yu; Li, Ying
2018-01-01
The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation
Parameter values for epidemiological models of foot-and-mouth disease in swine
Directory of Open Access Journals (Sweden)
Amy C Kinsley
2016-06-01
Full Text Available In the event of a foot-and-mouth disease (FMD incursion, response strategies are required to control, contain and eradicate the pathogen as efficiently as possible. Infectious disease simulation models are widely used tools that mimic disease dispersion in a population and that can be useful in the design and support of prevention and mitigation activities. However, there are often gaps in evidence-based research to supply models with quantities that are necessary to accurately reflect the system of interest. The objective of this study was to quantify values associated with the duration of the stages of FMD infection (latent period, subclinical period, incubation period, and duration of infection, probability of transmission (within-herd and between-herd via spatial spread, and diagnosis of a vesicular disease within a herd using a meta-analysis of the peer-reviewed literature and expert opinion. The latent period ranged from 1 to 7 days and incubation period ranged from 1 to 9 day; both were influenced by strain. In contrast, the subclinical period ranged from 0 to 6 days and was influenced by sampling method only. The duration of infection ranged from 1 to 10 days. The probability of spatial spread between an infected and fully susceptible swine farm was estimated as greatest within 5 km of the infected farm, highlighting the importance of possible long-range transmission through the movement of infected animals. Lastly, while most swine practitioners are confident in their ability to detect a vesicular disease in an average sized swine herd, a small proportion expect that up to half of the herd would need to show clinical signs before detection via passive surveillance would occur. The results of this study will be useful in within- and between-herd simulation models to develop efficient response strategies in the event an FMD in swine populations of disease-free countries or regions.
International Nuclear Information System (INIS)
Karlsson, Sara; Bergstroem, Ulla
2002-05-01
In this report the element and nuclide specific parameter values used in the biospheric models of the safety assessments SR 97 and SAFE are presented. The references used are presented and where necessary the process of estimation of data is described. The parameters treated in this report are distribution coefficients in soil, organic soil and suspended matter in freshwater and brackish water, root uptake factors for pasturage, cereals, root crops and vegetables, bioaccumulation factors for freshwater fish, brackish water fish, freshwater invertebrates and marine water plants, transfer coefficients for transfer to milk and meat, translocation factors and dose coefficients for external exposure, ingestion (age-dependent values) and inhalation (age-dependent values). The radionuclides treated are those which could be of interest in the two safety assessments. Physical data such as half-lives and type of decay are also presented
Energy Technology Data Exchange (ETDEWEB)
Karlsson, Sara; Bergstroem, Ulla [Studsvik Eco and Safety AB, Nykoeping (Sweden)
2002-05-01
In this report the element and nuclide specific parameter values used in the biospheric models of the safety assessments SR 97 and SAFE are presented. The references used are presented and where necessary the process of estimation of data is described. The parameters treated in this report are distribution coefficients in soil, organic soil and suspended matter in freshwater and brackish water, root uptake factors for pasturage, cereals, root crops and vegetables, bioaccumulation factors for freshwater fish, brackish water fish, freshwater invertebrates and marine water plants, transfer coefficients for transfer to milk and meat, translocation factors and dose coefficients for external exposure, ingestion (age-dependent values) and inhalation (age-dependent values). The radionuclides treated are those which could be of interest in the two safety assessments. Physical data such as half-lives and type of decay are also presented.
Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Caubel, A.; Huth, N.; Marin, F.; Martiné, J.-F.
2014-06-01
Agro-land surface models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugarcane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte Carlo sampling method associated with the calculation of partial ranked correlation coefficients is used to quantify the sensitivity of harvested biomass to input
Directory of Open Access Journals (Sweden)
Ingo W Nader
Full Text Available Parameters of the two-parameter logistic model are generally estimated via the expectation-maximization algorithm, which improves initial values for all parameters iteratively until convergence is reached. Effects of initial values are rarely discussed in item response theory (IRT, but initial values were recently found to affect item parameters when estimating the latent distribution with full non-parametric maximum likelihood. However, this method is rarely used in practice. Hence, the present study investigated effects of initial values on item parameter bias and on recovery of item characteristic curves in BILOG-MG 3, a widely used IRT software package. Results showed notable effects of initial values on item parameters. For tighter convergence criteria, effects of initial values decreased, but item parameter bias increased, and the recovery of the latent distribution worsened. For practical application, it is advised to use the BILOG default convergence criterion with appropriate initial values when estimating the latent distribution from data.
Amarti, Z.; Nurkholipah, N. S.; Anggriani, N.; Supriatna, A. K.
2018-03-01
Predicting the future of population number is among the important factors that affect the consideration in preparing a good management for the population. This has been done by various known method, one among them is by developing a mathematical model describing the growth of the population. The model usually takes form in a differential equation or a system of differential equations, depending on the complexity of the underlying properties of the population. The most widely used growth models currently are those having a sigmoid solution of time series, including the Verhulst logistic equation and the Gompertz equation. In this paper we consider the Allee effect of the Verhulst’s logistic population model. The Allee effect is a phenomenon in biology showing a high correlation between population size or density and the mean individual fitness of the population. The method used to derive the solution is the Runge-Kutta numerical scheme, since it is in general regarded as one among the good numerical scheme which is relatively easy to implement. Further exploration is done via the fuzzy theoretical approach to accommodate the impreciseness of the initial values and parameters in the model.
The strong prognostic value of KELIM, a model-based parameter from CA 125 kinetics in ovarian cancer
DEFF Research Database (Denmark)
You, Benoit; Colomban, Olivier; Heywood, Mark
2013-01-01
Unexpected results were recently reported about the poor surrogacy of Gynecologic Cancer Intergroup (GCIG) defined CA-125 response in recurrent ovarian cancer (ROC) patients. Mathematical modeling may help describe CA-125 decline dynamically and discriminate prognostic kinetic parameters....
Shuguang Liua; Pamela Anderson; Guoyi Zhoud; Boone Kauffman; Flint Hughes; David Schimel; Vicente Watson; Joseph. Tosi
2008-01-01
Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in...
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)
DEVELOPMENT OF VADOSE ZONE HYDRAULIC PARAMETER VALUES
International Nuclear Information System (INIS)
ROGERS PM
2008-01-01
Several approaches have been developed to establish a relation between the soil-moisture retention curve and readily available soil properties. Those relationships are referred to as pedotransfer functions. Described in this paper are the rationale, approach, and corroboration for use of a nonparametric pedotransfer function for the estimation of soil hydraulic-parameter values at the yucca Mountain area in Nevada for simulations of net infiltration. This approach, shown to be applicable for use at Yucca Mountain, is also applicable for use at the Hanford Site where the underlying data were collected
You, Benoit; Fronton, Ludivine; Boyle, Helen; Droz, Jean-Pierre; Girard, Pascal; Tranchand, Brigitte; Ribba, Benjamin; Tod, Michel; Chabaud, Sylvie; Coquelin, Henri; Fléchon, Aude
2010-08-01
The early decline profile of alpha-fetoprotein (AFP) and human chorionic gonadotropin (hCG) in patients with nonseminomatous germ cell tumors (NSGCT) treated with chemotherapy may be related to the risk of relapse. We assessed the predictive values of areas under the curve of hCG (AUC(hCG)) and AFP (AUC(AFP)) of modeled concentration-time equations on progression-free survival (PFS). Single-center retrospective analysis of hCG and AFP time-points from 65 patients with IGCCCG intermediate-poor risk NSGCT treated with 4 cycles of bleomycin-etoposide-cisplatin (BEP). To determine AUC(hCG) and AUC(AFP) for D0-D42, AUCs for D0-D7 were calculated using the trapezoid rule and AUCs for D7-D42 were calculated using the mathematic integrals of equations modeled with NONMEM. Combining AUC(AFP) and AUC(hCG) enabled us to define 2 predictive groups: namely, patients with favorable and unfavorable AUC(AFP-hCG). Survival analyses and ROC curves assessed the predictive values of AUC(AFP-hCG) groups regarding progression-free survival (PFS) and compared them with those of half-life (HL) and time-to-normalization (TTN). Mono-exponential models best fit the patterns of marker decreases. Patients with a favorable AUC(AFP-hCG) had a significantly better PFS (100% vs 71.5%, P = .014). ROC curves confirmed the encouraging predictive accuracy of AUC(AFP-hCG) against HL or TTN regarding progression risk (ROC AUCs = 79.6 vs 71.9 and 70.2 respectively). Because of the large number of patients with missing data, multivariate analysis could not be performed. AUC(AFP-hCG) is a dynamic parameter characterizing tumor marker decline in patients with NSGCT during BEP treatment. Its value as a promising predictive factor should be validated. Copyright 2010 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Vinu Sherimon
2017-07-01
Full Text Available Ensuring the quality of food, particularly seafood has increasingly become an important issue nowadays. Quality Management Systems empower any organization to identify, measure, control and improve the quality of the products manufactured that will eventually lead to improved business performance. With the advent of new technologies, now intelligent systems are being developed. To ensure the quality of seafood, an ontology based seafood quality analyzer and miner (ONTO SQAM model is proposed. The knowledge is represented using ontology. The domain concepts are defined using ontology. This paper presents the initial part of the proposed model – the analysis of quality test parameter values. Two algorithms are proposed to do the analysis – Comparison Algorithm and Data Store Updater algorithm. The algorithms ensure that the values of various quality tests are in the acceptable range. The real data sets taken from different seafood companies in Kerala, India, and validated by the Marine Product Export Development Authority of India (MPEDA are used for the experiments. The performance of the algorithms is evaluated using standard performance metrics such as precision, recall, and accuracy. The results obtained show that all the three measures achieved good results.
Parameter Estimation of Partial Differential Equation Models.
Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab
2013-01-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.
International Nuclear Information System (INIS)
Anon
2011-01-01
Occupational injuries, accidents, trips of equipment, emergencies, and idle times represent a loss from each megawatt hour which we could have supplied to the network, or other costs related to settlement or compensation for damages. All of it can be caused by short lack of attention while doing a routine job, ignoring safety indicators, and rules. Such behaviour would not be a characteristic of a professional. People working at the nuclear power plants are the first ones to learn about the Values and Behaviour Model. (author)
Polychronakos fractional statistics with a complex-valued parameter
International Nuclear Information System (INIS)
Rovenchak, Andrij
2012-01-01
A generalization of quantum statistics is proposed in a fashion similar to the suggestion of Polychronakos [Phys. Lett. B 365, 202 (1996)] with the parameter α varying between −1 (fermionic case) and +1 (bosonic case). However, unlike the original formulation, it is suggested that intermediate values are located on the unit circle in the complex plane. In doing so one can avoid the case α = 0 corresponding to the Boltzmann statistics, which is not a quantum one. The limits of α → +1 and α → −1 reproducing small deviations from the Bose and Fermi statistics, respectively, are studied in detail. The equivalence between the statistics parameter and a possible dissipative part of the excitation spectrum is established. The case of a non-conserving number of excitations is analyzed. It is defined from the condition that the real part of the chemical potential equals zero. Thermodynamic quantities of a model system of two-dimensional harmonic oscillators are calculated.
Application of lumped-parameter models
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Liingaard, Morten
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...
Consistent Stochastic Modelling of Meteocean Design Parameters
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Sterndorff, M. J.
2000-01-01
Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Model parameter updating using Bayesian networks
International Nuclear Information System (INIS)
Treml, C.A.; Ross, Timothy J.
2004-01-01
This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.
Photovoltaic module parameters acquisition model
Energy Technology Data Exchange (ETDEWEB)
Cibira, Gabriel, E-mail: cibira@lm.uniza.sk; Koščová, Marcela, E-mail: mkoscova@lm.uniza.sk
2014-09-01
Highlights: • Photovoltaic five-parameter model is proposed using Matlab{sup ®} and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.
Photovoltaic module parameters acquisition model
International Nuclear Information System (INIS)
Cibira, Gabriel; Koščová, Marcela
2014-01-01
Highlights: • Photovoltaic five-parameter model is proposed using Matlab ® and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model
Source term modelling parameters for Project-90
International Nuclear Information System (INIS)
Shaw, W.; Smith, G.; Worgan, K.; Hodgkinson, D.; Andersson, K.
1992-04-01
This document summarises the input parameters for the source term modelling within Project-90. In the first place, the parameters relate to the CALIBRE near-field code which was developed for the Swedish Nuclear Power Inspectorate's (SKI) Project-90 reference repository safety assessment exercise. An attempt has been made to give best estimate values and, where appropriate, a range which is related to variations around base cases. It should be noted that the data sets contain amendments to those considered by KBS-3. In particular, a completely new set of inventory data has been incorporated. The information given here does not constitute a complete set of parameter values for all parts of the CALIBRE code. Rather, it gives the key parameter values which are used in the constituent models within CALIBRE and the associated studies. For example, the inventory data acts as an input to the calculation of the oxidant production rates, which influence the generation of a redox front. The same data is also an initial value data set for the radionuclide migration component of CALIBRE. Similarly, the geometrical parameters of the near-field are common to both sub-models. The principal common parameters are gathered here for ease of reference and avoidance of unnecessary duplication and transcription errors. (au)
Analysis of Camera Parameters Value in Various Object Distances Calibration
International Nuclear Information System (INIS)
Yusoff, Ahmad Razali; Ariff, Mohd Farid Mohd; Idris, Khairulnizam M; Majid, Zulkepli; Setan, Halim; Chong, Albert K
2014-01-01
In photogrammetric applications, good camera parameters are needed for mapping purpose such as an Unmanned Aerial Vehicle (UAV) that encompassed with non-metric camera devices. Simple camera calibration was being a common application in many laboratory works in order to get the camera parameter's value. In aerial mapping, interior camera parameters' value from close-range camera calibration is used to correct the image error. However, the causes and effects of the calibration steps used to get accurate mapping need to be analyze. Therefore, this research aims to contribute an analysis of camera parameters from portable calibration frame of 1.5 × 1 meter dimension size. Object distances of two, three, four, five, and six meters are the research focus. Results are analyzed to find out the changes in image and camera parameters' value. Hence, camera calibration parameter's of a camera is consider different depend on type of calibration parameters and object distances
Model comparisons and genetic and environmental parameter ...
African Journals Online (AJOL)
arc
Model comparisons and genetic and environmental parameter estimates of growth and the ... breeding strategies and for accurate breeding value estimation. The objectives ...... Sci. 23, 72-76. Van Wyk, J.B., Fair, M.D. & Cloete, S.W.P., 2003.
Parameter Estimation for Thurstone Choice Models
Energy Technology Data Exchange (ETDEWEB)
Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-04-24
We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.
ECOS: values of parameters to be used for domestic animals
International Nuclear Information System (INIS)
Thorne, M.C.
1984-03-01
This report constitutes the database description for the domestic animals section of the biosphere code ECOS. Two categories of data are supplied, element-independent and element-dependent. The element-independent data comprise rates of food, water and soil consumption, inhalation rates and masses of animal tissues. The element-dependent data consist of f 1 (fractional gastrointestinal absorption), fsub(D) (fractional systematic deposition after inhalation) and NRF (weighted integrated retention function) values. All parameter values given are justified. (author)
Correlating substituent parameter values to electron transport properties of molecules
International Nuclear Information System (INIS)
Vedova-Brook, Natalie; Matsunaga, Nikita; Sohlberg, Karl
2004-01-01
There are a vast number of organic compounds that could be considered for use in molecular electronics. Because of this, the need for efficient and economical screening tools has emerged. We demonstrate that the substituent parameter values (σ), commonly found in advanced organic chemistry textbooks, correlate strongly with features of the charge migration process, establishing them as useful indicators of electronic properties. Specifically, we report that ab initio derived electronic charge transfer values for 16 different substituted aromatic molecules for molecular junctions correlate to the σ values with a correlation coefficient squared (R 2 ) of 0.863
The mobilisation model and parameter sensitivity
International Nuclear Information System (INIS)
Blok, B.M.
1993-12-01
In the PRObabillistic Safety Assessment (PROSA) of radioactive waste in a salt repository one of the nuclide release scenario's is the subrosion scenario. A new subrosion model SUBRECN has been developed. In this model the combined effect of a depth-dependent subrosion, glass dissolution, and salt rise has been taken into account. The subrosion model SUBRECN and the implementation of this model in the German computer program EMOS4 is presented. A new computer program PANTER is derived from EMOS4. PANTER models releases of radionuclides via subrosion from a disposal site in a salt pillar into the biosphere. For uncertainty and sensitivity analyses the new subrosion model Latin Hypercube Sampling has been used for determine the different values for the uncertain parameters. The influence of the uncertainty in the parameters on the dose calculations has been investigated by the following sensitivity techniques: Spearman Rank Correlation Coefficients, Partial Rank Correlation Coefficients, Standardised Rank Regression Coefficients, and the Smirnov Test. (orig./HP)
Systematic parameter inference in stochastic mesoscopic modeling
Energy Technology Data Exchange (ETDEWEB)
Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)
2017-02-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.
Diagnostic value of hematological parameters in patients with osteoarthritis
Directory of Open Access Journals (Sweden)
Serdar Hira
2017-03-01
Results: There were no significant differences in WBC, RDW, PLT, RPR levels between two groups. NLR and PLR values were significantly higher in the osteoarthritis group than in the control group. RBC, MPV and PDW values were significantly lower in the osteoarthritis group than in the control group (all . MPV and RBC were negatively correlated with ESR and CRP in osteoarthritis patients. Conclusion: Hematological inflammatory markers might be useful parameters that could be used in patients with osteoarthritis. [Cukurova Med J 2017; 42(1.000: 120-125
Models for estimating photosynthesis parameters from in situ production profiles
Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana
2017-12-01
The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of
Reference values of clinical chemistry and hematology parameters in rhesus monkeys (Macaca mulatta).
Chen, Younan; Qin, Shengfang; Ding, Yang; Wei, Lingling; Zhang, Jie; Li, Hongxia; Bu, Hong; Lu, Yanrong; Cheng, Jingqiu
2009-01-01
Rhesus monkey models are valuable to the studies of human biology. Reference values for clinical chemistry and hematology parameters of rhesus monkeys are required for proper data interpretation. Whole blood was collected from 36 healthy Chinese rhesus monkeys (Macaca mulatta) of either sex, 3 to 5 yr old. Routine chemistry and hematology parameters, and some special coagulation parameters including thromboelastograph and activities of coagulation factors were tested. We presented here the baseline values of clinical chemistry and hematology parameters in normal Chinese rhesus monkeys. These data may provide valuable information for veterinarians and investigators using rhesus monkeys in experimental studies.
DEFF Research Database (Denmark)
You, Benoit; Colomban, Olivier; Heywood, Mark
2011-01-01
Background: Although CA125 kinetic profiles may be related with relapse risk in ovarian cancer patients treated with chemotherapy, no reliable kinetic parameters have been reported. Mathematical modeling may help describe CA125 decline dynamically and determine parameters predictive of relapse....... Methods: Data from CALYPSO phase III trial data comparing 2 carboplatin-based regimens in ROC patients were analyzed. Based on population kinetic approach (Monolix software), a semi-mechanistic model was used to fit serum log (CA125) concentration-time profiles with following parameters: tumor growth rate...... the first 50 treatment days were tested regarding progression free survival (PFS) against other reported prognostic factors using Cox-models: treatment arm; platinum-free interval (PFI), metastatic site number, largest tumor size, elevated WBC and measurable disease. Results: The CA125 kinetics from 898...
Value encounters - Modeling and analyzing co-creation of value
Weigand, H.; Godart, C.; Gronau, N.; Sharma, S.; Canals, G.
2009-01-01
Recent marketing and management literature has introduced the concept of co-creation of value. Current value modeling approaches such as e3-value focus on the exchange of value rather than co-creation. In this paper, an extension to e3-value is proposed in the form of a “value encounter”. Value
Value encounters : Modelling and analyzing co-creation of value
Weigand, H.; Jayasinghe Arachchig, J.
2009-01-01
Recent marketing and management literature has introduced the concept of co-creation of value. Current value modeling approaches such as e3-value focus on the exchange of value rather than co-creation. In this paper, an extension to e3-value is proposed in the form of a “value encounter”. Value
DEVELOPMENT OF VADOSE-ZONE HYDRAULIC PARAMETER VALUES
Energy Technology Data Exchange (ETDEWEB)
ROGERS PM
2008-01-21
Several approaches have been developed to establish a relation between the soil-moisture retention curve and readily available soil properties. Those relationships are referred to as pedotransfer functions. Described in this paper are the rationale, approach, and corroboration for use of a nonparametric pedotransfer function for the estimation of soil hydraulic-parameter values at the yucca Mountain area in Nevada for simulations of net infiltration. This approach, shown to be applicable for use at Yucca Mountain, is also applicable for use at the Hanford Site where the underlying data were collected.
Directory of Open Access Journals (Sweden)
Mladenović Zorica
2006-01-01
Full Text Available In this paper different aspects of value-at-risk estimation are considered. Daily returns of CISCO, INTEL and NASDAQ stock indices are analyzed for period: September 1996 - September 2006. Methods that incorporate time varying variability and heavy tails of the empirical distributions of returns are implemented. The main finding of the paper is that standard econometric methods underestimate the value-at-risk parameter if heavy tails of the empirical distribution are not explicitly taken into account. .
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Maity, Arnab; Carroll, Raymond J.
2013-01-01
PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus
Brownian motion model with stochastic parameters for asset prices
Ching, Soo Huei; Hin, Pooi Ah
2013-09-01
The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.
Sensitivity of NTCP parameter values against a change of dose calculation algorithm
International Nuclear Information System (INIS)
Brink, Carsten; Berg, Martin; Nielsen, Morten
2007-01-01
Optimization of radiation treatment planning requires estimations of the normal tissue complication probability (NTCP). A number of models exist that estimate NTCP from a calculated dose distribution. Since different dose calculation algorithms use different approximations the dose distributions predicted for a given treatment will in general depend on the algorithm. The purpose of this work is to test whether the optimal NTCP parameter values change significantly when the dose calculation algorithm is changed. The treatment plans for 17 breast cancer patients have retrospectively been recalculated with a collapsed cone algorithm (CC) to compare the NTCP estimates for radiation pneumonitis with those obtained from the clinically used pencil beam algorithm (PB). For the PB calculations the NTCP parameters were taken from previously published values for three different models. For the CC calculations the parameters were fitted to give the same NTCP as for the PB calculations. This paper demonstrates that significant shifts of the NTCP parameter values are observed for three models, comparable in magnitude to the uncertainties of the published parameter values. Thus, it is important to quote the applied dose calculation algorithm when reporting estimates of NTCP parameters in order to ensure correct use of the models
Sun, T T; Liu, W H; Zhang, Y Q; Li, L H; Wang, R; Ye, Y Y
2017-08-01
Objective: To explore the differential between the value of dynamic contrast-enhanced MRI quantitative pharmacokinetic parameters and relative pharmacokinetic quantitative parameters in breast lesions. Methods: Retrospective analysis of 255 patients(262 breast lesions) who was obtained by clinical palpation , ultrasound or full-field digital mammography , and then all lessions were pathologically confirmed in Zhongda Hospital, Southeast University from May 2012 to May 2016. A 3.0 T MRI scanner was used to obtain the quantitative MR pharmacokinetic parameters: volume transfer constant (K(trans)), exchange rate constant (k(ep))and extravascular extracellular volume fraction (V(e)). And measured the quantitative pharmacokinetic parameters of normal glands tissues which on the same side of the same level of the lesions; and then calculated the value of relative pharmacokinetic parameters: rK(rans)、rk(ep) and rV(e).To explore the diagnostic value of two pharmacokinetic parameters in differential diagnosis of benign and malignant breast lesions using receiver operating curves and model of logistic regression. Results: (1)There were significant differences between benign lesions and malignant lesions in K(trans) and k(ep) ( t =15.489, 15.022, respectively, P 0.05). The areas under the ROC curve(AUC)of K(trans), k(ep) and V(e) between malignant and benign lesions were 0.933, 0.948 and 0.387, the sensitivity of K(trans), k(ep) and V(e) were 77.1%, 85.0%, 51.0% , and the specificity of K(trans), k(ep) and V(e) were 96.3%, 93.6%, 60.8% for the differential diagnosis of breast lesions if taken the maximum Youden's index as cut-off. (2)There were significant differences between benign lesions and malignant lesions in rK(trans), rk(ep) and rV(e) ( t =14.177, 11.726, 2.477, respectively, P quantitative pharmacokinetic parameters and the prediction probability of relative quantitative pharmacokinetic parameters( Z =0.867, P =0.195). Conclusion: There was no significant
Value Encounters - Modeling and Analyzing Co-creation of Value
Weigand, Hans
Recent marketing and management literature has introduced the concept of co-creation of value. Current value modeling approaches such as e3-value focus on the exchange of value rather than co-creation. In this paper, an extension to e3-value is proposed in the form of a “value encounter”. Value encounters are defined as interaction spaces where a group of actors meet and derive value by each one bringing in some of its own resources. They can be analyzed from multiple strategic perspectives, including knowledge management, social network management and operational management. Value encounter modeling can be instrumental in the context of service analysis and design.
Parameter optimization for surface flux transport models
Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.
2017-11-01
Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.
Impact of hierarchy upon the values of neutrino mixing parameters
International Nuclear Information System (INIS)
Escamilla-Roa, J.; Ernst, D. J.; Latimer, D. C.
2010-01-01
A neutrino-oscillation analysis is performed of the more finely binned Super-Kamiokande (Super-K) atmospheric, MINOS, and CHOOZ data to examine the effect of neutrino hierarchy in this data set on the value of θ 13 and the deviation of θ 23 from maximal mixing. Exact oscillation probabilities are used, thus incorporating all powers of θ 13 and ε:=θ 23 -π/4. The extracted oscillation parameters are found to be dependent on the hierarchy, particularly for θ 13 . We find, at a 90% confidence level, that these parameters are Δ 32 =2.44 -0.20 +0.26 and 2.48 -0.22 +0.25 x10 -3 eV 2 , ε=θ 23 -π/4=0.06 -0.16 +0.06 and 0.06 -0.17 +0.08 , and θ 13 =-0.07 -0.11 +0.18 and -0.13 -0.16 +0.23 , for the normal and inverted hierarchies, respectively. The inverted hierarchy is preferred at a statistically insignificant level of 0.3σ.
Are historical values of ionospheric parameters from ionosondes overestimated?
Laštovička, J.; Koucká Knížová, P.; Kouba, D.
2012-04-01
Ionogram-scaled values from pre-digital ionosonde times had been derived from ionograms under the assumption of the vertical reflection of ordinary mode of sounding radio waves. Classical ionosondes were unable to distinguish between the vertical and oblique reflections and in the case of the Es-layer also between the ordinary and extraordinary mode reflections due to mirror-like reflections. However, modern digisondes determine clearly the oblique or extraordinary mode reflections. Evaluating the Pruhonice digisonde ionograms in "classical" and in "correct" way we found for seven summers (2004-2010) that among strong foEs (> 6 MHz) only 10% of foEs values were correct and 90% were artificially enhanced in average by 1 MHz, in extreme cases by more than 3 MHz (some oblique reflections). 34% of all reflections were oblique reflections. With other ionospheric parameters like foF2 or foE the problem is less severe because non-mirror reflection makes delay of the extraordinary mode with respect to the ordinary mode and they are separated on ionograms, and oblique reflections are less frequent than with the patchy Es layer. At high latitudes another problem is caused by the z-mode, which is sometimes difficult to be distinguished from the ordinary mode.
Directory of Open Access Journals (Sweden)
Jian-cheng WANG
2007-06-01
Full Text Available Eleven evaluating parameters for rice core collection were assessed based on genotypic values and molecular marker information. Monte Carlo simulation combined with mixed linear model was used to eliminate the interference from environment in order to draw more reliable results. The coincidence rate of range (CR was the optimal parameter. Mean Simpson index (MD, mean Shannon-Weaver index of genetic diversity (MI and mean polymorphism information content (MPIC were important evaluating parameters. The variable rate of coefficient of variation (VR could act as an important reference parameter for evaluating the variation degree of core collection. Percentage of polymorphic loci (p could be used as a determination parameter for the size of core collection. Mean difference percentage (MD was a determination parameter for the reliability judgment of core collection. The effective evaluating parameters for core collection selected in the research could be used as criteria for sampling percentage in different plant germplasm populations.
Noszczyk-Nowak, Agnieszka; Cepiel, Alicja; Janiszewski, Adrian; Pasławski, Robert; Gajek, Jacek; Pasławska, Urszula; Nicpoń, Józef
2016-01-01
Swine are a well-recognized animal model for human cardiovascular diseases. Despite the widespread use of porcine model in experimental electrophysiology, still no reference values for intracardiac electrical activity and conduction parameters determined during an invasive electrophysiology study (EPS) have been developed in this species thus far. The aim of the study was to develop a set of normal values for intracardiac electrical activity and conduction parameters determined during an invasive EPS of swine. The study included 36 healthy domestic swine (24-40 kg body weight). EPS was performed under a general anesthesia with midazolam, propofol and isoflurane. The reference values for intracardiac electrical activity and conduction parameters were calculated as arithmetic means ± 2 standard deviations. The reference values were determined for AH, HV and PA intervals, interatrial conduction time at its own and imposed rhythm, sinus node recovery time (SNRT), corrected sinus node recovery time (CSNRT), anterograde and retrograde Wenckebach points, atrial, atrioventricular node and ventricular refractory periods. No significant correlations were found between body weight and heart rate of the examined pigs and their electrophysiological parameters. The hereby presented reference values can be helpful in comparing the results of various studies, as well as in more accurately estimating the values of electrophysiological parameters that can be expected in a given experiment.
Modelling tourists arrival using time varying parameter
Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.
2017-06-01
The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
Transfer parameter values in temperate forest ecosystems: a review
International Nuclear Information System (INIS)
Calmon, Philippe; Thiry, Yves; Zibold, Gregor; Rantavaara, Aino; Fesenko, Sergei
2009-01-01
Compared to agricultural lands, forests are complex ecosystems as they can involve diverse plant species associations, several vegetative strata (overstorey, shrubs, herbaceous and other annual plant layer) and multi-layered soil profiles (forest floor, hemi-organic and mineral layers). A high degree of variability is thus generally observed in radionuclide transfers and redistribution patterns in contaminated forests. In the long term, the soil compartment represents the major reservoir of radionuclides which can give rise to long-term plant and hence food contamination. For practical reasons, the contamination of various specific forest products has commonly been quantified using the aggregated transfer factor (T ag in m 2 kg -1 ) which integrates various environmental parameters including soil and plant type, root distribution as well as nature and vertical distribution of the deposits. Long lasting availability of some radionuclides was shown to be the source of much higher transfer in forest ecosystems than in agricultural lands. This study aimed at reviewing the most relevant quantitative information on radionuclide transfers to forest biota including trees, understorey vegetation, mushrooms, berries and game animals. For both radiocaesium and radiostrontium in trees, the order of magnitude of mean T ag values was 10 -3 m 2 kg -1 (dry weight). Tree foliage was usually 2-12 times more contaminated than trunk wood. Maximum contamination of tree components with radiocaesium was associated with (semi-)hydromorphic areas with thick humus layers. The transfer of radionuclides to mushrooms and berries is high, in comparison with foodstuffs grown in agricultural systems. Concerning caesium uptake by mushrooms, the transfer is characterized by a very large variability of T ag , from 10 -3 to 10 1 m 2 kg -1 (dry weight). For berries, typical values are around 0.01-0.1 m 2 kg -1 (dry weight). Transfer of radioactive caesium to game animals and reindeer and the rate of
Transfer parameter values in temperate forest ecosystems: a review
Energy Technology Data Exchange (ETDEWEB)
Calmon, Philippe [Department of Radioecology, Institute of Radioprotection and Nuclear Safety, CE Cadarache, BP 3, 13115 Saint Paul-les-Durance Cedex (France)], E-mail: philippe.calmon@irsn.fr; Thiry, Yves [Biosphere Impact Studies, Belgian Nuclear Research Center (SCK.CEN, Foundation of Public Utility), 2400 Mol (Belgium); Zibold, Gregor [Hochschule Ravensburg-Weingarten, University of Applied Sciences, 88250 Weingarten (Germany); Rantavaara, Aino [Research and Environmental Surveillance, Radiation and Nuclear Safety Authority (STUK), BP 14, FIN-00881 Helsinki (Finland); Fesenko, Sergei [International Atomic Energy Agency (IAEA), 1400 Vienna (Austria)
2009-09-15
Compared to agricultural lands, forests are complex ecosystems as they can involve diverse plant species associations, several vegetative strata (overstorey, shrubs, herbaceous and other annual plant layer) and multi-layered soil profiles (forest floor, hemi-organic and mineral layers). A high degree of variability is thus generally observed in radionuclide transfers and redistribution patterns in contaminated forests. In the long term, the soil compartment represents the major reservoir of radionuclides which can give rise to long-term plant and hence food contamination. For practical reasons, the contamination of various specific forest products has commonly been quantified using the aggregated transfer factor (T{sub ag} in m{sup 2} kg{sup -1}) which integrates various environmental parameters including soil and plant type, root distribution as well as nature and vertical distribution of the deposits. Long lasting availability of some radionuclides was shown to be the source of much higher transfer in forest ecosystems than in agricultural lands. This study aimed at reviewing the most relevant quantitative information on radionuclide transfers to forest biota including trees, understorey vegetation, mushrooms, berries and game animals. For both radiocaesium and radiostrontium in trees, the order of magnitude of mean T{sub ag} values was 10{sup -3} m{sup 2} kg{sup -1} (dry weight). Tree foliage was usually 2-12 times more contaminated than trunk wood. Maximum contamination of tree components with radiocaesium was associated with (semi-)hydromorphic areas with thick humus layers. The transfer of radionuclides to mushrooms and berries is high, in comparison with foodstuffs grown in agricultural systems. Concerning caesium uptake by mushrooms, the transfer is characterized by a very large variability of T{sub ag}, from 10{sup -3} to 10{sup 1} m{sup 2} kg{sup -1} (dry weight). For berries, typical values are around 0.01-0.1 m{sup 2} kg{sup -1} (dry weight). Transfer
An alternative approach to absolute-value test for the parameters of ...
African Journals Online (AJOL)
An alternative approach to absolute-value test statistic Mn is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. Under certain null and alternative hypotheses, the new test statistic is shown to have limiting central and noncentral chisquare distributions, respectively.
Quality assessment for radiological model parameters
International Nuclear Information System (INIS)
Funtowicz, S.O.
1989-01-01
A prototype framework for representing uncertainties in radiological model parameters is introduced. This follows earlier development in this journal of a corresponding framework for representing uncertainties in radiological data. Refinements and extensions to the earlier framework are needed in order to take account of the additional contextual factors consequent on using data entries to quantify model parameters. The parameter coding can in turn feed in to methods for evaluating uncertainties in calculated model outputs. (author)
Identifying the connective strength between model parameters and performance criteria
Directory of Open Access Journals (Sweden)
B. Guse
2017-11-01
Full Text Available In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria. To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash–Sutcliffe efficiency (NSE, Kling–Gupta efficiency (KGE and its three components (alpha, beta and r as well as RSR (the ratio of the root mean square error to the standard deviation for different segments of the flow duration curve (FDC are calculated. With a joint analysis of two regression tree (RT approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter. In this study, a high bijective connective strength between model parameters and performance criteria
Establishing statistical models of manufacturing parameters
International Nuclear Information System (INIS)
Senevat, J.; Pape, J.L.; Deshayes, J.F.
1991-01-01
This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature
Learning about physical parameters: the importance of model discrepancy
International Nuclear Information System (INIS)
Brynjarsdóttir, Jenný; O'Hagan, Anthony
2014-01-01
Science-based simulation models are widely used to predict the behavior of complex physical systems. It is also common to use observations of the physical system to solve the inverse problem, that is, to learn about the values of parameters within the model, a process which is often called calibration. The main goal of calibration is usually to improve the predictive performance of the simulator but the values of the parameters in the model may also be of intrinsic scientific interest in their own right. In order to make appropriate use of observations of the physical system it is important to recognize model discrepancy, the difference between reality and the simulator output. We illustrate through a simple example that an analysis that does not account for model discrepancy may lead to biased and over-confident parameter estimates and predictions. The challenge with incorporating model discrepancy in statistical inverse problems is being confounded with calibration parameters, which will only be resolved with meaningful priors. For our simple example, we model the model-discrepancy via a Gaussian process and demonstrate that through accounting for model discrepancy our prediction within the range of data is correct. However, only with realistic priors on the model discrepancy do we uncover the true parameter values. Through theoretical arguments we show that these findings are typical of the general problem of learning about physical parameters and the underlying physical system using science-based mechanistic models. (paper)
Handbook of parameter values for the prediction of radionuclide transfer in temperate environments
International Nuclear Information System (INIS)
1994-01-01
This Handbook has been prepared in response to a widely expressed interest in having a convenient and authoritative reference for radionuclide transfer parameter values used in biospheric assessment models. It draws on data from North America and Europe, much of which was collected through projects of the International Union of Radioecologists (IUR) and the Commission of European Communities (CEC) over the last decade. It is intended to supplement existing IAEA publications on environmental assessment methodology, primarily Generic Models and Parameters for Assessing the Environmental Transfer of Radionuclides from Routine Releases, IAEA Safety Series No. 57 (1982). 219 refs, 3 figs, 32 tabs
A simulation of water pollution model parameter estimation
Kibler, J. F.
1976-01-01
A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.
Robust estimation of hydrological model parameters
Directory of Open Access Journals (Sweden)
A. Bárdossy
2008-11-01
Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
Agricultural and Environmental Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
Kaylie Rasmuson; Kurt Rautenstrauch
2003-01-01
This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN
On parameter estimation in deformable models
DEFF Research Database (Denmark)
Fisker, Rune; Carstensen, Jens Michael
1998-01-01
Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...
Assessment of Optimum Value for Dip Angle and Locking Rate Parameters in Makran Subduction Zone
Safari, A.; Abolghasem, A. M.; Abedini, N.; Mousavi, Z.
2017-09-01
Makran subduction zone is one of the convergent areas that have been studied by spatial geodesy. Makran zone is located in the South Eastern of Iran and South of Pakistan forming the part of Eurasian-Arabian plate's border where oceanic crust in the Arabian plate (or in Oman Sea) subducts under the Eurasian plate ( Farhoudi and Karig, 1977). Due to lack of historical and modern tools in the area, a sampling of sparse measurements of the permanent GPS stations and temporary stations (campaign) has been conducted in the past decade. Makran subduction zone from different perspectives has unusual behaviour: For example, the Eastern and Western parts of the region have very different seismicity and also dip angle of subducted plate is in about 2 to 8 degrees that this value due to the dip angle in other subduction zone is very low. In this study, we want to find the best possible value for parameters that differs Makran subduction zone from other subduction zones. Rigid block modelling method was used to determine these parameters. From the velocity vectors calculated from GPS observations in this area, block model is formed. These observations are obtained from GPS stations that a number of them are located in South Eastern Iran and South Western Pakistan and a station located in North Eastern Oman. According to previous studies in which the locking depth of Makran subduction zone is 38km (Frohling, 2016), in the preparation of this model, parameter value of at least 38 km is considered. With this function, the amount of 2 degree value is the best value for dip angle but for the locking rate there is not any specified amount. Because the proposed model is not sensitive to this parameter. So we can not expect big earthquakes in West of Makran or a low seismicity activity in there but the proposed model definitely shows the Makran subduction layer is locked.
Determining extreme parameter correlation in ground water models
DEFF Research Database (Denmark)
Hill, Mary Cole; Østerby, Ole
2003-01-01
can go undetected even by experienced modelers. Extreme parameter correlation can be detected using parameter correlation coefficients, but their utility depends on the presence of sufficient, but not excessive, numerical imprecision of the sensitivities, such as round-off error. This work...... investigates the information that can be obtained from parameter correlation coefficients in the presence of different levels of numerical imprecision, and compares it to the information provided by an alternative method called the singular value decomposition (SVD). Results suggest that (1) calculated...... correlation coefficients with absolute values that round to 1.00 were good indicators of extreme parameter correlation, but smaller values were not necessarily good indicators of lack of correlation and resulting unique parameter estimates; (2) the SVD may be more difficult to interpret than parameter...
Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds
Directory of Open Access Journals (Sweden)
Indrajeet Chaubey
2010-11-01
Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.
Achieving Value in Primary Care: The Primary Care Value Model.
Rollow, William; Cucchiara, Peter
2016-03-01
The patient-centered medical home (PCMH) model provides a compelling vision for primary care transformation, but studies of its impact have used insufficiently patient-centered metrics with inconsistent results. We propose a framework for defining patient-centered value and a new model for value-based primary care transformation: the primary care value model (PCVM). We advocate for use of patient-centered value when measuring the impact of primary care transformation, recognition, and performance-based payment; for financial support and research and development to better define primary care value-creating activities and their implementation; and for use of the model to support primary care organizations in transformation. © 2016 Annals of Family Medicine, Inc.
Lubis, A. S.; Muis, Z. A.; Pasaribu, M. I.
2017-03-01
The strength and durability of pavement construction is highly dependent on the properties and subgrade bearing capacity. This then led to the idea of the selection methods to estimate the density of the soil with the proper implementation of the system, fast and economical. This study aims to estimate the compaction parameter value namely the maximum dry unit weight (γd max) and optimum moisture content (wopt) of the soil properties value that stabilized with Portland Cement. Tests conducted in the laboratory of soil mechanics to determine the index properties (fines and liquid limit) and Standard Compaction Test. Soil samples that have Plasticity Index (PI) between 0-15% then mixed with Portland Cement (PC) with variations of 2%, 4%, 6%, 8% and 10%, each 10 samples. The results showed that the maximum dry unit weight (γd max) and wopt has a significant relationship with percent fines, liquid limit and the percentation of cement. Equation for the estimated maximum dry unit weight (γd max) = 1.782 - 0.011*LL + 0,000*F + 0.006*PS with R2 = 0.915 and the estimated optimum moisture content (wopt) = 3.441 + 0.594*LL + 0,025*F + 0,024*PS with R2 = 0.726.
Handbook of parameter values for the prediction of radionuclide transfer to wildlife
Energy Technology Data Exchange (ETDEWEB)
NONE
2014-06-15
This handbook provides generic parameter values for estimating the transfer of radionuclides from environmental media to wildlife for the purpose of assessing potential radiation exposure under equilibrium conditions. These data are intended for use where site specific data are either not available or not required, and to parameterize generic assessment models. They are based on a comprehensive review of the available literature, including many Russian language publications that have not previously been available in English. The publication addresses the limitations of the parameter values and the applicability of data. Some general background information on the assessment of potential impacts of radioactive releases on wildlife is also included. It complements the existing handbook in the same IAEA series with parameter to assess the radiological impact to humans.
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.
Optimal parameters for the FFA-Beddoes dynamic stall model
Energy Technology Data Exchange (ETDEWEB)
Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)
1999-03-01
Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)
Parameter identification in multinomial processing tree models
Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.
2010-01-01
Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis
Continuous Spatial Process Models for Spatial Extreme Values
Sang, Huiyan; Gelfand, Alan E.
2010-01-01
process model for extreme values that provides mean square continuous realizations, where the behavior of the surface is driven by the spatial dependence which is unexplained under the latent spatio-temporal specification for the GEV parameters
Energy Technology Data Exchange (ETDEWEB)
Djuric-Stefanovic, A., E-mail: avstefan@eunet.rs [Faculty of Medicine, University of Belgrade, Belgrade (Serbia); Unit of Digestive Radiology (First University Surgical Clinic), Center of Radiology and MR, Clinical Center of Serbia, Belgrade (Serbia); Saranovic, Dj., E-mail: crvzve4@gmail.com [Faculty of Medicine, University of Belgrade, Belgrade (Serbia); Unit of Digestive Radiology (First University Surgical Clinic), Center of Radiology and MR, Clinical Center of Serbia, Belgrade (Serbia); Sobic-Saranovic, D., E-mail: dsobic2@gmail.com [Faculty of Medicine, University of Belgrade, Belgrade (Serbia); Center of Nuclear Medicine, Clinical Center of Serbia, Belgrade (Serbia); Masulovic, D., E-mail: draganmasulovic@yahoo.com [Faculty of Medicine, University of Belgrade, Belgrade (Serbia); Unit of Digestive Radiology (First University Surgical Clinic), Center of Radiology and MR, Clinical Center of Serbia, Belgrade (Serbia); Artiko, V., E-mail: veraart@beotel.rs [Faculty of Medicine, University of Belgrade, Belgrade (Serbia); Center of Nuclear Medicine, Clinical Center of Serbia, Belgrade (Serbia)
2015-03-15
Purpose: Standardized perfusion value (SPV) is a universal indicator of tissue perfusion, normalized to the whole-body perfusion, which was proposed to simplify, unify and allow the interchangeability among the perfusion measurements and comparison between the tumor perfusion and metabolism. The aims of our study were to assess the standardized perfusion value (SPV) of the esophageal carcinoma, and its correlation with quantitative CT perfusion measurements: blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface area product (PS) of the same tumor volume samples, which were obtained by deconvolution-based CT perfusion analysis. Methods: Forty CT perfusion studies of the esophageal cancer were analyzed, using the commercial deconvolution-based CT perfusion software (Perfusion 3.0, GE Healthcare). The SPV of the esophageal tumor and neighboring skeletal muscle were correlated with the corresponding mean tumor and muscle quantitative CT perfusion parameter values, using Spearman's rank correlation coefficient (r{sub S}). Results: Median SPV of the esophageal carcinoma (7.1; range: 2.8–13.4) significantly differed from the SPV of the skeletal muscle (median: 1.0; range: 0.4–2.4), (Z = −5.511, p < 0.001). The cut-off value of the SPV of 2.5 enabled discrimination of esophageal cancer from the skeletal muscle with sensitivity and specificity of 100%. SPV of the esophageal carcinoma significantly correlated with corresponding tumor BF (r{sub S} = 0.484, p = 0.002), BV (r{sub S} = 0.637, p < 0.001) and PS (r{sub S} = 0.432, p = 0.005), and SPV of the skeletal muscle significantly correlated with corresponding muscle BF (r{sub S} = 0.573, p < 0.001), BV (r{sub S} = 0.849, p < 0.001) and PS (r{sub S} = 0.761, p < 0.001). Conclusions: We presented a database of the SPV for the esophageal cancer and proved that SPV of the esophageal neoplasm significantly differs from the SPV of the skeletal muscle, which represented a sample of healthy
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Directory of Open Access Journals (Sweden)
Hadiyanto Hadiyanto
2012-05-01
Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels. Abstrak PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan
Researches Regarding Microbiological Parameters Values of Telemea Cheese
Directory of Open Access Journals (Sweden)
Andra Suler
2010-10-01
Full Text Available The main objectives of this paper were microbiological parameters which characterized the Telemea cheese for each season, assessment of technologies and thus assortment defects as well as projection of hygienic solution for obtaining qualitative products according to actual standards. We studied 5 units of Telemea cheese processing replaced in different area. For obtaining concrete results we used STAS methodologies and analyze procedure was based on observation, mathematical estimation and experiments (in lab and processing units.
Parameter estimation in stochastic rainfall-runoff models
DEFF Research Database (Denmark)
Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur
2006-01-01
A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...
Biological parameters for lung cancer in mathematical models of carcinogenesis
International Nuclear Information System (INIS)
Jacob, P.; Jacob, V.
2003-01-01
Applications of the two-step model of carcinogenesis with clonal expansion (TSCE) to lung cancer data are reviewed, including those on atomic bomb survivors from Hiroshima and Nagasaki, British doctors, Colorado Plateau miners, and Chinese tin miners. Different sets of identifiable model parameters are used in the literature. The parameter set which could be determined with the lowest uncertainty consists of the net proliferation rate gamma of intermediate cells, the hazard h 55 at an intermediate age, and the hazard H? at an asymptotically large age. Also, the values of these three parameters obtained in the various studies are more consistent than other identifiable combinations of the biological parameters. Based on representative results for these three parameters, implications for the biological parameters in the TSCE model are derived. (author)
Parameter identification in the logistic STAR model
DEFF Research Database (Denmark)
Ekner, Line Elvstrøm; Nejstgaard, Emil
We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th...
Exploiting intrinsic fluctuations to identify model parameters.
Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen
2015-04-01
Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.
Setting Parameters for Biological Models With ANIMO
Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran
2014-01-01
ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami
2017-06-01
A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.
Parameters and error of a theoretical model
International Nuclear Information System (INIS)
Moeller, P.; Nix, J.R.; Swiatecki, W.
1986-09-01
We propose a definition for the error of a theoretical model of the type whose parameters are determined from adjustment to experimental data. By applying a standard statistical method, the maximum-likelihoodlmethod, we derive expressions for both the parameters of the theoretical model and its error. We investigate the derived equations by solving them for simulated experimental and theoretical quantities generated by use of random number generators. 2 refs., 4 tabs
Parameter Estimation of Nonlinear Models in Forestry.
Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.
1999-01-01
Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...
Norms and values in sociohydrological models
Directory of Open Access Journals (Sweden)
M. Roobavannan
2018-02-01
Full Text Available Sustainable water resources management relies on understanding how societies and water systems coevolve. Many place-based sociohydrology (SH modeling studies use proxies, such as environmental degradation, to capture key elements of the social component of system dynamics. Parameters of assumed relationships between environmental degradation and the human response to it are usually obtained through calibration. Since these relationships are not yet underpinned by social-science theories, confidence in the predictive power of such place-based sociohydrologic models remains low. The generalizability of SH models therefore requires major advances in incorporating more realistic relationships, underpinned by appropriate hydrological and social-science data and theories. The latter is a critical input, since human culture – especially values and norms arising from it – influences behavior and the consequences of behaviors. This paper reviews a key social-science theory that links cultural factors to environmental decision-making, assesses how to better incorporate social-science insights to enhance SH models, and raises important questions to be addressed in moving forward. This is done in the context of recent progress in sociohydrological studies and the gaps that remain to be filled. The paper concludes with a discussion of challenges and opportunities in terms of generalization of SH models and the use of available data to allow future prediction and model transfer to ungauged basins.
Norms and values in sociohydrological models
Roobavannan, Mahendran; van Emmerik, Tim H. M.; Elshafei, Yasmina; Kandasamy, Jaya; Sanderson, Matthew R.; Vigneswaran, Saravanamuthu; Pande, Saket; Sivapalan, Murugesu
2018-02-01
Sustainable water resources management relies on understanding how societies and water systems coevolve. Many place-based sociohydrology (SH) modeling studies use proxies, such as environmental degradation, to capture key elements of the social component of system dynamics. Parameters of assumed relationships between environmental degradation and the human response to it are usually obtained through calibration. Since these relationships are not yet underpinned by social-science theories, confidence in the predictive power of such place-based sociohydrologic models remains low. The generalizability of SH models therefore requires major advances in incorporating more realistic relationships, underpinned by appropriate hydrological and social-science data and theories. The latter is a critical input, since human culture - especially values and norms arising from it - influences behavior and the consequences of behaviors. This paper reviews a key social-science theory that links cultural factors to environmental decision-making, assesses how to better incorporate social-science insights to enhance SH models, and raises important questions to be addressed in moving forward. This is done in the context of recent progress in sociohydrological studies and the gaps that remain to be filled. The paper concludes with a discussion of challenges and opportunities in terms of generalization of SH models and the use of available data to allow future prediction and model transfer to ungauged basins.
Wind Farm Decentralized Dynamic Modeling With Parameters
DEFF Research Database (Denmark)
Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran
2010-01-01
Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...
On the role of modeling parameters in IMRT plan optimization
International Nuclear Information System (INIS)
Krause, Michael; Scherrer, Alexander; Thieke, Christian
2008-01-01
The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way
Institute of Scientific and Technical Information of China (English)
李一哲; 张廷龙; 刘秋雨; 李英
2018-01-01
The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present.However,there are many parameters for these models,and weather the reasonable values of these parameters were taken,have important impact on the models simulation results.In the past,the sensitivity and the optimization of model parameters were analyzed and discussed in many researches.But the temporal and spatial heterogeneity of the optimal parameters is less concerned.In this paper,the BIOME-BGC model was used as an example.In the evergreen broad-leaved forest,deciduous broad-leaved forest and C3 grassland,the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type.The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site.Then we constructed the temporal heterogeneity judgment index,the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters.The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types,but the selected sensitive parameters were mostly consistent.The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types.The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity.In addition,the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation with the spatial
Models and parameters for environmental radiological assessments
International Nuclear Information System (INIS)
Miller, C.W.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
African Journals Online (AJOL)
Preferred Customer
Page 1 ... corresponding single-parameter Winkler model presented in this work. Keywords: Heterogeneous subgrade, Reissner's simplified continuum, Shear interaction, Simplified continuum, Winkler ... model in practical applications and its long time familiarity among practical engineers, its usage has endured to this date ...
Models and parameters for environmental radiological assessments
Energy Technology Data Exchange (ETDEWEB)
Miller, C W [ed.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)
Models and parameters for environmental radiological assessments
International Nuclear Information System (INIS)
Miller, C.W.
1983-01-01
This article reviews the forthcoming book Models and Parameters for Environmental Radiological Assessments, which presents a unified compilation of models and parameters for assessing the impact on man of radioactive discharges, both routine and accidental, into the environment. Models presented in this book include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Summaries are presented for each of the transport and dosimetry areas previously for each of the transport and dosimetry areas previously mentioned, and details are available in the literature cited. A chapter of example problems illustrates many of the methodologies presented throughout the text. Models and parameters presented are based on the results of extensive literature reviews and evaluations performed primarily by the staff of the Health and Safety Research Division of Oak Ridge National Laboratory
Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver
Kang, Ling; Zhou, Liwei
2018-02-01
Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.
Data Qualification Report For DTN: MO0012RIB00065.002, Parameter Values For Transfer Coefficients
International Nuclear Information System (INIS)
C.H. Tung
2001-01-01
A data-qualification evaluation was conducted on Reference Information Base (RIB) data set MOO0 12RIB00065.002, ''Parameter Values for Transfer Coefficients''. The corroborating data method was used to evaluate the data. This method was selected because it closely matches the literature-review method followed to select parameter values. Five criteria were considered when the corroborating method was used: adequacy of the corroborative literature, sufficiency of value-selection criteria, implementation of the selection criteria, documentation of the process, and whether the analysis was conducted in accordance with applicable quality assurance (QA) procedures. Three criteria were used when a literature review was not conducted: appropriate logic used to select parameters, documentation of the process, and whether the analysis was conducted in accordance with applicable QA procedures. The RIB data item, the associated Analysis and Model Report (AMR), the corroborative literature, and the results of an audit revision O/ICN--0 of the AMR were examined. All calculations and the selection process for all values were repeated and confirmed. The qualification team concluded: (1) A sufficient quantity of corroborative literature was reviewed and no additional literature was identified that should have been considered. (2) The selection criteria were sufficient and resulted in valid parameter values. (3) The process was well defined, adequately documented in the AMR, and correctly followed. (4) The analysis was developed in accordance with applicable QA procedures. No negative findings were documented that resulted in questions about the quality of the data. The qualification team therefore recommends that the qualification status of RIB data set MO0012RIB00065.002 be changed to qualified
Applying the Expectancy-Value Model to understand health values.
Zhang, Xu-Hao; Xie, Feng; Wee, Hwee-Lin; Thumboo, Julian; Li, Shu-Chuen
2008-03-01
Expectancy-Value Model (EVM) is the most structured model in psychology to predict attitudes by measuring attitudinal attributes (AAs) and relevant external variables. Because health value could be categorized as attitude, we aimed to apply EVM to explore its usefulness in explaining variances in health values and investigate underlying factors. Focus group discussion was carried out to identify the most common and significant AAs toward 5 different health states (coded as 11111, 11121, 21221, 32323, and 33333 in EuroQol Five-Dimension (EQ-5D) descriptive system). AAs were measured in a sum of multiplications of subjective probability (expectancy) and perceived value of attributes with 7-point Likert scales. Health values were measured using visual analog scales (VAS, range 0-1). External variables (age, sex, ethnicity, education, housing, marital status, and concurrent chronic diseases) were also incorporated into survey questionnaire distributed by convenience sampling among eligible respondents. Univariate analyses were used to identify external variables causing significant differences in VAS. Multiple linear regression model (MLR) and hierarchical regression model were used to investigate the explanatory power of AAs and possible significant external variable(s) separately or in combination, for each individual health state and a mixed scenario of five states, respectively. Four AAs were identified, namely, "worsening your quality of life in terms of health" (WQoL), "adding a burden to your family" (BTF), "making you less independent" (MLI) and "unable to work or study" (UWS). Data were analyzed based on 232 respondents (mean [SD] age: 27.7 [15.07] years, 49.1% female). Health values varied significantly across 5 health states, ranging from 0.12 (33333) to 0.97 (11111). With no significant external variables identified, EVM explained up to 62% of the variances in health values across 5 health states. The explanatory power of 4 AAs were found to be between 13
Directory of Open Access Journals (Sweden)
Yu. V. Zelenko
2016-06-01
Full Text Available Purpose.The success of the traffic on the railways of Ukraine depends on the number and the operational fleet of electric locomotives. Today, the locomotive depot exploit physically and morally outdated locomotives that have low reliability. Modernization of electric locomotives is not economically justified. The aim of this study is to improve the safety of the traction rolling stock by the frequency analysis of dynamical systems, which allows conducting the calculation of the natural (of resonant frequencies of the design and related forms of vibrations.Methodology.The study was conducted by methods of analytical mechanics and mathematical modeling of operating loads of freight locomotive when driving at different speeds on the straight and curved track sections. The theoretical value of the work is the technique of choice of constructive schemes and rational parameters of perspective electric locomotive taking into account the electric inertia ratios and stiffness coefficients of Lagrange second-order equations.Findings. The problems of theoretical research and the development of a mathematical model of the spatial electric vibrations are solved. The theoretical studies of the effect of inertia ratios and stiffness coefficients on the dynamic values and the parameter values of electric locomotive undercarriages are presented.Originality.The set of developed regulations and obtained results is a practical solution to selecting rational parameters of bogies of the freight mainline locomotive for railways of Ukraine. A concept of choice of constructive scheme and rational parameters of perspective locomotive is formulated. It is developed the method of calculation of spatial electric locomotive oscillations to determine its dynamic performance. The software complex for processing the data of experimental studies of dynamic parameters of electric locomotive and comparing the results of the theoretical calculations with the data of full
PV panel model based on datasheet values
DEFF Research Database (Denmark)
Sera, Dezso; Teodorescu, Remus; Rodriguez, Pedro
2007-01-01
This work presents the construction of a model for a PV panel using the single-diode five-parameters model, based exclusively on data-sheet parameters. The model takes into account the series and parallel (shunt) resistance of the panel. The equivalent circuit and the basic equations of the PV cell....... Based on these equations, a PV panel model, which is able to predict the panel behavior in different temperature and irradiance conditions, is built and tested....
Agricultural and Environmental Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
Kaylie Rasmuson; Kurt Rautenstrauch
2003-06-20
This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN.
Universally sloppy parameter sensitivities in systems biology models.
Directory of Open Access Journals (Sweden)
Ryan N Gutenkunst
2007-10-01
Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.
Universally sloppy parameter sensitivities in systems biology models.
Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P
2007-10-01
Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.
International Nuclear Information System (INIS)
Dyvorne, Hadrien; Jajamovich, Guido; Kakite, Suguru; Kuehn, Bernd; Taouli, Bachir
2014-01-01
Highlights: • We assess the precision and reproducibility of liver IVIM diffusion parameters. • Liver IVIM DWI can be performed with 4 b-values with good parameter precision. • Liver IVIM DWI can be performed with 4 b-values with good parameter reproducibility. - Abstract: Purpose: To increase diffusion sampling efficiency in intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) of the liver by reducing the number of diffusion weightings (b-values). Materials and methods: In this IRB approved HIPAA compliant prospective study, 53 subjects (M/F 38/15, mean age 52 ± 13 y) underwent IVIM DWI at 1.5 T using 16 b-values (0–800 s/mm 2 ), with 14 subjects having repeat exams to assess IVIM parameter reproducibility. A biexponential diffusion model was used to quantify IVIM hepatic parameters (PF: perfusion fraction, D: true diffusion and D*: pseudo diffusion). All possible subsets of the 16 b-values were probed, with number of b values ranging from 4 to 15, and corresponding parameters were quantified for each subset. For each b-value subset, global parameter estimation error was computed against the parameters obtained with all 16 b-values and the subsets providing the lowest error were selected. Interscan estimation error was also evaluated between repeat exams to assess reproducibility of the IVIM technique in the liver. The optimal b-values distribution was selected such that the number of b-values was minimal while keeping parameter estimation error below interscan reproducibility error. Results: As the number of b-values decreased, the estimation error increased for all parameters, reflecting decreased precision of IVIM metrics. Using an optimal set of 4 b-values (0, 15, 150 and 800 s/mm 2 ), the errors were 6.5, 22.8 and 66.1% for D, PF and D* respectively. These values lie within the range of test–retest reproducibility for the corresponding parameters, with errors of 12.0, 32.3 and 193.8% for D, PF and D* respectively. Conclusion: A set
da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; Picanço, Marcelo Coutinho
2018-04-01
A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using open-field Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed "sensitive". Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive.
Analysis of Modeling Parameters on Threaded Screws.
Energy Technology Data Exchange (ETDEWEB)
Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-06-01
Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.
Environmental Transport Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. Wasiolek
2004-09-10
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis
Environmental Transport Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. Wasiolek
2004-01-01
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573])
Environmental Transport Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
Wasiolek, M. A.
2003-01-01
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699], Section 6.2). Parameter values
Environmental Transport Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. A. Wasiolek
2003-06-27
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699
Parameter Estimation of Spacecraft Fuel Slosh Model
Gangadharan, Sathya; Sudermann, James; Marlowe, Andrea; Njengam Charles
2004-01-01
Fuel slosh in the upper stages of a spinning spacecraft during launch has been a long standing concern for the success of a space mission. Energy loss through the movement of the liquid fuel in the fuel tank affects the gyroscopic stability of the spacecraft and leads to nutation (wobble) which can cause devastating control issues. The rate at which nutation develops (defined by Nutation Time Constant (NTC can be tedious to calculate and largely inaccurate if done during the early stages of spacecraft design. Pure analytical means of predicting the influence of onboard liquids have generally failed. A strong need exists to identify and model the conditions of resonance between nutation motion and liquid modes and to understand the general characteristics of the liquid motion that causes the problem in spinning spacecraft. A 3-D computerized model of the fuel slosh that accounts for any resonant modes found in the experimental testing will allow for increased accuracy in the overall modeling process. Development of a more accurate model of the fuel slosh currently lies in a more generalized 3-D computerized model incorporating masses, springs and dampers. Parameters describing the model include the inertia tensor of the fuel, spring constants, and damper coefficients. Refinement and understanding the effects of these parameters allow for a more accurate simulation of fuel slosh. The current research will focus on developing models of different complexity and estimating the model parameters that will ultimately provide a more realistic prediction of Nutation Time Constant obtained through simulation.
E3value to BPMN model transformation
Fatemi, Hassan; van Sinderen, Marten J.; Wieringa, Roelf J.; Wieringa, P.A.; Camarinha-Matos, Luis M.; Pereira Klen, Alexandra; Afsarmanesh, Hamidesh
2011-01-01
Business value and coordination process perspectives need to be taken into consideration while modeling business collaborations. The need for these two models stems from the importance of separating the how from the what concerns. A business value model shows what is offered by whom to whom while a
Influence of lung parameter values for the Brazilian population on inhalation dose
International Nuclear Information System (INIS)
Reis, Arlene A.; Lopes, Ricardo T.
2009-01-01
The Human Respiratory Tract Model (HRTM) proposed by the ICRP Publication 66 accounts for the morphology and physiology of the respiratory tract. The ICRP 66 presents deposition fraction in the respiratory tract regions considering reference values from Caucasian man. However, in order to obtain a more accurate assessment of intake and dose the ICRP recommends the use of specific information when they are available. The main objective of this study is to evaluate the influence in dose calculation to each region of the respiratory tract when physiological parameters from samples of Brazilian population, in different levels of exercise, are applied in the deposition model.The dosimetric model of HRTM was implemented in the software EXCEL for Windows and committed equivalent dose was determined for each respiratory tract region. First it was calculated the total number of nuclear transformations considering the fractional deposition of activity in each source tissue obtained by application of physiological and morphological Brazilian parameters in the deposition model and then it was calculated the total energy absorbed per unit mass in the target tissue.The variation in the fractional deposition in the compartments of the respiratory tract in changing the physiological parameters from Caucasian to Brazilian adult man causes variation in the number of total transformations and also in the equivalent dose in each region of the respiratory tract. The variations are not the same for all regions of the respiratory tract and depend on levels of exercise. (author)
Investigation of RADTRAN Stop Model input parameters for truck stops
International Nuclear Information System (INIS)
Griego, N.R.; Smith, J.D.; Neuhauser, K.S.
1996-01-01
RADTRAN is a computer code for estimating the risks and consequences as transport of radioactive materials (RAM). RADTRAN was developed and is maintained by Sandia National Laboratories for the US Department of Energy (DOE). For incident-free transportation, the dose to persons exposed while the shipment is stopped is frequently a major percentage of the overall dose. This dose is referred to as Stop Dose and is calculated by the Stop Model. Because stop dose is a significant portion of the overall dose associated with RAM transport, the values used as input for the Stop Model are important. Therefore, an investigation of typical values for RADTRAN Stop Parameters for truck stops was performed. The resulting data from these investigations were analyzed to provide mean values, standard deviations, and histograms. Hence, the mean values can be used when an analyst does not have a basis for selecting other input values for the Stop Model. In addition, the histograms and their characteristics can be used to guide statistical sampling techniques to measure sensitivity of the RADTRAN calculated Stop Dose to the uncertainties in the stop model input parameters. This paper discusses the details and presents the results of the investigation of stop model input parameters at truck stops
The rho-parameter in supersymmetric models
International Nuclear Information System (INIS)
Lim, C.S.; Inami, T.; Sakai, N.
1983-10-01
The electroweak rho-parameter is examined in a general class of supersymmetric models. Formulae are given for one-loop contributions to Δrho from scalar quarks and leptons, gauge-Higgs fermions and an extra doublet of Higgs scalars. Mass differences between members of isodoublet scalar quarks and leptons are constrained to be less than about 200 GeV. (author)
A lumped parameter model of plasma focus
International Nuclear Information System (INIS)
Gonzalez, Jose H.; Florido, Pablo C.; Bruzzone, H.; Clausse, Alejandro
1999-01-01
A lumped parameter model to estimate neutron emission of a plasma focus (PF) device is developed. The dynamic of the current sheet is calculated using a snowplow model, and the neutron production with the thermal fusion cross section for a deuterium filling gas. The results were contrasted as a function of the filling pressure with experimental measurements of a 3.68 KJ Mather-type PF. (author)
One parameter model potential for noble metals
International Nuclear Information System (INIS)
Idrees, M.; Khwaja, F.A.; Razmi, M.S.K.
1981-08-01
A phenomenological one parameter model potential which includes s-d hybridization and core-core exchange contributions is proposed for noble metals. A number of interesting properties like liquid metal resistivities, band gaps, thermoelectric powers and ion-ion interaction potentials are calculated for Cu, Ag and Au. The results obtained are in better agreement with experiment than the ones predicted by the other model potentials in the literature. (author)
Focusing of high power ultrasound beams and limiting values of shock wave parameters
Bessonova, O. V.; Khokhlova, V. A.; Bailey, M. R.; Canney, M. S.; Crum, L. A.
2009-10-01
In this work, the influence of nonlinear and diffraction effects on amplification factors of focused ultrasound systems is investigated. The limiting values of acoustic field parameters obtained by focusing of high power ultrasound are studied. The Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation was used for the numerical modeling. Solutions for the nonlinear acoustic field were obtained at output levels corresponding to both pre- and post-shock formation conditions in the focal area of the beam in a weakly dissipative medium. Numerical solutions were compared with experimental data as well as with known analytic predictions.
Evaluation of some infiltration models and hydraulic parameters
International Nuclear Information System (INIS)
Haghighi, F.; Gorji, M.; Shorafa, M.; Sarmadian, F.; Mohammadi, M. H.
2010-01-01
The evaluation of infiltration characteristics and some parameters of infiltration models such as sorptivity and final steady infiltration rate in soils are important in agriculture. The aim of this study was to evaluate some of the most common models used to estimate final soil infiltration rate. The equality of final infiltration rate with saturated hydraulic conductivity (Ks) was also tested. Moreover, values of the estimated sorptivity from the Philips model were compared to estimates by selected pedotransfer functions (PTFs). The infiltration experiments used the doublering method on soils with two different land uses in the Taleghan watershed of Tehran province, Iran, from September to October, 2007. The infiltration models of Kostiakov-Lewis, Philip two-term and Horton were fitted to observed infiltration data. Some parameters of the models and the coefficient of determination goodness of fit were estimated using MATLAB software. The results showed that, based on comparing measured and model-estimated infiltration rate using root mean squared error (RMSE), Hortons model gave the best prediction of final infiltration rate in the experimental area. Laboratory measured Ks values gave significant differences and higher values than estimated final infiltration rates from the selected models. The estimated final infiltration rate was not equal to laboratory measured Ks values in the study area. Moreover, the estimated sorptivity factor by Philips model was significantly different to those estimated by selected PTFs. It is suggested that the applicability of PTFs is limited to specific, similar conditions. (Author) 37 refs.
Calibration of discrete element model parameters: soybeans
Ghodki, Bhupendra M.; Patel, Manish; Namdeo, Rohit; Carpenter, Gopal
2018-05-01
Discrete element method (DEM) simulations are broadly used to get an insight of flow characteristics of granular materials in complex particulate systems. DEM input parameters for a model are the critical prerequisite for an efficient simulation. Thus, the present investigation aims to determine DEM input parameters for Hertz-Mindlin model using soybeans as a granular material. To achieve this aim, widely acceptable calibration approach was used having standard box-type apparatus. Further, qualitative and quantitative findings such as particle profile, height of kernels retaining the acrylic wall, and angle of repose of experiments and numerical simulations were compared to get the parameters. The calibrated set of DEM input parameters includes the following (a) material properties: particle geometric mean diameter (6.24 mm); spherical shape; particle density (1220 kg m^{-3} ), and (b) interaction parameters such as particle-particle: coefficient of restitution (0.17); coefficient of static friction (0.26); coefficient of rolling friction (0.08), and particle-wall: coefficient of restitution (0.35); coefficient of static friction (0.30); coefficient of rolling friction (0.08). The results may adequately be used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc) of soybeans in post-harvest machinery and devices.
Ragulina, Galina; Reitan, Trond
2016-04-01
Assessing the probability of extreme precipitation events is of great importance in civil planning. This requires understanding of how return values change with different return periods, which is essentially described by the Generalized Extreme Value distribution's shape parameter. Some works in the field have suggested a constant shape parameter, while our analysis indicates a non-universal value. We first re-analyse an older precipitation dataset (169 stations) extended by Norwegian data (71 stations). We show that while each set seems to have a constant shape parameter, it differs between the two datasets, indicating regional differences. For a more comprehensive analysis of spatial effects, we examine a global dataset (1495 stations). We provide shape parameter maps for two models. We find clear evidence for the shape parameter being dependent on elevation while the effect of latitude remains uncertain. Our results confirm an explanation in terms of dominating precipitation systems based on a proxy derived from the Köppen-Geiger climate classification.
Value function in economic growth model
Bagno, Alexander; Tarasyev, Alexandr A.; Tarasyev, Alexander M.
2017-11-01
Properties of the value function are examined in an infinite horizon optimal control problem with an unlimited integrand index appearing in the quality functional with a discount factor. Optimal control problems of such type describe solutions in models of economic growth. Necessary and sufficient conditions are derived to ensure that the value function satisfies the infinitesimal stability properties. It is proved that value function coincides with the minimax solution of the Hamilton-Jacobi equation. Description of the growth asymptotic behavior for the value function is provided for the logarithmic, power and exponential quality functionals and an example is given to illustrate construction of the value function in economic growth models.
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rautenstrauch
2004-09-10
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
K. Rautenstrauch
2004-01-01
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception
Directory of Open Access Journals (Sweden)
Guo Yu
2016-01-01
Full Text Available As a major step surface mount technology, reflow process is the key factor affecting the quality of the final product. The setting parameters and characteristic value of temperature curve shows a nonlinear relationship. So parameter impacts on characteristic values are analyzed and the parameters adjustment process based on orthogonal experiment is proposed in the paper. First, setting parameters are determined and the orthogonal test is designed according to production conditions. Then each characteristic value for temperature profile is calculated. Further, multi-index orthogonal experiment is analyzed for acquiring the setting parameters which impacts the PCBA product quality greater. Finally, reliability prediction is carried out considering the main influencing parameters for providing a theoretical basis of parameters adjustment and product quality evaluation in engineering process.
Modeling Business Strategy: A Consumer Value Perspective
Svee , Eric-Oluf; Giannoulis , Constantinos; Zdravkovic , Jelena
2011-01-01
Part 3: Business Modeling; International audience; Business strategy lays out the plan of an enterprise to achieve its vision by providing value to its customers. Typically, business strategy focuses on economic value and its relevant exchanges with customers and does not directly address consumer values. However, consumer values drive customers’ choices and decisions to use a product or service, and therefore should have a direct impact on business strategy. This paper explores whether and h...
The heuristic value of redundancy models of aging.
Boonekamp, Jelle J; Briga, Michael; Verhulst, Simon
2015-11-01
Molecular studies of aging aim to unravel the cause(s) of aging bottom-up, but linking these mechanisms to organismal level processes remains a challenge. We propose that complementary top-down data-directed modelling of organismal level empirical findings may contribute to developing these links. To this end, we explore the heuristic value of redundancy models of aging to develop a deeper insight into the mechanisms causing variation in senescence and lifespan. We start by showing (i) how different redundancy model parameters affect projected aging and mortality, and (ii) how variation in redundancy model parameters relates to variation in parameters of the Gompertz equation. Lifestyle changes or medical interventions during life can modify mortality rate, and we investigate (iii) how interventions that change specific redundancy parameters within the model affect subsequent mortality and actuarial senescence. Lastly, as an example of data-directed modelling and the insights that can be gained from this, (iv) we fit a redundancy model to mortality patterns observed by Mair et al. (2003; Science 301: 1731-1733) in Drosophila that were subjected to dietary restriction and temperature manipulations. Mair et al. found that dietary restriction instantaneously reduced mortality rate without affecting aging, while temperature manipulations had more transient effects on mortality rate and did affect aging. We show that after adjusting model parameters the redundancy model describes both effects well, and a comparison of the parameter values yields a deeper insight in the mechanisms causing these contrasting effects. We see replacement of the redundancy model parameters by more detailed sub-models of these parameters as a next step in linking demographic patterns to underlying molecular mechanisms. Copyright © 2015 Elsevier Inc. All rights reserved.
Automated parameter estimation for biological models using Bayesian statistical model checking.
Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K
2015-01-01
Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.
The value of multivariate model sophistication
DEFF Research Database (Denmark)
Rombouts, Jeroen; Stentoft, Lars; Violante, Francesco
2014-01-01
We assess the predictive accuracies of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set of 444 multivariate models that differ in their spec....... In addition to investigating the value of model sophistication in terms of dollar losses directly, we also use the model confidence set approach to statistically infer the set of models that delivers the best pricing performances.......We assess the predictive accuracies of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set of 444 multivariate models that differ...
A software for parameter estimation in dynamic models
Directory of Open Access Journals (Sweden)
M. Yuceer
2008-12-01
Full Text Available A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.
Modelling of intermittent microwave convective drying: parameter sensitivity
Directory of Open Access Journals (Sweden)
Zhang Zhijun
2017-06-01
Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.
Constant-parameter capture-recapture models
Brownie, C.; Hines, J.E.; Nichols, J.D.
1986-01-01
Jolly (1982, Biometrics 38, 301-321) presented modifications of the Jolly-Seber model for capture-recapture data, which assume constant survival and/or capture rates. Where appropriate, because of the reduced number of parameters, these models lead to more efficient estimators than the Jolly-Seber model. The tests to compare models given by Jolly do not make complete use of the data, and we present here the appropriate modifications, and also indicate how to carry out goodness-of-fit tests which utilize individual capture history information. We also describe analogous models for the case where young and adult animals are tagged. The availability of computer programs to perform the analysis is noted, and examples are given using output from these programs.
Rights and Intentions in Value Modeling
Johannesson, Paul; Bergholtz, Maria
In order to manage increasingly complex business and IT environments, organizations need effective instruments for representing and understanding this complexity. Essential among these instruments are enterprise models, i.e. computational representations of the structure, processes, information, resources, and intentions of organizations. One important class of enterprise models are value models, which focus on the business motivations and intentions behind business processes and describe them in terms of high level notions like actors, resources, and value exchanges. The essence of these value exchanges is often taken to be an ownership transfer. However, some value exchanges cannot be analyzed in this way, e.g. the use of a service does not influence ownership. The goal of this chapter is to offer an analysis of the notion of value exchanges, based on Hohfeld's classification of rights, and to propose notation and practical modeling guidelines that make use of this analysis.
Environment Modeling Using Runtime Values for JPF-Android
van der Merwe, Heila; Tkachuk, Oksana; Nel, Seal; van der Merwe, Brink; Visser, Willem
2015-01-01
Software applications are developed to be executed in a specific environment. This environment includes external native libraries to add functionality to the application and drivers to fire the application execution. For testing and verification, the environment of an application is simplified abstracted using models or stubs. Empty stubs, returning default values, are simple to generate automatically, but they do not perform well when the application expects specific return values. Symbolic execution is used to find input parameters for drivers and return values for library stubs, but it struggles to detect the values of complex objects. In this work-in-progress paper, we explore an approach to generate drivers and stubs based on values collected during runtime instead of using default values. Entry-points and methods that need to be modeled are instrumented to log their parameters and return values. The instrumented applications are then executed using a driver and instrumented libraries. The values collected during runtime are used to generate driver and stub values on- the-fly that improve coverage during verification by enabling the execution of code that previously crashed or was missed. We are implementing this approach to improve the environment model of JPF-Android, our model checking and analysis tool for Android applications.
Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J
2014-01-01
Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.
A Note on the Item Information Function of the Four-Parameter Logistic Model
Magis, David
2013-01-01
This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…
Soil-related Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
A. J. Smith
2003-01-01
This analysis is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the geologic repository at Yucca Mountain. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash
Directory of Open Access Journals (Sweden)
O. M. Horobchenko
2015-12-01
Full Text Available Purpose. During development of intelligent control systems for locomotive there is a need in the evaluation of the current train situation in the terms of traffic safety. In order to estimate the probability of the development of various emergency situations in to the traffic accidents, it is necessary to determine their complexity. The purpose of this paper is to develop the methodology for determining the complexity of emergency situations during the locomotive operation. Methodology. To achieve this purpose the statistical material of traffic safety violations was accumulated. The causes of violations are divided into groups: technical factors, human factors and external influences. Using the theory of hybrid networks it was obtained a model that gives the output complexity parameter of the emergency situation. Network type: multilayer perceptron with hybrid neurons of the first layer and the sigmoid activation function. The methods of the probability theory were used for the analysis of the results. Findings. The approach to the formalization of manufacturing situations that can only be described linguistically was developed, that allowed to use them as input data to the model for emergency situation. It was established and proved that the exponent of complexity for emergency situation during driving the train is a random quantity and obeys to the normal distribution law. It was obtained the graph of the cumulative distribution function, which identified the areas for safe operation and an increased risk of accident. Originality. It was proposed theoretical basis for determining the complexity of emergency situations in the train work and received the maximum complexity value of emergency situations that can be admitted in the operating conditions. Practical value. Constant monitoring of this value allows not only respond to the threat of danger, but also getting it in numerical form and use it as one of the input parameters for the
Extreme values of meteorological parameters observed at Kalpakkam during the period 1968-1999
International Nuclear Information System (INIS)
Balagurunathan, M.R.; Chandresekharan, E.; Rajan, M.P.; Gurg, R.P.
2001-05-01
In the design phase of engineering structures, an understanding of extreme weather conditions that may occur at the site of interest is very essential, so that the structures can be designed to withstand climatological stresses during its life time. In this report an analysis of extreme values of meteorological parameters at Kalpakkam for the period 1968-99, which provide an insight into such situations is described. The extreme value analysis reveals that all the variables obey Fisher-Tippet Type-I extreme value distribution function. Parameter values of extreme value analysis functions are presented for the variables studied and the 50- and 100- year return period extreme values are arrived at. Frequency distribution of rainfall parameters is investigated. Time series of annual rainfall data suggests a cycle of 2-3 years period. (author)
Reconciling Planck with the local value of H0 in extended parameter space
Directory of Open Access Journals (Sweden)
Eleonora Di Valentino
2016-10-01
Full Text Available The recent determination of the local value of the Hubble constant by Riess et al., 2016 (hereafter R16 is now 3.3 sigma higher than the value derived from the most recent CMB anisotropy data provided by the Planck satellite in a ΛCDM model. Here we perform a combined analysis of the Planck and R16 results in an extended parameter space, varying simultaneously 12 cosmological parameters instead of the usual 6. We find that a phantom-like dark energy component, with effective equation of state w=−1.29−0.12+0.15 at 68% c.l. can solve the current tension between the Planck dataset and the R16 prior in an extended ΛCDM scenario. On the other hand, the neutrino effective number is fully compatible with standard expectations. This result is confirmed when including cosmic shear data from the CFHTLenS survey and CMB lensing constraints from Planck. However, when BAO measurements are included we find that some of the tension with R16 remains, as also is the case when we include the supernova type Ia luminosity distances from the JLA catalog.
The lumped parameter model for fuel pins
Energy Technology Data Exchange (ETDEWEB)
Liu, W S [Ontario Hydro, Toronto, ON (Canada)
1996-12-31
The use of a lumped fuel-pin model in a thermal-hydraulic code is advantageous because of computational simplicity and efficiency. The model uses an averaging approach over the fuel cross section and makes some simplifying assumptions to describe the transient equations for the averaged fuel, fuel centerline and sheath temperatures. It is shown that by introducing a factor in the effective fuel conductivity, the analytical solution of the mean fuel temperature can be modified to simulate the effects of the flux depression in the heat generation rate and the variation in fuel thermal conductivity. The simplified analytical method used in the transient equation is presented. The accuracy of the lumped parameter model has been compared with the results from the finite difference method. (author). 4 refs., 2 tabs., 4 figs.
Comparison of perceived value structural models
Directory of Open Access Journals (Sweden)
Sunčana Piri Rajh
2012-07-01
Full Text Available Perceived value has been considered an important determinant of consumer shopping behavior and studied as such for a long period of time. According to one research stream, perceived value is a variable determined by perceived quality and perceived sacrifice. Another research stream suggests that the perception of value is a result of the consumer risk perception. This implies the presence of two somewhat independent research streams that are integrated by a third research stream – the one suggesting that perceived value is a result of perceived quality and perceived sacrifices while perceived (performance and financial risk mediates the relationship between perceived quality and perceived sacrifices on the one hand, and perceived value on the other. This paper describes the three approaches (models that have been mentioned. The aim of the paper is to determine which of the observed models show the most acceptable level of fit to the empirical data. Using the survey method, research involving three product categories has been conducted on a sample of Croatian consumers. Collected data was analyzed by the structural equation modeling (SEM method. Research has shown an appropriate level of fit of each observed model to the empirical data. However, the model measuring the effect of perceived risk on perceived value indicates the best level of fit, which implies that perceived performance risk and perceived financial risk are the best predictors of perceived value.
The level density parameters for fermi gas model
International Nuclear Information System (INIS)
Zuang Youxiang; Wang Cuilan; Zhou Chunmei; Su Zongdi
1986-01-01
Nuclear level densities are crucial ingredient in the statistical models, for instance, in the calculations of the widths, cross sections, emitted particle spectra, etc. for various reaction channels. In this work 667 sets of more reliable and new experimental data are adopted, which include average level spacing D D , radiative capture width Γ γ 0 at neutron binding energy and cumulative level number N 0 at the low excitation energy. They are published during 1973 to 1983. Based on the parameters given by Gilbert-Cameon and Cook the physical quantities mentioned above are calculated. The calculated results have the deviation obviously from experimental values. In order to improve the fitting, the parameters in the G-C formula are adjusted and new set of level density parameters is obsained. The parameters is this work are more suitable to fit new measurements
Weak-value amplification and optimal parameter estimation in the presence of correlated noise
Sinclair, Josiah; Hallaji, Matin; Steinberg, Aephraim M.; Tollaksen, Jeff; Jordan, Andrew N.
2017-11-01
We analytically and numerically investigate the performance of weak-value amplification (WVA) and related parameter estimation methods in the presence of temporally correlated noise. WVA is a special instance of a general measurement strategy that involves sorting data into separate subsets based on the outcome of a second "partitioning" measurement. Using a simplified correlated noise model that can be analyzed exactly together with optimal statistical estimators, we compare WVA to a conventional measurement method. We find that WVA indeed yields a much lower variance of the parameter of interest than the conventional technique does, optimized in the absence of any partitioning measurements. In contrast, a statistically optimal analysis that employs partitioning measurements, incorporating all partitioned results and their known correlations, is found to yield an improvement—typically slight—over the noise reduction achieved by WVA. This result occurs because the simple WVA technique is not tailored to any specific noise environment and therefore does not make use of correlations between the different partitions. We also compare WVA to traditional background subtraction, a familiar technique where measurement outcomes are partitioned to eliminate unknown offsets or errors in calibration. Surprisingly, for the cases we consider, background subtraction turns out to be a special case of the optimal partitioning approach, possessing a similar typically slight advantage over WVA. These results give deeper insight into the role of partitioning measurements (with or without postselection) in enhancing measurement precision, which some have found puzzling. They also resolve previously made conflicting claims about the usefulness of weak-value amplification to precision measurement in the presence of correlated noise. We finish by presenting numerical results to model a more realistic laboratory situation of time-decaying correlations, showing that our conclusions hold
Modeling of Parameters of Subcritical Assembly SAD
Petrochenkov, S; Puzynin, I
2005-01-01
The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.
Parameter estimation in fractional diffusion models
Kubilius, Kęstutis; Ralchenko, Kostiantyn
2017-01-01
This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is “white,” i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides s...
International Nuclear Information System (INIS)
Beaujean, F.; Caldwell, A.; Kollar, D.; Kroeninger, K.
2011-01-01
Deciding whether a model provides a good description of data is often based on a goodness-of-fit criterion summarized by a p-value. Although there is considerable confusion concerning the meaning of p-values, leading to their misuse, they are nevertheless of practical importance in common data analysis tasks. We motivate their application using a Bayesian argumentation. We then describe commonly and less commonly known discrepancy variables and how they are used to define p-values. The distribution of these are then extracted for examples modeled on typical data analysis tasks, and comments on their usefulness for determining goodness-of-fit are given.
Empirical flow parameters : a tool for hydraulic model validity
Asquith, William H.; Burley, Thomas E.; Cleveland, Theodore G.
2013-01-01
The objectives of this project were (1) To determine and present from existing data in Texas, relations between observed stream flow, topographic slope, mean section velocity, and other hydraulic factors, to produce charts such as Figure 1 and to produce empirical distributions of the various flow parameters to provide a methodology to "check if model results are way off!"; (2) To produce a statistical regional tool to estimate mean velocity or other selected parameters for storm flows or other conditional discharges at ungauged locations (most bridge crossings) in Texas to provide a secondary way to compare such values to a conventional hydraulic modeling approach. (3.) To present ancillary values such as Froude number, stream power, Rosgen channel classification, sinuosity, and other selected characteristics (readily determinable from existing data) to provide additional information to engineers concerned with the hydraulic-soil-foundation component of transportation infrastructure.
Estimating model parameters in nonautonomous chaotic systems using synchronization
International Nuclear Information System (INIS)
Yang, Xiaoli; Xu, Wei; Sun, Zhongkui
2007-01-01
In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation
Parameter values for the Heysham site for use in the CODAR2 program
International Nuclear Information System (INIS)
Maul, P.R.
1985-03-01
Details are given of parameter values relevant to the Heysham site for the calculation of individual and collective radiation exposure arising from routine discharges of liquid effluent to the sea. These parameters are to be used in the CODAR2 computer program, and the approach taken in their specification is the same as that employed previously for the Sizewell site. (author)
Quinn, Terrance; Sinkala, Zachariah
2014-01-01
We develop a general method for computing extreme value distribution (Gumbel, 1958) parameters for gapped alignments. Our approach uses mixture distribution theory to obtain associated BLOSUM matrices for gapped alignments, which in turn are used for determining significance of gapped alignment scores for pairs of biological sequences. We compare our results with parameters already obtained in the literature.
Prediction of interest rate using CKLS model with stochastic parameters
International Nuclear Information System (INIS)
Ying, Khor Chia; Hin, Pooi Ah
2014-01-01
The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ (j) of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ (j) , we assume that φ (j) depends on φ (j−m) , φ (j−m+1) ,…, φ (j−1) and the interest rate r j+n at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r j+n+1 of the interest rate at the next time point when the value r j+n of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r j+n+d at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters
Prediction of interest rate using CKLS model with stochastic parameters
Energy Technology Data Exchange (ETDEWEB)
Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)
2014-06-19
The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.
Moose models with vanishing S parameter
International Nuclear Information System (INIS)
Casalbuoni, R.; De Curtis, S.; Dominici, D.
2004-01-01
In the linear moose framework, which naturally emerges in deconstruction models, we show that there is a unique solution for the vanishing of the S parameter at the lowest order in the weak interactions. We consider an effective gauge theory based on K SU(2) gauge groups, K+1 chiral fields, and electroweak groups SU(2) L and U(1) Y at the ends of the chain of the moose. S vanishes when a link in the moose chain is cut. As a consequence one has to introduce a dynamical nonlocal field connecting the two ends of the moose. Then the model acquires an additional custodial symmetry which protects this result. We examine also the possibility of a strong suppression of S through an exponential behavior of the link couplings as suggested by the Randall Sundrum metric
Dual Value Creation and Business Model Design
DEFF Research Database (Denmark)
Turcan, Romeo V.
This ethnographic research explores the process of business model design in the context of an NGO internationalizing to an emerging market. It contributes to the business model literature by investigating how this NGO - targeting multiple key stakeholders - was experimenting (1) with value...
Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.
Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E
2013-12-01
Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.
Estimation Parameters And Modelling Zero Inflated Negative Binomial
Directory of Open Access Journals (Sweden)
Cindy Cahyaning Astuti
2016-11-01
Full Text Available Regression analysis is used to determine relationship between one or several response variable (Y with one or several predictor variables (X. Regression model between predictor variables and the Poisson distributed response variable is called Poisson Regression Model. Since, Poisson Regression requires an equality between mean and variance, it is not appropriate to apply this model on overdispersion (variance is higher than mean. Poisson regression model is commonly used to analyze the count data. On the count data type, it is often to encounteredd some observations that have zero value with large proportion of zero value on the response variable (zero Inflation. Poisson regression can be used to analyze count data but it has not been able to solve problem of excess zero value on the response variable. An alternative model which is more suitable for overdispersion data and can solve the problem of excess zero value on the response variable is Zero Inflated Negative Binomial (ZINB. In this research, ZINB is applied on the case of Tetanus Neonatorum in East Java. The aim of this research is to examine the likelihood function and to form an algorithm to estimate the parameter of ZINB and also applying ZINB model in the case of Tetanus Neonatorum in East Java. Maximum Likelihood Estimation (MLE method is used to estimate the parameter on ZINB and the likelihood function is maximized using Expectation Maximization (EM algorithm. Test results of ZINB regression model showed that the predictor variable have a partial significant effect at negative binomial model is the percentage of pregnant women visits and the percentage of maternal health personnel assisted, while the predictor variables that have a partial significant effect at zero inflation model is the percentage of neonatus visits.
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. Wasiolek
2006-06-05
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. Wasiolek
2006-01-01
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This report is concerned primarily with the
Climate change decision-making: Model & parameter uncertainties explored
Energy Technology Data Exchange (ETDEWEB)
Dowlatabadi, H.; Kandlikar, M.; Linville, C.
1995-12-31
A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.
On the effect of model parameters on forecast objects
Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott
2018-04-01
Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.
The values of the parameters of some multilayer distributed RC null networks
Huelsman, L. P.; Raghunath, S.
1974-01-01
In this correspondence, the values of the parameters of some multilayer distributed RC notch networks are determined, and the usually accepted values are shown to be in error. The magnitude of the error is illustrated by graphs of the frequency response of the networks.
A critical look at the kinetic parameter values used in simulating the thermoluminescence glow-curve
Energy Technology Data Exchange (ETDEWEB)
Sadek, A.M., E-mail: dr_amrsadek@hotmail.com [Ionizing Radiation Metrology Department, National Institute for Standards, El-Haram, Giza (Egypt); Kitis, G. [Nuclear Physics and Elementary Particles Physics Section, Physics Department, Aristotle University of Thessaloniki, 54124 Thessaloniki, Makedonia (Greece)
2017-03-15
Objections against utilizing the peak fitting method in computing the kinetics parameters of thermoluminescence (TL) glow-peaks were discussed previously in the literature. These objections came through testing the accuracy of the peak fitting by applying on simulated peaks. The results showed that in some cases the simulated peaks may have unusual geometrical properties and do not reflect the real properties of TL peaks. Thereby, estimating the accuracy of the peak fitting by applying on such peaks would be misleading. Two main reasons may lead to unrealistic simulated peaks; the improper selection of the simulation inputs, and performing the TL simulation process via the heating stage only. It has been proved that considering the irradiation and the relaxation stages in the simulation process is crucial. However, there are other cases in which the analytical methods were not able to reveal the real values of the simulated peaks. These cases were successfully resolved using analytical expressions derived from the one trap-one recombination (OTOR) level model and the non-interactive multiple trap system (NMTS) model. A general conclusion can be drawn that the accuracy of the peak fitting method is critically dependent on the TL analytical expressions utilized in this method. The failure of this method in estimating the TL kinetic parameters should be attributed to the TL model equation utilized in fitting process. - Highlights: • Objections against using the TL peak fitting method are discussed. • Improper selection of simulation inputs may lead to non realistic TL peaks. • Considering the irradiation and the relaxation stages in simulation is crucial. • TL expressions could not describe TL peaks with unrealistic geometrical properties. • The accuracy of the peak fitting method depends on the model used in the fitting.
Exploring Parameter Tuning for Analysis and Optimization of a Computational Model
Mollee, J.S.; Fernandes de Mello Araujo, E.; Klein, M.C.A.
2017-01-01
Computational models of human processes are used for many different purposes and in many different types of applications. A common challenge in using such models is to find suitable parameter values. In many cases, the ideal parameter values are those that yield the most realistic simulation
Parameter estimation in nonlinear models for pesticide degradation
International Nuclear Information System (INIS)
Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.
1991-01-01
A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)
The estimation of parameter compaction values for pavement subgrade stabilized with lime
Lubis, A. S.; Muis, Z. A.; Simbolon, C. A.
2018-02-01
The type of soil material, field control, maintenance and availability of funds are several factors that must be considered in compaction of the pavement subgrade. In determining the compaction parameters in laboratory desperately requires considerable materials, time and funds, and reliable laboratory operators. If the result of soil classification values can be used to estimate the compaction parameters of a subgrade material, so it would save time, energy, materials and cost on the execution of this work. This is also a clarification (cross check) of the work that has been done by technicians in the laboratory. The study aims to estimate the compaction parameter values ie. maximum dry unit weight (γdmax) and optimum water content (Wopt) of the soil subgrade that stabilized with lime. The tests that conducted in the laboratory of soil mechanics were to determine the index properties (Fines and Liquid Limit/LL) and Standard Compaction Test. Soil samples that have Plasticity Index (PI) > 10% were made with additional 3% lime for 30 samples. By using the Goswami equation, the compaction parameter values can be estimated by equation γd max # = -0,1686 Log G + 1,8434 and Wopt # = 2,9178 log G + 17,086. From the validation calculation, there was a significant positive correlation between the compaction parameter values laboratory and the compaction parameter values estimated, with a 95% confidence interval as a strong relationship.
Iterative integral parameter identification of a respiratory mechanics model.
Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey
2012-07-18
Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
Iterative integral parameter identification of a respiratory mechanics model
Directory of Open Access Journals (Sweden)
Schranz Christoph
2012-07-01
Full Text Available Abstract Background Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual’s model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. Methods An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS patients. Results The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. Conclusion These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
Importance of hydrological parameters in contaminant transport modeling in a terrestrial environment
International Nuclear Information System (INIS)
Tsuduki, Katsunori; Matsunaga, Takeshi
2007-01-01
A grid type multi-layered distributed parameter model for calculating discharge in a watershed was described. Model verification with our field observation resulted in different sets of hydrological parameter values, all of which reproduced the observed discharge. The effect of those varied hydrological parameters on contaminant transport calculation was examined and discussed by simulation of event water transfer. (author)
Recommended food chain parameter values and distributions for use around CANDU sites in Ontario
Energy Technology Data Exchange (ETDEWEB)
Peterson, S R
1996-07-01
Site-specific parameter values should be used whenever possible to increase the accuracy of dose predictions. Parameter values specific to agricultural practices and human lifestyles in southern Ontario are presented for use in CSA-N288.1-M87 (Canadian Standards Association Guidelines for Calculating Derived Release Limits for Radioactive Material in Airborne and Liquid Effluents for Normal Operation of Nuclear Facilities) and CHERPAC (Chalk River Environmental Research Pathways Analysis Code). Use of these values in place of the default parameter values in CSA-N288.1-M87 is shown to reduce the predicted dose by nearly a factor of 2. (author). 27 refs., 6 tabs., 1 fig.
Recommended food chain parameter values and distributions for use around CANDU sites in Ontario
International Nuclear Information System (INIS)
Peterson, S.R.
1996-07-01
Site-specific parameter values should be used whenever possible to increase the accuracy of dose predictions. Parameter values specific to agricultural practices and human lifestyles in southern Ontario are presented for use in CSA-N288.1-M87 (Canadian Standards Association Guidelines for Calculating Derived Release Limits for Radioactive Material in Airborne and Liquid Effluents for Normal Operation of Nuclear Facilities) and CHERPAC (Chalk River Environmental Research Pathways Analysis Code). Use of these values in place of the default parameter values in CSA-N288.1-M87 is shown to reduce the predicted dose by nearly a factor of 2. (author). 27 refs., 6 tabs., 1 fig
Four-parameter analytical local model potential for atoms
International Nuclear Information System (INIS)
Fei, Yu; Jiu-Xun, Sun; Rong-Gang, Tian; Wei, Yang
2009-01-01
Analytical local model potential for modeling the interaction in an atom reduces the computational effort in electronic structure calculations significantly. A new four-parameter analytical local model potential is proposed for atoms Li through Lr, and the values of four parameters are shell-independent and obtained by fitting the results of X a method. At the same time, the energy eigenvalues, the radial wave functions and the total energies of electrons are obtained by solving the radial Schrödinger equation with a new form of potential function by Numerov's numerical method. The results show that our new form of potential function is suitable for high, medium and low Z atoms. A comparison among the new potential function and other analytical potential functions shows the greater flexibility and greater accuracy of the present new potential function. (atomic and molecular physics)
Revised Parameters for the AMOEBA Polarizable Atomic Multipole Water Model
Pande, Vijay S.; Head-Gordon, Teresa; Ponder, Jay W.
2016-01-01
A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. The protocol uses an automated procedure, ForceBalance, to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimentally obtained data for a variety of liquid phase properties across a broad temperature range. The values reported here for the new AMOEBA14 water model represent a substantial improvement over the previous AMOEBA03 model. The new AMOEBA14 water model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures ranging from 249 K to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to a variety of experimental properties as a function of temperature, including the 2nd virial coefficient, enthalpy of vaporization, isothermal compressibility, thermal expansion coefficient and dielectric constant. The viscosity, self-diffusion constant and surface tension are also well reproduced. In comparison to high-level ab initio results for clusters of 2 to 20 water molecules, the AMOEBA14 model yields results similar to the AMOEBA03 and the direct polarization iAMOEBA models. With advances in computing power, calibration data, and optimization techniques, we recommend the use of the AMOEBA14 water model for future studies employing a polarizable water model. PMID:25683601
Dolka, B; Włodarczyk, R; Zbikowski, A; Dolka, I; Szeleszczuk, P; Kluciński, W
2014-06-01
The knowledge of the correct morphological and biochemical parameters in mute swans is an important indicator of their health status, body condition, adaptation to habitat and useful diagnostic tools in veterinary practice and ecological research. The aim of the study was to obtain hematological parameters in relation to age, sex and serum biochemistry values in wild-living mute swans. We found the significant differences in the erythrocyte count, hematocrit, hemoglobin concentration and erythrocyte sedimentation rate in relation to age of mute swans. There were no differences in hematological values between males and females. The leukogram and H/L ratio did not vary by age and sex in swans. Among of biochemical parameters the slightly increased AST, ALP, CK, K, urea, decreased CHOL and TG values were recorded. As far as we know, this is the first study in which the morphometric parameters of blood cells in mute swans were presented. We found extremely low concentration of lead in blood (at subthreshold level). No blood parasites were found in blood smears. The analysis of body mass and biometric parameters revealed a significant differences dependent on age and sex. No differences in the scaled mass index were found. Our results represent a normal hematologic and blood chemistry values and age-sex related changes, as reference values for the mute swan.
Baseline values of immunologic parameters in the lizard Salvator merianae (Teiidae, Squamata)
Mestre, Ana Paula; Amavet, Patricia Susana; Siroski, Pablo Ariel
2017-01-01
The genus Salvator is widely distributed throughout South America. In Argentina, the species most abundant widely distributed is Salvator merianae. Particularly in Santa Fe province, the area occupied by populations of these lizards overlaps with areas where agriculture was extended. With the aim of established baseline values for four immunologic biomarkers widely used, 36 tegu lizards were evaluated tacking into account different age classes and both sexes. Total leukocyte counts were not different between age classes. Of the leucocytes count, eosinophils levels were higher in neonates compared with juvenile and adults; nevertheless, the heterophils group was the most prevalent leukocyte in the peripheral blood in all age classes. Lymphocytes, monocytes, heterophils, azurophils and basophils levels did not differ with age. Natural antibodies titres were higher in the adults compared with neonates and juveniles lizards. Lastly, complement system activity was low in neonates compared with juveniles and adults. Statistical analysis within each age group showed that gender was not a factor in the outcomes. Based on the results, we concluded that S. merianae demonstrated age (but not gender) related differences in the immune parameters analyzed. Having established baseline values for these four widely-used immunologic biomarkers, ongoing studies will seek to optimize the use of the S. merianae model in future research. PMID:28652981
Baseline values of immunologic parameters in the lizard Salvator merianae (Teiidae, Squamata).
Mestre, Ana Paula; Amavet, Patricia Susana; Siroski, Pablo Ariel
2017-01-01
The genus Salvator is widely distributed throughout South America. In Argentina, the species most abundant widely distributed is Salvator merianae . Particularly in Santa Fe province, the area occupied by populations of these lizards overlaps with areas where agriculture was extended. With the aim of established baseline values for four immunologic biomarkers widely used, 36 tegu lizards were evaluated tacking into account different age classes and both sexes. Total leukocyte counts were not different between age classes. Of the leucocytes count, eosinophils levels were higher in neonates compared with juvenile and adults; nevertheless, the heterophils group was the most prevalent leukocyte in the peripheral blood in all age classes. Lymphocytes, monocytes, heterophils, azurophils and basophils levels did not differ with age. Natural antibodies titres were higher in the adults compared with neonates and juveniles lizards. Lastly, complement system activity was low in neonates compared with juveniles and adults. Statistical analysis within each age group showed that gender was not a factor in the outcomes. Based on the results, we concluded that S. merianae demonstrated age (but not gender) related differences in the immune parameters analyzed. Having established baseline values for these four widely-used immunologic biomarkers, ongoing studies will seek to optimize the use of the S. merianae model in future research.
Baseline values of immunologic parameters in the lizard Salvator merianae (Teiidae, Squamata
Directory of Open Access Journals (Sweden)
Ana Paula Mestre
2017-05-01
Full Text Available The genus Salvator is widely distributed throughout South America. In Argentina, the species most abundant widely distributed is Salvator merianae. Particularly in Santa Fe province, the area occupied by populations of these lizards overlaps with areas where agriculture was extended. With the aim of established baseline values for four immunologic biomarkers widely used, 36 tegu lizards were evaluated tacking into account different age classes and both sexes. Total leukocyte counts were not different between age classes. Of the leucocytes count, eosinophils levels were higher in neonates compared with juvenile and adults; nevertheless, the heterophils group was the most prevalent leukocyte in the peripheral blood in all age classes. Lymphocytes, monocytes, heterophils, azurophils and basophils levels did not differ with age. Natural antibodies titres were higher in the adults compared with neonates and juveniles lizards. Lastly, complement system activity was low in neonates compared with juveniles and adults. Statistical analysis within each age group showed that gender was not a factor in the outcomes. Based on the results, we concluded that S. merianae demonstrated age (but not gender related differences in the immune parameters analyzed. Having established baseline values for these four widely-used immunologic biomarkers, ongoing studies will seek to optimize the use of the S. merianae model in future research.
Continuous Spatial Process Models for Spatial Extreme Values
Sang, Huiyan
2010-01-28
We propose a hierarchical modeling approach for explaining a collection of point-referenced extreme values. In particular, annual maxima over space and time are assumed to follow generalized extreme value (GEV) distributions, with parameters μ, σ, and ξ specified in the latent stage to reflect underlying spatio-temporal structure. The novelty here is that we relax the conditionally independence assumption in the first stage of the hierarchial model, an assumption which has been adopted in previous work. This assumption implies that realizations of the the surface of spatial maxima will be everywhere discontinuous. For many phenomena including, e. g., temperature and precipitation, this behavior is inappropriate. Instead, we offer a spatial process model for extreme values that provides mean square continuous realizations, where the behavior of the surface is driven by the spatial dependence which is unexplained under the latent spatio-temporal specification for the GEV parameters. In this sense, the first stage smoothing is viewed as fine scale or short range smoothing while the larger scale smoothing will be captured in the second stage of the modeling. In addition, as would be desired, we are able to implement spatial interpolation for extreme values based on this model. A simulation study and a study on actual annual maximum rainfall for a region in South Africa are used to illustrate the performance of the model. © 2009 International Biometric Society.
Electro-optical parameters of bond polarizability model for aluminosilicates.
Smirnov, Konstantin S; Bougeard, Daniel; Tandon, Poonam
2006-04-06
Electro-optical parameters (EOPs) of bond polarizability model (BPM) for aluminosilicate structures were derived from quantum-chemical DFT calculations of molecular models. The tensor of molecular polarizability and the derivatives of the tensor with respect to the bond length are well reproduced with the BPM, and the EOPs obtained are in a fair agreement with available experimental data. The parameters derived were found to be transferable to larger molecules. This finding suggests that the procedure used can be applied to systems with partially ionic chemical bonds. The transferability of the parameters to periodic systems was tested in molecular dynamics simulation of the polarized Raman spectra of alpha-quartz. It appeared that the molecular Si-O bond EOPs failed to reproduce the intensity of peaks in the spectra. This limitation is due to large values of the longitudinal components of the bond polarizability and its derivative found in the molecular calculations as compared to those obtained from periodic DFT calculations of crystalline silica polymorphs by Umari et al. (Phys. Rev. B 2001, 63, 094305). It is supposed that the electric field of the solid is responsible for the difference of the parameters. Nevertheless, the EOPs obtained can be used as an initial set of parameters for calculations of polarizability related characteristics of relevant systems in the framework of BPM.
Model parameters estimation and sensitivity by genetic algorithms
International Nuclear Information System (INIS)
Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca
2003-01-01
In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The
New Trends, News Values, and New Models.
Higgins, Mary Anne
1996-01-01
Explores implications of the prediction that in the next millennium the public will experience a scarcity of knowledge and a surplus of information. Reviews research suggesting that journalists focus on these news values: emphasizing how/why, devaluing immediacy, specializing/analyzing, representing a constituency. Examines two new models of…
Value as a parameter to consider in operational strategies for CSP plants
de Meyer, Oelof; Dinter, Frank; Govender, Saneshan
2017-06-01
This paper introduced a value parameter to consider when analyzing operational strategies for CSP plants. The electric system in South Africa, used as case study, is severely constrained with an influx of renewables in the early phase of deployment. The energy demand curve for the system is analyzed showing the total wind and solar photovoltaic contributions for winter and summer. Due to the intermittent nature and meteorological operating conditions of wind and solar photovoltaic plants, the value of CSP plants within the electric system is introduced. Analyzing CSP plants based on the value parameter alone will remain only a philosophical view. Currently there is no quantifiable measure to translate the philosophical view or subjective value and it solely remains the position of the stakeholder. By introducing three other parameters, Cost, Plant and System to a holistic representation of the Operating Strategies of generation plants, the Value parameter can be translated into a quantifiable measure. Utilizing the country's current procurement program as case study, CSP operating under the various PPA within the Bid Windows are analyzed. The Value Cost Plant System diagram developed is used to quantify the value parameter. This paper concluded that no value is obtained from CSP plants operating under the Bid Window 1 & 2 Power Purchase Agreement. However, by recognizing the dispatchability potential of CSP plants in Bid Window 3 & 3.5, the value of CSP in the electric system can be quantified utilizing Value Added Relationship VCPS-diagram. Similarly ancillary services to the system were analyzed. One of the relationships that have not yet been explored within the industry is an interdependent relationship. It was emphasized that the cost and value structure is shared between the plant and system. Although this relationship is functional when the plant and system belongs to the same entity, additional value is achieved by marginalizing the cost structure. A
Parameter-free methods distinguish Wnt pathway models and guide design of experiments
MacLean, Adam L.; Rosen, Zvi; Byrne, Helen M.; Harrington, Heather A.
2015-01-01
models can fit this time course. We appeal to algebraic methods (concepts from chemical reaction network theory and matroid theory) to analyze the models without recourse to specific parameter values. These approaches provide insight into aspects of Wnt
Directory of Open Access Journals (Sweden)
Long Yuhua
2017-12-01
Full Text Available In this paper, we study second-order nonlinear discrete Robin boundary value problem with parameter dependence. Applying invariant sets of descending flow and variational methods, we establish some new sufficient conditions on the existence of sign-changing solutions, positive solutions and negative solutions of the system when the parameter belongs to appropriate intervals. In addition, an example is given to illustrate our results.
Extreme value analysis of meterological parameters observed at Narora during the period 1989-2001
International Nuclear Information System (INIS)
Varakhedkar, V.K.; Dube, B.; Gurg, R.P.
2002-08-01
The design of engineering structures requires an understanding of extreme weather conditions that may occur at the site of interest, which is very essential, so that the structures can be designed to withstand weather stresses. In this report an analysis of extreme values of meteorological parameters observed at Narora for the period 1989- 2001 is described. The parameters considered are maximum and minimum air temperature, minimum relative humidity, maximum wind speed, maximum rainfall in a day and month, and annual rainfall. The extreme value analysis reveals that the variables such as annual maximum air temperature, minimum relative humidity and monthly maximum rainfall obey Fisher -Tippet Type -I extreme value distribution where as annual minimum air temperature, maximum hourly wind speed, daily maximum rainfall and maximum and minimum annual rainfall, obey Fisher -Tippet Type -2 extreme value distribution function. Various distribution function parameters for each variable are determined. Extreme values corresponding to return periods of 50 years and 100 years are worked out. These derived extreme values are particularly useful for arriving at suitable design values to ensure the safety of any civil structure in Narora area with respect to stresses due to weather conditions. (author)
Voss, S C; Varamenti, E; Elzain Elgingo, M; Bourdon, P C
2014-04-01
Hematological and biochemical parameters of 160 Middle Eastern adolescent male athletes (aged from 12-18 years) were tested in order to investigate their iron status and to establish reference values for this population. A focus of this study was also the investigation of Reticulocyte hemoglobin (RetHe) and soluble transferrin receptor (sTfR). Complete blood count, reticulocyte and sera parameters were analyzed at the beginning of the training season for these adolescent athletes. As the diagnosis of iron deficiency in adolescents is extremely difficult subjects were subdivided in three age groups (12-13, 14-15, 16-18). For most of the parameters our results confirmed the existing reference values reported in young athletes. Exceptions were however found with lower Mean Cell Volumes (79.9±4.3 fl) in this group when compared to other age matched data. RetHe, ferritin and sTfR levels were monitored for the interpretation of the iron status in this population and reference values for these parameters were also established. Information to help evidence based decision making about the need for supplementation or further investigations is provided to physicians and nutritionists. RetHe with a proposed threshold value of 25 pg expands the list of parameters which can be used to monitor athletes.
An Alignment Model for Collaborative Value Networks
Bremer, Carlos; Azevedo, Rodrigo Cambiaghi; Klen, Alexandra Pereira
This paper presents parts of the work carried out in several global organizations through the development of strategic projects with high tactical and operational complexity. By investing in long-term relationships, strongly operating in the transformation of the competitive model and focusing on the value chain management, the main aim of these projects was the alignment of multiple value chains. The projects were led by the Axia Transformation Methodology as well as by its Management Model and following the principles of Project Management. As a concrete result of the efforts made in the last years in the Brazilian market this work also introduces the Alignment Model which supports the transformation process that the companies undergo.
Directory of Open Access Journals (Sweden)
Wałęga Andrzej
2017-12-01
Full Text Available The aim of the study was to assess the applicability of asymptotic functions for determining the value of CN parameter as a function of precipitation depth in mountain and upland catchments. The analyses were carried out in two catchments: the Rudawa, left tributary of the Vistula, and the Kamienica, right tributary of the Dunajec. The input material included data on precipitation and flows for a multi-year period 1980–2012, obtained from IMGW PIB in Warsaw. Two models were used to determine empirical values of CNobs parameter as a function of precipitation depth: standard Hawkins model and 2-CN model allowing for a heterogeneous nature of a catchment area.
Soil-Related Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
Smith, A. J.
2004-01-01
analysis revises the previous version with the same name (BSC 2003 [DIRS 161239]), which was itself a revision of one titled ''Evaluate Soil/Radionuclide Removal by Erosion and Leaching'' (CRWMS M and O 2001 [DIRS 152517]). In Revision 00 of this report, the data generated were fixed values (i.e., taking no account of uncertainty and variability). Revision 01 (BSC 2003 [DIRS 161239]) incorporated uncertainty and variability into the values for the bulk density, elemental partition coefficients, average annual loss of soil from erosion, resuspension enhancement factor, and field capacity water content. The current revision of this document improves the transparency and traceability of the products without changing the details of the analysis. This analysis report supports the treatment of six of the features, events, and processes (FEPs) applicable to the Yucca Mountain reference biosphere (DTN: MO0407SEPFEPLA.000 [DIRS 170760]). The use of the more recent FEP list in DTN: MO0407SEPFEPLA.000 [DIRS 170760] represents a deviation from the detail provided in the TWP (BSC 2004 [DIRS 169573]), which referenced a previous version of the FEP list. The parameters developed in this report support treatment of these six FEPs addressed in the biosphere model that are listed in Table 1-1. Inclusion and treatment of FEPs in the biosphere model is described in the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460], Section 6.2)
Soil-Related Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
A. J. Smith
2004-09-09
was defined as AP-SIII.9Q, ''Scientific Analyses''. This analysis revises the previous version with the same name (BSC 2003 [DIRS 161239]), which was itself a revision of one titled ''Evaluate Soil/Radionuclide Removal by Erosion and Leaching'' (CRWMS M&O 2001 [DIRS 152517]). In Revision 00 of this report, the data generated were fixed values (i.e., taking no account of uncertainty and variability). Revision 01 (BSC 2003 [DIRS 161239]) incorporated uncertainty and variability into the values for the bulk density, elemental partition coefficients, average annual loss of soil from erosion, resuspension enhancement factor, and field capacity water content. The current revision of this document improves the transparency and traceability of the products without changing the details of the analysis. This analysis report supports the treatment of six of the features, events, and processes (FEPs) applicable to the Yucca Mountain reference biosphere (DTN: MO0407SEPFEPLA.000 [DIRS 170760]). The use of the more recent FEP list in DTN: MO0407SEPFEPLA.000 [DIRS 170760] represents a deviation from the detail provided in the TWP (BSC 2004 [DIRS 169573]), which referenced a previous version of the FEP list. The parameters developed in this report support treatment of these six FEPs addressed in the biosphere model that are listed in Table 1-1. Inclusion and treatment of FEPs in the biosphere model is described in the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460], Section 6.2).
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. A. Wasiolek
2003-09-24
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. A. Wasiolek
2003-01-01
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air inhaled by a receptor. Concentrations in air to which the
A Continuous-Time Model for Valuing Foreign Exchange Options
Directory of Open Access Journals (Sweden)
James J. Kung
2013-01-01
Full Text Available This paper makes use of stochastic calculus to develop a continuous-time model for valuing European options on foreign exchange (FX when both domestic and foreign spot rates follow a generalized Wiener process. Using the dollar/euro exchange rate as input for parameter estimation and employing our FX option model as a yardstick, we find that the traditional Garman-Kohlhagen FX option model, which assumes constant spot rates, values incorrectly calls and puts for different values of the ratio of exchange rate to exercise price. Specifically, it undervalues calls when the ratio is between 0.70 and 1.08, and it overvalues calls when the ratio is between 1.18 and 1.30, whereas it overvalues puts when the ratio is between 0.70 and 0.82, and it undervalues puts when the ratio is between 0.86 and 1.30.
Energy Technology Data Exchange (ETDEWEB)
Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)
2016-02-15
A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.
Model parameter learning using Kullback-Leibler divergence
Lin, Chungwei; Marks, Tim K.; Pajovic, Milutin; Watanabe, Shinji; Tung, Chih-kuan
2018-02-01
In this paper, we address the following problem: For a given set of spin configurations whose probability distribution is of the Boltzmann type, how do we determine the model coupling parameters? We demonstrate that directly minimizing the Kullback-Leibler divergence is an efficient method. We test this method against the Ising and XY models on the one-dimensional (1D) and two-dimensional (2D) lattices, and provide two estimators to quantify the model quality. We apply this method to two types of problems. First, we apply it to the real-space renormalization group (RG). We find that the obtained RG flow is sufficiently good for determining the phase boundary (within 1% of the exact result) and the critical point, but not accurate enough for critical exponents. The proposed method provides a simple way to numerically estimate amplitudes of the interactions typically truncated in the real-space RG procedure. Second, we apply this method to the dynamical system composed of self-propelled particles, where we extract the parameter of a statistical model (a generalized XY model) from a dynamical system described by the Viscek model. We are able to obtain reasonable coupling values corresponding to different noise strengths of the Viscek model. Our method is thus able to provide quantitative analysis of dynamical systems composed of self-propelled particles.
Contaminant transport in aquifers: improving the determination of model parameters
International Nuclear Information System (INIS)
Sabino, C.V.S.; Moreira, R.M.; Lula, Z.L.; Chausson, Y.; Magalhaes, W.F.; Vianna, M.N.
1998-01-01
Parameters conditioning the migration behavior of cesium and mercury are measured with their tracers 137 Cs and 203 Hg in the laboratory, using both batch and column experiments. Batch tests were used to define the sorption isotherm characteristics. Also investigated were the influences of some test parameters, in particular those due to the volume of water to mass of soil ratio (V/m). A provisional relationship between V/m and the distribution coefficient, K d , has been advanced, and a procedure to estimate K d 's valid for environmental values of the ratio V/m has been suggested. Column tests provided the parameters for a transport model. A major problem to be dealt with in such tests is the collimation of the radioactivity probe. Besides mechanically optimizing the collimator, a deconvolution procedure has been suggested and tested, with statistical criteria, to filter off both noise and spurious tracer signals. Correction procedures for the integrating effect introduced by sampling at the exit of columns have also been developed. These techniques may be helpful in increasing the accuracy required in the measurement of parameters conditioning contaminant migration in soils, thus allowing more reliable predictions based on mathematical model applications. (author)
Directory of Open Access Journals (Sweden)
N. K. Sajeevkumar
2014-09-01
Full Text Available In this article, we derived the Best Linear Unbiased Estimator (BLUE of the location parameter of certain distributions with known coefficient of variation by record values. Efficiency comparisons are also made on the proposed estimator with some of the usual estimators. Finally we give a real life data to explain the utility of results developed in this article.
Extreme value modelling of Ghana stock exchange index.
Nortey, Ezekiel N N; Asare, Kwabena; Mettle, Felix Okoe
2015-01-01
Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana stock exchange all-shares index (2000-2010) by applying the extreme value theory (EVT) to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before the EVT method was applied. The Peak Over Threshold approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model's goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the value at risk and expected shortfall risk measures at some high quantiles, based on the fitted GPD model.
Directory of Open Access Journals (Sweden)
Larry B. Crowder
2011-11-01
Full Text Available Valuing ecosystem services with microeconomic underpinnings presents challenges because these services typically constitute nonmarket values and contribute to human welfare indirectly through a series of ecological pathways that are dynamic, nonlinear, and difficult to quantify and link to appropriate economic spatial and temporal scales. This paper develops and demonstrates a method to value a portion of ecosystem services when a commercial fishery is dependent on the quality of estuarine habitat. Using a lumped-parameter, dynamic open access bioeconomic model that is spatially explicit and includes predator-prey interactions, this paper quantifies part of the value of improved ecosystem function in the Neuse River Estuary when nutrient pollution is reduced. Specifically, it traces the effects of nitrogen loading on the North Carolina commercial blue crab fishery by modeling the response of primary production and the subsequent impact on hypoxia (low dissolved oxygen. Hypoxia, in turn, affects blue crabs and their preferred prey. The discounted present value fishery rent increase from a 30% reduction in nitrogen loadings in the Neuse is $2.56 million, though this welfare estimate is fairly sensitive to some parameter values. Surprisingly, this number is not sensitive to initial conditions.
Efficiently enclosing the compact binary parameter space by singular-value decomposition
International Nuclear Information System (INIS)
Cannon, Kipp; Hanna, Chad; Keppel, Drew
2011-01-01
Gravitational-wave searches for the merger of compact binaries use matched filtering as the method of detecting signals and estimating parameters. Such searches construct a fine mesh of filters covering a signal parameter space at high density. Previously it has been shown that singular-value decomposition can reduce the effective number of filters required to search the data. Here we study how the basis provided by the singular-value decomposition changes dimension as a function of template-bank density. We will demonstrate that it is sufficient to use the basis provided by the singular-value decomposition of a low-density bank to accurately reconstruct arbitrary points within the boundaries of the template bank. Since this technique is purely numerical, it may have applications to interpolating the space of numerical relativity waveforms.
DEFF Research Database (Denmark)
Sørensen, Martin Kryspin; Durck, Tina Trier; Bork, Kristian
2016-01-01
normative values for adults and investigates the correlation between these MDVP parameters in relation to the "standardized" trauma of endotracheal intubation. METHODS: Preoperative and postoperative assessments of vocal fold pathology with flexible videolaryngoscopy and voice analysis with MDVP using...... the best-of-three standardized recording were performed in 121 patients with normal voices included consecutively in the RCT. The procedures of anesthesia were standardized. RESULTS: The normative MDVP values of this study are consistently lower compared with most normative values presented in other...... studies. The preoperative to postoperative differences in jitter values (jitter and relative average perturbation) were closely correlated to the shimmer values for patients with postoperative vocal fold edemas. In the patients with edema, the preoperative to postoperative differences in jitter had...
Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P
2014-05-20
average 15% of the mean values over the succeeding parameter sets. Our results indicate that the presented approach is effective for comparing model alternatives and reducing models to the minimum complexity replicating measured data. We therefore believe that this approach has significant potential for reparameterising existing frameworks, for identification of redundant model components of large biophysical models and to increase their predictive capacity.
Mathematical properties and parameter estimation for transit compartment pharmacodynamic models.
Yates, James W T
2008-07-03
One feature of recent research in pharmacodynamic modelling has been the move towards more mechanistically based model structures. However, in all of these models there are common sub-systems, such as feedback loops and time-delays, whose properties and contribution to the model behaviour merit some mathematical analysis. In this paper a common pharmacodynamic model sub-structure is considered: the linear transit compartment. These models have a number of interesting properties as the length of the cascade chain is increased. In the limiting case a pure time-delay is achieved [Milsum, J.H., 1966. Biological Control Systems Analysis. McGraw-Hill Book Company, New York] and the initial behaviour becoming increasingly sensitive to parameter value perturbation. It is also shown that the modelled drug effect is attenuated, though the duration of action is longer. Through this analysis the range of behaviours that such models are capable of reproducing are characterised. The properties of these models and the experimental requirements are discussed in order to highlight how mathematical analysis prior to experimentation can enhance the utility of mathematical modelling.
Genetic parameter and breeding value estimation of donkeys' problem-focused coping styles.
Navas González, Francisco Javier; Jordana Vidal, Jordi; León Jurado, José Manuel; Arando Arbulu, Ander; McLean, Amy Katherine; Delgado Bermejo, Juan Vicente
2018-05-12
Donkeys are recognized therapy or leisure-riding animals. Anecdotal evidence has suggested that more reactive donkeys or those more easily engaging flight mechanisms tend to be easier to train compared to those displaying the natural donkey behaviour of fight. This context brings together the need to quantify such traits and to genetically select donkeys displaying a neutral reaction during training, because of its implication with handler/rider safety and trainability. We analysed the scores for coping style traits from 300 Andalusian donkeys from 2013 to 2015. Three scales were applied to describe donkeys' response to 12 stimuli. Genetic parameters were estimated using multivariate models with year, sex, husbandry system and stimulus as fixed effects and age as a linear and quadratic covariable. Heritabilities were moderate, 0.18 ± 0.020 to 0.21 ± 0.021. Phenotypic correlations between intensity and mood/emotion or response type were negative and moderate (-0.21 and -0.25, respectively). Genetic correlations between the same variables were negative and moderately high (-0.46 and -0.53, respectively). Phenotypic and genetic correlations between mood/emotion and response type were positive and high (0.92 and 0.95, respectively). Breeding values enable selection methods that could lead to endangered breed preservation and genetically selecting donkeys for the uses that they may be most suitable. Copyright © 2018 Elsevier B.V. All rights reserved.
Determination of sustainable values for the parameters of the construction of residential buildings
Grigoreva, Larisa; Grigoryev, Vladimir
2018-03-01
For the formation of programs for housing construction and planning of capital investments, when developing the strategic planning companies by construction companies, the norms or calculated indicators of the duration of the construction of high-rise residential buildings and multifunctional complexes are mandatory. Determination of stable values of the parameters for the high-rise construction residential buildings provides an opportunity to establish a reasonable duration of construction at the planning and design stages of residential complexes, taking into account the influence of market conditions factors. The concept of the formation of enlarged models for the high-rise construction residential buildings is based on a real mapping in time and space of the most significant redistribution with their organizational and technological interconnection - the preparatory period, the underground part, the above-ground part, external engineering networks, landscaping. The total duration of the construction of a residential building, depending on the duration of each redistribution and the degree of their overlapping, can be determined by one of the proposed four options. At the same time, a unified approach to determining the overall duration of construction on the basis of the provisions of a streamlined construction organization with the testing of results on the example of high-rise residential buildings of the typical I-155B series was developed, and the coefficients for combining the work and the main redevelopment of the building were determined.
Determination of sustainable values for the parameters of the construction of residential buildings
Directory of Open Access Journals (Sweden)
Grigoreva Larisa
2018-01-01
Full Text Available For the formation of programs for housing construction and planning of capital investments, when developing the strategic planning companies by construction companies, the norms or calculated indicators of the duration of the construction of high-rise residential buildings and multifunctional complexes are mandatory. Determination of stable values of the parameters for the high-rise construction residential buildings provides an opportunity to establish a reasonable duration of construction at the planning and design stages of residential complexes, taking into account the influence of market conditions factors. The concept of the formation of enlarged models for the high-rise construction residential buildings is based on a real mapping in time and space of the most significant redistribution with their organizational and technological interconnection - the preparatory period, the underground part, the above-ground part, external engineering networks, landscaping. The total duration of the construction of a residential building, depending on the duration of each redistribution and the degree of their overlapping, can be determined by one of the proposed four options. At the same time, a unified approach to determining the overall duration of construction on the basis of the provisions of a streamlined construction organization with the testing of results on the example of high-rise residential buildings of the typical I-155B series was developed, and the coefficients for combining the work and the main redevelopment of the building were determined.
Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby
2013-12-01
This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.
Application of regression model on stream water quality parameters
International Nuclear Information System (INIS)
Suleman, M.; Maqbool, F.; Malik, A.H.; Bhatti, Z.A.
2012-01-01
Statistical analysis was conducted to evaluate the effect of solid waste leachate from the open solid waste dumping site of Salhad on the stream water quality. Five sites were selected along the stream. Two sites were selected prior to mixing of leachate with the surface water. One was of leachate and other two sites were affected with leachate. Samples were analyzed for pH, water temperature, electrical conductivity (EC), total dissolved solids (TDS), Biological oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO) and total bacterial load (TBL). In this study correlation coefficient r among different water quality parameters of various sites were calculated by using Pearson model and then average of each correlation between two parameters were also calculated, which shows TDS and EC and pH and BOD have significantly increasing r value, while temperature and TDS, temp and EC, DO and BL, DO and COD have decreasing r value. Single factor ANOVA at 5% level of significance was used which shows EC, TDS, TCL and COD were significantly differ among various sites. By the application of these two statistical approaches TDS and EC shows strongly positive correlation because the ions from the dissolved solids in water influence the ability of that water to conduct an electrical current. These two parameters significantly vary among 5 sites which are further confirmed by using linear regression. (author)
Chen, Ying; Lin, Li
2017-07-01
Preeclampsia is a relatively common complication of pregnancy and considered to be associated with different degrees of coagulation dysfunction. This study was developed to evaluate the potential value of coagulation parameters for suggesting preeclampsia during the third trimester of pregnancy. Data from 188 healthy pregnant women, 125 patients with preeclampsia in the third trimester and 120 age-matched nonpregnant women were analyzed. Prothrombin time, prothrombin activity, activated partial thromboplastin time, fibrinogen (Fg), antithrombin, platelet count, mean platelet volume, platelet distribution width and plateletcrit were tested. All parameters, excluding prothrombin time, platelet distribution width and plateletcrit, differed significantly between healthy pregnant women and those with preeclampsia. Platelet count, antithrombin and Fg were significantly lower and mean platelet volume and prothrombin activity were significantly higher in patients with preeclampsia (P preeclampsia was 0.872 for Fg with an optimal cutoff value of ≤2.87g/L (sensitivity = 0.68 and specificity = 0.98). For severe preeclampsia, the area under the curve for Fg reached up to 0.922 with the same optimal cutoff value (sensitivity = 0.84, specificity = 0.98, positive predictive value = 0.96 and negative predictive value = 0.93). Fg is a biomarker suggestive of preeclampsia in the third trimester of pregnancy, and our data provide a potential cutoff value of Fg ≤ 2.87g/L for screening preeclampsia, especially severe preeclampsia. Copyright © 2017 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.
Identification of grid model parameters using synchrophasor measurements
Energy Technology Data Exchange (ETDEWEB)
Boicea, Valentin; Albu, Mihaela [Politehnica University of Bucharest (Romania)
2012-07-01
Presently a critical element of the energy networks is represented by the active distribution grids, where generation intermittency and controllable loads contribute to a stochastic varability of the quantities characterizing the grid operation. The capability of controlling the electrical energy transfer is also limited by the incomplete knowledge of the detailed electrical model of each of the grid components. Asset management in distribution grids has to consider dynamic loads, while high loading of network sections might already have degraded some of the assets. Moreover, in case of functional microgrids, all elements need to be modelled accurately and an appropriate measurement layer enabling online control needs to be deployed. In this paper a method for online identification of the actual parameter values in grid electrical models is proposed. Laboratory results validating the proposed method are presented. (orig.)
Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters
Directory of Open Access Journals (Sweden)
Adeniyi Ganiyu Adeogun
2015-10-01
Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain. Keywords: Inundation, DEM, Sensitivity analysis, Model coupling, Flooding
Proving the ecosystem value through hydrological modelling
International Nuclear Information System (INIS)
Dorner, W; Spachinger, K; Metzka, R; Porter, M
2008-01-01
Ecosystems provide valuable functions. Also natural floodplains and river structures offer different types of ecosystem functions such as habitat function, recreational area and natural detention. From an economic stand point the loss (or rehabilitation) of these natural systems and their provided natural services can be valued as a damage (or benefit). Consequently these natural goods and services must be economically valued in project assessments e.g. cost-benefit-analysis or cost comparison. Especially in smaller catchments and river systems exists significant evidence that natural flood detention reduces flood risk and contributes to flood protection. Several research projects evaluated the mitigating effect of land use, river training and the loss of natural flood plains on development, peak and volume of floods. The presented project analysis the hypothesis that ignoring natural detention and hydrological ecosystem services could result in economically inefficient solutions for flood protection and mitigation. In test areas, subcatchments of the Danube in Germany, a combination of hydrological and hydrodynamic models with economic evaluation techniques was applied. Different forms of land use, river structure and flood protection measures were assed and compared from a hydrological and economic point of view. A hydrodynamic model was used to simulate flows to assess the extent of flood affected areas and damages to buildings and infrastructure as well as to investigate the impacts of levees and river structure on a local scale. These model results provided the basis for an economic assessment. Different economic valuation techniques, such as flood damage functions, cost comparison method and substation-approach were used to compare the outcomes of different hydrological scenarios from an economic point of view and value the ecosystem service. The results give significant evidence that natural detention must be evaluated as part of flood mitigation projects
Seo, Yu-Mi; Kang, Hyun-Mi; Lee, Sung-Churl; Yu, Jae-Won; Kil, Hong-Ryang; Rhim, Jung-Woo; Han, Ji-Whan; Lee, Kyung-Yil
2018-05-01
This study aimed to analyse laboratory values according to fever duration, and evaluate the relationship across these values during the acute phase of Kawasaki disease (KD) to aid in the early diagnosis for early-presenting KD and incomplete KD patients. Clinical and laboratory data of patients with KD (n=615) were evaluated according to duration of fever at presentation, and were compared between patients with and without coronary artery lesions (CALs). For evaluation of the relationships across laboratory indices, patients with a fever duration of 5 days or 6 days were used (n=204). The mean fever duration was 6.6±2.3 days, and the proportions of patients with CALs was 19.3% (n=114). C-reactive proteins (CRPs) and neutrophil differential values were highest and hemoglobin, albumin, and lymphocyte differential values were lowest in the 6-day group. Patients with CALs had longer total fever duration, higher CRP and neutrophil differential values and lower hemoglobin and albumin values compared to patients without CALs. CRP, albumin, neutrophil differential, and hemoglobin values at the peak inflammation stage of KD showed positive or negative correlations each other. The severity of systemic inflammation in KD was reflected in the laboratory values including CRP, neutrophil differential, albumin, and hemoglobin. Observing changes in these laboratory parameters by repeated examinations prior to the peak of inflammation in acute KD may aid in diagnosis of early-presenting KD patients.
Optimizing incomplete sample designs for item response model parameters
van der Linden, Willem J.
Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with
Parameter Estimates in Differential Equation Models for Chemical Kinetics
Winkel, Brian
2011-01-01
We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…
Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.
Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza
2015-09-15
The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.
The Effects of Uncertainty in Speed-Flow Curve Parameters on a Large-Scale Model
DEFF Research Database (Denmark)
Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo
2014-01-01
-delay functions express travel time as a function of traffic flows and the theoretical capacity of the modeled facility. The U.S. Bureau of Public Roads (BPR) formula is one of the most extensively applied volume delay functions in practice. This study investigated uncertainty in the BPR parameters. Initially......-stage Danish national transport model. The results clearly highlight the importance to modeling purposes of taking into account BPR formula parameter uncertainty, expressed as a distribution of values rather than assumed point values. Indeed, the model output demonstrates a noticeable sensitivity to parameter...
[South American camelids in Switzerland. II. Reference values for blood parameters].
Hengrave Burri, I; Tschudi, P; Martig, J; Liesegang, A; Meylan, M
2005-08-01
In order to establish reference values for blood parameters of South American camelids in Switzerland, 273 blood samples were collected from 141 llamas and 132 alpacas. These animals were classified in three categories (young animals blood cell count, white blood cell count, electrolytes, metabolites and enzymes). Significant differences between llamas and alpacas were evident for 26 parameters. This study also showed that differences between young animals, females and males must be taken into consideration. A comparison of blood values with the results of fecal analysis for parasite eggs showed that an infestation with Dicrocoelium dendriticum was associated with elevated activity of two liver enzymes (GLDH and gamma-GT) in the serum. In contrast, no differences were found in the results of blood analyses between animals shedding eggs of gastrointestinal strongyles or not.
Positive solutions for a nonlinear periodic boundary-value problem with a parameter
Directory of Open Access Journals (Sweden)
Jingliang Qiu
2012-08-01
Full Text Available Using topological degree theory with a partially ordered structure of space, sufficient conditions for the existence and multiplicity of positive solutions for a second-order nonlinear periodic boundary-value problem are established. Inspired by ideas in Guo and Lakshmikantham [6], we study the dependence of positive periodic solutions as a parameter approaches infinity, $$ lim_{lambdao +infty}|x_{lambda}|=+infty,quadhbox{or}quad lim_{lambdao+infty}|x_{lambda}|=0. $$
Study on Parameters Modeling of Wind Turbines Using SCADA Data
Directory of Open Access Journals (Sweden)
Yonglong YAN
2014-08-01
Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.
An improved state-parameter analysis of ecosystem models using data assimilation
Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.
2008-01-01
Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the
Analysis of the value recommended by the NCRP 151 and its relationship with Brazilian parameters
International Nuclear Information System (INIS)
Groppo, Daniela P.; Martins, Homero L.
2009-01-01
The methodology proposed by the National Council on Radiation Protection 151 (NCRP 151), relates technical information necessary to structural shielding design and evaluation for megavoltage X- and gamma- ray radiotherapy facilities. However, many parameters used to calculate the shield are based on estimates, and may not be adequate to the Brazilian reality. Thus, the central idea of this study is to obtain parameters and is to outline a profile closer to the treatments carried out in facilities in Brazil, through a data collection routine of the Department of Radiotherapy Service of the Real e Benemerita Associacao Portuguesa de Beneficencia, in particular the cobalt therapy Theratron 780 (Atomic Energy of Canada Ltd.) and the linear accelerator Varian Clinac 2100C for measurement of workload, use factor, number of patients, fields, dose and anatomic region treated. So, the work did not draw definite values of the parameters, but indicative values were obtained which showed the importance to carry out more detailed studies of the recommended values. (author)
Parameter uncertainty in CGE Modeling of the environmental impacts of economic policies
Energy Technology Data Exchange (ETDEWEB)
Abler, D.G.; Shortle, J.S. [Agricultural Economics, Pennsylvania State University, University Park, PA (United States); Rodriguez, A.G. [University of Costa Rica, San Jose (Costa Rica)
1999-07-01
This study explores the role of parameter uncertainty in Computable General Equilibrium (CGE) modeling of the environmental impacts of macroeconomic and sectoral policies, using Costa Rica as a case for study. A CGE model is constructed which includes eight environmental indicators covering deforestation, pesticides, overfishing, hazardous wastes, inorganic wastes, organic wastes, greenhouse gases, and air pollution. The parameters are treated as random variables drawn from prespecified distributions. Evaluation of each policy option consists of a Monte Carlo experiment. The impacts of the policy options on the environmental indicators are relatively robust to different parameter values, in spite of the wide range of parameter values employed. 33 refs.
Parameter uncertainty in CGE Modeling of the environmental impacts of economic policies
International Nuclear Information System (INIS)
Abler, D.G.; Shortle, J.S.; Rodriguez, A.G.
1999-01-01
This study explores the role of parameter uncertainty in Computable General Equilibrium (CGE) modeling of the environmental impacts of macroeconomic and sectoral policies, using Costa Rica as a case for study. A CGE model is constructed which includes eight environmental indicators covering deforestation, pesticides, overfishing, hazardous wastes, inorganic wastes, organic wastes, greenhouse gases, and air pollution. The parameters are treated as random variables drawn from prespecified distributions. Evaluation of each policy option consists of a Monte Carlo experiment. The impacts of the policy options on the environmental indicators are relatively robust to different parameter values, in spite of the wide range of parameter values employed. 33 refs
Convergence of surface diffusion parameters with model crystal size
Cohen, Jennifer M.; Voter, Arthur F.
1994-07-01
A study of the variation in the calculated quantities for adatom diffusion with respect to the size of the model crystal is presented. The reported quantities include surface diffusion barrier heights, pre-exponential factors, and dynamical correction factors. Embedded atom method (EAM) potentials were used throughout this effort. Both the layer size and the depth of the crystal were found to influence the values of the Arrhenius factors significantly. In particular, exchange type mechanisms required a significantly larger model than standard hopping mechanisms to determine adatom diffusion barriers of equivalent accuracy. The dynamical events that govern the corrections to transition state theory (TST) did not appear to be as sensitive to crystal depth. Suitable criteria for the convergence of the diffusion parameters with regard to the rate properties are illustrated.
Advanced empirical estimate of information value for credit scoring models
Directory of Open Access Journals (Sweden)
Martin Řezáč
2011-01-01
Full Text Available Credit scoring, it is a term for a wide spectrum of predictive models and their underlying techniques that aid financial institutions in granting credits. These methods decide who will get credit, how much credit they should get, and what further strategies will enhance the profitability of the borrowers to the lenders. Many statistical tools are avaiable for measuring quality, within the meaning of the predictive power, of credit scoring models. Because it is impossible to use a scoring model effectively without knowing how good it is, quality indexes like Gini, Kolmogorov-Smirnov statisic and Information value are used to assess quality of given credit scoring model. The paper deals primarily with the Information value, sometimes called divergency. Commonly it is computed by discretisation of data into bins using deciles. One constraint is required to be met in this case. Number of cases have to be nonzero for all bins. If this constraint is not fulfilled there are some practical procedures for preserving finite results. As an alternative method to the empirical estimates one can use the kernel smoothing theory, which allows to estimate unknown densities and consequently, using some numerical method for integration, to estimate value of the Information value. The main contribution of this paper is a proposal and description of the empirical estimate with supervised interval selection. This advanced estimate is based on requirement to have at least k, where k is a positive integer, observations of socres of both good and bad client in each considered interval. A simulation study shows that this estimate outperform both the empirical estimate using deciles and the kernel estimate. Furthermore it shows high dependency on choice of the parameter k. If we choose too small value, we get overestimated value of the Information value, and vice versa. Adjusted square root of number of bad clients seems to be a reasonable compromise.
Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.
Energy Technology Data Exchange (ETDEWEB)
Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilcox, Ian Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandoval, Andrew J [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reza, Shahed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-12-01
This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.
International Nuclear Information System (INIS)
Ju Haiyue; Gao Sijia; Xu Ke; Wang Qiang
2007-01-01
Objective: To explore the influence of the maximal value and peak enhancement value of arterial and venous enhancement curve on CT perfusion parameters and signal-to-noise ratio (SNR). Methods: Seventeen patients underwent brain CT perfusion scanning. All row data were analyzed with perfusion software for 6 times, and get different arterial and venous enhancement curves for each patient. The maximal values and peak enhancement values of each arterial and venous enhancement curves, as well as mean perfusion parameters including cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), permeability surface area product (PS), and their standard deviations (SD) in homolateral white and gray matter were measured and recorded. SNR was calculated by dividing the mean perfusion parameter value by its SD. Pearson correlation analysis and two-tailed paired Student t test were used for statistics. Results: The maximal values and peak enhancement values of arterial and venous curves were correlated with mean SNR CBF , SNR CBV and SNR MTT in both white matter and gray matters (r value range: 0.332-0.922, P PS in white matter(r=0.256, P PS (in both white matter and gray matters) and arterial peak enhancement values, the maximal values and venous peak enhancement values, or between SNR PS (in gray matter) and the maximal values of venous curve(r value range: -0.058-0.210, P>0.05). (2) Mean CBF, CBV and PS values in the group with low venous peak enhancement values were significantly different from the group with high venous peak enhancement values in both white and gray matters (t value range: 3.830-5.337, P 0.05). Conclusions: The mean perfusion parameters and SNR are influenced by the maximal values and peak enhancement values of the arterial and venous curves. Peak enhancement of arterial and venous curves should be adjusted to higher level to make parameter values more reliable and increase the SNR. (authors)
Numerical solution of system of boundary value problems using B-spline with free parameter
Gupta, Yogesh
2017-01-01
This paper deals with method of B-spline solution for a system of boundary value problems. The differential equations are useful in various fields of science and engineering. Some interesting real life problems involve more than one unknown function. These result in system of simultaneous differential equations. Such systems have been applied to many problems in mathematics, physics, engineering etc. In present paper, B-spline and B-spline with free parameter methods for the solution of a linear system of second-order boundary value problems are presented. The methods utilize the values of cubic B-spline and its derivatives at nodal points together with the equations of the given system and boundary conditions, ensuing into the linear matrix equation.
Optimization of Experimental Model Parameter Identification for Energy Storage Systems
Directory of Open Access Journals (Sweden)
Rosario Morello
2013-09-01
Full Text Available The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.
Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures
Lucas, D. D.; Klein, R.; Tannahill, J.; Brandon, S.; Covey, C. C.; Domyancic, D.; Ivanova, D. P.
2012-12-01
Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Statistical analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation failures of the Parallel Ocean Program (POP2). About 8.5% of our POP2 runs failed for numerical reasons at certain combinations of parameter values. We apply support vector machine (SVM) classification from the fields of pattern recognition and machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. The SVM classifiers readily predict POP2 failures in an independent validation ensemble, and are subsequently used to determine the causes of the failures via a global sensitivity analysis. Four parameters related to ocean mixing and viscosity are identified as the major sources of POP2 failures. Our method can be used to improve the robustness of complex scientific models to parameter perturbations and to better steer UQ ensembles. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).
Parameter Optimisation for the Behaviour of Elastic Models over Time
DEFF Research Database (Denmark)
Mosegaard, Jesper
2004-01-01
Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method tha...
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-11-01
simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.
Modelling of bio-optical parameters of open ocean waters
Directory of Open Access Journals (Sweden)
Vadim N. Pelevin
2001-12-01
Full Text Available An original method for estimating the concentration of chlorophyll pigments, absorption of yellow substance and absorption of suspended matter without pigments and yellow substance in detritus using spectral diffuse attenuation coefficient for downwelling irradiance and irradiance reflectance data has been applied to sea waters of different types in the open ocean (case 1. Using the effective numerical single parameter classification with the water type optical index m as a parameter over the whole range of the open ocean waters, the calculations have been carried out and the light absorption spectra of sea waters tabulated. These spectra are used to optimize the absorption models and thus to estimate the concentrations of the main admixtures in sea water. The value of m can be determined from direct measurements of the downward irradiance attenuation coefficient at 500 nm or calculated from remote sensing data using the regressions given in the article. The sea water composition can then be readily estimated from the tables given for any open ocean area if that one parameter m characterizing the basin is known.
International Nuclear Information System (INIS)
Choi, Yong Won; Lim, Sung Won; Lee, Un Chul; Kim, Man Woong; Kim, Kab; Ryu, Yong Ho
2009-01-01
As a part of development the evaluation system of safety margin effects for degradation of CANDU reactors, it is required that the degradation model represents the distribution of each ageing factor's value during operating year. Unfortunately, it is not easy to make an explicit relation between the RELAP-CANDU parameters and ageing mechanism because of insufficient data and lack of applicable models. So, operating parameter related with ageing is used for range determination of ageing factor. Then, relation between operating parameter and ageing elements is analyzed and ageing constant values for degradation model are determined. Also the other ageing factor is derived for more accurate ageing analysis
Resuspension parameters for TRAC dispersion model
International Nuclear Information System (INIS)
Langer, G.
1987-01-01
Resuspension factors for the wind erosion of soil contaminated with plutonium are necessary to run the Rocky Flats Plant Terrain Responsive Atmospheric Code (TRAC). The model predicts the dispersion and resulting population dose due to accidental plutonium releases
Directory of Open Access Journals (Sweden)
Slijepčević Dajana
2014-01-01
Full Text Available One of very important prerequisites for achieving good results in races, in addition to genetic predisposition, quality training and good health, are optimal values for number of erythrocytes, concentration of haemoglobin and hematocrit, of which depends efficient oxygen supply of muscles during great efforts. The stated values, along with data on heart rate, are useful indicators of the degree of horse fitness and readiness for horse race. The influence of physical exertion on the values of basic hematological parameters as well as on heart rate, was investigated on 6 trotters, in training at the Belgrade racetrack (one head of Italian trotter, male, 3 years old; 3 heads of American trotter, male, 3,4 and 6 years old and two heads of Serbian trotter, female, 4 and 5 years old. The blood samples for hematological tests were taken by punction of jugular vein in resting phase - immediately before the commencement of work, after light trot warming for 3000 m and fast trot for 1000 m, with 30 minutes rest between the two runnings. The heart rate was monitored continuously by radio telemetry cardiometer, from the moment they were taken from their boxes and harnessing to the completion of work. The obtained results confirm the relationship between the rise of heart rate and hematocrit values: maximal hematocrit values were determined after the first running (0.49±0.05, in regard to 0.42±0.03 in resting phase, but 30 minutes after the second running there was a slight drop of hematocrit values (0.46±0.04. The blood samples in both cases were taken after fast trot during which there were recorded maximal pulse values, so in the moment of sampling the pulse lowered close to the values in resting - after the first running from 192.23±19.66, and after the second from 180.33±17.22 to 40.67±5.76.
Issues in Value-at-Risk Modeling and Evaluation
J. Daníelsson (Jón); C.G. de Vries (Casper); B.N. Jorgensen (Bjørn); P.F. Christoffersen (Peter); F.X. Diebold (Francis); T. Schuermann (Til); J.A. Lopez (Jose); B. Hirtle (Beverly)
1998-01-01
textabstractDiscusses the issues in value-at-risk modeling and evaluation. Value of value at risk; Horizon problems and extreme events in financial risk management; Methods of evaluating value-at-risk estimates.
Application of Powell's optimization method to surge arrester circuit models' parameters
Energy Technology Data Exchange (ETDEWEB)
Christodoulou, C.A.; Stathopulos, I.A. [National Technical University of Athens, School of Electrical and Computer Engineering, 9 Iroon Politechniou St., Zografou Campus, 157 80 Athens (Greece); Vita, V.; Ekonomou, L.; Chatzarakis, G.E. [A.S.PE.T.E. - School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece)
2010-08-15
Powell's optimization method has been used for the evaluation of the surge arrester models parameters. The proper modelling of metal-oxide surge arresters and the right selection of equivalent circuit parameters are very significant issues, since quality and reliability of lightning performance studies can be improved with the more efficient representation of the arresters' dynamic behavior. The proposed approach selects optimum arrester model equivalent circuit parameter values, minimizing the error between the simulated peak residual voltage value and this given by the manufacturer. Application of the method in performed on a 120 kV metal oxide arrester. The use of the obtained optimum parameter values reduces significantly the relative error between the simulated and manufacturer's peak residual voltage value, presenting the effectiveness of the method. (author)
Directory of Open Access Journals (Sweden)
Jonathan R Karr
2015-05-01
Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.
Application of a free parameter model to plastic scintillation samples
Energy Technology Data Exchange (ETDEWEB)
Tarancon Sanz, Alex, E-mail: alex.tarancon@ub.edu [Departament de Quimica Analitica, Universitat de Barcelona, Diagonal 647, E-08028 Barcelona (Spain); Kossert, Karsten, E-mail: Karsten.Kossert@ptb.de [Physikalisch-Technische Bundesanstalt (PTB), Bundesallee 100, 38116 Braunschweig (Germany)
2011-08-21
In liquid scintillation (LS) counting, the CIEMAT/NIST efficiency tracing method and the triple-to-double coincidence ratio (TDCR) method have proved their worth for reliable activity measurements of a number of radionuclides. In this paper, an extended approach to apply a free-parameter model to samples containing a mixture of solid plastic scintillation microspheres and radioactive aqueous solutions is presented. Several beta-emitting radionuclides were measured in a TDCR system at PTB. For the application of the free parameter model, the energy loss in the aqueous phase must be taken into account, since this portion of the particle energy does not contribute to the creation of scintillation light. The energy deposit in the aqueous phase is determined by means of Monte Carlo calculations applying the PENELOPE software package. To this end, great efforts were made to model the geometry of the samples. Finally, a new geometry parameter was defined, which was determined by means of a tracer radionuclide with known activity. This makes the analysis of experimental TDCR data of other radionuclides possible. The deviations between the determined activity concentrations and reference values were found to be lower than 3%. The outcome of this research work is also important for a better understanding of liquid scintillation counting. In particular the influence of (inverse) micelles, i.e. the aqueous spaces embedded in the organic scintillation cocktail, can be investigated. The new approach makes clear that it is important to take the energy loss in the aqueous phase into account. In particular for radionuclides emitting low-energy electrons (e.g. M-Auger electrons from {sup 125}I), this effect can be very important.
Krüger, C; Lahm, T; Zugck, C; Kell, R; Schellberg, D; Schweizer, M W F; Kübler, W; Haass, M
2002-12-01
This prospective study evaluated whether heart rate variability (HRV) assessed from Holter ECG has prognostic value in addition to established parameters in patients with congestive heart failure (CHF). The study included 222 patients with CHF due to dilated or ischemic cardiomyopathy (left ventricular ejection fraction LVEF 21+/-1%; mean+/-SEM). During a mean follow-up of 15+/-1 months, 38 (17%) patients died and 45 (20%) were hospitalized due to worsening of CHF. The HRV parameter SDNN (standard deviation of all intervals between normal beats) was significantly lower in non-surviving or hospitalized than in event-free patients (118+/-6 vs 142+/-5 ms), as were LVEF (18+/-1 vs 23+/-1%), and peak oxygen uptake during exercise (peak VO(2)) (12.8+/-0.5 vs 15.6+/-0.5 ml/min/kg). While each of these parameters was a risk predictor in univariate analysis, multivariate analysis revealed that HRV provides both independent and additional prognostic information with respect to the risk 'cardiac mortality or deterioration of CHF'. It is concluded that the determination of HRV enhances the prognostic power given by the most widely used parameters LVEF and peak VO(2) in the prediction of mortality or deterioration of CHF and thus enables to improve risk stratification.
Directory of Open Access Journals (Sweden)
Milovanović Branislav
2007-01-01
Full Text Available Introduction: There are different proofs about association of autonomic nervous system dysfunction, especially nonlinear parameters, with higher mortality after myocardial infarction. Objective The objective of the study was to determine predictive value of Poincare plot as nonlinear parameter and other significant standard risk predictors: ejection fraction of the left ventricle, late potentials, ventricular arrhythmias, and QT interval. Method The study included 1081 patients with mean follow up of 28 months (ranging fom 0-80 months. End-point of the study was cardiovascular mortality. The following diagnostic methods were used during the second week: ECG with commercial software Schiller AT-10: short time spectral analysis of RR variability with analysis of Poincare plot as nonlinear parameter and late potentials; 24-hour ambulatory ECG monitoring: QT interval, RR interval, QT/RR slope, ventricular arrhythmias (Lown >II; echocardiography examinations: systolic disorder (defined as EF<40 %. Results There were 103 (9.52% cardiovascular deaths during the follow-up. In univariate analysis, the following parameters were significantly correlated with mortality: mean RR interval < 800 ms, QT and RR interval space relationship as mean RR interval < 800 ms and QT interval > 350 ms, positive late potentials, systolic dysfunction, Poincare plot as a point, ventricular arrhythmias (Lown > II. In multivariate analysis, the significant risk predictors were: Poincare plot as a point and mean RR interval lower than 800 ms. Conclusion Mean RR interval lower than 800 ms and nonlinear and space presentation of RR interval as a point Poincare plot were multivariate risk predictors.
Modeling Influenza Transmission Using Environmental Parameters
Soebiyanto, Radina P.; Kiang, Richard K.
2010-01-01
Influenza is an acute viral respiratory disease that has significant mortality, morbidity and economic burden worldwide. It infects approximately 5-15% of the world population, and causes 250,000 500,000 deaths each year. The role of environments on influenza is often drawn upon the latitude variability of influenza seasonality pattern. In regions with temperate climate, influenza epidemics exhibit clear seasonal pattern that peak during winter months, but it is not as evident in the tropics. Toward this end, we developed mathematical model and forecasting capabilities for influenza in regions characterized by warm climate Hong Kong (China) and Maricopa County (Arizona, USA). The best model for Hong Kong uses Land Surface Temperature (LST), precipitation and relative humidity as its covariates. Whereas for Maricopa County, we found that weekly influenza cases can be best modelled using mean air temperature as its covariates. Our forecasts can further guides public health organizations in targeting influenza prevention and control measures such as vaccination.
Edge Modeling by Two Blur Parameters in Varying Contrasts.
Seo, Suyoung
2018-06-01
This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.
Dynamics in the Parameter Space of a Neuron Model
Paulo, C. Rech
2012-06-01
Some two-dimensional parameter-space diagrams are numerically obtained by considering the largest Lyapunov exponent for a four-dimensional thirteen-parameter Hindmarsh—Rose neuron model. Several different parameter planes are considered, and it is shown that depending on the combination of parameters, a typical scenario can be preserved: for some choice of two parameters, the parameter plane presents a comb-shaped chaotic region embedded in a large periodic region. It is also shown that there exist regions close to these comb-shaped chaotic regions, separated by the comb teeth, organizing themselves in period-adding bifurcation cascades.
Advances in Modelling, System Identification and Parameter ...
Indian Academy of Sciences (India)
Authors show, using numerical simulation for two system functions, the improvement in percentage normalized ... of nonlinear systems. The approach is to use multiple linearizing models fitted along the operating trajectories. ... over emphasized in the light of present day high level of research activity in the field of aerospace ...
Parameter estimation and sensitivity analysis for a mathematical model with time delays of leukemia
Cândea, Doina; Halanay, Andrei; Rǎdulescu, Rodica; Tǎlmaci, Rodica
2017-01-01
We consider a system of nonlinear delay differential equations that describes the interaction between three competing cell populations: healthy, leukemic and anti-leukemia T cells involved in Chronic Myeloid Leukemia (CML) under treatment with Imatinib. The aim of this work is to establish which model parameters are the most important in the success or failure of leukemia remission under treatment using a sensitivity analysis of the model parameters. For the most significant parameters of the model which affect the evolution of CML disease during Imatinib treatment we try to estimate the realistic values using some experimental data. For these parameters, steady states are calculated and their stability is analyzed and biologically interpreted.
Shah, A A; Xing, W W; Triantafyllidis, V
2017-04-01
In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.
Average values of 235U resonance parameters up to 500 eV
International Nuclear Information System (INIS)
Leal, L.C.
1991-01-01
An R-matrix analysis of 235 U neutron cross sections was recently completed. The analysis was performed with the multilevel-multichannel Reich-Moore computer code SAMMY and extended the resolved resonance region up to 500 eV. Several high resolution measurements namely, transmission, fission and capture data as well as spin separated fission data were analyzed in a consistent manner and a very accurate parametrization up to 500 eV of these data were obtained. The aim of this paper is to present the results of average values of the resonance parameters. 9 refs., 1 tab
Wałęga, Andrzej; Młyński, Dariusz; Wachulec, Katarzyna
2017-12-01
The aim of the study was to assess the applicability of asymptotic functions for determining the value of CN parameter as a function of precipitation depth in mountain and upland catchments. The analyses were carried out in two catchments: the Rudawa, left tributary of the Vistula, and the Kamienica, right tributary of the Dunajec. The input material included data on precipitation and flows for a multi-year period 1980-2012, obtained from IMGW PIB in Warsaw. Two models were used to determine empirical values of CNobs parameter as a function of precipitation depth: standard Hawkins model and 2-CN model allowing for a heterogeneous nature of a catchment area. The study analyses confirmed that asymptotic functions properly described P-CNobs relationship for the entire range of precipitation variability. In the case of high rainfalls, CNobs remained above or below the commonly accepted average antecedent moisture conditions AMCII. The study calculations indicated that the runoff amount calculated according to the original SCS-CN method might be underestimated, and this could adversely affect the values of design flows required for the design of hydraulic engineering projects. In catchments with heterogeneous land cover, the results of CNobs were more accurate when 2-CN model was used instead of the standard Hawkins model. 2-CN model is more precise in accounting for differences in runoff formation depending on retention capacity of the substrate. It was also demonstrated that the commonly accepted initial abstraction coefficient λ = 0.20 yielded too big initial loss of precipitation in the analyzed catchments and, therefore, the computed direct runoff was underestimated. The best results were obtained for λ = 0.05.
The Advancement Value Chain: An Exploratory Model
Leonard, Edward F., III
2005-01-01
Since the introduction of the value chain concept in 1985, several varying, yet virtually similar, value chains have been developed for the business enterprise. Shifting to higher education, can a value chain be found that links together the various activities of advancement so that an institution's leaders can actually look at the philanthropic…
Water saturation in shaly sands: logging parameters from log-derived values
International Nuclear Information System (INIS)
Miyairi, M.; Itoh, T.; Okabe, F.
1976-01-01
The methods are presented for determining the relation of porosity to formation factor and that of true resistivity of formation to water saturation, which were investigated through the log interpretation of one of the oil and gas fields of northern Japan Sea. The values of the coefficients ''a'' and ''m'' in porosity-formation factor relation are derived from cross-plot of porosity and resistivity of formation corrected by clay content. The saturation exponent ''n'' is determined from cross-plot of porosity and resistivity index on the assumption that the product of porosity and irreducible water saturation is constant. The relation of porosity to irreducible water saturation is also investigated from core analysis. The new logging parameters determined from the methods, a = 1, m = 2, n = 1.4, improved the values of water saturation by 6 percent in average, and made it easy to distinguish the points which belong to the productive zone and ones belonging to the nonproductive zone
International Nuclear Information System (INIS)
Rout, S.; Mishra, D.G.; Ravi, P.M.; Tripathi, R.M.
2016-01-01
Tritium is one of the radionuclides likely to get released to the environment from Pressurized Heavy Water Reactors. Environmental models are extensively used to quantify the complex environmental transport processes of radionuclides and also to assess the impact to the environment. Model parameters exerting the significant influence on model results are identified through a sensitivity analysis (SA). SA is the study of how the variation (uncertainty) in the output of a mathematical model can be apportioned, qualitatively or quantitatively, to different sources of variation in the input parameters. This study was designed to identify the sensitive model parameters of specific activity model (TRS 1616, IAEA) for environmental transfer of 3 H following release to air and then to vegetation and animal products. Model includes parameters such as air to soil transfer factor (CRs), Tissue Free Water 3 H to Organically Bound 3 H ratio (Rp), Relative humidity (RH), WCP (fractional water content) and WEQp (water equivalent factor) any change in these parameters leads to change in 3 H level in vegetation and animal products consequently change in dose due to ingestion. All these parameters are function of climate and/or plant which change with time, space and species. Estimation of these parameters at every time is a time consuming and also required sophisticated instrumentation. Therefore it is necessary to identify the sensitive parameters and freeze the values of least sensitive parameters at constant values for more accurate estimation of 3 H dose in short time for routine assessment
Lumped parameter models for the interpretation of environmental tracer data
International Nuclear Information System (INIS)
Maloszewski, P.; Zuber, A.
1996-01-01
Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs
Lumped parameter models for the interpretation of environmental tracer data
Energy Technology Data Exchange (ETDEWEB)
Maloszewski, P [GSF-Inst. for Hydrology, Oberschleissheim (Germany); Zuber, A [Institute of Nuclear Physics, Cracow (Poland)
1996-10-01
Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs.
Microscopic calculation of parameters of the sdg interacting boson model for 104-110Pd isotopes
International Nuclear Information System (INIS)
Liu Yong
1995-01-01
The parameters of the sdg interacting boson model Hamiltonian are calculated for the 104-110 Pd isotopes. The calculations utilize the microscopic procedure based on the Dyson boson mapping proposed by Yang-Liu-Qi and extended to include the g boson effects. The calculated parameters reproduce those values from the phenomenological fits. The resulting spectra are compared with the experimental spectra
Pande, S.; Arkesteijn, L.; Savenije, H.H.G.; Bastidas, L.A.
2014-01-01
This paper presents evidence that model prediction uncertainty does not necessarily rise with parameter dimensionality (the number of parameters). Here by prediction we mean future simulation of a variable of interest conditioned on certain future values of input variables. We utilize a relationship
Parameters modelling of amaranth grain processing technology
Derkanosova, N. M.; Shelamova, S. A.; Ponomareva, I. N.; Shurshikova, G. V.; Vasilenko, O. A.
2018-03-01
The article presents a technique that allows calculating the structure of a multicomponent bakery mixture for the production of enriched products, taking into account the instability of nutrient content, and ensuring the fulfilment of technological requirements and, at the same time considering consumer preferences. The results of modelling and analysis of optimal solutions are given by the example of calculating the structure of a three-component mixture of wheat and rye flour with an enriching component, that is, whole-hulled amaranth flour applied to the technology of bread from a mixture of rye and wheat flour on a liquid leaven.
WATGIS: A GIS-Based Lumped Parameter Water Quality Model
Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya
2002-01-01
A Geographic Information System (GIS)Âbased, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogenÂloading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...
A test for the parameters of multiple linear regression models ...
African Journals Online (AJOL)
A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...
The influence of model parameters on catchment-response
International Nuclear Information System (INIS)
Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.
2002-01-01
This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)
Identification of ecosystem parameters by SDE-modelling
DEFF Research Database (Denmark)
Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation experiments in order to analyse how system noise propagates through the ordinary differential equation formulation of ecosystem...... models. Estimation of parameters in SDEs is, however, possible by combining Kalman filter techniques and likelihood estimation. By modelling parameters as random walks it is possible to identify linear as well as non-linear interactions between ecosystem components. By formulating a simple linear SDE...
Standard model parameters and the search for new physics
International Nuclear Information System (INIS)
Marciano, W.J.
1988-04-01
In these lectures, my aim is to present an up-to-date status report on the standard model and some key tests of electroweak unification. Within that context, I also discuss how and where hints of new physics may emerge. To accomplish those goals, I have organized my presentation as follows: I discuss the standard model parameters with particular emphasis on the gauge coupling constants and vector boson masses. Examples of new physics appendages are also briefly commented on. In addition, because these lectures are intended for students and thus somewhat pedagogical, I have included an appendix on dimensional regularization and a simple computational example that employs that technique. Next, I focus on weak charged current phenomenology. Precision tests of the standard model are described and up-to-date values for the Cabibbo-Kobayashi-Maskawa (CKM) mixing matrix parameters are presented. Constraints implied by those tests for a 4th generation, supersymmetry, extra Z/prime/ bosons, and compositeness are also discussed. I discuss weak neutral current phenomenology and the extraction of sin/sup 2/ /theta//sub W/ from experiment. The results presented there are based on a recently completed global analysis of all existing data. I have chosen to concentrate that discussion on radiative corrections, the effect of a heavy top quark mass, and implications for grand unified theories (GUTS). The potential for further experimental progress is also commented on. I depart from the narrowest version of the standard model and discuss effects of neutrino masses and mixings. I have chosen to concentrate on oscillations, the Mikheyev-Smirnov- Wolfenstein (MSW) effect, and electromagnetic properties of neutrinos. On the latter topic, I will describe some recent work on resonant spin-flavor precession. Finally, I conclude with a prospectus on hopes for the future. 76 refs
Performance Analysis of Different NeQuick Ionospheric Model Parameters
Directory of Open Access Journals (Sweden)
WANG Ningbo
2017-04-01
Full Text Available Galileo adopts NeQuick model for single-frequency ionospheric delay corrections. For the standard operation of Galileo, NeQuick model is driven by the effective ionization level parameter Az instead of the solar activity level index, and the three broadcast ionospheric coefficients are determined by a second-polynomial through fitting the Az values estimated from globally distributed Galileo Sensor Stations (GSS. In this study, the processing strategies for the estimation of NeQuick ionospheric coefficients are discussed and the characteristics of the NeQuick coefficients are also analyzed. The accuracy of Global Position System (GPS broadcast Klobuchar, original NeQuick2 and fitted NeQuickC as well as Galileo broadcast NeQuickG models is evaluated over the continental and oceanic regions, respectively, in comparison with the ionospheric total electron content (TEC provided by global ionospheric maps (GIM, GPS test stations and JASON-2 altimeter. The results show that NeQuickG can mitigate ionospheric delay by 54.2%~65.8% on a global scale, and NeQuickC can correct for 71.1%~74.2% of the ionospheric delay. NeQuick2 performs at the same level with NeQuickG, which is a bit better than that of GPS broadcast Klobuchar model.
Bayesian estimation of parameters in a regional hydrological model
Directory of Open Access Journals (Sweden)
K. Engeland
2002-01-01
Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis
Parameter values for the estimation of radionuclide transfer to major food crops in Korea
International Nuclear Information System (INIS)
Choi, Yong-Ho; Lim, Kwang-Muk; Jun, In; Keum, Dong-Kwon; Lee, Chang-Woo
2008-01-01
This paper summarizes the results of the radiotracer experiments and field studies performed in Korea for the past 20 years to obtain parameter values for estimating the environmental transfer of radionuclides to food crops. With regards to direct plant contamination, the interception fractions, weathering half-lives and translocation factors of Cs, Sr, Mn, Co and Ru were measured for depositions at different growth stages of selected food crops. In order to investigate an indirect contamination pathway, the soil-to-plant transfer factors (TF m , dimensionless) of Cs, Sr, Mn, Co and/or Zn were measured for rice, Chinese cabbage, radish, soybean, barley, lettuce and so on in one or more soils. In addition, the transfer factors (TF a , m 2 kg -1 ) based on a deposition density were also measured following depositions at different times during the growth periods of several food crops. Particularly for rice and Chinese cabbage, tritium experiments were also carried out for the TF a . The obtained parameter values varied considerably with the soils, crops, radionuclides and deposition times. These data would be applicable to both normal and acute releases not only in Korea but also in many other countries. (author)
Influence of puerperal gonadoreline application on reproductive parameter values in cows
Directory of Open Access Journals (Sweden)
Šabanović Mustafa
2006-01-01
Full Text Available This paper presents results of investigations conducted in order to investigate the influence of gonadoreline application 14-16, 17-20 and 21-25 days postpartum on reproductive parameters values in cows. A total of 241 cows was included in the study. Out of this number, 126 cows were treated with gonadoreline while 115 animals were placebo treated and served as controls. The estimation of progesterone concentration was conducted on 43 animals selected randomly from the first two groups of treated cows. Analyses of the results in cows that gave normal birth, revealed that mean anoestrus period, open day's period and intervals between calving were significantly lower in the gonadoreline treated groups. Reproductive parameter values in cows with different progesterone concentrations did not differ significantly. The period from gonadoreline application until conception, was shorter by 30, 30 and 14 days, respectively, compared to the controls. The total conception rate from the first three artificial inseminations was 88. 8% in gonadoreline treated groups and 83.47 % in the control groups.
International Nuclear Information System (INIS)
Goh, Vicky; Shastry, Manu; Endozo, Raymondo; Groves, Ashley M.; Engledow, Alec; Peck, Jacqui; Reston, Jonathan; Wellsted, David M.; Rodriguez-Justo, Manuel; Taylor, Stuart A.; Halligan, Steve
2011-01-01
To determine how commercial software platform upgrades impact on derived parameters for colorectal cancer. Following ethical approval, 30 patients with suspected colorectal cancer underwent Perfusion CT using integrated 64 detector PET/CT before surgery. Analysis was performed using software based on modified distributed parameter analysis (Perfusion software version 4; Perfusion 4.0), then repeated using the previous version (Perfusion software version 3; Perfusion 3.0). Tumour blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface area product (PS) were determined for identical regions-of-interest. Slice-by-slice and 'whole tumour' variance was assessed by Bland-Altman analysis. Mean BF, BV and PS was 20.4%, 59.5%, and 106% higher, and MTT 14.3% shorter for Perfusion 4.0 than Perfusion 3.0. The mean difference (95% limits of agreement) were +13.5 (-44.9 to 72.0), +2.61 (-0.06 to 5.28), -1.23 (-6.83 to 4.36), and +14.2 (-4.43 to 32.8) for BF, BV, MTT and PS respectively. Within subject coefficient of variation was 36.6%, 38.0%, 27.4% and 60.6% for BF, BV, MTT and PS respectively indicating moderate to poor agreement. Software version upgrades of the same software platform may result in significantly different parameter values, requiring adjustments for cross-version comparison. (orig.)
Parameter and State Estimator for State Space Models
Directory of Open Access Journals (Sweden)
Ruifeng Ding
2014-01-01
Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
Parameter uncertainty and model predictions: a review of Monte Carlo results
International Nuclear Information System (INIS)
Gardner, R.H.; O'Neill, R.V.
1979-01-01
Studies of parameter variability by Monte Carlo analysis are reviewed using repeated simulations of the model with randomly selected parameter values. At the beginning of each simulation, parameter values are chosen from specific frequency distributions. This process is continued for a number of iterations sufficient to converge on an estimate of the frequency distribution of the output variables. The purpose was to explore the general properties of error propagaton in models. Testing the implicit assumptions of analytical methods and pointing out counter-intuitive results produced by the Monte Carlo approach are additional points covered
Comparison of perceived value structural models
Sunčana Piri Rajh
2012-01-01
Perceived value has been considered an important determinant of consumer shopping behavior and studied as such for a long period of time. According to one research stream, perceived value is a variable determined by perceived quality and perceived sacrifice. Another research stream suggests that the perception of value is a result of the consumer risk perception. This implies the presence of two somewhat independent research streams that are integrated by a third research stream – the one sug...
Determination of the Corona model parameters with artificial neural networks
International Nuclear Information System (INIS)
Ahmet, Nayir; Bekir, Karlik; Arif, Hashimov
2005-01-01
Full text : The aim of this study is to calculate new model parameters taking into account the corona of electrical transmission line wires. For this purpose, a neural network modeling proposed for the corona frequent characteristics modeling. Then this model was compared with the other model developed at the Polytechnic Institute of Saint Petersburg. The results of development of the specified corona model for calculation of its influence on the wave processes in multi-wires line and determination of its parameters are submitted. Results of obtained calculation equations are brought for electrical transmission line with allowance for superficial effect in the ground and wires with reference to developed corona model
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
International Nuclear Information System (INIS)
Nemtsova, O.M.
2006-01-01
The task of Moessbauer spectra processing of complex locally inhomogeneous or multi-phase systems is to reveal subspectral contributions with appreciably different values of hyperfine interaction parameters (HFI) in them. A universal method of processing such spectra is suggested which allows to extract the probability density distribution (PDD) of HFI parameters corresponding to the subspectra with essentially different parameters values. The basis of the method is Tikhonov's regularization method with selection for each subspectrum its own value of the regularization parameter. The universal application of the method is demonstrated in the examples of processing real spectra with different sets of subspectral contributions
Assessing robustness of designs for random effects parameters for nonlinear mixed-effects models.
Duffull, Stephen B; Hooker, Andrew C
2017-12-01
Optimal designs for nonlinear models are dependent on the choice of parameter values. Various methods have been proposed to provide designs that are robust to uncertainty in the prior choice of parameter values. These methods are generally based on estimating the expectation of the determinant (or a transformation of the determinant) of the information matrix over the prior distribution of the parameter values. For high dimensional models this can be computationally challenging. For nonlinear mixed-effects models the question arises as to the importance of accounting for uncertainty in the prior value of the variances of the random effects parameters. In this work we explore the influence of the variance of the random effects parameters on the optimal design. We find that the method for approximating the expectation and variance of the likelihood is of potential importance for considering the influence of random effects. The most common approximation to the likelihood, based on a first-order Taylor series approximation, yields designs that are relatively insensitive to the prior value of the variance of the random effects parameters and under these conditions it appears to be sufficient to consider uncertainty on the fixed-effects parameters only.
Modeling and Parameter Estimation of a Small Wind Generation System
Directory of Open Access Journals (Sweden)
Carlos A. Ramírez Gómez
2013-11-01
Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.
NONLINEAR PLANT PIECEWISE-CONTINUOUS MODEL MATRIX PARAMETERS ESTIMATION
Directory of Open Access Journals (Sweden)
Roman L. Leibov
2017-09-01
Full Text Available This paper presents a nonlinear plant piecewise-continuous model matrix parameters estimation technique using nonlinear model time responses and random search method. One of piecewise-continuous model application areas is defined. The results of proposed approach application for aircraft turbofan engine piecewisecontinuous model formation are presented
Identification of parameters of discrete-continuous models
International Nuclear Information System (INIS)
Cekus, Dawid; Warys, Pawel
2015-01-01
In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible
Identification of parameters of discrete-continuous models
Energy Technology Data Exchange (ETDEWEB)
Cekus, Dawid, E-mail: cekus@imipkm.pcz.pl; Warys, Pawel, E-mail: warys@imipkm.pcz.pl [Institute of Mechanics and Machine Design Foundations, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa (Poland)
2015-03-10
In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.
International Nuclear Information System (INIS)
Jiang Haimei; Liu Xinjian; Qiu Lin; Li Fengju
2014-01-01
Based on the meteorological data from weather stations around several domestic nuclear power plants, the statistical results of extreme minimum temperatures, minimum. central pressures of tropical cyclones and some other parameters are calculated using extreme value I distribution function (EV- I), generalized extreme value distribution function (GEV) and generalized Pareto distribution function (GP), respectively. The influence of different distribution functions and parameter solution methods on the statistical results of extreme values is investigated. Results indicate that generalized extreme value function has better applicability than the other two distribution functions in the determination of standard meteorological parameters for nuclear power plants. (authors)
Some tests for parameter constancy in cointegrated VAR-models
DEFF Research Database (Denmark)
Hansen, Henrik; Johansen, Søren
1999-01-01
Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ......Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations......, and another in which the cointegrating relations are estimated recursively from a likelihood function, where the short-run parameters have been concentrated out. We suggest graphical procedures based on recursively estimated eigenvalues to evaluate the constancy of the long-run parameters in the model...
Choosing put option parameters based on quantiles from the distribution of portfolio value
Bell, Peter Newton
2014-01-01
This paper explores how a put option changes the probability distribution of portfolio value. The paper extends the model introduced in Bell (2014) by allowing both the quantity and strike price to vary. I use the 5% quantile from the portfolio distribution to measure riskiness and compare different put options. I report a so-called ‘quantile surface’ that shows the quantile across different combinations of quantity and strike price. I find that it is possible to maximize the quantile by ...
Incorporating model parameter uncertainty into inverse treatment planning
International Nuclear Information System (INIS)
Lian Jun; Xing Lei
2004-01-01
Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment
Value Reappraisal as a Conceptual Model for Task-Value Interventions
Acee, Taylor W.; Weinstein, Claire Ellen; Hoang, Theresa V.; Flaggs, Darolyn A.
2018-01-01
We discuss task-value interventions as one type of relevance intervention and propose a process model of value reappraisal whereby task-value interventions elicit cognitive-affective responses that lead to attitude change and in turn affect academic outcomes. The model incorporates a metacognitive component showing that students can intentionally…
A method for model identification and parameter estimation
International Nuclear Information System (INIS)
Bambach, M; Heinkenschloss, M; Herty, M
2013-01-01
We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)
International Nuclear Information System (INIS)
Yamazaki, Tadashi; Suzuki, Jun-ichi; Shimamoto, Ryoichi; Tsuji, Taeko; Ohmoto-Sekine, Yuki; Morita, Toshihiro; Yamashita, Hiroshi; Honye, Junko; Nagai, Ryozo; Komatsu, Shuhei; Akahane, Masaaki; Ohtomo, Kuni
2008-01-01
Purpose: Hounsfield CT values across coronary CT angiograms constitute CT value-spatial profile curves. These CT profile curves are independent of window settings, and therefore, parameters derived from the curves can be used for objective anatomic analyses. Applicability of parameters derived from the curves to quantification of coronary in-stent patency has not yet been evaluated. Methods: Twenty-five CT value-spatial profile curves were delineated from 10 consecutive coronary stents to test correlation between the curve derived parameter (i.e., the minimum extreme value normalized by dividing by the maximum value of the curves obtained at neighboring outside of stents) and three intravascular ultrasound (IVUS) parameters. Results: Correlation coefficients between normalized minimum extreme value of CT value-spatial profile curves and three IVUS parameters (such as patent cross-sectional in-stent area, the percentage of patent cross-sectional in-stent area, and coronary artery intra-stent diameter) were 0.65 (p < 0.01), 0.44 (p < 0.05) and 0.51 (p < 0.05), respectively. Conclusions: CT parameters defined on Hounsfield CT value-spatial profile curves correlated significantly with IVUS parameters for quantitative coronary in-stent patency. A new approach with CT coronary angiography is therefore indicated for the noninvasive assessment of in-stent re-stenosis
Modelling hydrodynamic parameters to predict flow assisted corrosion
International Nuclear Information System (INIS)
Poulson, B.; Greenwell, B.; Chexal, B.; Horowitz, J.
1992-01-01
During the past 15 years, flow assisted corrosion has been a worldwide problem in the power generating industry. The phenomena is complex and depends on environment, material composition, and hydrodynamic factors. Recently, modeling of flow assisted corrosion has become a subject of great importance. A key part of this effort is modeling the hydrodynamic aspects of this issue. This paper examines which hydrodynamic parameter should be used to correlate the occurrence and rate of flow assisted corrosion with physically meaningful parameters, discusses ways of measuring the relevant hydrodynamic parameter, and describes how the hydrodynamic data is incorporated into the predictive model
Synopses/physical significance of complex-valued catalyst parameters in heterogeneous catalysis
Energy Technology Data Exchange (ETDEWEB)
Hesse, D
1979-08-01
An independent parameter was used to describe the local values of the interdependent thermodynamic variables of the coupled effects of transfer, sorption, and surface reaction at steady state in a packed bed of porous catalyst. A system reduction yielded a generalized concept of the pore effectiveness factor, H, which was unity or a real or imaginary complex number when the coupled diffusion and reaction processes do not affect, inhibit, or enhance conversion, respectively. These concepts are illustrated by ethylene hydrogenation on platinum, a process in which ethylene adsorbs much more strongly than hydrogen, but diffuses more slowly; as the rate is proportional to the product of hydrogen and ethylene surface coverage and the more strongly adsorbed ethylene occupies the majority of the available sites, a decrease in gas-phase ethylene concentration would increase the conversion rate. The reaction rate also increases with decreasing distance from the catalyst particle core.
The EURISOL Beta-beam Facility: Parameter and Intensity Values, Version 2
Benedikt, M; Lindroos, M; Fabich, A
An initial “bottom-up” analysis of ion intensities along the accelerator chain is revised to take into account more recent simulations of the stacking of 18Ne ions in the decay ring and beneficial trends in output flux as functions of certain machine parameters. In addition, space charge detuning at injection in the PS has led to a rethink of the top energy of the RCS, while that at injection in the SPS has had an impact on the number of bunches per batch delivered by the PS. We present transverse emittance values (which enter the space charge tune shift calculations) together with an updated list of intensities for both ion species under consideration in the baseline scenario.
International Nuclear Information System (INIS)
Yeung, H.W.; Squire, O.D.; Larson, S.M.; Erdi, Y.E.; Sanches, A.; Macapinlac, H.A.
2002-01-01
Although the standardized uptake value (SUV) is currently used in fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) imaging, concerns have been raised over its accuracy and clinical relevance. Dependence of the SUV on body weight has been observed in adults and this should be of concern in the pediatric population, since there are significant body changes during childhood. The aim of the present study was to compare SUV measurements based on body weight, body surface area and lean body mass in the pediatric population and to determine a more reliable parameter across all ages. Sixty-eight pediatric FDG-PET studies were evaluated. Age ranged from 2 to 17 years and weight from 11 to 77 kg. Regions of interest were drawn at the liver for physiologic comparison and at FDG-avid malignant lesions. SUV based on body weight (SUV bw ) varied across different weights, a phenomenon less evident when body surface area (SUV bsa ) normalization is applied. Lean body mass-based SUV (SUV lbm ) also showed a positive correlation with weight, which again was less evident when normalized to bsa (SUV bsa-lbm ). The measured liver SUV bw was 1.1±0.3, a much lower value than in our adult population (1.9±0.3). The liver SUV bsa was 7.3±1.3. The tumor sites had an SUV bw of 4.0±2.7 and an SUV bsa of 25.9±15.4 (65% of the patients had neuroblastoma). The bsa-based SUVs were more constant across the pediatric ages and were less dependent on body weight than the SUV bw . These results indicate that SUV calculated on the basis of body surface area is a more uniform parameter than SUV based on body weight in pediatric patients and is probably the most appropriate approach for the follow-up of these patients. (orig.)
Directory of Open Access Journals (Sweden)
Hideya Takeuchi
Full Text Available Peripheral blood-derived inflammation-based markers, including C-reactive protein (CRP, neutrophil-to-lymphocyte ratio (NLR, lymphocyte-to-monocyte ratio (LMR, and platelet-to-lymphocyte ratio (PLR are indicators of prognosis in various malignant tumors. The present study aimed to identify the inflammation-based parameters that are most suitable for predicting outcomes in patients with breast cancer. Two hundred ninety-six patients who underwent surgery for localized breast cancer were reviewed retrospectively. The association between clinicopathological factors and inflammation-based parameters were investigated. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic indicators associated with disease-free survival (DFS. The NLR level correlated significantly with tumor size (P<0.05. The PLR level correlated with the expression of estrogen receptor and lymph node involvement (P<0.05. Univariate analysis revealed that lower CRP and PLR values as well as tumor size, lymph node involvement, and nuclear grade were significantly associated with superior DFS (CRP: P<0.01; PLR, tumor size, lymph node involvement, and nuclear grade: P<0.05. On multivariate analysis, CRP (hazard ratio [HR]: 2.85, 95% confidence interval [CI]: 1.03-7.88, P<0.05, PLR (HR: 2.61, 95% CI: 1.07-6.36, P<0.05 and nuclear grade (HR: 3.066, 95% CI: 1.26-7.49, P<0.05 were significant prognostic indicators of DFS in patients with breast cancer. Neither LMR nor NLR significantly predicted DFS. Both preoperative CRP and PLR values were independently associated with poor prognosis in patients with breast carcinoma; these were superior to other inflammation-based scores in terms of prognostic ability.
Checking the new IRI model: The bottomside B parameters
International Nuclear Information System (INIS)
Mosert, M.; Buresova, D.; Miro, G.; Lazo, B.; Ezquer, R.
2003-01-01
Electron density profiles obtained at Pruhonice (50.0, 15.0), El Arenosillo (37.1, 353.2) and Havana (23, 278) were used to check the bottom-side B parameters BO (thickness parameter) and B1 (shape parameter) predicted by the new IRI - 2000 version. The electron density profiles were derived from ionograms using the ARP technique. The data base includes daytime and nighttime ionograms recorded under different seasonal and solar activity conditions. Comparisons with IRI predictions were also done. The analysis shows that: a) The parameter B1 given by IRI 2000 reproduces better the observed ARP values than the IRI-90 version and b) The observed BO values are in general well reproduced by both IRI versions: IRI-90 and IRI-2000. (author)
Checking the new IRI model The bottomside B parameters
Mosert, M; Ezquer, R; Lazo, B; Miro, G
2002-01-01
Electron density profiles obtained at Pruhonice (50.0, 15.0), El Arenosillo (37.1, 353.2) and Havana (23, 278) were used to check the bottom-side B parameters BO (thickness parameter) and B1 (shape parameter) predicted by the new IRI - 2000 version. The electron density profiles were derived from ionograms using the ARP technique. The data base includes daytime and nighttime ionograms recorded under different seasonal and solar activity conditions. Comparisons with IRI predictions were also done. The analysis shows that: a) The parameter B1 given by IRI 2000 reproduces better the observed ARP values than the IRI-90 version and b) The observed BO values are in general well reproduced by both IRI versions: IRI-90 and IRI-2000.
Groenendijk, M.; Dolman, A.J.; Molen, van der M.K.; Leuning, R.; Arneth, A.; Delpierre, N.; Gash, J.H.C.; Lindroth, A.; Richardson, A.D.; Verbeeck, H.; Wohlfahrt, G.
2011-01-01
The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs). PFTs are used in global land-surface models to provide parameter values for every model grid cell. With a simple photosynthesis model we
Revisiting linear plasma waves for finite value of the plasma parameter
Grismayer, Thomas; Fahlen, Jay; Decyk, Viktor; Mori, Warren
2010-11-01
We investigate through theory and PIC simulations the Landau-damping of plasma waves with finite plasma parameter. We concentrate on the linear regime, γφB, where the waves are typically small and below the thermal noise. We simulate these condition using 1,2,3D electrostatic PIC codes (BEPS), noting that modern computers now allow us to simulate cases where (nλD^3 = [1e2;1e6]). We study these waves by using a subtraction technique in which two simulations are carried out. In the first, a small wave is initialized or driven, in the second no wave is excited. The results are subtracted to provide a clean signal that can be studied. As nλD^3 is decreased, the number of resonant electrons can be small for linear waves. We show how the damping changes as a result of having few resonant particles. We also find that for small nλD^3 fluctuations can cause the electrons to undergo collisions that eventually destroy the initial wave. A quantity of interest is the the life time of a particular mode which depends on the plasma parameter and the wave number. The life time is estimated and then compared with the numerical results. A surprising result is that even for large values of nλD^3 some non-Vlasov discreteness effects appear to be important.
Mean Value Modelling of Turbocharged SI Engines
DEFF Research Database (Denmark)
Müller, Martin; Hendricks, Elbert; Sorenson, Spencer C.
1998-01-01
The development of a computer simulation to predict the performance of a turbocharged spark ignition engine during transient operation. New models have been developed for the turbocharged and the intercooling system. An adiabatic model for the intake manifold is presented.......The development of a computer simulation to predict the performance of a turbocharged spark ignition engine during transient operation. New models have been developed for the turbocharged and the intercooling system. An adiabatic model for the intake manifold is presented....
Online State Space Model Parameter Estimation in Synchronous Machines
Directory of Open Access Journals (Sweden)
Z. Gallehdari
2014-06-01
The suggested approach is evaluated for a sample synchronous machine model. Estimated parameters are tested for different inputs at different operating conditions. The effect of noise is also considered in this study. Simulation results show that the proposed approach provides good accuracy for parameter estimation.
DEFF Research Database (Denmark)
Pauwels, Valentijn; Balenzano, Anna; Satalino, Giuseppe
2009-01-01
It is widely recognized that Synthetic Aperture Radar (SAR) data are a very valuable source of information for the modeling of the interactions between the land surface and the atmosphere. During the last couple of decades, most of the research on the use of SAR data in hydrologic applications has...... that no direct relationships between the remote-sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this paper is to retrieve a number of soil physical model parameters through...
International Nuclear Information System (INIS)
Harish, V.S.K.V.; Kumar, Arun
2016-01-01
Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.
Directory of Open Access Journals (Sweden)
Sylvia Chan-Olmsted
2016-07-01
Full Text Available This study models the dynamic nature of today’s media markets using the framework of value-adding activities in the provision and consumption of media products. The proposed user-centric approach introduces the notion that the actions of external users, social media, and interfaces affect the internal value activities of media firms via a feedback loop, and therefore should themselves be considered value activities. The model also suggests a more comprehensive list of indicators for value assessment.
Radon decay product in-door behaviour - parameter, measurement method, and model review
International Nuclear Information System (INIS)
Scofield, P.
1988-01-01
This report reviews parameters used to characterize indoor radon daughter behavior and concentrations. Certain parameters that affect indoor radon daughter concentrations are described and the values obtained experimentally or theoretically are summarized. Radon daughter measurement methods are reviewed, such as, PAEC, unattached daughters, particle size distributions, and plateout measurement methods. In addition, certain radon pressure driven/diffusion models and indoor radon daughter models are briefly described. (orig.)
Parameters Calculation of ZnO Surge Arrester Models by Genetic Algorithms
Directory of Open Access Journals (Sweden)
A. Bayadi
2006-09-01
Full Text Available This paper proposes to provide a new technique based on the genetic algorithm to obtain the best possible series of values of the parameters of the ZnO surge arresters models. The validity of the predicted parameters is then checked by comparing the results predicted with the experimental results available in the literature. Using the ATP-EMTP package an application of the arrester model on network system studies is presented and discussed.
Predictive value of some hematological parameters for non-invasive and invasive mole pregnancies.
Abide Yayla, Cigdem; Özkaya, Enis; Yenidede, Ilter; Eser, Ahmet; Ergen, Evrim Bostancı; Tayyar, Ahter Tanay; Şentürk, Mehmet Baki; Karateke, Ates
2018-02-01
The aim of this study was to discriminate mole pregnancies and invasive forms among cases with first trimester vaginal bleeding by the utilization of some complete blood count parameters conjunct to sonographic findings and beta human chorionic gonadotropin concentration. Consecutive 257 cases with histopathologically confirmed mole pregnancies and 199 women without mole pregnancy presented with first trimester vaginal bleeding who admitted to Zeynep Kamil Women and Children's Health Training Hospital between January 2012 and January 2016 were included in this cross-sectional study. The serum beta HCG level at presentation, and beta hCG levels at 1st, 2nd and 3rd weeks of postevacuation with some parameters of complete blood count were utilized to discriminate cases with molar pregnancy and cases with invasive mole among first trimester pregnants presented with vaginal bleeding and abnormal sonographic findings. Levels of beta hCG at baseline (AUC = 0.700, p < 0.05) and 1st (AUC = 0.704, p < 0.05), 2nd (AUC = 0.870, p < 0.001) and 3rd (AUC = 0.916, p < 0.001) weeks of postevacuation period were significant predictors for the cases with persistent disease. While area under curve for mean platelet volume is 0.715, it means that mean platelet volume has 21.5% additional diagnostic value for predicting persistency in molar patients. For 8.55 cut-off point for mean platelet volume, sensitivity is 84.6% and specificity is 51.6%. Area under curve for platelet/lymphocyte ratio is 0.683 means that platelet/lymphocyte ratio has additional 18.3% diagnostic value. For 102.25 cut-off point sensitivity is 86.6% and specificity is 46.2. Simple, widely available complete blood count parameters may be used as an adjunct to other risk factors to diagnose molar pregnancies and predict postevacuation trophoblastic disease.
Bates, P. D.; Neal, J. C.; Fewtrell, T. J.
2012-12-01
In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound
Georgiou, Stelios N; Fousiani, Kyriaki; Michaelides, Michalis; Stavrinides, Panayiotis
2013-01-01
The purpose of the present study was to examine the existing association between cultural value orientation, authoritarian parenting, and bullying and victimization at school. The participants (N = 231) were early adolescents, randomly selected from 11 different schools in urban and rural areas of Cyprus. Participants completed self reports measuring cultural value orientation, authoritarian parenting, bullying, and victimization. These instruments were the following: the cultural value scale (CVS), the parental authority questionnaire (PAQ), and the revised bullying and victimization questionnaire (BVQ-R). Structural equation modeling (SEM) was used to examine mediation effects. It was found that vertical individualism acted as a mediator between authoritarian parenting and bullying. Statistically significant positive correlations were found between authoritarian parenting and the vertical dimensions of both cultural value orientations (individualism and collectivism), but not with the horizontal dimensions of either cultural orientation. Further, authoritarian parenting was also positively associated with bullying and victimization at school. The main contribution of the present study is the finding that vertical individualism significantly mediates the relationship between authoritarian parental style and bullying propensity.
Retrospective forecast of ETAS model with daily parameters estimate
Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang
2016-04-01
We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.
Application of Artificial Bee Colony in Model Parameter Identification of Solar Cells
Directory of Open Access Journals (Sweden)
Rongjie Wang
2015-07-01
Full Text Available The identification of values of solar cell parameters is of great interest for evaluating solar cell performances. The algorithm of an artificial bee colony was used to extract model parameters of solar cells from current-voltage characteristics. Firstly, the best-so-for mechanism was introduced to the original artificial bee colony. Then, a method was proposed to identify parameters for a single diode model and double diode model using this improved artificial bee colony. Experimental results clearly demonstrate the effectiveness of the proposed method and its superior performance compared to other competing methods.
Sensitivity of numerical dispersion modeling to explosive source parameters
International Nuclear Information System (INIS)
Baskett, R.L.; Cederwall, R.T.
1991-01-01
The calculation of downwind concentrations from non-traditional sources, such as explosions, provides unique challenges to dispersion models. The US Department of Energy has assigned the Atmospheric Release Advisory Capability (ARAC) at the Lawrence Livermore National Laboratory (LLNL) the task of estimating the impact of accidental radiological releases to the atmosphere anywhere in the world. Our experience includes responses to over 25 incidents in the past 16 years, and about 150 exercises a year. Examples of responses to explosive accidents include the 1980 Titan 2 missile fuel explosion near Damascus, Arkansas and the hydrogen gas explosion in the 1986 Chernobyl nuclear power plant accident. Based on judgment and experience, we frequently estimate the source geometry and the amount of toxic material aerosolized as well as its particle size distribution. To expedite our real-time response, we developed some automated algorithms and default assumptions about several potential sources. It is useful to know how well these algorithms perform against real-world measurements and how sensitive our dispersion model is to the potential range of input values. In this paper we present the algorithms we use to simulate explosive events, compare these methods with limited field data measurements, and analyze their sensitivity to input parameters. 14 refs., 7 figs., 2 tabs
Parameter Estimates in Differential Equation Models for Population Growth
Winkel, Brian J.
2011-01-01
We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and two-species competition models. We discuss student-evolved strategies and offer "Mathematica" code for a gradient search approach. We use historical (1930s) data from microbial studies of the Russian biologist,…
Uncertainty in dual permeability model parameters for structured soils
Arora, B.; Mohanty, B. P.; McGuire, J. T.
2012-01-01
Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface (Ksa) and macropore tortuosity (lf) but also of other parameters of the matrix and macropore domains.
The added value of business models
Vliet, Harry van
An overview of innovations in a particular area, for example retail developments in the fashion sector (Van Vliet, 2014), and a subsequent discussion about the probability as to whether these innovations will realise a ‘breakthrough’, has to be supplemented with the question of what the added value
Modeling value creation with enterprise architecture
Singh, Prince Mayurank; Jonkers, H.; Iacob, Maria Eugenia; van Sinderen, Marten J.
2014-01-01
Firms may not succeed in business if strategies are not properly implemented in practice. Every firm needs to know, represent and master its value creation logic, not only to stay in business but also to keep growing. This paper is about focusing on an important topic in the field of strategic
Melching, C.S.; Marquardt, J.S.
1997-01-01
Design hydrographs computed from design storms, simple models of abstractions (interception, depression storage, and infiltration), and synthetic unit hydrographs provide vital information for stormwater, flood-plain, and water-resources management throughout the United States. Rainfall and runoff data for small watersheds in Lake County collected between 1990 and 1995 were studied to develop equations for estimation of synthetic unit-hydrograph parameters on the basis of watershed and storm characteristics. The synthetic unit-hydrograph parameters of interest were the time of concentration (TC) and watershed-storage coefficient (R) for the Clark unit-hydrograph method, the unit-graph lag (UL) for the Soil Conservation Service (now known as the Natural Resources Conservation Service) dimensionless unit hydrograph, and the hydrograph-time lag (TL) for the linear-reservoir method for unit-hydrograph estimation. Data from 66 storms with effective-precipitation depths greater than 0.4 inches on 9 small watersheds (areas between 0.06 and 37 square miles (mi2)) were utilized to develop the estimation equations, and data from 11 storms on 8 of these watersheds were utilized to verify (test) the estimation equations. The synthetic unit-hydrograph parameters were determined by calibration using the U.S. Army Corps of Engineers Flood Hydrograph Package HEC-1 (TC, R, and UL) or by manual analysis of the rainfall and run-off data (TL). The relation between synthetic unit-hydrograph parameters, and watershed and storm characteristics was determined by multiple linear regression of the logarithms of the parameters and characteristics. Separate sets of equations were developed with watershed area and main channel length as the starting parameters. Percentage of impervious cover, main channel slope, and depth of effective precipitation also were identified as important characteristics for estimation of synthetic unit-hydrograph parameters. The estimation equations utilizing area
Luminescence model with quantum impact parameter for low energy ions
Cruz-Galindo, H S; Martínez-Davalos, A; Belmont-Moreno, E; Galindo, S
2002-01-01
We have modified an analytical model of induced light production by energetic ions interacting in scintillating materials. The original model is based on the distribution of energy deposited by secondary electrons produced along the ion's track. The range of scattered electrons, and thus the energy distribution, depends on a classical impact parameter between the electron and the ion's track. The only adjustable parameter of the model is the quenching density rho sub q. The modification here presented, consists in proposing a quantum impact parameter that leads to a better fit of the model to the experimental data at low incident ion energies. The light output response of CsI(Tl) detectors to low energy ions (<3 MeV/A) is fitted with the modified model and comparison is made to the original model.
Directory of Open Access Journals (Sweden)
Jie Bao
2015-12-01
Full Text Available Effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash–Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA approaches, including analysis of variance based on the generalized linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.
Agricultural and Environmental Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
K. Rasmuson; K. Rautenstrauch
2004-01-01
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters
Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation
Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei
2018-04-01
Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.
Uncertainty of Modal Parameters Estimated by ARMA Models
DEFF Research Database (Denmark)
Jensen, Jacob Laigaard; Brincker, Rune; Rytter, Anders
1990-01-01
In this paper the uncertainties of identified modal parameters such as eidenfrequencies and damping ratios are assed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the parameters...... by simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been choosen as system identification method. It is concluded that both the sampling interval and number of sampled points may play a significant role with respect to the statistical errors. Furthermore......, it is shown that the model errors may also contribute significantly to the uncertainty....
SPOTting Model Parameters Using a Ready-Made Python Package.
Directory of Open Access Journals (Sweden)
Tobias Houska
Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.
Using many pilot points and singular value decomposition in groundwater model calibration
DEFF Research Database (Denmark)
Christensen, Steen; Doherty, John
2008-01-01
over the model area. Singular value decomposition (SVD) of the normal matrix is used to reduce the large number of pilot point parameters to a smaller number of so-called super parameters that can be estimated by nonlinear regression from the available observations. A number of eigenvectors...
Parameter resolution in two models for cell survival after radiation
International Nuclear Information System (INIS)
Di Cera, E.; Andreasi Bassi, F.; Arcovito, G.
1989-01-01
The resolvability of model parameters for the linear-quadratic and the repair-misrepair models for cell survival after radiation has been studied by Monte Carlo simulations as a function of the number of experimental data points collected in a given dose range and the experimental error. Statistical analysis of the results reveals the range of experimental conditions under which the model parameters can be resolved with sufficient accuracy, and points out some differences in the operational aspects of the two models. (orig.)
Simultaneous inference for model averaging of derived parameters
DEFF Research Database (Denmark)
Jensen, Signe Marie; Ritz, Christian
2015-01-01
Model averaging is a useful approach for capturing uncertainty due to model selection. Currently, this uncertainty is often quantified by means of approximations that do not easily extend to simultaneous inference. Moreover, in practice there is a need for both model averaging and simultaneous...... inference for derived parameters calculated in an after-fitting step. We propose a method for obtaining asymptotically correct standard errors for one or several model-averaged estimates of derived parameters and for obtaining simultaneous confidence intervals that asymptotically control the family...
Updating parameters of the chicken processing line model
DEFF Research Database (Denmark)
Kurowicka, Dorota; Nauta, Maarten; Jozwiak, Katarzyna
2010-01-01
A mathematical model of chicken processing that quantitatively describes the transmission of Campylobacter on chicken carcasses from slaughter to chicken meat product has been developed in Nauta et al. (2005). This model was quantified with expert judgment. Recent availability of data allows...... updating parameters of the model to better describe processes observed in slaughterhouses. We propose Bayesian updating as a suitable technique to update expert judgment with microbiological data. Berrang and Dickens’s data are used to demonstrate performance of this method in updating parameters...... of the chicken processing line model....
Lumped-parameter Model of a Bucket Foundation
DEFF Research Database (Denmark)
Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten
2009-01-01
efficient model that can be applied in aero-elastic codes for fast evaluation of the dynamic structural response of wind turbines. The target solutions, utilised for calibration of the lumped-parameter models, are obtained by a coupled finite-element/boundaryelement scheme in the frequency domain......, and the quality of the models are tested in the time and frequency domains. It is found that precise results are achieved by lumped-parameter models with two to four internal degrees of freedom per displacement or rotation of the foundation. Further, coupling between the horizontal sliding and rocking cannot...
Lumped-Parameter Models for Windturbine Footings on Layered Ground
DEFF Research Database (Denmark)
Andersen, Lars
The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computationalmodel significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...
Energy Technology Data Exchange (ETDEWEB)
Zou, Li [Dalian Univ. of Technology, Dalian City (China). State Key Lab. of Structural Analysis for Industrial Equipment; Liang, Songxin; Li, Yawei [Dalian Univ. of Technology, Dalian City (China). School of Mathematical Sciences; Jeffrey, David J. [Univ. of Western Ontario, London (Canada). Dept. of Applied Mathematics
2017-06-01
Nonlinear boundary value problems arise frequently in physical and mechanical sciences. An effective analytic approach with two parameters is first proposed for solving nonlinear boundary value problems. It is demonstrated that solutions given by the two-parameter method are more accurate than solutions given by the Adomian decomposition method (ADM). It is further demonstrated that solutions given by the ADM can also be recovered from the solutions given by the two-parameter method. The effectiveness of this method is demonstrated by solving some nonlinear boundary value problems modeling beam-type nano-electromechanical systems.
Value uncaptured perspective for sustainable business model innovation
Yang, M; Evans, S; Vladimirova, D; Rana, P
2016-01-01
Sustainability has become one of the key factors for long-term business success. Recent research and practice show that business model innovation is a promising approach for improving sustainability in manufacturing firms. To date business models have been examined mostly from the perspectives of value proposition, value capture, value creation and delivery. There is a need for a more comprehensive understanding of value in order to promote sustainability. This paper proposes value uncaptured...
See, J. J.; Jamaian, S. S.; Salleh, R. M.; Nor, M. E.; Aman, F.
2018-04-01
This research aims to estimate the parameters of Monod model of microalgae Botryococcus Braunii sp growth by the Least-Squares method. Monod equation is a non-linear equation which can be transformed into a linear equation form and it is solved by implementing the Least-Squares linear regression method. Meanwhile, Gauss-Newton method is an alternative method to solve the non-linear Least-Squares problem with the aim to obtain the parameters value of Monod model by minimizing the sum of square error ( SSE). As the result, the parameters of the Monod model for microalgae Botryococcus Braunii sp can be estimated by the Least-Squares method. However, the estimated parameters value obtained by the non-linear Least-Squares method are more accurate compared to the linear Least-Squares method since the SSE of the non-linear Least-Squares method is less than the linear Least-Squares method.
International Nuclear Information System (INIS)
Chen, B.C.J.; Hull, J.R.; Seitz, M.G.; Sha, W.T.; Shah, V.L.; Soo, S.L.
1984-07-01
Computer model simulation is required to evaluate the performance of proposed or future high-level radioactive waste geological repositories. However, the accuracy of a model in predicting the real situation depends on how well the values of the transport properties are prescribed as input parameters. Knowledge of transport parameters is therefore essential. We have modeled ANL's Experiment Analog Program which was designed to simulate long-term radwaste migration process by groundwater flowing through a high-level radioactive waste repository. Using this model and experimental measurements, we have evaluated neptunium (actinide) deposition velocity and analyzed the complex phenomena of simultaneous deposition, erosion, and reentrainment of bentonite when groundwater is flowing through a narrow crack in a basalt rock. The present modeling demonstrates that we can obtain the values of transport parameters, as added information without any additional cost, from the available measurements of laboratory analog experiments. 8 figures, 3 tables
CASIM calculations and angular dependent parameter β in the Moyer model
International Nuclear Information System (INIS)
Yamaguchi, Chiri.
1988-04-01
The dose equivalent on the shield surface has been calculated using both the Moyer model and the Monte Carlo code CASIM. Calculations with various values of the angular distribution parameter β in the Moyer model show that β = 7.0 ± 0.5 would meet the CASIM results at most, especially regarding locations at which the values of the maximum dose equivalent occur. (author)
MODELING OF FUEL SPRAY CHARACTERISTICS AND DIESEL COMBUSTION CHAMBER PARAMETERS
Directory of Open Access Journals (Sweden)
G. M. Kukharonak
2011-01-01
Full Text Available The computer model for coordination of fuel spray characteristics with diesel combustion chamber parameters has been created in the paper. The model allows to observe fuel sprays develоpment in diesel cylinder at any moment of injection, to calculate characteristics of fuel sprays with due account of a shape and dimensions of a combustion chamber, timely to change fuel injection characteristics and supercharging parameters, shape and dimensions of a combustion chamber. Moreover the computer model permits to determine parameters of holes in an injector nozzle that provides the required fuel sprays characteristics at the stage of designing a diesel engine. Combustion chamber parameters for 4ЧН11/12.5 diesel engine have been determined in the paper.
Arkuszewski, M; Krejza, J; Chen, R; Kwiatkowski, J L; Ichord, R; Zimmerman, R; Ohene-Frempong, K; Desiderio, L; Melhem, E R
2011-09-01
TCD screening is widely used to identify children with SCD at high risk of stroke. Those with high mean flow velocities in major brain arteries have increased risk of stroke. Thus, our aim was to establish reference values of interhemispheric differences and ratios of blood flow Doppler parameters in the tICA, MCA, and ACA as determined by conventional TCD in children with sickle cell anemia. Reference limits of blood flow parameters were established on the basis of a consecutive cohort of 56 children (mean age, 100 ± 40 months; range, 29-180 months; 30 females) free of neurologic deficits and intracranial stenosis detectable by MRA, with blood flow velocities <170 cm/s by conventional TCD. Reference limits were estimated by using tolerance intervals, within which are included with a probability of .90 of all possible data values from 95% of a population. Average peak systolic velocities were significantly higher in the right hemisphere in the MCA and ACA (185 ± 28 cm/s versus 179 ± 27 and 152 ± 30 cm/s versus 143 ± 34 cm/s respectively). Reference limits for left-to-right differences in the mean flow velocities were the following: -43 to 33 cm/s for the MCA; -49 to 38 cm/s for the ACA, and -38 to 34 cm/s for the tICA, respectively. Respective reference limits for left-to-right velocity ratios were the following: 0.72 to 1.25 cm/s for the MCA; 0.62 to 1.39 cm/s for the ACA, and 0.69 to 1.27 cm/s for the tICA. Flow velocities in major arteries were inversely related to age and Hct or Hgb. The study provides reference intervals of TCD flow velocities and their interhemispheric differences and ratios that may be helpful in identification of intracranial arterial stenosis in children with SCD undergoing sonographic screening for stroke prevention.
Application of an Evolutionary Algorithm for Parameter Optimization in a Gully Erosion Model
Energy Technology Data Exchange (ETDEWEB)
Rengers, Francis; Lunacek, Monte; Tucker, Gregory
2016-06-01
Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.
Seasonal and spatial variation in broadleaf forest model parameters
Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.
2009-04-01
Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and
Artificial Neural Network model for the determination of GSM Rxlevel from atmospheric parameters
Directory of Open Access Journals (Sweden)
Julia Ofure Eichie
2017-04-01
Full Text Available Accurate received signal level (Rxlevel values are useful for mobile telecommunication network planning. Rxlevel is affected by the dynamics of the atmosphere through which it propagates. Adequate knowledge of the prevailing atmospheric conditions in an environment is essential for proper network planning. However most of the existing GSM received signal determination model are function of distance between point of signal reception and transmitting site thus necessitating the development of a model that involve the use of atmospheric parameters in the determination of received GSM signal level. In this paper, a three stage approach was used in the development of the model using some atmospheric parameters such as atmospheric temperature, relative humidity and dew point. The selected and easily measurable atmospheric parameters were used as input parameters in developing two new models for computing the Rxlevel of GSM signal using a three-step approach. Data acquisition and pre-processing serves as the first stage and formulation of ANN design and the development of parametric model for the Rxlevel using ANN synaptic weights form the second stage of the proposed approach. The third stage involves the use of ANN weight and bias values, and network architecture in the development of the model equation. In evaluating the performance of the proposed models, network parameters were varied and the results obtained using mean squared error (MSE as performance measure showed the developed model with 33 neurons in the hidden layer and tansig activation, function in both the hidden and output layers as the optimal model with least MSE value of 0.056. Thus showing that the developed model has an acceptable accuracy value as demonstrated from comparison of results with actual measured values.
Directory of Open Access Journals (Sweden)
Jun Li
2017-01-01
Full Text Available Considering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a three-parameter model, including the initial abstraction coefficient λ, the initial abstraction Ia, and the rainfall loss coefficient R. The improved LCM model is superior to the original two-parameter model, which only includes r and R, where r is the initial rainfall loss index and can be calculated with λ using the Soil Conservation Service curve number (SCS-CN method, with r=1/(1+λ. The trial method was used to determine the parameter values of the improved LCM model at the watershed scale for 15 flood events in the Hongde Basin in China. The results show that larger r values are associated with smaller R values, and the parameter R ranges widely from 0.5 to 2.0. In order to improve the practicability of the LCM model, r=0.833 with λ=0.2 is reasonable for simplifying calculation. When the LCM model is applied to arid and semi-arid regions, rainfall without yielding runoff should be deducted from the total rainfall for more accurate estimation of rainfall-runoff.
The role of non-epistemic values in engineering models
Diekmann, S.; Peterson, M.B.
2013-01-01
We argue that non-epistemic values, including moral ones, play an important role in the construction and choice of models in science and engineering. Our main claim is that non-epistemic values are not only "secondary values" that become important just in case epistemic values leave some issues
Reflector modelization for neutronic diffusion and parameters identification
International Nuclear Information System (INIS)
Argaud, J.P.
1993-04-01
Physical parameters of neutronic diffusion equations can be adjusted to decrease calculations-measurements errors. The reflector being always difficult to modelize, we choose to elaborate a new reflector model and to use the parameters of this model as adjustment coefficients in the identification procedure. Using theoretical results, and also the physical behaviour of neutronic flux solutions, the reflector model consists then in its replacement by boundary conditions for the diffusion equations on the core only. This theoretical result of non-local operator relations leads then to some discrete approximations by taking into account the multiscaled behaviour, on the core-reflector interface, of neutronic diffusion solutions. The resulting model of this approach is then compared with previous reflector modelizations, and first results indicate that this new model gives the same representation of reflector for the core than previous. (author). 12 refs
Directory of Open Access Journals (Sweden)
G.B. Camilo
2015-01-01
Full Text Available The aims of this study were to evaluate the forced oscillation technique (FOT and pulmonary densitovolumetry in acromegalic patients and to examine the correlations between these findings. In this cross-sectional study, 29 non-smoking acromegalic patients and 17 paired controls were subjected to the FOT and quantification of lung volume using multidetector computed tomography (Q-MDCT. Compared with the controls, the acromegalic patients had a higher value for resonance frequency [15.3 (10.9-19.7 vs 11.4 (9.05-17.6 Hz, P=0.023] and a lower value for mean reactance [0.32 (0.21-0.64 vs 0.49 (0.34-0.96 cm H2O/L/s2, P=0.005]. In inspiratory Q-MDCT, the acromegalic patients had higher percentages of total lung volume (TLV for nonaerated and poorly aerated areas [0.42% (0.30-0.51% vs 0.25% (0.20-0.32%, P=0.039 and 3.25% (2.48-3.46% vs 1.70% (1.45-2.15%, P=0.001, respectively]. Furthermore, the acromegalic patients had higher values for total lung mass in both inspiratory and expiratory Q-MDCT [821 (635-923 vs 696 (599-769 g, P=0.021 and 844 (650-945 vs 637 (536-736 g, P=0.009, respectively]. In inspiratory Q-MDCT, TLV showed significant correlations with all FOT parameters. The TLV of hyperaerated areas showed significant correlations with intercept resistance (rs=−0.602, P<0.001 and mean resistance (rs=−0.580, P<0.001. These data showed that acromegalic patients have increased amounts of lung tissue as well as nonaerated and poorly aerated areas. Functionally, there was a loss of homogeneity of the respiratory system. Moreover, there were correlations between the structural and functional findings of the respiratory system, consistent with the pathophysiology of the disease.
On unique parameters and unified formal form of hot-wire anemometric sensor model
International Nuclear Information System (INIS)
LigePza, P.
2005-01-01
This note reviews the extensively adopted equations used as models of hot-wire anemometric sensors. An unified formal form of the mathematical model of a hot-wire anemometric sensor with otherwise defined parameters is proposed. Those parameters, static and dynamic, have simple physical interpretation and can be easily determined. They show directly the range of sensor application. They determine the metrological properties of the given sensor in the actual medium. Hence, the parameters' values might be ascribed to each sensor in the given medium and be quoted in manufacturers' catalogues, supplementing the sensor specifications. Because of their simple physical interpretation, those parameters allow the direct comparison of the fundamental metrological properties of various sensors and selection of the optimal sensor for the given research measurement application. The parameters are also useful in modeling complex hot-wire systems
One-Step Dynamic Classifier Ensemble Model for Customer Value Segmentation with Missing Values
Directory of Open Access Journals (Sweden)
Jin Xiao
2014-01-01
Full Text Available Scientific customer value segmentation (CVS is the base of efficient customer relationship management, and customer credit scoring, fraud detection, and churn prediction all belong to CVS. In real CVS, the customer data usually include lots of missing values, which may affect the performance of CVS model greatly. This study proposes a one-step dynamic classifier ensemble model for missing values (ODCEM model. On the one hand, ODCEM integrates the preprocess of missing values and the classification modeling into one step; on the other hand, it utilizes multiple classifiers ensemble technology in constructing the classification models. The empirical results in credit scoring dataset “German” from UCI and the real customer churn prediction dataset “China churn” show that the ODCEM outperforms four commonly used “two-step” models and the ensemble based model LMF and can provide better decision support for market managers.
Regionalising Parameters of a Conceptual Rainfall-Runoff Model for ...
African Journals Online (AJOL)
IHACRES, a lumped conceptual rainfall-runoff model, was calibrated to six catchments ranging in size from 49km2 to 600 km2 within the upper Tana River basin to obtain a set of model parameters that characterise the hydrological behaviour within the region. Physical catchment attributes indexing topography, soil and ...
Constraint on Parameters of Inverse Compton Scattering Model for ...
Indian Academy of Sciences (India)
B2319+60, two parameters of inverse Compton scattering model, the initial Lorentz factor and the factor of energy loss of relativistic particles are constrained. Key words. Pulsar—inverse Compton scattering—emission mechanism. 1. Introduction. Among various kinds of models for pulsar radio emission, the inverse ...
Geometry parameters for musculoskeletal modelling of the shoulder system
Van der Helm, F C; Veeger, DirkJan (H. E. J.); Pronk, G M; Van der Woude, L H; Rozendal, R H
A dynamical finite-element model of the shoulder mechanism consisting of thorax, clavicula, scapula and humerus is outlined. The parameters needed for the model are obtained in a cadaver experiment consisting of both shoulders of seven cadavers. In this paper, in particular, the derivation of
Rain storm models and the relationship between their parameters
Stol, P.T.
1977-01-01
Rainfall interstation correlation functions can be obtained with the aid of analytic rainfall or storm models. Since alternative storm models have different mathematical formulas, comparison should be based on equallity of parameters like storm diameter, mean rainfall amount, storm maximum or total
Directory of Open Access Journals (Sweden)
Jeng-Wen Lin
2009-01-01
Full Text Available This paper proposes a statistical confidence interval based nonlinear model parameter refinement approach for the health monitoring of structural systems subjected to seismic excitations. The developed model refinement approach uses the 95% confidence interval of the estimated structural parameters to determine their statistical significance in a least-squares regression setting. When the parameters' confidence interval covers the zero value, it is statistically sustainable to truncate such parameters. The remaining parameters will repetitively undergo such parameter sifting process for model refinement until all the parameters' statistical significance cannot be further improved. This newly developed model refinement approach is implemented for the series models of multivariable polynomial expansions: the linear, the Taylor series, and the power series model, leading to a more accurate identification as well as a more controllable design for system vibration control. Because the statistical regression based model refinement approach is intrinsically used to process a “batch” of data and obtain an ensemble average estimation such as the structural stiffness, the Kalman filter and one of its extended versions is introduced to the refined power series model for structural health monitoring.
Lumped-parameters equivalent circuit for condenser microphones modeling.
Esteves, Josué; Rufer, Libor; Ekeom, Didace; Basrour, Skandar
2017-10-01
This work presents a lumped parameters equivalent model of condenser microphone based on analogies between acoustic, mechanical, fluidic, and electrical domains. Parameters of the model were determined mainly through analytical relations and/or finite element method (FEM) simulations. Special attention was paid to the air gap modeling and to the use of proper boundary condition. Corresponding lumped-parameters were obtained as results of FEM simulations. Because of its simplicity, the model allows a fast simulation and is readily usable for microphone design. This work shows the validation of the equivalent circuit on three real cases of capacitive microphones, including both traditional and Micro-Electro-Mechanical Systems structures. In all cases, it has been demonstrated that the sensitivity and other related data obtained from the equivalent circuit are in very good agreement with available measurement data.
The performance of simulated annealing in parameter estimation for vapor-liquid equilibrium modeling
Directory of Open Access Journals (Sweden)
A. Bonilla-Petriciolet
2007-03-01
Full Text Available In this paper we report the application and evaluation of the simulated annealing (SA optimization method in parameter estimation for vapor-liquid equilibrium (VLE modeling. We tested this optimization method using the classical least squares and error-in-variable approaches. The reliability and efficiency of the data-fitting procedure are also considered using different values for algorithm parameters of the SA method. Our results indicate that this method, when properly implemented, is a robust procedure for nonlinear parameter estimation in thermodynamic models. However, in difficult problems it still can converge to local optimums of the objective function.
Impact of power plant reliability on the choice of operating parameter values
International Nuclear Information System (INIS)
Kramer, R.A.
1985-01-01
In this thesis, the basic structure for the development of a methodology to evaluate the effect of operating parameters on plant availability and generating system economic dispatch optimization is described. Plant availability is determined by a fault free model. In this model historic, time dependent, component induced forced outage data is utilized as the basis for the calculation of projected plant forced outage rates. The influence of a particular fuel-cycle length at a specific generating station on the operational planning of a multi unit generating system is considered. The basis of the dispatch of units in this analysis is optimal economic operation, i.e., the minimization of the cost of reliability supplying electricity to the system's customers. As a result of the utilization of this technique, a simplified example that considers the choice between a 12- and 18-month fuel cycle length is evaluated in terms of its impact on plant availability, fuel cycle economics and overall optimal generating system economic dispatch. The reliability portion of this methodology is applied to a simplified representation of the recirculation system of a pressurized water reactor nuclear power plant to illustrate the analytic techniques
Extension of the direct statistical approach to a volume parameter model (non-integer splitting)
International Nuclear Information System (INIS)
Burn, K.W.
1990-01-01
The Direct Statistical Approach is a rigorous mathematical derivation of the second moment for surface splitting and Russian Roulette games attached to the Monte Carlo modelling of fixed source particle transport. It has been extended to a volume parameter model (involving non-integer ''expected value'' splitting), and then to a cell model. The cell model gives second moment and time functions that have a closed form. This suggests the possibility of two different methods of solution of the optimum splitting/Russian Roulette parameters. (author)
Directory of Open Access Journals (Sweden)
Khaled MAMMAR
2013-11-01
Full Text Available In this paper, a new approach based on Experimental of design methodology (DoE is used to estimate the optimal of unknown model parameters proton exchange membrane fuel cell (PEMFC. This proposed approach combines the central composite face-centered (CCF and numerical PEMFC electrochemical. Simulation results obtained using electrochemical model help to predict the cell voltage in terms of inlet partial pressures of hydrogen and oxygen, stack temperature, and operating current. The value of the previous model and (CCF design methodology is used for parametric analysis of electrochemical model. Thus it is possible to evaluate the relative importance of each parameter to the simulation accuracy. However this methodology is able to define the exact values of the parameters from the manufacture data. It was tested for the BCS 500-W stack PEM Generator, a stack rated at 500 W, manufactured by American Company BCS Technologies FC.
Determination of appropriate models and parameters for premixing calculations
Energy Technology Data Exchange (ETDEWEB)
Park, Ik-Kyu; Kim, Jong-Hwan; Min, Beong-Tae; Hong, Seong-Wan
2008-03-15
The purpose of the present work is to use experiments that have been performed at Forschungszentrum Karlsruhe during about the last ten years for determining the most appropriate models and parameters for premixing calculations. The results of a QUEOS experiment are used to fix the parameters concerning heat transfer. The QUEOS experiments are especially suited for this purpose as they have been performed with small hot solid spheres. Therefore the area of heat exchange is known. With the heat transfer parameters fixed in this way, a PREMIX experiment is recalculated. These experiments have been performed with molten alumina (Al{sub 2}O{sub 3}) as a simulant of corium. Its initial temperature is 2600 K. With these experiments the models and parameters for jet and drop break-up are tested.
Parameter identification in a nonlinear nuclear reactor model using quasilinearization
International Nuclear Information System (INIS)
Barreto, J.M.; Martins Neto, A.F.; Tanomaru, N.
1980-09-01
Parameter identification in a nonlinear, lumped parameter, nuclear reactor model is carried out using discrete output power measurements during the transient caused by an external reactivity change. In order to minimize the difference between the model and the reactor power responses, the parameter promt neutron generation time and a parameter in fuel temperature reactivity coefficient equation are adjusted using quasilinearization. The influences of the external reactivity disturbance, the number and frequency of measurements and the measurement noise level on the method accuracy and rate of convergence are analysed through simulation. Procedures for the design of the identification experiments are suggested. The method proved to be very effective for low level noise measurements. (Author) [pt
Determination of appropriate models and parameters for premixing calculations
International Nuclear Information System (INIS)
Park, Ik-Kyu; Kim, Jong-Hwan; Min, Beong-Tae; Hong, Seong-Wan
2008-03-01
The purpose of the present work is to use experiments that have been performed at Forschungszentrum Karlsruhe during about the last ten years for determining the most appropriate models and parameters for premixing calculations. The results of a QUEOS experiment are used to fix the parameters concerning heat transfer. The QUEOS experiments are especially suited for this purpose as they have been performed with small hot solid spheres. Therefore the area of heat exchange is known. With the heat transfer parameters fixed in this way, a PREMIX experiment is recalculated. These experiments have been performed with molten alumina (Al 2 O 3 ) as a simulant of corium. Its initial temperature is 2600 K. With these experiments the models and parameters for jet and drop break-up are tested
Condition Parameter Modeling for Anomaly Detection in Wind Turbines
Directory of Open Access Journals (Sweden)
Yonglong Yan
2014-05-01
Full Text Available Data collected from the supervisory control and data acquisition (SCADA system, used widely in wind farms to obtain operational and condition information about wind turbines (WTs, is of important significance for anomaly detection in wind turbines. The paper presents a novel model for wind turbine anomaly detection mainly based on SCADA data and a back-propagation neural network (BPNN for automatic selection of the condition parameters. The SCADA data sets are determined through analysis of the cumulative probability distribution of wind speed and the relationship between output power and wind speed. The automatic BPNN-based parameter selection is for reduction of redundant parameters for anomaly detection in wind turbines. Through investigation of cases of WT faults, the validity of the automatic parameter selection-based model for WT anomaly detection is verified.
Ground level enhancement (GLE) energy spectrum parameters model
Qin, G.; Wu, S.
2017-12-01
We study the ground level enhancement (GLE) events in solar cycle 23 with the four energy spectra parameters, the normalization parameter C, low-energy power-law slope γ 1, high-energy power-law slope γ 2, and break energy E0, obtained by Mewaldt et al. 2012 who fit the observations to the double power-law equation. we divide the GLEs into two groups, one with strong acceleration by interplanetary (IP) shocks and another one without strong acceleration according to the condition of solar eruptions. We next fit the four parameters with solar event conditions to get models of the parameters for the two groups of GLEs separately. So that we would establish a model of energy spectrum for GLEs for the future space weather prediction.
Directory of Open Access Journals (Sweden)
G. Heuvelmans
2004-01-01
Full Text Available Operational applications of a hydrological model often require the prediction of stream flow in (future time periods without stream flow observations or in ungauged catchments. Data for a case-specific optimisation of model parameters are not available for such applications, so parameters have to be derived from other catchments or time periods. It has been demonstrated that for applications of the SWAT in Northern Belgium, temporal transfers of the parameters have less influence than spatial transfers on the performance of the model. This study examines the spatial variation in parameter optima in more detail. The aim was to delineate zones wherein model parameters can be transferred without a significant loss of model performance. SWAT was calibrated for 25 catchments that are part of eight larger sub-basins of the Scheldt river basin. Two approaches are discussed for grouping these units in zones with a uniform set of parameters: a single parameter approach considering each parameter separately and a parameter set approach evaluating the parameterisation as a whole. For every catchment, the SWAT model was run with the local parameter optima, with the average parameter values for the entire study region (Flanders, with the zones delineated with the single parameter approach and with the zones obtained by the parameter set approach. Comparison of the model performances of these four parameterisation strategies indicates that both the single parameter and the parameter set zones lead to stream flow predictions that are more accurate than if the entire study region were treated as one single zone. On the other hand, the use of zonal average parameter values results in a considerably worse model fit compared to local parameter optima. Clustering of parameter sets gives a more accurate result than the single parameter approach and is, therefore, the preferred technique for use in the parameterisation of ungauged sub-catchments as part of the
Parameters Optimization and Application to Glutamate Fermentation Model Using SVM
Zhang, Xiangsheng; Pan, Feng
2015-01-01
Aimed at the parameters optimization in support vector machine (SVM) for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO) algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effective...
Parameters Optimization and Application to Glutamate Fermentation Model Using SVM
Directory of Open Access Journals (Sweden)
Xiangsheng Zhang
2015-01-01
Full Text Available Aimed at the parameters optimization in support vector machine (SVM for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effectiveness of the proposed algorithm.
Utilising temperature differences as constraints for estimating parameters in a simple climate model
International Nuclear Information System (INIS)
Bodman, Roger W; Karoly, David J; Enting, Ian G
2010-01-01
Simple climate models can be used to estimate the global temperature response to increasing greenhouse gases. Changes in the energy balance of the global climate system are represented by equations that necessitate the use of uncertain parameters. The values of these parameters can be estimated from historical observations, model testing, and tuning to more complex models. Efforts have been made at estimating the possible ranges for these parameters. This study continues this process, but demonstrates two new constraints. Previous studies have shown that land-ocean temperature differences are only weakly correlated with global mean temperature for natural internal climate variations. Hence, these temperature differences provide additional information that can be used to help constrain model parameters. In addition, an ocean heat content ratio can also provide a further constraint. A pulse response technique was used to identify relative parameter sensitivity which confirmed the importance of climate sensitivity and ocean vertical diffusivity, but the land-ocean warming ratio and the land-ocean heat exchange coefficient were also found to be important. Experiments demonstrate the utility of the land-ocean temperature difference and ocean heat content ratio for setting parameter values. This work is based on investigations with MAGICC (Model for the Assessment of Greenhouse-gas Induced Climate Change) as the simple climate model.
Mathematical modelling of a farm enterprise value on the ...
African Journals Online (AJOL)
Mathematical modelling of a farm enterprise value on the agricultural market with the ... Subsidies in the EU countries reached 45-50% of the value of commodity output ... This financing gap entailed a number of negative consequences.
International Nuclear Information System (INIS)
Steinke, R.G.
1997-01-01
Signal-variable values and their component-parameter values differ in an end-of-timestep edit to the TRCOUT and TRCGRF files because signal variables have beginning-of-timestep values, and component parameters have end-of-timestep values. Oscillatory divergence in the MST2 standard test problem after 9000 s occurs because of TRAC-P's numerical evaluation at a 1000 material Courant number. The magnitude of that divergence has diminished by a factor of 3.5 from Version 5.3.01 to 5.4.15 and by a factor of 25 from Version 5.4.15 to 5.4.28. That divergence can be eliminated by evaluating MST2 with a maximum material Courant number of 500
A Bayesian framework for parameter estimation in dynamical models.
Directory of Open Access Journals (Sweden)
Flávio Codeço Coelho
Full Text Available Mathematical models in biology are powerful tools for the study and exploration of complex dynamics. Nevertheless, bringing theoretical results to an agreement with experimental observations involves acknowledging a great deal of uncertainty intrinsic to our theoretical representation of a real system. Proper handling of such uncertainties is key to the successful usage of models to predict experimental or field observations. This problem has been addressed over the years by many tools for model calibration and parameter estimation. In this article we present a general framework for uncertainty analysis and parameter estimation that is designed to handle uncertainties associated with the modeling of dynamic biological systems while remaining agnostic as to the type of model used. We apply the framework to fit an SIR-like influenza transmission model to 7 years of incidence data in three European countries: Belgium, the Netherlands and Portugal.
A lumped parameter, low dimension model of heat exchanger
International Nuclear Information System (INIS)
Kanoh, Hideaki; Furushoo, Junji; Masubuchi, Masami
1980-01-01
This paper reports on the results of investigation of the distributed parameter model, the difference model, and the model of the method of weighted residuals for heat exchangers. By the method of weighted residuals (MWR), the opposite flow heat exchanger system is approximated by low dimension, lumped parameter model. By assuming constant specific heat, constant density, the same form of tube cross-section, the same form of the surface of heat exchange, uniform flow velocity, the linear relation of heat transfer to flow velocity, liquid heat carrier, and the thermal insulation of liquid from outside, fundamental equations are obtained. The experimental apparatus was made of acrylic resin. The response of the temperature at the exit of first liquid to the variation of the flow rate of second liquid was measured and compared with the models. The MWR model shows good approximation for the low frequency region, and as the number of division increases, good approximation spreads to higher frequency region. (Kato, T.)
Ramadan, Ahmed; Boss, Connor; Choi, Jongeun; Peter Reeves, N; Cholewicki, Jacek; Popovich, John M; Radcliffe, Clark J
2018-07-01
Estimating many parameters of biomechanical systems with limited data may achieve good fit but may also increase 95% confidence intervals in parameter estimates. This results in poor identifiability in the estimation problem. Therefore, we propose a novel method to select sensitive biomechanical model parameters that should be estimated, while fixing the remaining parameters to values obtained from preliminary estimation. Our method relies on identifying the parameters to which the measurement output is most sensitive. The proposed method is based on the Fisher information matrix (FIM). It was compared against the nonlinear least absolute shrinkage and selection operator (LASSO) method to guide modelers on the pros and cons of our FIM method. We present an application identifying a biomechanical parametric model of a head position-tracking task for ten human subjects. Using measured data, our method (1) reduced model complexity by only requiring five out of twelve parameters to be estimated, (2) significantly reduced parameter 95% confidence intervals by up to 89% of the original confidence interval, (3) maintained goodness of fit measured by variance accounted for (VAF) at 82%, (4) reduced computation time, where our FIM method was 164 times faster than the LASSO method, and (5) selected similar sensitive parameters to the LASSO method, where three out of five selected sensitive parameters were shared by FIM and LASSO methods.
Entropy Parameter M in Modeling a Flow Duration Curve
Directory of Open Access Journals (Sweden)
Yu Zhang
2017-12-01
Full Text Available A flow duration curve (FDC is widely used for predicting water supply, hydropower, environmental flow, sediment load, and pollutant load. Among different methods of constructing an FDC, the entropy-based method, developed recently, is appealing because of its several desirable characteristics, such as simplicity, flexibility, and statistical basis. This method contains a parameter, called entropy parameter M, which constitutes the basis for constructing the FDC. Since M is related to the ratio of the average streamflow to the maximum streamflow which, in turn, is related to the drainage area, it may be possible to determine M a priori and construct an FDC for ungauged basins. This paper, therefore, analyzed the characteristics of M in both space and time using streamflow data from 73 gauging stations in the Brazos River basin, Texas, USA. Results showed that the M values were impacted by reservoir operation and possibly climate change. The values were fluctuating, but relatively stable, after the operation of the reservoirs. Parameter M was found to change inversely with the ratio of average streamflow to the maximum streamflow. When there was an extreme event, there occurred a jump in the M value. Further, spatially, M had a larger value if the drainage area was small.
distributed parameter model of spiral-wound sepralator for treatment of uranyl nitrate effluents
International Nuclear Information System (INIS)
El-Bialy, S.H; Elsherbiny, A.E.
2004-01-01
in this paper, mathematical formulation of spiral-wound sepralator was derived and applied for the treatment of effluent stream which is produced during nuclear fuel processing stage. the concentration of the stream has a value up to 200 ppm . cross-flow characteristic of both feed and permeate streams was taken into account and their mutual effects on the values of system variables were investigated. of course, such a flow pattern leads to a heterogeneous system which leads-in turn-to six partial differential equations, beside a set of algebraic equations. those were solved numerically and the results were used to estimate the average values of both permeate flux and percent solute rejection. then, these were compared with both experimental data in addition to the results of lumped parameter model. the study showed that distributed parameter model gives better results than lumped parameter one compared with experimental data
Reservoir theory, groundwater transit time distributions, and lumped parameter models
International Nuclear Information System (INIS)
Etcheverry, D.; Perrochet, P.
1999-01-01
The relation between groundwater residence times and transit times is given by the reservoir theory. It allows to calculate theoretical transit time distributions in a deterministic way, analytically, or on numerical models. Two analytical solutions validates the piston flow and the exponential model for simple conceptual flow systems. A numerical solution of a hypothetical regional groundwater flow shows that lumped parameter models could be applied in some cases to large-scale, heterogeneous aquifers. (author)
Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes
Guerrero, José-Luis; Pernica, Patricia; Wheater, Howard; Mackay, Murray; Spence, Chris
2017-12-01
Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere - heat-exchange fluxes - is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue - different parameter-value combinations yielding equivalent results - the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.
Parameter sensitivity and uncertainty of the forest carbon flux model FORUG : a Monte Carlo analysis
Energy Technology Data Exchange (ETDEWEB)
Verbeeck, H.; Samson, R.; Lemeur, R. [Ghent Univ., Ghent (Belgium). Laboratory of Plant Ecology; Verdonck, F. [Ghent Univ., Ghent (Belgium). Dept. of Applied Mathematics, Biometrics and Process Control
2006-06-15
The FORUG model is a multi-layer process-based model that simulates carbon dioxide (CO{sub 2}) and water exchange between forest stands and the atmosphere. The main model outputs are net ecosystem exchange (NEE), total ecosystem respiration (TER), gross primary production (GPP) and evapotranspiration. This study used a sensitivity analysis to identify the parameters contributing to NEE uncertainty in the FORUG model. The aim was to determine if it is necessary to estimate the uncertainty of all parameters of a model to determine overall output uncertainty. Data used in the study were the meteorological and flux data of beech trees in Hesse. The Monte Carlo method was used to rank sensitivity and uncertainty parameters in combination with a multiple linear regression. Simulations were run in which parameters were assigned probability distributions and the effect of variance in the parameters on the output distribution was assessed. The uncertainty of the output for NEE was estimated. Based on the arbitrary uncertainty of 10 key parameters, a standard deviation of 0.88 Mg C per year per NEE was found, which was equal to 24 per cent of the mean value of NEE. The sensitivity analysis showed that the overall output uncertainty of the FORUG model could be determined by accounting for only a few key parameters, which were identified as corresponding to critical parameters in the literature. It was concluded that the 10 most important parameters determined more than 90 per cent of the output uncertainty. High ranking parameters included soil respiration; photosynthesis; and crown architecture. It was concluded that the Monte Carlo technique is a useful tool for ranking the uncertainty of parameters of process-based forest flux models. 48 refs., 2 tabs., 2 figs.
DEFF Research Database (Denmark)
Christensen, Steen; Doherty, John
2008-01-01
A significant practical problem with the pilot point method is to choose the location of the pilot points. We present a method that is intended to relieve the modeler from much of this responsibility. The basic idea is that a very large number of pilot points are distributed more or less uniformly...... over the model area. Singular value decomposition (SVD) of the (possibly weighted) sensitivity matrix of the pilot point based model produces eigenvectors of which we pick a small number corresponding to significant eigenvalues. Super parameters are defined as factors through which parameter...... combinations corresponding to the chosen eigenvectors are multiplied to obtain the pilot point values. The model can thus be transformed from having many-pilot-point parameters to having a few super parameters that can be estimated by nonlinear regression on the basis of the available observations. (This...
Directory of Open Access Journals (Sweden)
Carlos Alberto Castro
2010-12-01
comportamento melhor de modelo.Time series models are quantitative techniques commonly used to forecast the behavior of variables. These models include the exponential smoothing with trend or Holt model that requires the definition of the smoothing constants α and β and the initialization values, both required for the model upgrade. This paper proposes a different way to obtain the parameter values and initial conditions of the Holts model, optimizing the tracking signal range (TSR, in order to achieve a more robust model from the viewpoint of accuracy of the results and historical performance. Some comparisons between the proposed approach and the traditional methods based on the mean absolute deviation (MAD and the mean square error (MSE are provided. These are the measures traditionally used to determine the degree of accuracy of a model, and a better model performance is obtained.
International Nuclear Information System (INIS)
Artemov, V.G.; Gusev, V.I.; Zinatullin, R.E.; Karpov, A.S.
2007-01-01
Using modeled WWER cram rod drop experiments, performed at the Rostov NPP, as an example, the influence of delayed neutron parameters on the modeling results was investigated. The delayed neutron parameter values were taken from both domestic and foreign nuclear databases. Numerical modeling was carried out on the basis of SAPFIR 9 5andWWERrogram package. Parameters of delayed neutrons were acquired from ENDF/B-VI and BNAB-78 validated data files. It was demonstrated that using delay fraction data from different databases in reactivity meters led to significantly different reactivity results. Based on the results of numerically modeled experiments, delayed neutron parameters providing the best agreement between calculated and measured data were selected and recommended for use in reactor calculations (Authors)
Wintoft, Peter; Wik, Magnus; Matzka, Jürgen; Shprits, Yuri
2017-11-01
We have developed neural network models that predict Kp from upstream solar wind data. We study the importance of various input parameters, starting with the magnetic component Bz, particle density n, and velocity V and then adding total field B and the By component. As we also notice a seasonal and UT variation in average Kp we include functions of day-of-year and UT. Finally, as Kp is a global representation of the maximum range of geomagnetic variation over 3-hour UT intervals we conclude that sudden changes in the solar wind can have a big effect on Kp, even though it is a 3-hour value. Therefore, 3-hour solar wind averages will not always appropriately represent the solar wind condition, and we introduce 3-hour maxima and minima values to some degree address this problem. We find that introducing total field B and 3-hour maxima and minima, derived from 1-minute solar wind data, have a great influence on the performance. Due to the low number of samples for high Kp values there can be considerable variation in predicted Kp for different networks with similar validation errors. We address this issue by using an ensemble of networks from which we use the median predicted Kp. The models (ensemble of networks) provide prediction lead times in the range 20-90 min given by the time it takes a solar wind structure to travel from L1 to Earth. Two models are implemented that can be run with real time data: (1) IRF-Kp-2017-h3 uses the 3-hour averages of the solar wind data and (2) IRF-Kp-2017 uses in addition to the averages, also the minima and maxima values. The IRF-Kp-2017 model has RMS error of 0.55 and linear correlation of 0.92 based on an independent test set with final Kp covering 2 years using ACE Level 2 data. The IRF-Kp-2017-h3 model has RMSE = 0.63 and correlation = 0.89. We also explore the errors when tested on another two-year period with real-time ACE data which gives RMSE = 0.59 for IRF-Kp-2017 and RMSE = 0.73 for IRF-Kp-2017-h3. The errors as function
SPOTting model parameters using a ready-made Python package
Houska, Tobias; Kraft, Philipp; Breuer, Lutz
2015-04-01
The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for
Application of isotopic information for estimating parameters in Philip infiltration model
Directory of Open Access Journals (Sweden)
Tao Wang
2016-10-01
Full Text Available Minimizing parameter uncertainty is crucial in the application of hydrologic models. Isotopic information in various hydrologic components of the water cycle can expand our knowledge of the dynamics of water flow in the system, provide additional information for parameter estimation, and improve parameter identifiability. This study combined the Philip infiltration model with an isotopic mixing model using an isotopic mass balance approach for estimating parameters in the Philip infiltration model. Two approaches to parameter estimation were compared: (a using isotopic information to determine the soil water transmission and then hydrologic information to estimate the soil sorptivity, and (b using hydrologic information to determine the soil water transmission and the soil sorptivity. Results of parameter estimation were verified through a rainfall infiltration experiment in a laboratory under rainfall with constant isotopic compositions and uniform initial soil water content conditions. Experimental results showed that approach (a, using isotopic and hydrologic information, estimated the soil water transmission in the Philip infiltration model in a manner that matched measured values well. The results of parameter estimation of approach (a were better than those of approach (b. It was also found that the analytical precision of hydrogen and oxygen stable isotopes had a significant effect on parameter estimation using isotopic information.
Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms
Berhausen, Sebastian; Paszek, Stefan
2016-01-01
In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.
Utama, D. N.; Ani, N.; Iqbal, M. M.
2018-03-01
Optimization is a process for finding parameter (parameters) that is (are) able to deliver an optimal value for an objective function. Seeking an optimal generic model for optimizing is a computer science study that has been being practically conducted by numerous researchers. Generic model is a model that can be technically operated to solve any varieties of optimization problem. By using an object-oriented method, the generic model for optimizing was constructed. Moreover, two types of optimization method, simulated-annealing and hill-climbing, were functioned in constructing the model and compared to find the most optimal one then. The result said that both methods gave the same result for a value of objective function and the hill-climbing based model consumed the shortest running time.
International Nuclear Information System (INIS)
Butcher, B.M.
1997-08-01
A summary of the input parameter values used in final predictions of closure and waste densification in the Waste Isolation Pilot Plant disposal room is presented, along with supporting references. These predictions are referred to as the final porosity surface data and will be used for WIPP performance calculations supporting the Compliance Certification Application to be submitted to the U.S. Environmental Protection Agency. The report includes tables and list all of the input parameter values, references citing their source, and in some cases references to more complete descriptions of considerations leading to the selection of values
Energy Technology Data Exchange (ETDEWEB)
Butcher, B.M.
1997-08-01
A summary of the input parameter values used in final predictions of closure and waste densification in the Waste Isolation Pilot Plant disposal room is presented, along with supporting references. These predictions are referred to as the final porosity surface data and will be used for WIPP performance calculations supporting the Compliance Certification Application to be submitted to the U.S. Environmental Protection Agency. The report includes tables and list all of the input parameter values, references citing their source, and in some cases references to more complete descriptions of considerations leading to the selection of values.
Value Chain Model for Steel Manufacturing Sector: A Case Study
S G Acharyulu; K Venkata Subbaiah; K Narayana Rao
2018-01-01
Michael E Porter developed a value chain model for manufacturing sector with five primary activities and four supporting activities. The value chain model developed by Porter is extended to a steel manufacturing sector due to expansions of steel plants has become a continual process for their growth and survival. In this paper a value chain model for steel manufacturing sector is developed considering five primary activities and six support activities.
A compact cyclic plasticity model with parameter evolution
DEFF Research Database (Denmark)
Krenk, Steen; Tidemann, L.
2017-01-01
The paper presents a compact model for cyclic plasticity based on energy in terms of external and internal variables, and plastic yielding described by kinematic hardening and a flow potential with an additive term controlling the nonlinear cyclic hardening. The model is basically described by five...... parameters: external and internal stiffness, a yield stress and a limiting ultimate stress, and finally a parameter controlling the gradual development of plastic deformation. Calibration against numerous experimental results indicates that typically larger plastic strains develop than predicted...
Derivation of potential model for LiAlO2 by simple and effective optimization of model parameters
International Nuclear Information System (INIS)
Tsuchihira, H.; Oda, T.; Tanaka, S.
2009-01-01
Interatomic potentials of LiAlO 2 were constructed by a simple and effective method. In this method, the model function consists of multiple inverse polynomial functions with an exponential truncation function, and parameters in the potential model can be optimized as a solution of simultaneous linear equations. Potential energies obtained by ab initio calculation are used as fitting targets for model parameter optimization. Lattice constants, elastic properties, defect-formation energy, thermal expansions and the melting point were calculated under the constructed potential models. The results showed good agreement with experimental values and ab initio calculation results, which underscores the validity of the presented method.
Influence of parameters and light e vironment under the canopy on the fuel moisture estimation model
International Nuclear Information System (INIS)
Tamai, K.; Goto, Y.
2006-01-01
Model parameterization was performed for estimation of the fuel moisture in adjacent plots with different tree species aiming at the mapping of forest fire hazard. One plot was covered with only deciduous species and the other with deciduous and evergreen trees. This model has our constant parameters. Three of them are for the relationship between evaporation and solar radiation. Another parameter is the maximum water content ratio of the litter. All of these parameters depend on the intrinsic drying properties of the litter. The water content ratio of the litter and solar radiation on the forest floor were measured in ach plot for one year. Parameters were fixed with the measured data. Though the parameter values were very different between the two plots, estimated moisture ratios were not so different. It was concluded that litter moisture depends on the microclimate, such as solar radiation, rather than on the intrinsic drying properties of the litter and litter layer
Global parameter estimation for thermodynamic models of transcriptional regulation.
Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N
2013-07-15
Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Gopinath, A.; Puhan, Sukumar; Nagarajan, G. [Internal Combustion Engineering Division, Department of Mechanical Engineering, Anna University, Chennai 600 025, Tamil Nadu (India)
2009-07-15
Biodiesel is an alternative fuel consisting of alkyl esters of fatty acids from vegetable oils or animal fats. The properties of biodiesel depend on the type of vegetable oil used for the transesterification process. The objective of the present work is to theoretically predict the iodine value and the saponification value of different biodiesels from their fatty acid methyl ester composition. The fatty acid ester compositions and the above values of different biodiesels were taken from the available published data. A multiple linear regression model was developed to predict the iodine value and saponification value of different biodiesels. The predicted results showed that the prediction errors were less than 3.4% compared to the available published data. The predicted values were also verified by substituting in the available published model which was developed to predict the higher heating values of biodiesel fuels from their iodine value and the saponification value. The resulting heating values of biodiesels were then compared with the published heating values and reported. (author)
Combustion Model and Control Parameter Optimization Methods for Single Cylinder Diesel Engine
Directory of Open Access Journals (Sweden)
Bambang Wahono
2014-01-01
Full Text Available This research presents a method to construct a combustion model and a method to optimize some control parameters of diesel engine in order to develop a model-based control system. The construction purpose of the model is to appropriately manage some control parameters to obtain the values of fuel consumption and emission as the engine output objectives. Stepwise method considering multicollinearity was applied to construct combustion model with the polynomial model. Using the experimental data of a single cylinder diesel engine, the model of power, BSFC, NOx, and soot on multiple injection diesel engines was built. The proposed method succesfully developed the model that describes control parameters in relation to the engine outputs. Although many control devices can be mounted to diesel engine, optimization technique is required to utilize this method in finding optimal engine operating conditions efficiently beside the existing development of individual emission control methods. Particle swarm optimization (PSO was used to calculate control parameters to optimize fuel consumption and emission based on the model. The proposed method is able to calculate control parameters efficiently to optimize evaluation item based on the model. Finally, the model which added PSO then was compiled in a microcontroller.
International Nuclear Information System (INIS)
Barroso, D.E.G.
1982-01-01
A sensitivity analysis of reactor integral parameter to more 10% variation in the resolved resonance parameters #betta##betta# of the fertile isotope and the variations of more 10% in the α values (#betta# sub(#betta#)/#betta# sub(f)) of fissile isotopes of PWR fuel elements, is done. The analysis is made with thermal and epithermal spectra, those last generated in a fuel cell with low V sub(M)/V sub(F). The HAMMER system, the interface programs HELP and LITHE and the HAMMER computer codes, were used as a base for this study. (E.G.) [pt
MODELLING BIOPHYSICAL PARAMETERS OF MAIZE USING LANDSAT 8 TIME SERIES
Directory of Open Access Journals (Sweden)
T. Dahms
2016-06-01
Full Text Available Open and free access to multi-frequent high-resolution data (e.g. Sentinel – 2 will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR, the leaf area index (LAI and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD: R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing
Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series
Dahms, Thorsten; Seissiger, Sylvia; Conrad, Christopher; Borg, Erik
2016-06-01
Open and free access to multi-frequent high-resolution data (e.g. Sentinel - 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model
Estimation of value at risk and conditional value at risk using normal mixture distributions model
Kamaruzzaman, Zetty Ain; Isa, Zaidi
2013-04-01
Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.
X-Parameter Based Modelling of Polar Modulated Power Amplifiers
DEFF Research Database (Denmark)
Wang, Yelin; Nielsen, Troels Studsgaard; Sira, Daniel
2013-01-01
X-parameters are developed as an extension of S-parameters capable of modelling non-linear devices driven by large signals. They are suitable for devices having only radio frequency (RF) and DC ports. In a polar power amplifier (PA), phase and envelope of the input modulated signal are applied...... at separate ports and the envelope port is neither an RF nor a DC port. As a result, X-parameters may fail to characterise the effect of the envelope port excitation and consequently the polar PA. This study introduces a solution to the problem for a commercial polar PA. In this solution, the RF-phase path...... PA for simulations. The simulated error vector magnitude (EVM) and adjacent channel power ratio (ACPR) were compared with the measured data to validate the model. The maximum differences between the simulated and measured EVM and ACPR are less than 2% point and 3 dB, respectively....
Identifiability and error minimization of receptor model parameters with PET
International Nuclear Information System (INIS)
Delforge, J.; Syrota, A.; Mazoyer, B.M.
1989-01-01
The identifiability problem and the general framework for experimental design optimization are presented. The methodology is applied to the problem of the receptor-ligand model parameter estimation with dynamic positron emission tomography data. The first attempts to identify the model parameters from data obtained with a single tracer injection led to disappointing numerical results. The possibility of improving parameter estimation using a new experimental design combining an injection of the labelled ligand and an injection of the cold ligand (displacement experiment) has been investigated. However, this second protocol led to two very different numerical solutions and it was necessary to demonstrate which solution was biologically valid. This has been possible by using a third protocol including both a displacement and a co-injection experiment. (authors). 16 refs.; 14 figs
Mathematical models to predict rheological parameters of lateritic hydromixtures
Directory of Open Access Journals (Sweden)
Gabriel Hernández-Ramírez
2017-10-01
Full Text Available The present work had as objective to establish mathematical models that allow the prognosis of the rheological parameters of the lateritic pulp at concentrations of solids from 35% to 48%, temperature of the preheated hydromixture superior to 82 ° C and number of mineral between 3 and 16. Four samples of lateritic pulp were used in the study at different process locations. The results allowed defining that the plastic properties of the lateritic pulp in the conditions of this study conform to the Herschel-Bulkley model for real plastics. In addition, they show that for current operating conditions, even for new situations, UPD mathematical models have a greater ability to predict rheological parameters than least squares mathematical models.
Averaging models: parameters estimation with the R-Average procedure
Directory of Open Access Journals (Sweden)
S. Noventa
2010-01-01
Full Text Available The Functional Measurement approach, proposed within the theoretical framework of Information Integration Theory (Anderson, 1981, 1982, can be a useful multi-attribute analysis tool. Compared to the majority of statistical models, the averaging model can account for interaction effects without adding complexity. The R-Average method (Vidotto & Vicentini, 2007 can be used to estimate the parameters of these models. By the use of multiple information criteria in the model selection procedure, R-Average allows for the identification of the best subset of parameters that account for the data. After a review of the general method, we present an implementation of the procedure in the framework of R-project, followed by some experiments using a Monte Carlo method.
Albert, Carlo; Ulzega, Simone; Stoop, Ruedi
2016-04-01
Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In many situations, the dominant sources of uncertainty must be included into the model for making reliable predictions. This naturally leads to stochastic models. Stochastic models render parameter inference much harder, as the aim then is to find a distribution of likely parameter values. In Bayesian statistics, which is a consistent framework for data-driven learning, this so-called posterior distribution can be used to make probabilistic predictions. We propose a novel, exact, and very efficient approach for generating posterior parameter distributions for stochastic differential equation models calibrated to measured time series. The algorithm is inspired by reinterpreting the posterior distribution as a statistical mechanics partition function of an object akin to a polymer, where the measurements are mapped on heavier beads compared to those of the simulated data. To arrive at distribution samples, we employ a Hamiltonian Monte Carlo approach combined with a multiple time-scale integration. A separation of time scales naturally arises if either the number of measurement points or the number of simulation points becomes large. Furthermore, at least for one-dimensional problems, we can decouple the harmonic modes between measurement points and solve the fastest part of their dynamics analytically. Our approach is applicable to a wide range of inference problems and is highly parallelizable.
Failure analysis of parameter-induced simulation crashes in climate models
Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.
2013-08-01
Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.
Analysis report for WIPP colloid model constraints and performance assessment parameters
Energy Technology Data Exchange (ETDEWEB)
Mariner, Paul E.; Sassani, David Carl
2014-03-01
An analysis of the Waste Isolation Pilot Plant (WIPP) colloid model constraints and parameter values was performed. The focus of this work was primarily on intrinsic colloids, mineral fragment colloids, and humic substance colloids, with a lesser focus on microbial colloids. Comments by the US Environmental Protection Agency (EPA) concerning intrinsic Th(IV) colloids and Mg-Cl-OH mineral fragment colloids were addressed in detail, assumptions and data used to constrain colloid model calculations were evaluated, and inconsistencies between data and model parameter values were identified. This work resulted in a list of specific conclusions regarding model integrity, model conservatism, and opportunities for improvement related to each of the four colloid types included in the WIPP performance assessment.
Comparisons of criteria in the assessment model parameter optimizations
International Nuclear Information System (INIS)
Liu Xinhe; Zhang Yongxing
1993-01-01
Three criteria (chi square, relative chi square and correlation coefficient) used in model parameter optimization (MPO) process that aims at significant reduction of prediction uncertainties were discussed and compared to each other with the aid of a well-controlled tracer experiment
Revised models and genetic parameter estimates for production and ...
African Journals Online (AJOL)
Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the ...
Determination of parameters in elasto-plastic models of aluminium.
Meuwissen, M.H.H.; Oomens, C.W.J.; Baaijens, F.P.T.; Petterson, R.; Janssen, J.D.; Sol, H.; Oomens, C.W.J.
1997-01-01
A mixed numerical-experimental method is used to determine parameters in elasto-plastic constitutive models. An aluminium plate of non-standard geometry is mounted in a uniaxial tensile testing machine at which some adjustments are made to carry out shear tests. The sample is loaded and the total
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
2002-01-01
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of non-linear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
response during excitation and the geometrical damping related to free vibrations of a hexagonal footing. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal and vertical translation as well as torsion and rocking. In particular, the necessity of coupling...... between horizontal sliding and rocking is discussed....
Key processes and input parameters for environmental tritium models
International Nuclear Information System (INIS)
Bunnenberg, C.; Taschner, M.; Ogram, G.L.
1994-01-01
The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs
Key processes and input parameters for environmental tritium models
Energy Technology Data Exchange (ETDEWEB)
Bunnenberg, C; Taschner, M [Niedersaechsisches Inst. fuer Radiooekologie, Hannover (Germany); Ogram, G L [Ontario Hydro, Toronto, ON (Canada)
1994-12-31
The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs.
Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle
Directory of Open Access Journals (Sweden)
Bambang Wahono
2015-07-01
Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.
Parameter identification of ZnO surge arrester models based on genetic algorithms
Energy Technology Data Exchange (ETDEWEB)
Bayadi, Abdelhafid [Laboratoire d' Automatique de Setif, Departement d' Electrotechnique, Faculte des Sciences de l' Ingenieur, Universite Ferhat ABBAS de Setif, Route de Bejaia Setif 19000 (Algeria)
2008-07-15
The correct and adequate modelling of ZnO surge arresters characteristics is very important for insulation coordination studies and systems reliability. In this context many researchers addressed considerable efforts to the development of surge arresters models to reproduce the dynamic characteristics observed in their behaviour when subjected to fast front impulse currents. The difficulties with these models reside essentially in the calculation and the adjustment of their parameters. This paper proposes a new technique based on genetic algorithm to obtain the best possible series of parameter values of ZnO surge arresters models. The validity of the predicted parameters is then checked by comparing the predicted results with the experimental results available in the literature. Using the ATP-EMTP package, an application of the arrester model on network system studies is presented and discussed. (author)
Integrating microbial diversity in soil carbon dynamic models parameters
Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie
2015-04-01
Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten
Luo, Rutao; Piovoso, Michael J.; Martinez-Picado, Javier; Zurakowski, Ryan
2012-01-01
Mathematical models based on ordinary differential equations (ODE) have had significant impact on understanding HIV disease dynamics and optimizing patient treatment. A model that characterizes the essential disease dynamics can be used for prediction only if the model parameters are identifiable from clinical data. Most previous parameter identification studies for HIV have used sparsely sampled data from the decay phase following the introduction of therapy. In this paper, model parameters are identified from frequently sampled viral-load data taken from ten patients enrolled in the previously published AutoVac HAART interruption study, providing between 69 and 114 viral load measurements from 3–5 phases of viral decay and rebound for each patient. This dataset is considerably larger than those used in previously published parameter estimation studies. Furthermore, the measurements come from two separate experimental conditions, which allows for the direct estimation of drug efficacy and reservoir contribution rates, two parameters that cannot be identified from decay-phase data alone. A Markov-Chain Monte-Carlo method is used to estimate the model parameter values, with initial estimates obtained using nonlinear least-squares methods. The posterior distributions of the parameter estimates are reported and compared for all patients. PMID:22815727
The sensitivity of flowline models of tidewater glaciers to parameter uncertainty
Directory of Open Access Journals (Sweden)
E. M. Enderlin
2013-10-01
Full Text Available Depth-integrated (1-D flowline models have been widely used to simulate fast-flowing tidewater glaciers and predict change because the continuous grounding line tracking, high horizontal resolution, and physically based calving criterion that are essential to realistic modeling of tidewater glaciers can easily be incorporated into the models while maintaining high computational efficiency. As with all models, the values for parameters describing ice rheology and basal friction must be assumed and/or tuned based on observations. For prognostic studies, these parameters are typically tuned so that the glacier matches observed thickness and speeds at an initial state, to which a perturbation is applied. While it is well know that ice flow models are sensitive to these parameters, the sensitivity of tidewater glacier models has not been systematically investigated. Here we investigate the sensitivity of such flowline models of outlet glacier dynamics to uncertainty in three key parameters that influence a glacier's resistive stress components. We find that, within typical observational uncertainty, similar initial (i.e., steady-state glacier configurations can be produced with substantially different combinations of parameter values, leading to differing transient responses after a perturbation is applied. In cases where the glacier is initially grounded near flotation across a basal over-deepening, as typically observed for rapidly changing glaciers, these differences can be dramatic owing to the threshold of stability imposed by the flotation criterion. The simulated transient response is particularly sensitive to the parameterization of ice rheology: differences in ice temperature of ~ 2 °C can determine whether the glaciers thin to flotation and retreat unstably or remain grounded on a marine shoal. Due to the highly non-linear dependence of tidewater glaciers on model parameters, we recommend that their predictions are accompanied by
Agricultural and Environmental Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rasmuson; K. Rautenstrauch
2004-09-14
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.
Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model
Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr
2017-10-01
Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations
Directory of Open Access Journals (Sweden)
Rudiati Evi Masithoh
2013-03-01
Full Text Available Artificial neural networks (ANN was used to predict the quality parameters of tomato, i.e. Brix, citric acid, total carotene, and vitamin C. ANN was developed from Red Green Blue (RGB image data of tomatoes measured using a developed computer vision system (CVS. Qualitative analysis of tomato compositions were obtained from laboratory experiments. ANN model was based on a feedforward backpropagation network with different training functions, namely gradient descent (traingd, gradient descent with the resilient backpropagation (trainrp, Broyden, Fletcher, Goldfrab and Shanno (BFGS quasi-Newton (trainbfg, as well as Levenberg Marquardt (trainlm. The network structure using logsig and linear (purelin activation function at the hidden and output layer, respectively, and using the trainlm as a training function resulted in the best performance. Correlation coefficient (r of training and validation process were 0.97 - 0.99 and 0.92 - 0.99, whereas the MAE values ranged from 0.01 to 0.23 and 0.03 to 0.59, respectively. Keywords: Artificial neural network, trainlm, tomato, RGB Jaringan syaraf tiruan (JST digunakan untuk memprediksi parameter kualitas tomat, yaitu Brix, asam sitrat, karoten total, dan vitamin C. JST dikembangkan dari data Red Green Blue (RGB citra tomat yang diukur menggunakan computer vision system. Data kualitas tomat diperoleh dari analisis di laboratorium. Struktur model JST didasarkan pada jaringan feedforward backpropagation dengan berbagai fungsi pelatihan, yaitu gradient descent (traingd, gradient descent dengan resilient backpropagation (trainrp, Broyden, Fletcher, Goldfrab dan Shanno (BFGS quasi-Newton (trainbfg, serta Levenberg Marquardt (trainlm. Fungsi pelatihan yang terbaik adalah menggunakan trainlm, serta pada struktur jaringan digunakan fungsi aktivasi logsig pada lapisan tersembunyi dan linier (purelin pada lapisan keluaran. dengan 1000 epoch. Nilai koefisien korelasi (r pada tahap pelatihan dan validasi
Study on Identification of Material Model Parameters from Compact Tension Test on Concrete Specimens
Hokes, Filip; Kral, Petr; Husek, Martin; Kala, Jiri
2017-10-01
Identification of a concrete material model parameters using optimization is based on a calculation of a difference between experimentally measured and numerically obtained data. Measure of the difference can be formulated via root mean squared error that is often used for determination of accuracy of a mathematical model in the field of meteorology or demography. The quality of the identified parameters is, however, determined not only by right choice of an objective function but also by the source experimental data. One of the possible way is to use load-displacement curves from three-point bending tests that were performed on concrete specimens. This option shows the significance of modulus of elasticity, tensile strength and specific fracture energy. Another possible option is to use experimental data from compact tension test. It is clear that the response in the second type of test is also dependent on the above mentioned material parameters. The question is whether the parameters identified within three-point bending test and within compact tension test will reach the same values. The presented article brings the numerical study of inverse identification of material model parameters from experimental data measured during compact tension tests. The article also presents utilization of the modified sensitivity analysis that calculates the sensitivity of the material model parameters for different parts of loading curve. The main goal of the article is to describe the process of inverse identification of parameters for plasticity-based material model of concrete and prepare data for future comparison with identified values of the material model parameters from different type of fracture tests.
Using a scalar parameter to trace dislocation evolution in atomistic modeling
Energy Technology Data Exchange (ETDEWEB)
Yang, Jinbo [ORNL; Zhang, Z F [Shenyang National Laboratory for Materials Science; Osetskiy, Yury N [ORNL; Stoller, Roger E [ORNL
2015-01-01
A scalar gamma-parameter is proposed from the Nye tensor. Its maximum value occurs along a dislocation line, either straight or curved, when the coordinate system is purposely chosen. This parameter can be easily obtained from the Nye tensor calculated at each atom in atomistic modeling. Using the gamma-parameter, a fully automated approach is developed to determine core atoms and the Burgers vectors of dislocations simultaneously. The approach is validated by revealing the smallest dislocation loop and by tracing the whole formation process of complicated dislocation networks on the fly.
Saputro, D. R. S.; Amalia, F.; Widyaningsih, P.; Affan, R. C.
2018-05-01
Bayesian method is a method that can be used to estimate the parameters of multivariate multiple regression model. Bayesian method has two distributions, there are prior and posterior distributions. Posterior distribution is influenced by the selection of prior distribution. Jeffreys’ prior distribution is a kind of Non-informative prior distribution. This prior is used when the information about parameter not available. Non-informative Jeffreys’ prior distribution is combined with the sample information resulting the posterior distribution. Posterior distribution is used to estimate the parameter. The purposes of this research is to estimate the parameters of multivariate regression model using Bayesian method with Non-informative Jeffreys’ prior distribution. Based on the results and discussion, parameter estimation of β and Σ which were obtained from expected value of random variable of marginal posterior distribution function. The marginal posterior distributions for β and Σ are multivariate normal and inverse Wishart. However, in calculation of the expected value involving integral of a function which difficult to determine the value. Therefore, approach is needed by generating of random samples according to the posterior distribution characteristics of each parameter using Markov chain Monte Carlo (MCMC) Gibbs sampling algorithm.
Simulating WTP Values from Random-Coefficient Models
Maurus Rischatsch
2009-01-01
Discrete Choice Experiments (DCEs) designed to estimate willingness-to-pay (WTP) values are very popular in health economics. With increased computation power and advanced simulation techniques, random-coefficient models have gained an increasing importance in applied work as they allow for taste heterogeneity. This paper discusses the parametrical derivation of WTP values from estimated random-coefficient models and shows how these values can be simulated in cases where they do not have a kn...
A modified Leslie-Gower predator-prey interaction model and parameter identifiability
Tripathi, Jai Prakash; Meghwani, Suraj S.; Thakur, Manoj; Abbas, Syed
2018-01-01
In this work, bifurcation and a systematic approach for estimation of identifiable parameters of a modified Leslie-Gower predator-prey system with Crowley-Martin functional response and prey refuge is discussed. Global asymptotic stability is discussed by applying fluctuation lemma. The system undergoes into Hopf bifurcation with respect to parameters intrinsic growth rate of predators (s) and prey reserve (m). The stability of Hopf bifurcation is also discussed by calculating Lyapunov number. The sensitivity analysis of the considered model system with respect to all variables is performed which also supports our theoretical study. To estimate the unknown parameter from the data, an optimization procedure (pseudo-random search algorithm) is adopted. System responses and phase plots for estimated parameters are also compared with true noise free data. It is found that the system dynamics with true set of parametric values is similar to the estimated parametric values. Numerical simulations are presented to substantiate the analytical findings.
Mass balance model parameter transferability on a tropical glacier
Gurgiser, Wolfgang; Mölg, Thomas; Nicholson, Lindsey; Kaser, Georg
2013-04-01
The mass balance and melt water production of glaciers is of particular interest in the Peruvian Andes where glacier melt water has markedly increased water supply during the pronounced dry seasons in recent decades. However, the melt water contribution from glaciers is projected to decrease with appreciable negative impacts on the local society within the coming decades. Understanding mass balance processes on tropical glaciers is a prerequisite for modeling present and future glacier runoff. As a first step towards this aim we applied a process-based surface mass balance model in order to calculate observed ablation at two stakes in the ablation zone of Shallap Glacier (4800 m a.s.l., 9°S) in the Cordillera Blanca, Peru. Under the tropical climate, the snow line migrates very frequently across most of the ablation zone all year round causing large temporal and spatial variations of glacier surface conditions and related ablation. Consequently, pronounced differences between the two chosen stakes and the two years were observed. Hourly records of temperature, humidity, wind speed, short wave incoming radiation, and precipitation are available from an automatic weather station (AWS) on the moraine near the glacier for the hydrological years 2006/07 and 2007/08 while stake readings are available at intervals of between 14 to 64 days. To optimize model parameters, we used 1000 model simulations in which the most sensitive model parameters were varied randomly within their physically meaningful ranges. The modeled surface height change was evaluated against the two stake locations in the lower ablation zone (SH11, 4760m) and in the upper ablation zone (SH22, 4816m), respectively. The optimal parameter set for each point achieved good model skill but if we transfer the best parameter combination from one stake site to the other stake site model errors increases significantly. The same happens if we optimize the model parameters for each year individually and transfer
A termination criterion for parameter estimation in stochastic models in systems biology.
Zimmer, Christoph; Sahle, Sven
2015-11-01
Parameter estimation procedures are a central aspect of modeling approaches in systems biology. They are often computationally expensive, especially when the models take stochasticity into account. Typically parameter estimation involves the iterative optimization of an objective function that describes how well the model fits some measured data with a certain set of parameter values. In order to limit the computational expenses it is therefore important to apply an adequate stopping criterion for the optimization process, so that the optimization continues at least until a reasonable fit is obtained, but not much longer. In the case of stochastic modeling, at least some parameter estimation schemes involve an objective function that is itself a random variable. This means that plain convergence tests are not a priori suitable as stopping criteria. This article suggests a termination criterion suited to optimization problems in parameter estimation arising from stochastic models in systems biology. The termination criterion is developed for optimization algorithms that involve populations of parameter sets, such as particle swarm or evolutionary algorithms. It is based on comparing the variance of the objective function over the whole population of parameter sets with the variance of repeated evaluations of the objective function at the best parameter set. The performance is demonstrated for several different algorithms. To test the termination criterion we choose polynomial test functions as well as systems biology models such as an Immigration-Death model and a bistable genetic toggle switch. The genetic toggle switch is an especially challenging test case as it shows a stochastic switching between two steady states which is qualitatively different from the model behavior in a deterministic model. Copyright © 2015. Published by Elsevier Ireland Ltd.
Constraining statistical-model parameters using fusion and spallation reactions
Directory of Open Access Journals (Sweden)
Charity Robert J.
2011-10-01
Full Text Available The de-excitation of compound nuclei has been successfully described for several decades by means of statistical models. However, such models involve a large number of free parameters and ingredients that are often underconstrained by experimental data. We show how the degeneracy of the model ingredients can be partially lifted by studying different entrance channels for de-excitation, which populate different regions of the parameter space of the compound nucleus. Fusion reactions, in particular, play an important role in this strategy because they ﬁx three out of four of the compound-nucleus parameters (mass, charge and total excitation energy. The present work focuses on ﬁssion and intermediate-mass-fragment emission cross sections. We prove how equivalent parameter sets for fusion-ﬁssion reactions can be resolved using another entrance channel, namely spallation reactions. Intermediate-mass-fragment emission can be constrained in a similar way. An interpretation of the best-ﬁt IMF barriers in terms of the Wigner energies of the nascent fragments is discussed.
Updated climatological model predictions of ionospheric and HF propagation parameters
International Nuclear Information System (INIS)
Reilly, M.H.; Rhoads, F.J.; Goodman, J.M.; Singh, M.
1991-01-01
The prediction performances of several climatological models, including the ionospheric conductivity and electron density model, RADAR C, and Ionospheric Communications Analysis and Predictions Program, are evaluated for different regions and sunspot number inputs. Particular attention is given to the near-real-time (NRT) predictions associated with single-station updates. It is shown that a dramatic improvement can be obtained by using single-station ionospheric data to update the driving parameters for an ionospheric model for NRT predictions of f(0)F2 and other ionospheric and HF circuit parameters. For middle latitudes, the improvement extends out thousands of kilometers from the update point to points of comparable corrected geomagnetic latitude. 10 refs
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...
Influential input parameters for reflood model of MARS code
Energy Technology Data Exchange (ETDEWEB)
Oh, Deog Yeon; Bang, Young Seok [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
2012-10-15
Best Estimate (BE) calculation has been more broadly used in nuclear industries and regulations to reduce the significant conservatism for evaluating Loss of Coolant Accident (LOCA). Reflood model has been identified as one of the problems in BE calculation. The objective of the Post BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) program of OECD/NEA is to make progress the issue of the quantification of the uncertainty of the physical models in system thermal hydraulic codes, by considering an experimental result especially for reflood. It is important to establish a methodology to identify and select the parameters influential to the response of reflood phenomena following Large Break LOCA. For this aspect, a reference calculation and sensitivity analysis to select the dominant influential parameters for FEBA experiment are performed.
Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates
Todorovic, Andrijana; Plavsic, Jasna
2015-04-01
. Correlation coefficients among optimised model parameters and total precipitation P, mean temperature T and mean flow Q are calculated to give an insight into parameter dependence on the hydrometeorological drivers. The results reveal high sensitivity of almost all model parameters towards calibration period. The highest variability is displayed by the refreezing coefficient, water holding capacity, and temperature gradient. The only statistically significant (decreasing) trend is detected in the evapotranspiration reduction threshold. Statistically significant correlation is detected between the precipitation gradient and precipitation depth, and between the time-area histogram base and flows. All other correlations are not statistically significant, implying that changes in optimised parameters cannot generally be linked to the changes in P, T or Q. As for the model performance, the model reproduces the observed runoff satisfactorily, though the runoff is slightly overestimated in wet periods. The Nash-Sutcliffe efficiency coefficient (NSE) ranges from 0.44 to 0.79. Higher NSE values are obtained over wetter periods, what is supported by statistically significant correlation between NSE and flows. Overall, no systematic variations in parameters or in model performance are detected. Parameter variability may therefore rather be attributed to errors in data or inadequacies in the model structure. Further research is required to examine the impact of the calibration strategy or model structure on the variability in optimised parameters in time.
Directory of Open Access Journals (Sweden)
Petras Rupšys
2015-01-01
Full Text Available A stochastic modeling approach based on the Bertalanffy law gained interest due to its ability to produce more accurate results than the deterministic approaches. We examine tree crown width dynamic with the Bertalanffy type stochastic differential equation (SDE and mixed-effects parameters. In this study, we demonstrate how this simple model can be used to calculate predictions of crown width. We propose a parameter estimation method and computational guidelines. The primary goal of the study was to estimate the parameters by considering discrete sampling of the diameter at breast height and crown width and by using maximum likelihood procedure. Performance statistics for the crown width equation include statistical indexes and analysis of residuals. We use data provided by the Lithuanian National Forest Inventory from Scots pine trees to illustrate issues of our modeling technique. Comparison of the predicted crown width values of mixed-effects parameters model with those obtained using fixed-effects parameters model demonstrates the predictive power of the stochastic differential equations model with mixed-effects parameters. All results were implemented in a symbolic algebra system MAPLE.
International Nuclear Information System (INIS)
Xu, J.; Peng, S.; Kong, W.
2015-01-01
The rectangular hyperbola (RH), Mitscherlich (M) and YE equation were applied to describe the photosynthetic light response (PLR) curves measured from rice leaves with different SPAD values, to reveal the relationship between SPAD values and parameters in different equations, and to establish the modified PLR equations. The parameters in PLR equations are largely varied. SPAD value, as an indicator of leaf N contents, was highly correlated to the parameter of Pnmax in RH, M and YE equations. Incorporating the factor SPAD into PLR equations, the modified equations (MRH, MM, and MYE) were established which were feasible to describing the PLR curves for leaves with different SPAD values using the identical parameters for the ten PLR curves as a whole, and perform much better than the general PLR equations (GRH, GM, and GYE). It indicated that incorporating easy available indicators of leaf physiological and morphological traits in the PLR equations, such as SPAD as an indicator of leaf N or Chlorophyll contents, is an easy way to overcome the shortcoming of parameters variation in PLR equations between individuals of the same specie growing in different environments. Further validation should be done for different crops with both SPAD and other possible factors. (author)
The development of the Professional Values Model in Nursing.
Kaya, Ayla; Boz, İlkay
2017-01-01
One of the most important criteria for professionalism is accumulation of knowledge that is usable in professional practice. Nursing models and theories are important elements of accumulating nursing knowledge and have a chance to guarantee the ethical professional practice. In recent years, there has been an increase in the use of models in nursing research and newly created terminology has started to be used in nursing. In this study, a new model, termed as the Professional Values Model, developed by the authors was described. Concepts comprising the conceptual framework of the model and relations between the concepts were explained. It is assumed that awareness about concepts of the model will increase not only the patients' satisfaction with nursing care, but also the nurses' job satisfaction and quality of nursing care. Contemporary literature has been reviewed and synthesized to develop this theoretical paper on the Professional Values Model in nursing. Having high values in nursing increases job satisfaction, which results in the improvement of patient care and satisfaction. Also, individual characteristics are effective in the determination of individual needs, priorities, and values. This relation, proved through research about the Professional Values Model, has been explained. With development of these concepts, individuals' satisfaction with care and nurses' job satisfaction will be enhanced, which will increase the quality of nursing care. Most importantly, nurses can take proper decisions about ethical dilemmas and take ethical action when they take these values into consideration when giving care. The Professional Values Model seems suitable for nurse managers and it is expected that testing will improve it. Implementation of the Professional Values Model by nurse managers may increase motivation of nurses they work with. It is suggested that guidance by the Professional Values Model may help in enhancement of motivation efforts of the nurse managers
Application of parameters space analysis tools for empirical model validation
Energy Technology Data Exchange (ETDEWEB)
Paloma del Barrio, E. [LEPT-ENSAM UMR 8508, Talence (France); Guyon, G. [Electricite de France, Moret-sur-Loing (France)
2004-01-01
A new methodology for empirical model validation has been proposed in the framework of the Task 22 (Building Energy Analysis Tools) of the International Energy Agency. It involves two main steps: checking model validity and diagnosis. Both steps, as well as the underlying methods, have been presented in the first part of the paper. In this part, they are applied for testing modelling hypothesis in the framework of the thermal analysis of an actual building. Sensitivity analysis tools have been first used to identify the parts of the model that can be really tested on the available data. A preliminary diagnosis is then supplied by principal components analysis. Useful information for model behaviour improvement has been finally obtained by optimisation techniques. This example of application shows how model parameters space analysis is a powerful tool for empirical validation. In particular, diagnosis possibilities are largely increased in comparison with residuals analysis techniques. (author)
Test models for improving filtering with model errors through stochastic parameter estimation
International Nuclear Information System (INIS)
Gershgorin, B.; Harlim, J.; Majda, A.J.
2010-01-01
The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.
Huberts, W; de Jonge, C; van der Linden, W P M; Inda, M A; Passera, K; Tordoir, J H M; van de Vosse, F N; Bosboom, E M H
2013-06-01
Decision-making in vascular access surgery for hemodialysis can be supported by a pulse wave propagation model that is able to simulate pressure and flow changes induced by the creation of a vascular access. To personalize such a model, patient-specific input parameters should be chosen. However, the number of input parameters that can be measured in clinical routine is limited. Besides, patient data are compromised with uncertainty. Incomplete and uncertain input data will result in uncertainties in model predictions. In part A, we analyzed how the measurement uncertainty in the input propagates to the model output by means of a sensitivity analysis. Of all 73 input parameters, 16 parameters were identified to be worthwhile to measure more accurately and 51 could be fixed within their measurement uncertainty range, but these latter parameters still needed to be measured. Here, we present a methodology for assessing the model input parameters that can be taken constant and therefore do not need to be measured. In addition, a method to determine the value of this parameter is presented. For the pulse wave propagation model applied to vascular access surgery, six patient-specific datasets were analyzed and it was found that 47 out of 73 parameters can be fixed on a generic value. These model parameters are not important for personalization of the wave propagation model. Furthermore, we were able to determine a generic value for 37 of the 47 fixable model parameters. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Man Zhu
2017-03-01
Full Text Available Determination of ship maneuvering models is a tough task of ship maneuverability prediction. Among several prime approaches of estimating ship maneuvering models, system identification combined with the full-scale or free- running model test is preferred. In this contribution, real-time system identification programs using recursive identification method, such as the recursive least square method (RLS, are exerted for on-line identification of ship maneuvering models. However, this method seriously depends on the objects of study and initial values of identified parameters. To overcome this, an intelligent technology, i.e., support vector machines (SVM, is firstly used to estimate initial values of the identified parameters with finite samples. As real measured motion data of the Mariner class ship always involve noise from sensors and external disturbances, the zigzag simulation test data include a substantial quantity of Gaussian white noise. Wavelet method and empirical mode decomposition (EMD are used to filter the data corrupted by noise, respectively. The choice of the sample number for SVM to decide initial values of identified parameters is extensively discussed and analyzed. With de-noised motion data as input-output training samples, parameters of ship maneuvering models are estimated using RLS and SVM-RLS, respectively. The comparison between identification results and true values of parameters demonstrates that both the identified ship maneuvering models from RLS and SVM-RLS have reasonable agreements with simulated motions of the ship, and the increment of the sample for SVM positively affects the identification results. Furthermore, SVM-RLS using data de-noised by EMD shows the highest accuracy and best convergence.
Multi-Valued Modal Fixed Point Logics for Model Checking
Nishizawa, Koki
In this paper, I will show how multi-valued logics are used for model checking. Model checking is an automatic technique to analyze correctness of hardware and software systems. A model checker is based on a temporal logic or a modal fixed point logic. That is to say, a system to be checked is formalized as a Kripke model, a property to be satisfied by the system is formalized as a temporal formula or a modal formula, and the model checker checks that the Kripke model satisfies the formula. Although most existing model checkers are based on 2-valued logics, recently new attempts have been made to extend the underlying logics of model checkers to multi-valued logics. I will summarize these new results.
Neuert, Mark A C; Dunning, Cynthia E
2013-09-01
Strain energy-based adaptive material models are used to predict bone resorption resulting from stress shielding induced by prosthetic joint implants. Generally, such models are governed by two key parameters: a homeostatic strain-energy state (K) and a threshold deviation from this state required to initiate bone reformation (s). A refinement procedure has been performed to estimate these parameters in the femur and glenoid; this study investigates the specific influences of these parameters on resulting density distributions in the distal ulna. A finite element model of a human ulna was created using micro-computed tomography (µCT) data, initialized to a homogeneous density distribution, and subjected to approximate in vivo loading. Values for K and s were tested, and the resulting steady-state density distribution compared with values derived from µCT images. The sensitivity of these parameters to initial conditions was examined by altering the initial homogeneous density value. The refined model parameters selected were then applied to six additional human ulnae to determine their performance across individuals. Model accuracy using the refined parameters was found to be comparable with that found in previous studies of the glenoid and femur, and gross bone structures, such as the cortical shell and medullary canal, were reproduced. The model was found to be insensitive to initial conditions; however, a fair degree of variation was observed between the six specimens. This work represents an important contribution to the study of changes in load transfer in the distal ulna following the implementation of commercial orthopedic implants.
Audiovisual preservation strategies, data models and value-chains
Addis, Matthew; Wright, Richard
2010-01-01
This is a report on preservation strategies, models and value-chains for digital file-based audiovisual content. The report includes: (a)current and emerging value-chains and business-models for audiovisual preservation;(b) a comparison of preservation strategies for audiovisual content including their strengths and weaknesses, and(c) a review of current preservation metadata models, and requirements for extension to support audiovisual files.
Gas ultracentrifuge separative parameters modeling using hybrid neural networks
International Nuclear Information System (INIS)
Crus, Maria Ursulina de Lima
2005-01-01
A hybrid neural network is developed for the calculation of the separative performance of an ultracentrifuge. A feed forward neural network is trained to estimate the internal flow parameters of a gas ultracentrifuge, and then these parameters are applied in the diffusion equation. For this study, a 573 experimental data set is used to establish the relation between the separative performance and the controlled variables. The process control variables considered are: the feed flow rate F, the cut θ and the product pressure Pp. The mechanical arrangements consider the radial waste scoop dimension, the rotating baffle size D s and the axial feed location Z E . The methodology was validated through the comparison of the calculated separative performance with experimental values. This methodology may be applied to other processes, just by adapting the phenomenological procedures. (author)
Biosphere modelling for a HLW repository - scenario and parameter variations
International Nuclear Information System (INIS)
Grogan, H.
1985-03-01
In Switzerland high-level radioactive wastes have been considered for disposal in deep-lying crystalline formations. The individual doses to man resulting from radionuclides entering the biosphere via groundwater transport are calculated. The main recipient area modelled, which constitutes the base case, is a broad gravel terrace sited along the south bank of the river Rhine. An alternative recipient region, a small valley with a well, is also modelled. A number of parameter variations are performed in order to ascertain their impact on the doses. Finally two scenario changes are modelled somewhat simplistically, these consider different prevailing climates, namely tundra and a warmer climate than present. In the base case negligibly low doses to man in the long term, resulting from the existence of a HLW repository have been calculated. Cs-135 results in the largest dose (8.4E-7 mrem/y at 6.1E+6 y) while Np-237 gives the largest dose from the actinides (3.6E-8 mrem/y). The response of the model to parameter variations cannot be easily predicted due to non-linear coupling of many of the parameters. However, the calculated doses were negligibly low in all cases as were those resulting from the two scenario variations. (author)
International Nuclear Information System (INIS)
Koyama, Hisanobu; Ohno, Yoshiharu; Seki, Shinichiro; Nishio, Mizuho; Yoshikawa, Takeshi; Matsumoto, Sumiaki; Maniwa, Yoshimasa; Itoh, Tomoo; Nishimura, Yoshihiro; Sugimura, Kazuro
2015-01-01
Highlights: •Signal–intensity ratio evaluation between lesion and spinal cord is practical method. •Apparent diffusion coefficients may not contribute to the diagnosis of malignant. •True diffusion coefficients may have low potential for the differentiation. •Perfusion fractions may be less specific parameter of diagnosis of pulmonary nodule. •Choice of b values shows little impact for differentiation of pulmonary nodules. -- Abstract: Objectives: To determine the appropriate parameters and evaluation method for characterizing solitary pulmonary nodules (SPNs) using quantitative parameters of diffusion-weighted imaging (DWI). Methods: Thirty-two subjects with 36 SPNs underwent DWI with seven different b values (0, 50, 100, 150, 300, 500, and 1000 s/mm 2 ). Five quantitative parameters were obtained from the region of interest drawn over each SPN: apparent diffusion coefficients (ADCs), true diffusion coefficients (DCs), and perfusion fractions (PFs), and signal–intensity ratios between lesion and spinal cord from DWI (b values: 1000 [LSR 1000 ] and 500 [LSR 500 )]). All quantitative parameters and the diagnostic capabilities were statistically compared. Results: SPNs were diagnosed as follow: malignant (n = 27) and benign (n = 9). Parameter comparisons for malignant and benign showed both LSRs differed significantly (p < 0.05). Applying feasible threshold values showed LSR 500 specificity (88.9% [8/9]) and accuracy (77.8% [28/36]) were significantly higher than ADC, DC, and PF specificity and accuracy (p < 0.05). LSR 1000 accuracy (72.2% [26/36]) was significantly higher than DC accuracy, and its specificity (88.9% [8/9]) was significantly higher than ADC, DC, and PF specificities (p < 0.05). Conclusions: For quantitative differentiation of SPNs, LSR evaluation was more useful and practical than ADC, DC, and PF, and choice of b values showed little impact for the differentiation
International Nuclear Information System (INIS)
Khawaja, Z; Mazeran, P-E; Bigerelle, M; Guillemot, G; Mansori, M El
2011-01-01
This article presents a multi-scale theory based on wavelet decomposition to characterize the evolution of roughness in relation with a finishing process or an observed surface property. To verify this approach in production conditions, analyses were developed for the finishing process of the hardened steel by abrasive belts. These conditions are described by seven parameters considered in the Tagushi experimental design. The main objective of this work is to identify the most relevant roughness parameter and characteristic length allowing to assess the influence of finishing process, and to test the relevance of the measurement scale. Results show that wavelet approach allows finding this scale.
International Nuclear Information System (INIS)
Ramkumar, S.; Dole, M.L.; Nankar, D.P.; Rajan, M.P.; Gurg, R.P.
2003-01-01
In the design of engineering structures, an understanding of extreme weather conditions that may occur at the site of interest is very essential, so that the structures can be designed to withstand such situations. In this report an analysis of extreme values of meteorological parameters observed at Kakrapar Atomic Power Station site for the period 1994 -2001 is described. The parameters considered are maximum and minimum air temperature, maximum wind speed and gust, and maximum rainfall in a month, in a day, in an hour and annual rainfall. The extreme value analysis reveals that annual rainfall, maximum monthly rainfall, minimum air temperature and maximum wind speed at 10 m obey Fisher-Tippet Type -1 distribution whereas maximum daily rainfall, maximum hourly rainfall, maxinlum air temperature and maximum wind speed at 30 m obey Fisher-Tippet Type -2 distribution function. There is no difference in correlation coefficients and fit both extreme value distribution function. Co-efficients of the distribution functions for each variable are established. Extreme values of parameters corresponding to return periods of 50 and 100 years are derived. These derived extreme values are particularly useful for arriving at suitable design basis values to ensure the safety of any civil structure in and around Kakrapar Atomic Power Station site with respect to stresses due to weather conditions. (author)
Progress on reference input parameter library for nuclear model calculations of nuclear data (III)
International Nuclear Information System (INIS)
Su Zongdi; Liu Jianfeng; Huang Zhongfu
1997-01-01
A new set of the average neutron resonance spacings D 0 and neutron strength functions S 0 for 309 nuclei were reestimated on the basis of the resolved resonance parameters reevaluated from BNL-325, ENDF/B-6, JEF-2, and JENDL-3, and the cumulative number N 0 of low low lying levels for 344 nuclei were also reevaluated by means of histograms. Three sets of level density parameters for the Gilbert-Cameron (GC) formula, back-shifted Fermi gas model(BS) and generated superfluid model (GSM) have been reesitmated by fitting the D 0 and N 0 values of CENPL.LRD-2
Monoenergetic electron parameters in a spheroid bubble model
Sattarian, H.; Sh., Rahmatallahpur; Tohidi, T.
2013-02-01
A reliable analytical expression for the potential of plasma waves with phase velocities near the speed of light is derived. The presented spheroid cavity model is more consistent than the previous spherical and ellipsoidal models and it explains the mono-energetic electron trajectory more accurately, especially at the relativistic region. The maximum energy of electrons is calculated and it is shown that the maximum energy of the spheroid model is less than that of the spherical model. The electron energy spectrum is also calculated and it is found that the energy distribution ratio of electrons ΔE/E for the spheroid model under the conditions reported here is half that of the spherical model and it is in good agreement with the experimental value in the same conditions. As a result, the quasi-mono-energetic electron output beam interacting with the laser plasma can be more appropriately described with this model.
Monoenergetic electron parameters in a spheroid bubble model
International Nuclear Information System (INIS)
Sattarian, H.; Rahmatallahpur, Sh.; Tohidi, T.
2013-01-01
A reliable analytical expression for the potential of plasma waves with phase velocities near the speed of light is derived. The presented spheroid cavity model is more consistent than the previous spherical and ellipsoidal models and it explains the mono-energetic electron trajectory more accurately, especially at the relativistic region. The maximum energy of electrons is calculated and it is shown that the maximum energy of the spheroid model is less than that of the spherical model. The electron energy spectrum is also calculated and it is found that the energy distribution ratio of electrons ΔE/E for the spheroid model under the conditions reported here is half that of the spherical model and it is in good agreement with the experimental value in the same conditions. As a result, the quasi-mono-energetic electron output beam interacting with the laser plasma can be more appropriately described with this model. (physics of gases, plasmas, and electric discharges)
Towards an Integrated Value Adding Management Model for FM and CREM
DEFF Research Database (Denmark)
Jensen, Per Anker; van der Voordt, Theo
2016-01-01
Purpose : To present an integrated process model of adding value by Facilities Management (FM) and Corporate Real Estate Management (CREM) that is a generalisation of existing conceptual frameworks and aims to be a basis for management of added value in practice. Background : The growing research...... frameworks are too complex and lack of common terminology and clear operationalisations of intervention-impact relationships. Approach (Theory/Methodology) :A generalised Value Adding Management process model is developed based on a common cause-effect model identified in existing conceptual frameworks...... aims at supporting the practical management and measurement of added value. A typology with six types of FM/CREM interventions is developed from earlier research. The concept of Value Adding Management is investigated and the 12 most important added value parameters are identified. Research limitations...
Self-Service Banking: Value Creation Models and Information Exchange
Directory of Open Access Journals (Sweden)
Ragnvald Sannes
2001-01-01
Full Text Available This paper argues that most banks have failed to exploit the potential of self-service banking because they base their service design on an incomplete business model for self-service. A framework for evaluation of self-service banking concepts is developed on the basis of Stabell and Fjeldstad's three value configurations. The value network and the value shop are consistent with self-service banking while the value chain is inappropriate. The impact of the value configurations on information exchange and self-service functionality is discussed, and a framework for design of such services proposed. Current self-service banking practices are compared to the framework, and it is concluded that current practice matches the concept of a value network and not the value shop. However, current practices are only a partial implementation of a value network-based self-service banking concept.
Ito, Tetsuya; Fukawa, Kazuo; Kamikawa, Mai; Nikaidou, Satoshi; Taniguchi, Masaaki; Arakawa, Aisaku; Tanaka, Genki; Mikawa, Satoshi; Furukawa, Tsutomu; Hirose, Kensuke
2018-01-01
Daily feed intake (DFI) is an important consideration for improving feed efficiency, but measurements using electronic feeder systems contain many missing and incorrect values. Therefore, we evaluated three methods for correcting missing DFI data (quadratic, orthogonal polynomial, and locally weighted (Loess) regression equations) and assessed the effects of these missing values on the genetic parameters and the estimated breeding values (EBV) for feeding traits. DFI records were obtained from 1622 Duroc pigs, comprising 902 individuals without missing DFI and 720 individuals with missing DFI. The Loess equation was the most suitable method for correcting the missing DFI values in 5-50% randomly deleted datasets among the three equations. Both variance components and heritability for the average DFI (ADFI) did not change because of the missing DFI proportion and Loess correction. In terms of rank correlation and information criteria, Loess correction improved the accuracy of EBV for ADFI compared to randomly deleted cases. These findings indicate that the Loess equation is useful for correcting missing DFI values for individual pigs and that the correction of missing DFI values could be effective for the estimation of breeding values and genetic improvement using EBV for feeding traits. © 2017 The Authors. Animal Science Journal published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Animal Science.
A new method to estimate parameters of linear compartmental models using artificial neural networks
International Nuclear Information System (INIS)
Gambhir, Sanjiv S.; Keppenne, Christian L.; Phelps, Michael E.; Banerjee, Pranab K.
1998-01-01
At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models. (author)
Plumb, John M.; Moffitt, Christine M.
2015-01-01
Researchers have cautioned against the borrowing of consumption and growth parameters from other species and life stages in bioenergetics growth models. In particular, the function that dictates temperature dependence in maximum consumption (Cmax) within the Wisconsin bioenergetics model for Chinook Salmon Oncorhynchus tshawytscha produces estimates that are lower than those measured in published laboratory feeding trials. We used published and unpublished data from laboratory feeding trials with subyearling Chinook Salmon from three stocks (Snake, Nechako, and Big Qualicum rivers) to estimate and adjust the model parameters for temperature dependence in Cmax. The data included growth measures in fish ranging from 1.5 to 7.2 g that were held at temperatures from 14°C to 26°C. Parameters for temperature dependence in Cmax were estimated based on relative differences in food consumption, and bootstrapping techniques were then used to estimate the error about the parameters. We found that at temperatures between 17°C and 25°C, the current parameter values did not match the observed data, indicating that Cmax should be shifted by about 4°C relative to the current implementation under the bioenergetics model. We conclude that the adjusted parameters for Cmax should produce more accurate predictions from the bioenergetics model for subyearling Chinook Salmon.
Ely, D. Matthew
2006-01-01
routing parameter. Although the primary objective of this study was to identify, by geographic region, the importance of the parameter value to the simulation of ground-water recharge, the secondary objectives proved valuable for future modeling efforts. The value of a rigorous sensitivity analysis can (1) make the calibration process more efficient, (2) guide additional data collection, (3) identify model limitations, and (4) explain simulated results.
Comparison of ionospheric profile parameters with IRI-2012 model over Jicamarca
International Nuclear Information System (INIS)
Bello, S A; Abdullah, M; Hamid, N S A; Reinisch, B W
2017-01-01
We used the hourly ionogram data obtained from Jicamarca station (12° S, 76.9° W, dip latitude: 1.0° N) an equatorial region to study the variation of the electron density profile parameters: maximum height of F2-layer ( hm F2), bottomside thickness ( B0 ) and shape ( B1 ) parameter of F-layer. The period of study is for the year 2010 (solar minimum period).The diurnal monthly averages of these parameters are compared with the updated IRI-2012 model. The results show that hm F2 is highest during the daytime than nighttime. The variation in hmF2 was observed to modulate the thickness of the bottomside F2-layer. The observed hm F2 and B0 post-sunset peak is as result of the upward drift velocity of ionospheric plasma. We found a close agreement between IRI-CCIR hm F2 model and observed hm F2 during 0000-0700 LT while outside this period the model predictions deviate significantly with the observational values. Significant discrepancies are observed between the IRI model options for B0 and the observed B0 values. Specifically, the modeled values do not show B0 post-sunset peak. A fairly good agreement was observed between the observed B1 and IRI model options (ABT-2009 and Bill 2000) for B1 . (paper)
Comparison of ionospheric profile parameters with IRI-2012 model over Jicamarca
Bello, S. A.; Abdullah, M.; Hamid, N. S. A.; Reinisch, B. W.
2017-05-01
We used the hourly ionogram data obtained from Jicamarca station (12° S, 76.9° W, dip latitude: 1.0° N) an equatorial region to study the variation of the electron density profile parameters: maximum height of F2-layer (hmF2), bottomside thickness (B0) and shape (B1) parameter of F-layer. The period of study is for the year 2010 (solar minimum period).The diurnal monthly averages of these parameters are compared with the updated IRI-2012 model. The results show that hmF2 is highest during the daytime than nighttime. The variation in hmF2 was observed to modulate the thickness of the bottomside F2-layer. The observed hmF2 and B0 post-sunset peak is as result of the upward drift velocity of ionospheric plasma. We found a close agreement between IRI-CCIR hmF2 model and observed hmF2 during 0000-0700 LT while outside this period the model predictions deviate significantly with the observational values. Significant discrepancies are observed between the IRI model options for B0 and the observed B0 values. Specifically, the modeled values do not show B0 post-sunset peak. A fairly good agreement was observed between the observed B1 and IRI model options (ABT-2009 and Bill 2000) for B1.
Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.
El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher
2018-01-01
Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.
Propagation channel characterization, parameter estimation, and modeling for wireless communications
Yin, Xuefeng
2016-01-01
Thoroughly covering channel characteristics and parameters, this book provides the knowledge needed to design various wireless systems, such as cellular communication systems, RFID and ad hoc wireless communication systems. It gives a detailed introduction to aspects of channels before presenting the novel estimation and modelling techniques which can be used to achieve accurate models. To systematically guide readers through the topic, the book is organised in three distinct parts. The first part covers the fundamentals of the characterization of propagation channels, including the conventional single-input single-output (SISO) propagation channel characterization as well as its extension to multiple-input multiple-output (MIMO) cases. Part two focuses on channel measurements and channel data post-processing. Wideband channel measurements are introduced, including the equipment, technology and advantages and disadvantages of different data acquisition schemes. The channel parameter estimation methods are ...
Value-based resource management: a model for best value nursing care.
Caspers, Barbara A; Pickard, Beth
2013-01-01
With the health care environment shifting to a value-based payment system, Catholic Health Initiatives nursing leadership spearheaded an initiative with 14 hospitals to establish best nursing care at a lower cost. The implementation of technology-enabled business processes at point of care led to a new model for best value nursing care: Value-Based Resource Management. The new model integrates clinical patient data from the electronic medical record and embeds the new information in care team workflows for actionable real-time decision support and predictive forecasting. The participating hospitals reported increased patient satisfaction and cost savings in the reduction of overtime and improvement in length of stay management. New data generated by the initiative on nursing hours and cost by patient and by population (Medicare severity diagnosis-related groups), and patient health status outcomes across the acute care continuum expanded business intelligence for a value-based population health system.
Modeling and Application of Customer Lifetime Value in Online Retail
Pavel Jasek; Lenka Vrana; Lucie Sperkova; Zdenek Smutny; Marek Kobulsky
2018-01-01
This article provides an empirical statistical analysis and discussion of the predictive abilities of selected customer lifetime value (CLV) models that could be used in online shopping within e-commerce business settings. The comparison of CLV predictive abilities, using selected evaluation metrics, is made on selected CLV models: Extended Pareto/NBD model (EP/NBD), Markov chain model and Status Quo model. The article uses six online store datasets with annual revenues in the order of tens o...
Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model
DEFF Research Database (Denmark)
Åberg, Andreas; Widd, Anders; Abildskov, Jens
2016-01-01
be used directly for accurate full-scale transient simulations. The model was validated against full-scale data with an engine following the European Transient Cycle. The validation showed that the predictive capability for nitrogen oxides (NOx) was satisfactory. After re-estimation of the adsorption...... and desorption parameters with full-scale transient data, the fit for both NOx and NH3-slip was satisfactory....
Mathematical models to predict rheological parameters of lateritic hydromixtures
Gabriel Hernández-Ramírez; Arístides A. Legrá-Lobaina; Beatriz Ramírez-Serrano; Liudmila Pérez-García
2017-01-01
The present work had as objective to establish mathematical models that allow the prognosis of the rheological parameters of the lateritic pulp at concentrations of solids from 35% to 48%, temperature of the preheated hydromixture superior to 82 ° C and number of mineral between 3 and 16. Four samples of lateritic pulp were used in the study at different process locations. The results allowed defining that the plastic properties of the lateritic pulp in the conditions of this study conform to...
Timmerhuis, Th.P.J.; Hageman, G.; Oosterloo, Sebe J.; Rozeboom, A.R.
1996-01-01
The prognostic value of magnetic evoked potentials (MEP), somatosensory evoked potentials (SSEP), age and radiological parameters was determined in 50 patients with acute middle cerebral artery infarction. We performed MEP and SSEP within 4 days and after 6 weeks and 3 months of the infarction and
The 4-parameter Compressible Packing Model (CPM) including a critical cavity size ratio
Roquier, Gerard
2017-06-01
The 4-parameter Compressible Packing Model (CPM) has been developed to predict the packing density of mixtures constituted by bidisperse spherical particles. The four parameters are: the wall effect and the loosening effect coefficients, the compaction index and a critical cavity size ratio. The two geometrical interactions have been studied theoretically on the basis of a spherical cell centered on a secondary class bead. For the loosening effect, a critical cavity size ratio, below which a fine particle can be inserted into a small cavity created by touching coarser particles, is introduced. This is the only parameter which requires adaptation to extend the model to other types of particles. The 4-parameter CPM demonstrates its efficiency on frictionless glass beads (300 values), spherical particles numerically simulated (20 values), round natural particles (125 values) and crushed particles (335 values) with correlation coefficients equal to respectively 99.0%, 98.7%, 97.8%, 96.4% and mean deviations equal to respectively 0.007, 0.006, 0.007, 0.010.
Effect of calibration data series length on performance and optimal parameters of hydrological model
Directory of Open Access Journals (Sweden)
Chuan-zhe Li
2010-12-01
Full Text Available In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments (data are non-continuous and fragmental in some catchments, we used non-continuous calibration periods for more independent streamflow data for SIMHYD (simple hydrology model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization (PSO method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.
COMPREHENSIVE CHECK MEASUREMENT OF KEY PARAMETERS ON MODEL BELT CONVEYOR
Directory of Open Access Journals (Sweden)
Vlastimil MONI
2013-07-01
Full Text Available Complex measurements of characteristic parameters realised on a long distance model belt conveyor are described. The main objective was to complete and combine the regular measurements of electric power on drives of belt conveyors operated in Czech opencast mines with measurements of other physical quantities and to gain by this way an image of their mutual relations and relations of quantities derived from them. The paper includes a short description and results of the measurements on an experimental model conveyor with a closed material transport way.
Information Theoretic Tools for Parameter Fitting in Coarse Grained Models
Kalligiannaki, Evangelia
2015-01-07
We study the application of information theoretic tools for model reduction in the case of systems driven by stochastic dynamics out of equilibrium. The model/dimension reduction is considered by proposing parametrized coarse grained dynamics and finding the optimal parameter set for which the relative entropy rate with respect to the atomistic dynamics is minimized. The minimization problem leads to a generalization of the force matching methods to non equilibrium systems. A multiplicative noise example reveals the importance of the diffusion coefficient in the optimization problem.
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.
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.
Kim, Kyung Yong; Lee, Won-Chan
2017-01-01
This article provides a detailed description of three factors (specification of the ability distribution, numerical integration, and frame of reference for the item parameter estimates) that might affect the item parameter estimation of the three-parameter logistic model, and compares five item calibration methods, which are combinations of the…
Identifying the effects of parameter uncertainty on the reliability of riverbank stability modelling
Samadi, A.; Amiri-Tokaldany, E.; Darby, S. E.
2009-05-01
Bank retreat is a key process in fluvial dynamics affecting a wide range of physical, ecological and socioeconomic issues in the fluvial environment. To predict the undesirable effects of bank retreat and to inform effective measures to prevent it, a wide range of bank stability models have been presented in the literature. These models typically express bank stability by defining a factor of safety as the ratio of driving and resisting forces acting on the incipient failure block. These forces are affected by a range of controlling factors that include such aspects as the bank profile (bank height and angle), the geotechnical properties of the bank materials, as well as the hydrological status of the riverbanks. In this paper we evaluate the extent to which uncertainties in the parameterization of these controlling factors feed through to influence the reliability of the resulting bank stability estimate. This is achieved by employing a simple model of riverbank stability with respect to planar failure (which is the most common type of bank stability model) in a series of sensitivity tests and Monte Carlo analyses to identify, for each model parameter, the range of values that induce significant changes in the simulated factor of safety. These identified parameter value ranges are compared to empirically derived parameter uncertainties to determine whether they are likely to confound the reliability of the resulting bank stability calculations. Our results show that parameter uncertainties are typically high enough that the likelihood of generating unreliable predictions is typically very high (> ˜ 80% for predictions requiring a precision of < ± 15%). Because parameter uncertainties are derived primarily from the natural variability of the parameters, rather than measurement errors, much more careful attention should be paid to field sampling strategies, such that the parameter uncertainties and consequent prediction unreliabilities can be quantified more
Ordinary Mathematical Models in Calculating the Aviation GTE Parameters
Directory of Open Access Journals (Sweden)
E. A. Khoreva
2017-01-01
Full Text Available The paper presents the analytical review results of the ordinary mathematical models of the operating process used to study aviation GTE parameters and characteristics at all stages of its creation and operation. Considers the mathematical models of the zero and the first level, which are mostly used when solving typical problems in calculating parameters and characteristics of engines.Presents a number of practical problems arising in designing aviation GTE for various applications.The application of mathematical models of the zero-level engine can be quite appropriate when the engine is considered as a component in the aircraft system to estimate its calculated individual flight performance or when modeling the flight cycle of the aircrafts of different purpose.The paper demonstrates that introduction of correction functions into the first-level mathematical models in solving typical problems (influence of the Reynolds number, characteristics deterioration of the units during the overhaul period of engine, as well as influence of the flow inhomogeneity at the inlet because of manufacturing tolerance, etc. enables providing a sufficient engineering estimate accuracy to reflect a realistic operating process in the engine and its elements.
Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J
2013-10-28
Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.
Brownian gas models for extreme-value laws
International Nuclear Information System (INIS)
Eliazar, Iddo
2013-01-01
In this paper we establish one-dimensional Brownian gas models for the extreme-value laws of Gumbel, Weibull, and Fréchet. A gas model is a countable collection of independent particles governed by common diffusion dynamics. The extreme-value laws are the universal probability distributions governing the affine scaling limits of the maxima and minima of ensembles of independent and identically distributed one-dimensional random variables. Using the recently introduced concept of stationary Poissonian intensities, we construct two gas models whose global statistical structures are stationary, and yield the extreme-value laws: a linear Brownian motion gas model for the Gumbel law, and a geometric Brownian motion gas model for the Weibull and Fréchet laws. The stochastic dynamics of these gas models are studied in detail, and closed-form analytical descriptions of their temporal correlation structures, their topological phase transitions, and their intrinsic first-passage-time fluxes are presented. (paper)
Spatial extrapolation of light use efficiency model parameters to predict gross primary production
Directory of Open Access Journals (Sweden)
Karsten Schulz
2011-12-01
Full Text Available To capture the spatial and temporal variability of the gross primary production as a key component of the global carbon cycle, the light use efficiency modeling approach in combination with remote sensing data has shown to be well suited. Typically, the model parameters, such as the maximum light use efficiency, are either set to a universal constant or to land class dependent values stored in look-up tables. In this study, we employ the machine learning technique support vector regression to explicitly relate the model parameters of a light use efficiency model calibrated at several FLUXNET sites to site-specific characteristics obtained by meteorological measurements, ecological estimations and remote sensing data. A feature selection algorithm extracts the relevant site characteristics in a cross-validation, and leads to an individual set of characteristic attributes for each parameter. With this set of attributes, the model parameters can be estimated at sites where a parameter calibration is not possible due to the absence of eddy covariance flux measurement data. This will finally allow a spatially continuous model application. The performance of the spatial extrapolation scheme is evaluated with a cross-validation approach, which shows the methodology to be well suited to recapture the variability of gross primary production across the study sites.
Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J
2011-09-01
When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.
MODEL OF INTEGRATED VALUE OF PROJECTS IN THE FIELD OF ALTERNATIVE ENERGY
Directory of Open Access Journals (Sweden)
Наталія Ігорівна БОРИСОВА
2015-05-01
Full Text Available Development of alternative energy sources requires the implementation of complex problems, the solution of which is necessary to apply the project approach. The uniqueness of alternative energy projects (AEP necessitates individual approach to evaluating the effectiveness of each. The paper contains the results of the project management features's analysis in the field of alternative energy, determining the values and developing of the value management integrated conceptual model of AEP. In assessing the effectiveness of AEP considered the socio-economic and commercial aspects. Value management integrated conceptual model of AEP was obtained by combining the classical model of the project management goals with the project values model "Five "E" and two "A". The classical model of the project management goals have been complemented with risk parameters.
Development of a Value Inquiry Model in Biology Education.
Jeong, Eun-Young; Kim, Young-Soo
2000-01-01
Points out the rapid advances in biology, increasing bioethical issues, and how students need to make rational decisions. Introduces a value inquiry model development that includes identifying and clarifying value problems; understanding biological knowledge related to conflict situations; considering, selecting, and evaluating each alternative;…
Towards the Integration of Value and Coordination Models - Position Paper -
Bodenstaff, L.; Reichert, M.U.; Wieringa, Roelf J.; Pernici, B; Gulla, J.A.
Cross-organizational collaborations have a high complexity. Modelling these collaborations can be done from di®erent perspectives. For example, the value perspective represents expected value exchanges in a collaboration while the coordination perspective represents the order in which these
Satisfaction with virtual worlds: An integrated model of experiential value
Verhagen, T.; Feldberg, J.F.M.; van den Hooff, B.J.; Meents, S.; Merikivi, J.
2011-01-01
Although virtual worlds increasingly attract users today, few studies have addressed what satisfies virtual world users. We therefore defined and tested an integrated model of experiential system value and virtual world satisfaction. Drawing upon expectancy-value and cognitive evaluation theories,
Environment modeling using runtime values for JPF-Android
CSIR Research Space (South Africa)
Van der Merwe, H
2015-11-01
Full Text Available , the environment of an application is simplified/abstracted using models or stubs. Empty stubs, returning default values, are simple to generate automatically, but they do not perform well when the application expects specific return values. Symbolic execution...
Wang, Xiandi; Wang, Hongli; Sun, Chi; Zhou, Shuyi; Meng, Tao; Lv, Feizhou; Ma, Xiaosheng; Xia, Xinlei; Jiang, Jianyuan
2018-04-26
Previous studies have indicated that decreased fractional anisotropy (FA) values on diffusion tensor imaging (DTI) are well correlated with the symptoms of nerve root compression. The aim of our study is to determine primary radiological parameters associated with decreased FA values in patients with lumbar spinal stenosis involving single L5 nerve root. Patients confirmed with single L5 nerve root compression by transforaminal nerve root blocks were included in this study. FA values of L5 nerve roots on both symptomatic and asymptomatic side were obtained. Conventional radiological parameters, such as disc height, degenerative scoliosis, dural sac cross-sectional area (DSCSA), foraminal height (FH), hypertrophic facet joint degeneration (HFJD), sagittal rotation (SR), sedimentation sign, sagittal translation and traction spur were measured. Correlation and regression analyses were performed between the radiological parameters and FA values of the symptomatic L5 nerve roots. A predictive regression equation was established. Twenty-one patients were included in this study. FA values were significantly lower at the symptomatic side comparing to the asymptomatic side (0.263 ± 0.069 vs. 0.334 ± 0.080, P = 0.038). DSCSA, FH, HFJD, and SR were significantly correlated with the decreased FA values, with r = 0.518, 0.443, 0.472 and - 0.910, respectively (P values, and the regression equation is FA = - 0.012 × SR + 0.002 × DSCSA. DSCSA and SR were primary contributors to decreased FA values in LSS patients involving single L5 nerve root, indicating that central canal decompression and segmental stability should be the first considerations in preoperative planning of these patients. These slides can be retrieved under Electronic Supplementary Material.
Innovation of Methods for Measurement and Modelling of Twisted Pair Parameters
Directory of Open Access Journals (Sweden)
Lukas Cepa
2011-01-01
Full Text Available The goal of this paper is to optimize a measurement methodology for the most accurate broadband modelling of characteristic impedance and other parameters for twisted pairs. Measured values and theirs comparison is presented in this article. Automated measurement facility was implemented at the Department of telecommunication of Faculty of electrical engineering of Czech technical university in Prague. Measurement facility contains RF switches allowing measurements up to 300 MHz or 1GHz. Measured twisted pair’s parameters can be obtained by measurement but for purposes of fundamental characteristics modelling is useful to define functions that model the properties of the twisted pair. Its primary and secondary parameters depend mostly on the frequency. For twisted pair deployment, we are interested in a frequency band range from 1 MHz to 100 MHz.
International Nuclear Information System (INIS)
Kim, Joo Yeon; Ryu, Hyung Joon; Jung, Gyu Hwan; Lee, Jai Ki
2011-01-01
The dependency within the sequential realizations in the generated Markov chains and their reliabilities are monitored by introducing the autocorrelation and the potential scale reduction factor (PSRF) by model parameters in the atmospheric dispersion. These two diagnostics have been applied for the posterior quantities of the release point and the release rate inferred through the inverse tracking of unknown model parameters for the Yonggwang atmospheric tracer experiment in Korea. The autocorrelations of model parameters are decreasing to low values approaching to zero with increase of lag, resulted in decrease of the dependencies within the two sequential realizations. Their PSRFs are reduced to within 1.2 and the adequate simulation number recognized from these results. From these two convergence diagnostics, the validation of Markov chains generated have been ensured and PSRF then is especially suggested as the efficient tool for convergence monitoring for the source reconstruction in atmospheric dispersion. (author)
International Nuclear Information System (INIS)
Sarkar, S.; Kosson, D.S.; Mahadevan, S.; Meeussen, J.C.L.; Sloot, H. van der; Arnold, J.R.; Brown, K.G.
2012-01-01
Chemical equilibrium modeling of cementitious materials requires aqueous–solid equilibrium constants of the controlling mineral phases (K sp ) and the available concentrations of primary components. Inherent randomness of the input and model parameters, experimental measurement error, the assumptions and approximations required for numerical simulation, and inadequate knowledge of the chemical process contribute to uncertainty in model prediction. A numerical simulation framework is developed in this paper to assess uncertainty in K sp values used in geochemical speciation models. A Bayesian statistical method is used in combination with an efficient, adaptive Metropolis sampling technique to develop probability density functions for K sp values. One set of leaching experimental observations is used for calibration and another set is used for comparison to evaluate the applicability of the approach. The estimated probability distributions of K sp values can be used in Monte Carlo simulation to assess uncertainty in the behavior of aqueous–solid partitioning of constituents in cement-based materials.
Applicability of genetic algorithms to parameter estimation of economic models
Directory of Open Access Journals (Sweden)
Marcel Ševela
2004-01-01
Full Text Available The paper concentrates on capability of genetic algorithms for parameter estimation of non-linear economic models. In the paper we test the ability of genetic algorithms to estimate of parameters of demand function for durable goods and simultaneously search for parameters of genetic algorithm that lead to maximum effectiveness of the computation algorithm. The genetic algorithms connect deterministic iterative computation methods with stochastic methods. In the genteic aůgorithm approach each possible solution is represented by one individual, those life and lifes of all generations of individuals run under a few parameter of genetic algorithm. Our simulations resulted in optimal mutation rate of 15% of all bits in chromosomes, optimal elitism rate 20%. We can not set the optimal extend of generation, because it proves positive correlation with effectiveness of genetic algorithm in all range under research, but its impact is degreasing. The used genetic algorithm was sensitive to mutation rate at most, than to extend of generation. The sensitivity to elitism rate is not so strong.
Value Creation Challenges in Multichannel Retail Business Models
Directory of Open Access Journals (Sweden)
Mika Yrjölä
2014-08-01
Full Text Available Purpose: The purpose of the paper is to identify and analyze the challenges of value creation in multichannel retail business models. Design/methodology/approach: With the help of semi-structured interviews with top executives from different retailing environments, this study introduces a model of value creation challenges in the context of multichannel retailing. The challenges are analyzed in terms of three retail business model elements, i.e., format, activities, and governance. Findings: Adopting a multichannel retail business model requires critical rethinking of the basic building blocks of value creation. First of all, as customers effortlessly move between multiple channels, multichannel formats can lead to a mismatch between customer and firm value. Secondly, retailers face pressures to use their activities to form integrated total offerings to customers. Thirdly, multiple channels might lead to organizational silos with conflicting goals. A careful orchestration of value creation is needed to determine the roles and incentives of the channel parties involved. Research limitations/implications: In contrast to previous business model literature, this study did not adopt a network-centric view. By embracing the boundary-spanning nature of the business model, other challenges and elements might have been discovered (e.g., challenges in managing relationships with suppliers. Practical implications: As a practical contribution, this paper has analyzed the challenges retailers face in adopting multichannel business models. Customer tendencies for showrooming behavior highlight the need for generating efficient lock-in strategies. Customized, personal offers and information are ways to increase customer value, differentiate from competition, and achieve lock-in. Originality/value: As a theoretical contribution, this paper empirically investigates value creation challenges in a specific context, lowering the level of abstraction in the mostly
Integral-Value Models for Outcomes over Continuous Time
DEFF Research Database (Denmark)
Harvey, Charles M.; Østerdal, Lars Peter
Models of preferences between outcomes over continuous time are important for individual, corporate, and social decision making, e.g., medical treatment, infrastructure development, and environmental regulation. This paper presents a foundation for such models. It shows that conditions on prefere...... on preferences between real- or vector-valued outcomes over continuous time are satisfied if and only if the preferences are represented by a value function having an integral form......Models of preferences between outcomes over continuous time are important for individual, corporate, and social decision making, e.g., medical treatment, infrastructure development, and environmental regulation. This paper presents a foundation for such models. It shows that conditions...
Estimation of k-ε parameters using surrogate models and jet-in-crossflow data
Energy Technology Data Exchange (ETDEWEB)
Lefantzi, Sophia [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ray, Jaideep [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Arunajatesan, Srinivasan [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Dechant, Lawrence [Sandia National Lab. (SNL-CA), Livermore, CA (United States)
2014-11-01
We demonstrate a Bayesian method that can be used to calibrate computationally expensive 3D RANS (Reynolds Av- eraged Navier Stokes) models with complex response surfaces. Such calibrations, conditioned on experimental data, can yield turbulence model parameters as probability density functions (PDF), concisely capturing the uncertainty in the parameter estimates. Methods such as Markov chain Monte Carlo (MCMC) estimate the PDF by sampling, with each sample requiring a run of the RANS model. Consequently a quick-running surrogate is used instead to the RANS simulator. The surrogate can be very difficult to design if the model's response i.e., the dependence of the calibration variable (the observable) on the parameter being estimated is complex. We show how the training data used to construct the surrogate can be employed to isolate a promising and physically realistic part of the parameter space, within which the response is well-behaved and easily modeled. We design a classifier, based on treed linear models, to model the "well-behaved region". This classifier serves as a prior in a Bayesian calibration study aimed at estimating 3 k - ε parameters ( C _{μ}, C _{ε2} , C _{ε1} ) from experimental data of a transonic jet-in-crossflow interaction. The robustness of the calibration is investigated by checking its predictions of variables not included in the cal- ibration data. We also check the limit of applicability of the calibration by testing at off-calibration flow regimes. We find that calibration yield turbulence model parameters which predict the flowfield far better than when the nomi- nal values of the parameters are used. Substantial improvements are still obtained when we use the calibrated RANS model to predict jet-in-crossflow at Mach numbers and jet strengths quite different from those used to generate the ex- perimental (calibration) data. Thus the primary reason for poor predictive skill of RANS, when using nominal
A Review of Distributed Parameter Groundwater Management Modeling Methods
Gorelick, Steven M.
1983-04-01
Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.
Parameters of oscillation generation regions in open star cluster models
Danilov, V. M.; Putkov, S. I.
2017-07-01
We determine the masses and radii of central regions of open star cluster (OCL) models with small or zero entropy production and estimate the masses of oscillation generation regions in clustermodels based on the data of the phase-space coordinates of stars. The radii of such regions are close to the core radii of the OCL models. We develop a new method for estimating the total OCL masses based on the cluster core mass, the cluster and cluster core radii, and radial distribution of stars. This method yields estimates of dynamical masses of Pleiades, Praesepe, and M67, which agree well with the estimates of the total masses of the corresponding clusters based on proper motions and spectroscopic data for cluster stars.We construct the spectra and dispersion curves of the oscillations of the field of azimuthal velocities v φ in OCL models. Weak, low-amplitude unstable oscillations of v φ develop in cluster models near the cluster core boundary, and weak damped oscillations of v φ often develop at frequencies close to the frequencies of more powerful oscillations, which may reduce the non-stationarity degree in OCL models. We determine the number and parameters of such oscillations near the cores boundaries of cluster models. Such oscillations points to the possible role that gradient instability near the core of cluster models plays in the decrease of the mass of the oscillation generation regions and production of entropy in the cores of OCL models with massive extended cores.
da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G
2016-07-08
Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.
Norton, P. A., II
2015-12-01
The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.
Value of a new inflammatory parameter in malignant pleural mesothelioma prognosis
Directory of Open Access Journals (Sweden)
Özlem Abakay
2013-01-01
Full Text Available Malignant Pleural Mesothelioma (MPM generallyassociated with asbestos exposure is a tumor withpoor prognosis. Modified Glasgow Prognostic Score(GPS which may be a prognostic parameter in patientswith MPM is a designed based score including increasedC-reactive protein (CRP levels and decreased albumin.In this study we aimed to investigate the effect of GPSscore on the prognosis of MPM and the role of other potentialfactors.Methods: In this retrospective planned study 140 histologicaldiagnosed MPM patients were included.Results: Mean age of 140 MPM patients were 52.92years (83 male and 57 female. A total of 91 patients hadenvironmental asbestos exposure and exposure timewas the 31 years. Symptoms of the patients started approximately4.8 months before the application. The mostfrequently seen symptoms were in 125 patients dyspnea,in 94 patients chest pain and in 22 patients weight loss.GPS score of the patients were as follows; 64 patientstwo, 14 patients one, 22 patients zero. Of the patients,112 died and 28 were alive. Mean survival time was 14months. Patients with GPS score 2 lived for 10 months,GPS score 1 lived for 15 and GPS score 0 lived for 18months. This difference was statistically significant. Furthermore,the male sex and age older than 65 years werefound as poor prognostic parameters on the survival.Conclusion: A simple and inexpensive parameter able tobe used to estimate the prognosis of MPM patients couldnot be developed .GPS score increases in inflammatoryconditions. GPS is a simple and inexpensive para